A Computational Study of Some Cancer Causing S100 Proteins Interacting with A Ligand, Parecoxib and Investigation of Drug Likeness Potential of the Ligand
Abstract
Arup Kumar Sarma and Rajendra Kumar
In silico method of drug discovery plays an important role witnessing a cost effective and highly accurate method. Computer- aided drug screening by molecular docking, molecular dynamics (MD) simulation and MMPBSA calculation can offer an efficient approach in identifying promising drug candidates for cancer or other disease. In this study, computational approach is performed by Autodock Vina, a docking software followed by MD simulation using Gromacs-2024.5 on Ubuntu command prompt. Free energy calculation is performed by Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA), a different type of MD simulation technic involving forcefield and solvation terms. MMPBSA calculate enthalpic and entropic contributions to the ligand free energy. Results obtained using these softwares are close to experimental results. Proteins of S100 class are vital to cancer diseases. Functions of the affected proteins can be altered or inhibited with the ligands having strong non-bonded interactions. Ligands are also selected on the basis of having drug like properties. In this study we select Parecoxib as ligand and found high degree of interaction with S100A11 protein.