HIVCoR: A sequence-based tool for predicting HIV-1 CRF01_AE coreceptor usage
Institution:
1. Research Institute for Health Sciences, Chiang Mai University, Chiangmai 50200, Thailand;2. Faculty of Associated Medical Sciences, Chiang Mai University, Chiangmai 50200, Thailand;3. Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand;1. Department of Chemistry, Annamalai University, Annamalainagar, Chidambaram 608 002, India;2. Laboratory of Green Chemistry, Lappeenranta University of Technology, Sammonkatu 12, FI-50130 Mikkeli, Finland;1. Anadolu University, Science Faculty, Department of Physics, 26470, Eskişehir, Turkey;2. Eskişehir Osmangazi University, Art and Sciences Faculty, Department of Physics, Eskişehir, Turkey;3. Eskişehir Osmangazi University, Central Research Laboratory, Application and Research Centre, Eskişehir, Turkey;1. Department of Chemistry, Xinzhou Teachers University, Xinzhou 034000, Shanxi, China;2. Nanocluster Laboratory, Institute of Molecular Science, Shanxi University, Taiyuan 030006, China
Abstract:
Determination of HIV-1 coreceptor usage is strongly recommended before starting the coreceptor-specific inhibitors for HIV treatment. Currently, the genotypic assays are the most interesting tools due to they are more feasible than phenotypic assays. However, most of prediction models were developed and validated by data set of HIV-1 subtype B and C. The present study aims to develop a powerful and reliable model to accurately predict HIV-1 coreceptor usage for CRF01_AE subtype called HIVCoR. HIVCoR utilized random forest and support vector machine as the prediction model, together with amino acid compositions, pseudo amino acid compositions and relative synonymous codon usage frequencies as the input feature. The overall success rate of 93.79% was achieved from the external validation test on the objective benchmark dataset. Comparison results indicated that HIVCoR was superior to other bioinformatics tools and genotypic predictors. For the convenience of experimental scientists, a user-friendly webserver has been established at http://codes.bio/hivcor/.
