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\begin{document}

\title{Computational models in the service of X-ray and cryo-EM structure
determination}



\author[1]{Andriy Kryshtafovych}%
\author[2]{John Moult}%
\author[3]{Reinhard Albrecht}%
\author[4]{Geoffrey Chang}%
\author[2]{Kinlin Chao}%
\author[5]{Alec Fraser}%
\author[2]{Julia Greenfield}%
\author[3]{Marcus Hartmann}%
\author[6]{Oznat Herzberg}%
\author[7]{Inokentijs Josts}%
\author[5]{Petr Leiman}%
\author[2]{Sara Linden}%
\author[8]{Andrei N. Lupas}%
\author[6]{Daniel Nelson}%
\author[4]{Steven Rees}%
\author[2]{Xiaoran Shang}%
\author[9]{Maria Sokolova}%
\author[7]{Henning Tidow}%
\affil[1]{University of California Davis}%
\affil[2]{University of Maryland Biotechnology Institute}%
\affil[3]{Max Planck Institute for Developmental Biology}%
\affil[4]{University of California San Diego}%
\affil[5]{University of Texas Medical Branch at Galveston}%
\affil[6]{University of Maryland}%
\affil[7]{University of Hamburg}%
\affil[8]{Max-Planck-Inst. for Developmental Biology}%
\affil[9]{Skolkovo Institute of Science and Technology}%


\vspace{-1em}



  
  \date{June 14, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
CASP (Critical Assessment of Structure prediction) conducts community
experiments to determine the state of the art in computing protein
structure from amino acid sequence. The process relies on the
experimental community providing information about not yet public or
about to be solved structures, for use as targets. For some targets, the
experimental structure is not solved in time for use in CASP. Calculated
structure accuracy improved dramatically in this round, implying that
models should now be much more useful for resolving many sorts of
experimental difficulty. To test this, selected models for seven
unsolved targets were provided to the experimental groups. These models
were from the AlphaFold2 group, who overall submitted the most accurate
predictions in CASP14. Four targets were solved with the aid of the
models, and, additionally, the structure of an already solved target was
improved. An a-posteriori analysis showed that in some cases models from
other groups would also be effective. This paper provides accounts of
the successful application of models to structure determination,
including molecular replacement for X-ray crystallography, backbone
tracing and sequence positioning in a Cryo-EM structure, and correction
of local features. The results suggest that in future there will be
greatly increased synergy between computational and experimental
approaches to structure determination.%
\end{abstract}%



\sloppy


\textbf{Computational models in the service of X-ray and cryo-EM
structure determination}

Running title: Models in service

\textbf{Andriy Kryshtafovych} , \textsuperscript{1} - Genome Center,
University of California, Davis, California 95616, USA

\textbf{John Moult,} \textsuperscript{2} - Institute for Bioscience and
Biotechnology Research, Department of Cell Biology and Molecular
genetics, University of Maryland, 9600 Gudelsky Drive, Rockville, MD
20850, USA

\textbf{Reinhard Albrecht,} \textsuperscript{3} - Department of Protein
Evolution, Max Planck Institute for Developmental Biology, 72076
T\selectlanguage{ngerman}übingen, Germany

\textbf{Geoffrey A. Chang} , \textsuperscript{4} - Department of
Pharmacology, University of California-San Diego, La Jolla, CA, 92093,
USA

\textbf{Kinlin Chao} \textsuperscript{5}, Institute for Bioscience and
Biotechnology Research, University of Maryland, Rockville, MD 20850, USA

\textbf{Alec Fraser} , \textsuperscript{6} - Department of Biochemistry
and Molecular Biology, Sealy Center for Structural Biology and Molecular
Biophysics (SCSB), The University of Texas Medical Branch at Galveston,
TX 77555, USA

\textbf{Julia Greenfield} \textsuperscript{5}, Institute for Bioscience
and Biotechnology Research, University of Maryland, Rockville, MD 20850,
USA

\textbf{Marcus D. Hartmann} , \textsuperscript{3} - Department of
Protein Evolution, Max Planck Institute for Developmental Biology, 72076
Tübingen, Germany

\textbf{Osnat Herzberg} , \textsuperscript{5, 7} --
\textsuperscript{5}Institute for Bioscience and Biotechnology Research,
University of Maryland, Rockville, MD 20850, USA; \textsuperscript{7}
Department of Chemistry and Biochemistry, University of Maryland,
College Park, MD 20742, USA

\textbf{Inokentijs Josts,} \textsuperscript{8} - The Hamburg Advanced
Research Center for Bioorganic Chemistry (HARBOR) \& Department of
Chemistry, Institute for Biochemistry and Molecular Biology, University
of Hamburg, Luruper Chaussee 149, 22761 Hamburg, Germany

\textbf{Petr G. Leiman} , \textsuperscript{6} - Department of
Biochemistry and Molecular Biology, Sealy Center for Structural Biology
and Molecular Biophysics (SCSB), The University of Texas Medical Branch
at Galveston, TX 77555, USA

\textbf{Sara B. Linden} \textsuperscript{5} - Institute for Bioscience
and Biotechnology Research, University of Maryland, Rockville, MD 20850,
USA

\textbf{Andrei N. Lupas} , \textsuperscript{3} - Department of Protein
Evolution, Max Planck Institute for Developmental Biology, 72076
Tübingen, Germany

\textbf{Daniel C. Nelson} \textsuperscript{5, 9}
\textbf{-}\textsuperscript{5} Institute for Bioscience and Biotechnology
Research, University of Maryland, Rockville, MD 20850, USA;
\textsuperscript{9}Department of Veterinary Medicine, University of
Maryland, College Park, MD 20742, USA

\textbf{Steven D. Rees} , \textsuperscript{4} - Department of
Pharmacology, University of California-San Diego, La Jolla, CA, 92093,
USA

\textbf{Xiaoran Shang} \textsuperscript{5} - Institute for Bioscience
and Biotechnology Research, University of Maryland, Rockville, MD 20850,
USA

\textbf{Maria L. Sokolova,} \textsuperscript{10} - Center of Life
Sciences, Skolkovo Institute of Science and Technology, Moscow, 121205,
Russia

\textbf{Henning Tidow,} \textsuperscript{8} - The Hamburg Advanced
Research Center for Bioorganic Chemistry (HARBOR) \& Department of
Chemistry, Institute for Biochemistry and Molecular Biology, University
of Hamburg, Luruper Chaussee 149, 22761 Hamburg, Germany

and

\textbf{AlphaFold2 team} , \textsuperscript{11} - DeepMind, London, EC4A
3TW, UK

\textbf{Keywords:} X-ray crystallography; cryo-EM; CASP, Protein
Structure Prediction.

\textbf{Abbreviations: CASP:} community wide experiment on the Critical
Assessment of Techniques for Protein Structure Prediction;
\textbf{MR:}molecular replacement; \textbf{cryo-EM:} cryo-electron
microscopy;\textbf{NMR:} nuclear magnetic resonance



\textbf{Abstract}

CASP (Critical Assessment of Structure prediction) conducts community
experiments to determine the state of the art in computing protein
structure from amino acid sequence. The process relies on the
experimental community providing information about not yet public or
about to be solved structures, for use as targets. For some targets, the
experimental structure is not solved in time for use in CASP. Calculated
structure accuracy improved dramatically in this round, implying that
models should now be much more useful for resolving many sorts of
experimental difficulty. To test this, selected models for seven
unsolved targets were provided to the experimental groups. These models
were from the AlphaFold2 group, who overall submitted the most accurate
predictions in CASP14. Four targets were solved with the aid of the
models, and, additionally, the structure of an already solved target was
improved. An a-posteriori analysis showed that in some cases models from
other groups would also be effective. This paper provides accounts of
the successful application of models to structure determination,
including molecular replacement for X-ray crystallography, backbone
tracing and sequence positioning in a Cryo-EM structure, and correction
of local features. The results suggest that in future there will be
greatly increased synergy between computational and experimental
approaches to structure determination.



\textbf{Introduction}

Besides being a challenging and interesting problem in itself,
computational modeling of protein structure has significant practical
impact on the biomedical field\textsuperscript{1-3}. The most direct
application is in structural biology where models are used to help
determine protein structures by experimental methods including X-ray
crystallography, cryo-electron microscopy and NMR spectroscopy. In X-ray
crystallography, models are often used to solve the phase problem by
molecular replacement (MR), which relies on the existence of similar
protein structures or accurate models that serve as templates to be
placed in the crystal cell, consistent with the diffraction
data\textsuperscript{4}. In NMR, models can assist with the prediction
of chemical shifts and NMR spectra, or the interpretation of real
spectra (i.e., chemical shift assignments and then NOE assignments) and
in building structures that satisfy experimentally derived distance and
angle restraints\textsuperscript{5,6}. In cryo-EM, models are of value
for backbone tracing and fitting sequence into a map, especially at low
and moderate resolution (3.5-5.0 Å)\textsuperscript{7,8}. Regardless of
the structure determination technique, models can be used to identify
and sometimes fix problematic regions in experimental structures
\textsuperscript{9}. With the recent major advances in protein structure
modeling\textsuperscript{10-13}, it is clear that in future models will
play a substantially larger role in determining and validating
experimental structures.

In CASP, not-yet solved or not-yet released structures are solicited
from the experimental community as modeling targets. The suitability of
a structure as a target is largely determined by three factors:
estimated modeling difficulty (some may be too easy), whether there is
sufficient time available before experimental structure release, and
conversely, whether the experimental structure will be solved in time
for model assessment. Inevitably, some targets will encounter problems,
and normally have to be abandoned. There were eleven such targets in
CASP14, including seven where experimental data have been collected,
but, nevertheless, the structure could not be determined. Because of the
very high accuracy of many submitted models on other targets, especially
those from the AlphaFold2 group\textsuperscript{11,12}, the organizers
decided to see how many of the challenging structures could be resolved
with the aid of models. In previous CASPs, generated models have
occasionally helped solve structures. For example, the crystal structure
of Sla2 ANTH domain of Chaetomium thermophilum (CASP11 target T0839) was
determined by molecular replacement using CASP
models\textsuperscript{14} , but these have been exceptions. In CASP14,
four structures were solved with the aid of AlphaFold2 models. A
post-CASP analysis has shown\textsuperscript{15} that models from other
groups would also have been effective in some cases. In the three
remaining unsolved cases, poor data quality appears to have been the
issue. These are all `hard' targets with limited or no homology
information available for at least some domains, demonstrating the power
of the new methods for all classes of modeling difficulty. For one other
target, provision of the models resulted in correction of a local
experimental error. The paper discusses these success stories, with
content for each target provided by the corresponding experimental
group.

\textbf{Results}

\textbf{AlphaFold2 models help solve crystal structure of the inner
membrane reductase FoxB (CASP: T1058) by molecular replacement -- by IJ
and HT.}

From email to the CASP Prediction Center: \emph{The model you sent me
(from the leading group) worked for molecular replacement and we finally
solved the structure by MR-SAD. I am still astonished that the human
expert model worked, while none of the server models we tried did (as
they were rather similar). Henning Tidow}

\textbf{Brief description of the target}

Most microorganisms rely on the bioavailability of iron for their
survival. Due to the low solubility of ferric iron, they often use
secreted siderophores for the chelation and uptake of iron. In
Gram-negative bacteria, siderophores are usually taken up by
TonB-dependent transporters (TBDTs) located in the bacterial outer
membrane. The route of ferric-siderophores across the inner membrane
(IM) is less straightforward and differs across many bacterial species
and siderophore chemistries. Ferric-siderophore complexes are either
recognized by the dedicated periplasmic-binding proteins for delivery to
IM transporters for uptake into the cytoplasm or the iron is released
from the ferric-siderophore complexes by a reduction mechanism. The
Gram-negative bacterium \emph{Pseudomonas aeruginosa} (an opportunistic
human pathogen) is able to take up Fe-siderophore complexes called
ferrioxamines via a dedicated TBDT FoxA in an act of siderophore
piracy\textsuperscript{16}. For several years we also worked towards the
structure determination of FoxB, another protein of unknown function
located in the same operon as FoxA. With the help of the AlphaFold2
model generated in the course of the CASP14 competition, we were able to
determine the structure of FoxB. It possesses a novel fold with the
transmembrane domain harboring two heme molecules indicating a role as
inner membrane reductase involved in Fe-siderophore uptake and
processing\textsuperscript{17}.

\textbf{Workflow of how an AlphaFold2 model helped to solve the
structure}

Native FoxB crystals obtained in decyl-maltopyranoside (DM) diffracted
to approximately 5 Å resolution on average. Most of the crystals
belonged to the
P2\textsubscript{1}2\textsubscript{1}2\textsubscript{1}space group. All
crystals were obtained in 30\% PEG 600, 0.1 M BICINE pH 9, 0.1 M
ZnSO\textsubscript{4}. Use of a lipid-like peptide (LLP7) as additive
allowed us to collect several datasets extending to 3.4-3.5
Å\textsuperscript{18}.

All molecular replacement attempts using distant homologs and homology
models thereof failed. We acquired Se-Met anomalous data to 3.5 Å
resolution, with anomalous signal to 4.5 Å as well as anomalous data at
the Fe edge with anomalous signal to 4 Å, as we knew from spectroscopic
characterization that FoxB most likely contained at least one heme
group. Combining all anomalous data provided some experimental phases
and allowed partial model building. A single FoxB was present in the
asymmetric unit. However, phasing power was only sufficient to build
approximately 60-70\% of the backbone structure (Fig. 1). Although two
heme groups could be successfully placed, further tracing of the protein
backbone and confident sequence assignment was prevented by the low
number of Met residues (5/382) and low resolution of the datasets.
Lysozyme fusion at the N-terminus also resulted in crystals diffracting
to approximately 4.5 Å.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1}

\textbf{Figure 1.} (A) Partial FoxB model obtained by experimental
phasing before the CASP14 model became available. At this point the
model could not be further improved and the project was stuck for a
year. (B) Experimental phases with partial FoxB model (map shown at 1.2\selectlanguage{greek}σ
\selectlanguage{english}level).

At that point we were stuck with experimental phasing and submitted the
FoxB sequence to CASP14. The model provided by AlphaFold2
(T1058TS427\_3) resulted in a clear molecular replacement (MR) solution
(TFZ: 18.9 / LLG: 324). We have also succeeded in finding a suitable
crystal which diffracted to better than 3.5 \selectlanguage{ngerman}Å, the crystal belonged to
the P2\textsubscript{1}2\textsubscript{1}2 space group and contained 2
molecules of FoxB in the asymmetric unit. The final resolution of the
diffraction dataset after starANISO processing was 3.1 Å. Subsequent
MR-SAD and several rounds of building/refinement using
COOT\textsuperscript{19} and REFMAC\textsuperscript{20} further improved
the model and resulted in a good electron density map for the entire
protein. Anomalous difference maps were also used to validate the model
(Fig. 2).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Figure 2}

\textbf{Figure 2.} Workflow of FoxB structure determination. The
structure was determined by MR-SAD using the AlphaFold2 model and
experimental phases. (A) Anomalous difference map with Se and Fe sites
at 2\selectlanguage{greek}σ. \selectlanguage{english}(B) Overall map of FoxB after refinement (2\selectlanguage{greek}σ\selectlanguage{english}). (C) Superposition
of the final model (green) and AlphaFold2 model (cyan) shows excellent
agreement. Density for heme groups (not present in AlphaFold2 model) is
shown.

\textbf{Model accuracy}

The AlphaFold2 model that was used for the study (T1058TS427\_3) shows a
remarkable similarity to the final structure\textsuperscript{17}. The
overall RMSD is 1.17 \selectlanguage{ngerman}Å for all atoms and 0.973 Å for C\selectlanguage{greek}α \selectlanguage{english}atoms. Not only
were all transmembrane helices built and registered correctly, but also
the periplasmic domains containing several loops were modelled with high
accuracy. There was no density for the cytoplasmic loop connecting TM
helices 2 and 3 (residues 172-188), and it was therefore omitted from
the final model. Molecular replacement was only successful with the
AlphaFold2 model but not with server models from the CASP14 experiment
(\textgreater{}30 models tried, many of them with correct overall fold).

The success of the AlphaFold2 models seems to be due to their models
``getting the details right'', which was required for a clear MR
solution. As one example for the accuracy of the AlphaFold2 model, the
His residues coordinating the two heme groups in FoxB were positioned
correctly, although this model did not contain heme groups (as we only
provided the protein sequence to CASP14). This fact however, also
highlights a current limitation of the AlphaFold2 model: While it
provides an astonishing good model for the apo protein, it is obviously
still lacking the functional groups (two heme groups in case of FoxB),
which are responsible for the biological function.

\textbf{The astounding accuracy of AlphaFold2 models of all subunits of
phage AR9 non-virion RNA polymerase (CASP: T1092-T1096) -- by AF, MLS
and PGL.}

From email to the CASP Prediction Center: \emph{We are shocked\ldots{}
stunned\ldots{} by the quality of the model. You would not believe how
much effort we have put into getting this structure. Years of
work\ldots{} Both cryo-EM and crystallography\ldots{} I mean, this is
really shocking. Petr Leiman}

\textbf{Brief description of the target}

A group of large or ``jumbo'' bacteriophages, with genomes larger than
200 kbp, encode two distinct DNA-dependent RNA polymerases (RNAPs),
allowing these phages to assemble independently from the host
RNAP\textsuperscript{21-24}. One of these phage-encoded RNAPs is
packaged into the phage capsid and hence is called the virion RNAP
(vRNAP). Following the attachment to the host cell, the virus injects
the vRNAP together with its DNA into the host cytoplasm. After
injection, the vRNAP transcribes early phage genes, including those of
the second RNAP (the non-virion RNAP, nvRNAP). The latter transcribes
late genes, including those that encode for the vRNAP, which is then
packaged into newly assembled phage particles. The exact mechanism of
this temporal and spatial activation/regulation of transcription is
unclear but it is known that v- and nvRNAPs recognize different
promoters \textsuperscript{23}.

Both v- and nvRNAPs are distantly related to multi-subunit RNAPs
(msRNAPs) of bacteria, eukaryotes, and archaea\textsuperscript{23}. The
universally conserved core of cellular msRNAPs contains six subunits
\selectlanguage{greek}α\selectlanguage{english}\textsubscript{2}\selectlanguage{greek}ββ\selectlanguage{english}'o, \selectlanguage{english}and the catalytic cavity is formed by \selectlanguage{greek}β \selectlanguage{english}and
\selectlanguage{greek}β\selectlanguage{english}'\selectlanguage{english}\textsuperscript{25}. However, neither v- or nvRNAPs contain homologs
of \selectlanguage{greek}α \selectlanguage{english}or \selectlanguage{greek}ω \selectlanguage{english}subunits, and their \selectlanguage{greek}β \selectlanguage{english}and \selectlanguage{greek}β\selectlanguage{english}' \selectlanguage{english}subunits are split into two or
three separate genes that are located in different regions of the phage
genome. For sequence-specific initiation of transcription, the phage AR9
nvRNAP core is required to form a complex with a promoter specificity
subunit gene product 226 (gp226) that shows no sequence similarity to
any known bacterial, eukaryotic, or archaeal transcription initiation
factor. In fact, the amino acid sequence of gp226 was a singleton in the
GenBank database at the time of CASP14 experiment.

Besides employing a unique transcription factor, the AR9 nvRNAP
possesses a number of other distinct properties. Unlike any known
msRNAP, the AR9 nvRNAP recognizes the promoter in the template strand of
double stranded DNA and can initiate promoter-specific transcription on
single stranded DNA \textsuperscript{26}. Furthermore, as the genomic
DNA of bacteriophage AR9 contains deoxyuridine instead of
thymidine\textsuperscript{21}, the AR9 nvRNAP is critically sensitive to
the presence of uracils in two key positions of its promoter sequence,
and promoters with thymines in these positions are not recognized
\textsuperscript{26}. To understand the novel and unusual mechanism of
promoter recognition by the AR9 nvRNAP, we decided to determine the
structure of this enzyme in various states: in complex with the
specificity subunit and without it, and in DNA template-bound and
DNA-free forms. For the template, we used a short DNA oligonucleotide
that contained a promoter recognized by the AR9 nvRNAP \emph{in vivo}
and \emph{in vitro} .

\textbf{How AlphaFold2 models helped solve the structure}

The most feature-full and continuous electron density map of the AR9
nvRNAP was initially obtained by cryo-electron microscopy (cryo-EM)
imaging of the nvRNAP holoenzyme (i.e. containing the specificity
subunit) in complex with the promoter-containing DNA oligonucleotide.
This complex contained five polypeptide chains -- the specificity
subunit gp226, the N- and C-terminal parts of the \selectlanguage{greek}β \selectlanguage{english}subunit gp105 and
gp089 (respectively), and the N- and C-terminal parts of the \selectlanguage{greek}β\selectlanguage{english}' \selectlanguage{english}subunit
gp270 and gp154 (respectively) -- and the DNA oligonucleotide, the
structure of which will be described elsewhere. The cryo-EM
reconstruction was calculated using cryoSPARC\textsuperscript{27} and
had a resolution of 3.8 \selectlanguage{ngerman}Å.

In parallel, several maps of the AR9 nvRNAP \selectlanguage{greek}β-β\selectlanguage{english}' \selectlanguage{english}core (i.e. without the
specificity subunit) of varying quality and resolutions were obtained
using X-ray crystallography. The dataset that produced the best electron
density also extended to 3.8 \selectlanguage{ngerman}Å resolution, albeit this map was
significantly worse (poorer connectivity and quality of side chain
features) than the cryo-EM map. The phases for this dataset were
obtained by eight-fold non-crystallographic
averaging~\textsuperscript{28,29}of molecular replacement
phases\textsuperscript{30} calculated with the help of a partial model.
The latter was built using a single wavelength anomalous dispersion map
of a dataset with a smaller unit cell\textsuperscript{31-33}.

According to HHpred analysis at the time\textsuperscript{34}, the most
similar RNAP with a known atomic structure was that of
\emph{Mycobacterium tuberculosis} (PDB code 5ZX3\textsuperscript{35}).
The AR9 nvRNAP gp089, gp270, and gp154 proteins could all be aligned --
with a 20-24\% sequence identity and 100\% probabilities -- to
continuous stretches of the \emph{M. tuberculosis} RNAP \selectlanguage{greek}β \selectlanguage{english}and \selectlanguage{greek}β\selectlanguage{english}'
\selectlanguage{english}subunits. Gp105 was a more difficult target, with only its C-terminal
half being predicted to be similar to a fragment of the \emph{M.
tuberculosis} RNAP \selectlanguage{greek}β \selectlanguage{english}subunit with an 80\% probability and an E value of
2.3. The structure of gp226, as it was a unique sequence in the entire
GenBank, could not be reliably predicted by any tool.

Using both the best cryo-EM and X-ray maps of the AR9 nvRNAP and the
structure of the \emph{M. tuberculosis} RNAP as a chain-tracing guide in
stretches of high sequence similarity, we manually built
\textasciitilde{}90\% of the AR9 nvRNAP structure\textsuperscript{19}.
Some peripheral domains of gp105, gp154, and gp226 and regions for which
no homology models existed were particularly challenging. Fortunately,
while we were working on improving the cryo-EM map and X-ray phases to
make the structure building process for these regions possible, the
models of all five proteins produced by the AlphaFold2 team were made
available to us by the CASP14 organizers. To our amazement, the
AlphaFold2 models were of excellent quality and fit the cryo-EM and
X-ray maps near perfectly almost everywhere including the no-homology
regions (Fig. 3). This made the completion of the structure building
process nearly trivial.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\textbf{Figure 3}

\textbf{Figure 3} . AlphaFold2 models of AR9 nvRNAP proteins fit the
cryo-EM density nearly perfectly. The cryo-EM-derived structures of
gp105, gp154, and two gp226 domains are colored according to the color
code given in the upper left corner of each panel. All AlphaFold2 models
are colored magenta. The electron density is contoured at 4.25 standard
deviations above the mean and colored semi-transparent grey. Regions
where no cryo-EM-derived structure existed prior to the availability of
the AlphaFold2 models are indicated with a dashed line and their
boundary residues are labeled.

\textbf{The accuracy of AlphaFold2 models}

The AlphaFold2 models of individual domains were extremely similar to
the cryo-EM-derived structures. The only notable disagreement of
AlphaFold2 models with experimental data was in several regions of
subunit contacts some of which are shown in Fig. 4. The superposition of
cryo-EM-derived structures and AlphaFold2 models resulted in the
following root mean square deviations between the equivalent C\selectlanguage{greek}α \selectlanguage{english}atoms:
3.08 \selectlanguage{ngerman}Å (465 out of 484 atoms) for gp105, 2.00 Å (628 out of 649 atoms)
for gp089, 2.50 Å (417 out of 426 atoms) for gp270, 2.42 Å (629 out of
631 atoms) for gp154, 1.54 Å (256 out of 261 atoms) for the N-terminal
domain of gp226 (gp226 NTD), and 2.76 Å (169 out of 169 atoms) for the
C-terminal domain of gp226 (gp226 CTD). Notably, the AlphaFold2 models
were excellent at predicting the structure of dynamic peripheral domains
(e.g. the NTD and CTD of gp226). Additionally, the AlphaFold2 helped to
identify several \emph{cis} prolines, which significantly improved the
geometry of the surrounding regions.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\textbf{Figure 4}

\textbf{Figure 4} . Inaccuracies in AlphaFold2 models. Cryo-EM-derived
structures and AlphaFold2 models of several AR9 nvRNAP subunits are
superimposed and regions where the conformation of the AlphaFold2 model
deviates significantly from the cryo-EM-derived structure are indicated
with a dashed line and their boundary residues are labeled. Note that
the folds of both the N- and C-terminal domains of gp226 were predicted
correctly, but the structure of the interdomain linker and the relative
orientation of the two domains were incorrect.

The overall accuracy of AlphaFold2 models on multidomain targets was
lower than that on individual domains, albeit still remarkably good
(Fig. 4), and the structures of the four multidomain proteins that
comprise the \selectlanguage{greek}β-β\selectlanguage{english}' \selectlanguage{english}core of the AR9 nvRNAP were predicted correctly. The
model of the gp226 interdomain linker and, as a consequence, the
complete model of gp226 was incorrect, although this is hardly
surprising considering the fact that the interdomain linker does not
have a well-defined secondary structure.

Besides collecting cryo-EM data on the AR9 nvRNAP holoenzyme in complex
with the promoter-containing DNA oligonucleotide, we crystallized it
separately and collected X-ray diffraction data to 3.4 \selectlanguage{ngerman}Å resolution.
This dataset had a solvent content of \textasciitilde{}64\% and
contained one molecule of the complete holoenzyme-DNA complex in the
asymmetric unit of the \emph{C} 2 space group. As a final test of the
accuracy of the AlphaFold2 models, we examined whether they could serve
as search models for solving the phase problem of this dataset by
molecular replacement. The models of gp105, gp089, gp270, and gp154 were
used as is, without any modification. The gp226 model consisted of two
spatially separated globular domains (NTD) and (CTD) connected by a long
linker, so we treated the two domains as independent entities. We then
used Phaser \textsuperscript{30} to perform an automatic molecular
replacement procedure with these six sets of coordinates as search
models. The four proteins comprising the \selectlanguage{greek}β-β\selectlanguage{english}' \selectlanguage{english}core of the enzyme (gp105,
gp089, gp270, and gp154) were placed correctly while the placement of
both gp226 domains was incorrect. Manual inspection of the map showed
that an electron density for both domains of gp226 was present although
was weak, and that the density of a peripheral domain of gp154 was
slightly shifted compared to its location in the AlphaFold2 model. We
proceeded with fitting the AlphaFold2 models of both gp226 domains into
the density and adjusting the location of the peripheral gp154 domain --
all as rigid bodies -- using Coot \textsuperscript{19}. A subsequent
20-cycle restrained refinement run with Refmac5\textsuperscript{20}
brought the R-free factor to 39\%, which resulted in a much better and
cleaner electron density in which many of the minor model inaccuracies
(some of which are shown in Fig. 4) became obvious and could be easily
corrected using a long segment refine/morph procedure implemented in
Coot. Further corrections and refinement of the atomic model with
Refmac5\textsuperscript{20} and Phenix\textsuperscript{36} improved the
density and revealed the presence of the DNA oligonucleotide. Subsequent
rounds of refinement and model building made the AlphaFold2-derived
structure indistinguishable (within the expected accuracy) from that
obtained by an MR procedure that used the complete cryo-EM-derived
holoenzyme complex structure as a search model.

In conclusion we note that the AlphaFold2 team has clearly developed a
methodology to accurately predict the tertiary structure of individual
domains not only for proteins for which deep sequence alignments could
be built but even for unique proteins, such as AR9 gp226. Furthermore,
the structures of multidomain proteins, such as those comprising
individual subunits of the \selectlanguage{greek}β-β\selectlanguage{english}' \selectlanguage{english}core of the AR9 nvRNAP enzyme, were also
predicted with astounding accuracy. This places the AlphaFold2 team
within reach of predicting the quaternary structure of larger complexes,
and one can argue that they already demonstrated this by the accuracy of
their prediction of individual subunits of the AR9 nvRNAP \selectlanguage{greek}β-β\selectlanguage{english}' \selectlanguage{english}core that
could be assembled into a complex that closely resembles the
experimentally determined structure.

\textbf{AlphaFold2 helped correct cis and trans proline assignments and
the subsequent tracing of 20 amino acid residues in the crystal
structure of the baseplate anchor and partner TSP assembly region of
TSP4 from Bacteriophage CBA120 (CASP T1070) -- by OH, KC, XS, JG, SBL
and DCN}

From email to the CASP Prediction Center: \emph{Unbelievable. They
predicted residues 16-75 correctly with an RMS of 1.26 A. Also, the
prediction includes a different assignment of a cis proline (P236) than
my original assignment. It turned out that the predicted version is
correct because it enables repositioning of a tyrosine residue (Y247) in
the right place. The change, together with another adjustment ultimately
results in a 2-residue shift of 20 residues (237-256). Osnat Herzberg}

\textbf{3.1. Brief description of the target}

As a member of the recently defined \emph{Kuttervirus} genus,
the\emph{Escherichia coli} O157:H7 bacteriophage CBA120 infects multiple
hosts using four tailspike proteins (TSP1-4). Each TSP has a distinct
endo-glycosidase activity specific to the lipopolysaccharides of
different bacterial hosts. The four phage CBA120 TSPs are so far the
best characterized, thus they served as a paradigm for understanding the
infection mechanism and host range expansion characteristic to
the\emph{Kuttervirus} genus. All TSPs assemble into trimers and employ
the same overall fold of their catalytic domains (trimers of \selectlanguage{greek}β-\selectlanguage{english}helix
subunits). Nevertheless, within this fold, the different active site
architectures confer different endo-glycosidase substrate specificities,
which in turn facilitates the host range expansion of the
phage\textsuperscript{37-40}. The four TSPs form a complex, seen on
negative-stained electron micrographs as a branched appendage emanating
from the phage tail\textsuperscript{41}. The 335 N-terminal amino acids
of TSP4 mediate this assembly and anchoring function. The sequence of
this region (herewith termed TSP4-N) comprise the target submitted for
CASP14 structure prediction (target T1070). The crystal structure of
TSP4-N was determined initially at a resolution limit of 3.2 \selectlanguage{ngerman}Å using
Single-wavelength Anomalous Dispersion at the Se absorption edge of
crystals containing SeMet protein. This structure served as a Molecular
Replacement search model to determine the crystal structure of the
wild-type TSP4-N using crystals that diffracted to a resolution limit of
2.6 Å. Structure refinement of this crystal form yielded\emph{R} = 0.206
and \emph{R} \textsubscript{free} = 0.229.

Consistent with the full-length TSP4, the TSP4-N also assembled into
trimers. The structure revealed four domains connected by flexible
linkers. The 75 N-terminal amino acids comprise the domain that anchors
TSP4 to the phage tail baseplate (herewith termed AD). Of these,
approximately 50 amino acid residues fold into an intertwined triple
\selectlanguage{greek}β-\selectlanguage{english}helix, which then disengage to form an antiparallel \selectlanguage{greek}β-\selectlanguage{english}prism II from
the ensuing 25 residues, with each subunit contributing 3-stranded
antiparallel \selectlanguage{greek}β-\selectlanguage{english}sheet to the trimer prism (Fig. 5A). This was the most
challenging region for structure prediction because of its lack of
sequence homology to sequences of known protein structure. Following a
short linker region, the polypeptide chain folds into three domains
(herewith termed XD1-3) that recruit the partner TSPs. While XD1
exhibits a low but clear sequence identity to a domain of gp9 from phage
T4 baseplate (18\% over 95 of 100 shared amino acid residues), XD2 and
XD3 exhibit only remote sequence homology to proteins of known crystal
structure, which can be detected by Hidden Markov Model methods. Domain
XD1 adopts a mixed \selectlanguage{greek}β-\selectlanguage{english}sandwich fold, while both XD2 and XD3 adopt a
jellyroll fold. In the crystal structures, whether the trimers employ a
crystallographic or non-crystallographic 3-fold symmetry axis, all
domains obey the same 3-fold symmetry axis. The XD1 and XD3 monomers
form closely packed trimeric assemblies. However, XD2 subunits splay
apart and do not interact with one another even though they remain
related by the 3-fold symmetry axis. This spatial separation of XD2
subunits prevents binding of a trimeric partner TSP, and is probably a
crystal packing artifact. Indeed, a crystal structure of a protein
construct lacking the XD3 domain revealed closely packed XD2 subunits,
as necessary for binding of a trimeric TSP partner.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

\textbf{Figure 5.}

\textbf{Figure 5.} (A) The structure of TSP4-N homo-trimer with each
subunit in different color. The dash lines indicate structurally
disordered linkers between XD2 and XD3. (B) Superposition of XD2 as seen
in the crystal structure (magenta) and the structure predicted by group
427 (green) and group 226 (sky blue). (C) Superposition of AD crystal
structure (magenta) and the structure predicted by group 427 (green).

\textbf{3.2. How AlphaFold2 models helped improve the structure}

The 2.6 \selectlanguage{ngerman}Å resolution crystal structure of TSP4-N was determined by
Molecular Replacement using a low-resolution structure (3.2 Å) that was
initially built using the automated tracing program
Autobuild\textsuperscript{42}. Although the refinement progressed well,
a strong residual difference electron density associated with Ile247 in
the XD2 domain suggested that the experimental model required
modification. A close examination of the AlphaFold2 model and the
crystal structure revealed a polypeptide tracing error due to a wrong
assignment of two neighboring proline residues (Pro236 and Pro239)
carried over from the initial 3.2 Å structure. To better fit the
electron density map, Pro236, located on a tight turn, was assigned a
cis conformation, and Pro239 was assigned a trans conformation (Fig.
6A). Guided by the AlphaFold2 model, the two proline conformations were
switched (now trans Pro236 and cis Pro239), and their positions shifted.
The position of 20 amino acids were adjusted concomitantly so that
Tyr249 was placed at the initial Ile247 position, which eliminated the
residual difference electron density (Fig. 6B). This example
demonstrates that in the future, the highly accurate models generated by
AI methods will guide correct interpretations of low-resolution electron
density maps generated by x-ray crystallography and cryo-EM, whenever
difficulties exist in differentiating between cis and trans peptides.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image6/image6}

\end{center}
\end{figure}

\textbf{Figure 6.}

\textbf{Figure 6.} Polypeptide chain tracing errors that were corrected
by examination of the AlphaFold2 (group 427) structure. (A) The
incorrect model in the vicinity of two neighboring proline residues
(Pro236 and Pro239) together with the associated difference electron
density map with the coefficient
2F\textsubscript{o}-F\textsubscript{c}colored blue (left) and the model
corrected based on the AlphaFold2 predicted structure with the
associated 2F\textsubscript{o}-F\textsubscript{c} difference electron
density map (right). The cis bond conformations are highlighted in green
(B) The incorrect placement of Ile247 with the associated
2F\textsubscript{o}-F\textsubscript{c} difference electron density map
colored blue and the F\textsubscript{o}-F\textsubscript{c} difference
electron density map colored green (left). Correcting the positions of
Pro236 and Pro239 allowed placement of Tyr249 instead of Ile247 and
eliminated the residual F\textsubscript{o}-F\textsubscript{c} difference
electron density (right).

\textbf{3.3. Model accuracy}

We assessed the CASP14 predictions of TSP4-N by individual domains
because the flexible interdomain linkers may adopt different
conformations than those seen in the crystal structures. Several groups
predicted the correct folds of domains XD1-XD3, with different level of
accuracy. Overall, the AlphaFold2 predictions (DeepMind team, group 427)
were the most accurate with respect to the XD domains. Superposition of
the crystal structure and the AlphaFold2 model 1 using
PyMOL\textsuperscript{43} yielded root mean squared deviation (RMSD)
values for aligned C\selectlanguage{greek}α \selectlanguage{english}atoms of 0.38 \selectlanguage{ngerman}Å for XD1 (90 of 100 superposed
amino acid residues), 0.36 Å for XD2 (52 of 60 superposed amino acid
residues) and 0.63 Å for XD3 (63 of 65 superposed amino acid residues).
Several other CASP14 participants predicted the structures of these
domains successfully, typically with twice or more the RMSD values. Fig.
5B shows the superposition of the XD2 domain, illustrating the
remarkable similarity between the experimental and Alphafold2
structures, and also an excellent structure similarity produced by
another group, even though not as good as the AlphaFold2 structure
(ZhangTBM server, group 226, RMSD = 0.7-0.8 Å).

None of the structure predictions of the AD domain resembled the entire
triple \selectlanguage{greek}β-\selectlanguage{english}helix region. Nevertheless, the AlphaFold2 model of the AD
subunit contains a meandered polypeptide chain covering residues 20-50
that resembles the \selectlanguage{greek}β-\selectlanguage{english}helix trace seen in the crystal structure, with
RMSD value for 28 of the 31 aligned C\selectlanguage{greek}α \selectlanguage{english}atoms of 1.7 \selectlanguage{ngerman}Å. Moreover, the
predicted ensuing 3-stranded antiparallel \selectlanguage{greek}β-\selectlanguage{english}sheet that forms the
trimeric antiparallel \selectlanguage{greek}β-\selectlanguage{english}prism II (residues 51-75) is quite accurate,
with RMSD value for all 25 aligned C\selectlanguage{greek}α \selectlanguage{english}atoms of 0.65 \selectlanguage{ngerman}Å. In contrast, the
AlphaFold2 residues 1-19 diverge from the experimental structure and the
five deposited models exhibit a wide range of extended polypeptide chain
orientations. Fig. 5C illustrates this by superposing only the closely
related 3-stranded antiparallel \selectlanguage{greek}β-\selectlanguage{english}sheet regions of the X-ray structure
and the AlphaFold2 model 1. Considering that the AD triple \selectlanguage{greek}β-\selectlanguage{english}helix
polypeptide lacks significant amino acid sequence homology to those of
known protein structures, and that there are no intra subunit
interactions in triple \selectlanguage{greek}β-\selectlanguage{english}helices, it is surprising that the fold
calculated by the AI methods resembles at all the actual fold.

\textbf{AlphaFold2 models enable solving crystal structure of Af1503
transmembrane receptor (CASP: T1100) that withstood experimental
approaches for years -- by MDH, RA and ANL.}From email to the CASP
Prediction Center: \emph{I cannot overstate my excitement at the fact
that Marcus Hartmann solved the structure of Af1503 by molecular
replacement with the models of group g427. Andrei Lupas}

\textbf{Brief description of the target}

Our department has a long-standing interest in coiled coils and their
role in transmembrane signal transduction. Coiled coils are bundles of
\selectlanguage{greek}α-\selectlanguage{english}helices with a specific regular and repetitive
packing\textsuperscript{44}; they are found in innumerable structural
contexts in essentially all aspects of cell biology
\textsuperscript{45}. While their structural and functional roles are
well understood in many contexts, their role in transmembrane signal
transduction is still debated. Many transmembrane receptors are
homo-dimeric proteins in which a membrane-spanning coiled coil connects
extracellular sensor domains to intracellular effector domains, such
that signals have to be passed along the coiled-coil segment. To study
this process, we have been working on the minimalistic putative receptor
Af1503 from\emph{Archaeoglobus fulgidus} - fortuitously, we had already
entered its genomic neighbor, Af1502, into the CASP 11
experiment\textsuperscript{46,47}. Sequence analysis suggested that
Af1503 forms a homo-dimer merely consisting of an extracellular PAS
domain connected to an intracellular HAMP domain via an antiparallel
tetrameric coiled coil. While we conducted several structural studies on
the isolated HAMP domain\textsuperscript{48,49}and on chimeric fusion
proteins in which we fused the Af1503 HAMP domain to other coiled
coil-based signaling domains\textsuperscript{50,51}, we were so far
unable to determine the structure of the full
receptor\textsuperscript{52}.

\textbf{How AlphaFold2 models helped to solve the structure}

Our problems in obtaining the structure of the full receptor did not lie
in the behavior of the protein. The protein was very well behaved,
stable, and readily crystallized in a range of conditions. However,
crystal quality was very erratic, could not be improved systematically,
and diffraction was generally strongly anisotropic and not to high
resolution. This led to the failure of experimental phasing approaches,
despite several different strategies employed. On the other hand,
molecular replacement (MR) was not successful, as we only had the
structure of the HAMP domain as an available search model, and as the
approach was further complicated by the presence of translational
non-crystallographic symmetry. To aid MR, we decided to tackle a
truncated construct covering the extracellular PAS domain, but this
construct failed to crystallize. In contrast, we succeeded with an NMR
analysis of this construct, revealing the fold of the PAS domain, but
the structural models derived from the NMR data were too far from the
actual crystal structure to succeed in MR attempts.

Finally, years later, we easily managed to solve the crystal structure
using the AlphaFold2 models. As the predictions were modeled as
monomers, without constraints for the homo-dimeric state, they were not
fully compatible with the dimeric state along the whole chain, and a
very first, naive MR attempt employing a full model did not succeed.
However, in the second attempt, only employing a single PAS domain with
a short coiled-coil segment as a search model, the structure was
essentially solved using MOLREP with standard
parameters\textsuperscript{53}; after the correct placement and initial
refinement of the PAS domains, the electron density for the rest of the
protein was clearly traceable.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image7/image7}

\end{center}
\end{figure}

\textbf{Figure 7}

\textbf{Figure 7.} The crystal structure of dimeric Af1503 (grey) is
shown in a superposition with the best AlphaFold2 model (green,
monomer). The only noteworthy difference between the prediction and the
crystal structure is found in a loop in the PAS domain, which was found
to coordinate an ion in the crystal structure.

\textbf{Model accuracy}

Although the AlphaFold2 predictions were modeled as monomers that are
not fully compatible with the dimeric state of Af1503, the predicted
models superimpose closely on the final crystal structure (Fig. 7). Of
the five AlphaFold2 models, four are in a conformation that closely
matches the dimeric state, and all of them superimpose with an RMSD
below 2.5 \selectlanguage{ngerman}Å over their full length on all chains of the crystal
structure. Consequently, more focused, local superimpositions yield RMSD
values far below 2 Å. In short, the model accuracy is fairly close to
what one would expect for another crystal structure of the same protein.
There is just one region that deviates from the crystal structure: The
electron density revealed that an elongated loop within the PAS domain
is actually coordinating a metal ion, which has a pronounced impact on
its structure. Needless to say, AlphaFold2 did not predict the presence
and coordination of that ion, but nevertheless, it predicted this loop
in a conformation that is at least close to the ion-bound state.

\textbf{AlphaFold2 models aid in crystal structure determination of the
bacterial exo-sialidase Sia24 (CASP: T1089) by molecular replacement --
by SDR and GAC.}From email to the CASP Prediction Center: \emph{Models
1, 2, 3, and 5 worked quite well as an ensemble for molecular
replacement, and quite well on their own. We eventually achieved similar
results with an ensemble of current PDB models, but this one scored much
higher in MR from the beginning. Steven Rees}

\textbf{Brief description of the target}

Sialidase enzymes (or neuraminidases) cleave sialic acid (SA) moieties
found on mucin glycoproteins of the gastrointestinal (GI) tract, and are
utilized by microbial communities for the sequestration of SAs as
metabolic substrates, or (in the case of some pathogenic species) a
means of biofilm formation, surface adhesion, and revealing
toxin-binding sites\textsuperscript{54,55}. Exo-sialidases, which cleave
terminal SAs, are typically classified in the carbohydrate-active
enzymes database (CAZy) as GH family 33 (GH33) and are the most common
sialidases identified\textsuperscript{54,56,57}, typically utilizing a
two-step catalytic mechanism where a conserved Glu activates a spatially
proximal Tyr for nucleophilic attack of C5 of the SA, prompting
acid-base catalysis at C5 by an Asp residue\textsuperscript{58,59}.
While most sialidases characterized to date are ambivalent towards the
mammalian SAs Neu5Ac and Neu5Gc (differing only by a hydroxyl group at
the acetamido C5 on the latter), we and others characterized a series of
Neu5Gc-favoring sialidases in both the microbial communities of mice fed
Neu5Gc-enriched diets and a human population during Neu5Gc-enriched
dietary seasons \textsuperscript{59}. This study identified an
upregulation of Sia24, a Neu5Gc-favoring sialidase likely from
\emph{Bacteroides acidifaciens} with low sequence homology to published
sialidase structures.

\textbf{Methodology}

Sia24 was purified and concentrated to 10-12 mg/mL\textsuperscript{59},
and crystallized in 100 mM Bis-Tris pH 6.5 and 20\% polyethylene glycol
monomethyl ether 5,000. Crystals in the P4\textsubscript{1} space group
typically diffracted to 2.2-2.6 Å, with a single high-resolution dataset
collected at 2.0 Å. A more detailed description of the protein
production and crystallization are provided in the Supplementary
Material, and will be presented in a future study.

Our initial molecular replacement attempts used cross-species homolog
structures identified by sequence-based searches in the PDB. These
searches focused on using the catalytic domain of exo-sialidase models
derived from the GH33 family, as Sia24 lacks the carbohydrate-binding
motif found in some members. Various identified catalytic domain search
models (from PDB accession codes 1DIL, 1EUR, 1WCQ, 2VK5, 4FJ6, 4J9T,
4BBW, 4Q6K, and 5TSP) initially failed to find a reasonable phasing
solution by molecular replacement regardless of model modification
(e.g., poly-alanine, CCP4's Chainsaw-mediated side-chain pruning and
mutagenesis, and removal of flexible loop regions outside of canonical
beta-propeller domain secondary structure). \emph{Ab initio} models
generated by Robetta (https://robetta.bakerlab.org/) and
I-TASSER\textsuperscript{60-62} did not yield a solution by molecular
replacement. Phyre2\textsuperscript{63} offered reasonable solutions
(TFZ=14.1, LLG=194), as did using PHENIX.ENSEMBLER to generate an
ensemble of the nine models mentioned above (TFZ=16.9, LLG=256). Both of
these approaches struggled during subsequent refinement and manual
building steps, and the latter ensemble models lacked much of the Sia24
sequence because of low homology. Concurrently, we tried models of Sia24
generated by the AlphaFold2 team and provided by the CASP14 organizers.
Four of their five coordinate models were quickly successful in initial
phase estimation by molecular replacement after removal of flexible N-
and C-terminal regions, with model 2 (T1089TS427\_2) showing the highest
performance (TFZ=62.5, LLG=3791).

\textbf{Model accuracy}

AlphaFold2's model had high coordinate similarity (RMSD=1.08 Å on all
atoms, 0.55 Å after 5 cycles of outlier rejection) to the
crystallographic structure (PDB code 7MHU), and displays the
beta-propeller structure of the canonical exo-sialidase catalytic domain
(Fig. 8). Most side-chains are also reasonably oriented. The largest
deviations in the models were localized to the N- and C-termini and
regions between anti-parallel beta strand propeller motifs. The
low-homology model ensemble described above has a similar consistency,
albeit lacking most information on side-chain and flexible loop
placement. Similarly, models from other \emph{ab initio} methods display
reasonable overlap, but were not successful in initial molecular
replacement attempts.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image8/image8}

\end{center}
\end{figure}

\textbf{Figure 8}

\textbf{Figure 8.} Superposition of Sia24 predictive and
crystallographic models. The structure of Sia24 (dark blue) was solved
with initial phase determination by molecular replacement using a model
generated by AlphaFold2 (yellow).

Given the initial results for both Phyre2 and ensembled low-homology
models in molecular replacement, a solution for Sia24 without AlphaFold2
would have likely been eventually determined. However, the greatly
improved accuracy of the AlphaFold2 models, with all side chains and
flexible loops in place, is undeniable. Sia24 exhibits roughly 20\%
sequence homology with previously known structures, which in most cases
is at the threshold of likely success with molecular replacement for
most targets. AlphaFold2 was able to use information from known
structures in a novel way compared to previous algorithms, and provide
an effective solution where the alternatives struggled.

\textbf{Discussion}

This paper describes the solution of four experimental structures using
molecular replacement with models submitted to CASP14. We also report
improvement of an already solved target using models.

Molecular replacement is a very well established technique, but high
accuracy models are needed, and until now that has almost always
required the availability of templates based on high levels of sequence
identity \textsuperscript{64}. The three most recent CASPs have seen
dramatic improvements in the accuracy of non-homologous models, first
from the successful application of 3D contact prediction methods using
statistical approaches\textsuperscript{65} and then from the use of deep
learning methods\textsuperscript{13,66}. In CASP14, the Alphafold2 group
submitted models for many targets that rival the corresponding
experimental structures in accuracy\textsuperscript{10-13}. The
difficulties in obtaining experimental structures for seven of the
CASP14 targets provided an opportunity to objectively test the ability
of new methods in this respect. As the accounts in this paper show, the
models are indeed powerful.

A post-CASP analysis by Randy Read and colleagues\textsuperscript{15}
found that all CASP14 targets with available diffraction data could be
solved or at least partially solved using molecular replacement with
Alphafold2 models. The analysis implies that in future, structure
modeling should be a viable means of solving all but the most
challenging crystal structures with molecular replacement, providing
good data are available.

\textbf{Acknowledgements}

Initials of the authors contributing to specific sections are provided
in the sections' titles.

Idea, concept, abstract, introduction, discussion, editing and
coordination - by AK and JM.

CASP experiment is supported by the US National Institute of General
Medical Sciences (NIGMS/NIH), grant number GM100482.

OH and DNC studies were supported by US National Institute of General
Medical Sciences (NIGMS/NIH), grant number RO1GM110202.

\par\null

\textbf{FIGURE CAPTIONS}

\textbf{Figure 1.} (A) Partial FoxB model obtained by experimental
phasing before the CASP14 model became available. At this point the
model could not be further improved and the project was stuck for a
year. (B) Experimental phases with partial FoxB model (map shown at 1.2\selectlanguage{greek}σ
\selectlanguage{english}level).

\textbf{Figure 2.} Workflow of FoxB structure determination. The
structure was determined by MR-SAD using the AlphaFold2 model and
experimental phases. (A) Anomalous difference map with Se and Fe sites
at 2\selectlanguage{greek}σ. \selectlanguage{english}(B) Overall map of FoxB after refinement (2\selectlanguage{greek}σ\selectlanguage{english}). (C) Superposition
of the final model (green) and AlphaFold2 model (cyan) shows excellent
agreement. Density for heme groups (not present in AlphaFold2 model) is
shown.

\textbf{Figure 3} . AlphaFold2 models of AR9 nvRNAP proteins fit the
cryo-EM density nearly perfectly. The cryo-EM-derived structures of
gp105, gp154, and two gp226 domains are colored according to the color
code given in the upper left corner of each panel. All AlphaFold2 models
are colored magenta. The electron density is contoured at 4.25 standard
deviations above the mean and colored semi-transparent grey. Regions
where no cryo-EM-derived structure existed prior to the availability of
the AlphaFold2 models are indicated with a dashed line and their
boundary residues are labeled.

\textbf{Figure 4} . Inaccuracies in AlphaFold2 models. Cryo-EM-derived
structures and AlphaFold2 models of several AR9 nvRNAP subunits are
superimposed and regions where the conformation of the AlphaFold2 model
deviates significantly from the cryo-EM-derived structure are indicated
with a dashed line and their boundary residues are labeled. Note that
the folds of both the N- and C-terminal domains of gp226 were predicted
correctly, but the structure of the interdomain linker and the relative
orientation of the two domains were incorrect.

\textbf{Figure 5.} (A) The structure of TSP4-N homo-trimer with each
subunit in different color. The dash lines indicate structurally
disordered linkers between XD2 and XD3. (B) Superposition of XD2 as seen
in the crystal structure (magenta) and the structure predicted by group
427 (green) and group 226 (sky blue). (C) Superposition of AD crystal
structure (magenta) and the structure predicted by group 427 (green).

\textbf{Figure 6.} Polypeptide chain tracing errors that were corrected
by examination of the AlphaFold2 (group 427) structure. (A) The
incorrect model in the vicinity of two neighboring proline residues
(Pro236 and Pro239) together with the associated difference electron
density map with the coefficient
2F\textsubscript{o}-F\textsubscript{c}colored blue (left) and the model
corrected based on the AlphaFold2 predicted structure with the
associated 2F\textsubscript{o}-F\textsubscript{c} difference electron
density map (right). The cis bond conformations are highlighted in green
(B) The incorrect placement of Ile247 with the associated
2F\textsubscript{o}-F\textsubscript{c} difference electron density map
colored blue and the F\textsubscript{o}-F\textsubscript{c} difference
electron density map colored green (left). Correcting the positions of
Pro236 and Pro239 allowed placement of Tyr249 instead of Ile247 and
eliminated the residual F\textsubscript{o}-F\textsubscript{c} difference
electron density (right).

\textbf{Figure 7.} The crystal structure of dimeric Af1503 (grey) is
shown in a superposition with the best AlphaFold2 model (green,
monomer). The only noteworthy difference between the prediction and the
crystal structure is found in a loop in the PAS domain, which was found
to coordinate an ion in the crystal structure.

\textbf{Figure 8.} Superposition of Sia24 predictive and
crystallographic models. The structure of Sia24 (dark blue) was solved
with initial phase determination by molecular replacement using a model
generated by AlphaFold2 (yellow).

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