Three-dimensional analysis of binding sites for predicting binding affinities in drug design
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Tarih
2019
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Amer Chemical Soc
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
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 offer promising results in predicting the binding affinities. It becomes possible to do accurate predictions by using the known protein-ligand interactions. In this study, the electrostatic potential values extracted from 3-dimensional grid cubes of the drug-protein binding sites are used for predicting binding affinities of related complexes. A new algorithm with a dynamic feature selection method was implemented, which is derived from Compressed Images For Affinity Prediction (CIFAP) study, to predict binding affinities of Checkpoint Kinase 1 and Caspase 3 inhibitors.
Açıklama
Alpaslan, Ferda Nur/0000-0002-9806-1543; Erdas Cicek, Ozlem/0000-0003-4019-7744
Anahtar Kelimeler
Kaynak
Journal of Chemical Information And Modeling
WoS Q Değeri
N/A
Scopus Q Değeri
Q1
Cilt
59
Sayı
11
