Evidence map›Paper›PMID 27517887›Full record

ArticleMolecules (Basel, Switzerland)2016

Predicting Protein-Protein Interactions Using BiGGER: Case Studies.

Rui M Almeida, Simone Dell'Acqua, Ludwig Krippahl, José J G Moura, Sofia R Pauleta

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Docking-Based Prediction of Peptide Binding to MHC Proteins.Methods in molecular biology (Clifton, N.J.) · 2023
    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

5 authors.

Rui M AlmeidaUCIBIO, REQUIMTE, Departamento de Química, Faculdade de Ciências e Tecnologia, NOVA, 2829-516 Caparica, Portugal. rui.almeida@fct.unl.pt.
Simone Dell'AcquaDepartment of Chemistry, University of Pavia, Via Taramelli 12, 27100 Pavia, Italy. simone.dellacqua@unipv.it.
Ludwig KrippahlCENTRIA, Departamento de Informática, Faculdade de Ciências e Tecnologia, NOVA, 2829-516 Caparica, Portugal. a4338@fct.unl.pt.
José J G MouraUCIBIO, REQUIMTE, Departamento de Química, Faculdade de Ciências e Tecnologia, NOVA, 2829-516 Caparica, Portugal. jjgm@fct.unl.pt.
Sofia R PauletaUCIBIO, REQUIMTE, Departamento de Química, Faculdade de Ciências e Tecnologia, NOVA, 2829-516 Caparica, Portugal. srp@fct.unl.pt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The importance of understanding interactomes makes preeminent the study of protein interactions and protein complexes. Traditionally, protein interactions have been elucidated by experimental methods or, with lower impact, by simulation with protein docking algorithms. This article describes features and applications of the BiGGER docking algorithm, which stands at the interface of these two approaches. BiGGER is a user-friendly docking algorithm that was specifically designed to incorporate experimental data at different stages of the simulation, to either guide the search for correct structures or help evaluate the results, in order to combine the reliability of hard data with the convenience of simulations. Herein, the applications of BiGGER are described by illustrative applications divided in three Case Studies: (Case Study A) in which no specific contact data is available; (Case Study B) when different experimental data (e.g., site-directed mutagenesis, properties of the complex, NMR chemical shift perturbation mapping, electron tunneling) on one of the partners is available; and (Case Study C) when experimental data are available for both interacting surfaces, which are used during the search and/or evaluation stage of the docking. This algorithm has been extensively used, evidencing its usefulness in a wide range of different biological research fields.

Indexed as

AlgorithmsMolecular Docking SimulationProteinsProteinsBiGGERdockingelectron transfer complexesmolecular recognitionNMRprotein-protein interactions

Identifiers

PMID27517887
PMCPMC6274584

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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.