3D analysis of the binding sites for predicting binding affinities in drug design

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2014

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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

Collections

Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

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.