Subtractive proteomics approach to Unravel the druggable proteins of the emerging pathogen Waddlia chondrophila and drug repositioning on its MurB protein.

Waddlia chondrophila is an emerging pathogen that has been implicated in numerous unpropitious pregnancy events in humans and ruminants. Taking into account its association with abortigenic events, possible modes of transmission, and future risk, immediate clinical measures are required to prevent widespread damage caused by this organism and hence this study. Here, a subtractive proteomics approach was employed to identify druggable proteins of W. chondrophila. Considering the essential genes, antibiotic resistance proteins, and virulence factors, 676 unique important proteins were initially identified for this bacterium. Afterward, NCBI BLASTp performed against human proteome identified 223 proteins that were further pushed into KEGG Automatic Annotation Server (KAAS) for automatic annotation. Using the information from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database 14 Waddlia specific metabolic pathways were identified with respect to humans. Analyzing the data from KAAS and KEGG databases, forty-eight metabolic pathway-dependent, and seventy metabolic pathway independent proteins were identified. Standalone BLAST search against DrugBank FDA approved drug targets revealed eight proteins that are finally considered druggable proteins. Prediction of three-dimensional structures was done for the eight proteins through homology modeling and the Ramachandran plot model showed six models as a valid prediction. Finally, virtual screening against MurB protein was performed using FDA approved drugs to employ the drug repositioning strategy. Three drugs showed promising docking results that can be used for therapeutic purposes against W. chondrophila following the clinical validation of the study.

Antiviral Peptides as Promising Therapeutics against SARS-CoV-2.

Over 50 peptides, which were known to inhibit SARS-CoV-1, were computationally screened against the receptor-binding domain (RBD) of the spike protein of SARS-CoV-2. Based on the binding affinity and interaction, 15 peptides were selected, which showed higher affinity compared to the α-helix of the human ACE2 receptor. Molecular dynamics simulation demonstrated that two peptides, S2P25 and S2P26, were the most promising candidates, which could potentially block the entry of SARS-CoV-2. Tyr489 and Tyr505 residues present in the "finger-like" projections of the RBD were found to be critical for peptide interaction. Hydrogen bonding and hydrophobic interactions played important roles in prompting peptide-protein binding and interaction. Structure-activity relationship indicated that peptides containing aromatic (Tyr and Phe), nonpolar (Pro, Gly, Leu, and Ala), and polar (Asn, Gln, and Cys) residues were the most significant contributors. These findings can facilitate the rational design of selective peptide inhibitors targeting the spike protein of SARS-CoV-2.

Predicting and Designing Epitope Ensemble Vaccines against HTLV-1.

The infection mechanism and pathogenicity of Human T-lymphotropic virus 1 (HTLV-1) are ambiguously known for hundreds of years. Our knowledge about this virus is recently emerging. The purpose of the study is to design a vaccine targeting the envelope glycoprotein, GP62, an outer membrane protein of HTLV-1 that has an increased number of epitope binding sites. Data collection, clustering and multiple sequence alignment of HTLV-1 glycoprotein B, variability analysis of envelope Glycoprotein GP62 of HTLV-1, population protection coverage, HLA-epitope binding prediction, and B-cell epitope prediction were performed to predict an effective vaccine. Among all the predicted peptides, ALQTGITLV and VPSSSTPL epitopes interact with three MHC alleles. The summative population protection coverage worldwide by these epitopes as vaccine candidates was found nearly 70%. The docking analysis revealed that ALQTGITLV and VPSSSTPL epitopes interact strongly with the epitope-binding groove of HLA-A*02:03, and HLA-B*35:01, respectively, as this HLA molecule was found common with which every predicted epitope interacts. Molecular dynamics simulations of the docked complexes show they form stable complexes. So, these potential epitopes might pave the way for vaccine development against HTLV-1.

Halogenated derivatives of methotrexate as human dihydrofolate reductase inhibitors in cancer chemotherapy.

Methotrexate is a widely used anti-metabolite in cancer chemotherapy. A series of halogenated drugs is designed from Methotrexate to assess their interactions with human dihydrofolate reductase. The aim of this study is to evaluate the performance of the modified drugs compared to the parent Methotrexate. Density Functional Theory is employed to optimize these drugs. Molecular docking calculation of these optimized drugs against dihydrofolate reductase is performed to find out binding affinity. In addition, molecular dynamics simulation is considered for the complexes of best two modified drugs with their receptors. Modifications by the halogens show significant changes in the charge distribution, dipole moment, thermodynamic stability, enthalpy and free energy. The highest binding affinity value (-36.401 KJ/mol) was obtained for M14. Hybrid quantum mechanics/molecular mechanics calculation shows a binding energy of -255.140 KJ/mol. Modified drugs have significant hydrogen and non-covalent bonding interactions with amino acids of the receptor. Molecular dynamics simulation disclosed that the root-mean-square-deviation of the alpha carbon associated with M6-1KMV and M14-1KMV complexes is 2.367 Å and 2.622 Å, respectively. Moreover, the interactions between modified drugs and receptor are mostly persevered in 25 nanosecond molecular dynamics simulation. Ensemble-based docking also confirmed that modified drugs show strong non-bonding interactions with different crystallographic and molecular dynamics based conformers. The best scored drugs show considerable pharmacokinetic properties. Modified derivatives M5, M6, M8, M10, M13 and M14 show the better binding affinity and a good number of hydrogen and other non-bonding interactions with the target protein which are similar to other anticancer drugs.Communicated by Ramaswamy H. Sarma.

Prediction of Deleterious Non-synonymous SNPs of Human STK11 Gene by Combining Algorithms, Molecular Docking, and Molecular Dynamics Simulation.

Serine-threonine kinase11 (STK11) is a tumor suppressor gene which plays a key role in regulating cell growth and apoptosis. It is widely known as a multitasking kinase and engaged in cell polarity, cell cycle arrest, chromatin remodeling, energy metabolism, and Wnt signaling. The substitutions of single amino acids in highly conserved regions of the STK11 protein are associated with Peutz-Jeghers syndrome (PJS), which is an autosomal dominant inherited disorder. The abnormal function of the STK11 protein is still not well understood. In this study, we classified disease susceptible single nucleotide polymorphisms (SNPs) in STK11 by using different computational algorithms. We identified the deleterious nsSNPs, constructed mutant protein structures, and evaluated the impact of mutation by employing molecular docking and molecular dynamics analysis. Our results show that W239R and W308C variants are likely to be highly deleterious mutations found in the catalytic kinase domain, which may destabilize structure and disrupt the activation of the STK11 protein as well as reduce its catalytic efficiency. The W239R mutant is likely to have a greater impact on destabilizing the protein structure compared to the W308C mutant. In conclusion, these mutants can help to further realize the large pool of disease susceptibilities linked with catalytic kinase domain activation of STK11 and assist to develop an effective drug for associated diseases.

Molecular Recognition of Azelaic Acid and Related Molecules with DNA Polymerase I Investigated by Molecular Modeling Calculations.

Molecular recognition has central role on the development of rational drug design. Binding affinity and interactions are two key components which aid to understand the molecular recognition in drug-receptor complex and crucial for structure-based drug design in medicinal chemistry. Herein, we report the binding affinity and the nonbonding interactions of azelaic acid and related compounds with the receptor DNA polymerase I (2KFN). Quantum mechanical calculation was employed to optimize the modified drugs using B3LYP/6-31G(d,p) level of theory. Charge distribution, dipole moment and thermodynamic properties such as electronic energy, enthalpy and free energy of these optimized drugs are also explored to evaluate how modifications impact the drug properties. Molecular docking calculation was performed to evaluate the binding affinity and nonbonding interactions between designed molecules and the receptor protein. We notice that all modified drugs are thermodynamically more stable and some of them are more chemically reactive than the unmodified drug. Promise in enhancing hydrogen bonds is found in case of fluorine-directed modifications as well as in the addition of trifluoroacetyl group. Fluorine participates in forming fluorine bonds and also stimulates alkyl, pi-alkyl interactions in some drugs. Designed drugs revealed increased binding affinity toward 2KFN. A1, A2 and A3 showed binding affinities of -8.7, -8.6 and -7.9 kcal/mol, respectively against 2KFN compared to the binding affinity -6.7 kcal/mol of the parent drug. Significant interactions observed between the drugs and Thr358 and Asp355 residues of 2KFN. Moreover, designed drugs demonstrated improved pharmacokinetic properties. This study disclosed that 9-octadecenoic acid and drugs containing trifluoroacetyl and trifluoromethyl groups are the best 2KFN inhibitors. Overall, these results can be useful for the design of new potential candidates against DNA polymerase I.

Multiple receptor conformers based molecular docking study of fluorine enhanced ethionamide with mycobacterium enoyl ACP reductase (InhA).

A major limitation in current molecular docking method is that of failure to account for receptor flexibility. Herein we report multiple receptor conformers based molecular docking as a practical alternative to account for the receptor flexibility. Multiple (forty) conformers of Mycobacterium Enoyl ACP Reductase (InhA) are generated from Molecular Dynamics simulation and twenty crystallographic structures of InhA bound to different inhibitors are obtained from the Protein Data Bank. Fluorine directed modifications are performed to currently available anti-tuberculosis drug ethionamide. The modified drugs are optimized using B3LYP 6-31G (d,p) level of theory. Dipole moment, frontier orbital gap and thermodynamical properties such as electronic energy, enthalpy and Gibbs free energy of these optimized drugs are investigated. These drugs are subsequently docked against the conformers of InhA. Molecular docking against multiple InhA conformations show variation in ligand binding affinity and suggest that Ser94, Gly96, Lys165 and Ile194 amino acids play critical role on strong drug-InhA interaction. Modified drug N1 showed greater binding affinity compared to EN in most conformations. Structure of PDB ID: 2NSD and snapshot conformer at 5.5ns show most favorable binding with N1 compared to other conformers. Fluorine participates in forming fluorine bonds and contributes significantly in increasing binding affinity. Our study reveal that addition of trifluoromethyl group explicitly shows promise in improving thermodynamic properties and in enhancing hydrogen bonding and non-bonded interactions. Molecular dynamics (MD) simulation show that EN and N1 remained in the binding pocket similar to the docked pose of EN-InhA and E1-InhA complexes and also suggested that InhA binds to its inhibitor in inhibitor-induced folding manner. ADMET calculations predict modified drugs to have improved pharmacokinetic properties. Our study concludes that multiple receptor conformers based molecular docking can be an alternative to study the effect of receptor flexibility in ligand binding and fluorine directed modifications can improve drug efficacy.