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Publisher Correction: MEMOTE for standardized genome-scale metabolic model testing

Nature biotechnology 2020年第4期38卷 504页

作者： Christian Lieven Moritz E Beber Brett G Olivier Frank T Bergmann Meric Ataman Parizad Babaei Jennifer A Bartell Lars M Blank Siddharth Chauhan Kevin Correia Christian Diener Andreas Dräger Birgitta E Ebert Janaka N Edirisinghe José P Faria Adam M Feist Georgios Fengos Ronan M T Fleming Beatriz García-Jiménez Vassily Hatzimanikatis Wout van Helvoirt Christopher S Henry Henning Hermjakob Markus J Herrgård Ali Kaafarani Hyun Uk Kim Zachary King Steffen Klamt Edda Klipp Jasper J Koehorst Matthias König Meiyappan Lakshmanan Dong-Yup Lee Sang Yup Lee Sunjae Lee Nathan E Lewis Filipe Liu Hongwu Ma Daniel Machado Radhakrishnan Mahadevan Paulo Maia Adil Mardinoglu Gregory L Medlock Jonathan M Monk Jens Nielsen Lars Keld Nielsen Juan Nogales Intawat Nookaew Bernhard O Palsson Jason A Papin Kiran R Patil Mark Poolman Nathan D Price Osbaldo Resendis-Antonio Anne Richelle Isabel Rocha Benjamín J Sánchez Peter J Schaap Rahuman S Malik Sheriff Saeed Shoaie Nikolaus Sonnenschein Bas Teusink Paulo Vilaça Jon Olav Vik Judith A H Wodke Joana C Xavier Qianqian Yuan Maksim Zakhartsev Cheng Zhang Novo Nordisk Foundation Center for Biosustainability Technical University of Denmark Lyngby Denmark. Systems Biology Lab Amsterdam Institute of Molecular and Life Sciences (AIMMS) Vrije Universiteit Amsterdam Amsterdam the Netherlands. BioQUANT/COS Heidelberg University Heidelberg Germany. Ecole Polytechnique Fédérale de Lausanne Laboratory of Computational Systems Biotechnology Lausanne Switzerland. iAMB-Institute of Applied Microbiology ABBt-Aachen Biology and Biotechnology RWTH Aachen University Aachen Germany. Department of Bioengineering University of California La Jolla CA USA. Department of Chemical Engineering and Applied Chemistry University of Toronto Toronto Ontario Canada. Human Systems Biology Laboratory Instituto Nacional de Medicina Genomica & Coordinación de la Investigación Científica-Red de Apoyo a la Investigación UNAM Mexico City Mexico. Institute for Systems Biology Seattle WA USA. Computational Systems Biology of Infection and Antimicrobial-Resistant Pathogens Institute for Biomedical Informatics (IBMI) Tübingen Germany. Department of Computer Science University of Tübingen Tübingen Germany. German Center for Infection Research (DZIF) partner site Tübingen Tübingen Germany. Australian Institute for Bioengineering and Nanotechnology The University of Queensland Brisbane Queensland Australia. Argonne National Laboratory Lemont IL USA. Analytical Biosciences Division of Systems Biomedicine and Pharmacology Leiden Academic Centre for Drug Research Leiden University Leiden the Netherlands. Department of Systems Biology Centro Nacional de Biotecnología Consejo Superior de Investigaciones Científicas (CNB-CSIC) Madrid Spain. Centro de Biotecnología y Genómica de Plantas (CBGP UPM-INIA) Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA) Madrid Spain. Department of Animal and Aquacultural Sciences Faculty of Biosciences Norwegian University of Life Sciences Oslo Norway

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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Cover Image, Volume 86, Issue 5

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Proteins: Structure, Function, and Bioinformatics 2018年第5期86卷

作者： J. C. Gaines S. Acebes A. Virrueta M. Butler L. Regan C. S. O'Hern Program in Computational Biology and Bioinformatics Yale University New Haven Connecticut 06520 Integrated Graduate Program in Physical and Engineering Biology (IGPPEB) Yale University New Haven Connecticut 06520 Department of Mechanical Engineering and Materials Science Yale University New Haven Connecticut 06520 Department of Physics and Astronomy University of Southern California Los Angeles California 90007 Department of Molecular Biophysics & Biochemistry Yale University New Haven Connecticut 06520 Department of Chemistry Yale University New Haven Connecticut 06520 Department of Physics Yale University New Haven Connecticut 06520 Department of Applied Physics Yale University New Haven Connecticut 06520

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Evaluating drug targets through human loss-of-function genetic variation (vol 581, pg 459, 2020)

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NATURE 2021年第7846期590卷 E56-E56页

作者： Minikel, Eric Vallabh Karczewski, Konrad J. Martin, Hilary C. Cummings, Beryl B. Whiffin, Nicola Rhodes, Daniel Alfoldi, Jessica Trembath, Richard C. van Heel, David A. Daly, Mark J. Schreiber, Stuart L. MacArthur, Daniel G. Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge MA USA Chemical Biology and Therapeutics Science Program Broad Institute of MIT and Harvard Cambridge MA USA Analytical and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Program in Biological and Biomedical Sciences Harvard Medical School Boston MA USA Henry and Allison McCance Center for Brain Health Massachusetts General Hospital Boston MA USA Department of Neurology Massachusetts General Hospital Boston MA USA Prion Alliance Cambridge MA USA National Heart and Lung Institute and MRC London Institute of Medical Sciences Imperial College London London UK National Heart & Lung Institute and MRC London Institute of Medical Sciences Imperial College London London UK Cardiovascular Research Centre Royal Brompton & Harefield Hospitals NHS Trust London UK European Molecular Biology Laboratory European Bioinformatics Institute Wellcome Genome Campus Hinxton Cambridge UK Center for Genomic Medicine Massachusetts General Hospital Boston MA USA Program in Bioinformatics and Integrative Genomics Harvard Medical School Boston MA USA Broad Genomics Broad Institute of MIT and Harvard Cambridge MA USA Division of Genetics and Genomics Boston Children’s Hospital Boston MA USA Department of Pediatrics Harvard Medical School Boston MA USA Cardiac Arrhythmia Service and Cardiovascular Research Center Massachusetts General Hospital Boston MA USA Estonian Genome Center Institute of Genomics University of Tartu Tartu Estonia Department of Medicine Harvard Medical School Boston MA USA Cardiac Arrhythmia Service Massachusetts General Hospital Boston MA USA Centre for Population Genomics Garvan Institute of Medical Research and UNSW Sydney Sydney Australia Centre for Population Genomics Murdoch Children’s Research Institute Melbourne Australia Divi

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Transcript expression-aware annotation improves rare variant interpretation (vol 581, pg 452, 2020)

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NATURE 2021年第7846期590卷 E54-E54页

作者： Cummings, Beryl B. Karczewski, Konrad J. Kosmicki, Jack A. Seaby, Eleanor G. Watts, Nicholas A. Singer-Berk, Moriel Mudge, Jonathan M. Karjalainen, Juha Satterstrom, F. Kyle O'Donnell-Luria, Anne H. Poterba, Timothy Seed, Cotton Solomonson, Matthew Alfoldi, Jessica Daly, Mark J. MacArthur, Daniel G. Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Analytical and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Program in Biological and Biomedical Sciences Harvard Medical School Boston MA USA Program in Bioinformatics and Integrative Genomics Harvard Medical School Boston MA USA Genomic Informatics Group University Hospital Southampton Southampton UK Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge MA USA Division of Genetics and Genomics Boston Children’s Hospital Boston MA USA Department of Pediatrics Harvard Medical School Boston MA USA European Molecular Biology Laboratory European Bioinformatics Institute Wellcome Genome Campus Hinxton Cambridge UK Center for Genomic Medicine Massachusetts General Hospital Boston MA USA Broad Genomics Broad Institute of MIT and Harvard Cambridge MA USA National Heart & Lung Institute and MRC London Institute of Medical Sciences Imperial College London London UK Cardiovascular Research Centre Royal Brompton & Harefield Hospitals NHS Trust London UK Cardiac Arrhythmia Service and Cardiovascular Research Center Massachusetts General Hospital Boston MA USA Estonian Genome Center Institute of Genomics University of Tartu Tartu Estonia Department of Medicine Harvard Medical School Boston MA USA Cardiac Arrhythmia Service Massachusetts General Hospital Boston MA USA Division of General Internal Medicine Massachusetts General Hospital Boston MA USA Institute for Molecular Medicine FIMM University of Helsinki Helsinki Finland Department of Public Health Faculty of Medicine University of Helsinki Helsinki Finland Department of Genetics Harvard Medical School Boston MA USA Data Sciences Platform Broad Institute of MIT and Harvard Cambridge MA USA Genomics Platform Broad Institute of MIT and Harvard Cambridge MA USA Wellcome Sanger Institute Hinxton Cambridgeshire UK Unidad de Investigaci

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The mutational constraint spectrum quantified from variation in 141,456 humans (vol 581, pg 434, 2020)

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NATURE 2021年第7846期590卷 E53-E53页

作者： Karczewski, Konrad J. Francioli, Laurent C. Tiao, Grace Cummings, Beryl B. Alfoldi, Jessica Wang, Qingbo Collins, Ryan L. Laricchia, Kristen M. Ganna, Andrea Birnbaum, Daniel P. Gauthier, Laura D. Brand, Harrison Solomonson, Matthew Watts, Nicholas A. Rhodes, Daniel Singer-Berk, Moriel England, Eleina M. Seaby, Eleanor G. Kosmicki, Jack A. Walters, Raymond K. Tashman, Katherine Farjoun, Yossi Banks, Eric Poterba, Timothy Wang, Arcturus Seed, Cotton Whiffin, Nicola Chong, Jessica X. Samocha, Kaitlin E. Pierce-Hoffman, Emma Zappala, Zachary O'Donnell-Luria, Anne H. Minikel, Eric Vallabh Weisburd, Ben Lek, Monkol Ware, James S. Vittal, Christopher Armean, Irina M. Bergelson, Louis Cibulskis, Kristian Connolly, Kristen M. Covarrubias, Miguel Donnelly, Stacey Ferriera, Steven Gabriel, Stacey Gentry, Jeff Gupta, Namrata Jeandet, Thibault Kaplan, Diane Llanwarne, Christopher Munshi, Ruchi Novod, Sam Petrillo, Nikelle Roazen, David Ruano-Rubio, Valentin Saltzman, Andrea Schleicher, Molly Soto, Jose Tibbetts, Kathleen Tolonen, Charlotte Wade, Gordon Talkowski, Michael E. Aggregation, Genome Neale, Benjamin M. Daly, Mark J. MacArthur, Daniel G. Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Program in Biological and Biomedical Sciences Harvard Medical School Boston MA USA Program in Bioinformatics and Integrative Genomics Harvard Medical School Boston MA USA Center for Genomic Medicine Massachusetts General Hospital Boston MA USA Institute for Molecular Medicine Finland Helsinki Finland Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge MA USA National Heart & Lung Institute and MRC London Institute of Medical Sciences Imperial College London London UK Cardiovascular Research Centre Royal Brompton & Harefield Hospitals NHS Trust London UK Vertex Pharmaceuticals Inc Boston MA USA Division of Genetics and Genomics Boston Children’s Hospital Boston MA USA Department of Pediatrics Harvard Medical School Boston MA USA Broad Genomics Broad Institute of MIT and Harvard Cambridge MA USA Department of Neurology Harvard Medical School Boston MA USA Cardiac Arrhythmia Service and Cardiovascular Research Center Massachusetts General Hospital Boston MA USA Estonian Genome Center Institute of Genomics University of Tartu Tartu Estonia Data Sciences Platform Broad Institute of MIT and Harvard Cambridge MA USA Diabetes Unit Massachusetts General Hospital Boston MA USA Program in Metabolism Broad Institute of MIT and Harvard Cambridge MA USA Department of Medicine Harvard Medical School Boston MA USA Division of General Internal Medicine Massachusetts General Hospital Boston MA USA Department of Public Health Faculty of Medicine University of Helsinki Helsinki Finland Cardiovascular Disease Initiative and Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Genomics Diabetes and Endocrinology Lund University Lund Sweden Folkhälsan Institute of Genetics Folkhälsan Research C

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The mutational constraint spectrum quantified from variation in 141,456 humans (vol 581, pg 434, 2020)

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NATURE 2021年第7874期597卷 E3-E4页

作者： Gudmundsson, Sanna Karczewski, Konrad J. Francioli, Laurent C. Tiao, Grace Cummings, Beryl B. Alfoldi, Jessica Wang, Qingbo Collins, Ryan L. Laricchia, Kristen M. Ganna, Andrea Birnbaum, Daniel P. Gauthier, Laura D. Brand, Harrison Solomonson, Matthew Watts, Nicholas A. Rhodes, Daniel Singer-Berk, Moriel England, Eleina M. Seaby, Eleanor G. Kosmicki, Jack A. Walters, Raymond K. Tashman, Katherine Farjoun, Yossi Banks, Eric Poterba, Timothy Wang, Arcturus Seed, Cotton Whiffin, Nicola Chong, Jessica X. Samocha, Kaitlin E. Pierce-Hoffman, Emma Zappala, Zachary O'Donnell-Luria, Anne H. Minikel, Eric Vallabh Weisburd, Ben Lek, Monkol Ware, James S. Vittal, Christopher Armean, Irina M. Bergelson, Louis Cibulskis, Kristian Connolly, Kristen M. Covarrubias, Miguel Donnelly, Stacey Ferriera, Steven Gabriel, Stacey Gentry, Jeff Gupta, Namrata Jeandet, Thibault Kaplan, Diane Llanwarne, Christopher Munshi, Ruchi Novod, Sam Petrillo, Nikelle Roazen, David Ruano-Rubio, Valentin Saltzman, Andrea Schleicher, Molly Soto, Jose Tibbetts, Kathleen Tolonen, Charlotte Wade, Gordon Talkowski, Michael E. Neale, Benjamin M. Daly, Mark J. MacArthur, Daniel G. Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Division of Genetics and Genomics Boston Children’s Hospital Boston MA USA Program in Biological and Biomedical Sciences Harvard Medical School Boston MA USA Program in Bioinformatics and Integrative Genomics Harvard Medical School Boston MA USA Center for Genomic Medicine Massachusetts General Hospital Boston MA USA Institute for Molecular Medicine Finland Helsinki Finland Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge MA USA National Heart & Lung Institute and MRC London Institute of Medical Sciences Imperial College London London UK Cardiovascular Research Centre Royal Brompton & Harefield Hospitals NHS Trust London UK Vertex Pharmaceuticals Inc Boston MA USA Department of Pediatrics Harvard Medical School Boston MA USA Broad Genomics Broad Institute of MIT and Harvard Cambridge MA USA Department of Neurology Harvard Medical School Boston MA USA Cardiac Arrhythmia Service and Cardiovascular Research Center Massachusetts General Hospital Boston MA USA Estonian Genome Center Institute of Genomics University of Tartu Tartu Estonia Data Sciences Platform Broad Institute of MIT and Harvard Cambridge MA USA Diabetes Unit Massachusetts General Hospital Boston MA USA Program in Metabolism Broad Institute of MIT and Harvard Cambridge MA USA Department of Medicine Harvard Medical School Boston MA USA Division of General Internal Medicine Massachusetts General Hospital Boston MA USA Department of Public Health Faculty of Medicine University of Helsinki Helsinki Finland Cardiovascular Disease Initiative and Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Genomics Diabetes and Endocrinology Lund University Lund Sweden Folkhälsan Institute of Genetics Folkhälsan Research C

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A structural variation reference for medical and population genetics (vol 581, pg 444, 2020)

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NATURE 2021年第7846期590卷 E55-E55页

作者： Collins, Ryan L. Brand, Harrison Karczewski, Konrad J. Zhao, Xuefang Alfoldi, Jessica Francioli, Laurent C. Khera, Amit V. Lowther, Chelsea Gauthier, Laura D. Wang, Harold Watts, Nicholas A. Solomonson, Matthew O'Donnell-Luria, Anne Baumann, Alexander Munshi, Ruchi Walker, Mark Whelan, Christopher W. Huang, Yongqing Brookings, Ted Sharpe, Ted Stone, Matthew R. Valkanas, Elise Fu, Jack Tiao, Grace Laricchia, Kristen M. Ruano-Rubio, Valentin Stevens, Christine Gupta, Namrata Cusick, Caroline Margolin, Lauren Taylor, Kent D. Lin, Henry J. Rich, Stephen S. Post, Wendy S. Chen, Yii-Der Ida Rotter, Jerome I. Nusbaum, Chad Philippakis, Anthony Lander, Eric Gabriel, Stacey Neale, Benjamin M. Kathiresan, Sekar Daly, Mark J. Banks, Eric MacArthur, Daniel G. Talkowski, Michael E. Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Center for Genomic Medicine Massachusetts General Hospital Boston MA USA Division of Medical Sciences Harvard Medical School Boston MA USA Department of Neurology Massachusetts General Hospital and Harvard Medical School Boston MA USA Analytical and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Department of Medicine Harvard Medical School Boston MA USA Data Science Platform Broad Institute of MIT and Harvard Cambridge MA USA Broad Genomics Broad Institute of MIT and Harvard Cambridge MA USA European Molecular Biology Laboratory European Bioinformatics Institute Wellcome Genome Campus Hinxton Cambridge UK Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge MA USA Division of Genetics and Genomics Boston Children’s Hospital Boston MA USA Department of Pediatrics Harvard Medical School Boston MA USA National Heart & Lung Institute and MRC London Institute of Medical Sciences Imperial College London London UK Cardiovascular Research Centre Royal Brompton & Harefield Hospitals NHS Trust London UK Cardiac Arrhythmia Service Cardiovascular Research Center Massachusetts General Hospital Boston MA USA Estonian Genome Center Institute of Genomics University of Tartu Tartu Estonia Diabetes Unit Massachusetts General Hospital Boston MA USA Program in Metabolism Broad Institute of MIT and Harvard Cambridge MA USA Division of Cardiology Massachusetts General Hospital Boston MA USA Cardiovascular Disease Initiative Broad Institute of MIT and Harvard Cambridge MA USA Division of General Internal Medicine Massachusetts General Hospital Boston MA USA Institute for Molecular Medicine Finland (FIMM) HiLIFE University of Helsinki Helsinki Finland Department of Public Health Faculty of Medicine University

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GENFIRE: A generalized Fourier iterative reconstruction algorithm for high-resolution 3D imaging

arXiv

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arXiv 2017年

作者： Pryor, Alan Yang, Yongsoo Rana, Arjun Gallagher-Jones, Marcus Zhou, Jihan Lo, Yuan Hung Melinte, Georgian Chiu, Wah Rodriguez, Jose A. Miao, Jianwei Department of Physics and Astronomy California NanoSystems Institute University of California Los AngelesCA90095 United States Department of Chemistry & Biochemistry UCLA-DOE Institute of Genomics and Proteomics Los AngelesCA90095-1570 United States Department of Bioengineering University of California Los AngelesCA90095 United States Institut de Physique et Chimie des Matériaux de Strasbourg CNRS-Université de Strasbourg 23 rue du Loess Cedex 08 Strasbourg67037 France Program in Structural and Computational Biology and Molecular Biophysics Baylor College of Medicine HoustonTX77030 United States

Tomography has made a radical impact on diverse fields ranging from the study of 3D atomic arrangements in matter to the study of human health in medicine. Despite its very diverse applications, the core of tomography remains the same, that is, a mathematical method must be implemented to reconstruct the 3D structure of an object from a number of 2D projections. In many scientific applications, however, the number of projections that can be measured is limited due to geometric constraints, tolerable radiation dose and/or acquisition speed. Thus it becomes an important problem to obtain the best-possible reconstruction from a limited number of projections. Here, we present the mathematical implementation of a tomographic algorithm, termed GENeralized Fourier Iterative REconstruction (GENFIRE). By iterating between real and reciprocal space, GENFIRE searches for a global solution that is concurrently consistent with the measured data and general physical constraints. The algorithm requires minimal human intervention and also incorporates angular refinement to reduce the tilt angle error. We demonstrate that GENFIRE can produce superior results relative to several other popular tomographic reconstruction techniques by numerical simulations, and by experimentally by reconstructing the 3D structure of a porous material and a frozen-hydrated marine cyanobacterium. Equipped with a graphical user interface, GENFIRE is freely available from our website and is expected to find broad applications across different disciplines. Copyright © 2017, The Authors. All rights reserved.

关键词： Tomography

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Analytical strategies for studying stem cell metabolism

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Frontiers in biology 2015年第2期10卷 141-153页

作者： James M. Arnold William T. Choi Arun Sreekumar Mirjana Maletic-Savatic Department of Molecular and Cell Biology Baylor College of Medicine Houston TX 77030 USA Program in Developmental Biology and Medical Scientist Training Program Baylor College of Medicine Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital Houston TX 77030 USA Departments of Pediatrics-Neurology and Neuroscience and Program in Structural and Computational Biology and Molecular Biophysics Baylor College of Medicine Houston TX 77030 USA

Owing to their capacity for self-renewal and pluripotency, stem cells possess untold potential for revolutionizing the field of regenerative medicine through the development of novel therapeutic strategies for treating cancer, diabetes, cardiovascular and neurodegenerative diseases. Central to developing these strategies is improving our understanding of biological mechanisms responsible for governing stem cell fate and self-renewal. Increasing attention is being given to the significance of metabolism, through the production of energy and generation of small molecules, as a critical regulator of stem cell functioning. Rapid advances in the field of metabolomics now allow for in-depth profiling of stem cells both in vitro and in vivo, providing a systems perspective on key metabolic and molecular pathways which influence stem cell biology. Understanding the analytical platforms and techniques that are currently used to study stem cell metabolomics, as well as how new insights can be derived from this knowledge, will accelerate new research in the field and improve future efforts to expand our understanding of the interplay between metabolism and stem cell biology.

关键词： stem cell metabolism NMR mass spectrometry MRS flux analysis

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Random close packing in protein cores

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Physical Review E 2016年第3期93卷 032415-032415页

作者： Jennifer C. Gaines W. Wendell Smith Lynne Regan Corey S. O'Hern Program in Computational Biology and Bioinformatics Yale University New Haven Connecticut 06520 USA Integrated Graduate Program in Physical and Engineering Biology (IGPPEB) Yale University New Haven Connecticut 06520 USA Department of Physics Yale University New Haven Connecticut 06520 USA Department of Molecular Biophysics & Biochemistry Yale University New Haven Connecticut 06520 USA Department of Chemistry Yale University New Haven Connecticut 06520 USA Department of Mechanical Engineering & Materials Science Yale University New Haven Connecticut 06520 USA Department of Applied Physics Yale University New Haven Connecticut 06520 USA

Shortly after the determination of the first protein x-ray crystal structures, researchers analyzed their cores and reported packing fractions ϕ≈0.75, a value that is similar to close packing of equal-sized spheres. A limitation of these analyses was the use of extended atom models, rather than the more physically accurate explicit hydrogen model. The validity of the explicit hydrogen model was proved in our previous studies by its ability to predict the side chain dihedral angle distributions observed in proteins. In contrast, the extended atom model is not able to recapitulate the side chain dihedral angle distributions, and gives rise to large atomic clashes at side chain dihedral angle combinations that are highly probable in protein crystal structures. Here, we employ the explicit hydrogen model to calculate the packing fraction of the cores of over 200 high-resolution protein structures. We find that these protein cores have ϕ≈0.56, which is similar to results obtained from simulations of random packings of individual amino acids. This result provides a deeper understanding of the physical basis of protein structure that will enable predictions of the effects of amino acid mutations to protein cores and interfaces of known structure.

关键词： Protein structure Proteins

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