Repurposing DrugBank compounds as potential Plasmodium falciparum class 1a aminoacyl tRNA synthetase multi-stage pan-inhibitors with a specific focus on mitomycin.

Plasmodium falciparum aminoacyl tRNA synthetases (PfaaRSs) are potent antimalarial targets essential for proteome fidelity and overall parasite survival in every stage of the parasite's life cycle. So far, some of these proteins have been singly targeted yielding inhibitor compounds that have been limited by incidences of resistance which can be overcome via pan-inhibition strategies. Hence, herein, for the first time, we report the identification and in vitro antiplasmodial validation of Mitomycin (MMC) as a probable pan-inhibitor of class 1a (arginyl(A)-, cysteinyl(C), isoleucyl(I)-, leucyl(L), methionyl(M), and valyl(V)-) PfaaRSs which hypothetically may underlie its previously reported activity on the ribosomal RNA to inhibit protein translation and biosynthesis. We combined multiple in silico structure-based discovery strategies that first helped identify functional and druggable sites that were preferentially targeted by the compound in each of the plasmodial proteins: Ins1-Ins2 domain in Pf-ARS; anticodon binding domain in Pf-CRS; CP1-editing domain in Pf-IRS and Pf-MRS; C-terminal domain in Pf-LRS; and CP-core region in Pf-VRS. Molecular dynamics studies further revealed that MMC allosterically induced changes in the global structures of each protein. Likewise, prominent structural perturbations were caused by the compound across the functional domains of the proteins. More so, MMC induced systematic alterations in the binding of the catalytic nucleotide and amino acid substrates which culminated in the loss of key interactions with key active site residues and ultimate reduction in the nucleotide-binding affinities across all proteins, as deduced from the binding energy calculations. These altogether confirmed that MMC uniformly disrupted the structure of the target proteins and essential substrates. Further, MMC demonstrated IC50 < 5 µM against the Dd2 and 3D7 strains of parasite making it a good starting point for malarial drug development. We believe that findings from our study will be important in the current search for highly effective multi-stage antimalarial drugs.

Draft genome of Microsporidia sp. MB-a malaria-blocking microsporidian symbiont of the Anopheles arabiensis.

We report the draft whole-genome assembly of Microsporidia sp. MB, a symbiotic malaria-transmission-blocking microsporidian isolated from Anopheles arabiensis in Kenya. The whole-genome sequence of Microsporidia sp. MB has a length of 5,908,979 bp, 2,335 contigs, and an average GC content of 31.12%.

Genome Study of α-, ß-, and γ-Carbonic Anhydrases from the Thermophilic Microbiome of Marine Hydrothermal Vent Ecosystems.

Carbonic anhydrases (CAs) are metalloenzymes that can help organisms survive in hydrothermal vents by hydrating carbon dioxide (CO2). In this study, we focus on alpha (α), beta (ß), and gamma (γ) CAs, which are present in the thermophilic microbiome of marine hydrothermal vents. The coding genes of these enzymes can be transferred between hydrothermal-vent organisms via horizontal gene transfer (HGT), which is an important tool in natural biodiversity. We performed big data mining and bioinformatics studies on α-, ß-, and γ-CA coding genes from the thermophilic microbiome of marine hydrothermal vents. The results showed a reasonable association between thermostable α-, ß-, and γ-CAs in the microbial population of the hydrothermal vents. This relationship could be due to HGT. We found evidence of HGT of α- and ß-CAs between Cycloclasticus sp., a symbiont of Bathymodiolus heckerae, and an endosymbiont of Riftia pachyptila via Integrons. Conversely, HGT of ß-CA genes from the endosymbiont Tevnia jerichonana to the endosymbiont Riftia pachyptila was detected. In addition, Hydrogenovibrio crunogenus SP-41 contains a ß-CA gene on genomic islands (GIs). This gene can be transferred by HGT to Hydrogenovibrio sp. MA2-6, a methanotrophic endosymbiont of Bathymodiolus azoricus, and a methanotrophic endosymbiont of Bathymodiolus puteoserpentis. The endosymbiont of R. pachyptila has a γ-CA gene in the genome. If α- and ß-CA coding genes have been derived from other microorganisms, such as endosymbionts of T. jerichonana and Cycloclasticus sp. as the endosymbiont of B. heckerae, through HGT, the theory of the necessity of thermostable CA enzymes for survival in the extreme ecosystem of hydrothermal vents is suggested and helps the conservation of microbiome natural diversity in hydrothermal vents. These harsh ecosystems, with their integral players, such as HGT and endosymbionts, significantly impact the enrichment of life on Earth and the carbon cycle in the ocean.

Investigation of Multi-Subunit Mycobacterium tuberculosis DNA-Directed RNA Polymerase and Its Rifampicin Resistant Mutants.

Emerging Mycobacterium tuberculosis (Mtb) resistant strains have continued to limit the efficacies of existing antitubercular therapies. More specifically, mutations in the RNA replicative machinery of Mtb, RNA polymerase (RNAP), have been widely linked to rifampicin (RIF) resistance, which has led to therapeutic failures in many clinical cases. Moreover, elusive details on the underlying mechanisms of RIF-resistance caused by Mtb-RNAP mutations have hampered the development of new and efficient drugs that are able to overcome this challenge. Therefore, in this study we attempt to resolve the molecular and structural events associated with RIF-resistance in nine clinically reported missense Mtb RNAP mutations. Our study, for the first time, investigated the multi-subunit Mtb RNAP complex and findings revealed that the mutations commonly disrupted structural-dynamical attributes that may be essential for the protein's catalytic functions, particularly at the ßfork loop 2, ß'zinc-binding domain, the ß' trigger loop and ß'jaw, which in line with previous experimental reports, are essential for RNAP processivity. Complementarily, the mutations considerably perturbed the RIF-BP, which led to alterations in the active orientation of RIF needed to obstruct RNA extension. Consequentially, essential interactions with RIF were lost due to the mutation-induced repositioning with corresponding reductions in the binding affinity of the drug observed in majority of the mutants. We believe these findings will significantly aid future efforts in the discovery of new treatment options with the potential to overcome antitubercular resistance.

Human Cytochrome P450 1, 2, 3 Families as Pharmacogenes with Emphases on Their Antimalarial and Antituberculosis Drugs and Prevalent African Alleles.

Precision medicine gives individuals tailored medical treatment, with the genotype determining the therapeutic strategy, the appropriate dosage, and the likelihood of benefit or toxicity. Cytochrome P450 (CYP) enzyme families 1, 2, and 3 play a pivotal role in eliminating most drugs. Factors that affect CYP function and expression have a major impact on treatment outcomes. Therefore, polymorphisms of these enzymes result in alleles with diverse enzymatic activity and drug metabolism phenotypes. Africa has the highest CYP genetic diversity and also the highest burden of malaria and tuberculosis, and this review presents current general information on CYP enzymes together with variation data concerning antimalarial and antituberculosis drugs, while focusing on the first three CYP families. Afrocentric alleles such as CYP2A6*17, CYP2A6*23, CYP2A6*25, CYP2A6*28, CYP2B6*6, CYP2B6*18, CYP2C8*2, CYP2C9*5, CYP2C9*8, CYP2C9*9, CYP2C19*9, CYP2C19*13, CYP2C19*15, CYP2D6*2, CYP2D6*17, CYP2D6*29, and CYP3A4*15 are implicated in diverse metabolic phenotypes of different antimalarials such as artesunate, mefloquine, quinine, primaquine, and chloroquine. Moreover, CYP3A4, CYP1A1, CYP2C8, CYP2C18, CYP2C19, CYP2J2, and CYP1B1 are implicated in the metabolism of some second-line antituberculosis drugs such as bedaquiline and linezolid. Drug-drug interactions, induction/inhibition, and enzyme polymorphisms that influence the metabolism of antituberculosis, antimalarial, and other drugs, are explored. Moreover, a mapping of Afrocentric missense mutations to CYP structures and a documentation of their known effects provided structural insights, as understanding the mechanism of action of these enzymes and how the different alleles influence enzyme function is invaluable to the advancement of precision medicine.

Structural and Functional Annotation of Hypothetical Proteins from the Microsporidia Species Vittaforma corneae ATCC 50505 Using in silico Approaches.

Microsporidia are spore-forming eukaryotes that are related to fungi but have unique traits that set them apart. They have compact genomes as a result of evolutionary gene loss associated with their complete dependency on hosts for survival. Despite having a relatively small number of genes, a disproportionately high percentage of the genes in microsporidia genomes code for proteins whose functions remain unknown (hypothetical proteins-HPs). Computational annotation of HPs has become a more efficient and cost-effective alternative to experimental investigation. This research developed a robust bioinformatics annotation pipeline of HPs from Vittaforma corneae, a clinically important microsporidian that causes ocular infections in immunocompromised individuals. Here, we describe various steps to retrieve sequences and homologs and to carry out physicochemical characterization, protein family classification, identification of motifs and domains, protein-protein interaction network analysis, and homology modelling using a variety of online resources. Classification of protein families produced consistent findings across platforms, demonstrating the accuracy of annotation utilizing in silico methods. A total of 162 out of 2034 HPs were fully annotated, with the bulk of them categorized as binding proteins, enzymes, or regulatory proteins. The protein functions of several HPs from Vittaforma corneae were accurately inferred. This improved our understanding of microsporidian HPs despite challenges related to the obligate nature of microsporidia, the absence of fully characterized genes, and the lack of homologous genes in other systems.

Evolutionary progression of collective mutations in Omicron sub-lineages towards efficient RBD-hACE2: Allosteric communications between and within viral and human proteins.

The interaction between the Spike (S) protein of SARS-CoV-2 and the human angiotensin converting enzyme 2 (hACE2) is essential for infection, and is a target for neutralizing antibodies. Consequently, selection of mutations in the S protein is expected to be driven by the impact on the interaction with hACE2 and antibody escape. Here, for the first time, we systematically characterized the collective effects of mutations in each of the Omicron sub-lineages (BA.1, BA.2, BA.3 and BA.4) on both the viral S protein receptor binding domain (RBD) and the hACE2 protein using post molecular dynamics studies and dynamic residue network (DRN) analysis. Our analysis suggested that Omicron sub-lineage mutations result in altered physicochemical properties that change conformational flexibility compared to the reference structure, and may contribute to antibody escape. We also observed changes in the hACE2 substrate binding groove in some sub-lineages. Notably, we identified unique allosteric communication paths in the reference protein complex formed by the DRN metrics betweenness centrality and eigencentrality hubs, originating from the RBD core traversing the receptor binding motif of the S protein and the N-terminal domain of the hACE2 to the active site. We showed allosteric changes in residue network paths in both the RBD and hACE2 proteins due to Omicron sub-lineage mutations. Taken together, these data suggest progressive evolution of the Omicron S protein RBD in sub-lineages towards a more efficient interaction with the hACE2 receptor which may account for the increased transmissibility of Omicron variants.

Allostery and Missense Mutations as Intermittently Linked Promising Aspects of Modern Computational Drug Discovery.

Drug research and development is a multidisciplinary field with its own successes. Yet, given the complexity of the process, it also faces challenges over the long development stages and even includes those that develop once a drug is marketed, i.e. drug toxicity and drug resistance. Better success can be achieved via well designed criteria in the early drug development stages. Here, we introduce the concepts of allostery and missense mutations, and argue that incorporation of these two intermittently linked biological phenomena into the early computational drug discovery stages would help to reduce the attrition risk in later stages of the process. We discuss the individual or in concert mechanisms of actions of mutations in allostery. Design of allosteric drugs is challenging compared to orthosteric drugs, yet they have been gaining popularity in recent years as alternative systems for the therapeutic regulation of proteins with an action-at-a-distance mode and non-invasive mechanisms. We propose an easy-to-apply computational allosteric drug discovery protocol which considers the mutation effect, and detail it with three case studies focusing on (1) analysis of effect of an allosteric mutation related to isoniazid drug resistance in tuberculosis; (2) identification of a cryptic pocket in the presence of an allosteric mutation of falcipain-2 as a malarial drug target; and (3) deciphering the effects of SARS-CoV-2 evolutionary mutations on a potential allosteric modulator with changes to allosteric communication paths.

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.

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.

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 ß-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.

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.

Computational Applications in Secondary Metabolite Discovery (CAiSMD): an online workshop.

We report the major conclusions of the online open-access workshop "Computational Applications in Secondary Metabolite Discovery (CAiSMD)" that took place from 08 to 10 March 2021. Invited speakers from academia and industry and about 200 registered participants from five continents (Africa, Asia, Europe, South America, and North America) took part in the workshop. The workshop highlighted the potential applications of computational methodologies in the search for secondary metabolites (SMs) or natural products (NPs) as potential drugs and drug leads. During 3 days, the participants of this online workshop received an overview of modern computer-based approaches for exploring NP discovery in the "omics" age. The invited experts gave keynote lectures, trained participants in hands-on sessions, and held round table discussions. This was followed by oral presentations with much interaction between the speakers and the audience. Selected applicants (early-career scientists) were offered the opportunity to give oral presentations (15 min) and present posters in the form of flash presentations (5 min) upon submission of an abstract. The final program available on the workshop website ( https://caismd.indiayouth.info/ ) comprised of 4 keynote lectures (KLs), 12 oral presentations (OPs), 2 round table discussions (RTDs), and 5 hands-on sessions (HSs). This meeting report also references internet resources for computational biology in the area of secondary metabolites that are of use outside of the workshop areas and will constitute a long-term valuable source for the community. The workshop concluded with an online survey form to be completed by speakers and participants for the goal of improving any subsequent editions.

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.

GTP Cyclohydrolase I as a Potential Drug Target: New Insights into Its Allosteric Modulation via Normal Mode Analysis.

Guanosine triphosphate (GTP) cyclohydrolase I (GCH1) catalyzes the conversion of GTP into dihydroneopterin triphosphate (DHNP). DHNP is the first intermediate of the folate de novo biosynthesis pathway in prokaryotic and lower eukaryotic microorganisms and the tetrahydrobiopterin (BH4) biosynthesis pathway in higher eukaryotes. The de novo folate biosynthesis provides essential cofactors for DNA replication, cell division, and synthesis of key amino acids in rapidly replicating pathogen cells, such as Plasmodium falciparum (P. falciparum), a causative agent of malaria. In eukaryotes, the product of the BH4 biosynthesis pathway is essential for the production of nitric oxide and several neurotransmitter precursors. An increased copy number of the malaria parasite P. falciparum GCH1 gene has been reported to influence antimalarial antifolate drug resistance evolution, whereas mutations in the human GCH1 are associated with neuropathic and inflammatory pain disorders. Thus, GCH1 stands as an important and attractive drug target for developing therapeutics. The GCH1 intrinsic dynamics that modulate its activity remains unclear, and key sites that exert allosteric effects across the structure are yet to be elucidated. This study employed the anisotropic network model to analyze the intrinsic motions of the GCH1 structure alone and in complex with its regulatory partner protein. We showed that the GCH1 tunnel-gating mechanism is regulated by a global shear motion and an outward expansion of the central five-helix bundle. We further identified hotspot residues within sites of structural significance for the GCH1 intrinsic allosteric modulation. The obtained results can provide a solid starting point to design novel antineuropathic treatments for humans and novel antimalarial drugs against the malaria parasite P. falciparum GCH1 enzyme.

Polyphenols Epigallocatechin Gallate and Resveratrol, and Polyphenol-Functionalized Nanoparticles Prevent Enterovirus Infection through Clustering and Stabilization of the Viruses.

To efficiently lower virus infectivity and combat virus epidemics or pandemics, it is important to discover broadly acting antivirals. Here, we investigated two naturally occurring polyphenols, Epigallocatechin gallate (EGCG) and Resveratrol (RES), and polyphenol-functionalized nanoparticles for their antiviral efficacy. Concentrations in the low micromolar range permanently inhibited the infectivity of high doses of enteroviruses (107 PFU/mL). Sucrose gradient separation of radiolabeled viruses, dynamic light scattering, transmission electron microscopic imaging and an in-house developed real-time fluorescence assay revealed that polyphenols prevented infection mainly through clustering of the virions into very stable assemblies. Clustering and stabilization were not compromised even in dilute virus solutions or after diluting the polyphenols-clustered virions by 50-fold. In addition, the polyphenols lowered virus binding on cells. In silico docking experiments of these molecules against 2- and 3-fold symmetry axes of the capsid, using an algorithm developed for this study, discovered five binding sites for polyphenols, out of which three were novel binding sites. Our results altogether suggest that polyphenols exert their antiviral effect through binding to multiple sites on the virion surface, leading to aggregation of the virions and preventing RNA release and reducing cell surface binding.

Differences in Gluco and Galacto Substrate-Binding Interactions in a Dual 6Pß-Glucosidase/6Pß-Galactosidase Glycoside Hydrolase 1 Enzyme from Bacillus licheniformis.

Bacterial glycoside hydrolase 1 (GH1) enzymes with 6-phospho-ß-galactosidase and 6-phospho-ß-glucosidase activities have the important task of releasing phosphorylated and nonphosphorylated monosaccharides into the cytoplasm. Curiously, dual 6-phospho-ß-galactosidase/6-phospho-ß-glucosidase (dual-phospho) enzymes have broad specificity and are able to hydrolyze galacto- and gluco-derived substrates. This study investigates the structure and substrate specificity of a GH family 1 enzyme from Bacillus licheniformis, hereafter known as BlBglC. The enzyme structure has been solved, and sequence analysis, molecular dynamics simulations, and binding free energy calculations offered evidence of dual-phospho activity. Both test ligands p-nitrophenyl-ß-d-galactoside-6-phosphate (PNP6Pgal) and p-nitrophenyl-ß-d-glucoside-6-phosphate (PNP6Pglc) demonstrated strong binding to BlBglC although the pose and interactions of the PNP6Pglc triplicates were slightly more consistent. Interestingly, known specificity-inducing residues, Gln23 and Trp433, bind strongly to the ligand O3 hydroxyl group in the PNP6Pgal-BlBglC complex and to the ligand O4 hydroxyl group in the PNP6Pglc-BlBglC complex. Additionally, the BlBglC-His124 residue is a major contributor of hydrogen bonds to the PNP6Pgal O3 hydroxyl group but does not form any hydrogen bonds with PNP6Pglc. On the other hand, BlBglC residues Tyr173, Tyr301, Gln302, and Thr321 form hydrogen bonds with PNP6Pglc but not PNP6Pgal. These findings provide important details of the broad specificity of dual-phospho activity GH1 enzymes.

Force Field Parameters for Fe2+4S2-4 Clusters of Dihydropyrimidine Dehydrogenase, the 5-Fluorouracil Cancer Drug Deactivation Protein: A Step towards In Silico Pharmacogenomics Studies.

The dimeric dihydropyrimidine dehydrogenase (DPD), metalloenzyme, an adjunct anti-cancer drug target, contains highly specialized 4 × Fe2+4S2-4 clusters per chain. These clusters facilitate the catalysis of the rate-limiting step in the pyrimidine degradation pathway through a harmonized electron transfer cascade that triggers a redox catabolic reaction. In the process, the bulk of the administered 5-fluorouracil (5-FU) cancer drug is inactivated, while a small proportion is activated to nucleic acid antimetabolites. The occurrence of missense mutations in DPD protein within the general population, including those of African descent, has adverse toxicity effects due to altered 5-FU metabolism. Thus, deciphering mutation effects on protein structure and function is vital, especially for precision medicine purposes. We previously proposed combining molecular dynamics (MD) and dynamic residue network (DRN) analysis to decipher the molecular mechanisms of missense mutations in other proteins. However, the presence of Fe2+4S2-4 clusters in DPD poses a challenge for such in silico studies. The existing AMBER force field parameters cannot accurately describe the Fe2+ center coordination exhibited by this enzyme. Therefore, this study aimed to derive AMBER force field parameters for DPD enzyme Fe2+ centers, using the original Seminario method and the collation features Visual Force Field Derivation Toolkit as a supportive approach. All-atom MD simulations were performed to validate the results. Both approaches generated similar force field parameters, which accurately described the human DPD protein Fe2+4S2-4 cluster architecture. This information is crucial and opens new avenues for in silico cancer pharmacogenomics and drug discovery related research on 5-FU drug efficacy and toxicity issues.

SANCDB: an update on South African natural compounds and their readily available analogs.

BACKGROUND: South African Natural Compounds Database (SANCDB; https://sancdb.rubi.ru.ac.za/ ) is the sole and a fully referenced database of natural chemical compounds of South African biodiversity. It is freely available, and since its inception in 2015, the database has become an important resource to several studies. Its content has been: used as training data for machine learning models; incorporated to larger databases; and utilized in drug discovery studies for hit identifications. DESCRIPTION: Here, we report the updated version of SANCDB. The new version includes 412 additional compounds that have been reported since 2015, giving a total of 1012 compounds in the database. Further, although natural products (NPs) are an important source of unique scaffolds, they have a major drawback due to their complex structure resulting in low synthetic feasibility in the laboratory. With this in mind, SANCDB is, now, updated to provide direct links to commercially available analogs from two major chemical databases namely Mcule and MolPort. To our knowledge, this feature is not available in other NP databases. Additionally, for easier access to information by users, the database and website interface were updated. The compounds are now downloadable in many different chemical formats. CONCLUSIONS: The drug discovery process relies heavily on NPs due to their unique chemical organization. This has inspired the establishment of numerous NP chemical databases. With the emergence of newer chemoinformatic technologies, existing chemical databases require constant updates to facilitate information accessibility and integration by users. Besides increasing the NPs compound content, the updated SANCDB allows users to access the individual compounds (if available) or their analogs from commercial databases seamlessly.