Resistance to antimalarial drugs inevitably follows their deployment in malaria endemic parts of the world. For instance, current malaria control efforts which significantly rely on artemisinin combination therapies (ACTs) are being threatened by the emergence of resistance to artemisinins and ACTs. Understanding the role of genetic determinants of artemisinin resistance is therefore important for implementation of mitigation strategies. Moreover, elucidating the mode of action for drugs that are in advanced stages of development is specifically critical as drug resistance mechanisms can be prospectively predicted and possible means of surveillance put in place.
In the present work, CRISPR-Cas9 genome editing has been used to engineer candidate artemisinin resistance mutations (Kelch13 and UBP-1) in the rodent malaria parasite Plasmodium berghei. The role of these mutations in mediating artemisinin (and chloroquine) resistance under both in vitro and in vivo conditions has been assessed which up until now, has either remained un-validated (UBP-1) or debated (Kelch13, under in vivo conditions) in human infecting Plasmodium falciparum. The results have provided an in vivo model for understanding and validating artemisinin resistance phenotypes which just like their Plasmodium falciparum equivalents do not just mediate resistance phenotypes, but also carry accompanying fitness costs.
In addition to the above findings, biochemical and drug inhibition studies have been carried out to demonstrate that small molecule inhibitors targeting ubiquitin hydrolases (to which UBP-1 is a class member) display activity in human and rodent infecting malaria parasites in vitro and in vivo. These inhibitors also show evidence of ability to potentiate artemisinin action which can be exploited to overcome the emerging resistance as combination partner drugs. Untargeted metabolomic screens have also been used to characterize the mode of action of lead antimalarial drug candidates that are emerging from the Novartis Institute of Tropical Diseases drug discovery pipeline. A common biochemical and metabolic profile of these compounds which display a very fast parasite killing rate is presented and can hopefully be used to identify compounds that can achieve a similar feat. Moreover, these profiles have pointed to possible mode of action for novel drugs whose mechanistic mode of parasite killing is still unknown or disputed.
Item Type: | Thesis (PhD) |
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Qualification Level: | Doctoral |
Keywords: | Antimalarial drugs, mode of action, resistance, genetics models, biochemistry, metabolomics. |
Subjects: | > |
Colleges/Schools: | > > |
Funder's Name: | , |
Supervisor's Name: | Waters, Professor Andy and Barrett, Professor Mike |
Date of Award: | 2020 |
Depositing User: | |
Unique ID: | glathesis:2020-81876 |
Copyright: | Copyright of this thesis is held by the author. |
Date Deposited: | 17 Dec 2020 17:02 |
Last Modified: | 16 Sep 2022 15:52 |
Thesis DOI: | |
URI: |
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In response to the malaria parasite’s resistance towards quinoline-based antimalarial drugs, we have employed quinoline-containing compounds in combination with dihydropyrimidinone (DHPM) analogues as resistance reversal agents (RAs) and investigated their antimalarial activities based on DHPM’s resistance reversal abilities. The present study employed click chemistry to link DHPM and quinoline compounds which offered several synthetic advantages over the previously used amide coupling for the same hybrids. Among the synthesised compounds, 4 hybrids with the 7-chloroquinoline moiety showed antimalarial activity below 1 µM while compounds with the mefloquine moiety showed lower antimalarial activity than chloroquine (CQ) and the 7-chloroquinoline hybrids. Among the tested hybrids for the IC 50 determination, four compounds displayed good antimalarial activity with increased sensitivity against the CQ-resistant K1 strain between 421 and 567 nM and showed higher activity between 138 and 245 nM against the NF54 CQ-sensitive strain, while three compounds have IC 50 values greater than 5 µM. Additionally, in silico molecular docking and molecular dynamics studies were conducted to investigate the binding affinities of all the synthesised compounds as glutathione reductase protein competitive inhibitors. Further optimisation of the compound with the highest binding affinity generated 16 compounds with higher binding affinities than the flavine adenine dinucleotide (FAD) cofactor.
Synthesis of new chloroquine derivatives as antimalarial agents.
Avoid common mistakes on your manuscript.
Recent data indicates that the challenge to overcome malaria still lingers [ 1 ], regardless of all the significant efforts and advances in drug developments and medical technologies. The rise of drug or multidrug resistance in Plasmodia strains has made malaria the most important tropical parasitic disease [ 2 ]. Therefore, developing new antimalarial drugs is necessary to rectify this situation. Despite the development of many antimalarial leads, quinoline compounds remain important in malarial chemotherapy [ 3 ].
For many years, chloroquine (CQ) from the quinoline family was the first-line antimalarial drug. Despite the huge success recorded in using quinoline for malaria therapeutics, these drugs have been challenged by Plasmodium parasites due to their rapid development of resistance [ 4 , 5 ]. Drug resistance in malaria occurs when the parasite strain continues to multiply or survive even though the therapeutic has been given in the recommended tolerable dose. This situation is not malaria-specific but is also observed in cancer and other parasitic diseases like the case with antibiotics. As for the case of chloroquine (CQ) resistance, there is strong evidence through different research that resistant malaria parasites accumulate less CQ in their food vacuole than sensitive parasites [ 6 ]. This could result from an efflux pumping system, reduced CQ uptake by the parasite, or a combination of both processes [ 7 ]. This implies that CQ concentration does not reach the parasite’s lethal dose, thereby resulting in its continuous survival.
The use of resistance reversal agents (RAs) is among the strategies to reverse this drug resistance in malaria parasites. Resistance reversal refers to the use of a compound that can restore the sensitivity of resistant strains to a drug while it might have little or no therapeutic action against the parasite [ 8 ]. In the context of malaria, resistance RAs ensure antimalarial drugs accumulate within the parasite’s food vacuole. An interesting feature of this strategy is the ability to combine two biologically active compounds in a hybrid, maintaining the properties of both without the setback of differing elimination half-life (t 1/2 ) or pharmacokinetic properties associated with separate drugs that are used in combination therapy. Furthermore, a major advantage of this approach over the rest is the ability of the RA to competitively bind to the P. falciparum chloroquine resistance transporter ( Pf CRT) protein, thereby inhibiting the efflux of the CQ from the digestive food vacuole of the Plasmodium parasite. In contrast, other strategies lack this feature to bind to the mutated CQ-resistant P. falciparum [ 9 , 10 ].
Previously, it was discovered that concurrent exposure of resistant strains of P. falciparum to both CQ and verapamil reversed resistance in vitro [ 4 , 11 ]. Since verapamil is a calcium channel blocker used to treat hypertension and other cardiovascular diseases, researchers have used different calcium channel blockers and other drugs in combination with quinoline-based antimalarial drugs in attempts to reverse antimalarial drug resistance. It was observed that the RA combinations were able to increase the sensitivity of cloned CQ-resistant P. falciparum strains in vitro but did not affect the sensitivity of CQ-sensitive strains [ 6 , 11 , 12 , 13 ].
Before Peyton and co-workers coined the term “Reversed Chloroquine” (RCQ) to describe a hybrid compound containing CQ and an RA, the use of RAs in antimalarial chemotherapy involved the administration of the two agents as separate doses [ 14 ]. They discovered that covalently linking a CQ-like moiety to imipramine was effective against both sensitive and resistant strains of the Plasmodium parasite. The hybrid molecule delivered the RA in a 1:1 ratio to the antimalarial quinoline, which would lower the dose required if the two drugs, was to be given in separate forms, with resultant lower cost and toxicity [ 4 ]. This arrangement would favour the drug accumulation in the parasite’s digestive vacuole and also interfere with the CQ export by the mutated CQ-resistant P. falciparum [ 14 ].
In our previous work, we covalently linked CQ to dihydropyrimidinone (DHPM) using an amide bond linker at position 3 of the DHPM. The resulting hybrids could reverse resistance in the K1 strain of P. falciparum in vitro [ 15 ]. Since DHPMs present various sites of functionalisation that could be used for structure–activity relationship (SAR), several synthetic strategies could be employed to link quinoline-based antimalarials to various DHPM scaffolds.
The previous report of the synthesis of DHPM-based hybrids of chloroquine (CQ) moiety used amide coupling to link the CQ to DHPM, specifically at N3 of the reversal agent [ 15 ]. The synthetic route to these hybrids involved the protection of N1 nitrogen with a methyl group. Furthermore, the synthesis of the amide carbamate ester intermediate involved overnight reflux with a large excess of phenyl chloroformate and NaH, 10.0, and 11.0 molar equivalents, respectively. This synthetic procedure generated a lot of waste. However, we report on the use of click chemistry as an alternative route to synthesise DHPM-based quinoline hybrids and their antimalarial activities. This project employs a triazole covalent linker between quinoline-based compounds and different DHPMs using the C6 of the DHPM as the point of attachment. Two series of quinoline-based compounds related to chloroquine and mefloquine antimalarial drugs were chosen (Scheme 1 )
General structure of the target DHPM hybrids based on CQ ( III ) and mefloquine ( IV )
It also has been demonstrated that quinoline derivatives block the P. falciparum glutathione reductase ( Pf GR) enzyme [ 16 ]. The host erythrocytes undergo significant structural and physiological changes when invaded by P. falciparum to aid the parasites’ survival and growth. The oxidative stress caused by these changes affects the malaria parasites. As a result, an effective antioxidant is necessary to inhibit reactive oxygen species from harming the parasites [ 17 ]. It is thought that reduced glutathione (GSH) is a crucial antioxidant during erythrocytic infection. As an oxidoreductase, glutathione reductase in P. falciparum converts oxidised glutathione (GS-SG) to reduced GSH using hydrogen from nicotinamide adenine dinucleotide phosphate (NADPH). The transfer of hydrogen from NADPH to GS-SG is the most essential task of the FAD cofactor in Pf GR because, without it, the parasite would experience oxidative stress [ 18 , 19 ]. Thus, P. falciparum’s glutathione reductase enzyme becomes a crucial target in antimalarial treatment [ 20 ]. Therefore, in addition to the in vitro antimalarial testing, the binding affinities and the molecular stabilities of the synthesised compounds within the glutathione reductase enzyme were estimated using molecular docking and molecular dynamics in silico methods.
The synthesis of the chlorinated DHPM and the subsequent azidation to form azides 9a-d was reported earlier [ 21 ]. The terminal alkynes were installed on the quinoline-based compounds using different protocols. Compound 2 was synthesised via a nucleophilic substitution reaction from 4,7-dichloroquinoline 1 according to the reported protocol (Scheme 2 ) [ 22 ]. This involved heating a mixture of 1 and propargylamine in a sealed tube under a nitrogen atmosphere.
Synthesis of quinolines 2 and 3 . Reagent and conditions: (i) propargylamine, 110 °C, N 2 , 18 h. (ii) propargyl alcohol, NaH, DMF, 0 °C, 50 °C
Formation of product 2 was confirmed by 1 H NMR spectroscopy with the observance of the terminal alkyne’s proton at δ H 2.66 ppm (t, 4 J HH = 2.5 Hz). The method reported by Kaval et al. was adapted to synthesise the oxyquinoline 3 (Scheme 2 ) [ 23 ]. The formation of compound 3 was confirmed from the 1 H NMR spectrum with the terminal alkyne’s proton appearing at δ H 2.62 ppm (t, 4 J HH = 2.4 Hz) and the Single crystal X-ray diffraction (SCXRD) technique (Fig. 1 ).
Molecular structure of compound 3 . Thermal ellipsoids are drawn at a 70% probability level
The quinolinol 6 was synthesised via Conrad-Limpach synthesis of quinolines, which was readily converted to the alkynes 7 and 8 (Scheme 3 ).
Synthesis of 2,8-bis(trifluoromethyl)quinolines. Reagents and conditions: (i) polyphosphoric acid, 150 °C, 3 h; (ii) K 2 CO 3 , dry DMF, 30 °C, 30 min, propargyl bromide, 6 h; (iii) butyn-1-ol, PPh 3 , DEAD, dry THF, 0 °C, 25 °C, 12 h
Aniline 4 was quantitatively cyclised to the quinolinol 6 by heating it at 150 C with ethyl 4,4,4-trifluoroacetoacetate ( 5 ) for 3 h in the presence of polyphosphoric acid (PPA) as the catalyst [ 24 ]. The nucleophilic alkylation of 6 to 7 was performed using the Williamson ether synthesis [ 25 ]. To extend the carbon chain linker, compound 8 was synthesised from the quinolinol 6 via the Mitsunobu reaction [ 26 ] as Williamson’s nucleophilic alkylation of the quinolinol 6 with excess 4-Bromo-1-butyne failed to give the desired product. From the mechanism of Conrad-Limpach synthesis of the quinolines [ 27 , 28 ], it is possible to obtain two tautomers for the quinolinol 6 : the enol (a) and the keto (b) (Fig. 2 ). The simultaneous presence of both tautomers was confirmed from the SCXRD data (Fig. 2 ). It corroborated the earlier isolation by Sarojini et al. [ 29 ], but the subsequent deprotonations only involved the enol (a) as was observed from the SCXRD of compound 7 (Fig. 3 ). The involvement of the enol form for the subsequent deprotonations points to its preference over the keto form. The more stable enol tautomer is not unexpected for two reasons: enol stability by conjugation with a neighbouring pi system and aromaticity [ 30 ]. The two factors are present as the quinoline moiety is highly conjugated in the two rings, and they both contain aromatic systems for additional resonance stability.
Molecular structure of compound 6 showing the two tautomers, the keto ( a ) and the enol ( b ) forms. Thermal ellipsoids are drawn at a 50% probability level
Molecular structure of compound 7 . Thermal ellipsoids are drawn at a 50% probability level
The structure of compound 8 was confirmed from the 1 H NMR spectrum with the observation of all the diagnostic peaks. The terminal alkyne proton appeared at δ H 2.10 ppm (t, 4 J HH = 2.7 Hz), while the two methylene protons were assigned to the signals δ H 2.90 ppm (td, 3 J HH = 6.7 Hz, 4 J HH = 2.7 Hz) and 4.41 ppm (t, 3 J HH = 6.7 Hz). All the aromatic protons were also observed at the expected peak positions. The hybrid compounds were synthesised by click chemistry reactions (Schemes 4 and 5 ) as adapted from Guantai et al. [ 31 ]. The reaction was first attempted in a mixture of tert -butanol and water using copper(I) iodide (CuI) as the catalyst. This gave three spots on the TLC, and no attempt was made to separate them because of their close R f values. The catalyst was changed to freshly prepared 1-M solution of copper(II) sulphate pentahydrate (CuSO 4 .5H 2 O) and sodium ascorbate which reductively produces the required Cu(I) in situ. Initially, this approach seemed to work for the reaction where only one prominent spot was observed on the TLC. However, a difficult-to-filter precipitate also formed from the solution. Another setback was the persistent appearance of the starting materials even after long hours of stirring at 25 °C. The solvent was changed to DMF with the catalyst freshly prepared in distilled water. The reaction mixture was stirred for 12 h, and the TLC analysis showed a single spot for the product with complete consumption of the starting materials.
Synthesis of the triazoles 10a-h. Reagents and conditions: CuSO 4 , sodium ascorbate, DMF, H 2 O, 25 °C, 12 h
Synthesis of the triazoles 11a-h. Reagents and conditions: CuSO 4 , sodium ascorbate, DMF, H 2 O, 25 °C, 12 h
The 1 H NMR spectra obtained for 11a-h correlated well with the proposed structures, and all the diagnostic peaks were observed (see the supplementary information for details). Additionally, the predicted connectivity of the compounds was confirmed from the SCXRD structure elucidations of 11d and 11 g (Fig. 4 ).
Molecular structures of compounds 11d ( a ) and 11g ( b ). Thermal ellipsoids are drawn at a 50% probability level
The percent growth inhibitory activities of DHPMs 9a-d and hybrids 10a-h and 11a-h were evaluated at 1-µM and 5-µM concentrations in an in vitro antiplasmodial assay (Fig. 5 , Table 1 ). An NF54 CQ-sensitive (CQS) P. falciparum asexual strain was used. The most potent compounds 10a-d were further evaluated for the IC 50 against NF54 CQS, and K1 CQ-resistant (CQR) strains, while the IC 50 of the moderately potent compounds 11c , 11e, and 11 g were determined against the K1 CQR strain only. In all the assays, CQ was used as the reference drug (Table 2 ).
In vitro activity of DHPM-CQ triazole hybrids at 1 μM and 5 μM against asexual P. falciparum (NF54 and K1)
Among the compounds tested against the NF54 strain to determine the percentage inhibition, the reversal agents (RAs) 9a-d displayed minimal inhibition (Fig. 5 , Table 1 ). This was expected as they lack the antiplasmodial quinoline moiety, and their role in the hybrids is to inhibit the underlying process responsible for drug resistance. Within the same series, compounds 10a-d with 4-amino functionality displayed the highest inhibitions and were comparable to CQ at the two concentrations tested. Compounds 10e-f with the 4-oxyquinoline moiety exhibited very low inhibitions, even at 5 µM. The decrease in the activity of these oxygen-containing hybrids 10e-f could be attributed to the absence of the 4-amino functionality, which is present in compounds 10a-d . This agrees with previous reports that quinolines containing an amino group at the 4-position show higher antiplasmodial activities than those containing oxygen or lacking the 4-amino group [ 32 , 33 , 34 , 35 ]. This stresses the importance of the 4-amino moiety in maintaining the basic property required for the CQ and its analogues to accumulate in the food vacuole of P. falciparum [ 34 ]. Compounds 11a-h with the mefloquine moiety showed lower antiplasmodial activity than CQ and the hybrids 10a-h . Among these hybrids, compounds 11a , 11c , 11e, and 11 g , with unsubstituted acidic protons at N1 and N3, showed better activities than compounds 11b , 11d , 11f, and 11 h which instead have a methyl group at N1. The generally lower activities of hybrids 11a-h could also be ascribed to the lack of 4-amino functionality in the quinoline ring [ 34 ].
Compounds 10a-d displayed good antiplasmodial activities against the CQR K1 strain. The IC 50 s for this strain were between 421 and 567 nM, but much greater potencies of 138–245 nM were observed against the NF54 CQS strain. Compounds 11c , 11e , and 11 g were at least three orders of magnitude weaker. Hybrids 10b and 10d , containing chloroquine moiety with a methyl group at N1 of the DHPM, showed better antiplasmodial activities than hybrids 10a and 10c with unsubstituted acidic protons at N1 and N3 in both NF54 and K1 strains. This higher antiplasmodial activity could result from the decreased acidity associated with the removal of the acidic proton, which increases the basic property of the quinoline hybrid needed for its accumulation in the acidic food vacuole of the P. falciparum [ 36 ]. In addition, replacing the acidic proton with a methyl group increases the lipophilicity and in turn increases the antimalarial activities [ 37 ]. However, other substitutions, particularly the para -methoxy and the para -fluoro groups on the DHPM aromatic, do not seem to influence the activities of the hybrid compounds. Hybrids 10a-d also showed reduced Resistance indices (RI) factor ranging from 2.3 to 3.6 as compared to CQ with an RI factor of 8.5. The reduced RI factor suggests that the addition of the DHPM to the quinoline scaffold was able to change the sensitivity of the K1 strain observed.
Using the Maestro tool from the Schrödinger software, we performed the in silico study utilising the crystal structure of glutathione reductase (PDB ID: 1ONF). The X-ray crystallographic structure of P. falciparum glutathione reductase was retrieved from the Protein Data Bank (PDB, https://www.rcsb.org/ ). The raw protein structure was prepared using the protein preparation wizard of the Schrodinger suite. This was used to assign bond orders, remove water molecules beyond 3 Å, and add H atoms. In addition, both missing side chains and missing loops were added using the Prime. While refining, water orientations were sampled using the PROPKA at a pH of 7.0 for the energy optimisation process and the restrained minimisation was done to confine the root-mean-square deviation (RMSD) of heavy atoms to 0.30 Å using an OPLS4 force field [ 38 ]. The active site of the protein residues surrounding the FAD cofactor (the bound ligand) was taken as the binding site, and these residues were used for the preparation of the docking grid using the receptor grid generation panel of the Schrodinger suite. No volume was excluded, and likewise, no constraint was defined. The input ligand structures of the synthesised compounds were built using the LigPrep module of the Schrödinger suite. For each 2D structure, the LigPrep process creates 3D structures with minimised energy, proper bond lengths, and angles. At a physiological pH of 7.0 ± 0.2, the possible ionisation states for each ligand structure were generated using the EPIK tool. Lastly, the Glide ligand docking module and the related default force field OPLS4 were used to execute the molecular docking in an extra precision (XP) mode.
The docking simulations of the synthesised compounds were run in the binding site of P. falciparum glutathione reductase crystal structure (PDB ID: 1ONF) co-crystallised with FAD cofactor, and the outcomes are shown in Table 3 . The binding energy of the ligand–protein complex corresponds to the intensity and affinity of the ligand–protein interaction. The docked complexes were rated according to their lowest energy value (kcal/mol). The negative value of the binding energy increases with the increasing strength of the interaction and vice versa. As expected, the FAD cofactor showed the highest binding affinity at −9.644 kcal/mol, followed by compound 10a at −8.1 kcal/mol. Accidentally, no correlation was observed between the docking scores and the antiplasmodial IC 50 values of the synthesised compounds. As it is well known with competitive inhibitors, it is always a challenge to design compounds that could competitively bind at the active site with higher binding affinity than the cofactor [ 39 ]; however, rational optimisations could be a saving grace. Though all the synthesised compounds showed insignificantly lower binding affinity than the FAD cofactor, all of them displayed considerable binding energy, and five of the synthesised compounds showed higher binding affinity than the chloroquine standard.
Binding pose and electronic interactions of compound 10a within the active site of glutathione reductase. 3D and 2D structures are shown in a and b , respectively
Analysis of the binding pose of compound 10a showed different electronic interactions as shown in Fig. 6 . The compound was able to make different interactions within the active site of glutathione reductase. The + NH 3 of the Lys151 side chain was able to simultaneously make two π-cation interactions with the phenyl group on the DHPM ring (at 4.69 Å) and the DHPM ring itself (at 4.94 Å), while the benzene ring of the quinoline moiety was able to form another π-cation interaction with + NH 3 side chain of Lys32 (at 3.67 Å). In addition, several H-bond interactions were noted. These include H-bond interactions between N3H of the DHPM and the carboxylic OH of the Asp167 side chain at 1.90 Å, C = O of DHPM, and one NH of the guanidino group of Arg272 side chain at 1.89 A. Most importantly, the nitrogen of the pyridine ring of the quinoline moiety was able to form hydrophobically packed H-bond interaction with NH of Ala110 backbone at 1.92 Å (Fig. 7 ). This type of H-bond is very crucial in maintaining the ligand stability within a protein because of the difficulty involved in breaking the H-bond formed in a hydrophobic space [ 38 ]. Another notable feature is the halogen interaction between the chlorine atom on the quinoline and the C = O backbone of Asn278 at 3.36 Å.
Hydrophobically packed H-bond (labelled yellow dotted lines) between N of the pyridine ring of compound 10a and Ala110 within the hydrophobic region of glutathione reductase (interacting residues in CPK representation)
The synthesised compounds must exhibit stronger interactions than the FAD cofactor in order to function as competitive inhibitors at the active site of glutathione reductase. To achieve this, the protein–ligand complex of compound 10a with the highest binding affinity was loaded onto the workspace and rationally optimised using the Ligand Designer tool in the Maestro platform. Analysis of the workspace showed the 4-methoxy substituent on the phenyl ring of DHPM in a solvent-exposed region. The 4-methoxy group was therefore truncated, leading to an increase in the binding affinity from −8.1 to −8.2 kcal/mol. The growth space of compound 10a , the ligand–protein interaction, and the truncated 10a are shown in Fig. 8 a, b, and c, respectively. The light blue regions show the cavity space within the binding pocket, while the deep blue regions show the solvent-exposed areas.
The growth space of compound 10a within the glutathione reductase active site ( a ), the ligand-protein interaction ( b ), and the truncated 10a ( c )
The truncated 10a was then loaded into the workspace with the protein crystal structure. The pathfinder bonds were activated to identify possible points of R group attachments. With this, the acetate group at position 5 of the DHPM was selected and enumerated to be replaced with the default R groups in Maestro Ligand Designer. The methyl group of the acetate moiety was subsequently replaced and this generated 916 optimised derivatives of compound 10a . The top 20 ligands are shown in Table 4 .
From the generated 916 new ligands, the highest scoring ligand was LD_350 with a docking score of −11.0 kcal/mol, while ligand LD_753 had the lowest docking score of −0.3 kcal/mol. The mean was found to be −8.2 kcal/mol, while the median was −8.4 kcal/mol. This indicates that more than 50% of the optimised ligands had higher binding affinity than the original compound 10a at −8.1 kcal/mol. Interestingly, the optimisation process generated 16 ligands with higher binding affinities than the FAD cofactor, as seen in Table 4 . In comparison, 664 ligands had higher binding affinities than the original compound 10a .
The interaction diagrams of the top two ligands LD 350 ( a ) and LD 762 ( b )
The interaction diagrams of the top two ligands (LD 350 and LD 762) are shown in Fig. 9 , showing the changes, especially in the electronic interactions from the added R groups. In LD 350, for example, all the original electronic interactions in compound 10a were preserved, while the added R group could generate additional H-bond interactions. These are the H-bond between 2-OH of the phenyl ring and C = O backbone of Asp167 at 2.05 Å, the H-bond between 4-OH of the phenyl ring and C = O side chain of Glu168 at 1.55 Å and H-bond between the C = O at the benzyl position and NH side chain of Asn171 at 2.01 Å. These interactions alone with the truncated 4-methoxy group on the DHPM contributed −2.9 kcal/mol of binding energy, which is a 35% increase in binding affinity compared to the original compound 10a .
Because molecular docking lacks precise information on the explicit biological water system and the inherent flexibility of the receptor, studies of molecular dynamics that imitate similar biological settings can help to understand the stability of the ligand–protein complex. Based on the docking findings, we ran molecular dynamics simulations for compounds 10a , LD_350, and LD_762 in this work. The MD simulation was carried out using the Schrödinger Desmond MD simulation software (version 2021–1). To achieve the biological solvation system, the ligand–protein complex was placed in a TIP3P solvation model and then subsequently neutralised by adding 6Cl − counter ions. The energy minimisation step was also completed to confirm that the system has no steric conflict. The simulation was run for 50 ns at 300 K and 1 bar under an “isothermal-isobaric ensemble” (NPT) condition. The “Nose–Hoover chain thermostat” and “Martyna-Tobias-Klein barostat” approaches were ensembled, respectively, for isothermal-isobaric conditions [ 40 , 41 ]. At 50-ps intervals, simulation trajectories were obtained, and the resulting trajectories were evaluated.
The MD simulation utilises protein equilibration, flexibility, and the average distance between backbone atoms to calculate the RMSD to estimate the fluctuation of the total protein–ligand complex. A protein–ligand complex with a lower RMSD value indicates a more stable interaction. In the case of compound 10a , both the protein and the ligand RMSD values lie at approximately 3.0 Å, though the RMSD of the protein averagely lies above 3.0. In contrast, the ligand averagely lies below 3.0 Å except at approximately 35 and 43 ns, where it went slightly above 3.0 Å (See SI Fig. S1 a). In addition, the protein and the ligand attained equilibration at less than 5 ns, and no apparent separation between them could be seen throughout the 50-ns MD simulation. Indicating the stability of the original docked structures, the approximately constant RMSD of Cα atoms and minor fluctuations of the ligand atoms during the MD simulation show that the conformation of the ligand did not change or varied very little. Comparing this with the RMSD of the optimised ligands, the LD_350 complex (See SI Fig. S1 b), for example, showed lower RMSD values at the beginning of the simulation for the ligand but was only able to achieve equilibration at around 37 ns. Though the RMSD of the ligand increased from ~ 1.8 Å to ~ 4.2 Å during the equilibration, no separation was observed after the equilibration till the end of the simulation period. The RMSD diagram of LD_762 revealed that the protein–ligand complex achieved equilibration at ~ 18 ns, and no separation was observed till the end of the simulation period (See SI Fig. S1 c). In this case, the protein showed the slightest deviation and had a maximum RMSD value of 2.4 Å till the end of the simulation, while the RMSD value of the ligand was higher at ~ 5.6 Å at the end of the simulation.
The molecular dynamics simulation identified the major binding interactions between the simulated ligands and glutathione reductase protein. One of the most significant advantages of MD simulation is its ability to precisely identify stable binding interactions from those revealed by molecular docking studies. In most cases, the flexibility of the protein and the ligand in MD, as obtained in a physiological condition, gives rise to the observed differences. In addition, the contact time of each interaction of the ligand with different protein residues as a function of the total simulation period is shown in percentage (See SI Fig. S2 ). In the case of compound 10a , for example, the two π-cation interactions between + NH 3 of Lys151 and the DHPM rings, as shown in molecular docking, were not preserved. The π-cation interaction of the amino side of Lys32 was preserved at 45% of the simulation time but with the triazole ring rather than the benzene ring of the quinoline moiety. Likewise, the halogen bond interaction between Cl of the quinoline moiety and Asn278 was not preserved.
Interestingly, most of the H-bond interactions involving compound 10a were preserved, and MD was able to identify new H-bond interactions. H-bond interactions involving N3H of DHPM and Asp167 and that of the N of the pyridine ring in quinoline with Ala110 were preserved at 96 and 92%, respectively. In comparison, that of the C = O of the DHPM with Arg272 was lost, but the same C = O was able to form two new H-bond interactions with Thr38 and Asn150 simultaneously at 72 and 94%, respectively. As for the newly identified H-bond interactions, these involved N1H of the DHPM with Gly37 and N3 of the triazole ring with Gly149 at 62 and 32%, respectively. The same trend was observed with the optimised ligands. Analysing LD_350, for instance, the MD did not preserve any of the identified H-bond interactions from the added R-group except for the newly formed intramolecular H-bond interaction between the 2-OH on the benzene ring and its C = O (See SI Fig. S2 b). The π-cation interactions between the quinoline rings and Lys32, as well as the DHPM ring and Lys151, are also noteworthy. These were preserved from the molecular docking interactions except for the newly identified π-cation interaction between the pyridine ring of the quinoline moiety and Lys32. Interestingly, the changes in either atomic distances or bond angles beyond the allowed limits resulted in the observed lost interactions in all the cases.
Using the root mean square fluctuation (RMSF) approach, we identified the protein regions exhibiting residue fluctuations across the simulation time. This clarifies how the flexibility of the protein is impacted by ligand binding. As expected, the graphs show the high flexibility of the protein’s N and C termini [ 39 ]. Although there were non-terminal residues with greater RSMF values, they were either extremely close to the terminal or very far from the protein’s binding pocket, as demonstrated by Gly67 in the 10a -protein complex, which had an RMSF value of 3.29 Å. All the protein residues interacting with the ligands generally displayed variations at a mean value of 1.0 Å (See SI Fig. S3 a, b, and c).
Click chemistry has been successfully used to link DHPM to quinoline-based compounds. The use of click chemistry offers several advantages over the previous amide coupling method. These include a better functional group tolerance, ease of synthesis, lesser waste generation, and better atom economy. From the antimalarial results obtained, we have been able to show that the hybrids containing DHPM and 4-aminoquinoline moieties with triazole linker at position 6 of the DHPM showed good antimalarial activity with IC 50 values below 1 µM and decreased resistance indices than CQ. In general, hybrids with 4-amino functionality displayed better antimalarial activities than those containing oxygen at position 4 of the quinoline ring. The hybrids with mefloquine moiety could be modified in the future to include a 4-amino group on the quinoline ring for comparative antimalarial activities. Apart from position 6 of the DHPM, other positions on the DHPM ring could also be explored to link the quinolines using triazole linkers. Using molecular docking and dynamics approaches, we further explored the synthesised compounds as glutathione reductase inhibitors. Five of the synthesised compounds showed higher binding affinity than the CQ standard, though none showed a higher binding affinity than the FAD cofactor. Rational optimisation of the compound with the highest binding affinity generated 916 ligands, with 664 having higher binding affinities than the original compound and 16 ligands higher than the FAD cofactor. The rational optimisation approach was necessary to produce ligands that could serve as competitive inhibitors of glutathione reductase.
A Gallenkamp melting-point apparatus was used for the melting point determination in open capillary tubes and is uncorrected. 1 H and 13 C NMR spectra were recorded on either a Bruker Avance 400 (at 400.21 MHz for 1 H and 100.64 MHz for 13 C) or 300 (at 300.13 MHz for 1 H and 75.48 MHz for 13 C) spectrometers using CDCl 3 or DMSO-d 6 as solvents at room temperature. Chemical shifts were recorded as part per million (ppm) using tetramethylsilane as an internal standard. 2D NMR experiments were recorded on Bruker Avance 400. Mass analysis was performed on Waters® Synapt G2 High Definition Mass Spectrometry (HDMS) system with flow injection analysis (FIA) using electrospray ionisation (ESI) probe. The MS data were acquired and processed on MassLynx™ software (version 4.1). FT-IR measurements were made on a Bruker Alpha Platinum-ATR spectrometer as neat. All reagents and solvents were purchased from Sigma-Aldrich and used without further purification.
Single-crystal diffraction experiments of compounds 3 and 6 were performed using Quazar multi-layer optics monochromated Cu Kα radiation ( k = 1.54178 Å) on a Bruker D8 Venture kappa geometry diffractometer with duo Iμs sources, a Photon 100 CMOS detector and APEX III control software [ 42 ]. Data reduction was performed using the SAINT + [ 42 ], and the intensities were corrected for absorption using the SADABS [ 42 ]. Single crystals of 7 , 11d , and 11 g were analysed on a Rigaku XtaLAB Synergy R diffractometer with a rotating-anode X-ray source and a HyPix CCD detector. Data reduction and absorption were carried out using the CrysAlis Pro (version 1.171.40.23a) software package [ 43 ]. All X-ray diffraction measurements were performed at 150(1) K, using an Oxford Cryogenics Cryostat. All structures were solved by direct methods with SHELXT-2016 [ 44 ] using the SHELXL-2016 algorithm [ 45 ]. All H atoms were placed in geometrically idealised positions and constrained to ride on their parent atoms. For data collection and refinement parameters, see the SI (Tables S1 , S2 ). The X-ray crystallographic coordinates for all structures have been deposited at the Cambridge Crystallographic Data Centre (CCDC), with deposition numbers CCDC 2076919–2076923. The data can be obtained free of charge from The Cambridge Crystallographic Data Centre via www.ccdc.cam.ac.uk/data_request/cif .
Colourless crystals: yield 26.64 g, 79%; 1 H NMR (400 MHz, CDCl 3 ): δ H 8.62 (d, 3 J HH = 8.3 Hz, 1H, Ar H ), 8.10 (d, 3 J HH = 7.4 Hz, 1H, Ar H ), 7.61 (t, 3 J HH = 7.8 Hz, 1H, Ar H ), 7.45 (s, 1H, py H ), and 6.95 (bs, 1H, OH).
The general procedure for the click chemistry used for coupling azido DHPHs to acetylenic quinolines is described below using 10 h as an example.
9d (0.19 g, 0.60 mmol) and 3 (0.13 g, 0.60 mmol) were dissolved in 3.0 mL DMF. To this mixture was added freshly prepared 1-M aqueous solution of Na ascorbate (240.0 µL, 0.24 mmol) and CuSO 4 (120.0 µL. 0.12 mmol) in sequential. The reaction mixture was stirred at ambient temperature overnight. The mixture was poured into distilled water (25.0 mL) and extracted with EtOAc (3 × 10.0 mL). The organic layers were combined and washed with brine (10.0 mL), distilled water (5 × 10.0 mL), dried with MgSO 4 , and filtered. The filtrate was concentrated in vacuo to give the crude product, which was purified on column chromatography with SiO 2 using 6% MeOH in DCM as the eluent. See the supplementary information for the full characterisations of the final compounds.
Some of the datasets generated during and/or analysed during the current study are in the manuscripts while the rest are available from the corresponding authors on reasonable request.
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The authors would also like to thank the Centre for High Performance Computing (CHPC, Cape Town, South Africa) for access to CHPC Lengau Cluster and Schrödinger molecular docking software.
Open access funding provided by University of Pretoria. This work was supported by the National Research Foundation (South Africa) (Grant number: 105152) and the University of Pretoria, South Africa (doctoral financial support to Rasheed A. Adigun).
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Department of Chemistry, University of Pretoria, Lynnwood Road, 0002, Hatfield, Pretoria, South Africa
Rasheed A. Adigun, Frederick P. Malan & Natasha October
Biopolymer Modification & Therapeutics Lab, Chemicals Cluster, Council for Scientific and Industrial Research, Meiring Naude Road, 0001, Brummeria, Pretoria, South Africa
Mohammed O. Balogun
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All authors contributed to the study. Conception and design, material preparation, data collection, and analysis were performed by Rasheed A. Adigun, Frederick P. Malan, Mohammed O. Balogun, and Natasha October. The first draught of the manuscript was written by Rasheed A. Adigun, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Correspondence to Rasheed A. Adigun or Natasha October .
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Adigun, R.A., Malan, F.P., Balogun, M.O. et al. Design, synthesis, and in silico-in vitro antimalarial evaluation of 1,2,3-triazole-linked dihydropyrimidinone quinoline hybrids. Struct Chem 34 , 2065–2082 (2023). https://doi.org/10.1007/s11224-023-02142-y
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Vandana guleria.
1 Department of Biotechnology, Faculty of Applied Sciences and Biotechnology, Shoolini University of Biotechnology and Management Sciences, Solan, Himachal Pradesh, India
2 Department of Biotechnology, Vignan’s Foundation for Science, Technology and Research, Vadlamudi, Guntur, Andhra Pradesh, India
Shweta chauhan, varun jaiswal.
3 Department of Engineering, School of Electrical and Computer Science Engineering, Shoolini University of Biotechnology and Management Sciences, Solan, Himachal Pradesh, India
4 Department of Food and Nutrition, College of BioNano Technology, Gachon University, Seongnam-si 13120, Gyeonggi-do, Korea
The data used in this study are available and will be provided by the corresponding author on a reasonable request.
Malaria is an ancient disease that still causes more than 200 million of cases 7 with high mortality globally. Identification of new drug targets and development of novel antimalarial drugs with unique mode of action encounter the drug resistance and reduce the mortality by Plasmodium parasites. Actin protein is one of the key proteins in Plasmodium falciparum playing multifarious important roles including transport, cell motility, cell division, and shape determination. This study investigated Actin I as a drug target, in silico screening of diverse molecules through molecular docking was considered. Further, pharmacokinetic parameters of the selected molecules from the docking and interaction studies were planned to propose the lead molecules.b
Molecules were selected according to score and protein ligand interaction and selected molecules were subjected for pharmacokinetic studies to investigate important drug parameters.
The docked molecules were ranked according to the binding score and good interaction pattern was observed with Actin I within top 20 scoring molecules. The selected molecules also had optimum pharmacokinetic parameters.
The current study provides a set of hit molecules which can be further explored through in vitro and in vivo experiments for the development of potential drugs against malaria, there by encountering drug resistance and establishing Actin I as an important drug target.
Malaria is a life-threatening disease caused by parasites belonging to five species of genus Plasmodium falciparum which are transmitted through the bite of female Anopheles mosquito. In 2017 as per the WHO report, 219 million cases of malaria were reported in 87 countries and the estimated number of deaths was found to be 435,000. Despite such drastic figures there is still no widely used efficacious vaccine available for malaria parasites.[ 1 ] Although, antimalarial drugs are available from long back and the popular antimalarial medications used against malarial parasites includes Chloroquine, Chloroguanide (Proguanil), Sulfadoxine/pyrimethamine, Quinine, Mefloquine, Halofantrine, Artemisinin (ART), and Atovaquone. In 21 st century, the drug resistance has emerged to almost all classes of antimalarial drugs and therefore a sudden leap has been witnessed in malaria-related mortality, especially in Africa.[ 1 ]
Both drug resistance and unavailability of highly effective vaccine makes malaria a highly challenging disease and a great public health burden. The identification of new/novel drug targets as well as development of novel antimalarial drugs with unique mode of action can be the possible answer to drug resistance in malaria and subsequently it can control the mortality due to malaria.[ 2 , 3 ] Being highly studied diseases several potential drug targets have been suggested in research which can be further developed as a drug target in experiments. Actin I is also such kind of drug target in malaria. Recently, our group has discovered that Actin I protein is expressed in almost all stages of P. falciparum which are present in human which justifies its importance in plasmodium lifecycle and its drug target potential.[ 4 ] Although in different literature actin is proposed as the drug target in malaria, it is not yet studied for structure based drug design and subsequently not developed as an important drug target.[ 4 , 5 ] The main reasons for the selection of the Actin I in the current study are the Actin I protein is novel drug target which is important in different stages of P. falciparum and can be a probable answer to drug resistance.[ 4 ] Although the Actin I protein is conserved in both, there is difference between human and P. falciparum actin protein. In human, three isoforms of actin have been identified, alpha, beta, and gamma whereas in P. falciparum there exists only two isoforms, that is, Actin I and Actin II.[ 6 , 7 ] This protein is an essential part of the parasite motor machinery and responsible for gliding motility of the parasite.[ 8 , 9 ] In nature, there exists six different mammalian actin isoforms which differ from each other by a maximum of 6% of the sequence, and are practically identical across the species. Commonly most actins have the capacity to form long filaments but in P. falciparum the presence of regular actin filaments is uncertain. In P. falciparum Actin I is abundant and expressed throughout the lifecycle of the parasite. In vitro, apicomplexan actins form short, ~100-nm long filaments, which suffer from rapid tread milling.[ 10 , 11 ] Recently, specific antibodies revealed filament-like structures in motile forms of P. falciparum .[ 12 ] The P. falciparum Actin I fibers are refined from merozoites and are thereby distinctive for their helical symmetry from canonical actin structures.[ 13 , 14 ]
The most prevalent forms of actin protein are ATP-G-actin and ADP-F-actin. The structural determination of G-actin reveals that it has two lobes separated by a cleft, which is an ATPase fold. The functional form of G-actin exhibits only when the cleft comprises of an ATP or ADP. The F-actin polymer is a filamentous protein which is also referred as microfilament with levorotatory helix structure. The cell creeping process helps actin cytoskeleton to encounter dynamic assembly and disassembly, which further controls central attachment of assembly/disassembly bulge advancement, and contractile fiber association. Moreover cell relocation and adhesion is inhibited by the disturbance of the actin cytoskeleton.[ 15 - 17 ] The assembly and disassembly of local Actin I filament regulates the dynamic formation of lamellipodia. The lamellipodia is slim, sheet-like film distensions of the motile cells. During movement, cells grow the film forward to explore their environment. The branching and elongation are the two examples of actin fiber assembly, which advance the improvement of the actin “work” in the cell distension.[ 16 , 18 ] The nucleation promoting factors such as neuronal Wiskott - Aldrich syndrome Protein (N-WASP) and WASP-family verprolin-homologous protein (WAVE) prohibit the movement of Arp2/3 complex, which are in turn modulated by upstream regulators.[ 16 ] The Actin I fibers are organized into two kinds of arrays: Bundles and web like systems. Similarly, the Actin I fibers cross-connecting the proteins help to stabilize and keep up these structures and are divided into two classes: Packaging proteins and web-forming proteins. Actin I plays an important role in the intracellular blood stages of P. falciparum , such as endocytosis and vesicle trafficking,[ 18 , 19 ] ring stage morphology,[ 20 ] and spatial positioning of genes in the nucleus.[ 21 ] As per the recent studies, the actin elements have appeared to assume significant roles in the inheritance of intracellular organelles, for example, the apicoplast, mitochondria and secretory vesicles during intracellular parasite replication.[ 21 - 24 ] The Actin I association has also been well studied in zoite and asexual blood stages. In this intracellular stage, the parasite experiences a wonderful morphological change during which the parasite embraces a crescent or falci from shape in anticipation for transmission by means of the Anopheles mosquito.[ 25 , 26 ] In Actin I structure the C terminus acquires the shape of a-helix and it interacts with the bottom of the sub domain 1. Actin I protein consist of cleft named hydrophobic cleft between the sub-domains I and III. This cleft is major regulatory site and regarded as hotspot for the protein binding.[ 7 ] The binding pocket of Actin I has two parameters, the “mouth” and “phosphate clamp.” The “mouth” is considered as the distance between the Ca atoms of Gln59and Glu207. The distance between the Caatoms of Gly15 and Asp157 makes the “phosphate clamp.” As compared to the canonical actins, in Actin I there is a smaller cleft where large hydrophobic residues have adopted different conformations together withTrp357. Actin I shows significant structural deviations in specific regions which are involved in binding of proteins.[ 7 , 27 ] This may provide opportunities for structure-based drug design targeted at the P. falciparum act in-regulatory boundaries. The importance of Actin I protein is established in most of the stages of parasite. The crucial function of Actin I in asexual, blood, liver, mosquito and sexual stages is reported in the literature which also correlates with our earlier finding of its expression in nearly all stages of P. falciparum .[ 4 ] The active site residues of protein consist of amino acids, that is, Asn 17(A), Gly 16(A), Lys 19 (A), Gly 303(A), Glu 215(A), Lys 214(A), Val 160 (A), and Gly 159(A).
In current study, Actin I protein was taken for molecular docking studies because it is a new potential drug target and relatively not explored as drug target in drug discovery in spite of its conservation in different species of P. falciparum . In P. falciparum intracellular functions of Actin I have been recommended, that is, endocytosis,[ 20 ] secretion, and antigenic variation.[ 18 , 28 , 29 ] Molecular docking is an important tool for drug discovery and can be used to model the interaction between small drug like molecule and a protein at atomic level, which permit us to describe the enactment of small molecules in the binding sites of target proteins as well as to irradiate the biochemical processes. Docking is very useful and one of the most commonly used methods in structure-based drug design, due to its capability to predict the binding-conformation of small molecule ligands to the appropriate target binding site.[ 4 , 30 - 32 ] In the current study, the library of small molecules is screened against Actin I protein. The top scoring molecules from docking study were subjected for protein-ligand interaction studies and prediction of pharmacokinetics properties. Favorable pharmacokinetics property is also essential parameter for the ligand to be considered in drug discovery process. Therefore, the best molecules according to these three studies can be strongly suggested for further wet lab experiments of drug design.
Retrieval of protein and ligand libraries.
The crystal structure of Actin I of P. falciparum (PDB ID: 4CBU) was downloaded from protein databank in pdb format [ https://www.rcsb.org/structure/4CBU ]. For virtual screening organic molecule library from NPACT database consisting of total 1574 molecules ( https://zinc.docking.org/browse/catalogs/natural-products ) was downloaded from zinc database in mol2 format.
The crystal structure of P. falciparum Actin I (PDB ID: 4CBU) is of 1.3 A ° resolution with bound ligand ATP and have two chains; chain A and chain G. It was observed that the binding pocket is located in chain-A and chain-G was away from binding pocket. Hence, chain-G was removed through UCSF Chimera before the protein preparation and in further docking studies only chain-A was considered. The bound ligand molecule was also removed before docking. The protein was prepared for docking studies by assigning hydrogen, polaraties, calculating Gasteiger charges to protein structures, and converting protein structures from the pdb format to pdbqt format using Auto-Dock tool1.5.4.
The natural occurring plant-based compound activity target database library was downloaded from ZINC database ( https://zinc.docking.org/ )in MOL2 format and was further used for performing docking studies. The library was in a single molecular file and all the ligand molecules were extracted from it with the help of in-house developed PERL scripts. Subsequently all the ligand molecules were converted into PDB format from MOL2 format by using open babel with the help of in-house developed PERL scripts. Antimalarial drugs including Chloroquine, Chloroguanide, Quinine, Mefloquine, and Halofantrine were also used as positive control to target ACTIN I and structure of these molecules were taken from PubChem ( https://pubchem.ncbi.nlm.nih.gov/ ).
All the ligands within the organic molecular library were used to perform molecular docking studies[ 33 , 34 ] against Actin I to find the potential hit molecules for further drug discovery experiments. In the current research for performing the docking studies the version 4.2 of AutoDock was used. AutoDock uses a Lamarckian Genetic Algorithm (LGA) and is based on a semi empirical free energy force field.[ 35 ] The docking grid was set manually through visualization of the protein and grid was defined to cover entire binding site of Actin I.
The size of grid was defined as X=54, Y=54 and Z=54 and the coordinates used for docking of ligands library with 4CBU were X=9.175, Y=20.366, and Z=18.583. Also for molecular docking for every molecule ten runs of LGA were performed. The main interacting residues in the binding site were Asn17, Lys19, Tyr338, Lys337, Lys214, Gln215, and other nearby residues. Finally, molecular docking was carried out on target proteins with all ligands from the library using self-developed PERL script, which was used for screening of these large number of ligand molecules one by one [ Figure 1 ]. The top scoring compounds were selected on the basis of binding energy of ligands with the receptor. The lower is the binding energy of ligand with the receptor the more strongly it will bound to the target receptor.
The methodology followed for docking and screening
The UCSF Chimera1.8.1 was used to visualize and analyze docked complexes of ligand and protein.[ 36 ] The interaction such as hydrogen bonds and hydrophobic interaction was also analyzed using Ligplot+.[ 37 , 38 ] The generated plots have shown the hydrophobic interaction patterns and hydrogen bonding between the main chain/side-chain atoms of the protein with the ligand.
The pharmacokinetic profile prediction of potential compounds was done using pkCSM ( http://biosig.unimelb.edu.au/pkcsm/prediction ) with incorporated prediction of toxicity, metabolism, distribution, absorption, and excretion.[ 39 ] Some other properties such as molecular descriptors and drug likeliness properties were also analyzed with the help of pkCSM. The drug likeliness properties were predicted according to the Lipinski Rules of five.[ 40 ]
In the present study, considering the importance of Actin I protein as a drug target in P. falciparum molecular docking of actin I of P. falciparum was carried out. The organic molecular library was docked into the active site of Actin I to find the potential ligand molecules which can be used in further drug design experiments and also establish the Actin I as an important drug target in malaria. Pharmacokinetics properties of top ranked molecules were also calculated computationally so that molecules with better pharmacokinetics properties can be further shortlisted for wet lab experiments.
Molecular docking of all the ligands within the library was found to be successful on the basis that all the ligands were docked in the active site of the receptor. The 20 top scoring molecules as per estimated free energy of binding (EFEB) were selected for further investigations. The protein ligand complexes of top scoring molecules were analyzed for interactions, the orientation of the docked compound, and interacting active site residues were visualized. The selected 20 molecules had EFEB in the range of −13.20–−10.51 [ Table 1 ]. The molecule, that is, ZINC30724344 shows least EFEB of −13.20 [ Table 1 ]. The four other top scoring molecules ZINC13515285, ZINC03943903, ZINC95098956, and ZINC03984030 showed the EFEB −12.61, −12.57, −12.37, and −12.23, respectively [ Table 1 ] [Supplementary Figures Figures1 1 - -3]. 3 ]. Despite these molecules the other molecules also had EFEB better than-10 and also show good interaction with the target molecule [ Table 1 ] [ Supplementary Table 2 ] [ Supplementary Table 3 ].
Binding affinity of selected potential molecules
The top scoring molecule, that is, ZINC30724344 strongly interacts with the Glu215, Lys19 and Asn17 residues of the binding cavity [ Figure 2 ] [ Table 1 ]. The second-best scoring molecule as per the EFEB, that is, ZINC13515285 forms hydrogen bonds with the Lys337, Asn17, Lys19, Lys214, Tyr307, Thr304, and Gly303 [ Figure 3 ] [ Table 1 ].
(a and b) Interactions of ZINC30724344 with Actin I
(a and b) Interaction of ZINC13515285 with Actin I
The molecule ZINC03943903 strongly interacts with the Lys19, Ca1370, Lys337, Gly303, Gly16, Asn17, Asp158, Thr304, and Lys214. All other selected molecules also show good patterns of hydrogen bond and hydrophobic interactions [ Table 1 ].
Among the five antimalarial drugs which were used for control docking Mefloquine exhibit the best estimated free energy of −8.5 kcal/mol with Actin I and interact strongly with Thr278, Ala273 [ Supplementary Table 1 ]. The other drugs which were used as positive controls, that is, Chloroquine, Chloroguanide, Quinine, and Halofantrine show the EFEB −8.2, −7.1, −7.6, and −8.0, respectively [ Supplementary Table 1 ].
The drug molecules which are having molecular weight less than 500Da can be easily transported, diffused and absorbed as compared to bigger molecules.[ 41 ] The physicochemical properties were calculated and the molecular weight of 10 hit molecules out of 20 was less than 500 Da. Most of the molecules [ Table 1 ] showed log P < 5 [ Table 1 ]. The 13 out of 20 selected hit molecules have less than 5 hydrogen bond donors and also have less than 10 hydrogen bond acceptors [ Table 2 ].
Physicochemical properties of potential compounds
The selected 20 top scoring molecules were subjected to ADMET properties prediction. In ADMET, the absorption properties such as intestinal solubility (% absorbed), water solubility (log mol/L), and skin permeability (logKp) values were calculated. The other properties such as Ames test, BBB penetrability, and Caco2 (cell line of human colorectal adenocarcinoma cells) permeability was included under ADMET. For human intestinal absorption, the compounds which have value less than 30% are poorly absorbed [ 41 , 42 ] Out of the 20 selected hit molecules only three molecules depicted the intestinal absorption value less than 30% and other molecules displayed good absorption potential in human intestine [ Table 3] . The selected top 20 scoring molecules also showed good skin permeability values as compared to standard value (−2.5 logKp) [ 41 ] and only few can penetrate to Caco2 as compared to (>0.90 as per pkCSM) standard value [Tables [Tables3 3 and and4 4 ].
Absorption profile of potential compounds
Distribution/excretion profile of compounds
The human microsomal P450s aromatase catalyze the metabolism of a wide variety of compounds including drugs and xenobiotic. In ADMET under metabolism profile, the top scoring molecules were tested whether they were acting as an inhibitor or substrate for different isoforms of cytochrome P450 as it is important for drug metabolism. Many drugs can be inactivated by cytochrome P450 whereas some can be activated also. The inhibitors of cytochrome P450 can affect metabolism of drugs. Hence, from the predicted values, it was observed that the ten molecules out of 20 can acts as a substrate for one of the isoforms of P450, that is, CYP3A4 and none of the molecule acts as a substrate for other isoforms, that is, CYP2D6. The predictive values of the selected hit compounds suggest that only few compounds were acting as inhibitors for CYP3A4, CYP2C19, CYP2C9 and CYP3A4 isoforms of the cytochrome [ Table 5 ].
Metabolism profile of potential compounds
The toxicity and mutagenicity of the selected molecules were depicted with the help of Ames test data, only single molecule, that is, ZINC95099527 displayed the positive results and remaining 19 molecules were note found to be toxic according to Ames test data [ Table 6 ]. Furthermore, for a given molecule maximum recommended tolerated dose (MRTD) ≤0.477 was considered as low and MRTD high if greater than 0.477 as per pkCSM, although most of selected molecules show low MRTD [ Table 6 ].
Toxicity profile of the potential compounds
Malaria is still a major global health problem, although antimalarial drugs are available drug resistance has emerged thereby increasing morbidity and mortality rate. The research for the development of efficient licensed malaria vaccine is still not over despite many rigorous efforts have been made in the last decade. It was previously suggested in the literature that the proteins such as actin, tubulin, and histone are involved in the structural assembly of the pathogen.[ 43 , 44 ] Hence, the potential new drug target Actin I is one of the most important structural proteins which is found in P. falciparum and plays important role in its motility apparatus, sexual, asexual and blood stages of the organism.[ 39 ] It is expressed in all human stages and little is known about its potential as a drug target. In the current repertoire, we have considered library of 1574 natural organic molecules of diverse nature which were docked with Actin I protein of P. falciparum employ in one of the most important docking software.[ 6 ] AutoDock 4.2. The selected molecules were further subjected to their pharmacokinetic studies to make them potentially promising drug candidates.[ 45 ] These approaches were widely utilized to design drugs against a number of pathologies such as cardiovascular diseases and cancer.[ 46 - 48 ] The current study is the first report to explore the potential of receptor protein Actin I as an efficient drug target in structure-based drug design.
The prospect of virtual screening techniques was employed to screen the 20 top scoring molecules on the basis of their binding affinity. Although EFEB of ligand protein interaction is relative score and direct correlation of this score is not studied in different docking studies, EFEB of selected ligands in current study was better than the ligands found to be active in recent in silico and in vitro studies conducted by our group in falcipains 2 and 3 of P. falciparum .[ 49 ] In addition, when the docked complexes of these selected hit molecules were subjected to post docking analysis, they displayed good interaction patterns (hydrogen as well as hydrophobic interactions). The compound with zinc ID ZINC30724344 was the top scoring molecule and also depicted good interactions indicating a potent promising candidate. Similar trend was also discovered for other remaining 19 molecules which were also prioritized as hit molecules displaying good binding affinities and interaction patterns [ Table 1 ]. Furthermore, the 20 top scoring molecules interact strongly with the target protein forming number of hydrogen bonds [ Table 1 ] [Figures [Figures2 2 and and3]. 3 ]. In most of these top scoring molecules Lys337, Asn17, and Lys19 were found to be most common interacting residues forming hydrogen bonding. The top scoring molecules exhibit better binding affinity in terms of EFEB as compared to the antimalarial drugs which were used as positive control [ Supplementary Table 1 ].
Further, these top scoring molecules were subjected to ADMET prediction and physicochemical analysis to ensure drug likeness of hit molecules as part of Lipinski’s rule of five. The ADMET properties are important criteria because significant number of molecules failed in the clinical trial due to poor ADMET properties.[ 50 ] The top scoring molecule from docking studies ZINC30724344 exhibited molecular weight of 592.696 Da, logP of5.01246, HBA of 6 and HBD value as 2. Furthermore, this hit molecule was non-toxic as per Ames test data and displayed good intestinal absorption (84.303%) and skin permeability (logKp-2.735) values. The molecular weight and logP were observed to be slightly higher as per the standard rules, but natural origin and all other parameters justified that the above potential hit molecule can be developed against malaria which can serve as a roadmap for perusing drug discovery process. The remaining molecules having zinc ID ZINC38145808, ZINC95099570, ZINC14883289, and ZINC02138728also showed high binding affinities and these molecules also justified the different essential parameters to be considered as hit molecules for the drug discovery [ Table 1 ] [Figures [Figures2 2 and and3]. 3 ]. Although current results are very promising, computational studies require further wet lab experimental verification including target validation. Moreover, current findings warrants that these selected hit molecules can be subjected to further wet lab experimentations for the efficacy of hits compound in vitro and in vivo studies against plasmodium and subsequently modification accordingly so that these molecules can be used as potential hit molecules for anti-malarial drug discovery.
First time virtual screening methodology was implemented successfully for Actin I of P. falciparum using structure-based drug design. Library of diverse molecules was screened to find potential hit molecules on the basis of EFEB. Protein ligand interaction and ADMET properties of top selected scoring molecules were found to be favorable. Among the selected top scoring molecules, the five molecules, that is, ZINC30724344, ZINC13515285, ZINC03943903, ZINC95098956, and ZINC03984030 looks more prominent as a potential candidate for further drug development. The current findings provide a suitable starting point for further in vitro and in vivo analyses to exploit Actin I as an optimal drug target which can encounter drug resistance.
Ethics approval and consent to participate.
Not applicable (as no human subject was used in the study)
Availability of data and material, competing interests.
None declared.
This research received no specific grant from any funding agency
The research “Conceptualization, V.J. and S.C.; Methodology, V.G.; Software, B.S. and V.G.; Validation, T.P., and B.S.; Formal Analysis, B.S. and V.G.; Data Curation, T.P. and B.S.; Writing – Original Draft Preparation, S.C. and V.G.; Writing – Review & Editing, V.J., T.P., B.S. and S.C.; Visualization, V.G. and B.S.; Supervision, V.J. and T.P.; Project Administration, V.J.;
Authors would like to acknowledge Shoolini University, Solan Himachal Pradesh, India.
ORCID link of the submitting author: https://orcid.org/0000-0001-8068-0672
Supplementary table 1.
Docking of Actin I with different Antimalarial drugs:
Top 20 molecules ki (Values)
Top 20 molecules structures
Interactions of ZINC03984030 with Actin I
Interactions of ZINC95098956 with Actin I
Interactions of ZINC03943903 with Actin I
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Combination of antimalarial agents has been introduced as a response to widespread drug resistance. The higher number of mutations required to express complete resistance against combinations may retard the further development of resistance. Combination of drugs, especially with the artemisinin drugs, may also offer complete and rapid eradication of the parasite load in symptomatic patients and thus reduce the chance of survival of resistant strains. The advantages of combination therapy should be balanced against the increased chance of drug interactions. During the last decade, much of the pharmacokinetics and metabolic pathways of antimalarial drugs have been elucidated, including the role of the cytochrome P450 (CYP) enzyme complex. Change in protein binding is not a significant cause of interactions between antimalarial agents. CYP3A4 and CYP2C19 are frequently involved in the metabolism of antimalarial agents. Quinidine is a potent inhibitor of CYP2D6, but it appears that this enzyme does not mediate the metabolism of any other antimalarial agent. The new combinations proguanil-atovaquone and chlorproguanil-dapsone do not show significant interactions. CYP2B6 and CYP3A4 are involved in the metabolism of artemisinin and derivatives, but further studies may reveal involvement of more enzymes. Artemisinin may induce CYP2C19. Several artemisinin drugs suffer from auto-induction of the first-pass effect, resulting in a decline of bioavailability after repeated doses. The mechanism of this effect is not yet clear, but induction by other agents cannot be excluded. The combination of artemisinin drugs with mefloquine and the fixed combination artemether-lumefantrine have been studied widely, and no significant drug interactions have been found. The artemisinin drugs will be used at an increasing rate, particularly in combination with other agents. Although clinical studies have so far not shown any significant interactions, drug interactions should be given appropriate attention when other combinations are used.
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Malaria, which is caused by several protozoan Plasmodium species that transmit the disease through mosquitoes, continues to affect individuals throughout the world, particularly in sub-Saharan Africa, where 95% and 96% of cases and deaths occur, respectively 1 .
Common symptoms associated with malaria can include fever, headache, malaise, weakness, gastrointestinal distress, dizziness, confusion, disorientation, and, in severe cases, coma.
Despite the World Health Organization's (WHO) Global Technical Strategy (GTS) goal to eradicate malaria by 2030, case numbers have increased over the past several years. In 2021 alone, over 247 million malaria cases were reported, 619,000 of which resulted in death, a significant rise of 33 million cases and 181,000 deaths compared to those reported in 2015.
Several antimalarial drugs are currently available to limit the detrimental effects of this disease and reduce associated mortality. However, many of these drugs are associated with limitations that prevent their widespread availability. Resistance to malaria medications also necessitates continuous monitoring and the identification of new candidate drugs with superior efficacy profiles.
Suspected malaria cases must be quickly identified and treated to reduce the risk of mortality, as this disease can evolve rapidly into lethal symptoms. Some of the most widely used treatments for uncomplicated Plasmodium falciparum malaria include artemisinin (ART)-based combination treatments (ACTs), which include aremether-lumefantrine (AL) and artesunate-amodiaquine, which comprise 75% and 24% of the African market share, respectively 1 .
Other less frequently utilized treatment options include combinations of dihydroartemisinin-piperaquine (DHA-PPQ), atovaquone-proguanil (Malarone), and quinine with doxycycline or clindamycin. The choice of treatment will depend on the patient’s age, severity of symptoms, and immune status.
Despite the availability of these treatments, there remains an urgent need to treat asymptomatic patients, as these individuals are still capable of spreading disease through dormant Plasmodium vivax parasites.
Furthermore, patients with severe malaria often cannot be treated with oral medications and, as a result, require injectable treatments like artesunate or quinine.
To date, many different drug candidates are being investigated in preclinical exploratory phases, as well as human volunteer and malaria patient exploratory phases. For example, several novel small molecules have been evaluated in patients with malaria, including ZY-19489 and ferroquine. Recent studies on the combination treatment of ZY-19489 and ferroquine indicate that single-dose and long-term efficacy may be possible in children 1 .
Other notable small molecules that have been identified and studied in humans include cabamiquine, cipargamin, and ganaplacide. The latter is considered the most advanced antimalarial, as it is highly potent and has a favorable pharmacokinetic and safety profile.
The combination of ganaplacide with lumefantrine, a partner drug traditionally used in ACTs, has been shown to reduce the risk of resistance while also maintaining efficacy in large patient cohorts 1 .
The United States National Institutes of Health (NIH) is currently investigating the prophylactic efficacy of two monoclonal antibodies, CIS43LS and L9LS. CIS43LS targets the circumsporozoite protein (CSP), which is crucial for parasites' ability to invade and infect hepatocytes.
Both phase I and phase II clinical trials have demonstrated that CIS43LS is associated with over 88% efficacy for at least six months 1 . As compared to CIS43, the parent antibody of CIS43LS, L9LS, has been shown to be three times more potent.
MMA01 and TB-21F are other monoclonal antibodies being investigated for malaria prophylaxis. Despite their potential, monoclonal antibodies are expensive to produce and often require specific storage conditions; therefore, their practical use in low—and medium-income countries will be a challenge.
For several decades, insecticidal nets have been successful in mitigating malaria transmission; however, this approach has been shown to increase the risk of mosquito resistance.
As an alternative vector control method, researchers have investigated the potential of treating mosquitos with antimalarials to support malaria control and elimination.
Some of the different methods that have been investigated include genetically modifying mosquitos so that they are resistant to parasitic infection and systemic treatment of mosquitos with insecticides like ivermectin, lota liner, or isooxazoline 1 .
What Role do Natural Products Play in Modern Drug Discovery?
Non-compliance with the three-day regimen for ART, as well as its short half-life, has contributed to resistance to this drug and, as a result, its limited efficacy in treating malaria. Both total and partial resistance to other malaria drugs have also been reported throughout the world.
‘’The development of plasmodium parasites resistance to many drugs shows that more innovative research is still required, particularly on discovery of small molecules with novel mechanisms of action and targeted delivery approach of drugs to specific organs/tissues in order to increase efficacy and reduce adverse drug interactions. 3 ”
Malaria primarily affects sub-Saharan African populations, particularly those residing in the poorest areas of this region. Agencies like the Global Fund have historically provided these communities with free anti-malaria medications; however, limited funding has been available to support the production and subsequent distribution of these medications on a larger scale.
Furthermore, many pharmaceutical companies have excluded malaria and other tropical diseases from their portfolio due to the high cost of drug development and limited commercial return.
Despite the lack of innovative drug discovery by pharmaceutical companies, several programs have been developed to support the discovery and delivery of new antimalarials to high-risk populations.
The Medicines for Malaria Venture (MMV), for example, is funded by governments and philanthropic organizations worldwide to ensure the dissemination of current anti-malarial medications while also supporting research endeavors for next-generation treatments 1 .
The Malaria Drug Accelerator (MaIDA), formed in 2012, primarily focuses on discovering novel malaria targets and advancing phenotypic drug screening to ultimately identify highly efficacious drug candidates 2 . To date, MaIDA has facilitated the discovery and prioritization of several malaria targets and tool compound characteristics capable of their inhibition.
The Biggest Challenges in Drug Discovery
Recent advancements in artificial intelligence (AI) indicate that this technology is capable of leveraging existing data to identify hit compounds more efficiently and rapidly than traditional screening platforms.
DeepMalaria, a deep-learning program, has recently been trained on 13,446 antiplasmodial hit compounds from the GlaxoSmithKline (FSK) database that are currently being investigated for their anti-malaria potential.
In a 2023 study, DeepMalaria successfully identified 72.32% of active molecules with increasing accuracy in its ability to distinguish more potent compounds 4 . Although these results are promising, additional research is needed to determine the potential role of AI-based approaches in malaria drug discovery projects.
Multiomics technologies have been widely used over the past several years to understand better the biological mechanisms involved in Plasmodium falciparum infection. For example, genomics studies have provided important insights into the various stages of liver-stage infection with this parasite, which has been crucial for the identification of potential target genes involved in the development of severe malaria 5 .
Thus, future studies will continue to utilize omics-based methodologies to identify novel malaria targets and those involved in other protozoan diseases.
Last Updated: Sep 3, 2024
After completing her Bachelor of Science in Toxicology with two minors in Spanish and Chemistry in 2016, Benedette continued her studies to complete her Master of Science in Toxicology in May of 2018. During graduate school, Benedette investigated the dermatotoxicity of mechlorethamine and bendamustine; two nitrogen mustard alkylating agents that are used in anticancer therapy.
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