Literature DB >> 11911698

E-state modeling of HIV-1 protease inhibitor binding independent of 3D information.

Hlaing Hlaing Maw1, Lowell H Hall.   

Abstract

Data for HIV-1 protease inhibitors (in vitro enzyme binding) were used as a training set to develop a QSAR model based on topological descriptors, including two hydrogen E-state indices, along with a molecular connectivity chi and a kappa shape index. A statistically satisfactory four-variable model was obtained for the 32 compounds in the training set, r2 = 0.86, s = 0.60, and q2 = 0.79, without the use of information from 3D geometries or detailed interaction energy calculations. The model was validated through the prediction of 15 compounds in the external test set, yielding a mean absolute error, MAE, = 0.82. Structure interpretation is given for each variable to assist in the design of new compounds. Structure features emphasized in the model include hydrogen bond donating ability, nonpolar groups, skeletal branching, and molecular globularity. On the basis of these statistical criteria, this E-state model may be considered useful for prediction of pIC50 values for new HIV-1 protease inhibitors.

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Year:  2002        PMID: 11911698     DOI: 10.1021/ci010091z

Source DB:  PubMed          Journal:  J Chem Inf Comput Sci        ISSN: 0095-2338


  2 in total

1.  QSAR modeling of beta-lactam binding to human serum proteins.

Authors:  L Mark Hall; Lowell H Hall; Lemont B Kier
Journal:  J Comput Aided Mol Des       Date:  2003 Feb-Apr       Impact factor: 3.686

2.  Effective estimation of the inhibitor affinity of HIV-1 protease via a modified LIE approach.

Authors:  Son Tung Ngo; Nam Dao Hong; Le Huu Quynh Anh; Dinh Minh Hiep; Nguyen Thanh Tung
Journal:  RSC Adv       Date:  2020-02-21       Impact factor: 4.036

  2 in total

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