Computational Study of CCR5 Antagonist with Support Vector Machines and Three Dimensional Quantitative Structure Activity Relationship Methods

CCR5 is the key receptor of HIV-1 virus entry into host cells and it becomes an attractive target for antiretroviral drug design. To date, six types of CCR5 antagonist were synthesized and evaluated. To search more potent bio-active compounds, non-linear support vector machine was used to construct the relationship models for 103 oximino-piperidino-piperidine CCR5 antagonists. Then, comparative molecular field analysis and comparative molecular similarity indices analysis models were constructed after alignment with their common substructure. Twenty-one structural diverse compounds, which were not included in the support vector machine, comparative molecular field analysis, and comparative molecular similarity indices analysis models, validated these models. The results show that these models possess good predictive ability. When comparing between support vector machine and 3D-quantitative structure activity relationship models, the results obtained from these two methods are compatible. However, 3D-quantitative structure activity relationship model is significantly better than support vector machine model and previous reported pharmacophore model. These models can help us to make quantitative prediction of their bio-activities before in vitro and in vivo stages.