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arXiv 2020年

作者： Grigas, Alex T. Mei, Zhe Treado, John D. Levine, Zachary A. Regan, Lynne O'Hern, Corey S. Graduate Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States Integrated Graduate Program in Physical and Engineering Biology Yale University New HavenCT06520 United States Department of Chemistry Yale University New HavenCT06520 United States Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Department of Pathology Yale University New HavenCT06520 United States Department of Molecular Biophysics and Biochemistry Yale University New HavenCT06520 United States Institute of Quantitative Biology Biochemistry and Biotechnology Centre for Synthetic and Systems Biology School of Biological Sciences University of Edinburgh Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States

The ability to consistently distinguish real protein structures from computationally generated model decoys is not yet a solved problem. One route to distinguish real protein structures from decoys is to delineate the important physical features that specify a real protein. For example, it has long been appreciated that the hydrophobic cores of proteins contribute signifficantly to their stability. As a dataset of decoys to compare with real protein structures, we studied submissions to the bi-annual CASP competition (speciffically CASP11, 12, and 13), in which researchers attempt to predict the structure of a protein only knowing its amino acid sequence. Our analysis reveals that many of the submissions possess cores that do not recapitulate the features that define real proteins. In particular, the model structures appear more densely packed (because of energetically unfavorable atomic overlaps), contain too few residues in the core, and have improper distributions of hydrophobic residues throughout the structure. Based on these observations, we developed a deep learning method, which incorporates key physical features of protein cores, to predict how well a computational model recapitulates the real protein structure without knowledge of the structure of the target sequence. By identifying the important features of protein structure, our method is able to rank decoys from the CASP competitions equally well, if not better than, state-of-the-art methods that incorporate many additional features. Copyright © 2020, The Authors. All rights reserved.

关键词： Proteins

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Investigation of RNA-RNA Interactions Using the RISE Database

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Current Protocols in Bioinformatics 2018年第1期64卷 e58/1-e58/1页

作者： Ju, Yanyan Gong, Jing Yang, Yucheng T. Zhang, Qiangfeng Cliff MOE Key Laboratory of Bioinformatics Beijing Advanced Innovation Center for Structural Biology Center for Synthetic and Systems Biology Tsinghua-Peking Joint Center for Life Sciences School of Life Sciences Tsinghua University Beijing China Department of Molecular Biophysics and Biochemistry Yale University New Haven CT United States Program in Computational Biology and Bioinformatics Yale University New Haven CT United States

RNA-RNA interactions (RRIs) are essential to understanding the regulatory mechanisms of RNAs. Mapping RRIs in vivo in a transcriptome-wide manner remained challenging until the recent development of several sequencing-based technologies. However, RRIs generated from large-scale studies had not been systematically collected and analyzed before. This article introduces RISE, a database of the RNA Interactome from Sequencing Experiments. RISE provides a comprehensive collection of RRIs in human, mouse, and yeast, derived from transcriptome-wide sequencing experiments, as well as targeted sequencing studies and other public databases/datasets. To facilitate better understanding of the biological roles of these RRIs, RISE also offers rich functional annotations involving RNAs, and an interactive interface to explore the analysis results. Here, we provide a brief description of the RISE website and a step-by-step protocol for using RISE to study RRIs. © 2018 by John Wiley & Sons, Inc. © 2018 John Wiley & Sons, Inc.

关键词： interaction RISE RNA RNA structure RNA-RNA sequencing experiments

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Mapping the interaction surface between Ca_Vβ and actin and its role in calcium channel clearance

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Nature Communications 2025年第1期16卷 1-21页

作者： Castilla, Francisco Lugo, Victor Miranda-Laferte, Erick Jordan, Nadine Huesgen, Pitter F. Santiago-Schübel, Beatrix Alfonso-Prieto, Mercedes Hidalgo, Patricia Institute of Biological Information Processing (IBI-1)—Molecular and Cellular Physiology Forschungszentrum Jülich Jülich Germany Graduate Program Faculty of Mathematics and Natural Sciences Heinrich-Heine University Düsseldorf Germany Central Institute of Engineering Electronics and Analytics (ZEA-3) Forschungszentrum Jülich Jülich Germany Institute of Biological Information Processing (IBI-7)—Structural Biochemistry Forschungszentrum Jülich Jülich Germany Institute of Neuroscience and Medicine (INM-9)—Computational Biomedicine Forschungszentrum Jülich Jülich Germany Cécile and Vogt Institute for Brain Research Medical Faculty Heinrich-Heine University Düsseldorf Germany Institute of Biochemistry Heinrich-Heine University Düsseldorf Germany Biologics Analytical Research and Development AbbVie Deutschland GmbH & Co. KG Ludwigshafen Germany Institute of Biology II University of Freiburg Freiburg Germany

Defective ion channel turnover and clearance of damaged proteins are associated with aging and neurodegeneration. The L-type CaV1.2 voltage-gated calcium channel mediates depolarization-induced calcium signals in hear...

Defective ion channel turnover and clearance of damaged proteins are associated with aging and neurodegeneration. The L-type Ca_V1.2 voltage-gated calcium channel mediates depolarization-induced calcium signals in heart and brain. Here, we determined the interaction surface between actin and two calcium channel subunits, Ca_Vβ₂ and Ca_Vβ₄, using cross-linking mass spectrometry and protein-protein docking, and uncovered a role in replenishing conduction-defective Ca_V1.2 channels. computational and in vitro mutagenesis identified hotspots in Ca_Vβ that decreased the affinity for actin but not for Ca_V1.2. When coexpressed with Ca_V1.2, none of the tested actin-association-deficient Ca_Vβ mutants altered the single-channel properties or the total number of channels at the cell surface. However, coexpression with the Ca_Vβ₂ hotspot mutant downregulated current amplitudes, and with a concomitant reduction in the number of functionally available channels, indicating that current inhibition resulted from a build-up of conduction silent channels. Our findings established Ca_Vβ₂–actin interaction as a key player for clearing the plasma membrane of corrupted Ca_V1.2 proteins to ensure the maintenance of a functional pool of channels and proper calcium signal transduction. The Ca_Vβ–actin molecular model introduces a potentially druggable protein-protein interface to intervene Ca_V-mediated signaling processes. © The Author(s) 2025.

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Proteome Analysis Using Gel-LC-MS/MS

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Current Protocols in Protein Science 2019年第1期96卷 e93页

作者： Goldman, Aaron R. Beer, Lynn A. Tang, Hsin-Yao Hembach, Peter Zayas-Bazan, Delaine Speicher, David W. Proteomics and Metabolomics Facility The Wistar Institute Philadelphia PA United States Center for Systems and Computational Biology and Molecular and Cellular Oncogenesis Program The Wistar Institute Philadelphia PA United States Biochemistry and Biophysics Graduate Group Perelman School of Medicine University of Pennsylvania Philadelphia PA United States

This article describes processing of protein samples using 1D SDS gels prior to protease digestion for proteomics workflows that subsequently utilize reversed-phase nanocapillary ultra-high-pressure liquid chromatography (LC) coupled to tandem mass spectrometry (MS/MS). The resulting LC-MS/MS data are used to identify peptides and thereby infer proteins present in samples ranging from simple mixtures to very complex proteomes. Bottom-up proteome studies usually involve quantitative comparisons across several or many samples. For either situation, 1D SDS gels represent a simple, widely available technique that can be used to either fractionate complex proteomes or rapidly clean up low microgram samples with minimal losses. After gel separation and staining/destaining, appropriate gel slices are excised, and in-gel reduction, alkylation, and protease digestion are performed. Digests are then processed for LC-MS/MS analysis. Protocols are described for either sample fractionation with high-throughput processing of many samples or simple cleanup without fractionation. An optional strategy is to conduct in-solution reduction and alkylation prior to running gels, which is advantageous when a large number of samples will be separated into large numbers of fractions. Optimization of trypsin digestion parameters and comparison to in-solution protease digestion are also described. © 2019 by John Wiley & Sons, Inc. © 2019 John Wiley & Sons, Inc.

关键词： gel-LC-MS/MS in-gel digestion LC-MS/MS mass spectrometry proteome fractionation proteomics SDS gels

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Author Correction: Cryo-EM structure and biochemical analysis reveal the basis of the functional difference between human PI3KC3-C1 and -C2

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Cell research 2020年第6期30卷 551-552页

作者： Meisheng Ma Jun-Jie Liu Yan Li Yuwei Huang Na Ta Yang Chen Hua Fu Ming-Da Ye Yuehe Ding Weijiao Huang Jia Wang Meng-Qiu Dong Li Yu Hong-Wei Wang The State Key Laboratory of Membrane Biology Tsinghua University-Peking University Joint Center for Life Sciences School of Life Sciences Tsinghua University Beijing 100084 China. Ministry of Education Key Laboratory of Protein Sciences Tsinghua-Peking Joint Center for Life Sciences Beijing Advanced Innovation Center for Structural Biology School of Life Sciences Tsinghua University Beijing 100084 China. Joint Graduate Program of Peking-Tsinghua-National Institute of Biological Science Tsinghua University Beijing 100084 China. Molecular Biophysics and Integrated Bioimaging Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. MOH Key Laboratory of Systems Biology of Pathogens Institute of Pathogen Biology Chinese Academy of Medical Sciences & Peking Union Medical College Beijing 100730 China. National Institute of Biological Sciences Beijing 102206 China. The State Key Laboratory of Membrane Biology Tsinghua University-Peking University Joint Center for Life Sciences School of Life Sciences Tsinghua University Beijing 100084 China. liyulab@***. Ministry of Education Key Laboratory of Protein Sciences Tsinghua-Peking Joint Center for Life Sciences Beijing Advanced Innovation Center for Structural Biology School of Life Sciences Tsinghua University Beijing 100084 China. hongweiwang@***.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Void distributions reveal structural link between jammed packings and protein cores

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Physical Review E 2019年第2期99卷 022416-022416页

作者： John D. Treado Zhe Mei Lynne Regan Corey S. O'Hern Department of Mechanical Engineering & Materials Science Yale University New Haven Connecticut 06520 USA Integrated Graduate Program in Physical & Engineering Biology Yale University New Haven Connecticut 06520 USA Department of Chemistry Yale University New Haven Connecticut 06520 USA Department of Molecular Biophysics & Biochemistry Yale University New Haven Connecticut 06520 USA Department of Physics Yale University New Haven Connecticut 06520 USA Department of Applied Physics Yale University New Haven Connecticut 06520 USA Program in Computational Biology and Bioinformatics Yale University New Haven Connecticut 06520 USA

Dense packing of hydrophobic residues in the cores of globular proteins determines their stability. Recently, we have shown that protein cores possess packing fraction ϕ≈0.56, which is the same as dense, random packing of amino-acid-shaped particles. In this article, we compare the structural properties of protein cores and jammed packings of amino-acid-shaped particles in much greater depth by measuring their local and connected void regions. We find that the distributions of surface Voronoi cell volumes and local porosities obey similar statistics in both systems. We also measure the probability that accessible, connected void regions percolate as a function of the size of a spherical probe particle and show that both systems possess the same critical probe size. We measure the critical exponent τ that characterizes the size distribution of connected void clusters at the onset of percolation. We find that the cluster size statistics are similar for void percolation in packings of amino-acid-shaped particles and randomly placed spheres, but different from that for void percolation in jammed sphere packings. We propose that the connected void regions are a defining structural feature of proteins and can be used to differentiate experimentally observed proteins from decoy structures that are generated using computational protein design software. This work emphasizes that jammed packings of amino-acid-shaped particles can serve as structural and mechanical analogs of protein cores, and could therefore be useful in modeling the response of protein cores to cavity-expanding and -reducing mutations.

关键词： Jamming Protein structure Packing & jamming problems Proteins Crystal structures Finite-size scaling molecular dynamics Percolation theory

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Current md forcefields fail to capture key features of protein structure and fluctuations: a case study of cyclophilin a and t4 lysozyme

arXiv

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arXiv 2020年

作者： Mei, Zhe Grigas, Alex T. Treado, John D. Corres, Gabriel Melendez Vuorte, Maisa Sammalkorpi, Maria Regan, Lynne Levine, Zachary A. O’Hern, Corey S. Department of Chemistry Yale University New HavenCT06520 United States Integrated Graduate Program in Physical and Engineering Biology Yale University New HavenCT06520 United States Graduate Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Department of Biology UPR Humacao Puerto RicoHumacao00792 Puerto Rico Department of Chemistry and Materials Science School of Chemical Engineering Aalto University Aalto Finland Department of Bioproducts and Biosystems School of Chemical Engineering Aalto University Aalto Finland Institute of Quantitative Biology Biochemistry and Biotechnology Center for Synthetic and Systems Biology School of Biological Sciences University of Edinburgh Edinburgh United Kingdom Department of Pathology Yale School of Medicine New HavenCT06520 United States Department of Molecular Biophysics and Biochemistry Yale University New HavenCT06520 United States Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States

Globular proteins undergo thermal fluctuations in solution, while maintaining an overall well-defined folded structure. In particular, studies have shown that the core structure of globular proteins differs in small, but significant ways when they are solved by x-ray crystallography versus solution-based NMR spectroscopy. Given these discrepancies, it is unclear whether molecular dynamics (MD) simulations can accurately recapitulate protein conformations. We therefore perform extensive MD simulations across multiple force fields and sampling techniques to investigate the degree to which computer simulations can capture the ensemble of conformations observed in experiments. By analyzing fluctuations in the atomic coordinates and core packing, we show that conformations sampled in MD simulations both move away from and sample a larger conformational space than the ensemble of structures observed in NMR experiments. However, we find that adding inter-residue distance restraints that match those obtained via Nuclear Overhauser Effect measurements enables the MD simulations to sample more NMR-like conformations, though significant differences between the core packing features in restrained MD and the NMR ensemble remain. Given that the protein structures obtained from the MD simulations possess smaller and less dense protein cores compared to those solved by NMR, we suggest that future improvements to MD forcefields should aim to increase the packing of hydrophobic residues in protein cores. © 2020, CC BY.

关键词： molecular dynamics

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Mitigation of Chromosome Loss in Clinical CRISPR-Cas9-Engineered T Cells

SSRN

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SSRN 2023年

作者： Tsuchida, Connor A. Brandes, Nadav Bueno, Raymund Trinidad, Marena Mazumder, Thomas Yu, Bingfei Hwang, Byungjin Chang, Christopher Liu, Jamin Sun, Yang Hopkins, Caitlin R. Parker, Kevin R. Qi, Yanyan Satpathy, Ansuman T. Stadtmauer, Edward A. Cate, Jamie H.D. Eyquem, Justin Fraietta, Joseph A. June, Carl H. Chang, Howard Y. Ye, Chun Jimmie Doudna, Jennifer A. University of California Berkeley - University of California San Francisco Graduate Program in Bioengineering University of California Berkeley BerkeleyCA United States Innovative Genomics Institute University of California Berkeley BerkeleyCA United States Division of Rheumatology Department of Medicine University of California San Francisco San FranciscoCA United States Center for Personal Dynamic Regulomes Stanford University StanfordCA United States Parker Institute for Cancer Immunotherapy Stanford University School of Medicine StanfordCA United States Biomedical Sciences Graduate Program University of California San Francisco San FranciscoCA United States Medical Scientist Training Program University of California San Francisco San FranciscoCA United States Department of Medicine University of California San Francisco San FranciscoCA United States Parker Institute for Cancer Immunotherapy San FranciscoCA United States Gladstone-UCSF Institute of Genomic Immunology San FranciscoCA United States Department of Biochemistry and Biophysics University of California San Francisco San FranciscoCA United States Abramson Cancer Center Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Parker Institute for Cancer Immunotherapy Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Center for Cellular Immunotherapies Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Microbiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology Stanford University School of Medicine StanfordCA United States Division of Hematology-Oncology Department of Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department o

CRISPR-Cas9 genome editing has enabled advanced T cell therapies, but occasional loss of the targeted chromosome could be a safety concern. To investigate whether Cas9-induced chromosome loss is a universal phenomenon and evaluate its clinical significance, we conducted a systematic analysis in primary human T cells. Arrayed and pooled CRISPR screens revealed that partial or entire chromosome loss after Cas9-induced DNA cutting is a rare but generalized phenomenon, occurring also in pre-clinical chimeric antigen receptor T cells. T cells with chromosome loss persist for weeks in culture, implying potential interference with clinical use. A modified cell manufacturing process, employed in our first-in-human clinical trial of Cas9-engineered T cells, dramatically reduced chromosome loss while largely preserving genome editing efficacy. Expression of p53 correlated with the protection from chromosome loss observed with this protocol, suggesting both a mechanism and a strategy for T cell engineering that mitigates genotoxicity in the clinic. © 2023, The Authors. All rights reserved.

关键词： T-cells

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Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

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NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine Ne

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The repertoire of mutational signatures in human cancer (vol 578, pg 94, 2020)

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NATURE 2023年第7948期614卷 E41-E41页

作者： Alexandrov, Ludmil B. Kim, Jaegil Haradhvala, Nicholas J. Huang, Mi Ni Ng, Alvin Wei Tian Wu, Yang Boot, Arnoud Covington, Kyle R. Gordenin, Dmitry A. Bergstrom, Erik N. Islam, S. M. Ashiqul Lopez-Bigas, Nuria Klimczak, Leszek J. McPherson, John R. Morganella, Sandro Sabarinathan, Radhakrishnan Wheeler, David A. Mustonen, Ville Getz, Gad Rozen, Steven G. Stratton, Michael R. Department of Cellular and Molecular Medicine Department of Bioengineering Moores Cancer Center University of California San Diego CA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Cellular and Molecular Medicine and Department of Bioengineering University of California San Diego La Jolla CA USA UC San Diego Moores Cancer Center San Diego CA USA University of California San Diego San Diego CA USA Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Massachusetts General Hospital Boston MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama Japan Computational Biology Program Ontario Institute for Cancer Research Toronto ON Canada Programme in Cancer & Stem Cell Biology Duke-NUS Medical School Singapore Singapore Centre for Computational Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Centre for Computational Biology Duke-NUS Medical School Singapore Singapore SingHealth Duke-NUS Institute of Precision Medicine National Heart Centre Singapore Singapore Singapore Cancer Science Institute of Singapore National University of Singapore Singapore Singapore Institute of Molecular and Cell Biology Singapore Singapore Laboratory of Cancer Epigenome Division of Medical Science National Cancer Centre Singapore Singapore Singapore Duke-NUS Medical School Singapore Singapore Human Genome Sequencing Center Baylor College of Medicine Houston TX USA Dan L. Duncan Cancer Center Baylor College of Medicine Houston TX USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Genome Integrity and Structural Biology Laboratory National Ins

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