Qureshi, Abid and Rajput, Akanksha and Kaur, Gazaldeep and Kumar, Manoj (2018) HIVprotI: an integrated web based platform for prediction and design of HIV proteins inhibitors. Journal of Cheminformatics, 10 (1). ISSN 1758-2946
Full text not available from this repository. (Request a copy)Abstract
A number of anti-retroviral drugs are being used for treating Human Immunodeficiency Virus (HIV) infection. Due to emergence of drug resistant strains, there is a constant quest to discover more effective anti-HIV compounds. In this endeavor, computational tools have proven useful in accelerating drug discovery. Although methods were published to design a class of compounds against a specific HIV protein, but an integrated web server for the same is lacking. Therefore, we have developed support vector machine based regression models using experimentally validated data from ChEMBL repository. Quantitative structure activity relationship based features were selected for predicting inhibition activity of a compound against HIV proteins namely protease (PR), reverse transcriptase (RT) and integrase (IN). The models presented a maximum Pearson correlation coefficient of 0.78, 0.76, 0.74 and 0.76, 0.68, 0.72 during tenfold cross-validation on IC50 and percent inhibition datasets of PR, RT, IN respectively. These models performed equally well on the independent datasets. Chemical space mapping, applicability domain analyses and other statistical tests further support robustness of the predictive models. Currently, we have identified a number of chemical descriptors that are imperative in predicting the compound inhibition potential. HIVprotI platform ( http://bioinfo.imtech.res.in/manojk/hivproti ) would be useful in virtual screening of inhibitors as well as designing of new molecules against the important HIV proteins for therapeutics development.
| Item Type: | Article |
|---|---|
| Additional Information: | Copyright of this article belongs to Chemistry Central Ltd. in association with BioMed Central. |
| Uncontrolled Keywords: | Algorithm; HIV; Inhibitors; Integrase; Protease; QSAR; Reverse transcriptase; Web server |
| Subjects: | Q Science > QR Microbiology |
| Depositing User: | Dr. K.P.S.Sengar |
| Date Deposited: | 27 Mar 2018 05:37 |
| Last Modified: | 20 Mar 2019 13:44 |
| URI: | http://crdd.osdd.net/open/id/eprint/2022 |
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