Introducing Pep McConst — A user-friendly peptide modeler for biophysical applications
Fabian Schuhmann, Vasili Korol, Ilia A. Solov'yov
Journal of Computational Chemistry
42
572-580
2021
abstract
We are introducing Pep McConst — a software that employs a Monte-Carlo algorithm to construct 3D structures of polypeptidechains which could subsequently be studied as stand-alone macromolecules or complement the structure of known proteins. Using an approach to avoid steric clashes, Pep 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 Pep 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.

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