Homology modeling in drug discovery: current trends and applications.
By Claudio N. Cavasotto, Sharangdhar S. Phatak. Drug Discovery Today, 2009
409 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Molecular Biology, Pharmacology
View Paper: https://www.semanticscholar.org/paper/8c114e289e403e208e879b3ac2d499e00588d55c
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In Computational Theory and Mathematics
- Vsevolod Katritch
- Vivek K. Vyas
- Chanjin Jung
- Jingyu Lee
- Ravi Ukawala
- Bilal Shaker
- Ruben Abagyan
- Dokyun Na
In Molecular Biology
- Vsevolod Katritch
- Raymond C. Stevens
- Burkhard Rost
- Ruben Abagyan
- Marco Punta
- Vadim Cherezov
- P. Kuhn
- Kurt Wüthrich
In Pharmacology
Citations in the corpus
- In silico methods and tools for drug discovery (2021, methodology): “When neither is available, in silico prediction methods such as homology modeling [16] or ab initio modeling [17] can be used to predict the 3D structure of the target protein.”
- Structure-based drug discovery and protein targets in the CNS. (2011, methodology): “The most robust method for protein structure prediction is homology modelling (see recent review by Cavasotto and Phatak, 2009).”
- Homology Modeling a Fast Tool for Drug Discovery: Current Perspectives (2012, background): “This can often achieved using different types of approaches and the first and most accurate approach is “comparative” or “homology” modeling[1].”
- An estimated 5% of new protein structures solved today represent a new Pfam family (2013, background): “While homology models have lower resolution compared with the experimentally determined structures that they are derived from, they are of sufficient quality to be of use during drug discovery (Patny et al., 2006; Cavasotto & Phatak, 2009).”
- GPCR Network: a large-scale collaboration on GPCR structure and function (2012, background): “2) , which has previously proven to be successful in applications to other major protein families 14 .”