Understanding the Pyrimethamine Drug Resistance Mechanism via Combined Molecular Dynamics and Dynamic Residue Network Analysis

Computational Methodologies in Synthesis, Preparation and Application of Antimicrobial Polymers, Biomolecules, and Nanocomposites

The design and optimization of antimicrobial materials (polymers, biomolecules, or nanocomposites) can be significantly advanced by computational methodologies like molecular dynamics (MD), which provide insights into the interactions and stability of the antimicrobial agents within the polymer matrix, and machine learning (ML) or design of experiment (DOE), which predicts and optimizes antimicrobial efficacy and material properties. These innovations not only enhance the efficiency of developing antimicrobial polymers but also enable the creation of materials with tailored properties to meet specific application needs, ensuring safety and longevity in their usage. Therefore, this paper will present the computational methodologies employed in the synthesis and application of antimicrobial polymers, biomolecules, and nanocomposites. By leveraging advanced computational techniques such as MD, ML, or DOE, significant advancements in the design and optimization of antimicrobial materials are achieved. A comprehensive review on recent progress, together with highlights of the most relevant methodologies' contributions to state-of-the-art materials science will be discussed, as well as future directions in the field will be foreseen. Finally, future possibilities and opportunities will be derived from the current state-of-the-art methodologies, providing perspectives on the potential evolution of polymer science and engineering of novel materials.

Antiplasmodial action of 4-nitrobenzenesulfonamide chalcones: Design, synthesis, characterisation, in vitro and in silico evaluation against blood stages of Plasmodium falciparum 3D7

Malaria is an intracellular protozoan parasitic disease caused by Plasmodium species with significant morbidity and mortality in endemic regions. The complex lifecycle of the parasite and the emergence of drug-resistant Plasmodium falciparum have hampered the efficacy of current anti-malarial agents. To circumvent this situation, the present study attempts to demonstrate the blood-stage anti-plasmodial action of 26 hybrid compounds containing the three privileged bioactive scaffolds (sulfonamide, chalcone, and nitro group) with synergistic and multitarget action. These three parent scaffolds exhibit divergent activities, such as antibacterial, anti-malarial, anti-fungal, anti-inflammatory, and anticancer. All the synthesised compounds were characterised using various spectroscopic techniques. The in vitro blood-stage inhibitory activity of 26 hybrid compounds was evaluated against mixed-stage culture (asynchronize) of human malarial parasite P. falciparum, Pf 3D7 at different concentrations ranging from 25.0 µg/mL to 0.78 µg/mL using SYBR 1 green assay, with IC50 values determined after 48 h of treatment based on the drug-response curves. Two potent compounds (11 and 10), with 2-Br and 2,6-diCl substitutions, showed pronounced activity with IC50 values of 5.4 µg/mL and 5.6 µg/mL, whereas others displayed varied activity with IC50 values ranging from 7.0 µg/mL to 22.0 µg/mL. Both 11 and 10 showed greater susceptibility towards mature-stage trophozoites than ring-stage parasites. The hemolytic and in vitro cytotoxicity assays revealed that compounds 11 and 10 did not cause any toxic effects on host red blood cells (uninfected), human-derived Mo7e cells, and murine-derived BA/F3 cells. The in vitro observations are consistent with the in silico studies using P. falciparum-dihydrofolate reductase, where 11 and 10 showed a binding affinity of -10.4 Kcal/mol. This is the first report of the hybrid scaffold, 4-nitrobenzenesulfonamide chalcones, demonstrating its potential as an anti-plasmodial agent.

Antileishmanial natural products as potential inhibitors of the Leishmania pteridine reductase: insights from molecular docking and molecular dynamics simulations

Although many natural product-derived compounds possess anti-leishmanial activities in vitro and in vivo, their molecular targets in the Leishmania parasite remain elusive. This is a major challenge in optimizing these compounds into leads. The Leishmania pteridine reductase (PTR1) is peculiar for folate and pterin metabolism and has been validated as a drug target. In this study, 17 compounds with anti-leishmanial activities were screened against Leishmania major PTR1 (LmPTR1) using molecular docking and molecular dynamics (MD) simulations. All ligands were bound in the active site pocket of LmPTR1 with binding affinities ranging from -11.2 to -5.2 kcal/mol. Agnuside, betulin, betulinic acid, gerberinol, ismailin, oleanolic acid, pristimerin, and ursolic acid demonstrated binding affinities similar to a known inhibitor, methyl 1-(4-{[2,4-diaminopteridin-6-yl) methyl] amino} benzoyl) piperidine-4-carboxylate (DVP). MD simulations revealed that betulin, betulinic acid, ismailin, oleanolic acid, pristimerin, and ursolic acid formed stable complexes with LmPTR1. The binding free energies of the complexes were very good (-87 to -148 kJ/mol), and much higher than the complex of the standard DVP inhibitor and LmPTR1 (-27 kJ/mol). Betulin, betulinic acid, ismailin, oleanolic acid, pristimerin, and ursolic acid likely exert their antileishmanial action by inhibiting PTR1 and could thus be used as a basis for the development of potential antileishmanial chemotherapeutic agents.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00247-8.

Oplodiol and nitidine as potential inhibitors of Plasmodium falciparum dihydrofolate reductase: insights from a computational study

Many natural products have been shown to possess antiplasmodial activities, but their protein targets are unknown. This work employed molecular docking and molecular dynamics simulations to explore the inhibitory activity of some antiplasmodial natural products against wild-type and mutant strains of Plasmodium falciparum dihydrofolate reductase (PfDHFR). From the molecular docking study, 6 ligands preferentially bind at the active site of the DHFR domain with binding energies ranging from -6.4 to -9.5 kcal/mol. Interactions of compounds with MET55 and PHE58 were mostly observed in the molecular docking study. From the molecular dynamics study, the binding of 2 of the ligands-nitidine and oplodiol-was observed to be stable against all tested strains of PfDHFR. The average binding free energy of oplodiol in complex with the various PfDHFR strains was -93.701 kJ/mol whereas that of nitidine was -106.206 kJ/mol. The impressive in silico activities of the 2 compounds suggest they could be considered for development as potential antifolate agents.Communicated by Ramaswamy H. Sarma.

The Amaryllidaceae alkaloid, montanine, is a potential inhibitor of the Trypanosoma cruzi trans-sialidase enzyme

Trypanosoma cruzi is the parasite that causes the chronic malady known as Chagas disease (CD). Only nifurtimox and benznidazole are currently approved to treat CD in acute and chronic phases. To minimize the danger of disease transmission and as a therapy, new compounds that are safer and more effective are required. It has been demonstrated that Amaryllidaceae plants suppress the growth of T. cruzi - the causative agent of CD. However, little research has been done on their potential protein targets in the parasite. In this study, an in-silico approach was used to investigate the interactions of the Amaryllidaceae alkaloids with trans-sialidase, a confirmed protein target of T. cruzi. The nature and efficiency of the main binding modes of the alkaloids were investigated by molecular docking. Trans-sialidase active site residues were bound by the alkaloids with binding energies varying from -8.9 to -6.9 kcal/mol. From the molecular docking investigation, all the alkaloids had strong interactions with the crucial amino acid residues (Glu230, Tyr342, and Asp59) required for trans-sialidase catalysis. Montanine was the most stable compound throughout the molecular dynamics simulation and had a favorable docking binding energy (-8.9 kcal/mol). The binding free energy (MM-GBSA) of the montanine complex was -14.6 kcal/mol. The pharmacokinetic properties investigated demonstrated that all the evaluated compounds exhibit suitable oral administration requirements. Overall, this in silico study suggests that the Amaryllidaceae alkaloids could potentially act as inhibitors of trans-sialidase.Communicated by Ramaswamy H. Sarma.

Roles of Virtual Screening and Molecular Dynamics Simulations in Discovering and Understanding Antimalarial Drugs

Malaria continues to be a global health threat, with approximately 247 million cases worldwide. Despite therapeutic interventions being available, patient compliance is a problem due to the length of treatment. Moreover, drug-resistant strains have emerged over the years, necessitating urgent identification of novel and more potent treatments. Given that traditional drug discovery often requires a great deal of time and resources, most drug discovery efforts now use computational methods. In silico techniques such as quantitative structure-activity relationship (QSAR), docking, and molecular dynamics (MD) can be used to study protein-ligand interactions and determine the potency and safety profile of a set of candidate compounds to help prioritize those tested using assays and animal models. This paper provides an overview of antimalarial drug discovery and the application of computational methods in identifying candidate inhibitors and elucidating their potential mechanisms of action. We conclude with the continued challenges and future perspectives in the field of antimalarial drug discovery.

Identification of Active Compounds against Melanoma Growth by Virtual Screening for Non-Classical Human DHFR Inhibitors

Antifolates such as methotrexate (MTX) have been largely known as anticancer agents because of their role in blocking nucleic acid synthesis and cell proliferation. Their mechanism of action lies in their ability to inhibit enzymes involved in the folic acid cycle, especially human dihydrofolate reductase (hDHFR). However, most of them have a classical structure that has proven ineffective against melanoma, and, therefore, inhibitors with a non-classical lipophilic structure are increasingly becoming an attractive alternative to circumvent this clinical resistance. In this study, we conducted a protocol combining virtual screening (VS) and cell-based assays to identify new potential non-classical hDHFR inhibitors. Among 173 hit compounds identified (average logP = 3.68; average MW = 378.34 Da), two-herein, called C1 and C2-exhibited activity against melanoma cell lines B16 and A375 by MTT and Trypan-Blue assays. C1 showed cell growth arrest (39% and 56%) and C2 showed potent cytotoxic activity (77% and 51%) in a dose-dependent manner. The effects of C2 on A375 cell viability were greater than MTX (98% vs 60%) at equivalent concentrations and times. Our results indicate that the integrated in silico/in vitro approach provided a benchmark to identify novel promising non-classical DHFR inhibitors showing activity against melanoma cells.

Application of Computational Biology and Artificial Intelligence in Drug Design

Traditional drug design requires a great amount of research time and developmental expense. Booming computational approaches, including computational biology, computer-aided drug design, and artificial intelligence, have the potential to expedite the efficiency of drug discovery by minimizing the time and financial cost. In recent years, computational approaches are being widely used to improve the efficacy and effectiveness of drug discovery and pipeline, leading to the approval of plenty of new drugs for marketing. The present review emphasizes on the applications of these indispensable computational approaches in aiding target identification, lead discovery, and lead optimization. Some challenges of using these approaches for drug design are also discussed. Moreover, we propose a methodology for integrating various computational techniques into new drug discovery and design.

Preliminary Structure-Activity Relationship Study of the MMV Pathogen Box Compound MMV675968 (2,4-Diaminoquinazoline) Unveils Novel Inhibitors of Trypanosoma brucei brucei

New drugs are urgently needed for the treatment of human African trypanosomiasis (HAT). In line with our quest for novel inhibitors of trypanosomes, a small library of analogs of the antitrypanosomal hit (MMV675968) available at MMV as solid materials was screened for antitrypanosomal activity. In silico exploration of two potent antitrypanosomal structural analogs (7-MMV1578647 and 10-MMV1578445) as inhibitors of dihydrofolate reductase (DHFR) was achieved, together with elucidation of other antitrypanosomal modes of action. In addition, they were assessed in vitro for tentative inhibition of DHFR in a crude trypanosome extract. Their ADMET properties were also predicted using dedicated software. Overall, the two diaminoquinazoline analogs displayed approximately 40-fold and 60-fold more potency and selectivity in vitro than the parent hit, respectively (MMV1578445 (10): IC₅₀ = 0.045 µM, SI = 1737; MMV1578467 (7): IC₅₀ = 0.06 µM; SI = 412). Analogs 7 and 10 were also strong binders of the DHFR enzyme in silico, in all their accessible protonation states, and interacted with key DHFR ligand recognition residues Val32, Asp54, and Ile160. They also exhibited significant activity against trypanosome protein isolate. MMV1578445 (10) portrayed fast and irreversible trypanosome growth arrest between 4–72 h at IC₉₉. Analogs 7 and 10 induced in vitro ferric iron reduction and DNA fragmentation or apoptosis induction, respectively. The two potent analogs endowed with predicted suitable physicochemical and ADMET properties are good candidates for further deciphering their potential as starting points for new drug development for HAT.

Evaluating the accuracy of the AMBER protein force fields in modeling dihydrofolate reductase structures: misbalance in the conformational arrangements of the flexible loop domains

Protein flexible loop regions were once thought to be simple linkers between other more functional secondary structural elements. However, as it becomes clearer that these loop domains are critical players in a plethora of biological processes, accurate conformational sampling of 3D loop structures is vital to the advancement of drug design techniques and the overall growth of knowledge surrounding molecular systems. While experimental techniques provide a wealth of structural information, the resolution of flexible loop domains is sometimes low or entirely absent due to their complex and dynamic nature. This highlights an opportunity for de novo structure prediction using in silico methods with molecular dynamics (MDs). This study evaluates some of the AMBER protein force field's (ffs) ability to accurately model dihydrofolate reductase (DHFR) conformations, a protein complex characterized by specific arrangements and interactions of multiple flexible loops whose conformations are determined by the presence or absence of bound ligands and cofactors. Although the AMBER ffs, including ff19SB, studied well model most protein structures with rich secondary structure, results obtained here suggest the inability to significantly sample the expected DHFR loop-loop conformations - of the six distinct protein-ligand systems simulated, a majority lacked consistent stabilization of experimentally derived metrics definitive the three enzyme conformations. Although under-sampling and the chosen ff parameter combinations could be the cause, given past successes with these MD approaches for many protein systems, this suggests a potential misbalance in available ff parameters required to accurately predict the structure of multiple flexible loop regions present in proteins.Communicated by Ramaswamy H. Sarma.

Allosteric Modulation of the Main Protease (MPro) of SARS-CoV-2 by Casticin—Insights from Molecular Dynamics Simulations

Inhibition of the main protease (M^pro) of SARS-CoV-2 has been suggested to be vital in shutting down viral replication in a host. Most efforts aimed at inhibiting M^Pro activity have been channeled into competitive inhibition at the active site, but this strategy will require a high inhibitor concentration and impressive inhibitor-M^Pro binding affinity. Allosteric inhibition can potentially serve as an effective strategy for alleviating these limitations. In this study, the ability of antiviral natural products to inhibit M^Pro in an allosteric fashion was explored with in silico techniques. Molecular docking revealed a strong interaction between casticin, an antiviral flavonoid, and M^pro at a site distant from the active site. This site, characterized as a distal site, has been shown to have an interdependent dynamic effect with the active site region. M^pro only, M^pro-peptide (binary) and M^pro-peptide-casticin (ternary) complexes were subjected to molecular dynamics simulations for 50 ns to investigate the modulatory activity of casticin binding on M^pro. Molecular dynamic simulations revealed that binding of casticin at the distal site interferes with the proper orientation of the peptide substrate in the oxyanion hole of the active site, and this could lead to a halt or decrease in catalytic activity. This study therefore highlights casticin as a potential allosteric modulator of the SARS-CoV-2 main protease, which could be optimized and developed into a potential lead compound for anti-SARS-CoV-2 chemotherapy.

An In Silico Study of the Interactions of Alkaloids from Cryptolepis sanguinolenta with Plasmodium falciparum Dihydrofolate Reductase and Dihydroorotate Dehydrogenase

The Plasmodium falciparum dihydrofolate reductase (PfDHFR) and dihydroorotate dehydrogenase (PfDHODH) are essential for Plasmodium falciparum growth and development, and have been validated as targets for the development of new antimalarial agents. Several alkaloids isolated from Cryptolepis sanguinolenta have been reported to have antiplasmodial activity, but their protein targets are unknown. Therefore, molecular docking and molecular dynamics simulations were used to investigate the interactions and stability of the alkaloids with PfDHFR and PfDHODH. Based on physicochemical characteristics, alkaloids were grouped as sterically bulky (sb) or planar (pg). Docking results revealed strong binding affinities (−6.0 to −13.4 kcal/mol) of the alkaloids against PfDHODH and various strains of PfDHFR while interacting with key residues such as Asp54 and Phe58 in PfDHFR. The pg alkaloids had high binding affinity and preference for the inhibitor binding domain over the flavin mononucleotide (FMN) binding domain in PfDHODH due to size considerations. From the molecular dynamics trajectories, protein-alkaloid complexes were stable throughout the simulation, with supporting evidence from root mean square deviations, root mean square fluctuations, radius of gyration, free binding energies, and other parameters. We report herein that biscryptolepine and cryptomisrine (sb class), as well as cryptolepinone, cryptoheptine, cryptolepine, and neocryptolepine (pg class), are capable of inhibiting PfDHFR effectively in pyrimethamine sensitive and resistant cells. Also, our results show that alkaloids of the pg class can inhibit PfDHODH as FMN decoys, as well as direct enzyme inhibitors, thereby halting crucial protein function.

Deciphering Isoniazid Drug Resistance Mechanisms on Dimeric Mycobacterium tuberculosis KatG via Post-molecular Dynamics Analyses Including Combined Dynamic Residue Network Metrics

Resistance mutations in Mycobacterium tuberculosis (Mtb) catalase peroxidase protein (KatG), an essential enzyme in isoniazid (INH) activation, reduce the sensitivity of Mtb to first-line drugs, hence presenting challenges in tuberculosis (TB) management. Thus, understanding the mutational imposed resistance mechanisms remains of utmost importance in the quest to reduce the TB burden. Herein, effects of 11 high confidence mutations in the KatG structure and residue network communication patterns were determined using extensive computational approaches. Combined traditional post-molecular dynamics analysis and comparative essential dynamics revealed that the mutant proteins have significant loop flexibility around the heme binding pocket and enhanced asymmetric protomer behavior with respect to wild-type (WT) protein. Heme contact analysis between WT and mutant proteins identified a reduction to no contact between heme and residue His270, a covalent bond vital for the heme-enabled KatG catalytic activity. Betweenness centrality calculations showed large hub ensembles with new hubs especially around the binding cavity and expanded to the dimerization domain via interface in the mutant systems, providing possible compensatory allosteric communication paths for the active site as a result of the mutations which may destabilize the heme binding pocket and the loops in its vicinity. Additionally, an interesting observation came from Eigencentrality hubs, most of which are located in the C-terminal domain, indicating relevance of the domain in the protease functionality. Overall, our results provide insight toward the mechanisms involved in KatG-INH resistance in addition to identifying key regions in the enzyme functionality, which can be used for future drug design.

Dissecting mutational allosteric effects in alkaline phosphatases associated with different Hypophosphatasia phenotypes: An integrative computational investigation

Hypophosphatasia (HPP) is a rare inherited disorder characterized by defective bone mineralization and is highly variable in its clinical phenotype. The disease occurs due to various loss-of-function mutations in ALPL, the gene encoding tissue-nonspecific alkaline phosphatase (TNSALP). In this work, a data-driven and biophysics-based approach is proposed for the large-scale analysis of ALPL mutations-from nonpathogenic to severe HPPs. By using a pipeline of synergistic approaches including sequence-structure analysis, network modeling, elastic network models and atomistic simulations, we characterized allosteric signatures and effects of the ALPL mutations on protein dynamics and function. Statistical analysis of molecular features computed for the ALPL mutations showed a significant difference between the control, mild and severe HPP phenotypes. Molecular dynamics simulations coupled with protein structure network analysis were employed to analyze the effect of single-residue variation on conformational dynamics of TNSALP dimers, and the developed machine learning model suggested that the topological network parameters could serve as a robust indicator of severe mutations. The results indicated that the severity of disease-associated mutations is often linked with mutation-induced modulation of allosteric communications in the protein. This study suggested that ALPL mutations associated with mild and more severe HPPs can exert markedly distinct effects on the protein stability and long-range network communications. By linking the disease phenotypes with dynamic and allosteric molecular signatures, the proposed integrative computational approach enabled to characterize and quantify the allosteric effects of ALPL mutations and role of allostery in the pathogenesis of HPPs.

The Structural Basis of Mycobacterium tuberculosis RpoB Drug-Resistant Clinical Mutations on Rifampicin Drug Binding

Tuberculosis (TB), caused by the Mycobacterium tuberculosis infection, continues to be a leading cause of morbidity and mortality in developing countries. Resistance to the first-line anti-TB drugs, isoniazid (INH) and rifampicin (RIF), is a major drawback to effective TB treatment. Genetic mutations in the β-subunit of the DNA-directed RNA polymerase (rpoB) are reported to be a major reason of RIF resistance. However, the structural basis and mechanisms of these resistant mutations are insufficiently understood. In the present study, thirty drug-resistant mutants of rpoB were initially modeled and screened against RIF via a comparative molecular docking analysis with the wild-type (WT) model. These analyses prioritized six mutants (Asp441Val, Ser456Trp, Ser456Gln, Arg454Gln, His451Gly, and His451Pro) that showed adverse binding affinities, molecular interactions, and RIF binding hinderance properties, with respect to the WT. These mutant models were subsequently analyzed by molecular dynamics (MD) simulations. One-hundred nanosecond all-atom MD simulations, binding free energy calculations, and a dynamic residue network analysis (DRN) were employed to exhaustively assess the impact of mutations on RIF binding dynamics. Considering the global structural motions and protein-ligand binding affinities, the Asp441Val, Ser456Gln, and His454Pro mutations generally yielded detrimental effects on RIF binding. Locally, we found that the electrostatic contributions to binding, particularly by Arg454 and Glu487, might be adjusted to counteract resistance. The DRN analysis revealed that all mutations mostly distorted the communication values of the critical hubs and may, therefore, confer conformational changes in rpoB to perturb RIF binding. In principle, the approach combined fundamental molecular modeling tools for robust "global" and "local" level analyses of structural dynamics, making it well suited for investigating other similar drug resistance cases.

Slipknot or Crystallographic Error: A Computational Analysis of the Plasmodium falciparum DHFR Structural Folds

The presence of protein structures with atypical folds in the Protein Data Bank (PDB) is rare and may result from naturally occurring knots or crystallographic errors. Proper characterisation of such folds is imperative to understanding the basis of naturally existing knots and correcting crystallographic errors. If left uncorrected, such errors can frustrate downstream experiments that depend on the structures containing them. An atypical fold has been identified in P. falciparum dihydrofolate reductase (PfDHFR) between residues 20–51 (loop 1) and residues 191–205 (loop 2). This enzyme is key to drug discovery efforts in the parasite, necessitating a thorough characterisation of these folds. Using multiple sequence alignments (MSA), a unique insert was identified in loop 1 that exacerbates the appearance of the atypical fold-giving it a slipknot-like topology. However, PfDHFR has not been deposited in the knotted proteins database, and processing its structure failed to identify any knots within its folds. The application of protein homology modelling and molecular dynamics simulations on the DHFR domain of P. falciparum and those of two other organisms (E. coli and M. tuberculosis) that were used as molecular replacement templates in solving the PfDHFR structure revealed plausible unentangled or open conformations of these loops. These results will serve as guides for crystallographic experiments to provide further insights into the atypical folds identified.

Novel dynamic residue network analysis approaches to study allosteric modulation: SARS-CoV-2 Mpro and its evolutionary mutations as a case study

The rational search for allosteric modulators and the allosteric mechanisms of these modulators in the presence of mutations is a relatively unexplored field. Here, we established novel in silico approaches and applied them to SARS-CoV-2 main protease (Mpro) as a case study. First, we identified six potential allosteric modulators. Then, we focused on understanding the allosteric effects of these modulators on each of its protomers. We introduced a new combinatorial approach and dynamic residue network (DRN) analysis algorithms to examine patterns of change and conservation of critical nodes, according to five independent criteria of network centrality. We observed highly conserved network hubs for each averaged DRN metric on the basis of their existence in both protomers in the absence and presence of all ligands (persistent hubs). We also detected ligand specific signal changes. Using eigencentrality (EC) persistent hubs and ligand introduced hubs we identified a residue communication path connecting the allosteric binding site to the catalytic site. Finally, we examined the effects of the mutations on the behavior of the protein in the presence of selected potential allosteric modulators and investigated the ligand stability. One crucial outcome was to show that EC centrality hubs form an allosteric communication path between the allosteric ligand binding site to the active site going through the interface residues of domains I and II; and this path was either weakened or lost in the presence of some of the mutations. Overall, the results revealed crucial aspects that need to be considered in rational computational drug discovery.

Allosteric pockets and dynamic residue network hubs of falcipain 2 in mutations including those linked to artemisinin resistance

Continually emerging resistant strains of malarial parasites to current drugs present challenges. Understanding the underlying resistance mechanisms, especially those linked to allostery is, thus, highly crucial for drug design. This forms the main concern of the paper through a case study of falcipain 2 (FP-2) and its mutations, some of which are linked to artemisinin (ART) drug resistance. Here, we applied a variety of in silico approaches and tools that we developed recently, together with existing computational tools. This included novel essential dynamics and dynamic residue network (DRN) analysis algorithms. We identified six pockets demonstrating dynamic differences in the presence of some mutations. We observed striking allosteric effects in two mutant proteins. In the presence of M245I, a cryptic pocket was detected via a unique mechanism in which Pocket 2 fused with Pocket 6. In the presence of the A353T mutation, which is located at Pocket 2, the pocket became the most rigid among all protein systems analyzed. Pocket 6 was also highly stable in all cases, except in the presence of M245I mutation. The effect of ART linked mutations was more subtle, and the changes were at residue level. Importantly, we identified an allosteric communication path formed by four unique averaged BC hubs going from the mutated residue to the catalytic site and passing through the interface of three identified pockets. Collectively, we established and demonstrated that we have robust tools and a pipeline that can be applicable to the analysis of mutations.

MDM-TASK-web: MD-TASK and MODE-TASK web server for analyzing protein dynamics

The web server, MDM-TASK-web, combines the MD-TASK and MODE-TASK software suites, which are aimed at the coarse-grained analysis of static and all-atom MD-simulated proteins, using a variety of non-conventional approaches, such as dynamic residue network analysis, perturbation-response scanning, dynamic cross-correlation, essential dynamics and normal mode analysis. Altogether, these tools allow for the exploration of protein dynamics at various levels of detail, spanning single residue perturbations and weighted contact network representations, to global residue centrality measurements and the investigation of global protein motion. Typically, following molecular dynamic simulations designed to investigate intrinsic and extrinsic protein perturbations (for instance induced by allosteric and orthosteric ligands, protein binding, temperature, pH and mutations), this selection of tools can be used to further describe protein dynamics. This may lead to the discovery of key residues involved in biological processes, such as drug resistance. The server simplifies the set-up required for running these tools and visualizing their results. Several scripts from the tool suites were updated and new ones were also added and integrated with 2D/3D visualization via the web interface. An embedded work-flow, integrated documentation and visualization tools shorten the number of steps to follow, starting from calculations to result visualization. The Django-powered web server (available at https://mdmtaskweb.rubi.ru.ac.za/) is compatible with all major web browsers. All scripts implemented in the web platform are freely available at https://github.com/RUBi-ZA/MD-TASK/tree/mdm-task-web and https://github.com/RUBi-ZA/MODE-TASK/tree/mdm-task-web.

Decoding the Molecular Effects of Atovaquone Linked Resistant Mutations on Plasmodium falciparum Cytb-ISP Complex in the Phospholipid Bilayer Membrane

Atovaquone (ATQ) is a drug used to prevent and treat malaria that functions by targeting the Plasmodium falciparum cytochrome b (PfCytb) protein. PfCytb catalyzes the transmembrane electron transfer (ET) pathway which maintains the mitochondrial membrane potential. The ubiquinol substrate binding site of the protein has heme bL, heme bH and iron-sulphur [2FE-2S] cluster cofactors that act as redox centers to aid in ET. Recent studies investigating ATQ resistance mechanisms have shown that point mutations of PfCytb confer resistance. Thus, understanding the resistance mechanisms at the molecular level via computational approaches incorporating phospholipid bilayer would help in the design of new efficacious drugs that are also capable of bypassing parasite resistance. With this knowledge gap, this article seeks to explore the effect of three drug resistant mutations Y268C, Y268N and Y268S on the PfCytb structure and function in the presence and absence of ATQ. To draw reliable conclusions, 350 ns all-atom membrane (POPC:POPE phospholipid bilayer) molecular dynamics (MD) simulations with derived metal parameters for the holo and ATQ-bound -proteins were performed. Thereafter, simulation outputs were analyzed using dynamic residue network (DRN) analysis. Across the triplicate MD runs, hydrophobic interactions, reported to be crucial in protein function were assessed. In both, the presence and absence of ATQ and a loss of key active site residue interactions were observed as a result of mutations. These active site residues included: Met 133, Trp136, Val140, Thr142, Ile258, Val259, Pro260 and Phe264. These changes to residue interactions are likely to destabilize the overall intra-protein residue communication network where the proteins' function could be implicated. Protein dynamics of the ATQ-bound mutant complexes showed that they assumed a different pose to the wild-type, resulting in diminished residue interactions in the mutant proteins. In summary, this study presents insights on the possible effect of the mutations on ATQ drug activity causing resistance and describes accurate MD simulations in the presence of the lipid bilayer prior to conducting inhibitory drug discovery for the PfCytb-iron sulphur protein (Cytb-ISP) complex.

Computational SNP Analysis and Molecular Simulation Revealed the Most Deleterious Missense Variants in the NBD1 Domain of Human ABCA1 Transporter

The ATP-binding cassette transporter A1 (ABCA1) is a membrane-bound exporter protein involved in regulating serum HDL level by exporting cholesterol and phospholipids to load up in lipid-poor ApoA-I and ApoE, which allows the formation of nascent HDL. Mutations in the ABCA1 gene, when presents in both alleles, disrupt the canonical function of ABCA1, which associates with many disorders related to lipid transport. Although many studies have reported the phenotypic effects of a large number of ABCA1 variants, the pathological effect of non-synonymous polymorphisms (nsSNPs) in ABCA1 remains elusive. Therefore, aiming at exploring the structural and functional consequences of nsSNPs in ABCA1, in this study, we employed an integrated computational approach consisting of nine well-known in silico tools to identify damaging SNPs and molecular dynamics (MD) simulation to get insights into the magnitudes of the damaging effects. In silico tools revealed four nsSNPs as being most deleterious, where the two SNPs (G1050V and S1067C) are identified as the highly conserved and functional disrupting mutations located in the NBD1 domain. MD simulation suggested that both SNPs, G1050V and S1067C, changed the overall structural flexibility and dynamics of NBD1, and induced substantial alteration in the structural organization of ATP binding site. Taken together, these findings direct future studies to get more insights into the role of these variants in the loss of the ABCA1 function.

AMBER force field parameters for the Zn (II) ions of the tunneling-fold enzymes GTP cyclohydrolase I and 6-pyruvoyl tetrahydropterin synthase

The folate biosynthesis pathway is an essential pathway for cell growth and survival. Folate derivatives serve as a source of the one-carbon units in several intracellular metabolic reactions. Rapidly dividing cells rely heavily on the availability of folate derivatives for their proliferation. As a result, drugs targeting this pathway have shown to be effective against tumor cells and pathogens, but drug resistance against the available antifolate drugs emerged quickly. Therefore, there is a need to develop new treatment strategies and identify alternative metabolic targets. The two de novo folate biosynthesis pathway enzymes, GTP cyclohydrolase I (GCH1) and 6-pyruvoyl tetrahydropterin synthase (PTPS), can provide an alternative strategy to overcome the drug resistance that emerged in the two primary targeted enzymes dihydrofolate reductase and dihydropteroate synthase. Both GCH1 and PTPS enzymes contain Zn²⁺ ions in their active sites, and to accurately study their dynamic behaviors using all-atom molecular dynamics (MD) simulations, appropriate parameters that can describe their metal sites should be developed and validated. In this study, force field parameters of the GCH1 and PTPS metal centers were generated using quantum mechanics (QM) calculations and then validated through MD simulations to ensure their accuracy in describing and maintaining the Zn²⁺ ion coordination environment. The derived force field parameters will provide accurate and reliable MD simulations involving these two enzymes for future in-silico identification of drug candidates against the GCH1 and PTPS enzymes. Communicated by Ramaswamy H. Sarma.