title: Improved lead-finding for kinase targets using high-throughput docking.
abstract: Protein kinases represent a major class of drug targets for the pharmaceutical industry, and the identification of kinase inhibitors with novel and diverse chemotypes is therefore a high priority. Virtual screening methods are a primary source for the discovery of lead molecules for drug development, with high-throughput docking algorithms being among the most extensively used of these methods. A number of developments in virtual screening technologies have resulted in more effective computer-based compound screening of potential kinase inhibitors. These developments include the following: (i) conformational search methods for pose generation; (ii) improvements in the prediction of protein-ligand binding energy through the use of scoring functions; (iii) the use of interaction filters for identifying ligand poses with known binding determinants; and (iv) the impact of binding site flexibility upon high-throughput docking success. This review discusses the application of these methods in the context of the discovery of kinase adenosine triphosphate antagonists.
authors.affiliation: Cyclacel Ltd, James Lindsay Place, Dundee, DD1 5JJ, UK. cmcinnes@cyclacel.com
authors.forename: Campbell
authors.initials: C
authors.lastname: McInnes
mesh_terms: D000818:Animals; D003198:Computer Simulation; D015195:Drug Design; D006801:Humans; D008024:Ligands; D008958:Models, Molecular; D011485:Protein Binding; D047428:Protein Kinase Inhibitors / Q000737:chemistry*; D011494:Protein Kinases / Q000378:metabolism; D013329:Structure-Activity Relationship
chemical_list: D008024:Ligands; D047428:Protein Kinase Inhibitors; D011494:Protein Kinases