InterCriteria Analysis Approach for Decision-Making in Virtual Screening: Comparative Study of Various Scoring Functions

Abstract

AbstractThe goal of this study is to evaluate the ability of the recently developed InterCriteria Analysis (ICrA) approach to support decision making in computer-aided drug design projects. ICrA is a method for multicriteria analysis based on two fundamental mathematical concepts – index matrices and intuitionistic fuzzy sets. The approach is designed to distinguish possible relations in the behavior of pairs of criteria when multiple objects are considered, meanwhile allowing to account for the uncertainty in information processing. In this study, ICrA has been applied to examine diverse scoring functions, implemented in AMMOS, FRED, and X-Score software platforms for docking performance. Two protein targets have been considered in this study – estrogen receptor and neuraminidase, selected for dissimilar physicochemical properties and topology of their binding sites. The ability of the scoring functions to evaluate the interactions between protein targets and receptor-based focused libraries, based on the ChemBridge diversity set of drug-like molecules, has been examined, and the relationships between the scoring functions have been analyzed, applying ICrA.