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.

Characterisation of plasmodial transketolases and identification of potential inhibitors: an in silico study.

BACKGROUND: Plasmodial transketolase (PTKT) enzyme is one of the novel pharmacological targets being explored as potential anti-malarial drug target due to its functional role and low sequence identity to the human enzyme. Despite this, features contributing to such have not been exploited for anti-malarial drug design. Additionally, there are no anti-malarial drugs targeting PTKTs whereas the broad activity of these inhibitors against PTKTs from other Plasmodium spp. is yet to be reported. This study characterises different PTKTs [Plasmodium falciparum (PfTKT), Plasmodium vivax (PvTKT), Plasmodium ovale (PoTKT), Plasmodium malariae (PmTKT) and Plasmodium knowlesi (PkTKT) and the human homolog (HsTKT)] to identify key sequence and structural based differences as well as the identification of selective potential inhibitors against PTKTs. METHODS: A sequence-based study was carried out using multiple sequence alignment, phylogenetic tree calculations and motif discovery analysis. Additionally, TKT models of PfTKT, PmTKT, PoTKT, PmTKT and PkTKT were modelled using the Saccharomyces cerevisiae TKT structure as template. Based on the modelled structures, molecular docking using 623 South African natural compounds was done. The stability, conformational changes and detailed interactions of selected compounds were accessed viz all-atom molecular dynamics (MD) simulations and binding free energy (BFE) calculations. RESULTS: Sequence alignment, evolutionary and motif analyses revealed key differences between plasmodial and the human TKTs. High quality homodimeric three-dimensional PTKTs structures were constructed. Molecular docking results identified three compounds (SANC00107, SANC00411 and SANC00620) which selectively bind in the active site of all PTKTs with the lowest (better) binding affinity ≤ - 8.5 kcal/mol. MD simulations of ligand-bound systems showed stable fluctuations upon ligand binding. In all systems, ligands bind stably throughout the simulation and form crucial interactions with key active site residues. Simulations of selected compounds in complex with human TKT showed that ligands exited their binding sites at different time steps. BFE of protein-ligand complexes showed key residues involved in binding. CONCLUSIONS: This study highlights significant differences between plasmodial and human TKTs and may provide valuable information for the development of novel anti-malarial inhibitors. Identified compounds may provide a starting point in the rational design of PTKT inhibitors and analogues based on these scaffolds.

Comparing sequence and structure of falcipains and human homologs at prodomain and catalytic active site for malarial peptide based inhibitor design.

BACKGROUND: Falcipains are major cysteine proteases of Plasmodium falciparum involved in haemoglobin degradation and remain attractive anti-malarial drug targets. Several inhibitors against these proteases have been identified, yet none of them has been approved for malaria treatment. Other Plasmodium species also possess highly homologous proteins to falcipains. For selective therapeutic targeting, identification of sequence and structure differences with homologous human cathepsins is necessary. The substrate processing activity of these proteins is tightly controlled via a prodomain segment occluding the active site which is chopped under low pH conditions exposing the catalytic site. Current work characterizes these proteases to identify residues mediating the prodomain regulatory function for the design of peptide based anti-malarial inhibitors. METHODS: Sequence and structure variations between prodomain regions of plasmodial proteins and human cathepsins were determined using in silico approaches. Additionally, evolutionary clustering of these proteins was evaluated using phylogenetic analysis. High quality partial zymogen protein structures were modelled using homology modelling and residue interaction analysis performed between the prodomain segment and mature domain to identify key interacting residues between these two domains. The resulting information was used to determine short peptide sequences which could mimic the inherent regulatory function of the prodomain regions. Through flexible docking, the binding affinity of proposed peptides on the proteins studied was evaluated. RESULTS: Sequence, evolutionary and motif analyses showed important differences between plasmodial and human proteins. Residue interaction analysis identified important residues crucial for maintaining prodomain integrity across the different proteins as well as the pro-segment responsible for inhibitory mechanism. Binding affinity of suggested peptides was highly dependent on their residue composition and length. CONCLUSIONS: Despite the conserved structural and catalytic mechanism between human cathepsins and plasmodial proteases, current work revealed significant differences between the two protein groups which may provide valuable information for selective anti-malarial inhibitor development. Part of this study aimed to design peptide inhibitors based on endogenous inhibitory portions of protease prodomains as a novel aspect. Even though peptide inhibitors may not be practical solutions to malaria at this stage, the approach followed and results offer a promising means to find new malarial inhibitors.

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.

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.

Determining the unbinding events and conserved motions associated with the pyrazinamide release due to resistance mutations of Mycobacterium tuberculosis pyrazinamidase.

Pyrazinamide (PZA) is the only first-line antitubercular drug active against latent Mycobacterium tuberculosis (Mtb). It is activated to pyrazinoic acid by the pncA-encoded pyrazinamidase enzyme (PZase). Despite the emergence of PZA drug resistance, the underlying mechanisms of resistance remain unclear. This study investigated part of these mechanisms by modelling a PZA-bound wild type and 82 mutant PZase structures before applying molecular dynamics (MD) with an accurate Fe2+ cofactor coordination geometry. After observing nanosecond-scale PZA unbinding from several PZase mutants, an algorithm was developed to systematically detect ligand release via centre of mass distances (COM) and ligand average speed calculations, before applying the statistically guided network analysis (SGNA) method to investigate conserved protein motions associated with ligand unbinding. Ligand and cofactor perspectives were also investigated. A conserved pair of lid-destabilising motions was found. These consisted of (1) antiparallel lid and side flap motions; (2) the contractions of a flanking region within the same flap and residue 74 towards the core. Mutations affecting the hinge residues (H51 and H71), nearby residues or L19 were found to destabilise the lid. Additionally, other metal binding site (MBS) mutations delocalised the Fe2+ cofactor, also facilitating lid opening. In the early stages of unbinding, a wider variety of PZA poses were observed, suggesting multiple exit pathways. These findings provide insights into the late events preceding PZA unbinding, which we found to occur in some resistant PZase mutants. Further, the algorithm developed here to identify unbinding events coupled with SGNA can be applicable to other similar problems.