Literature DB >> 23744289

Small-molecule ligand docking into comparative models with Rosetta.

Steven A Combs1, Samuel L Deluca, Stephanie H Deluca, Gordon H Lemmon, David P Nannemann, Elizabeth D Nguyen, Jordan R Willis, Jonathan H Sheehan, Jens Meiler.   

Abstract

Structure-based drug design is frequently used to accelerate the development of small-molecule therapeutics. Although substantial progress has been made in X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy, the availability of high-resolution structures is limited owing to the frequent inability to crystallize or obtain sufficient NMR restraints for large or flexible proteins. Computational methods can be used to both predict unknown protein structures and model ligand interactions when experimental data are unavailable. This paper describes a comprehensive and detailed protocol using the Rosetta modeling suite to dock small-molecule ligands into comparative models. In the protocol presented here, we review the comparative modeling process, including sequence alignment, threading and loop building. Next, we cover docking a small-molecule ligand into the protein comparative model. In addition, we discuss criteria that can improve ligand docking into comparative models. Finally, and importantly, we present a strategy for assessing model quality. The entire protocol is presented on a single example selected solely for didactic purposes. The results are therefore not representative and do not replace benchmarks published elsewhere. We also provide an additional tutorial so that the user can gain hands-on experience in using Rosetta. The protocol should take 5-7 h, with additional time allocated for computer generation of models.

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Year:  2013        PMID: 23744289      PMCID: PMC5750396          DOI: 10.1038/nprot.2013.074

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  89 in total

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4.  Toward high-resolution de novo structure prediction for small proteins.

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Journal:  Nat Rev Drug Discov       Date:  2005-08       Impact factor: 84.694

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10.  De novo structure generation using chemical shifts for proteins with high-sequence identity but different folds.

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5.  PreDTIs: prediction of drug-target interactions based on multiple feature information using gradient boosting framework with data balancing and feature selection techniques.

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7.  Web-accessible molecular modeling with Rosetta: The Rosetta Online Server that Includes Everyone (ROSIE).

Authors:  Rocco Moretti; Sergey Lyskov; Rhiju Das; Jens Meiler; Jeffrey J Gray
Journal:  Protein Sci       Date:  2017-10-27       Impact factor: 6.725

8.  Nanomechanical properties of steric zipper globular structures.

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9.  A novel Ste20-related proline/alanine-rich kinase (SPAK)-independent pathway involving calcium-binding protein 39 (Cab39) and serine threonine kinase with no lysine member 4 (WNK4) in the activation of Na-K-Cl cotransporters.

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10.  Computational and biochemical docking of the irreversible cocaine analog RTI 82 directly demonstrates ligand positioning in the dopamine transporter central substrate-binding site.

Authors:  Rejwi Acharya Dahal; Akula Bala Pramod; Babita Sharma; Danielle Krout; James D Foster; Joo Hwan Cha; Jianjing Cao; Amy Hauck Newman; John R Lever; Roxanne A Vaughan; L Keith Henry
Journal:  J Biol Chem       Date:  2014-08-31       Impact factor: 5.157

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