Evidence map›Paper›PMID 26573864›Full record

ArticleJournal of structural and functional genomics2015

Automated protein motif generation in the structure-based protein function prediction tool ProMOL.

Mikhail Osipovitch, Mitchell Lambrecht, Cameron Baker, Shariq Madha, Jeffrey L Mills, Paul A Craig, Herbert J Bernstein

Open access · greenAbstract read
In one paragraph

Article in Journal of structural and functional genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.6field-weighted citation impact, top 35% of its field
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

8 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Genomic characterization of respiratoryFrontiers in microbiology · 2026
    Article
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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

7 authors at 1 institution in 1 country.

Mikhail OsipovitchGosnell School of Life Sciences, Rochester Institute of Technology, Rochester, NY, USA.
Mitchell LambrechtSchool of Chemistry and Materials Science, Rochester Institute of Technology, Rochester, NY, USA.
Cameron BakerGosnell School of Life Sciences, Rochester Institute of Technology, Rochester, NY, USA.
Shariq MadhaGosnell School of Life Sciences, Rochester Institute of Technology, Rochester, NY, USA.
Jeffrey L MillsSchool of Chemistry and Materials Science, Rochester Institute of Technology, Rochester, NY, USA.
Paul A CraigSchool of Chemistry and Materials Science, Rochester Institute of Technology, Rochester, NY, USA. paul.craig@rit.edu.ORCID http://orcid.org/0000-0002-2085-7816
Herbert J BernsteinSchool of Chemistry and Materials Science, Rochester Institute of Technology, Rochester, NY, USA.
Rochester Institute of Technology · US

Funding

SBEVSL -- Structural Biology Extensible Visualization Scripting LanguageR15GM078077 · NIGMS · DOWLING COLLEGE · PI BERNSTEIN, HERBERT J., CRAIG, PAUL A · 2006 to 2014
$855k
NIGMS NIH HHS GM078077NIGMS NIH HHS R15 GM078077
6 · The paper itself

Abstract

ProMOL, a plugin for the PyMOL molecular graphics system, is a structure-based protein function prediction tool. ProMOL includes a set of routines for building motif templates that are used for screening query structures for enzyme active sites. Previously, each motif template was generated manually and required supervision in the optimization of parameters for sensitivity and selectivity. We developed an algorithm and workflow for the automation of motif building and testing routines in ProMOL. The algorithm uses a set of empirically derived parameters for optimization and requires little user intervention. The automated motif generation algorithm was first tested in a performance comparison with a set of manually generated motifs based on identical active sites from the same 112 PDB entries. The two sets of motifs were equally effective in identifying alignments with homologs and in rejecting alignments with unrelated structures. A second set of 296 active site motifs were generated automatically, based on Catalytic Site Atlas entries with literature citations, as an expansion of the library of existing manually generated motif templates. The new motif templates exhibited comparable performance to the existing ones in terms of hit rates against native structures, homologs with the same EC and Pfam designations, and randomly selected unrelated structures with a different EC designation at the first EC digit, as well as in terms of RMSD values obtained from local structural alignments of motifs and query structures. This research is supported by NIH grant GM078077.

Indexed as

Amino Acid MotifsModels, MolecularProtein ConformationSoftwareAlgorithmsAmino Acid SequenceCatalytic DomainComputational BiologyDatabases, ProteinMolecular Sequence DataProteinsSequence AlignmentStructure-Activity RelationshipProteinsCatalytic site motifEnzymeMolecular visualizationProMOLPyMOLStructural bioinformaticsTemplate-based alignment

Identifiers

PMID26573864
PMCPMC4684744
OpenAlexW2180608901

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.