Evidence map›Paper›PMID 32611389›Full record

ArticleBMC bioinformatics2020

Proteus: An algorithm for proposing stabilizing mutation pairs based on interactions observed in known protein 3D structures.

José Renato M S Barroso, Diego Mariano, Sandro R Dias, Rafael E O Rocha, Lucianna H Santos, Ronaldo A P Nagem, Raquel C de Melo-Minardi

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

4 citing papers in PubMed, 16 citations in OpenAlex.

  1. COCFrontiers in bioinformatics · 2025
    Article
  2. The stability and dynamics of computationally designed proteins.Protein engineering, design & selection : PEDS · 2022
    Review
  3. Article
  4. Article
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 2 institutions in 1 country.

José Renato M S BarrosoDepartment of Computer Science, Laboratory of Bioinformatics and Systems, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil.
Diego MarianoDepartment of Computer Science, Laboratory of Bioinformatics and Systems, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil. diegomariano@ufmg.br.ORCID http://orcid.org/0000-0002-5899-2052
Sandro R DiasDepartament of Computing, CEFET-MG, Belo Horizonte, 30510-000, Brazil.
Rafael E O RochaDepartment of Computer Science, Laboratory of Bioinformatics and Systems, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil.
Lucianna H SantosDepartment of Computer Science, Laboratory of Bioinformatics and Systems, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil.
Ronaldo A P NagemDepartment of Biochemistry and Immunology, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil. nagem@icb.ufmg.br.
Raquel C de Melo-MinardiDepartment of Computer Science, Laboratory of Bioinformatics and Systems, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil. raquelcm@dcc.ufmg.br.
Universidade Federal de Minas Gerais · BRFederal Center for Technological Education of Minas Gerais · BR

Funding

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 3379/2013 - 23038.010059/2013-15Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 51/2013 - 23038.004007/2014-82
6 · The paper itself

Abstract

backgroundProtein engineering has many applications for industry, such as the development of new drugs, vaccines, treatment therapies, food, and biofuel production. A common way to engineer a protein is to perform mutations in functionally essential residues to optimize their function. However, the discovery of beneficial mutations for proteins is a complex task, with a time-consuming and high cost for experimental validation. Hence, computational approaches have been used to propose new insights for experiments narrowing the search space and reducing the costs.

resultsIn this study, we developed Proteus (an acronym for Protein Engineering Supporter), a new algorithm for proposing mutation pairs in a target 3D structure. These suggestions are based on contacts observed in other known structures from Protein Data Bank (PDB). Proteus' basic assumption is that if a non-interacting pair of amino acid residues in the target structure is exchanged to an interacting pair, this could enhance protein stability. This trade is only allowed if the main-chain conformation of the residues involved in the contact is conserved. Furthermore, no steric impediment is expected between the proposed mutations and the surrounding protein atoms. To evaluate Proteus, we performed two case studies with proteins of industrial interests. In the first case study, we evaluated if the mutations suggested by Proteus for four protein structures enhance the number of inter-residue contacts. Our results suggest that most mutations proposed by Proteus increase the number of interactions into the protein. In the second case study, we used Proteus to suggest mutations for a lysozyme protein. Then, we compared Proteus' outcomes to mutations with available experimental evidence reported in the ProTherm database. Four mutations, in which our results agree with the experimental data, were found. This could be initial evidence that changes in the side-chain of some residues do not cause disturbances that harm protein structure stability.

conclusionWe believe that Proteus could be used combined with other methods to give new insights into the rational development of engineered proteins. Proteus user-friendly web-based tool is available at < http://proteus.dcc.ufmg.br >.

Indexed as

User-Computer InterfaceAlgorithmsDatabases, ProteinMuramidaseMutagenesisProtein EngineeringProteinsProtein Structure, TertiaryMuramidaseProteinsAlgorithmDatabaseMutationsProtein engineeringWebtool

Identifiers

PMID32611389
PMCPMC7330979
OpenAlexW3038717615

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.