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BioMed Research International
Volume 2014, Article ID 210672, 8 pages
Research Article

Prediction on the Inhibition Ratio of Pyrrolidine Derivatives on Matrix Metalloproteinase Based on Gene Expression Programming

1College of Pharmacy, Taishan Medical University, Taian, Shandong 271016, China
2Institute of Computer Science and Engineering Technology, Qingdao University, Qingdao 266071, China
3College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou 271000, China

Received 27 February 2014; Accepted 29 April 2014; Published 22 May 2014

Academic Editor: Nick V. Grishin

Copyright © 2014 Yuqin Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Quantitative structure-activity relationships (QSAR) were developed to predict the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase via heuristic method (HM) and gene expression programming (GEP). The descriptors of 33 pyrrolidine derivatives were calculated by the software CODESSA, which can calculate quantum chemical, topological, geometrical, constitutional, and electrostatic descriptors. HM was also used for the preselection of 5 appropriate molecular descriptors. Linear and nonlinear QSAR models were developed based on the HM and GEP separately and two prediction models lead to a good correlation coefficient ( ) of 0.93 and 0.94. The two QSAR models are useful in predicting the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase during the discovery of new anticancer drugs and providing theory information for studying the new drugs.