NDLI: Homology modeling and in silico screening of inhibitors for the substrate binding domain of human Siah2: implications for hypoxia-induced cancers

Content Provider	Springer Nature Link
Author	Anupriya, Gopalsamy Roopa, Kothapalli Basappa, S. Chong, Yap Seng Annamalai, Loganath
Copyright Year	2011
Abstract	The three-dimensional (3D) structure of the substrate binding domain (SBD) of human ubiquitin ligase Siah2 (seven in absentia homolog) was constructed based on the homology modeling approach using the Modeller 9v7 program. The molecular dynamics method was utilized to refine the model and it was further assessed by ProSA, three-dimensional structural superposition (3d-SS) and PROCHEK in order to analyze the quality and reliability of the generated model. Furthermore, we predicted the binding pocket of Siah2 and also validated it by both blind and normal docking using a known functional inhibitor, menadione. Using structure-based high-throughput virtual screening, we identified five lead drug-like molecules against the modeled SBD of Siah2 and analyzed its pharmacokinetic properties to identify the potential inhibitors for Siah2. The docking results for menadione and the lead molecules at the ligand binding site of SBD of Siah2 revealed that the residue Ser39 (corresponding to Ser167 in the full-length protein) is consistently involved in strong hydrogen bonding, and plays an important role in phosphorylation and the enhanced activity of Siah2.
Starting Page	3325
Ending Page	3332
Page Count	8
File Format	PDF
ISSN	16102940
Journal	Journal of Molecular Modeling
Volume Number	17
Issue Number	12
e-ISSN	09485023
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-03-16
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Homology modeling Molecular dynamics Menadione Virtual screening Docking Substrate binding domain Siah2 Health Informatics Life Sciences Molecular Medicine Biomedicine general Computer Applications in Chemistry Computer Application in Life Sciences
Content Type	Text
Resource Type	Article
Subject	Organic Chemistry Physical and Theoretical Chemistry Computational Theory and Mathematics Catalysis Inorganic Chemistry Computer Science Applications

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