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

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dc.creator MUHAMMED, Muhammed Tılahun
dc.creator Aki-Yalcin, Esin
dc.date 2018-12-31T21:00:00Z
dc.date.accessioned 2020-10-06T09:36:17Z
dc.date.available 2020-10-06T09:36:17Z
dc.identifier 2c0426b3-d1ea-4c07-979f-8701b01fba53
dc.identifier 10.1111/cbdd.13388
dc.identifier https://avesis.sdu.edu.tr/publication/details/2c0426b3-d1ea-4c07-979f-8701b01fba53/oai
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/56256
dc.description 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.
dc.language eng
dc.rights info:eu-repo/semantics/openAccess
dc.title Homology modeling in drug discovery: Overview, current applications, and future perspectives
dc.type info:eu-repo/semantics/article


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