ReviewJournal of industrial microbiology & biotechnology2017
Correlated positions in protein evolution and engineering.
Review in Journal of industrial microbiology & biotechnology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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.
Who cites it
7 citing papers in PubMed.
- Ancestral sequence reconstruction as a tool for structural analysis of modular polyketide synthases.Nature communications · 2025Article
- The many functions of carbohydrate-active enzymes in family GH65: diversity and application.Applied microbiology and biotechnology · 2024Review
- Discovery of a Kojibiose Hydrolase by Analysis of Specificity-Determining Correlated Positions in Glycoside Hydrolase Family 65.Molecules (Basel, Switzerland) · 2021Article
- Engineering of a Thermostable Biocatalyst for the Synthesis of 2-O-Glucosylglycerol.Chembiochem : a European journal of chemical biology · 2021Article
- Recent advances in user-friendly computational tools to engineer protein function.Briefings in bioinformatics · 2021Review
- A machine learning approach for reliable prediction of amino acid interactions and its application in the directed evolution of enantioselective enzymes.Scientific reports · 2018Article
- Co-evolution techniques are reshaping the way we do structural bioinformatics.F1000Research · 2017Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Statistical analysis of a protein multiple sequence alignment can reveal groups of positions that undergo interdependent mutations throughout evolution. At these so-called correlated positions, only certain combinations of amino acids appear to be viable for maintaining proper folding, stability, catalytic activity or specificity. Therefore, it is often speculated that they could be interesting guides for semi-rational protein engineering purposes. Because they are a fingerprint from protein evolution, their analysis may provide valuable insight into a protein's structure or function and furthermore, they may also be suitable target positions for mutagenesis. Unfortunately, little is currently known about the properties of these correlation networks and how they should be used in practice. This review summarises the recent findings, opportunities and pitfalls of the concept.
Indexed as
Identifiers
27514664What OpenQuestion holds
Registered trials
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.