Evidence map›Paper›PMID 27936493›Full record

ArticleProteins2017

New additions to the ClusPro server motivated by CAPRI.

Sandor Vajda, Christine Yueh, Dmitri Beglov, Tanggis Bohnuud, Scott E Mottarella, Bing Xia, David R Hall, Dima Kozakov

Abstract read
In one paragraph

Article in Proteins, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 321 papers.

0numbers the graph read from it
0cells of the map it votes in
321citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

321 citing papers in PubMed.

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  7. Breaking glycolysis: allosteric hotspots for multi-target drug repurposing.Journal of computer-aided molecular design · 2026
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261 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Sandor VajdaDepartment of Biomedical Engineering, Boston University, Boston, Massachusetts, 02215.
Christine YuehDepartment of Biomedical Engineering, Boston University, Boston, Massachusetts, 02215.
Dmitri BeglovDepartment of Biomedical Engineering, Boston University, Boston, Massachusetts, 02215.
Tanggis BohnuudDepartment of Biomedical Engineering, Boston University, Boston, Massachusetts, 02215.
Scott E MottarellaDepartment of Biomedical Engineering, Boston University, Boston, Massachusetts, 02215.
Bing XiaDepartment of Biomedical Engineering, Boston University, Boston, Massachusetts, 02215.
David R HallAcpharis Inc, Holliston, Massachusetts, 01746.
Dima KozakovDepartment of Applied Mathematics and Statistics, Stony Brook University, New York.

Funding

Analysis and Prediction of Molecular InteractionsR35GM118078 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI SANDOR VAJDA · 2016 to 2026
$6.5M
A MULTISTAGE APPROACH TO PROTEIN-PROTEIN DOCKINGR01GM061867 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI VAJDA, SANDOR · 2000 to 2016
$4.0M
Refinement Methods for Protein Docking based on Exploring Multi-Dimensional EnergR01GM093147 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI KOZAKOV, DMYTRO, PASCHALIDIS, IOANNIS · 2011 to 2014
$1.2M
NIGMS NIH HHS R01 GM061867NIGMS NIH HHS R01 GM093147NIGMS NIH HHS R35 GM118078
6 · The paper itself

Abstract

The heavily used protein-protein docking server ClusPro performs three computational steps as follows: (1) rigid body docking, (2) RMSD based clustering of the 1000 lowest energy structures, and (3) the removal of steric clashes by energy minimization. In response to challenges encountered in recent CAPRI targets, we added three new options to ClusPro. These are (1) accounting for small angle X-ray scattering data in docking; (2) considering pairwise interaction data as restraints; and (3) enabling discrimination between biological and crystallographic dimers. In addition, we have developed an extremely fast docking algorithm based on 5D rotational manifold FFT, and an algorithm for docking flexible peptides that include known sequence motifs. We feel that these developments will further improve the utility of ClusPro. However, CAPRI emphasized several shortcomings of the current server, including the problem of selecting the right energy parameters among the five options provided, and the problem of selecting the best models among the 10 generated for each parameter set. In addition, results convinced us that further development is needed for docking homology models. Finally, we discuss the difficulties we have encountered when attempting to develop a refinement algorithm that would be computationally efficient enough for inclusion in a heavily used server. Proteins 2017; 85:435-444. © 2016 Wiley Periodicals, Inc.

Indexed as

AlgorithmsSoftwareBenchmarkingBinding SitesCluster AnalysisComputational BiologyCrystallography, X-RayDatabases, ProteinInternetMolecular Docking SimulationProtein BindingProtein ConformationProtein Interaction MappingProtein MultimerizationProteinsResearch DesignProteinsWaterdimer classificationdocking with distance restraintspeptide-protein dockingprotein-protein dockingscoring functionsmall angle X-ray scattering datastructure refinement

Identifiers

PMID27936493
PMCPMC5313348

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.