Molecular and Structural Analysis of Specific Mutations from Saudi Isolates of SARS-CoV-2 RNA-Dependent RNA Polymerase and their Implications on Protein Structure and Drug-Protein Binding

Selected phytochemicals of Momordica charantia L. as potential anti-DENV-2 through the docking, DFT and molecular dynamic simulation

Dengue fever is now one of the major global health concerns particularly for tropical and sub-tropical countries. However, there has been no FDA approved medication to treat dengue fever. Researchers are looking into DENV NS5 RdRp protease as a potential therapeutic target for discovering effective anti-dengue agents. The aim of this study to discover dengue virus inhibitor from a set of five compounds from Momordica charantia L. using a series of in-silico approaches. The compounds were docked into the active area of the DENV-2 NS5 RdRp protease to obtain the hit compounds. The successful compounds underwent additional testing for a study on drug-likeness similarity. Our study obtained Momordicoside-I as a lead compound which was further exposed to the Cytochrome P450 (CYP450) toxicity analysis to determine the toxicity based on docking scores and drug-likeness studies. Moreover, DFT studies were carried out to calculate the thermodynamic, molecular orbital and electrostatic potential properties for the lead compound. Moreover, the lead compound was next subjected to molecular dynamic simulation for 200 ns in order to confirm the stability of the docked complex and the binding posture discovered during docking experiment. Overall, the lead compound has demonstrated good medication like qualities, non-toxicity, and significant binding affinity towards the DENV-2 RdRp enzyme.Communicated by Ramaswamy H. Sarma.

Unveiling MurE ligase potential inhibitors for treating multi-drug resistant Acinetobacter baumannii

Acinetobacter baumannii is an opportunistic pathogen with ability to cause serious infection such as bacteremia, ventilator associated pneumonia, and wound infections. As strains of A. baumannii are resistant to almost all clinically used antibiotics and with the emergence of carbapenems resistant phenotypes warrants the search for novel antibiotics. Considering this, herein, a series of computer aided drug designing approach was utilized to search novel chemical scaffolds that bind stronger to MurE ligase enzyme of A. baumannii, which is involved peptidoglycan synthesis. The work identified LAS_22461675, LAS_34000090 and LAS_51177972 compounds as promising binding molecules with MurE enzyme having binding energy score of -10.5 kcal/mol, -9.3 kcal/mol and -8.6 kcal/mol, respectively. The compounds were found to achieve docked inside the MurE substrate binding pocket and established close distance chemical interactions. The interaction energies were dominated by van der Waals and less contributions were seen from hydrogen bonding energy. The dynamic simulation assay predicted the complexes stable with no major global and local changes noticed. The docked stability was also validated by MM/PBSA and MM/GBSA binding free energy methods. The net MM/GBSA binding free energy of LAS_22461675 complex, LAS_34000090 complex and LAS_51177972 complex is -26.25 kcal/mol, -27.23 kcal/mol and -29.64 kcal/mol, respectively. Similarly in case of MM-PBSA, the net energy value was in following order; LAS_22461675 complex (-27.67 kcal/mol), LAS_34000090 complex (-29.94 kcal/mol) and LAS_51177972 complex (-27.32 kcal/mol). The AMBER entropy and WaterSwap methods also confirmed stable complexes formation. Further, molecular features of the compounds were determined that predicted compounds to have good druglike properties and pharmacokinetic favorable. The study concluded the compounds to good candidates to be tested by in vivo and in vitro experimental assays.Communicated by Ramaswamy H. Sarma.

The Lost and Found: Unraveling the Functions of Orphan Genes

Orphan Genes (OGs) are a mysterious class of genes that have recently gained significant attention. Despite lacking a clear evolutionary history, they are found in nearly all living organisms, from bacteria to humans, and they play important roles in diverse biological processes. The discovery of OGs was first made through comparative genomics followed by the identification of unique genes across different species. OGs tend to be more prevalent in species with larger genomes, such as plants and animals, and their evolutionary origins remain unclear but potentially arise from gene duplication, horizontal gene transfer (HGT), or de novo origination. Although their precise function is not well understood, OGs have been implicated in crucial biological processes such as development, metabolism, and stress responses. To better understand their significance, researchers are using a variety of approaches, including transcriptomics, functional genomics, and molecular biology. This review offers a comprehensive overview of the current knowledge of OGs in all domains of life, highlighting the possible role of dark transcriptomics in their evolution. More research is needed to fully comprehend the role of OGs in biology and their impact on various biological processes.

Advanced network pharmacology study reveals multi-pathway and multi-gene regulatory molecular mechanism of Bacopa monnieri in liver cancer based on data mining, molecular modeling, and microarray data analysis

Liver cancer is a malignant tumor that grows on the surface or inside the liver. The leading cause is a viral infection with hepatitis B or C virus. Natural products and their structural analogues have historically made a major contribution to pharmacotherapy, especially for cancer. A list of studies evidences the therapeutic efficacy of Bacopa monnieri against liver cancer, but the precise molecular mechanism is yet to be discovered. This study combines data mining, network pharmacology, and molecular docking analysis to potentially revolutionize liver cancer treatment by identifying effective phytochemicals. Initially, the information on active constituents of B. monnieri and target genes of both liver cancer and B. monnieri were retrieved from literature as well as from publicly available databases. Based on the matching results between B. monnieri potential targets and liver cancer targets, the protein-protein interaction (PPI) network was constructed using the STRING database and imported into Cytoscape for screening of hub genes based on their degree of connectivity. Later, the interactions network between compounds and overlapping genes was constructed using Cytoscape software to analyze the network pharmacological prospective effects of B. monnieri on liver cancer. Gene Ontology (GO) and KEGG pathway analysis of hub genes revealed that these genes are involved in the cancer-related pathway. Lastly, the expression level of core targets was analyzed using microarray data (GSE39791, GSE76427, GSE22058, GSE87630, and GSE112790). Further, the GEPIA server and PyRx software were used for survival and molecular docking analysis, respectively. In summary, we proposed that quercetin, luteolin, apigenin, catechin, epicatechin, stigmasterol, beta-sitosterol, celastrol, and betulic acid inhibit tumor growth by affecting tumor protein 53 (TP53), interleukin 6 (IL6), RAC-alpha serine/threonine protein kinases 1 (AKT1), caspase-3 (CASP3), tumor necrosis factor (TNF), jun proto-oncogene (JUN), heat shot protein 90 AA1 (HSP90AA1), vascular endothelial growth factor A (VEGFA), epidermal growth factor receptor (EGFR), and SRC proto-oncogene (SRC). Through, microarray data analysis, the expression level of JUN and IL6 were found to be upregulated while the expression level of HSP90AA1 was found to be downregulated. Kaplan-Meier survival analysis indicated that HSP90AA1 and JUN are promising candidate genes that can serve as diagnostic and prognostic biomarkers for liver cancer. Moreover, the molecular docking and molecular dynamic simulation of 60ns well complemented the binding affinity of the compound and revealed strong stability of predicted compounds at the docked site. Calculation of binding free energies using MMPBSA and MMGBSA validated the strong binding affinity between the compound and binding pockets of HSP90AA1 and JUN. Despite that, in vivo and in vitro studies are mandatory to unveil pharmacokinetics and biosafety profiles to completely track the candidature status of B. monnieri in liver cancer.

Targeting Toxoplasma gondii ME49 TgAPN2: A Bioinformatics Approach for Antiparasitic Drug Discovery

As fewer therapeutic options are available for treating toxoplasmosis, newer antiparasitic drugs that can block TgAPN2 M1 aminopeptidase are of significant value. Herein, we employed several computer-aided drug-design approaches with the objective of identifying drug molecules from the Asinex library with stable conformation and binding energy scores. By a structure-based virtual screening process, three molecules—LAS_52160953, LAS_51177972, and LAS_52506311—were identified as promising candidates, with binding affinity scores of −8.6 kcal/mol, −8.5 kcal/mol, and −8.3 kcal/mol, respectively. The compounds produced balanced interacting networks of hydrophilic and hydrophobic interactions, vital for holding the compounds at the docked cavity and stable binding conformation. The docked compound complexes with TgAPN2 were further subjected to molecular dynamic simulations that revealed mean RMSD for the LAS_52160953 complex of 1.45 Å), LAS_51177972 complex 1.02 Å, and LAS_52506311 complex 1.087 Å. Another round of binding free energy validation by MM-GBSA/MM-PBSA was done to confirm docking and simulation findings. The analysis predicted average MM-GBSA value of <−36 kcal/mol and <−35 kcal/mol by MM-PBSA. The compounds were further classified as appropriate candidates to be used as drug-like molecules and showed favorable pharmacokinetics. The shortlisted compounds showed promising biological potency against the TgAPN2 enzyme and may be used in experimental validation. They may also serve as parent structures to design novel derivatives with enhanced biological potency.

Identification of novel inhibitors against hantaviruses through 2D fingerprinting and molecular modeling approaches

With the immensely growing outbreaks of hantavirus with still no effective treatment available, there is an urgent need of exploring new computational approaches which will target potential virulent proteins that will eventually reduce its growth. In this study, an envelope glycoprotein, Gn, was targeted. The glycoproteins, which are the sole targets of neutralizing antibodies, drive virus entry via receptor-mediated endocytosis and endosomal membrane fusion. Inhibitors are herein proposed to negate its action mechanism. On the basis of the scaffolds of favipiravir, a FDA compound already used against hantavirus, a library was designed using a 2D fingerprinting approach. Upon molecular docking analysis, the top four docked compounds-(1) favipiravir (-4.5 kcal/mol), (2) N-hydroxy-3-oxo-3, 4-dihydropyrazine-2-carboxamide (-4.7 kcal/mol), (3) N, 5, 6-trimethyl-2-oxo-1H-pyrazine-3-carboxamide (-4.5 kcal/mol), and (4) 3-propyl-1H-pyrazin-2-one (-3.8)-were prioritized on the basis of the lowest binding energies score. Through molecular docking, the best-categorized compound was subjected to molecular dynamics simulation for a 100-ns time span. Molecular dynamics sheds light on each ligand behavior within the active site. Among the four complexes, only favipiravir and 6320122 compound were found to be stable inside the pocket. This is due to the presence of common rings, pyrazine and carboxamide ring, which make a significant interaction with active key residues Furthermore, the MMPB/GBSA binding free energy analysis calculated for all complexes supported the dynamics results by calculating the most stable values for favipiravir complex (-9.9933 and -8.6951 kcal/mol) and for 6320122 compound complex (-13.8675 and -9.3439 kcal/mol), which demonstrated that the selected compounds have a proper binding affinity with the targeted proteins. The hydrogen bond analysis similarly revealed a strong bonding interaction. The results yielded a strong interaction between the enzyme and the inhibitor throughout the simulation; thus, the inhibitor has the potential to become a lead compound and could be subjected to experimental evaluation to unveil their blockage ability.

Discovery of potential phytochemicals as inhibitors of TcdB, a major virulence factors of Clostridioides difficile

Clostridioides difficile is a gram-positive bacterium which is associated with different gastrointestinal related infections, and the numbers of cases related to it are continuously increasing in the past few years. Owing to high prevalence and development of resistance towards available antibiotics, it is required to develop new therapeutics to combat C. difficile infection. The current study was aimed to identify novel phytochemicals that could bind and inhibits the TcdB, an exotoxin which is required for the pathogenesis of bacteria, and hence can be considered as the future drug candidates against C. difficile. ∼2500 therapeutically important phyto-compounds were docked against the active sites of TcdB protein by using AutoDock-Vina software. The interactions between the ligands and the binding site of the top five docked complexes, based on the docking scores, were further elucidated by Molecular Dynamics Simulations of 500 ns, Molecular Mechanics Energies combined with the Poisson-Boltzmann and Surface Area (MMPBSA) or Generalized Born and Surface Area (MMGBSA), and WaterSwap Analysis. Findings of molecular docking suggested that natural compounds A183, A704, A1528, A2083, and A2129 with distinct chemical scaffolds are best docked in the binding site of TcdB and their bonding remained stable throughout the simulation studies of 500 ns. Compounds A2129 and A704 can be considered as prospective drug candidates against Clostridioides difficile, however, further wet lab experiments are needed to confirm our study.Communicated by Ramaswamy H. Sarma.