Structure prediction of linear and cyclic peptides using CABS-flex.

The structural modeling of peptides can be a useful aid in the discovery of new drugs and a deeper understanding of the molecular mechanisms of life. Here we present a novel multiscale protocol for the structure prediction of linear and cyclic peptides. The protocol combines two main stages: coarse-grained simulations using the CABS-flex standalone package and an all-atom reconstruction-optimization process using the Modeller program. We evaluated the protocol on a set of linear peptides and two sets of cyclic peptides, with cyclization through the backbone and disulfide bonds. A comparison with other state-of-the-art tools (APPTEST, PEP-FOLD, ESMFold and AlphaFold implementation in ColabFold) shows that for most cases, AlphaFold offers the highest resolution. However, CABS-flex is competitive, particularly when it comes to short linear peptides. As demonstrated, the protocol performance can be further improved by combination with the residue-residue contact prediction method or more efficient scoring. The protocol is included in the CABS-flex standalone package along with online documentation to aid users in predicting the structure of peptides and mini-proteins. © The Author(s) 2024. Published by Oxford University Press.

Citation

Aleksandra Badaczewska-Dawid, Karol Wróblewski, Mateusz Kurcinski, Sebastian Kmiecik. Structure prediction of linear and cyclic peptides using CABS-flex. Briefings in bioinformatics. 2024 Jan 22;25(2)

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PMID: 38305457

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