Systematic approach for enrichment of docking outcome using consensus scoring functions

Abstract

Traditional drug discovery is an expensive and time consuming process. Pharmaceutical industry suffers from a huge attrition due to last stage failure in traditional drug discovery. Bioinformatics principles can be utilized to overcome this pressure and speedup the process of drug discovery. Computer aided drug design is a remedy to avoid this loss. Drug design means designing the ligand that has high affinity towards target protein. This can be achieved by Virtual Screening. Ligand based virtual screening utilizes information from the ligand about the target. It is a ligand centric approach. The availability of three dimensional structures of protein targets and their possible ligands are utilized for identification and optimization of lead molecules (positive hits) in Structure based virtual screening. It is a target centric approach. To find out fit poses of ligand and its affinity at the active site of target Molecular Docking is done. Molecular docking is tool that contains search algorithm and scoring function. Search algorithms predict the binding modes of a target and fit ligand conformations towards the target. Scoring function is involved in prediction of the affinity of a ligand to bind to a protein target. There are various plat forms and scoring functions for predicting ligand – protein interactions. Consensus Scoring is a technique of combing information from multiple scoring functions and gives relatively accurate result when compared to single scoring function. It shows improvement in terms of quality of hit scores, false positive rate and enrichment. Consensus Scoring gives better, accurate and consistent results across the receptor systems when compared to individual or single scoring functions.

Molecular Docking as a Therapeutic Approach for Targeting Cancer Stem Cell Metabolic Processes

“…Searching algorithms can be defined as a process that can lead to exploring the predominant and effective matching docking modes of ligand to the molecular target among the myriad configurations. Because a large number of binding modes are actually found between a ligand and a biological target molecule, searching algorithms not only can consider the optimum possible orientations of the ligand with the target but also can be an economical and time-saving solution in the docking process (Meng et al, 2011;Salmaso and Moro, 2018) (Madhavilatha and Babu, 2019;Sethi et al, 2019).…”

“…Scoring function refers to a process in which putative docking modes are ranked by evaluating their binding affinity and lowest binding energy to achieve top-ranked poses between a ligand and a target molecule. Force field function, Empirical scoring functions, knowledge based scoring functions, knowledge-based potentials, machine learning based scoring functions, comparative assessment of scoring functions, physics-based methods, and descriptor-based scoring functions are some of the examples of scoring function classifications in molecular docking ( Madhavilatha and Babu, 2019 ; Sethi et al, 2019 ).…”