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.
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We thankfully acknowledge the financial support received from the Department of Biotechnology (DBT), Government of India, New Delhi, India.
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Kandel, D.D., Raychaudhury, C. & Pal, D. Two new atom centered fragment descriptors and scoring function enhance classification of antibacterial activity. J Mol Model 20, 2164 (2014). https://doi.org/10.1007/s00894-014-2164-1
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DOI: https://doi.org/10.1007/s00894-014-2164-1