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作者： Baker, Matthew L. Baker, Mariah R. Hryc, Corey F. Ju, Tao Chiu, Wah Verna and Marrs McLean Department of Biochemistry and Molecular Biology National Center for Macromolecular Imaging Baylor College of Medicine Houston TX 77030 United States Program in Structural and Computational Biology and Molecular Biophysics Baylor College of Medicine Houston TX 77030 United States Department of Computer Science and Engineering Washington University in St. Louis St. Louis MO 63130 United States

The complex interplay of proteins and other molecules, often in the form of large transitory assemblies, are critical to cellular function. Today, X-ray crystallography and electron cryo-microscopy (cryo-EM) are routinely used to image these macromolecular complexes, though often at limited resolutions. Despite the rapidly growing number of macromolecular structures, few tools exist for modeling and annotating structures in the range of 3-10 Å resolution. To address this need, we have developed a number of utilities specifically targeting subnanometer resolution density maps. As part of the 2010 Cryo-EM Modeling Challenge, we demonstrated two of our latest de novo modeling tools, Pathwalking and Gorgon, as well as a tool for secondary structure identification (SSEHunter) and a new rigid-body/flexible fitting tool in Gorgon. In total, we submitted 30 structural models from ten different subnanometer resolution data sets in four of the six challenge categories. Each of our utlities produced accurate structural models and annotations across the various density maps. In the end, the utilities that we present here offer users a robust toolkit for analyzing and modeling protein structure in macromolecular assemblies at non-atomic resolutions. © 2012 Wiley Periodicals, Inc.

关键词： X ray crystallography

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Zernike Phase Contrast Cryo-Electron Microscopy of Virus Particles

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Microscopy and Microanalysis 2012年第S2期18卷 462-463页

作者： Chiu, W. Rochat, R.H. Liu, X. Murata, K. Khant, H. Nagayama, K. Rixon, Frazer National Center for Macromolecular Imaging Baylor College of Medicine Houston TX 77030 United States Graduate Program in Structural Computational Biology Molecular Biophysics Baylor College of Medicine Houston TX 77030 United States Okazaki Institute for Integrative Bioscience National Institute of Natural Sciences Okazaki Aichi 444-8787 5-1 Higashiyama Myodaiji-cho Japan MRC - University of Glasgow Centre for Virus Research Glasgow G11 5JR United Kingdom

Extended abstract of a paper presented at Microscopy and Microanalysis 2012 in Phoenix, Arizona, USA, July 29 – August 2, 2012.

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Abstracts from the 3rd International Genomic Medicine Conference (3rd IGMC 2015) : Jeddah, Kingdom of Saudi Arabia. 30 November - 3 December 2015

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BMC genomics 2016年第6期17 Suppl 6卷 487页

作者： Jerry W. Shay Noriko Homma Ruyun Zhou Muhammad Imran Naseer Adeel G. Chaudhary Mohammed Al-Qahtani Nobutaka Hirokawa Maryam Goudarzi Albert J. Fornace Saleh Baeesa Deema Hussain Mohammed Bangash Fahad Alghamdi Hans-Juergen Schulten Angel Carracedo Ishaq Khan Hanadi Qashqari Nawal Madkhali Mohamad Saka Kulvinder S. Saini Awatif Jamal Jaudah Al-Maghrabi Adel Abuzenadah Adeel Chaudhary Mohammed Al Qahtani Ghazi Damanhouri Heba Alkhatabi Anne Goodeve Laura Crookes Nikolas Niksic Nicholas Beauchamp Adel M. Abuzenadah Jim Vaught Bruce Budowle Mourad Assidi Abdelbaset Buhmeida Leena Merdad Sudhir Kumar Sayaka Miura Karen Gomez Mahmood Rasool Ahmed Rebai Sajjad Karim Hend F. Nour Eldin Heba Abusamra Elham M. Alhathli Nada Salem Mohammed H. Al-Qahtani Hossam Faheem Ashok Agarwa Eberhard Nieschlag Joachim Wistuba Oliver S. Damm Mohd A. Beg Taha A. Abdel-Meguid Hisham A. Mosli Osama S. Bajouh Serdar Coskun Muhammad Abu-Elmagd Ashraf Dallol Sahar Hakamy Wejdan Al-Qahtani Asia Al-Harbi Shireen Hussain Burak Ozkosem Rick DuBois Safia S. Messaoudi Maryam T. Dandana Touhami Mahjoub Wassim Y. Almawi S. Abdalla M. Nabil Al-Aama Asmaa Elzawahry Tsuyoshi Takahashi Sachiyo Mimaki Eisaku Furukawa Rie Nakatsuka Isao Kurosaka Takahiko Nishigaki Hiromi Nakamura Satoshi Serada Tetsuji Naka Seiichi Hirota Tatsuhiro Shibata Katsuya Tsuchihara Toshirou Nishida Mamoru Kato Sajid Mehmood Naeem Mahmood Ashraf Awais Asif Muhammad Bilal Malik Siddique Mehmood Aadil Hussain Qazi Mohammad Sajid Jamal Mughees Uddin Siddiqui Mohammad A. Alzohairy Mohammad A. Al Karaawi Taoufik Nedjadi Heba Al-Khattabi Adel Al-Ammari Ahmed Al-Sayyad Hédia Zitouni Nozha Raguema Marwa Ben Ali Wided Malah Raja Lfalah Wassim Almawi Mohammed Elanbari Andrey Ptitsyn Sana Mahjoub Rabeb El Ghali Bechir Achour Nidhal Ben Amor Brahim N’siri Hamid Morjani Esam Azhar Vera Chayeb Maryam Dendena Hedia Zitouni Khedija Zouari-Limayem Bassem Refaat Ahmed M. Ashshi Sarah A. Batwa Hazem Ramadan Amal Awad Ahmed Ateya Adel Galal Ahmed El-Shemi Ahmad Ashshi Mohammed Basalamah Youjin Na Cha University of Texas Southwestern Medical Center Dallas USA Department of Cell Biology and Anatomy Graduate School of Medicine the University of Tokyo Tokyo Japan Center of Excellence in Genomic Medicine Research King Abdulaziz University Jeddah Saudi Arabia Department of Biochemistry and Molecular & Cellular Biology Lombardi Comprehensive Cancer Center Georgetown University Washington USA Department of Oncology Lombardi Comprehensive Cancer Center Georgetown University Washington USA Department of Radiation Medicine Lombardi Comprehensive Cancer Center Georgetown University Washington USA Center of Excellence in Genomic Medicine Research (CEGMR) King Abdulaziz University Jeddah Kingdom of Saudi Arabia King Fahd Medical Research Centre King Abdulaziz University Jeddah Saudi Arabia Centre of Excellence in Genomic Medicine Research King Abdulaziz University Jeddah Saudi Arabia Sheffield Diagnostic Genetic Service Sheffield Children’s NHS Foundation Trust Western Bank Sheffield UK Center of Innovations in Personalized Medicine King Abdulaziz University Jeddah Saudi Arabia President ISBER Editor-in-Chief Biopreservation & Biobanking ᅟ USA Institute of Applied Genetics Department of Molecular and Medical Genetics University of North Texas Health Science Center Fort Worth USA Department of Dental Public Health Faculty of Dentistry King Abdulaziz University Jeddah Saudi Arabia Institute for Genomics and Evolutionary Medicine Temple University Philadelphia USA Center of Excellence in Genomic Medicine King Abdulaziz University Jeddah Kingdom of Saudi Arabia Laboratory of Molecular and Cellular Screening Processes (Bioinformatics Group) Centre of Biotechnology of Sfax Sfax Tunisia Fujitsu Technology Solutions International ᅟ ᅟ Case Western Reserve University School of Medicine and Lerner College of Medicine Cleveland Clinic Foundation Cleveland USA American Center for Reproductive Medicine Andrology Center Cleveland USA Center for Reproductive Medicine and

O1 Regulation of genes by telomere length over long distances Jerry W. Shay O2 The microtubule destabilizer KIF2A regulates the postnatal establishment of neuronal circuits in addition to prenatal cell survival, cell migration, and axon elongation, and its loss leading to malformation of cortical development and severe epilepsy Noriko Homma, Ruyun Zhou, Muhammad Imran Naseer, Adeel G. Chaudhary, Mohammed Al-Qahtani, Nobutaka Hirokawa O3 Integration of metagenomics and metabolomics in gut microbiome research Maryam Goudarzi, Albert J. Fornace Jr. O4 A unique integrated system to discern pathogenesis of central nervous system tumors Saleh Baeesa, Deema Hussain, Mohammed Bangash, Fahad Alghamdi, Hans-Juergen Schulten, Angel Carracedo, Ishaq Khan, Hanadi Qashqari, Nawal Madkhali, Mohamad Saka, Kulvinder S. Saini, Awatif Jamal, Jaudah Al-Maghrabi, Adel Abuzenadah, Adeel Chaudhary, Mohammed Al Qahtani, Ghazi Damanhouri O5 RPL27A is a target of miR-595 and deficiency contributes to ribosomal dysgenesis Heba Alkhatabi O6 Next generation DNA sequencing panels for haemostatic and platelet disorders and for Fanconi anaemia in routine diagnostic service Anne Goodeve, Laura Crookes, Nikolas Niksic, Nicholas Beauchamp O7 Targeted sequencing panels and their utilization in personalized medicine Adel M. Abuzenadah O8 International biobanking in the era of precision medicine Jim Vaught O9 Biobank and biodata for clinical and forensic applications Bruce Budowle, Mourad Assidi, Abdelbaset Buhmeida O10 Tissue microarray technique: a powerful adjunct tool for molecular profiling of solid tumors Jaudah Al-Maghrabi O11 The CEGMR biobanking unit: achievements, challenges and future plans Abdelbaset Buhmeida, Mourad Assidi, Leena Merdad O12 Phylomedicine of tumors Sudhir Kumar, Sayaka Miura, Karen Gomez O13 Clinical implementation of pharmacogenomics for colorectal cancer treatment Angel Carracedo, Mahmood Rasool O14 From association to causality: translation of GWAS findings for genomic me

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A Bayesian model for SNP discovery based on next-generation sequencing data

A Bayesian model for SNP discovery based on next-generation ...

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

作者： Yanxun Xu Xiaofeng Zheng Yuan Yuan Marcos R Estecio Jean-Pierre Issa Yuan Ji Shoudan Liang Department of Statistics Rice University Houston TX USA Department of Bioinformatics and Computational Biology University of Texas M.D. Anderson Cancer Center Houston TX USA Graduate Program in Structural and Computational Biology and Molecular Biophysics Baylor College of Medicine Houston TX USA Department of Biochemistry and Molecular Biology University of Texas M.D. Anderson Cancer Center Houston TX USA Fels Institute for Cancer Research and Molecular Biology Temple University Philadelphia PA USA CCRI NorthShore University HealthSystem Chicago IL USA

ISBN: (纸本)9781467352345

A single-nucleotide polymorphism (SNP) is a single base change in the DNA sequence and is the most common polymorphism. Since some SNPs have a major influence on disease susceptibility, detecting SNPs plays an important role in biomedical research. To take fully advantage of the next-generation sequencing (NGS) technology and detect SNP more effectively, we propose a Bayesian approach that computes a posterior probability of hidden nucleotide variations at each covered genomic position. The position with higher posterior probability of hidden nucleotide variation has a higher chance to be a SNP. We apply the proposed method to detect SNPs in two cell lines: the prostate cancer cell line PC3 and the embryonic stem cell line H1. A comparison between our results with dbSNP database shows a high ratio of overlap (≥95 %). The positions that are called only under our model but not in dbSNP may serve as candidates for new SNPs.

关键词： comparison candidates generation Single nucleotide polymorphism sequence number protection a posteriori probability DNA Sequence Bayesian inference Disease Susceptibility Analyses, Sequence

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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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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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Efficient and Stereoselective Synthesis of α(2→9) Oligosialic Acids: From Monomers to Dodecamers†

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Angewandte Chemie 2011年第40期123卷

作者： Kuo‐Ching Chu Chien‐Tai Ren Chun‐Ping Lu Che‐Hsiung Hsu Tsung‐Hsien Sun Jeng‐Liang Han Bikash Pal Tsung‐An Chao Yung‐Feng Lin Shih‐Hsiung Wu Chi‐Huey Wong Chung‐Yi Wu Genomics Research Center Academia Sinica 128 Academia Road Section 2 Nankang Taipei 115 (Taiwan) Institute of Biological Chemistry Academia Sinica (Taiwan) Chemical Biology and Molecular Biophysics Taiwan International Graduate Program Academia Sinica 128 Academia Road Section 2 Nankang Taipei 115 (Taiwan) Institute of Bioinformatics and Structural Biology National Tsing‐Hua University Hsin‐Chu (Taiwan)

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Auf dem Weg zur automatisierten Oligosaccharid‐ Synthese

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Angewandte Chemie 2011年第50期123卷

作者： Che‐Hsiung Hsu Shang‐Cheng Hung Chung‐Yi Wu Chi‐Huey Wong The Genomics Research Center Academia Sinica Taiwan 128 Academia Road Section 2 Nankang Taipei 115 (Taiwan) Chemical Biology and Molecular Biophysics Taiwan International Graduate Program Academia Sinica (Taiwan) Institute of Bioinformatics and Structural Biology National Tsing‐Hua University Hsin‐Chu (Taiwan) Department of Chemistry The Scripps Research Institute 10550 North Torrey Pines Road La Jolla CA 92037 (USA)

Kohlenhydrate spielen eine wichtige Rolle bei biologischen Vorgängen. Das Fortschrittstempo der Kohlenhydratforschung ist jedoch relativ langsam, was unter anderem mit der Komplexität der Kohlenhydratstrukturen und dem Fehlen allgemein anwendbarer Synthesemethoden und Verfahren zur Untersuchung dieser Klasse von Biomolekülen zusammenhängt. Jüngste Fortschritte in der Synthese haben ergeben, dass viele dieser Probleme umgangen werden können. In diesem Aufsatz beschreiben wir die Methoden, die entwickelt wurden, um mit den Herausforderungen kohlenhydratvermittelter biologischer Vorgänge umzugehen. Besonderes Augenmerk wird dabei auf die Entwicklung der automatisierten Synthese von Oligosacchariden gerichtet. Darüber hinaus werden auch Kohlenhydrat‐Mikroarrays und Impfstoffe auf Kohlenhydratbasis behandelt.

关键词： Eintopfreaktionen Festphasensynthese Impfstoffe Kohlenhydrate Mikroarrays

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Bayesian estimation of genomic copy number with single nucleotide polymorphism genotyping arrays

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BMC Research Notes 2010年第1期3卷 1-18页

作者： Guo, Beibei Villagran, Alejandro Vannucci, Marina Wang, Jian Davis, Caleb Man, Tsz-Kwong Lau, Ching Guerra, Rudy Department of Statistics Rice University Houston TX 77005-1827 6100 Main United States Department of Statistics University of Connecticut Storrs CT 06269-4120 United States Department of Pediatrics Baylor College of Medicine Texas Children's Hospital Houston TX 77030 6621 Fannin St. United States Structural and Computational Biology and Molecular Biophysics Program Baylor College of Medicine Houston TX 77030 One Baylor Plaza United States

Background. The identification of copy number aberration in the human genome is an important area in cancer research. We develop a model for determining genomic copy numbers using high-density single nucleotide polymorphism genotyping microarrays. The method is based on a Bayesian spatial normal mixture model with an unknown number of components corresponding to true copy numbers. A reversible jump Markov chain Monte Carlo algorithm is used to implement the model and perform posterior inference. Results. The performance of the algorithm is examined on both simulated and real cancer data, and it is compared with the popular CNAG algorithm for copy number detection. Conclusions. We demonstrate that our Bayesian mixture model performs at least as well as the hidden Markov model based CNAG algorithm and in certain cases does better. One of the added advantages of our method is the flexibility of modeling normal cell contamination in tumor samples. © 2010 Guerra et al;licensee BioMed Central Ltd.

关键词： Comparative Genomic Hybridization Misclassification Rate Copy Number Aberration Normal Copy Number Reversible Jump Markov Chain Monte Carlo

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structural insights into TDP-43 in nucleic-acid binding and domain interactions

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Nucleic Acids Research 2009年第6期37卷 1799-1808页

作者： Kuo, Pan-Hsien Doudeva, Lyudmila G. Wang, Yi-Ting Shen, Che-Kun James Yuan, Hanna S. Institute of Bioinformatics and Structural Biology National Tsing Hua University Taipei Taiwan Institute of Molecular Biology National Taiwan University Taipei Taiwan Taiwan International Graduate Program Chemical Biology and Molecular Biophysics National Taiwan University Taipei Taiwan Graduate Institute of Biochemistry and Molecular Biology National Taiwan University Taipei Taiwan

TDP-43 is a pathogenic protein: its normal function in binding to UG-rich RNA is related to cystic fibrosis, and inclusion of its C-terminal fragments in brain cells is directly linked to frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS). Here we report the 1.65 Å crystal structure of the C-terminal RRM2 domain of TDP-43 in complex with a single-stranded DNA. We show that TDP-43 is a dimeric protein with two RRM domains, both involved in DNA and RNA binding. The crystal structure reveals the basis of TDP-43's TG/ UG preference in nucleic acids binding. It also reveals that RRM2 domain has an atypical RRM-fold with an additional β-strand involved in making protein-protein interactions. This self association of RRM2 domains produced thermal-stable RRM2 assemblies with a melting point greater than 85°C as monitored by circular dichroism at physiological conditions. These studies thus characterize the recognition between TDP-43 and nucleic acids and the mode of RRM2 self association, and provide molecular models for understanding the role of TDP-43 in cystic fibrosis and the neurodegenerative diseases related to TDP-43 proteinopathy. © 2009 The Author(s).

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