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arXiv 2021年

作者： Narayanasamy, Sankar Raju Vasireddi, Ramakrishna Holman, Hoi-Ying Berkeley Synchrotron Infrared Structural Biology Imaging Program Lawrence Berkeley National Laboratory Berkeley United States Molecular Biophysics and Integrated Bioimaging Division Lawrence Berkeley National Laboratory Berkeley United States Proxima-1 & Microfluidics Laboratory Synchrotron SOLEIL Saint-Aubin France

High-density microfluidics is becoming an important experimental platform for studying complex biological systems such as synthetic gene regulatory networks, molecular biocomputating of engineered cells, distributing rapid point-of-care diagnosis, and monitoring pathological environment. Imaging transient bio-chemical reactions happening in these systems at a single particle or cellular level requires precise time-dependent control of sample reaction and imaging conditions at the desired fluidic momentum. In this study, we showed our novel miniaturized and programmable electronic-based pneumatic system to meet the requirement. We demonstrated its capability to control reaction parameters such as concentrations and injection rates in a liposome production system. © 2021, CC BY-SA.

关键词： Liposomes

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Cover Picture: The Exploding Genetic Code (ChemBioChem 12/2014)

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ChemBioChem 2014年第12期15卷 1689-1689页

作者： Dr. Edward A. Lemke European Molecular Biology Laboratory Structural and Computational Biology Unit Cell Biology and Biophysics Unit Meyerhofstrasse 1 69117 Heidelberg (Germany)

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Open structural Data in Precision Medicine

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Biomedical Data Science 1000年第1期5卷 95-117页

作者： Ruth Nussinov Hyunbum Jang Guy Nir Chung-Jung Tsai Feixiong Cheng 2Department of Human Molecular Genetics and Biochemistry Sackler School of Medicine Tel Aviv University Tel Aviv Israel 1Computational Structural Biology Section Frederick National Laboratory for Cancer Research in the Cancer Innovation Laboratory National Cancer Institute Frederick Maryland USA email: NussinoR@mail.nih.gov 3Department of Biochemistry and Molecular Biology Department of Neuroscience Cell Biology and Anatomy and Sealy Center for Structural Biology and Molecular Biophysics University of Texas Medical Branch Galveston Texas USA 6Case Comprehensive Cancer Center Case Western Reserve University School of Medicine Cleveland Ohio USA 5Department of Molecular Medicine Cleveland Clinic Lerner College of Medicine Case Western Reserve University Cleveland Ohio USA 4Genomic Medicine Institute Lerner Research Institute Cleveland Clinic Cleveland Ohio USA

Three-dimensional protein structural data at the molecular level are pivotal for successful precision medicine. Such data are crucial not only for discovering drugs that act to block the active site of the target mutant protein but also for clarifying to the patient and the clinician how the mutations harbored by the patient work. The relative paucity of structural data reflects their cost, challenges in their interpretation, and lack of clinical guidelines for their utilization. Rapid technological advancements in experimental high-resolution structural determination increasingly generate structures. computationally, modeling algorithms, including molecular dynamics simulations, are becoming more powerful, as are compute-intensive hardware, particularly graphics processing units, overlapping with the inception of the exascale era. Accessible, freely available, and detailed structural and dynamical data can be merged with big data to powerfully transform personalizedpharmacology. Here we review protein and emerging genome high-resolution data, along with means, applications, and examples underscoring their usefulness in precision medicine.

关键词： drug resistance chromatin accessibility targeted therapy AI machine learning signaling KRas network medicine cancer free-energy landscape

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TOPAZ: A Positive-Unlabeled Convolutional Neural Network CryoEM Particle Picker that can Pick Any Size and Shape Particle

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Microscopy and Microanalysis 2019年第S2期25卷 986-987页

作者： Tristan Bepler Andrew Morin Micah Rapp Julia Brasch Lawrence Shapiro Alex J Noble Bonnie Berger Computational and Systems Biology MIT Cambridge MA USA. Computer Science and Artificial Intelligence Laboratory MIT Cambridge MA USA. Department of Mathematics MIT Cambridge MA USA. Department of Biochemistry and Molecular Biophysics Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University NY NY USA. National Resource for Automated Molecular Microscopy Simons Electron Microscopy Center New York Structural Biology Center NY NY USA.

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A broad antibody with enhanced HIV-1 neutralization via bispecific antibody-mediated prepositioning

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Nature Communications 2025年第1期16卷 1-14页

作者： Kim, Soohyun Radford, Caelan E. Xu, Duo Zhong, Jianing Do, Jonathan Pham, Dominic M. Travisano, Katie A. Filsinger Interrante, Maria V. Bruun, Theodora U. J. Rezek, Valerie Wilder, Bailey Palomares, Martina Seaman, Michael S. Kitchen, Scott G. Bloom, Jesse D. Kim, Peter S. Department of Biochemistry Stanford University School of Medicine Stanford CA United States Sarafan ChEM-H Stanford University Stanford CA United States Molecular and Cellular Biology Graduate Program University of Washington and Basic Sciences Division Fred Hutchinson Cancer Center Seattle WA United States Basic Sciences Division and Computational Biology Program Fred Hutchinson Cancer Center Seattle WA United States Department of Chemistry Stanford University Stanford CA United States Stanford Biophysics Program Stanford University School of Medicine Stanford CA United States Department of Microbiology & Immunology Stanford University School of Medicine Stanford CA United States Stanford Medical Scientist Training Program Stanford University School of Medicine Stanford CA United States Department of Medicine Division of Hematology and Oncology David Geffen School of Medicine at University of California Los Angeles (UCLA) Los Angeles CA United States UCLA AIDS Institute and the Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research David Geffen School of Medicine University of California Los Angeles (UCLA) Los Angeles CA United States Center for Virology and Vaccine Research Beth Israel Deaconess Medical Center Harvard Medical School Boston MA United States Howard Hughes Medical Institute Seattle WA United States Chan Zuckerberg Biohub San Francisco CA United States Department of Biochemistry University of Wisconsin-Madison Madison WI United States

Antibodies targeting the highly conserved prehairpin intermediate (PHI) of class I viral membrane-fusion proteins are generally weakly neutralizing and are not considered viable therapeutic agents. We previously demonstrated that antibodies targeting the gp41 N-heptad repeat (NHR), which is transiently exposed in the HIV-1 PHI, exhibit enhanced broad neutralization in cells expressing the Fc receptor, FcγRI. To enhance neutralization in cells lacking FcγRI, we here develop a bispecific antibody (bsAb) by fusing an NHR-targeting antibody to an antibody against CD4, the HIV-1 receptor on T cells. The bsAb provides a 5000-fold neutralization enhancement and shows unprecedented neutralization breadth compared to existing broadly neutralizing antibodies. Importantly, the bsAb reduces viral load in HIV-1-infected humanized male mice, and viral envelope sequencing under bsAb pressure revealed an NHR mutation that potentially impairs viral fitness. These findings validate the NHR as a potential HIV-1 therapeutic target, setting the stage for a new class of broadly neutralizing antibodies. © The Author(s) 2025.

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Biochemistry: Rev1 employs a novel mechanism of DNA synthesis using a protein template

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Science 2005年第5744期309卷 2219-2222页

作者： Nair, Deepak T. Johnson, Robert E. Prakash, Louise Prakash, Satya Aggarwal, Aneel K. Structural Biology Program Department of Physiology and Biophysics Mount Sinai School of Medicine 1425 Madison Avenue New York NY 10029 United States Sealy Center for Molecular Science University of Texas Medical Branch 6.014 Medical Research Building 11th and Mechanic Streets Galveston TX 77755-1061 United States

The Rev1 DNA polymerase is highly specialized for the incorporation of C opposite template G. We present here the crystal structure of yeast Rev1 bound to template G and incoming 2′-deoxycytidine 5′-triphosphate (dCTP), which reveals that the polymerase itself dictates the identity of the incoming nucleotide, as well as the identity of the templating base. Template G and incoming dCTP do not pair with each other. Instead, the template G is evicted from the DNA helix, and it makes optimal hydrogen bonds with a segment of Rev1. Also, unlike other DNA polymerases, incoming dCTP pairs with an arginine rather than the templating base, which ensures the incorporation of dCTP over other incoming nucleotides. This mechanism provides an elegant means for promoting proficient and error-free synthesis through N2-adducted guanines that obstruct replication.

关键词： DNA

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A Bayesian graphical model for integrative analysis of TCGA data

A Bayesian graphical model for integrative analysis of TCGA ...

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IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS)

作者： Yanxun Xu Jie Zhang Yuan Yuan Riten Mitra Peter Müller Yuan Ji Department of Statistics Rice University Houston TX USA Department of Statistics University of Wisconsin Madison Madison WI USA Graduate Program in Structural and Computational Biology and Molecular Biophysics Baylor College of Medicine Houston TX USA ICES University of Texas Austin Austin TX USA Department of Mathematics University of Texas Austin Austin TX USA CCRI NorthShore University HealthSystem Chicago IL USA

ISBN: (纸本)9781467352345

We integrate three TCGA data sets including measurements on matched DNA copy numbers (C), DNA methylation (M), and mRNA expression (E) over 500+ ovarian cancer samples. The integrative analysis is based on a Bayesian graphical model treating the three types of measurements as three vertices in a network. The graph is used as a convenient way to parameterize and display the dependence structure. Edges connecting vertices infer specific types of regulatory relationships. For example, an edge between M and E and a lack of edge between C and E implies methylation-controlled transcription, which is robust to copy number changes. In other words, the mRNA expression is sensitive to methylational variation but not copy number variation. We apply the graphical model to each of the genes in the TCGA data independently and provide a comprehensive list of inferred profiles. Examples are provided based on simulated data as well.

关键词： expression transcription variation Meta-Analysis Graphical models Genetic Transcription edges mRNA Expression Bayesian inference simulated data

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PRMT5 promotes full-length HTT expression by repressing multiple proximal intronic polyadenylation sites

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Nucleic Acids Research 2025年第8期53卷 gkaf347页

作者： Yadav, Manisha Alqazzaz, Mona A. Ciamponi, Felipe E. Ho, Jolene C. Maron, Maxim I. Sababi, Aiden M. Macleod, Graham Ahmadi, Moloud Bullivant, Garrett Tano, Vincent Langley, Sarah R. Sánchez-Osuna, María Sachamitr, Patty Kushida, Michelle Bardile, Costanza Ferrari Pouladi, Mahmoud A. Kurtz, Rebecca Richards, Laura Pugh, Trevor Tyers, Mike Angers, Stephane Dirks, Peter B. Bader, Gary D. Truant, Ray Massirer, Katlin B. Barsyte-Lovejoy, Dalia Shechter, David Harding, Rachel J. Arrowsmith, Cheryl H. Prinos, Panagiotis Department of Medical Biophysics University of Toronto Toronto M5G1L7 ON Canada Princess Margaret Cancer Centre University Health Network Toronto M5G1L7 ON Canada Structural Genomics Consortium University of Toronto Toronto M5G1L7 ON Canada Center for Molecular Biology and Genetic Engineering University of Campinas (UNICAMP) Campinas 13083-872 Brazil Department of Biochemistry Albert Einstein College of Medicine Bronx 10461 NY United States Donnelly Centre for Cellular and Biomolecular Research University of Toronto Toronto M5S3E1 ON Canada Department of Molecular Genetics University of Toronto Toronto M5S3E1 ON Canada Leslie Dan Faculty of Pharmacy University of Toronto Toronto M5S3M2 ON Canada Developmental and Stem Cell Biology Program Arthur and Sonia Labatt Brain Tumor Research Centre The Hospital for Sick Children Toronto M5G0A4 ON Canada Lee Kong Chian School of Medicine Nanyang Technological University Singapore 636921 Singapore School of Biosciences Cardiff University Cardiff CF103AX United Kingdom Institute for Research in Immunology and Cancer Universitéde Montréal Montreal H3C3J7 QC Canada Department of Medical Genetics Centre for Molecular Medicine and Therapeutics Djavad Mowafaghian Centre for Brain Health British Columbia Children's Hospital Research Institute University of British Columbia Vancouver V5Z4H4 BC Canada Department of Biochemistry and Biomedical Sciences McMaster University Hamilton L8N3Z5 ON Canada Ontario Institute for Cancer Research University Health Network Toronto M5G0A3 ON Canada Division of Neurosurgery Department of Surgery University of Toronto Toronto M5S1A8 ON Canada Department of Laboratory Medicine and Pathobiology University of Toronto Toronto M5S1A8 ON Canada Lunenfeld-Tanenbaum Research Institute Sinai Health System Toronto M5G1X5 ON Canada Department of Computer Science University of Toronto M5S3E1 ON Canada Department of Pharmacology and Toxicology University of Toronto

Expansion of the CAG trinucleotide repeat tract in exon 1 of the Huntingtin (HTT) gene causes Huntington's disease (HD) through the expression of a polyglutamine-expanded form of the HTT protein. This mutation triggers cellular and biochemical pathologies, leading to cognitive, motor, and psychiatric symptoms in HD patients. Targeting HTT splicing with small molecule drugs is a compelling approach to lowering HTT protein levels to treat HD, and splice modulators are currently being tested in the clinic. Here, we identify PRMT5 as a novel regulator of HTT messenger RNA (mRNA) splicing and alternative polyadenylation. PRMT5 inhibition disrupts the splicing of HTT introns 9 and 10, leading to the activation of multiple proximal intronic polyadenylation sites within these introns and promoting premature termination, cleavage, and polyadenylation of the HTT mRNA. This suggests that HTT protein levels may be lowered due to this mechanism. We also detected increasing levels of these truncated HTT transcripts across a series of neuronal differentiation samples, which correlated with lower PRMT5 expression. Notably, PRMT5 inhibition in glioblastoma stem cells potently induced neuronal differentiation. We posit that PRMT5-mediated regulation of intronic polyadenylation, premature termination, and cleavage of the HTT mRNA modulates HTT expression and plays an important role during neuronal differentiation. © 2025 The Author(s).

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Free energies for coarse-grained proteins by integrating multibody statistical contact potentials with entropies from elastic network models

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Journal of structural and Functional Genomics 2011年第2期12卷 137-147页

作者： Zimmermann, Michael T. Leelananda, Sumudu P. Gniewek, Pawel Feng, Yaping Jernigan, Robert L. Kloczkowski, Andrzej Department of Biochemistry Biophysics and Molecular Biology Iowa State University Ames IA 50011-0320 United States L.H.Baker Center for Bioinformatics and Biological Statistics Iowa State University Ames IA 50011-3020 United States Bioinformatics and Computational Biology Interdepartmental Graduate Program Iowa State University Ames IA 50011 United States Laboratory of Theory of Biopolymers Faculty of Chemistry University of Warsaw 02-093 Warsaw Pasteura 1 Poland Battelle Center for Mathematical Medicine Research Institute at Nationwide Children's Hospital Columbus OH 43205 United States Department of Pediatrics Ohio State University College of Medicine Columbus OH 43205 United States

We propose a novel method of calculation of free energy for coarse grained models of proteins by combining our newly developed multibody potentials with entropies computed from elastic network models of proteins. Multi-body potentials have been of much interest recently because they take into account three dimensional interactions related to residue packing and capture the cooperativity of these interactions in protein structures. Combining four-body non-sequential, four-body sequential and pairwise short range potentials with optimized weights for each term, our coarse-grained potential improved recognition of native structure among misfolded decoys, outperforming all other contact potentials for CASP8 decoy sets and performance comparable to the fully atomic empirical DFIRE potentials. By combing statistical contact potentials with entropies from elastic network models of the same structures we can compute free energy changes and improve coarse-grained modeling of protein structure and dynamics. The consideration of protein flexibility and dynamics should improve protein structure prediction and refinement of computational models. This work is the first to combine coarse-grained multibody potentials with an entropic model that takes into account contributions of the entire structure, investigating native-like decoy selection. © 2011 Springer Science+Business Media B.V.

关键词： 4-Body potentials Elastic network models Multibody potentials Protein dynamics Protein structure prediction Protein structure refinement

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Correction to: Efficient genetic code expansion without host genome modifications (Nature Biotechnology, (2024), 10.1038/s41587-024-02385-y)

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Nature Biotechnology 2024年

作者： Costello, Alan Peterson, Alexander A. Lanster, David L. Li, Zhiyi Carver, Gavriela D. Badran, Ahmed H. Department of Chemistry The Scripps Research Institute La Jolla CA United States Department of Integrative Structural and Computational Biology The Scripps Research Institute La Jolla CA United States Doctoral Program in Chemical and Biological Sciences The Scripps Research Institute La Jolla CA United States Department of Molecular Biology Princeton University PrincetonNJ United States

Correction to: Nature Biotechnologyhttps://***/10.1038/s41587-024-02385-y, published online 11 September 2024. In the version of the article initially published, the far left oxygen symbol was missing from Fig. 1b and "N346A;C348A" was mistakenly included in the figure legend for Fig. 4d. These errors have now been amended in the HTML and PDF versions of the article. © The Author(s), under exclusive licence to Springer Nature America, Inc. 2024.

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