Discovery of new inhibitors of Mycobacterium tuberculosis InhA enzyme using virtual screening and a 3D-pharmacophore-based approach.

Mycobacterium tuberculosis InhA (MtInhA) is an attractive enzyme to drug discovery efforts due to its validation as an effective biological target for tuberculosis therapy. In this work, two different virtual-ligand-screening approaches were applied in order to identify new InhA inhibitors' candidates from a library of ligands selected from the ZINC database. First, a 3-D pharmacophore model was built based on 36 available MtInhA crystal structures. By combining structure-based and ligand-based information, four pharmacophoric points were designed to select molecules able to satisfy the binding features of MtInhA substrate-binding cavity. The second approach consisted of using four well established docking programs, with different search algorithms, to compare the binding mode and score of the selected molecules from the aforementioned library. After detailed analyses of the results, six ligands were selected for in vitro analysis. Three of these molecules presented a satisfactory inhibitory activity with IC50 values ranging from 24 (±2) µM to 83 (±5) µM. The best compound presented an uncompetitive inhibition mode to NADH and 2-trans-dodecenoyl-CoA substrates, with Ki values of 24 (±3) µM and 20 (±2) µM, respectively. These molecules were not yet described as antituberculars or as InhA inhibitors, making its novelty interesting to start efforts on ligand optimization in order to identify new effective drugs against tuberculosis having InhA as a target. More studies are underway to dissect the discovered uncompetitive inhibitor interactions with MtInhA.

Rethinking the MtInhA tertiary and quaternary structure flexibility: a molecular dynamics view.

Flexibility and function are related properties in the study of protein dynamics. Flexibility reflects in the conformational potential of proteins and thus in their functionalities. The presence of interactions between protein-ligands and protein-protein complexes, substrates, and environmental changes can alter protein plasticity, acting from the rearrangement of the side chains of amino acids to the folding/unfolding of large structural motifs. To evaluate the effects of the flexibility in protein systems, we defined the enzyme 2-trans-enoyl-ACP (CoA) reductase from Mycobacterium tuberculosis, or MtInhA, as our target system. MtInhA is biologically active as a tetramer in solution; however, computational studies commonly use the monomer justifying the independence of its active sites due to their distances. However, differences in flexibility between tertiary and quaternary structures could present impact on the size of the active site, influencing the drug discovery process. In this study, we investigated the influence of flexibility restrictions in A- and B-loops of the MtInhA in order to suggest a monomeric structure that describes the conformational behavior of the tetrameric system. Overall, we observed that simulations where restrictions were applied to the A- and B-loops present a more similar behavior to the native structure when compared to unrestricted simulations. Therefore, our work presents a monomeric model of MtInhA, which has conformational characteristics of the biologically active structure. Thus, the data obtained in this work can be applied to the MtInhA system for the generation of more reliable flexible models for molecular docking experiments, and also for the performance of longer simulations by molecular dynamics and with a lower computational cost.

Evaluation of drug repositioning by molecular docking of pharmaceutical resources available in the Brazilian healthcare system against SARS-CoV-2.

In 2020 SARS-CoV-2 reached pandemic status, reaching Brazil in mid-February. As of now, no specific drugs for treating the disease are available. In this work, the possibility of interaction between SARS-CoV-2 viral proteins (open and closed spike protein, isolate spike protein RBD, NSP 10, NSP 16, main protease, and RdRp polymerase) and multiple molecules is addressed through the repositioning of drugs available for the treatment of other diseases that are approved by the FDA and covered by SUS, the Brazilian Public Health System. Three different docking software were used, followed by a unification of the results by independent evaluation. Afterwards, the chemical interactions of the compounds with the targets were inspected via molecular dynamics and analyzed. The results point to a potential effectiveness of Penciclovir, Ribavirin, and Zanamivir, from a set of 48 potential candidates. They may also be multi-target drugs, showing high affinity with more than one viral protein. Further in vitro and in vivo validation is required to assess the suitability of repositioning the proposed drugs for COVID-19.

Mutant Allele-Specific CRISPR Disruption in DYT1 Dystonia Fibroblasts Restores Cell Function.

Most individuals affected with DYT1 dystonia have a heterozygous 3-bp deletion in the TOR1A gene (c.907_909delGAG). The mutation appears to act through a dominant-negative mechanism compromising normal torsinA function, and it is proposed that reducing mutant torsinA may normalize torsinA activity. In this study, we used an engineered Cas9 variant from Streptococcus pyogenes (SpCas9-VRQR) to target the mutation in the TOR1A gene in order to disrupt mutant torsinA in DYT1 patient fibroblasts. Selective targeting of the DYT1 allele was highly efficient with most common non-homologous end joining (NHEJ) edits, leading to a predicted premature stop codon with loss of the torsinA C terminus (delta 302-332 aa). Structural analysis predicted a functionally inactive status of this truncated torsinA due to the loss of residues associated with ATPase activity and binding to LULL1. Immunoblotting showed a reduction of the torsinA protein level in Cas9-edited DYT1 fibroblasts, and a functional assay using HSV infection indicated a phenotypic recovery toward that observed in control fibroblasts. These findings suggest that the selective disruption of the mutant TOR1A allele using CRISPR-Cas9 inactivates mutant torsinA, allowing the remaining wild-type torsinA to exert normal function.

The importance of the quaternary structure to represent conformational ensembles of the major Mycobacterium tuberculosis drug target.

Flexibility is a feature intimately related to protein function, since conformational changes can be used to describe environmental changes, chemical modifications, protein-protein and protein-ligand interactions. In this study, we have investigated the influence of the quaternary structure of 2-trans-enoyl-ACP (CoA) reductase or InhA, from Mycobacterium tuberculosis, to its flexibility. We carried out classical molecular dynamics simulations using monomeric and tetrameric forms to elucidate the enzyme's flexibility. Overall, we observed statistically significant differences between conformational ensembles of tertiary and quaternary structures. In addition, the enzyme's binding site is the most affected region, reinforcing the importance of the quaternary structure to evaluate the binding affinity of small molecules, as well as the effect of single point mutations to InhA protein dynamics.

Pre-clinical evaluation of quinoxaline-derived chalcones in tuberculosis.

New effective compounds for tuberculosis treatment are needed. This study evaluated the effects of a series of quinoxaline-derived chalcones against laboratorial strains and clinical isolates of M. tuberculosis. Six molecules, namely N5, N9, N10, N15, N16, and N23 inhibited the growth of the M. tuberculosis H37Rv laboratorial strain. The three compounds (N9, N15 and N23) with the lowest MIC values were further tested against clinical isolates and laboratory strains with mutations in katG or inhA genes. From these data, N9 was selected as the lead compound for further investigation. Importantly, this chalcone displayed a synergistic effect when combined with moxifloxacin. Noteworthy, the anti-tubercular effects of N9 did not rely on inhibition of mycolic acids synthesis, circumventing important mechanisms of resistance. Interactions with cytochrome P450 isoforms and toxic effects were assessed in silico and in vitro. The chalcone N9 was not predicted to elicit any mutagenic, genotoxic, irritant, or reproductive effects, according to in silico analysis. Additionally, N9 did not cause mutagenicity or genotoxicity, as revealed by Salmonella/microsome and alkaline comet assays, respectively. Moreover, N9 did not inhibit the cytochrome P450 isoforms CYP3A4/5, CYP2C9, and CYP2C19. N9 can be considered a potential lead molecule for development of a new anti-tubercular therapeutic agent.

EPSP synthase flexibility is determinant to its function: computational molecular dynamics and metadynamics studies.

Flexibility is involved in a wide range of biological processes, such as protein assembly and binding recognition. EPSP synthase is an enzyme that must undergo a large conformational change to accommodate its ligands into its binding cavity. However, although the structure of EPSP synthase has been determined, its plasticity has not been explored in depth. Therefore, in this work, we extensively examined the influence of the flexibility of Mycobacterium tuberculosis EPSP (MtEPSP) synthase on the function of this protein using classical and replica-exchange metadynamics simulations. We were able to identify five well-populated conformational clusters for MtEPSP synthase: two corresponding to open, one to ajar, and two to closed conformations. We also pinpointed three hydrophobic regions that are responsible for guiding transitions among these states. Taken together, the new findings presented here indicate how the hydrophobic regions modulate the flexibility of MtEPSP synthase, and they highlight the importance of considering these dynamic features in drug design projects employing this enzyme as a target. Graphical abstract The flexibility of EPSP synthase as a function of the pincer angles.

An Effective Approach for Clustering InhA Molecular Dynamics Trajectory Using Substrate-Binding Cavity Features.

Protein receptor conformations, obtained from molecular dynamics (MD) simulations, have become a promising treatment of its explicit flexibility in molecular docking experiments applied to drug discovery and development. However, incorporating the entire ensemble of MD conformations in docking experiments to screen large candidate compound libraries is currently an unfeasible task. Clustering algorithms have been widely used as a means to reduce such ensembles to a manageable size. Most studies investigate different algorithms using pairwise Root-Mean Square Deviation (RMSD) values for all, or part of the MD conformations. Nevertheless, the RMSD only may not be the most appropriate gauge to cluster conformations when the target receptor has a plastic active site, since they are influenced by changes that occur on other parts of the structure. Hence, we have applied two partitioning methods (k-means and k-medoids) and four agglomerative hierarchical methods (Complete linkage, Ward's, Unweighted Pair Group Method and Weighted Pair Group Method) to analyze and compare the quality of partitions between a data set composed of properties from an enzyme receptor substrate-binding cavity and two data sets created using different RMSD approaches. Ensembles of representative MD conformations were generated by selecting a medoid of each group from all partitions analyzed. We investigated the performance of our new method for evaluating binding conformation of drug candidates to the InhA enzyme, which were performed by cross-docking experiments between a 20 ns MD trajectory and 20 different ligands. Statistical analyses showed that the novel ensemble, which is represented by only 0.48% of the MD conformations, was able to reproduce 75% of all dynamic behaviors within the binding cavity for the docking experiments performed. Moreover, this new approach not only outperforms the other two RMSD-clustering solutions, but it also shows to be a promising strategy to distill biologically relevant information from MD trajectories, especially for docking purposes.

Clustering molecular dynamics trajectories for optimizing docking experiments.

Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand.

A network flow approach to predict protein targets and flavonoid backbones to treat respiratory syncytial virus infection.

BACKGROUND: Respiratory syncytial virus (RSV) infection is the major cause of respiratory disease in lower respiratory tract in infants and young children. Attempts to develop effective vaccines or pharmacological treatments to inhibit RSV infection without undesired effects on human health have been unsuccessful. However, RSV infection has been reported to be affected by flavonoids. The mechanisms underlying viral inhibition induced by these compounds are largely unknown, making the development of new drugs difficult. METHODS: To understand the mechanisms induced by flavonoids to inhibit RSV infection, a systems pharmacology-based study was performed using microarray data from primary culture of human bronchial cells infected by RSV, together with compound-proteomic interaction data available for Homo sapiens. RESULTS: After an initial evaluation of 26 flavonoids, 5 compounds (resveratrol, quercetin, myricetin, apigenin, and tricetin) were identified through topological analysis of a major chemical-protein (CP) and protein-protein interacting (PPI) network. In a nonclustered form, these flavonoids regulate directly the activity of two protein bottlenecks involved in inflammation and apoptosis. CONCLUSIONS: Our findings may potentially help uncovering mechanisms of action of early RSV infection and provide chemical backbones and their protein targets in the difficult quest to develop new effective drugs.