ArticleActa crystallographica. Section D, Structural biology2021
How do I get the most out of my protein sequence using bioinformatics tools?
Article in Acta crystallographica. Section D, Structural biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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.
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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.
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Who cites it
9 citing papers in PubMed.
- Directed evolution of phage Romulus in biofilm-embeddedBiofilm · 2026Article
- Design and validation of an inducible and curable EvolvR system for directed evolution inFrontiers in bioengineering and biotechnology · 2026Article
- Identification of a novel phage depolymerase against ST11 K64 carbapenem-resistantJournal of bacteriology · 2025Article
- Architecture remodeling activates the HerA-DUF anti-phage defense system.Molecular cell · 2025Article
- Article
- Expanding the viewpoint: Leveraging sequence information in enzymology.Current opinion in chemical biology · 2023Review
- SEQUENCE SLIDER: integration of structural and genetic data to characterize isoforms from natural sources.Nucleic acids research · 2022Article
- MrParse: finding homologues in the PDB and the EBI AlphaFold database for molecular replacement and more.Acta crystallographica. Section D, Structural biology · 2022Article
- Artificial intelligence for microbial biotechnology: beyond the hype.Microbial biotechnology · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Biochemical and biophysical experiments are essential for uncovering the three-dimensional structure and biological role of a protein of interest. However, meaningful predictions can frequently also be made using bioinformatics resources that transfer knowledge from a well studied protein to an uncharacterized protein based on their evolutionary relatedness. These predictions are helpful in developing specific hypotheses to guide wet-laboratory experiments. Commonly used bioinformatics resources include methods to identify and predict conserved sequence motifs, protein domains, transmembrane segments, signal sequences, and secondary as well as tertiary structure. Here, several such methods available through the MPI Bioinformatics Toolkit (https://toolkit.tuebingen.mpg.de) are described and how their combined use can provide meaningful information on a protein of unknown function is demonstrated. In particular, the identification of homologs of known structure using HHpred, internal repeats using HHrepID, coiled coils using PCOILS and DeepCoil, and transmembrane segments using Quick2D are focused on.
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