Literature DB >> 26252196

CSAR Benchmark of Flexible MedusaDock in Affinity Prediction and Nativelike Binding Pose Selection.

Praveen Nedumpully-Govindan1, Domen B Jemec1, Feng Ding1.   

Abstract

While molecular docking with both ligand and receptor flexibilities can help capture conformational changes upon binding, correct ranking of nativelike binding poses and accurate estimation of binding affinities remains a major challenge. In addition to the commonly used scoring approach with intermolecular interaction energies, we included the contribution of intramolecular energies changes upon binding in our flexible docking method, MedusaDock. In CSAR 2013-2014 binding prediction benchmark exercises, the new scoring function MScomplex was found to better recapitulate experimental binding affinities and correctly identify ligand-binding sequences from decoy receptors. Our further analysis with the DUD data sets indicates significant improvement of virtual screening enrichment using the new scoring function when compared to the previous intermolecular energy based scoring method. Our postanalysis also suggests a new approach to select nativelike poses in the clustering-based pose ranking approach by MedusaDock. Since the calculation of intramolecular energy changes and clustering-based pose ranking and selection are not MedusaDock specific, we expect a broad application in force-field based estimation of binding affinities and pose ranking using flexible ligand-receptor docking.

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Year:  2015        PMID: 26252196     DOI: 10.1021/acs.jcim.5b00303

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


  8 in total

1.  Docking of small molecules to farnesoid X receptors using AutoDock Vina with the Convex-PL potential: lessons learned from D3R Grand Challenge 2.

Authors:  Maria Kadukova; Sergei Grudinin
Journal:  J Comput Aided Mol Des       Date:  2017-09-14       Impact factor: 3.686

Review 2.  Implications of peptide assemblies in amyloid diseases.

Authors:  Pu Chun Ke; Marc-Antonie Sani; Feng Ding; Aleksandr Kakinen; Ibrahim Javed; Frances Separovic; Thomas P Davis; Raffaele Mezzenga
Journal:  Chem Soc Rev       Date:  2017-10-30       Impact factor: 54.564

3.  Combined Approach of Patch-Surfer and PL-PatchSurfer for Protein-Ligand Binding Prediction in CSAR 2013 and 2014.

Authors:  Xiaolei Zhu; Woong-Hee Shin; Hyungrae Kim; Daisuke Kihara
Journal:  J Chem Inf Model       Date:  2015-12-30       Impact factor: 4.956

4.  Hydrophobic/Hydrophilic Ratio of Amphiphilic Helix Mimetics Determines the Effects on Islet Amyloid Polypeptide Aggregation.

Authors:  Huayuan Tang; Yunxiang Sun; Feng Ding
Journal:  J Chem Inf Model       Date:  2022-03-21       Impact factor: 6.162

5.  Nanoscale inhibition of polymorphic and ambidextrous IAPP amyloid aggregation with small molecules.

Authors:  Aleksandr Kakinen; Jozef Adamcik; Bo Wang; Xinwei Ge; Raffaele Mezzenga; Thomas P Davis; Feng Ding; Pu Chun Ke
Journal:  Nano Res       Date:  2018-08-02       Impact factor: 8.897

6.  CSAR 2014: A Benchmark Exercise Using Unpublished Data from Pharma.

Authors:  Heather A Carlson; Richard D Smith; Kelly L Damm-Ganamet; Jeanne A Stuckey; Aqeel Ahmed; Maire A Convery; Donald O Somers; Michael Kranz; Patricia A Elkins; Guanglei Cui; Catherine E Peishoff; Millard H Lambert; James B Dunbar
Journal:  J Chem Inf Model       Date:  2016-05-17       Impact factor: 4.956

7.  Star Polymers Reduce Islet Amyloid Polypeptide Toxicity via Accelerated Amyloid Aggregation.

Authors:  Emily H Pilkington; May Lai; Xinwei Ge; William J Stanley; Bo Wang; Miaoyi Wang; Aleksandr Kakinen; Marc-Antonie Sani; Michael R Whittaker; Esteban N Gurzov; Feng Ding; John F Quinn; Thomas P Davis; Pu Chun Ke
Journal:  Biomacromolecules       Date:  2017-10-31       Impact factor: 6.988

8.  Stabilizing Off-pathway Oligomers by Polyphenol Nanoassemblies for IAPP Aggregation Inhibition.

Authors:  Praveen Nedumpully-Govindan; Aleksandr Kakinen; Emily H Pilkington; Thomas P Davis; Pu Chun Ke; Feng Ding
Journal:  Sci Rep       Date:  2016-01-14       Impact factor: 4.379

  8 in total

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