Structural screening of HIV-1 protease/inhibitor docking by non-parametric binomial distribution test

• Main Authors: Piyarat Nimmanpipug, Vannajan Sanghiran Lee, Jeerayut Chaijaruwanich, Sukon Prasitwattanaseree, Patrinee Traisathit
• Format: Conference Proceeding
• Published: 2018
• Subjects: Computer Science; Mathematics
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=34548057878&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/60985
• Institution: Chiang Mai University

Attempts have been made to predict the binding structures of the human immunodeficiency virus-1 protease (HIV-1Pr) with various inhibitors within the shortest simulation time consuming. The purpose here is to improve the structural prediction by using statistical approach. We use a combination of molecular docking and non-parametric binomial distribution test considering the combination of binding energy, hydrogen bonding, and hydrophobichydrophilic interaction in term of binding residues to select the most probable binding structure. In this study, the binding of HTV-1Pr and two inhibitors: Saquinavir and Litchi chinensis extracts (3-oxotrirucalla-7, 24-dien-21-oic acid) were investigated. Each inhibitor was positioned in the active site of HIV-1Pr in many different ways using Lamarckian genetic algorithm and then score each orientation by applying a reasonable evaluation function by AutoDock3.0 program. The results from search methods were screened out using nonparametric binomial distribution test and compared with the binding structure from explicit molecular dynamic simulation. Both complexes from statistical selected docking simulation were found to be comparable with those from X-ray diffraction analysis and explicit molecular dynamic simulation structures. © Springer-Verlag Berlin Heidelberg 2007.