Article in Proteins, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Gang DongMax Perutz Labs, Vienna Biocenter, Medical University of Vienna, Vienna, Austria.ORCID 0000-0001-9745-8103
Rebecca DuBoisDepartment of Biomolecular Engineering, University of California, Santa Cruz, California, USA.ORCID 0000-0003-4185-5673
Deborah FassDepartment of Chemical and Structural Biology, Weizmann Institute of Science, Rehovot, Israel.ORCID 0000-0001-9418-6069
Juliana Martinez FiescoKinase Complexes Section, Center for Structural Biology, Center for Cancer Research, National Cancer Institute, Frederick, Maryland, USA.ORCID 0000-0002-2396-0974
Daniel R FoxDepartment of Microbiology, Biomedicine Discovery Institute, Monash University, Melbourne, Victoria, Australia.ORCID 0000-0003-0271-2776
Jonathan M GrimesDivision of Structural Biology, Centre for Human Genetics, University of Oxford, Oxford, UK.ORCID 0000-0001-9698-0389
Rhys GrinterDepartment of Microbiology, Biomedicine Discovery Institute, Monash University, Melbourne, Victoria, Australia.ORCID 0000-0002-8195-5348
Roman KamyshinskyDepartment of Chemical Research Support, Weizmann Institute of Science, Rehovot, Israel.ORCID 0000-0002-8546-7763
Jeremy R KeownSchool of Life Sciences, University of Warwick, Coventry, UK.ORCID 0000-0003-0159-9257
Gerald LacknerChair of Biochemistry of Microorganisms, University of Bayreuth, Kulmbach, Germany.ORCID 0000-0002-0307-8319
Michael LammersInstitute of Biochemistry, University of Greifswald, Greifswald, Germany.ORCID 0000-0003-4168-4640
Shiheng LiuDepartment of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, California, USA.ORCID 0000-0002-0561-1981
Gottfried J PalmInstitute of Biochemistry, University of Greifswald, Greifswald, Germany.ORCID 0000-0003-0329-0413
Christian SieboldDivision of Structural Biology, Centre for Human Genetics, University of Oxford, Oxford, UK.ORCID 0000-0002-6635-3621
Tiantian SuDepartment of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, California, USA.
Ping ZhangKinase Complexes Section, Center for Structural Biology, Center for Cancer Research, National Cancer Institute, Frederick, Maryland, USA.
Z Hong ZhouDepartment of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, California, USA.ORCID 0000-0002-8373-4717
Krzysztof FidelisGenome Center, University of California, Davis, California, USA.ORCID 0000-0002-8061-412X
Maya TopfLeibniz Institute of Virology and Centre for Structural Systems Biology, Deutsches Elektronen-Synchrotron, Hamburg, Germany.ORCID 0000-0002-8185-1215
John MoultDepartment of Cell Biology and Molecular Genetics, Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland, USA.ORCID 0000-0002-3012-2282
Structures and Mechanisms of Kinase Signaling ComplexesZIABC011744 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI ZHANG, PING · 2017 to 2025
$12.6M
Prospective analysis to determine model accuracy performance and boundaries in the post-AlphaFold2 environmentR01GM100482 · NIGMS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI FIDELIS, KRZYSZTOF A · 2012 to 2025
$11.1M
High-Resolution CryoEM Reconstruction of Large ComplexesR01GM071940 · NIGMS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ZHOU, Z HONG · 2006 to 2025
$5.0M
Structure-guided engineering to increase respiratory syncytial virus G protein immunogenicityR01AI166066 · NIAID · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI Rebecca Michelle DuBois, ROBERT J HOGAN · 2022 to 2026
$3.8M
HIGH-END CRYOEM INSTRUMENT FOR UCLA ELECTRON IMAGING CTR FOR NANOMACHINES: AIDSS10RR023057 · NCRR · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ZHOU, Z HONG · 2006 to 2006
$1.6M
Direct Detection Device for atomic resolution cryoEM of macromolecular complexesS10OD018111 · OD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ZHOU, Z HONG · 2014 to 2014
$598k
Agence Nationale de la Recherche ANR-10-IDEX-0002Agence Nationale de la Recherche ANR-10-INBS-05-02Agence Nationale de la Recherche ANR-16-CE11-0027Agence Nationale de la Recherche ANR-20-CE11-0023Agence Nationale de la Recherche CBH-EUR-GSANR-17-EURE-0003Agence Nationale de la Recherche IMCBioANR-17-EUR-0Australian Synchrotron, Part of ANSTO CAP20894Austrian Science Fund I5960-B2BBSRC and MIBTP BB/T00746X/1Cancer Research UK C20724/A26752Cancer Research UK DRCRPG-May23/100002Human Frontier Science Program LT000021/2014-LIntramural NIH HHS ZIA BC011744National Health and Medical Research Council APP1197376National Science Foundation DBI-1338135National Science Foundation DMR-1548924NCI NIH HHS ZIA BC 011744NCRR NIH HHS S10 RR023057NIAID NIH HHS R01 AI166066NIGMS NIH HHS R01 GM071940NIGMS NIH HHS R01 GM100482NIGMS NIH HHS R01GM100482NIH HHS S10 OD018111Université de StrasbourgUS National Institutes of Health R01GM071940US National Institutes of Health S10OD018111US National Institutes of Health S10RR23057Wellcome TrustWellcome Trust 200835/Z/16/Z
6 · The paper itself
Abstract
This article presents an in-depth analysis of selected CASP16 targets, with a focus on their biological and functional significance. The authors highlight the most relevant features of the target proteins and discuss how well these were reproduced in the submitted predictions. While the overall performance of structure prediction methods remains impressive, challenges persist, particularly in modeling rare structural motifs, flexible regions, small molecule interactions, posttranslational modifications, and biologically important interfaces. Addressing these limitations can strengthen the role of structure prediction in complementing experimental efforts and advancing both basic research and biomedical applications.
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Protein Target Highlights in CASP16: Insights From the Structure Providers. · full record | OpenQuestion