HIGH-THROUGHPUT SCREENING AND DYNAMIC STUDIES OF SELECTED COMPOUNDS AGAINST SARS-COV-2

Objective: This study was aimed to analyze the inhibitory effect of the drugs used in nanocarrier as well as nanoparticles formulation based drug delivery system selected from PubChem database literature against 3CLpro (3C-like protease) receptor of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) by implementing several in silico analysis techniques. Methods: This paper detailed a molecular docking-based virtual screening of 5240 compounds previously utilized in nanoparticle and nanocarrier drug delivery systems utilizing AutoDock Vina software on 3CL protease to discover potential inhibitors using a molecular docking technique. Results: According to the results of the screening, the top two compounds, PubChem Id 58823276 and PubChem Id 60838 exhibited a high affinity for the 3CL protease binding region. Their binding affinities were-9.6 and-8.5 kJ/mol, indicating that they were tightly bound to the target receptor, respectively. These results outperformed those obtained using the co-crystallized native ligand, which exhibited a binding affinity of-7.4 kJ/mol. PubChem Id 60838, the main hit compound in terms of both binding affinity and ADMET analysis, displayed substantial deformability after MD simulation. As a result of the VS and molecular docking techniques, novel 3CL protease inhibitors from the PubChem database were discovered using the Lipinski rule of five and functional molecular contacts with the target protein, as evidenced by the findings of this work. Conclusion: The findings suggest that the compounds discovered may represent attractive opportunities for the development of COVID-19 3CLpro inhibitors and that they need further evaluation and investigation.

In Silico Study of Pubchem Compounds for Solanum torvum as Antiviral Agent against SARS-CoV-2

Background: The recent epidemic outbreak of a novel coronavirus called SARS-CoV-2 has caused suffering among many people in the form of respiratory tract infection. Currently, there are no targeted drugs, and effective treatment options remain limited. Objective: In order to rapidly discover new compounds for clinical purposes, in silico drug design and virtual drug screening have been initiated to identify new drug leads that target the main protease of the COVID-19 virus. Mpro is a key CoV enzyme, which plays a pivotal role in mediating viral replication and transcription, making it an attractive drug target for this virus. Methods: The present study was done to investigate the PubChem compounds of an ayurvedic herb Solanum torvum as an effective antiviral agent against COVID-19. The PubChem compounds like Torvoside H, Torvoside A, Torvoside E, Torvoside F, Torvonin A, 2,3,4-trimethyltriacontane, Torvanol A Q27134802, 5-hexatriacontanone, Jurubine, Tritriacontan-3-one, Torvanol A, Chlorogenone Spirostane-3,6-dione of Solanum torvum were downloaded from NCBI PubChem database acting as ligands for protein ligand docking. The 3D structure of the viral MPro (PDB ID: 6yb7) was retrieved from the RCSB PDB database. The active sites and binding sites were analyzed, and Docking molecular simulations were realized among a total of 12 ligands against COVID-19. Results: The PubChem compounds from the fruits of Solanum torvum showed good docking score and protein-ligand interaction, indicating that the PubChem compounds can cure the COVID-19 disease and act as an effective antiviral agent. Conclusion: Most of the PubChem compounds in the fruits of Solanum torvum showed better paramagnetic parameters.

Integration of System Biology Tools to Investigate Huperzine A as an Anti-Alzheimer Agent

Aim: The present study aimed to investigate huperzine A as an anti-Alzheimer agent based on the principle that a single compound can regulate multiple proteins and associated pathways, using system biology tools.Methodology: The simplified molecular-input line-entry system of huperzine A was retrieved from the PubChem database, and its targets were predicted using SwissTargetPrediction. These targets were matched with the proteins deposited in DisGeNET for Alzheimer disease and enriched in STRING to identify the probably regulated pathways, cellular components, biological processes, and molecular function. Furthermore, huperzine A was docked against acetylcholinesterase using AutoDock Vina, and simulations were performed with the Gromacs package to take into account the dynamics of the system and its effect on the stability and function of the ligands.Results: A total of 100 targets were predicted to be targeted by huperzine A, of which 42 were regulated at a minimum probability of 0.05. Similarly, 101 Kyoto Encyclopedia of Genes and Genomes pathways were triggered, in which neuroactive ligand–receptor interactions scored the least false discovery rate. Also, huperzine A was predicted to modulate 54 cellular components, 120 molecular functions, and 873 biological processes. Furthermore, huperzine A possessed a binding affinity of −8.7 kcal/mol with AChE and interacted within the active site of AChE via H-bonds and hydrophobic interactions.

Molecular Docking Approach of Natural Compound from Herbal Medicine in Java against Severe Acute Respiratory Syndrome Coronavirus-2 Receptor

Indonesia's diversity of natural resources presents an intriguing opportunity for the exploration of potential herbal medicines. Numerous compounds, both purified and crude, have been reported to exhibit antiviral activity. The ACE-2 receptor may be a therapeutic target for SARS-CoV-2 infection. We used a search engine to search for herbal medicines with ACE-2 inhibitory activity to predict the potential inhibition of natural compounds (i.e., theaflavin, deoxypodophyllotoxin, gallocatechin, allicin, quercetin, annonamine, Curcumin, 6-gingerol, and cucurbitacin B) to SARS-CoV2 – ACE-2 complex. We performed molecular docking analysis using the ACE-2 protein target from Protein Data Bank. Protein stabilization was carried out to adjust to the body's physiology, carried out using Pymol by removing water atoms and adding hydrogen atoms. Ligands of active compounds from natural resources were selected and downloaded from the PubChem database, then optimized by Pymol software. The complexes of the tested ligand compounds and ACE-2 receptors, which have a bond strength smaller than the control were selected for analysis. Theaflavin, Deoxypodophyllotoxin, Gallocatechin, Curcumin, and Cucurbitacin B had a strong bond affinity than the control ligands. Based on our data, deoxypodophylotoxin and Curcumin had the same interaction amino acid residus compare to the control ligand. This study concludes that deoxypodophyllotoxin and Curcumin have the greatest potential to inhibit the formation of the SARS-Cov2-ACE-2 complex; additionally, these compounds exhibit favorable pharmacological and pharmacodynamic properties. It is suggested that additional research be conducted to determine the biological effects of deoxypodopyllotoxin and Curcumin on ACE-2 receptors.

ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds

Synthetic biology and metabolic engineering rely on computational search tools for predictions of novel biosynthetic pathways to industrially important compounds, many of which are derived from aromatic amino acids. Pathway search tools vary in their scope of covered reactions and compounds, as well as in metrics for ranking and evaluation. In this work, we present a new computational resource called ARBRE: Aromatic compounds RetroBiosynthesis Repository and Explorer. It consists of a comprehensive biochemical reaction network centered around aromatic amino acid biosynthesis and a computational toolbox for navigating this network. ARBRE encompasses over 28’000 known and 100’000 novel reactions predicted with generalized enzymatic reactions rules and over 70’000 compounds, of which 22’000 are known to biochemical databases and 48’000 only to PubChem. Over 1,000 molecules that were solely part of the PubChem database before and were previously impossible to integrate into a biochemical network are included into the ARBRE reaction network by assigning enzymatic reactions. ARBRE can be applied for pathway search, enzyme annotation, pathway ranking, visualization, and network expansion around known biochemical pathways to predict valuable compound derivations. In line with the standards of open science, we have made the toolbox freely available to the scientific community at http://lcsb-databases.epfl.ch/arbre/. We envision that ARBRE will provide the community with a new computational toolbox and comprehensive search tool to predict and rank pathways towards industrially important aromatic compounds.

In silico Analysis of Plant Based Quorum Sensing Inhibitor against Chromobacterium violaceum CviR

Background: Chromobacterium violaceum (C. violaceum), a Gram-negative, facultative anaerobic, non-sporing coccobacillus has a quorum-sensing system consisting of CviI/CviR, a homologous gene. Quorum sensing (QS) is a mechanism of intercellular communication in bacteria that received substantial attention as an alternate strategy for combating bacterial resistance and the development of new anti-infective agents. Methods: DATA SET Information of photochemical from the natural source deposited as a machine readable format in PubChem database was utilized to retrieve the compound for the study. To study ligand - receptor interactions, docking paves way to accomplish the protein ligand interaction was docked through rigid docking CviR protein (PDB ID: 3QP5) was prepared and energy minimized to evaluate the best affinity among the complex. Results: The results showed that the Alpha.,2.Alpha.- Epoxy-1.Beta.- Methyl Cholesta-4,6- Dien-3-One had high affinity for CviR receptor protein and Alpha.,2.Alpha.- Epoxy-1.Beta.- Methyl Cholesta-4,6- Dien-3-One binds to the active site of CviR with binding energy of -9.6 kcal/mol. Conclusion: Overall study concluded that 1. Alpha., 2. Alpha.- Epoxy-1.Beta.-Methyl Cholesta-4,6-Dien-3-One with highest binding affinity for the CviR protein possessing strong inhibitory binding interaction. Hence, we concluded that 1.Alpha.,2.Alpha.-Epoxy-1.Beta.- Methyl Cholesta-4, 6-Dien-3-One good serves as potential an anti-quorum sensing molecule for treating C. violaceum infection.

Comparison of Molecular Geometry Optimization Methods Based on Molecular Descriptors

Various methods (Hartree–Fock methods, semi-empirical methods, Density Functional Theory, Molecular Mechanics) used to optimize a molecule structure feature the same basic approach but differ in the mathematical approximations used. The geometry optimization procedure calculates the energy at an initial geometry of a molecule and then proceeds to search a new geometry with a lower energy. Using the 3D structures collected from the PubChem database, 20 amino acid geometry optimization calculations were performed with several methods. The purpose of the study was to analyze these methods (39) to find the relationship between them and to determine which to use under different circumstances. Cluster analysis and principal component analysis were performed to evaluate the similarities between the different methods. The results after the analysis can classified into three main groups and can be selected accordingly to solve different types of problems.

Screening of β1- and β2-Adrenergic Receptor Modulators through Advanced Pharmacoinformatics and Machine Learning Approaches

Cardiovascular diseases (CDs) are a major concern in the human race and one of the leading causes of death worldwide. β-Adrenergic receptors (β1-AR and β2-AR) play a crucial role in the overall regulation of cardiac function. In the present study, structure-based virtual screening, machine learning (ML), and a ligand-based similarity search were conducted for the PubChem database against both β1- and β2-AR. Initially, all docked molecules were screened using the threshold binding energy value. Molecules with a better binding affinity were further used for segregation as active and inactive through ML. The pharmacokinetic assessment was carried out on molecules retained in the above step. Further, similarity searching of the ChEMBL and DrugBank databases was performed. From detailed analysis of the above data, four compounds for each of β1- and β2-AR were found to be promising in nature. A number of critical ligand-binding amino acids formed potential hydrogen bonds and hydrophobic interactions. Finally, a molecular dynamics (MD) simulation study of each molecule bound with the respective target was performed. A number of parameters obtained from the MD simulation trajectories were calculated and substantiated the stability between the protein-ligand complex. Hence, it can be postulated that the final molecules might be crucial for CDs subjected to experimental validation.

In Silico Study of Vacuolin-1 as an Inhibitor of HSP27 for Precancerous Treatment of Breast Cancer

Breast cancer has a great chance of being cured if it is diagnosed and treated properly in its early stage. The pre-cancer stage is an early stage of cancer development characterized by the overexpression of HSP27. Therefore, HSP27 can be a therapeutic target of cancer. This study aims to analyze whether vacuolin-1, a small drug compound known for its ability to inhibit metastasis, can inhibit HSP27 to prevent precancerous development in breast cancer, as well as its ADME and biosafety aspects. Protein & ligand structures were obtained from RCSB PDB and PubChem database. Preparation was performed with Discovery Studio and PyRx. Drug-likeness/ADME analysis was performed in Swiss-ADME web server. Biosafety analysis was performed in MetaTox web server. Molecular docking was performed using PyRx. The visualization of docking results was performed using Discovery Studio. The docking result between vacuolin-1 and HSP27 showed that vacuolin-1 can act as an HSP27 inhibitor by interacting with S78 residue of HSP27 and blocking its phosphorylation as well as depolymerization process. The drug-likeness characterization result of this compound showed that vacuolin-1 violates one of the four Lipinski's Rule of Five. Biosafety analysis showed that vacuolin-1 has a low toxicity level with an estimated LD50 around 13,016.65 mg/kg.

Evaluation of selected carotenoids of Lycopersicon esculentum variants as therapeutic targets for ‘Alzheimer’s disease: an in silico approach

The seriousness and menace of the worldwide weight of ‘Alzheimer’s disease have been related to a few factors, which incorporate antioxidant system depletion, mutation of proteins, and high expression of cholinesterases due to aging, environmental influence, diet, infectious agents, and hormonal imbalance. Overexpression of cholinesterases has been emphatically connected to ‘Alzheimer’s disease because of the unreasonable hydrolysis of acetylcholine and butyrylcholine. Certain plant phytochemicals, for example, beta-carotenoids, lutein, neoxanthin, and viola-xanthine from Lycopersicon esculentum Mill. Var. esculentum (ESC) and Lycopersicon esculentum Mill. Var. cerasiforme (CER) has been utilized altogether as a therapeutic candidate for the treatment of ‘Alzheimer’s disease. Therefore, this research sought to investigate the drug-likeness of the individual carotenoids as detailed for cholinesterase inhibition in the treatment of ‘Alzheimer’s disease. Four potential cholinesterase inhibitors from ESC and CER were retrieved from the PubChem database. Investigation of their drug-likeness, toxicity prediction, molecular docking, and dynamic simulations were carried out using Molinspiration, PreADMET V.2.0, Patchdock server, and Schrodinger Maestro software respectively. Neoxanthin was ranked the safest with a greater tendency to inhibit the cholinesterases with high binding affinity. In addition, its stability after simulation in a mimicked biological environment suggests its relevance as a potential drug candidate for the treatment of ‘Alzheimer’s disease through the inhibition of cholinesterases.