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3D analysis of the binding sites for predicting binding affinities in drug design
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index.pdf
Date
2014
Author
Ataç, Ali Osman
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Understanding the interaction between drug molecules and proteins is one of the main challenges in drug design. Several tools have been developed recently to decrease the complexity of the process. Artificial intelligence and machine learning methods have promising results in predicting the affinities. Recently, accurate estimations have been performed by extracting the electrostatic potentials from images of the drug-protein binding sites which were generated by autodocking simulator. In this study, a new algorithm has been implemented, which is a modified version of CIFAP, to predict binding affinities of CheckPoint Kinase1 and Caspase3 inhibitors.
Subject Keywords
Drugs
,
Drug development.
,
Machine learning.
,
Three-dimensional modeling.
URI
http://etd.lib.metu.edu.tr/upload/12618158/index.pdf
https://hdl.handle.net/11511/24177
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Graduate School of Natural and Applied Sciences, Thesis
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A. O. Ataç, “3D analysis of the binding sites for predicting binding affinities in drug design,” M.S. - Master of Science, Middle East Technical University, 2014.