Abstract
We have proposed a new method for quantitative structure-activity relationship (QSAR) analysis. This tool, termed GEMPLS, combines a genetic evolutionary method with partial least squares (PLS). We designed a new genetic operator and used Mahalanobis distance to improve predicted accuracy and speed up a solution for QSAR. The number of latent variables (lv) was encoded into the chromosome of GA, instead of scanning the best lv for PLS. We applied GEMPLS on a comparative binding energy (COMBINE) analysis system of 48 inhibitors of the HIV-1 protease. Using GEMPLS, the cross-validated correlation coefficient (q 2) is 0.9053 and external SDEP (SDEP ex ) is 0.61. The results indicate that GEMPLS is very comparative to GAPLS and GEMPLS is faster than GAPLS for this data set. GEMPLS yielded the QSAR models, in which selected residues are consistent with some experimental evidences.
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References
Kubinyi, H.: QSAR and 3-D QSAR in drug design. 2. Applications and problems. Drug Discovery Today 2, 538–546 (1997)
Cramer, R.D., Patterson, D.E., Bunce, J.D.: Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. Journal of the American Chemical Society 110, 5959–5967 (1988)
Wold, S., Johansson, E., Cocchi, M.: PLS - Partial least-squares projections to latent structures. In: Kubinyi, H. (ed.) 3D QSAR in Drug Design; Theory, Methods and Applications. ESCOM Science Publishers, Leiden Holland (1993)
Ortiz, A.R., Pisabarro, M.T., Gago, F., Wade, R.C.: Prediction of drug binding affinities by comparative binding energy analysis. Journal of Medicinal Chemistry 38, 2681–2691 (1995)
Perez, C., Pastor, M., Ortiz, A.R., Gago, F.: Comparative binding energy analysis of HIV-1 protease inhibitors: incorporation of solvent effects and validation as a powerful tool in receptor-based drug design. Journal of Medicinal Chemistry 41, 836–852 (1998)
Wanchana, S., Yamashita, F., Hashida, M.: QSAR analysis of the inhibition of recombinant CYP 3A4 activity by structurally diverse compounds using a genetic algorithm-combined partial least squares method. Pharmaceutical Research 20, 1401–1408 (2003)
Hasegawa, K., Kimura, T., Funatsu, K.: GA Strategy for Variable Selection in QSAR Studies: Enhancement of Comparative Molecular Binding Energy Analysis by GA-Based PLS Method. Quantitative Structure-Activity Relationships 18, 262–272 (1999)
Holloway, B.: A prior prediction of activity for HIV-1 protease inhibitors employing energy minimization in the active site. Journal of Medicinal Chemistry 38, 305–317 (1995)
Yang, J.-M., Chen, C.-C.: GEMDOCK: a generic evolutionary method for molecular docking. Proteins: Structure, Function, and Bioinformatics 55, 288–304 (2004)
Yang, J.M., Kao, C.Y.: An evolutionary algorithm for the synthesis of multilayer coatings at oblique light incidence. IEEE/OSA Journal of Lightwave Technology 19, 559–570 (2001)
Thompson, W.J., Fitzgerald, P.M., Holloway, M.K., Emini, E.A., Darke, P.L., et al.: Synthesis and antiviral activity of a series of HIV-1 protease inhibitors with functionality tethered to the P1 or P1’ phenyl substituents: X-ray crystal structure assisted design. Journal of Medicinal Chemistry 35, 1685–1701 (1992)
Wang, Y.X., Freedberg, D.I., Yamazaki, T., Wingfield, P.T., Stahl, S.J., et al.: Solution NMR Evidence That the HIV-1 Protease Catalytic Aspartyl Groups Have Different Ionization States in the Complex Formed with the Asymmetric Drug KNI-272. Biochemistry 35, 9945–9950 (1996)
Lifson, S., Hagler, A.T., Dauber, P.: Consistent Force Field Studies of Intermolecular Forces in Hydrogen Bonded Crystals I: Carboxylic Acids, Amides, and the C = O...H Hydrogen Bonds. Journal of the American Chemical Society 101, 5111–5120 (1979)
Dewar, M.J.S., Zoebisch, E.G., Healy, E.F., Stewart, J.J.P.: AM1: A New General Purpose Quantum Mechanical Molecular Model. Journal of the American Chemical Society 107, 3902–3909 (1985)
Besler, B.H., Merz, K.M., Kollman, P.A.: Atomic Charges Derived from Semiempirical Methods. Journal of Computational Chemistry 11, 431–439 (1990)
Baker, J.E.: Reducing Bias and Inefficiency in the Selection Algorithm. In: The Second International Conference on Genetic Algorithms and their Application, pp. 14–21 (1987)
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Chen, YC., Yang, JM., Tsai, CH., Kao, CY. (2005). GEMPLS: A New QSAR Method Combining Generic Evolutionary Method and Partial Least Squares. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2005. Lecture Notes in Computer Science, vol 3449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32003-6_13
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DOI: https://doi.org/10.1007/978-3-540-32003-6_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25396-9
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