Design and screening of tetracycline antibiotics: an in-silico approach

Abstract

A prominent class of broad-spectrum antibiotics known as tetracycline works by inhibiting the synthesis of proteins, which prevents the development of bacteria. Tetracycline resistance is typically attributed to one or more of the following causes: ribosomal binding site mutations, acquisition of mobile genetic elements carrying tetracycline-specific resistance genes, and/or chromosomal mutations that increase the expression of intrinsic resistance mechanisms. In this research, our objective is to virtually plan and conduct in-silico experiments to find tetracycline derivatives with inhibitory capability against tetracycline resistance protein. The tetracycline derivatives were screened using the Data Warrior, Discovery Studio, PyRx, and Swiss ADME web tools. Initially, 19 tetracycline derivatives were primarily screened for ADME and toxicity study followed by docking study. Among the tetracycline derivatives, C1, C11, C12, C14, C16, and C17 were found to be the potential drug-like molecules with binding energies of -8.9 kcal/mol, -8.4 kcal/mol, -8.5 kcal/mol, -7.7 kcal/mol, -7.7 kcal/mol, -8.6 kcal/mol respectively. In particular, C1 was predicted to have a better binding affinity towards the target protein than the others.