Literature DB >> 28042965

Molecular Simulations Identify Binding Poses and Approximate Affinities of Stapled α-Helical Peptides to MDM2 and MDMX.

Joseph A Morrone1, Alberto Perez1, Qiaolin Deng2, Sookhee N Ha2, M Katharine Holloway3, Tomi K Sawyer4, Bradley S Sherborne2, Frank K Brown3, Ken A Dill1,5,6.   

Abstract

Traditionally, computing the binding affinities of proteins to even relatively small and rigid ligands by free-energy methods has been challenging due to large computational costs and significant errors. Here, we apply a new molecular simulation acceleration method called MELD (Modeling by Employing Limited Data) to study the binding of stapled α-helical peptides to the MDM2 and MDMX proteins. We employ free-energy-based molecular dynamics simulations (MELD-MD) to identify binding poses and calculate binding affinities. Even though stapled peptides are larger and more complex than most protein ligands, the MELD-MD simulations can identify relevant binding poses and compute relative binding affinities. MELD-MD appears to be a promising method for computing the binding properties of peptide ligands with proteins.

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Year:  2017        PMID: 28042965     DOI: 10.1021/acs.jctc.6b00978

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  13 in total

1.  Accelerating physical simulations of proteins by leveraging external knowledge.

Authors:  Alberto Perez; Joseph A Morrone; Ken A Dill
Journal:  Wiley Interdiscip Rev Comput Mol Sci       Date:  2017-04-19

Review 2.  Computational membrane biophysics: From ion channel interactions with drugs to cellular function.

Authors:  Williams E Miranda; Van A Ngo; Laura L Perissinotti; Sergei Yu Noskov
Journal:  Biochim Biophys Acta Proteins Proteom       Date:  2017-08-26       Impact factor: 3.036

3.  Peptide Gaussian accelerated molecular dynamics (Pep-GaMD): Enhanced sampling and free energy and kinetics calculations of peptide binding.

Authors:  Jinan Wang; Yinglong Miao
Journal:  J Chem Phys       Date:  2020-10-21       Impact factor: 3.488

4.  Computing Ligands Bound to Proteins Using MELD-Accelerated MD.

Authors:  Cong Liu; Emiliano Brini; Alberto Perez; Ken A Dill
Journal:  J Chem Theory Comput       Date:  2020-09-23       Impact factor: 6.006

5.  Monte Carlo on the manifold and MD refinement for binding pose prediction of protein-ligand complexes: 2017 D3R Grand Challenge.

Authors:  Mikhail Ignatov; Cong Liu; Andrey Alekseenko; Zhuyezi Sun; Dzmitry Padhorny; Sergei Kotelnikov; Andrey Kazennov; Ivan Grebenkin; Yaroslav Kholodov; Istvan Kolosvari; Alberto Perez; Ken Dill; Dima Kozakov
Journal:  J Comput Aided Mol Des       Date:  2018-11-12       Impact factor: 3.686

6.  Predicting Protein Dimer Structures Using MELD × MD.

Authors:  Emiliano Brini; Dima Kozakov; Ken A Dill
Journal:  J Chem Theory Comput       Date:  2019-04-05       Impact factor: 6.006

7.  Gaussian accelerated molecular dynamics (GaMD): principles and applications.

Authors:  Jinan Wang; Pablo R Arantes; Apurba Bhattarai; Rohaine V Hsu; Shristi Pawnikar; Yu-Ming M Huang; Giulia Palermo; Yinglong Miao
Journal:  Wiley Interdiscip Rev Comput Mol Sci       Date:  2021-03-01

8.  Modeling beta-sheet peptide-protein interactions: Rosetta FlexPepDock in CAPRI rounds 38-45.

Authors:  Alisa Khramushin; Orly Marcu; Nawsad Alam; Orly Shimony; Dzmitry Padhorny; Emiliano Brini; Ken A Dill; Sandor Vajda; Dima Kozakov; Ora Schueler-Furman
Journal:  Proteins       Date:  2020-01-06

9.  Improved Modeling of Peptide-Protein Binding Through Global Docking and Accelerated Molecular Dynamics Simulations.

Authors:  Jinan Wang; Andrey Alekseenko; Dima Kozakov; Yinglong Miao
Journal:  Front Mol Biosci       Date:  2019-10-30

10.  Structure-based designing efficient peptides based on p53 binding site residues to disrupt p53-MDM2/X interaction.

Authors:  Nasim Rasafar; Abolfazl Barzegar; Elnaz Mehdizadeh Aghdam
Journal:  Sci Rep       Date:  2020-07-10       Impact factor: 4.379

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