Literature DB >> 28766941

A Computational Investigation of Small-Molecule Engagement of Hot Spots at Protein-Protein Interaction Interfaces.

David Xu1, Yubing Si, Samy O Meroueh.   

Abstract

The binding affinity of a protein-protein interaction is concentrated at amino acids known as hot spots. It has been suggested that small molecules disrupt protein-protein interactions by either (i) engaging receptor protein hot spots or (ii) mimicking hot spots of the protein ligand. Yet, no systematic studies have been done to explore how effectively existing small-molecule protein-protein interaction inhibitors mimic or engage hot spots at protein interfaces. Here, we employ explicit-solvent molecular dynamics simulations and end-point MM-GBSA free energy calculations to explore this question. We select 36 compounds for which high-quality binding affinity and cocrystal structures are available. Five complexes that belong to three classes of protein-protein interactions (primary, secondary, and tertiary) were considered, namely, BRD4•H4, XIAP•Smac, MDM2p53, Bcl-xL•Bak, and IL-2IL-2Rα. Computational alanine scanning using MM-GBSA identified hot-spot residues at the interface of these protein interactions. Decomposition energies compared the interaction of small molecules with individual receptor hot spots to those of the native protein ligand. Pharmacophore analysis was used to investigate how effectively small molecules mimic the position of hot spots of the protein ligand. Finally, we study whether small molecules mimic the effects of the native protein ligand on the receptor dynamics. Our results show that, in general, existing small-molecule inhibitors of protein-protein interactions do not optimally mimic protein-ligand hot spots, nor do they effectively engage protein receptor hot spots. The more effective use of hot spots in future drug design efforts may result in smaller compounds with higher ligand efficiencies that may lead to greater success in clinical trials.

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Year:  2017        PMID: 28766941      PMCID: PMC6148373          DOI: 10.1021/acs.jcim.7b00181

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  64 in total

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8.  Structure- and ligand-based virtual screening identifies new scaffolds for inhibitors of the oncoprotein MDM2.

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10.  Discovery of novel small-molecule inhibitors of BRD4 using structure-based virtual screening.

Authors:  Lewis R Vidler; Panagis Filippakopoulos; Oleg Fedorov; Sarah Picaud; Sarah Martin; Michael Tomsett; Hannah Woodward; Nathan Brown; Stefan Knapp; Swen Hoelder
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  5 in total

1.  Chemical Space Overlap with Critical Protein-Protein Interface Residues in Commercial and Specialized Small-Molecule Libraries.

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Journal:  ChemMedChem       Date:  2018-12-20       Impact factor: 3.466

2.  Analysis of physicochemical properties of protein-protein interaction modulators suggests stronger alignment with the "rule of five".

Authors:  Jia Truong; Ashwin George; Jessica K Holien
Journal:  RSC Med Chem       Date:  2021-07-27

3.  HawkDock: a web server to predict and analyze the protein-protein complex based on computational docking and MM/GBSA.

Authors:  Gaoqi Weng; Ercheng Wang; Zhe Wang; Hui Liu; Feng Zhu; Dan Li; Tingjun Hou
Journal:  Nucleic Acids Res       Date:  2019-07-02       Impact factor: 16.971

4.  Identifying protein-protein interface via a novel multi-scale local sequence and structural representation.

Authors:  Fei Guo; Quan Zou; Guang Yang; Dan Wang; Jijun Tang; Junhai Xu
Journal:  BMC Bioinformatics       Date:  2019-12-24       Impact factor: 3.169

5.  Hot spot prediction in protein-protein interactions by an ensemble system.

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Journal:  BMC Syst Biol       Date:  2018-12-31
  5 in total

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