التفاصيل البيبلوغرافية
| العنوان: |
pyScoMotif: discovery of similar 3D structural motifs across proteins. |
| المؤلفون: |
Cia, Gabriel, Kwasigroch, Jean, Stamatopoulos, Basile, Rooman, Marianne, Pucci, Fabrizio |
| المصدر: |
Bioinformatics Advances; 2023, Vol. 3 Issue 1, p1-5, 5p |
| مصطلحات موضوعية: |
PROTEIN structure, DRUG discovery, BINDING sites, BIOINFORMATICS, COMPUTATIONAL biology |
| مستخلص: |
Motivation The fast and accurate detection of similar geometrical arrangements of protein residues, known as 3D structural motifs, is highly relevant for many applications such as binding region and catalytic site detection, drug discovery and structure conservation analyses. With the recent publication of new protein structure prediction methods, the number of available protein structures is exploding, which makes efficient and easy-to-use tools for identifying 3D structural motifs essential. Results We present an open-source Python package that enables the search for both exact and mutated motifs with position-specific residue substitutions. The tool is efficient, flexible, accurate, and suitable to run both on computer clusters and personal laptops. Two successful applications of pyScoMotif for catalytic site identification are showcased. Availability and implementation The pyScoMotif package can be installed from the PyPI repository and is also available at https://github.com/3BioCompBio/pyScoMotif. It is free to use for non-commercial purposes. [ABSTRACT FROM AUTHOR] |
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Copyright of Bioinformatics Advances is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| قاعدة البيانات: |
Complementary Index |
