Predicting Targeted Polypharmacology for Drug Repositioning and Multi- Target Drug Discovery

Title:Predicting Targeted Polypharmacology for Drug Repositioning and Multi- Target Drug Discovery

Volume: 20 Issue: 13

Author(s): X. Liu, F. Zhu, X. H. Ma, Z. Shi, S. Y. Yang, Y. Q. Wei and Y. Z. Chen

Affiliation:

Keywords: Computer aided drug design, drug discovery, drug repositioning, gene expression, multi-target, network pharmacology, systems pharmacology, virtual screening

Abstract: Prediction of polypharmacology of known drugs and new molecules against selected multiple targets is highly useful for finding new therapeutic applications of existing drugs (drug repositioning) and for discovering multi-target drugs with improved therapeutic efficacies by collective regulations of primary therapeutic targets, compensatory signalling and drug resistance mechanisms. In this review, we describe recent progresses in exploration of in-silico methods for predicting polypharmacology of known drugs and new molecules by means of structure-based (molecular docking, binding- site structural similarity, receptor-based pharmacophore searching), expression-based (expression profile/signature similarity disease-drug and drug-drug networks), ligand-based (similarity searching, side-effect similarity, QSAR, machine learning), and fragment-based approaches that have shown promising potential in facilitating drug repositioning and the discovery of multi-target drugs.

Cite this article as:

Liu X., Zhu F., H. Ma X., Shi Z., Y. Yang S., Q. Wei Y. and Z. Chen Y., Predicting Targeted Polypharmacology for Drug Repositioning and Multi- Target Drug Discovery, Current Medicinal Chemistry 2013; 20(13) . https://dx.doi.org/10.2174/0929867311320130005