Rapid activity prediction of HIV-1 integrase inhibitors: harnessing docking energetic components for empirical scoring by chemometric and artificial neural network approaches

• Main Authors: Patcharapong Thangsunan, Sila Kittiwachana, Puttinan Meepowpan, Nawee Kungwan, Panchika Prangkio, Supa Hannongbua, Nuttee Suree
• Format: Journal
• Published: 2018
• Subjects: Chemistry; Computer Science; Pharmacology, Toxicology and Pharmaceutics
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84975136186&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/55454
• Institution: Chiang Mai University

© 2016, Springer International Publishing Switzerland. Abstract: Improving performance of scoring functions for drug docking simulations is a challenging task in the modern discovery pipeline. Among various ways to enhance the efficiency of scoring function, tuning of energetic component approach is...