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\begin{document}

\title{Tertiary structure assessment at CASP15}



\author[1]{Daniel Rigden}%
\author[1]{Adam Simpkin}%
\author[1]{Shahram Mesdaghi}%
\author[1]{Filomeno Sánchez Rodríguez}%
\author[1]{Luc Elliott}%
\author[1]{David Murphy}%
\author[2]{Andriy Kryshtafovych}%
\author[3]{Ronan Keegan}%
\affil[1]{University of Liverpool Institute of Systems Molecular and Integrative Biology}%
\affil[2]{University of California Davis Genome Center}%
\affil[3]{Rutherford Appleton Laboratory}%


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  \date{May 13, 2024}


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\begin{abstract}
The results of tertiary structure assessment at CASP15 are reported. For
the first time, recognising the outstanding performance of AlphaFold 2
(AF2) at CASP14, all single chain predictions were assessed together,
irrespective of whether a template was available. At CASP15 there was no
single stand-out group, with most of the best-scoring groups - led by
PEZYFoldings, UM-TBM and Yang Server - employing AF2 in one way or
another. Many top groups paid special attention to generating deep
Multiple Sequence Alignments (MSAs) and testing variant MSAs, thereby
allowing them to successfully address some of the hardest targets. Such
difficult targets, as well as lacking templates, were typically proteins
with few homologues: small size, high \selectlanguage{greek}α-\selectlanguage{english}helical content and monomeric
structure were other likely aggravating factors. Local divergence
between prediction and target correlated with localisation at crystal
lattice or chain interfaces, and with regions exhibiting high B-factor
factors in crystal structure targets, but should not necessarily be
considered as representing error in the prediction. However, analysis of
exposed and buried side chain accuracy showed room for improvement even
in the latter. Nevertheless, a majority of groups, including those
applying methods similar to those used to generate major resources such
as the AlphaFold Protein Structure Database and the ESM Metagenomic
atlas, produced high quality predictions for most targets which are
valuable for experimental structure determination, functional analysis
and many other tasks across biology.%
\end{abstract}%



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