Two new atom centered fragment descriptors and scoring function enhance classification of antibacterial activity

Abstract

Classification of pharmacologic activity of a chemical compound is an essential step in any drug discovery process. We develop two new atom-centered fragment descriptors (vertex indices)--one based solely on topological considerations without discriminating atom or bond types, and another based on topological and electronic features. We also assess their usefulness by devising a method to rank and classify molecules with regard to their antibacterial activity. Classification performances of our method are found to be superior compared to two previous studies on large heterogeneous data sets for hit finding and hit-to-lead studies even though we use much fewer parameters. It is found that for hit finding studies topological features (simple graph) alone provide significant discriminating power, and for hit-to-lead process small but consistent improvement can be made by additionally including electronic features (colored graph). Our approach is simple, interpretable, and suitable for design of molecules as we do not use any physicochemical properties. The singular use of vertex index as descriptor, novel range based feature extraction, and rigorous statistical validation are the key elements of this study.

Dynamic ligand-based pharmacophore modeling and virtual screening to identify mycobacterial cyclopropane synthase inhibitors

“…These snapshots were shown to screen maximum numbers of CmaA1 active compounds. 6 Top scoring compounds of each docking run with each snapshot were analyzed. The compounds present in the top 25% of all the five snapshots were passed to the next level of screening.…”

“…New targets and drug candidates are being explored by researchers across the globe to fulfill the * For correspondence urgent need of new drugs for TB. [5][6][7] These emerging targets include GlgE, enzymes involving mycolic acid cyclopropanation, DprE1/DprE2, MshC, HisG, AtpE, Def and methionine amino peptidase, etc., which are crucial for the actively growing mycobacteria. Few new chemical entities such as dioctylamine, benzothiazinone, dinitrobenzamides, dequalinium chloride, nitrobenzothiazole, diarylquinoline, TMC207, LBK-611 and 2,3-dichloro-1,4-naphthoquinones are in clinical trials.…”

Evolution of Optimal Descriptors

“…2011;Castillo-Garit et al 2012;Castillo-Garit et al 2015). The QSPR/QSAR analysis of peptides (large systems of amino acids) is also important and specific task of medicinal chemistry Almerico et al 2013;Kandel et al 2014;Chen et al 2015). The estimation of ability of optimal descriptors to be a tool to solve the above tasks has been target of a few works (García et al 2011;Garro Martinez et al 2011;Mullen et al 2011;Ibezim et al 2012;Veselinović et al 2013;Li et al 2014).…”