In Silico Screening of the DrugBank Database to Search for Possible Drugs against SARS-CoV-2

Abstract

Coronavirus desease 2019 (COVID-19) is responsible for more than 1.80 M deaths worldwide. A Quantitative Structure-Activity Relationships (QSAR) model is developed based on experimental pIC50 values reported for a structurally diverse dataset. A robust model with only five descriptors is found, with values of R2 = 0.897, Q2LOO = 0.854, and Q2ext = 0.876 and complying with all the parameters established in the validation Tropsha’s test. The analysis of the applicability domain (AD) reveals coverage of about 90% for the external test set. Docking and molecular dynamic analysis are performed on the three most relevant biological targets for SARS-CoV-2: main protease, papain-like protease, and RNA-dependent RNA polymerase. A screening of the DrugBank database is executed, predicting the pIC50 value of 6664 drugs, which are IN the AD of the model (coverage = 79%). Fifty-seven possible potent anti-COVID-19 candidates with pIC50 values > 6.6 are identified, and based on a pharmacophore modelling analysis, four compounds of this set can be suggested as potent candidates to be potential inhibitors of SARS-CoV-2. Finally, the biological activity of the compounds was related to the frontier molecular orbitals shapes.

Protein–Ligand Docking in the Machine-Learning Era

“…Recently, Jiankun and coworkers performed docking-based VS using a ultra-large compound library (more than 100 million compounds from ZINC make-on-demand compounds) to discover inhibitors targeting AmpC β-lactamase and D 4 dopamine receptor [ 29 ]. Other databases, such as DrugBank [ 153 , 154 , 155 ] and Human Metabolome Database (HMDB) [ 156 , 157 , 158 , 159 ] are used to repurpose the approved drugs or human metabolites to the novel targets. The next step is to detect the binding site.…”

In silico study of natural compounds from sesame against COVID-19 by targeting Mpro, PLpro and RdRp

“…40–42 (iii) Compounds that can achieve Δ G of −7 kcal mol −1 of lower have high potential to be active in vitro . 43–45 (iv) Compounds with good scores and binding stability should also have good drug-like properties to be active in vitro . 46–48…”

“…[40][41][42] (iii) Compounds that can achieve DG of À7 kcal mol À1 of lower have high potential to be active in vitro. [43][44][45] (iv) Compounds with good scores and binding stability should also have good druglike properties to be active in vitro. [46][47][48] Pi-Pi 3.83 0 a S: the score of a compound placement inside the protein binding pocket.…”

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

“… 563 Other MM/PB(GB)SA-based drug repurposing works considering two or more targets include studies in the literature. 564 − 580 …”