Literature DB >> 25947277

Molecular dynamics to enhance structure-based virtual screening on cathepsin B.

Mitja Ogrizek1, Samo Turk, Samo Lešnik, Izidor Sosič, Milan Hodošček, Bojana Mirković, Janko Kos, Dušanka Janežič, Stanislav Gobec, Janez Konc.   

Abstract

Molecular dynamics (MD) and molecular docking are commonly used to study molecular interactions in drug discovery. Most docking approaches consider proteins as rigid, which can decrease the accuracy of predicted docked poses. Therefore MD simulations can be used prior to docking to add flexibility to proteins. We evaluated the contribution of using MD together with docking in a docking study on human cathepsin B, a well-studied protein involved in numerous pathological processes. Using CHARMM biomolecular simulation program and AutoDock Vina molecular docking program, we found, that short MD simulations significantly improved molecular docking. Our results, expressed with the area under the receiver operating characteristic curves, show an increase in discriminatory power i.e. the ability to discriminate active from inactive compounds of molecular docking, when docking is performed to selected snapshots from MD simulations.

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Year:  2015        PMID: 25947277     DOI: 10.1007/s10822-015-9847-2

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  25 in total

1.  Molden: a pre- and post-processing program for molecular and electronic structures.

Authors:  G Schaftenaar; J H Noordik
Journal:  J Comput Aided Mol Des       Date:  2000-02       Impact factor: 3.686

2.  A 'rule of three' for fragment-based lead discovery?

Authors:  Miles Congreve; Robin Carr; Chris Murray; Harren Jhoti
Journal:  Drug Discov Today       Date:  2003-10-01       Impact factor: 7.851

Review 3.  CHARMM: the biomolecular simulation program.

Authors:  B R Brooks; C L Brooks; A D Mackerell; L Nilsson; R J Petrella; B Roux; Y Won; G Archontis; C Bartels; S Boresch; A Caflisch; L Caves; Q Cui; A R Dinner; M Feig; S Fischer; J Gao; M Hodoscek; W Im; K Kuczera; T Lazaridis; J Ma; V Ovchinnikov; E Paci; R W Pastor; C B Post; J Z Pu; M Schaefer; B Tidor; R M Venable; H L Woodcock; X Wu; W Yang; D M York; M Karplus
Journal:  J Comput Chem       Date:  2009-07-30       Impact factor: 3.376

Review 4.  Cathepsin B, Cathepsin H, and cathepsin L.

Authors:  A J Barrett; H Kirschke
Journal:  Methods Enzymol       Date:  1981       Impact factor: 1.600

Review 5.  Cysteine cathepsins: multifunctional enzymes in cancer.

Authors:  Mona Mostafa Mohamed; Bonnie F Sloane
Journal:  Nat Rev Cancer       Date:  2006-10       Impact factor: 60.716

6.  Automation of the CHARMM General Force Field (CGenFF) II: assignment of bonded parameters and partial atomic charges.

Authors:  K Vanommeslaeghe; E Prabhu Raman; A D MacKerell
Journal:  J Chem Inf Model       Date:  2012-11-28       Impact factor: 4.956

7.  Inhibition of cathepsin B reduces beta-amyloid production in regulated secretory vesicles of neuronal chromaffin cells: evidence for cathepsin B as a candidate beta-secretase of Alzheimer's disease.

Authors:  Vivian Hook; Thomas Toneff; Matthew Bogyo; Doron Greenbaum; Katalin F Medzihradszky; John Neveu; William Lane; Gregory Hook; Terry Reisine
Journal:  Biol Chem       Date:  2005-09       Impact factor: 3.915

8.  Cathepsin B activity regulation. Heparin-like glycosaminogylcans protect human cathepsin B from alkaline pH-induced inactivation.

Authors:  P C Almeida; I L Nantes; J R Chagas; C C Rizzi; A Faljoni-Alario; E Carmona; L Juliano; H B Nader; I L Tersariol
Journal:  J Biol Chem       Date:  2001-01-12       Impact factor: 5.157

9.  CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields.

Authors:  K Vanommeslaeghe; E Hatcher; C Acharya; S Kundu; S Zhong; J Shim; E Darian; O Guvench; P Lopes; I Vorobyov; A D Mackerell
Journal:  J Comput Chem       Date:  2010-03       Impact factor: 3.376

10.  Directory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking.

Authors:  Michael M Mysinger; Michael Carchia; John J Irwin; Brian K Shoichet
Journal:  J Med Chem       Date:  2012-07-05       Impact factor: 7.446

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  5 in total

Review 1.  Docking Screens for Novel Ligands Conferring New Biology.

Authors:  John J Irwin; Brian K Shoichet
Journal:  J Med Chem       Date:  2016-03-15       Impact factor: 7.446

2.  Ligand-Binding-Site Refinement to Generate Reliable Holo Protein Structure Conformations from Apo Structures.

Authors:  Hugo Guterres; Sang-Jun Park; Wei Jiang; Wonpil Im
Journal:  J Chem Inf Model       Date:  2020-12-18       Impact factor: 4.956

3.  Improving Protein-Ligand Docking Results with High-Throughput Molecular Dynamics Simulations.

Authors:  Hugo Guterres; Wonpil Im
Journal:  J Chem Inf Model       Date:  2020-04-10       Impact factor: 4.956

4.  PyPLIF HIPPOS and Receptor Ensemble Docking Increase the Prediction Accuracy of the Structure-Based Virtual Screening Protocol Targeting Acetylcholinesterase.

Authors:  Enade P Istyastono; Florentinus Dika Octa Riswanto; Nunung Yuniarti; Vivitri D Prasasty; Sudi Mungkasi
Journal:  Molecules       Date:  2022-09-02       Impact factor: 4.927

Review 5.  Structure-Based Virtual Screening: From Classical to Artificial Intelligence.

Authors:  Eduardo Habib Bechelane Maia; Letícia Cristina Assis; Tiago Alves de Oliveira; Alisson Marques da Silva; Alex Gutterres Taranto
Journal:  Front Chem       Date:  2020-04-28       Impact factor: 5.221

  5 in total

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