Identification of Potential Multitarget Compounds against Alzheimer's Disease through Pharmacophore-Based Virtual Screening.

Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive loss of cognitive functions, and it is the most prevalent type of dementia worldwide, accounting for 60 to 70% of cases. The pathogenesis of AD seems to involve three main factors: deficiency in cholinergic transmission, formation of extracellular deposits of ß-amyloid peptide, and accumulation of deposits of a phosphorylated form of the TAU protein. The currently available drugs are prescribed for symptomatic treatment and present adverse effects such as hepatotoxicity, hypertension, and weight loss. There is urgency in finding new drugs capable of preventing the progress of the disease, controlling the symptoms, and increasing the survival of patients with AD. This study aims to present new multipurpose compounds capable of simultaneously inhibiting acetylcholinesterase (AChE), butyrylcholinesterase (BChE)-responsible for recycling acetylcholine in the synaptic cleft-and beta-secretase 1 (BACE-1)-responsible for the generation of amyloid-ß plaques. AChE, BChE, and BACE-1 are currently considered the best targets for the treatment of patients with AD. Virtual hierarchical screening based on a pharmacophoric model for BACE-1 inhibitors and a dual pharmacophoric model for AChE and BChE inhibitors were used to filter 214,446 molecules by QFITBACE > 0 and QFITDUAL > 56.34. The molecules selected in this first round were subjected to molecular docking studies with the three targets and further evaluated for their physicochemical and toxicological properties. Three structures: ZINC45068352, ZINC03873986, and ZINC71787288 were selected as good fits for the pharmacophore models, with ZINC03873986 being ultimately prioritized for validation through activity testing and synthesis of derivatives for SAR studies.

Molecular Multi-Target Approach for Human Acetylcholinesterase, Butyrylcholinesterase and ß-Secretase 1: Next Generation for Alzheimer's Disease Treatment.

Alzheimer's Disease (AD) is a neurodegenerative condition characterized by progressive memory loss and other affected cognitive functions. Pharmacological therapy of AD relies on inhibitors of the enzymes acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), offering only a palliative effect and being incapable of stopping or reversing the neurodegenerative process. However, recent studies have shown that inhibiting the enzyme ß-secretase 1 (BACE-1) may be able to stop neurodegeneration, making it a promising target. Considering these three enzymatic targets, it becomes feasible to apply computational techniques to guide the identification and planning of molecules capable of binding to all of them. After virtually screening 2119 molecules from a library, 13 hybrids were built and further screened by triple pharmacophoric model, molecular docking, and molecular dynamics (t = 200 ns). The selected hybrid G meets all stereo-electronic requirements to bind to AChE, BChE, and BACE-1 and offers a promising structure for future synthesis, enzymatic testing, and validation.

Identification of potential human beta-secretase 1 inhibitors by hierarchical virtual screening and molecular dynamics.

Alzheimer's disease (AD) is a neurodegenerative pathology responsible for 70% of dementia cases worldwide. Despite its relevance, the few drugs available for the treatment of this disease offer only symptomatic relief, with limited efficacy and serious adverse effects. The most accepted hypothesis about the pathogenesis involves the aggregation and deposition of ß-amyloid peptides, mainly in the cerebral cortex and hippocampus, through the catalytic action of beta-secretase 1 (BACE-1), making this enzyme a promising target for the development of new drugs. In order to prioritize candidates for BACE-1 inhibitors, a hierarchical virtual screening by pharmacophore model and molecular docking was performed against the 216,833 molecules contained in several databases. Our previously built pharmacophore model was used for the first filtering step, which resulted in the selection of 399 molecules. The remaining molecules were filtered through molecular docking with GOLD 5.4.0. In this step, molecules with scoring values ​​greater than the mean plus standard deviation were evaluated for commercial availability and absence of asymmetric centers. Four molecules were selected and evaluated for mutagenic potential by the AMES test with the help of the pkCSM server. Finally, they were tested against the descriptors on Lipinski and Veber rules, and ZINC01589617 (QFIT = 56.52/Score = 44.95) satisfied all requirements, being subjected to molecular dynamics simulations (t = 100 ns) in order to obtain robust data on the mode of bonding and profile of intermolecular interactions. Those in silico strategies demonstrated that ZINC01589617 is a potential candidate for biological tests.Communicated by Ramaswamy H. Sarma.

Rational-Based Discovery of Novel ß-Carboline Derivatives as Potential Antimalarials: From In Silico Identification of Novel Targets to Inhibition of Experimental Cerebral Malaria.

Malaria is an infectious disease widespread in underdeveloped tropical regions. The most severe form of infection is caused by Plasmodium falciparum, which can lead to development of cerebral malaria (CM) and is responsible for deaths and significant neurocognitive sequelae throughout life. In this context and considering the emergence and spread of drug-resistant P. falciparum isolates, the search for new antimalarial candidates becomes urgent. ß-carbolines alkaloids are good candidates since a wide range of biological activity for these compounds has been reported. Herein, we designed 20 chemical entities and performed an in silico virtual screening against a pool of P. falciparum molecular targets, the Brazilian Malaria Molecular Targets (BRAMMT). Seven structures showed potential to interact with PfFNR, PfPK7, PfGrx1, and PfATP6, being synthesized and evaluated for in vitro antiplasmodial activity. Among them, compounds 3−6 and 10 inhibited the growth of the W2 strain at µM concentrations, with low cytotoxicity against the human cell line. In silico physicochemical and pharmacokinetic properties were found to be favorable for oral administration. The compound 10 provided the best results against CM, with important values of parasite growth inhibition on the 5th day post-infection for both curative (67.9%) and suppressive (82%) assays. Furthermore, this compound was able to elongate mice survival and protect them against the development of the experimental model of CM (>65%). Compound 10 also induced reduction of the NO level, possibly by interaction with iNOS. Therefore, this alkaloid showed promising activity for the treatment of malaria and was able to prevent the development of experimental cerebral malaria (ECM), probably by reducing NO synthesis.

Evaluation of Docking Machine Learning and Molecular Dynamics Methodologies for DNA-Ligand Systems.

DNA is a molecular target for the treatment of several diseases, including cancer, but there are few docking methodologies exploring the interactions between nucleic acids with DNA intercalating agents. Different docking methodologies, such as AutoDock Vina, DOCK 6, and Consensus, implemented into Molecular Architect (MolAr), were evaluated for their ability to analyze those interactions, considering visual inspection, redocking, and ROC curve. Ligands were refined by Parametric Method 7 (PM7), and ligands and decoys were docked into the minor DNA groove (PDB code: 1VZK). As a result, the area under the ROC curve (AUC-ROC) was 0.98, 0.88, and 0.99 for AutoDock Vina, DOCK 6, and Consensus methodologies, respectively. In addition, we proposed a machine learning model to determine the experimental ∆Tm value, which found a 0.84 R2 score. Finally, the selected ligands mono imidazole lexitropsin (42), netropsin (45), and N,N'-(1H-pyrrole-2,5-diyldi-4,1-phenylene)dibenzenecarboximidamide (51) were submitted to Molecular Dynamic Simulations (MD) through NAMD software to evaluate their equilibrium binding pose into the groove. In conclusion, the use of MolAr improves the docking results obtained with other methodologies, is a suitable methodology to use in the DNA system and was proven to be a valuable tool to estimate the ∆Tm experimental values of DNA intercalating agents.

A novel antiplasmodial compound: integration of in silico and in vitro assays.

Malaria is a disease caused by Plasmodium genus. which P. falciparum is responsible for the most severe form of the disease, cerebral malaria. In 2018, 405,000 people died of malaria. Antimalarial drugs have serious adverse effects and limited efficacy due to multidrug-resistant strains. One way to overcome these limitations is the use of computational approaches for prioritizing candidates to phenotypic assays and/or in vitro assays against validated targets. Plasmodium falciparum Enoyl-ACP reductase (PfENR) is noteworthy because it catalyzes the rate-limiting step of the biosynthetic pathway of fatty acid. Thus, the study aimed to identify potential PfENR inhibitors by ligand (2D molecular similarity and pharmacophore models) and structure-based virtual screening (molecular docking). 2D similarity-based virtual screening using Tanimoto Index (> 0.45) selected 29,236 molecules from natural products subset available in ZINC database (n = 181,603). Next, 10 pharmacophore models for PfENR inhibitors were generated and evaluated based on the internal statistical parameters from GALAHAD™ and ROC/AUC curve. These parameters selected a suitable pharmacophore model with one hydrophobic center and two hydrogen bond acceptors. The alignment of the filtered molecules on best pharmacophore model resulted in the selection of 10,977 molecules. These molecules were directed to the docking-based virtual screening by AutoDock Vina 1.1.2 program. These strategies selected one compound to phenotypic assays against parasite. ZINC630259 showed EC50 = 0.12 ± 0.018 µM in antiplasmodial assays and selective index similar to other antimalarial drugs. Finally, MM/PBSA method showed stability of molecule within PfENR binding site (ΔGbinding=-57.337 kJ/mol).Communicated by Ramaswamy H. Sarma.

Identification of novel antiplasmodial compound by hierarquical virtual screening and in vitro assays.

Malaria is an infectious disease caused by protozoa of the genus Plasmodium spp. with approximately 219 million cases in 2017. P. falciparum is main responsible for the most severe form of the disease, cerebral malaria. Despite of public health impacts, chemotherapy against malaria is still limited due to the emergence of drug resistance cases used in monotherapy and combination therapies. Thus, the development of new antimalarial drugs becomes emergency. One way of achieve this goal is to explore essential and/or unique therapeutic targets of the parasite, or at least sufficiently different to ensure selective inhibition. Enoil-ACP reductase (ENR) is a NADH-dependent enzyme responsible for the limiting step of the type II fatty acid biosynthetic pathway (FAS II). Thus, pharmacophore and docking based virtual screening were applied to prioritize molecules for in vitro assays against P. falciparum W2 strain. The application of successive filters at OOCC database (n = 618) resulted in the identification of one molecule (13) (EC50 = 0.098 ± 0.021 µM) with similar biological activity to artemether. The molecule 13 is a typical drug repurposing case due to previous other approved therapeutic uses on Chinese medicine as a non-specific cholinergic antagonist, thus it could be accelerated the drug development process. Additionally, molecular dynamics studies were used to confirm stability of the molecular interactions identified by molecular docking. Thus, representative structures of P. falciparum ENR can be used in a study to propose new derivatives for evaluation of biological activity in vitro and in vivo. Communicated by Ramaswamy H. Sarma.

Accelerating the identification of subtype selective inhibitors via Three-Dimensional Biologically Relevant Spectrum (BRS-3D): The monoamine oxidase subtypes as a case study.

Subtype-selective drugs are of great therapeutic importance as they are expected to be more effective and with less side-effects. However, discovery of subtype selective inhibitors was hampered by the high similarity of the binding sites within subfamilies. In this study, we further evaluated the applicability of "Three-Dimensional Biologically Relevant Spectrum (BRS-3D)" for the identification of subtype-selective inhibitors. A case study was performed on monoamine oxidase, which has two subtypes related to distinct diseases. The inhibitory activity against MAO-A/B of 347 compounds experimentally tested in this research was reported. Compound M124 (5H-thiazolo[3,2-a]pyrimidin-5-one) with IC50 less than 100 nM (SI = 23) was selected as a probe to investigate the structure selectivity relationship. Similarity search led to the identification of compound M229 and M249 with IC50 values of 7.4 nM, 4 nM and acceptable selectivity index over MAO-A (M229 SI > 1351, M249 SI > 2500). The molecular basis for subtype selectivity was explored through docking study and attention based DNN model. Additionally, in silico ADME properties were characterized. Accordingly, it is found that BRS-3D is a robust method for subtype selectivity in the early stage of drug discovery and the compounds reported here can be promising leads for further experimental analysis.

Reverse and structural vaccinology approach to design a highly immunogenic multi-epitope subunit vaccine against Streptococcus pneumoniae infection.

Streptococcus pneumoniae is a pathogen that resides in the upper respiratory tract of healthy individuals, maintaining a commensal relationship with its host. However, the virulent form may be the etiology of pneumonia, meningitis, bacteremia, and other respiratory tract infections. Streptococcal diseases are preventable by vaccination; but currently available vaccines have some drawbacks, especially due to the high capsule variability of streptococci strains. Thus, an effective prevention strategy continues to be the focus of extensive research. In our work, several bioinformatics tools were used to identify immunogenic peptides from a selected pool of 46 conserved proteins from Streptococcus pneumoniae. In silico analysis showed that 10 proteins had epitopes with affinity for B and T lymphocytes, which were present in at least 26 different pathogens serotypes and were considered promiscuous. The multi-epitope protein, designated HC44, was designed based on these epitopes and specific linkers to improve stability and exposure to T lymphocytes. The recombinant HC44 protein was expressed in E.coli and Swiss-Webster mice were immunised by intraperitoneal injection. Immunisation with the multi-epitope HC44 protein resulted in the production of very high levels of IgG with title superior to 1/1.200.000. However, subtype IgG was highly unbalanced toward IgG1 and no protection was afforded after challenge with S.pneumoniae in a sepsis model. Thus, our strategy has been effective in constructing a highly antigenic protein but novel immunisation strategies should be investigated to reorient the immune system toward a protective response.

Structure-Based Virtual Screening: From Classical to Artificial Intelligence.

The drug development process is a major challenge in the pharmaceutical industry since it takes a substantial amount of time and money to move through all the phases of developing of a new drug. One extensively used method to minimize the cost and time for the drug development process is computer-aided drug design (CADD). CADD allows better focusing on experiments, which can reduce the time and cost involved in researching new drugs. In this context, structure-based virtual screening (SBVS) is robust and useful and is one of the most promising in silico techniques for drug design. SBVS attempts to predict the best interaction mode between two molecules to form a stable complex, and it uses scoring functions to estimate the force of non-covalent interactions between a ligand and molecular target. Thus, scoring functions are the main reason for the success or failure of SBVS software. Many software programs are used to perform SBVS, and since they use different algorithms, it is possible to obtain different results from different software using the same input. In the last decade, a new technique of SBVS called consensus virtual screening (CVS) has been used in some studies to increase the accuracy of SBVS and to reduce the false positives obtained in these experiments. An indispensable condition to be able to utilize SBVS is the availability of a 3D structure of the target protein. Some virtual databases, such as the Protein Data Bank, have been created to store the 3D structures of molecules. However, sometimes it is not possible to experimentally obtain the 3D structure. In this situation, the homology modeling methodology allows the prediction of the 3D structure of a protein from its amino acid sequence. This review presents an overview of the challenges involved in the use of CADD to perform SBVS, the areas where CADD tools support SBVS, a comparison between the most commonly used tools, and the techniques currently used in an attempt to reduce the time and cost in the drug development process. Finally, the final considerations demonstrate the importance of using SBVS in the drug development process.

Identification of a Potential Zika Virus Inhibitor Targeting NS5 Methyltransferase Using Virtual Screening and Molecular Dynamics Simulations.

The NS5 methyltransferase (MTase) has been reported as an attractive molecular target for antivirals discovery against the Zika virus (ZIKV). Here, we report structure-based virtual screening of 42 390 structures from the Development Therapeutics Program (DTP) AIDS Antiviral Screen Database. Among the docked compounds, ZINC1652386 stood out due to its high affinity for MTase in comparison to the cocrystallized ligand MS2042, which interacts with the Asp146 residue in the MTase binding site by hydrogen bonding. Subsequent molecular dynamics simulations predicted that this compound forms a stable complex with MTase within 50 ns. Thus, ZINC1652386 may represent a promising ZIKV methyltransferase inhibitor.

Brazilian malaria molecular targets (BraMMT): selected receptors for virtual high-throughput screening experiments.

BACKGROUND: Owing to increased spending on pharmaceuticals since 2010, discussions about rising costs for the development of new medical technologies have been focused on the pharmaceutical industry. Computational techniques have been developed to reduce costs associated with new drug development. Among these techniques, virtual high-throughput screening (vHTS) can contribute to the drug discovery process by providing tools to search for new drugs with the ability to bind a specific molecular target. OBJECTIVES: In this context, Brazilian malaria molecular targets (BraMMT) was generated to execute vHTS experiments on selected molecular targets of Plasmodium falciparum. METHODS: In this study, 35 molecular targets of P. falciparum were built and evaluated against known antimalarial compounds. FINDINGS: As a result, it could predict the correct molecular target of market drugs, such as artemisinin. In addition, our findings suggested a new pharmacological mechanism for quinine, which includes inhibition of falcipain-II and a potential new antimalarial candidate, clioquinol. MAIN CONCLUSIONS: The BraMMT is available to perform vHTS experiments using OCTOPUS or Raccoon software to improve the search for new antimalarial compounds. It can be retrieved from www.drugdiscovery.com.br or download of Supplementary data.

Brazilian malaria molecular targets (BraMMT): selected receptors for virtual high-throughput screening experiments

BACKGROUND Owing to increased spending on pharmaceuticals since 2010, discussions about rising costs for the development of new medical technologies have been focused on the pharmaceutical industry. Computational techniques have been developed to reduce costs associated with new drug development. Among these techniques, virtual high-throughput screening (vHTS) can contribute to the drug discovery process by providing tools to search for new drugs with the ability to bind a specific molecular target. OBJECTIVES In this context, Brazilian malaria molecular targets (BraMMT) was generated to execute vHTS experiments on selected molecular targets of Plasmodium falciparum. METHODS In this study, 35 molecular targets of P. falciparum were built and evaluated against known antimalarial compounds. FINDINGS As a result, it could predict the correct molecular target of market drugs, such as artemisinin. In addition, our findings suggested a new pharmacological mechanism for quinine, which includes inhibition of falcipain-II and a potential new antimalarial candidate, clioquinol. MAIN CONCLUSIONS The BraMMT is available to perform vHTS experiments using OCTOPUS or Raccoon software to improve the search for new antimalarial compounds. It can be retrieved from www.drugdiscovery.com.br or download of Supplementary data.

Methyl Chavicol and Its Synthetic Analogue as Possible Antioxidant and Antilipase Agents Based on the In Vitro and In Silico Assays.

This study investigated the in vitro and in silico biological properties of the methyl chavicol (MC) and its analogue 2-[(4-methoxyphenyl)methyl]oxirane (MPMO), emphasizing the antioxidant and antilipase effects. MPMO was synthesized from MC that reacted with meta-chloroperbenzoic acid and, after separation and purification, was identified by 1H and 13C NMR and GC-MS. The antioxidant activity was investigated by DPPH, cooxidation ß-carotene/linoleic acid, and thiobarbituric acid assays. With the use of colorimetric determination, the antilipase effect on the pancreatic lipase was tested, while the molecular interaction profiles were evaluated by docking molecular study. MC (IC50 = 312.50 ± 2.28 µg/mL) and MPMO (IC50 = 8.29 ± 0.80 µg/mL) inhibited the DPPH free radical. The inhibition of lipid peroxidation (%) was 73.08 ± 4.79 and 36.16 ± 4.11 to MC and MPMO, respectively. The malonaldehyde content was significantly reduced in the presence of MC and MPMO. MC and MPMO inhibited the pancreatic lipase in 58.12 and 26.93%, respectively. MC and MPMO (-6.1 kcal·mol-1) produced a binding affinity value lower than did diundecylphosphatidylcholine (-5.6 kcal·mol-1). These findings show that MC and MPMO present antioxidant and antilipase activities, which may be promising molecular targets for the treatment of diseases associated with oxidative damage and lipid metabolism.

Pharmacophoric characteristics of dengue virus NS2B/NS3pro inhibitors: a systematic review of the most promising compounds.

Dengue virus (DENV) infection can lead to a wide range of clinical manifestations, including fatal hemorrhagic complications. There is a need to find effective pharmacotherapies to treat this disease due to the lack of specific immunotherapies and antiviral drugs. That said, the DENV NS2B/NS3pro protease complex is essential in both the viral multiplication cycle and in disease pathogenesis, and is considered a promising target for new antiviral therapies. Here, we performed a systematic review to evaluate the pharmacophoric characteristics of promising compounds against NS2B/NS3pro reported in the past 10 years. Online searches in the PUBMED/MEDLINE and SCOPUS databases resulted in 165 articles. Eight studies, which evaluated 3,384,268 molecules exhibiting protease inhibition activity, were included in this review. These studies evaluated anti-dengue activity in vitro and the IC50 and EC50 values were provided. Most compounds exhibited non-competitive inhibition. Cytotoxicity was evaluated in BHK-21, Vero, and LLC-MK2 cells, and the CC50 values obtained ranged from < 1.0 to 780.5 µM. Several groups were associated with biological activity against dengue, including nitro, catechol, halogen and ammonium quaternaries. Thus, these groups seem to be potential pharmacophores that can be further investigated to treat dengue infections.

Synthesis, SAR, and Docking Studies Disclose 2-Arylfuran-1,4-naphthoquinones as In Vitro Antiplasmodial Hits.

A total of 28 lapachol-related naphthoquinones with four different scaffolds were synthesized and spectroscopically characterized. In vitro antiplasmodial activity was assayed against the chloroquine-resistant Plasmodium falciparum W2 strain by the parasite lactate dehydrogenase (pLDH) method. Cytotoxicity against Hep G2A16 cell was determined by the MTT assay. All compounds disclosed higher in vitro antiplasmodial activity than lapachol. Ortho- and para-naphthoquinones with a furan ring fused to the quinonoid moiety were more potent than 2-hydroxy-3-(1'-alkenyl)-1,4-naphthoquinones, while ortho-furanonaphthoquinones were more cytotoxic. Molecular docking to Plasmodium targets Pfcyt bc1 complex and PfDHOD enzyme showed that five out of the 28 naphthoquinones disclosed favorable binding energies. Furanonaphthoquinones endowed with an aryl moiety linked to the furan ring are highlighted as new in vitro antiplasmodial lead compounds and warrant further investigation.

Octopus: a platform for the virtual high-throughput screening of a pool of compounds against a set of molecular targets.

Octopus is an automated workflow management tool that is scalable for virtual high-throughput screening (vHTS). It integrates MOPAC2016, MGLTools, PyMOL, and AutoDock Vina. In contrast to other platforms, Octopus can perform docking simulations of an unlimited number of compounds into a set of molecular targets. After generating the ligands in a drawing package in the Protein Data Bank (PDB) format, Octopus can carry out geometry refinement using the semi-empirical method PM7 implemented in MOPAC2016. Docking simulations can be performed using AutoDock Vina and can utilize the Our Own Molecular Targets (OOMT) databank. Finally, the proposed software compiles the best binding energies into a standard table. Here, we describe two successful case studies that were verified by biological assay. In the first case study, the vHTS process was carried out for 22 (phenylamino)urea derivatives. The vHTS process identified a metalloprotease with the PDB code 1GKC as a molecular target for derivative LE&007. In a biological assay, compound LE&007 was found to inhibit 80% of the activity of this enzyme. In the second case study, compound Tx001 was submitted to the Octopus routine, and the results suggested that Plasmodium falciparum ATP6 (PfATP6) as a molecular target for this compound. Following an antimalarial assay, Tx001 was found to have an inhibitory concentration (IC50) of 8.2 µM against PfATP6. These successful examples illustrate the utility of this software for finding appropriate molecular targets for compounds. Hits can then be identified and optimized as new antineoplastic and antimalarial drugs. Finally, Octopus has a friendly Linux-based user interface, and is available at www.drugdiscovery.com.br . Graphical Abstract Octopus: A platform for inverse virtual screening (IVS) to search new molecular targets for drugs.

Caffeoylquinic acids from antiplasmodial active extract of Xanthium cavanillesii fruits and their molecular modelling studies.

The antiplasmodial active extract of Xanthium cavanillesii contains 3,4-dicaffeoyl quinic acid (3,4-DCQA), 3,5-dicaffeoyl quinic acid (3,5-DCQA) and 1,3,5-tricaffeoyl quinic acid (1,3,5-TCQA). These results inspired us to investigate the interaction of these molecules with a promising validated target of Plasmodium, PfATP6 orthologue of mammalian Ca+2-ATPase. Models of this receptor were obtained through comparative modelling. Afterwards, molecular docking studies were used to identify possible interaction modes of these caffeoyl quinic derivatives on the binding site. The 1,3,5-TCQA had the best energy, but all of these had better energy than thapsigargin, a non-competitive inhibitor of the sarco/endoplasmatic reticulum Ca+2-ATPase (SERCA).

Successful application of virtual screening and molecular dynamics simulations against antimalarial molecular targets.

The main challenge in the control of malaria has been the emergence of drug-resistant parasites. The presence of drug-resistant Plasmodium sp. has raised the need for new antimalarial drugs. Molecular modelling techniques have been used as tools to develop new drugs. In this study, we employed virtual screening of a pyrazol derivative (Tx001) against four malaria targets: plasmepsin-IV, plasmepsin-II, falcipain-II, and PfATP6. The receiver operating characteristic curves and area under the curve (AUC) were established for each molecular target. The AUC values obtained for plasmepsin-IV, plasmepsin-II, and falcipain-II were 0.64, 0.92, and 0.94, respectively. All docking simulations were carried out using AutoDock Vina software. The ligand Tx001 exhibited a better interaction with PfATP6 than with the reference compound (-12.2 versus -6.8 Kcal/mol). The Tx001-PfATP6 complex was submitted to molecular dynamics simulations in vacuum implemented on an NAMD program. The ligand Tx001 docked at the same binding site as thapsigargin, which is a natural inhibitor of PfATP6. Compound TX001 was evaluated in vitro with a P. falciparum strain (W2) and a human cell line (WI-26VA4). Tx001 was discovered to be active against P. falciparum (IC50 = 8.2 µM) and inactive against WI-26VA4 (IC50 > 200 µM). Further ligand optimisation cycles generated new prospects for docking and biological assays.

Successful application of virtual screening and molecular dynamics simulations against antimalarial molecular targets

The main challenge in the control of malaria has been the emergence of drug-resistant parasites. The presence of drug-resistant Plasmodium sp. has raised the need for new antimalarial drugs. Molecular modelling techniques have been used as tools to develop new drugs. In this study, we employed virtual screening of a pyrazol derivative (Tx001) against four malaria targets: plasmepsin-IV, plasmepsin-II, falcipain-II, and PfATP6. The receiver operating characteristic curves and area under the curve (AUC) were established for each molecular target. The AUC values obtained for plasmepsin-IV, plasmepsin-II, and falcipain-II were 0.64, 0.92, and 0.94, respectively. All docking simulations were carried out using AutoDock Vina software. The ligand Tx001 exhibited a better interaction with PfATP6 than with the reference compound (-12.2 versus -6.8 Kcal/mol). The Tx001-PfATP6 complex was submitted to molecular dynamics simulations in vacuum implemented on an NAMD program. The ligand Tx001 docked at the same binding site as thapsigargin, which is a natural inhibitor of PfATP6. Compound TX001 was evaluated in vitro with a P. falciparum strain (W2) and a human cell line (WI-26VA4). Tx001 was discovered to be active against P. falciparum (IC50 = 8.2 µM) and inactive against WI-26VA4 (IC50 > 200 µM). Further ligand optimisation cycles generated new prospects for docking and biological assays.