Critical assessment of methods for predicting the 3D structure of proteins and protein complexes.
journal contributionposted on 2023-05-11, 09:21 authored by Shoshana J Wodak, Sandor Vajda, Marc F Lensink, Dima Kozakov, Paul A Bates
Advances in a scientific discipline are often measured by small, incremental steps. In this review, we report on two intertwined disciplines in the protein structure prediction field, modeling of single chains and modeling of complexes, that have over decades emulated this pattern, as monitored by the community-wide blind prediction experiments CASP and CAPRI. However, over the past few years, dramatic advances were observed for the accurate prediction of single protein chains, driven by a surge of deep learning methodologies entering the prediction field. We review the main scientific developments that enabled these recent breakthroughs and feature the important role of blind prediction experiments in building up and nurturing the structure prediction field. We discuss how the new wave of artificial intelligence-based methods is impacting the fields of computational and experimental structural biology and highlight areas in which deep learning methods are likely to lead to future developments, provided that major challenges are overcome. Expected final online publication date for the Annual Review of Biophysics, Volume 52 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.