%0 Journal Article %1 Si:2006:BMC %A Si, Hong Zong %A Wang, Tao %A Zhang, Ke Jun %A Hu, Zhi De %A Fan, Bo Tao %D 2006 %J Bioorganic & Medicinal Chemistry %K Calcium Expression Gene Programming, QSAR, algorithms, antagonists channel genetic programming, %N 14 %P 4834--4841 %R doi:10.1016/j.bmc.2006.03.019 %T QSAR study of 1,4-dihydropyridine calcium channel antagonists based on gene expression programming %V 14 %X The gene expression programming, a novel machine learning algorithm, is used to develop quantitative model as a potential screening mechanism for a series of 1,4-dihydropyridine calcium channel antagonists for the first time. The heuristic method was used to search the descriptor space and select the descriptors responsible for activity. A nonlinear, six-descriptor model based on gene expression programming with mean-square errors 0.19 was set up with a predicted correlation coefficient (R2) 0.92. This paper provides a new and effective method for drug design and screening. Graphical abstract The log (1/IC50) for 45 1,4-dihydropyridines was modelled using the descriptors calculated from the molecular structure along with a quantitative structure\u2013activity relationship (QSAR) technique. The heuristic method (HM) and gene expression programming (GEP) were used to construct the linear and nonlinear prediction models, leading to a good prediction.

@article{Si:2006:BMC, abstract = {The gene expression programming, a novel machine learning algorithm, is used to develop quantitative model as a potential screening mechanism for a series of 1,4-dihydropyridine calcium channel antagonists for the first time. The heuristic method was used to search the descriptor space and select the descriptors responsible for activity. A nonlinear, six-descriptor model based on gene expression programming with mean-square errors 0.19 was set up with a predicted correlation coefficient (R2) 0.92. This paper provides a new and effective method for drug design and screening. Graphical abstract The log (1/IC50) for 45 1,4-dihydropyridines was modelled using the descriptors calculated from the molecular structure along with a quantitative structure\u2013activity relationship (QSAR) technique. The heuristic method (HM) and gene expression programming (GEP) were used to construct the linear and nonlinear prediction models, leading to a good prediction.}, added-at = {2008-06-19T17:46:40.000+0200}, author = {Si, Hong Zong and Wang, Tao and Zhang, Ke Jun and Hu, Zhi De and Fan, Bo Tao}, biburl = {https://www.bibsonomy.org/bibtex/268bfa0bc6e1d96ad3c70488119d68fc1/brazovayeye}, doi = {doi:10.1016/j.bmc.2006.03.019}, interhash = {0e80cf98867975cfc493588053d835d0}, intrahash = {68bfa0bc6e1d96ad3c70488119d68fc1}, journal = {Bioorganic \& Medicinal Chemistry}, keywords = {Calcium Expression Gene Programming, QSAR, algorithms, antagonists channel genetic programming,}, month = {15 July}, notes = {a Department of Chemistry, Lanzhou University, 730000 Lanzhou, PR China b Center for Disease Control of Gansu Province, 730020 Lanzhou, PR China c Clinical Laboratory, The First Hospital of Lanzhou University, 73000 Lanzhou, PR China d School of Mechanical and Electrical Engineering, JUST, 341000 Ganzhou, PR China e University Paris 7-Denis Diderot, ITODYS 1, rue Guy de la Brosse, 75005 Paris, France}, number = 14, pages = {4834--4841}, timestamp = {2008-06-19T17:51:39.000+0200}, title = {{QSAR} study of 1,4-dihydropyridine calcium channel antagonists based on gene expression programming}, volume = 14, year = 2006 }