1
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The marionette mechanism of domain-domain communication in the antagonist, agonist, and coactivator responses of the estrogen receptor. Proc Natl Acad Sci U S A 2023; 120:e2216906120. [PMID: 36730193 PMCID: PMC9963092 DOI: 10.1073/pnas.2216906120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
The human estrogen receptor α (hERα) is involved in the regulation of growth, development, and tissue homeostasis. Agonists that bind to the receptor's ligand-binding domain (LBD) lead to recruitment of coactivators and the enhancement of gene expression. In contrast, antagonists bind to the LBD and block the binding of coactivators thus decreasing gene expressions. In this work, we carry out simulations using the AWSEM (Associative memory, Water mediated, Structure and Energy Model)-Suite force field along with the 3SPN.2C force field for DNA to predict the structure of hERα and study its dynamics when binding to DNA and coactivators. Using simulations of antagonist-bound hERα and agonist-bound hERα by themselves and also along with bound DNA and coactivators, principal component analyses and free energy landscape analyses capture the pathway of domain-domain communication for agonist-bound hERα. This communication is mediated through the hinge domains that are ordinarily intrinsically disordered. These disordered segments manipulate the hinge domains much like the strings of a marionette as they twist in different ways when antagonists or agonists are bound to the ligand-binding domain.
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2
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Roh S, Lee T, Cheong DY, Kim Y, Oh S, Lee G. Direct observation of surface charge and stiffness of human metaphase chromosomes. NANOSCALE ADVANCES 2023; 5:368-377. [PMID: 36756276 PMCID: PMC9846444 DOI: 10.1039/d2na00620k] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 12/17/2022] [Indexed: 06/18/2023]
Abstract
Metaphase chromosomes in which both polynucleotides and proteins are condensed with hierarchies are closely related to life phenomena such as cell division, cancer development, and cellular senescence. Nevertheless, their nature is rarely revealed, owing to their structural complexity and technical limitations in analytical methods. In this study, we used surface potential and nanomechanics mapping technology based on atomic force microscopy to measure the surface charge and intrinsic stiffness of metaphase chromosomes. We found that extra materials covering the chromosomes after the extraction process were positively charged. With the covering materials, the chromosomes were positively charged (ca. 44.9 ± 16.48 mV) and showed uniform stiffness (ca. 6.23 ± 1.98 MPa). In contrast, after getting rid of the extra materials through treatment with RNase and protease, the chromosomes were strongly negatively charged (ca. -197.4 ± 77.87 mV) and showed relatively non-uniform and augmented stiffness (ca. 36.87 ± 17.56 MPa). The results suggested undulating but compact coordination of condensed chromosomes. Additionally, excessive treatment with RNase and protease could destroy the chromosomal structure, providing an exceptional opportunity for multiscale stiffness mapping of polynucleotides, nucleosomes, chromatin fibers, and chromosomes in a single image. Our approach offers a new horizon in terms of an analytical technique for studying chromosome-related diseases.
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Affiliation(s)
- Seokbeom Roh
- Department of Biotechnology and Bioinformatics, Korea University Sejong 30019 Korea
- Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology, Korea University Sejong 30019 Korea
| | - Taeha Lee
- Department of Biotechnology and Bioinformatics, Korea University Sejong 30019 Korea
- Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology, Korea University Sejong 30019 Korea
| | - Da Yeon Cheong
- Department of Biotechnology and Bioinformatics, Korea University Sejong 30019 Korea
- Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology, Korea University Sejong 30019 Korea
| | - Yeonjin Kim
- Department of Biotechnology and Bioinformatics, Korea University Sejong 30019 Korea
| | - Soohwan Oh
- College of Pharmacy, Korea University Sejong 30019 Korea
| | - Gyudo Lee
- Department of Biotechnology and Bioinformatics, Korea University Sejong 30019 Korea
- Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology, Korea University Sejong 30019 Korea
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3
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Brandani GB, Gopi S, Yamauchi M, Takada S. Molecular dynamics simulations for the study of chromatin biology. Curr Opin Struct Biol 2022; 77:102485. [PMID: 36274422 DOI: 10.1016/j.sbi.2022.102485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 09/05/2022] [Accepted: 09/18/2022] [Indexed: 12/14/2022]
Abstract
The organization of Eukaryotic DNA into chromatin has profound implications for the processing of genetic information. In the past years, molecular dynamics (MD) simulations proved to be a powerful tool to investigate the mechanistic basis of chromatin biology. We review recent all-atom and coarse-grained MD studies revealing how the structure and dynamics of chromatin underlie its biological functions. We describe the latest method developments; the structural fluctuations of nucleosomes and the various factors affecting them; the organization of chromatin fibers, with particular emphasis on its liquid-like character; the interactions and dynamics of transcription factors on chromatin; and how chromatin organization is modulated by molecular motors acting on DNA.
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Affiliation(s)
- Giovanni B Brandani
- Department of Biophysics, Graduate School of Science, Kyoto University, Japan.
| | - Soundhararajan Gopi
- Department of Biophysics, Graduate School of Science, Kyoto University, Japan
| | - Masataka Yamauchi
- Department of Biophysics, Graduate School of Science, Kyoto University, Japan
| | - Shoji Takada
- Department of Biophysics, Graduate School of Science, Kyoto University, Japan
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4
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A walk through the SMC cycle: From catching DNAs to shaping the genome. Mol Cell 2022; 82:1616-1630. [PMID: 35477004 DOI: 10.1016/j.molcel.2022.04.006] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2021] [Revised: 02/02/2022] [Accepted: 04/04/2022] [Indexed: 12/16/2022]
Abstract
SMC protein complexes are molecular machines that provide structure to chromosomes. These complexes bridge DNA elements and by doing so build DNA loops in cis and hold together the sister chromatids in trans. We discuss how drastic conformational changes allow SMC complexes to build such intricate DNA structures. The tight regulation of these complexes controls fundamental chromosomal processes such as transcription, recombination, repair, and mitosis.
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5
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Angriman S, Cobelli PJ, Bourgoin M, Huisman SG, Volk R, Mininni PD. Broken Mirror Symmetry of Tracer's Trajectories in Turbulence. PHYSICAL REVIEW LETTERS 2021; 127:254502. [PMID: 35029439 DOI: 10.1103/physrevlett.127.254502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 07/05/2021] [Accepted: 11/12/2021] [Indexed: 06/14/2023]
Abstract
Topological properties of physical systems play a crucial role in our understanding of nature, yet their experimental determination remains elusive. We show that the mean helicity, a dynamical invariant in ideal flows, quantitatively affects trajectories of fluid elements: the linking number of Lagrangian trajectories depends on the mean helicity. Thus, a global topological invariant and a topological number of fluid trajectories become related, and we provide an empirical expression linking them. The relation shows the existence of long-term memory in the trajectories: the links can be made of the trajectory up to a given time, with particles positions in the past. This property also allows experimental measurements of mean helicity.
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Affiliation(s)
- S Angriman
- Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Física, & IFIBA, CONICET, Ciudad Universitaria, Buenos Aires 1428, Argentina
| | - P J Cobelli
- Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Física, & IFIBA, CONICET, Ciudad Universitaria, Buenos Aires 1428, Argentina
| | - M Bourgoin
- Université Lyon, ENS de Lyon, Université Claude Bernard, CNRS, Laboratoire de Physique, 46 Allée d'Italie F-69342 Lyon, France
| | - S G Huisman
- Physics of Fluids Group, Max Planck UT Center for Complex Fluid Dynamics, Faculty of Science and Technology, MESA+ Institute and J.M. Burgers Centre for Fluid Dynamics, University of Twente, P.O. Box 217, 7500 AE Enschede, Netherlands
| | - R Volk
- Université Lyon, ENS de Lyon, Université Claude Bernard, CNRS, Laboratoire de Physique, 46 Allée d'Italie F-69342 Lyon, France
| | - P D Mininni
- Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Física, & IFIBA, CONICET, Ciudad Universitaria, Buenos Aires 1428, Argentina
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6
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Oliveira Junior AB, Estrada CP, Aiden EL, Contessoto VG, Onuchic JN. Chromosome Modeling on Downsampled Hi-C Maps Enhances the Compartmentalization Signal. J Phys Chem B 2021; 125:8757-8767. [PMID: 34319725 DOI: 10.1021/acs.jpcb.1c04174] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The human genome is organized within a nucleus where chromosomes fold into an ensemble of different conformations. Chromosome conformation capture techniques such as Hi-C provide information about the genome architecture by creating a 2D heat map. Initially, Hi-C map experiments were performed in human interphase cell lines. Recently, efforts were expanded to several different organisms, cell lines, tissues, and cell cycle phases where obtaining high-quality maps is challenging. Poor sampled Hi-C maps present high sparse matrices where compartments located far from the main diagonal are difficult to observe. Aided by recently developed models for chromatin folding and dynamics investigation, we introduce a framework to enhance the compartments' information far from the diagonal observed in experimental sparse matrices. The simulations were performed using the Open-MiChroM platform aided by new trained parameters in the minimal chromatin model (MiChroM) energy function. The simulations optimized on a downsampled experimental map (10% of the original data) allow the prediction of a contact frequency similar to that of the complete (100%) experimental Hi-C. The modeling results open a discussion on how simulations and modeling can increase the statistics and help fill in some Hi-C regions not captured by poor sampling experiments. Open-MiChroM simulations allow us to explore the 3D genome organization of different organisms, cell lines, and cell phases that often do not produce high-quality Hi-C maps.
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Affiliation(s)
| | - Cynthia Perez Estrada
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States
| | - Erez Lieberman Aiden
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States
| | - Vinícius G Contessoto
- Instituto de Biociências, Letras e Ciências Exatas, UNESP - Univ. Estadual Paulista, Departamento de Física, São José do Rio Preto, SP, Brazil
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Koide H, Kodera N, Bisht S, Takada S, Terakawa T. Modeling of DNA binding to the condensin hinge domain using molecular dynamics simulations guided by atomic force microscopy. PLoS Comput Biol 2021; 17:e1009265. [PMID: 34329301 PMCID: PMC8357123 DOI: 10.1371/journal.pcbi.1009265] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 08/11/2021] [Accepted: 07/10/2021] [Indexed: 11/19/2022] Open
Abstract
The condensin protein complex compacts chromatin during mitosis using its DNA-loop extrusion activity. Previous studies proposed scrunching and loop-capture models as molecular mechanisms for the loop extrusion process, both of which assume the binding of double-strand (ds) DNA to the hinge domain formed at the interface of the condensin subunits Smc2 and Smc4. However, how the hinge domain contacts dsDNA has remained unknown. Here, we conducted atomic force microscopy imaging of the budding yeast condensin holo-complex and used this data as basis for coarse-grained molecular dynamics simulations to model the hinge structure in a transient open conformation. We then simulated the dsDNA binding to open and closed hinge conformations, predicting that dsDNA binds to the outside surface when closed and to the outside and inside surfaces when open. Our simulations also suggested that the hinge can close around dsDNA bound to the inside surface. Based on these simulation results, we speculate that the conformational change of the hinge domain might be essential for the dsDNA binding regulation and play roles in condensin-mediated DNA-loop extrusion.
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Affiliation(s)
- Hiroki Koide
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
| | - Noriyuki Kodera
- Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, Kanazawa, Japan
| | - Shveta Bisht
- Cell Biology and Biophysics Unit, Structural and Computational Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Shoji Takada
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
| | - Tsuyoshi Terakawa
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
- PREST, Japan Science and Technology Agency (JST), Kawaguchi, Japan
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8
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Lu W, Bueno C, Schafer NP, Moller J, Jin S, Chen X, Chen M, Gu X, Davtyan A, de Pablo JJ, Wolynes PG. OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations. PLoS Comput Biol 2021; 17:e1008308. [PMID: 33577557 PMCID: PMC7906472 DOI: 10.1371/journal.pcbi.1008308] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 02/25/2021] [Accepted: 01/09/2021] [Indexed: 01/28/2023] Open
Abstract
We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM’s Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM’s Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen’s early Nobel prize winning experiments by using OpenMM’s Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology. The cell’s most important pieces of machinery are large complexes of proteins often along with nucleic acids. From the ribosome, to CRISPR-Cas9, to transcription factors and DNA-wrangling proteins like the SMC-Kleisins, these complexes allow organisms to replicate and enable cells to respond to environmental cues. Computer simulation is a key technology that can be used to connect physical theories with biological reality. Unfortunately, the time and length scales accessible to molecular simulation have not kept pace with our ambition to study the cell’s molecular factories. Many simulation codes also unfortunately remain effectively locked away from the user community who need to modify them as more of the underlying physics is learned. In this paper, we present OpenAWSEM and Open3SPN2, two new easy-to-use and easy to modify implementations of efficient and accurate coarse-grained protein and DNA simulation forcefields that can now be run hundreds of times faster than before, thereby making studies of large biomolecular machines more facile.
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Affiliation(s)
- Wei Lu
- Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America
- Department of Physics, Rice University, Houston, Texas, United States of America
| | - Carlos Bueno
- Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America
- Department of Chemistry, Rice University, Houston, Texas, United States of America
| | - Nicholas P. Schafer
- Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America
- Department of Chemistry, Rice University, Houston, Texas, United States of America
- Schafer Science, LLC, Houston, Texas United States of America
| | - Joshua Moller
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois, United States of America
- Argonne National Laboratory, Lemont, Illinois, United States of America
| | - Shikai Jin
- Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America
- Department of Biosciences, Rice University, Houston, Texas, United States of America
| | - Xun Chen
- Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America
- Department of Chemistry, Rice University, Houston, Texas, United States of America
| | - Mingchen Chen
- Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America
| | - Xinyu Gu
- Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America
- Department of Chemistry, Rice University, Houston, Texas, United States of America
| | - Aram Davtyan
- Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America
| | - Juan J. de Pablo
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois, United States of America
- Argonne National Laboratory, Lemont, Illinois, United States of America
| | - Peter G. Wolynes
- Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America
- Department of Chemistry, Rice University, Houston, Texas, United States of America
- Department of Physics, Rice University, Houston, Texas, United States of America
- Department of Biosciences, Rice University, Houston, Texas, United States of America
- * E-mail:
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9
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Datta S, Lecomte L, Haering CH. Structural insights into DNA loop extrusion by SMC protein complexes. Curr Opin Struct Biol 2020; 65:102-109. [DOI: 10.1016/j.sbi.2020.06.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 06/03/2020] [Accepted: 06/16/2020] [Indexed: 12/14/2022]
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10
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Jin S, Chen M, Chen X, Bueno C, Lu W, Schafer NP, Lin X, Onuchic JN, Wolynes PG. Protein Structure Prediction in CASP13 Using AWSEM-Suite. J Chem Theory Comput 2020; 16:3977-3988. [PMID: 32396727 DOI: 10.1021/acs.jctc.0c00188] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Recently several techniques have emerged that significantly enhance the quality of predictions of protein tertiary structures. In this study, we describe the performance of AWSEM-Suite, an algorithm that incorporates template-based modeling and coevolutionary restraints with a realistic coarse-grained force field, AWSEM. With its roots in neural networks, AWSEM contains both physical and bioinformatical energies that have been optimized using energy landscape theory. AWSEM-Suite participated in CASP13 as a server predictor and generated reliable predictions for most targets. AWSEM-Suite ranked eighth in both the free-modeling category and the hard-to-model category and in one case provided the best submitted prediction. Here we critically discuss the prediction performance of AWSEM-Suite using several examples from different categories in CASP13. Structure prediction tests on these selected targets, two of them being hard-to-model targets, show that AWSEM-Suite can achieve high-resolution structure prediction after incorporating both template guidances and coevolutionary restraints even when homology is weak. For targets with reliable templates (template-easy category), introducing coevolutionary restraints sometimes damages the overall quality of the predictions. Free energy profile analyses demonstrate, however, that the incorporations of both of these evolutionarily informed terms effectively increase the funneling of the landscape toward native-like structures while still allowing sufficient flexibility to correct for discrepancies between the correct target structure and the provided guidance. In contrast to other predictors that are exclusively oriented toward structure prediction, the connection of AWSEM-Suite to a statistical mechanical basis and affiliated molecular dynamics and importance sampling simulations makes it suitable for functional explorations.
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Affiliation(s)
| | | | - Xun Chen
- Department of Chemistry, Rice University, Houston, Texas 77005, United States
| | | | - Wei Lu
- Department of Physics, Rice University, Houston, Texas 77005, United States
| | | | - Xingcheng Lin
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - José N Onuchic
- Department of Chemistry, Rice University, Houston, Texas 77005, United States.,Department of Physics, Rice University, Houston, Texas 77005, United States
| | - Peter G Wolynes
- Department of Chemistry, Rice University, Houston, Texas 77005, United States.,Department of Physics, Rice University, Houston, Texas 77005, United States
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11
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Tanaka H, Shew CY, Yoshikawa Y, Kenmotsu T, Yoshikawa K. Low-efficiency of gene expression with a long diamine is attributable to the effect on DNA zipping. Chem Phys Lett 2020. [DOI: 10.1016/j.cplett.2020.137253] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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12
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Insights into the energy landscapes of chromosome organization proteins from coevolutionary sequence variation and structural modeling. Proc Natl Acad Sci U S A 2020; 117:2241-2242. [PMID: 31924744 DOI: 10.1073/pnas.1921727117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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