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bioRxiv · 10.1101/2021.03.09.434600

APPTEST is an innovative new method for the automatic prediction of peptide tertiary structures

Timmons, P. B.·Hewage, C. M.
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Abstract

Good knowledge of a peptides tertiary structure is important for understanding its function and its interactions with its biological targets. APPTEST is a novel computational method that employs a neural network architecture and simulated annealing methods for the prediction of peptide tertiary structure from the primary sequence. APPTEST works for both linear and cyclic peptides of 5-40 natural amino acids. APPTEST is computationally efficient, returning predicted structures within a number of minutes. APPTEST performance was evaluated on a set of 356 test peptides; the best structure predicted for each peptide deviated by an average of 1.9[A] from its experimentally determined backbone conformation, and a native or near-native structure was predicted for 97% of the target sequences. A comparison of APPTEST performance with PEP-FOLD, PEPstrMOD and Peplook across benchmark datasets of short, long and cyclic peptides shows that on average APPTEST produces structures more-native than the existing methods in all three categories. This innovative, cutting-edge peptide structure prediction method is available as an online web server at https://research.timmons.eu/apptest, facilitating in silico study and design of peptides by the wider research community.

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Timmons, P. B., Hewage, C. M.. 2021-03-09. APPTEST is an innovative new method for the automatic prediction of peptide tertiary structures. https://doi.org/10.1101/2021.03.09.434600

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