Homology Modeling a Fast Tool for Drug Discovery: Current Perspectives
By Vivek K. Vyas, Ravi Ukawala, M. Ghate, Chetan Chintha. 2012
245 citations recorded by the source corpus.
Major goal of structural biology involve formation of protein-ligand complexes; in which the protein molecules act energetically in the course of binding. Therefore, perceptive of protein-ligand interaction will be very important for structure based drug design. Lack of knowledge of 3D structures has hindered efforts to understand the binding specificities of ligands with protein. With increasing in modeling software and the growing number of known protein structures, homology modeling is rapidly becoming the method of choice for obtaining 3D coordinates of proteins. Homology modeling is a representation of the similarity of environmental residues at topologically corresponding positions in the reference proteins. In the absence of experimental data, model building on the basis of a known 3D structure of a homologous protein is at present the only reliable method to obtain the structural information. Knowledge of the 3D structures of proteins provides invaluable insights into the molecular basis of their functions. The recent advances in homology modeling, particularly in detecting and aligning sequences with template structures, distant homologues, modeling of loops and side chains as well as detecting errors in a model contributed to consistent prediction of protein structure, which was not possible even several years ago. This review focused on the features and a role of homology modeling in predicting protein structure and described current developments in this field with victorious applications at the different stages of the drug design and discovery.
Subfields: Computational Theory and Mathematics, Molecular Biology, Computational Chemistry & Drug Discovery
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In Computational Theory and Mathematics
In Molecular Biology
- Carolina S. Silva
- M. O. Santos
- C. K. Surratt
- V. C. de Souza
- Jeffry D. Madura
- V. L. da Silva
- L. Tavares
- C. G. Diniz
In Computational Chemistry & Drug Discovery
Citations in the corpus
- A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets (2015, methodology): “VS uses computational methods to predict how the compounds in a structural (virtual) library would interact with a crystal structure representation or homology model of the target receptor (17).”
- Strategies and molecular tools to fight antimicrobial resistance: resistome, transcriptome, and antimicrobial peptides (2013, methodology): “The information modeler generated is also combined with the statistical calculation preferences of constraints derived from the sequence template homology (Eswar et al., 2003; Vyas et al., 2012).”
- Structural model of PORCN illuminates disease-associated variants and drug binding sites (2021, methodology): “Here, taking advantage of advances in structural prediction algorithms, we developed a highquality structural homology model of human PORCN (Sánchez and Šali, 1997; Vyas et al., 2012; White, 2009).”