Name
Title | ||
|---|---|---|
Identifying P-Glycoprotein Substrates Using a Support Vector Machine Optimized by a Particle Swarm. |
Abstract | ||
|---|---|---|
P-Glycoprotein (P-gp) contributes to extruding a structurally, chemically, and pharmacologically diverse range of substrates out of cells. This function may result in the failure of chemotherapy in cancer and influence pharmacokinetic properties of many drugs. Although a great deal of research has been devoted to the investigation of P-gp and its substrate specificity, still we do not have a clear understanding of the resolution of the three-dimensional structure of P-gp and its working role as a drug efflux pump at a molecular level. Hence to identify whether a compound is a P-gp substrate or not, computational methods are promising both in cancer treatment and the drug discovery processes. We have established more effective models for prediction of P-gp substrates with an average accuracy of > 90% using a Particle Swarm (PS) algorithm and a Support Vector Machine (SVM) approach. The applied models yielded higher accuracies and contained fewer variables in comparison with previous studies. An analysis of P-gp substrate specificity based on the data set is also presented by a PS and a SVM. The aim of this study is 3-fold: (i) presentation of a modified PS algorithm that is applicable for selection of molecular descriptors in quantitative structure-activity relationship (QSAR) model construction, (ii) application of this modified PS algorithm as a wrapper to undertake feature selection in construction of a QSAR model to predict P-gp substrates with a multiple linear (ML) and SVM approach, and (iii) also finding factors (molecular descriptors) that most likely are associated with P-gp substrate specificity by using a PS and a SVM from the data set. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1021/ci700083n | JOURNAL OF CHEMICAL INFORMATION AND MODELING |
Keywords | Field | DocType |
particle swarm,support vector machine | Substrate (chemistry),Particle swarm optimization,Drug discovery,Support vector machine,Chemistry,Bioinformatics,P-glycoprotein | Journal |
Volume | Issue | ISSN |
47 | 4 | 1549-9596 |
Citations | PageRank | References |
4 | 0.55 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianping Huang | 1 | 30 | 5.34 |
| Guangli Ma | 2 | 4 | 0.55 |
| Ishtiaq Muhammad | 3 | 4 | 0.55 |
| Yiyu Cheng | 4 | 68 | 8.54 |