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Introducing P ep McConst —A user‐friendly peptide modeler for biophysical applications
Author(s) -
Schuhmann Fabian,
Korol Vasili,
Solov'yov Ilia A.
Publication year - 2021
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.26479
Subject(s) - computer science , complement (music) , peptide , construct (python library) , software , steric effects , sequence (biology) , chemistry , amino acid , monte carlo method , computational biology , biochemistry , stereochemistry , biology , mathematics , programming language , gene , complementation , phenotype , statistics
We are introducing P ep McConst—a software that employs a Monte‐Carlo algorithm to construct 3D structures of polypeptide chains which could subsequently be studied as stand‐alone macromolecules or complement the structure of known proteins. Using an approach to avoid steric clashes, P ep McConst allows to create multiple structures for a predefined primary sequence of amino acids. These structures could then effectively be used for further structural analysis and investigations. The article introduces the algorithm and describes its user‐friendly approach that was made possible through the VIKING online platform. Finally, the manuscript provides several highlight examples where P ep McConst was used to predict the structure of the C‐terminal of a known protein, generate a missing bit of already crystallized protein structures and simply generate short polypeptide chains.