Homology modeling in drug discovery: Overview, current applications, and future perspectives

By M. T. Muhammed, Esin Aki-Yalcin. 2018

264 citations recorded by the source corpus.

Homology modeling is one of the computational structure prediction methods that are used to determine protein 3D structure from its amino acid sequence. It is considered to be the most accurate of the computational structure prediction methods. It consists of multiple steps that are straightforward and easy to apply. There are many tools and servers that are used for homology modeling. There is no single modeling program or server which is superior in every aspect to others. Since the functionality of the model depends on the quality of the generated protein 3D structure, maximizing the quality of homology modeling is crucial. Homology modeling has many applications in the drug discovery process. Since drugs interact with receptors that consist mainly of proteins, protein 3D structure determination, and thus homology modeling is important in drug discovery. Accordingly, there has been the clarification of protein interactions using 3D structures of proteins that are built with homology modeling. This contributes to the identification of novel drug candidates. Homology modeling plays an important role in making drug discovery faster, easier, cheaper, and more practical. As new modeling methods and combinations are introduced, the scope of its applications widens.

Subfields: Computational Theory and Mathematics, Molecular Biology, Radiology, Nuclear Medicine and Imaging

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Citations in the corpus

AlphaFold2 and its applications in the fields of biology and medicine (2023, methodology): “25 (2) De novo modeling De novo modeling is a protein structure prediction method based on the “ ﬁ rst principles ” .”
Structure-based methods for binding mode and binding affinity prediction for peptide-MHC complexes (2019, unknown): “chemistry since the 60’s (44), producing several approaches for structural prediction, analysis, and refinement (45, 46).”
Artificial intelligence to deep learning: machine intelligence approach for drug discovery (2021, methodology): “Thus, a technique like homology modeling has been developed to overcome this hindrance [297].”
Molecular Docking: Shifting Paradigms in Drug Discovery (2019, background): “(iii) crystallography [36–39] and homology modeling [155,156] techniques, which allow expanding our knowledge on structural biology;”