Development of QSAR models for predicting anti-HIV-1 activity using the Monte Carlo method
作者： Andrey Toropov , Alla Toropova , Ivan Raska , Emilio Benfenati , Giuseppina Gini
DOI: 10.2478/S11532-012-0166-3
关键词: Simplified molecular-input line-entry system 、 Computational chemistry 、 Test set 、 Chemistry 、 Monte Carlo method 、 Invariant (mathematics) 、 Molecule 、 Covalent bond 、 Nanotechnology 、 Quantitative structure–activity relationship 、 Chemical bond
摘要: The CORAL software ( http://www.insilico.eu/coral/ ) has been examined as a tool for modeling anti-HIV-1 activity by quantitative structure — relationships (QSAR) three different sets: (i) TIBO derivatives (n=82) (ii) of 2-amino-6-arylsulfonylbenzonitriles and their congeners (n=64), (iii) the measured binding affinity fullerene-based HIV-1 PR inhibitors (n=48). A new global invariant ATOMPAIR molecular which can be calculated with simplified input line entry system (SMILES) was studied. is an indicator joint presence pairs chemical elements (F, Cl, Br, N, O, S, P) types bonds (double covalent bond, triple stereo bond). Six random splits into sub-training, calibration, test set were each set. For aforementioned sets, use in process improves predictive potential models six splits.
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