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\begin{document}

\title{Estimation of Model Accuracy in CASP15 Using the ModFOLDdock Server}



\author[1]{Liam McGuffin}%
\author[1]{Nicholas S. Edmunds}%
\author[1]{Shuaa M. A. Alharbi}%
\author[1]{Ahmet G. Genc}%
\author[1]{Recep Adiyaman}%
\affil[1]{University of Reading School of Biological Sciences}%


\vspace{-1em}



  
  \date{May 27, 2024}


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\begin{abstract}
In CASP15 there was a greater emphasis on multimeric modelling than in
previous experiments, with assembly structures nearly doubling in number
(41 up from 22) since the previous round. CASP15 also included a new
estimation of model accuracy (EMA) category in recognition of the
importance of objective quality assessment for quaternary structure
models. ModFOLDdock is a multimeric model quality assessment server
developed by the McGuffin group at the University of Reading, which
brings together a range of single-model, clustering and deep learning
methods to form a consensus of approaches. For CASP15 three variants of
ModFOLDdock were developed to optimise for the different facets of the
quality estimation problem. The standard ModFOLDdock variant produced
predicted scores optimised for positive linear correlations with the
observed scores. The ModFOLDdockR variant produced predicted scores
optimised for ranking, i.e., the top-ranked models have highest
accuracy. In addition, the ModFOLDdockS variant used a quasi-single
model approach to score each model on an individual basis. The scores
from all three variants achieved strongly positive Pearson correlation
coefficients with the CASP observed scores (oligo-lDDT) in excess of
0.70, which were maintained across both homomeric and heteromeric model
populations. In addition, at least one of the ModFOLDdock variants was
consistently ranked in the top two methods across all three EMA
categories. Specifically, for overall global fold prediction accuracy,
ModFOLDdock placed second and ModFOLDdockR placed third; for overall
interface quality prediction accuracy ModFOLDdockR, ModFOLDdock and
ModFOLDdockS were placed above all other predictor methods, and
ModFOLDdockR and ModFOLDdockS were placed second and third respectively
for individual residue confidence scores. The ModFOLDdock server is
available at:
{[}https://www.reading.ac.uk/bioinf/ModFOLDdock/{]}(https://www.reading.ac.uk/bioinf/ModFOLDdock/).
ModFOLDdock is also available as part of the MultiFOLD docker package:
{[}https://hub.docker.com/r/mcguffin/multifold{]}(https://hub.docker.com/r/mcguffin/multifold)%
\end{abstract}%



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\verb`ModFOLDdock_Proteins_Final.docx`  available at \url{https://authorea.com/users/602656/articles/633404-estimation-of-model-accuracy-in-casp15-using-the-modfolddock-server}\selectlanguage{english}
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