Structure features of peptide-type SARS-CoV main protease inhibitors: Quantitative structure activity relationship study

Vijay H Masand; Siddhartha Akasapu; Ajaykumar Gandhi; Vesna Rastija; Meghshyam K Patil

doi:10.1016/j.chemolab.2020.104172

Structure features of peptide-type SARS-CoV main protease inhibitors: Quantitative structure activity relationship study

Chemometr Intell Lab Syst. 2020 Nov 15:206:104172. doi: 10.1016/j.chemolab.2020.104172. Epub 2020 Oct 3.

Authors

Vijay H Masand¹, Siddhartha Akasapu², Ajaykumar Gandhi³, Vesna Rastija⁴, Meghshyam K Patil⁵

Affiliations

¹ Department of Chemistry, Vidya Bharati Mahavidyalaya, Amravati, Maharashtra, 444 602, India.
² Corden Pharma, Colorado, USA.
³ Department of Chemistry, Government College of Arts and Science, Aurangabad, Maharashtra, 431 004, India.
⁴ Department of Agroecology and Environmental Protection, Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia.
⁵ Department of Chemistry, Osmanabad Sub-Centre Dr. Babasaheb Ambedkar Marathwada University, Osmanabad, Maharashtra, India.

Abstract

In the present work, an extensive QSAR (Quantitative Structure Activity Relationships) analysis of a series of peptide-type SARS-CoV main protease (MPro) inhibitors following the OECD guidelines has been accomplished. The analysis was aimed to identify salient and concealed structural features that govern the MPro inhibitory activity of peptide-type compounds. The QSAR analysis is based on a dataset of sixty-two peptide-type compounds which resulted in the generation of statistically robust and highly predictive multiple models. All the developed models were validated extensively and satisfy the threshold values for many statistical parameters (for e.g. R² = 0.80-0.82, Q² _loo = 0.74-0.77, Q ² _LMO = 0.66-0.67). The developed QSAR models identified number of sp² hybridized Oxygen atoms within seven bonds from aromatic Carbon atoms, the presence of Carbon and Nitrogen atoms at a topological distance of 3 and other interrelations of atom pairs as important pharmacophoric features. Hence, the present QSAR models have a good balance of Qualitative (Descriptive QSARs) and Quantitative (Predictive QSARs) approaches, therefore useful for future modifications of peptide-type compounds for anti- SARS-CoV activity.

Keywords: ADMET, Absorption, Distribution, Metabolism, Excretion and Toxicity; COVID-19; GA, Genetic algorithm; MLR, Multiple linear Regression; OECD, Organisation for Economic Co-operation and Development; OFS, Objective Feature Selection; OLS, Ordinary Least Square; Peptide-type compounds; QSAR; QSAR, Quantitative structure-activity analysis; QSARINS, QSAR Insubria; SARS-CoV; SARS-CoV-2; SFS, Subjective Feature Selection; SMILES, Simplified molecular-Input Line-Entry System; WHO, World health organization.