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Wiley, Angewandte Chemie, 28(135), 2023

DOI: 10.1002/ange.202303526

Wiley, Angewandte Chemie International Edition, 28(62), 2023

DOI: 10.1002/anie.202303526

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Who Binds Better? Let Alphafold2 Decide!

Journal article published in 2023 by Julia K. Varga ORCID, Ora Schueler‐Furman ORCID
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Data provided by SHERPA/RoMEO

Abstract

AbstractDeep learning is revolutionizing structural biology to an unprecedented extent. Spearheaded by DeepMind's Alphafold2, structural models of high quality can be generated, and are now available for most known proteins and many protein interactions. The next challenge will be to leverage this rich structural corpus to learn about binding: which protein can contact which partner(s), and at what affinity? In a recent study, Chang and Perez have presented an elegant approach towards this challenging goal for interactions that involve a short peptide binding to its receptor. The basic idea is straightforward: given a receptor that binds to two peptides, if the receptor sequence is presented with both peptides together at the same time, AlphaFold2 should model the tighter binding peptide into the binding site, while excluding the second. A simple idea that works!