Predicting Complexation Thermodynamic Parameters of β-Cyclodextrin with Chiral Guests by Using Swarm Intelligence and Support Vector Machines

doi:10.3390/ijms10052107

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Int. J. Mol. Sci. 2009, 10(5), 2107-2121; doi:10.3390/ijms10052107

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Predicting Complexation Thermodynamic Parameters of β-Cyclodextrin with Chiral Guests by Using Swarm Intelligence and Support Vector Machines

Chakguy Prakasvudhisarn ¹ , Peter Wolschann ² and Luckhana Lawtrakul ³^,*

¹ School of Technology, Shinawatra University, Shinawatra Tower III, 15th floor, 1010 Viphavadi Rangsit Road, Chatuchak, Bangkok, 10900, Thailand ² Institute of Theoretical Chemistry, University of Vienna, Währinger Straβe 17, Vienna, 1090, Austria ³ Sirindhorn International Institute of Technology (SIIT), Thammasat University, P.O.Box 22 Thammasat Rangsit Post Office, Pathum Thani, 12121, Thailand

* Author to whom correspondence should be addressed.

Received: 17 April 2009 / Accepted: 6 May 2009 / Published: 14 May 2009

(This article belongs to the Special Issue Recent Advances in QSAR/QSPR Theory)

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Abstract: The Particle Swarm Optimization (PSO) and Support Vector Machines (SVMs) approaches are used for predicting the thermodynamic parameters for the 1:1 inclusion complexation of chiral guests with β-cyclodextrin. A PSO is adopted for descriptor selection in the quantitative structure-property relationships (QSPR) of a dataset of 74 chiral guests due to its simplicity, speed, and consistency. The modified PSO is then combined with SVMs for its good approximating properties, to generate a QSPR model with the selected features. Linear, polynomial, and Gaussian radial basis functions are used as kernels in SVMs. All models have demonstrated an impressive performance with R² higher than 0.8.

Keywords: Particle Swarm Optimization; Support Vector Machines; QSPR; β-cyclo-dextrin inclusion complexes

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MDPI and ACS Style

Prakasvudhisarn, C.; Wolschann, P.; Lawtrakul, L. Predicting Complexation Thermodynamic Parameters of β-Cyclodextrin with Chiral Guests by Using Swarm Intelligence and Support Vector Machines. Int. J. Mol. Sci. 2009, 10, 2107-2121.

AMA Style

Prakasvudhisarn C., Wolschann P., Lawtrakul L. Predicting Complexation Thermodynamic Parameters of β-Cyclodextrin with Chiral Guests by Using Swarm Intelligence and Support Vector Machines. International Journal of Molecular Sciences. 2009; 10(5):2107-2121.

Chicago/Turabian Style

Prakasvudhisarn, Chakguy; Wolschann, Peter; Lawtrakul, Luckhana. 2009. "Predicting Complexation Thermodynamic Parameters of β-Cyclodextrin with Chiral Guests by Using Swarm Intelligence and Support Vector Machines." Int. J. Mol. Sci. 10, no. 5: 2107-2121.

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