A structural biology view of target drugability

被引:38
作者
Egner, Ursula [1 ]
Hillig, Roman C. [1 ]
机构
[1] Bayer Schering Pharma AG, Lead Discovery Berlin Struct Biol, D-13342 Berlin, Germany
关键词
drugability prediction; structural biology; structural target assessment;
D O I
10.1517/17460441.3.4.391
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Background: With long and costly drug development times there is a need in the pharmaceutical industry to prioritize targets early in the drug discovery process. One of the possible criteria is 'protein drugability', a term with multiple understandings in the literature. Among others, it is the likelihood of finding a selective, low-molecular weight molecule that binds with high affinity to the target. Objective: Which methods are available for drugability prediction? What can be achieved by such predictions and how can they influence the target prioritization process? Methods: The main focus is on sequence- and structure-related computational methods for drugability prediction, giving an overview on their background as well as their bias and limitations with an emphasis on the structural biology point of view. Results/conclusion: Structural drugability assessment presents one criterion for prioritization of a target portfolio by enabling classification of targets into low, average, or high drugability.
引用
收藏
页码:391 / 401
页数:11
相关论文
共 67 条
[1]   Crystal structures of two potent nonamidine inhibitors bound to factor Xa [J].
Adler, M ;
Kochanny, MJ ;
Ye, B ;
Rumennik, G ;
Light, DR ;
Biancalana, S ;
Whitlow, M .
BIOCHEMISTRY, 2002, 41 (52) :15514-15523
[2]   Kinase inhibition with BAY 43-9006 n renal cell carcinoma [J].
Ahmad, T ;
Eisen, T .
CLINICAL CANCER RESEARCH, 2004, 10 (18) :6388S-6392S
[3]   Pocketome via comprehensive identification and classification of ligand binding envelopes [J].
An, JH ;
Totrov, M ;
Abagyan, R .
MOLECULAR & CELLULAR PROTEOMICS, 2005, 4 (06) :752-761
[4]  
BAINS W, 2004, DRUG DISCOVERY WORLD, P9
[5]  
BERGNER A, 2001, STRUCTURAL ASPECTS B
[6]   The Protein Data Bank and the challenge of structural genomics [J].
Berman, HM ;
Bhat, TN ;
Bourne, PE ;
Feng, ZK ;
Gilliland, G ;
Weissig, H ;
Westbrook, J .
NATURE STRUCTURAL BIOLOGY, 2000, 7 (Suppl 11) :957-959
[7]   The Protein Data Bank [J].
Berman, HM ;
Westbrook, J ;
Feng, Z ;
Gilliland, G ;
Bhat, TN ;
Weissig, H ;
Shindyalov, IN ;
Bourne, PE .
NUCLEIC ACIDS RESEARCH, 2000, 28 (01) :235-242
[8]   Effects of conformational dynamics on predicted protein druggability [J].
Brown, Scott P. ;
Hajduk, Philip J. .
CHEMMEDCHEM, 2006, 1 (01) :70-+
[9]   TTD: Therapeutic Target Database [J].
Chen, X ;
Ji, ZL ;
Chen, YZ .
NUCLEIC ACIDS RESEARCH, 2002, 30 (01) :412-415
[10]   Structure-based maximal affinity model predicts small-molecule druggability [J].
Cheng, Alan C. ;
Coleman, Ryan G. ;
Smyth, Kathleen T. ;
Cao, Qing ;
Soulard, Patricia ;
Caffrey, Daniel R. ;
Salzberg, Anna C. ;
Huang, Enoch S. .
NATURE BIOTECHNOLOGY, 2007, 25 (01) :71-75