Highly Accurate Protein Structure Prediction for the Human Proteome
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Bioinformatic Analysis of Structure and Function of LIM Domains of Human Zyxin Family Proteins
International Journal of Molecular Sciences Article Bioinformatic Analysis of Structure and Function of LIM Domains of Human Zyxin Family Proteins M. Quadir Siddiqui 1,† , Maulik D. Badmalia 1,† and Trushar R. Patel 1,2,3,* 1 Alberta RNA Research and Training Institute, Department of Chemistry and Biochemistry, University of Lethbridge, 4401 University Drive, Lethbridge, AB T1K 3M4, Canada; [email protected] (M.Q.S.); [email protected] (M.D.B.) 2 Department of Microbiology, Immunology and Infectious Disease, Cumming School of Medicine, University of Calgary, 3330 Hospital Drive, Calgary, AB T2N 4N1, Canada 3 Li Ka Shing Institute of Virology, University of Alberta, Edmonton, AB T6G 2E1, Canada * Correspondence: [email protected] † These authors contributed equally to the work. Abstract: Members of the human Zyxin family are LIM domain-containing proteins that perform critical cellular functions and are indispensable for cellular integrity. Despite their importance, not much is known about their structure, functions, interactions and dynamics. To provide insights into these, we used a set of in-silico tools and databases and analyzed their amino acid sequence, phylogeny, post-translational modifications, structure-dynamics, molecular interactions, and func- tions. Our analysis revealed that zyxin members are ohnologs. Presence of a conserved nuclear export signal composed of LxxLxL/LxxxLxL consensus sequence, as well as a possible nuclear localization signal, suggesting that Zyxin family members may have nuclear and cytoplasmic roles. The molecular modeling and structural analysis indicated that Zyxin family LIM domains share Citation: Siddiqui, M.Q.; Badmalia, similarities with transcriptional regulators and have positively charged electrostatic patches, which M.D.; Patel, T.R. -
Phylogenomic Analysis of the Chlamydomonas Genome Unmasks Proteins Potentially Involved in Photosynthetic Function and Regulation
Photosynth Res DOI 10.1007/s11120-010-9555-7 REVIEW Phylogenomic analysis of the Chlamydomonas genome unmasks proteins potentially involved in photosynthetic function and regulation Arthur R. Grossman • Steven J. Karpowicz • Mark Heinnickel • David Dewez • Blaise Hamel • Rachel Dent • Krishna K. Niyogi • Xenie Johnson • Jean Alric • Francis-Andre´ Wollman • Huiying Li • Sabeeha S. Merchant Received: 11 February 2010 / Accepted: 16 April 2010 Ó The Author(s) 2010. This article is published with open access at Springerlink.com Abstract Chlamydomonas reinhardtii, a unicellular green performed to identify proteins encoded on the Chlamydo- alga, has been exploited as a reference organism for iden- monas genome which were likely involved in chloroplast tifying proteins and activities associated with the photo- functions (or specifically associated with the green algal synthetic apparatus and the functioning of chloroplasts. lineage); this set of proteins has been designated the Recently, the full genome sequence of Chlamydomonas GreenCut. Further analyses of those GreenCut proteins with was generated and a set of gene models, representing all uncharacterized functions and the generation of mutant genes on the genome, was developed. Using these gene strains aberrant for these proteins are beginning to unmask models, and gene models developed for the genomes of new layers of functionality/regulation that are integrated other organisms, a phylogenomic, comparative analysis was into the workings of the photosynthetic apparatus. Keywords Chlamydomonas Á GreenCut Á Chloroplast Á Phylogenomics Á Regulation A. R. Grossman (&) Á M. Heinnickel Á D. Dewez Á B. Hamel Department of Plant Biology, Carnegie Institution for Science, 260 Panama Street, Stanford, CA 94305, USA Introduction e-mail: [email protected] Chlamydomonas reinhardtii as a reference organism S. -
An Emerging Field for the Structural Analysis of Proteins on the Proteomic Scale † ‡ ‡ ‡ § ‡ ∥ Upneet Kaur, He Meng, Fang Lui, Renze Ma, Ryenne N
Perspective Cite This: J. Proteome Res. 2018, 17, 3614−3627 pubs.acs.org/jpr Proteome-Wide Structural Biology: An Emerging Field for the Structural Analysis of Proteins on the Proteomic Scale † ‡ ‡ ‡ § ‡ ∥ Upneet Kaur, He Meng, Fang Lui, Renze Ma, Ryenne N. Ogburn, , Julia H. R. Johnson, , ‡ † Michael C. Fitzgerald,*, and Lisa M. Jones*, ‡ Department of Chemistry, Duke University, Durham, North Carolina 27708-0346, United States † Department of Pharmaceutical Sciences, University of Maryland, Baltimore, Maryland 21201, United States ABSTRACT: Over the past decade, a suite of new mass- spectrometry-based proteomics methods has been developed that now enables the conformational properties of proteins and protein− ligand complexes to be studied in complex biological mixtures, from cell lysates to intact cells. Highlighted here are seven of the techniques in this new toolbox. These techniques include chemical cross-linking (XL−MS), hydroxyl radical footprinting (HRF), Drug Affinity Responsive Target Stability (DARTS), Limited Proteolysis (LiP), Pulse Proteolysis (PP), Stability of Proteins from Rates of Oxidation (SPROX), and Thermal Proteome Profiling (TPP). The above techniques all rely on conventional bottom-up proteomics strategies for peptide sequencing and protein identification. However, they have required the development of unconventional proteomic data analysis strategies. Discussed here are the current technical challenges associated with these different data analysis strategies as well as the relative analytical capabilities of the different techniques. The new biophysical capabilities that the above techniques bring to bear on proteomic research are also highlighted in the context of several different application areas in which these techniques have been used, including the study of protein ligand binding interactions (e.g., protein target discovery studies and protein interaction network analyses) and the characterization of biological states. -
Journal of Molecular Graphics and Modelling 73 (2017) 179–190
Journal of Molecular Graphics and Modelling 73 (2017) 179–190 Contents lists available at ScienceDirect Journal of Molecular Graphics and Modelling journa l homepage: www.elsevier.com/locate/JMGM Combined Monte Carlo/torsion-angle molecular dynamics for ensemble modeling of proteins, nucleic acids and carbohydrates a b c d,1 Weihong Zhang , Steven C. Howell , David W. Wright , Andrew Heindel , e a, b, Xiangyun Qiu , Jianhan Chen ∗, Joseph E. Curtis ∗∗ a Kansas State University, Manhattan, KS, USA b NIST Center for Neutron Research, 100 Bureau Drive, Gaithersburg, MD, USA c Centre for Computational Science, Department of Chemistry, University College London, 10 Gordon St., London, UK d James Madison University, Department of Chemistry & Biochemistry, Harrisonburg, VA, USA e Department of Physics, The George Washington University, Washington, DC, USA a r t i c l e i n f o a b s t r a c t Article history: We describe a general method to use Monte Carlo simulation followed by torsion-angle molecular dynam- Received 13 October 2016 ics simulations to create ensembles of structures to model a wide variety of soft-matter biological systems. Received in revised form 19 January 2017 Our particular emphasis is focused on modeling low-resolution small-angle scattering and reflectivity Accepted 17 February 2017 structural data. We provide examples of this method applied to HIV-1 Gag protein and derived fragment Available online 23 February 2017 proteins, TraI protein, linear B-DNA, a nucleosome core particle, and a glycosylated monoclonal antibody. This procedure will enable a large community of researchers to model low-resolution experimental data MSC: with greater accuracy by using robust physics based simulation and sampling methods which are a 00-01 99-00 significant improvement over traditional methods used to interpret such data. -
1 Supporting Information for a Microrna Network Regulates
Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: [email protected] (M.J.W.); yi- [email protected] (Y.X.); Email: [email protected] (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia. -
Missense Variant of Endoplasmic Reticulum Region of WFS1 Gene Causes Autosomal Dominant Hearing Loss Without Syndromic Phenotype
Hindawi BioMed Research International Volume 2021, Article ID 6624744, 9 pages https://doi.org/10.1155/2021/6624744 Research Article Missense Variant of Endoplasmic Reticulum Region of WFS1 Gene Causes Autosomal Dominant Hearing Loss without Syndromic Phenotype Jinying Li ,1,2 Hongen Xu ,3,4 Jianfeng Sun ,5 Yongan Tian ,6,7 Danhua Liu ,4 Yaping Qin ,4 Huanfei Liu,3 Ruijun Li ,3 Lingling Neng ,1 Xiaohua Deng ,8 Binbin Xue ,1 Changyun Yu ,1 and Wenxue Tang 3,4,7 1Department of Otolaryngology Head and Neck Surgery, The First Affiliated Hospital of Zhengzhou University, Jianshedong Road No. 1, Zhengzhou 450052, China 2Academy of Medical Science, Zhengzhou University, Daxuebei Road No. 40, Zhengzhou 450052, China 3Precision Medicine Center, Academy of Medical Science, Zhengzhou University, Daxuebei Road No. 40, Zhengzhou 450052, China 4The Second Affiliated Hospital of Zhengzhou University, Jingba Road No. 2, Zhengzhou 450014, China 5Department of Bioinformatics, Technical University of Munich, Wissenschaftszentrum Weihenstephan, 85354 Freising, Germany 6BGI College, Zhengzhou University, Daxuebei Road No. 40, Zhengzhou 450052, China 7Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Daxuebei Road No. 40, Zhengzhou 450052, China 8The Third Affiliated Hospital of Xinxiang Medical University, Hualan Road, No. 83, Xinxiang 453000, China Correspondence should be addressed to Changyun Yu; [email protected] and Wenxue Tang; [email protected] Received 24 November 2020; Revised 1 February 2021; Accepted 14 February 2021; Published 4 March 2021 Academic Editor: Burak Durmaz Copyright © 2021 Jinying Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. -
Biological Sciences 1
Biological Sciences 1 BIOL UN3208 Introduction to Evolutionary Biology or EEEB UN2001 BIOLOGICAL SCIENCES Environmental Biology I: Elements to Organisms. Departmental Office: 600 Fairchild, 212-854-4581; Interested students should consult listings in other departments for [email protected]; [email protected] courses related to biology. For courses in environmental studies, see listings for Earth and environmental sciences or for ecology, evolution, Director of Undergraduate Studies, Undergraduate Programs and and environmental biology. For courses in human evolution, see listings Laboratories: for anthropology or for ecology, evolution, and environmental biology. Prof. Deborah Mowshowitz, 744D Mudd; 212-854-4497; For courses in the history of evolution, see listings for history and for [email protected] philosophy of science. For a list of courses in computational biology and genomics, visit http://systemsbiology.columbia.edu/courses. Biology Major and Concentration Advisers: For a list of current biology, biochemistry, biophysics, and neuroscience and behavior advisers, please visit http://biology.columbia.edu/ Advanced Placement programs/advisors Transfer Credit A-F: Prof. Alice Heicklen, 744B Mudd; [email protected] Transfer credits granted toward the degree are not automatically counted G-O: Prof. Mary Ann Price, 744A Mudd; [email protected] toward the major. The department determines which transfer credits P-Z: Prof. Tulle Hazelrigg, 753A Mudd, [email protected] can be counted toward the major. For most majors, at least four biology Backup Advisor: Prof. Deborah Mowshowitz, 744D Mudd; 212-854-4497; or biochemistry courses and at least 18 credits of the total (biology, [email protected] biochemistry, math, physics, and chemistry) must be taken at Columbia. -
Static Retention of the Lumenal Monotopic Membrane Protein Torsina in the Endoplasmic Reticulum
The EMBO Journal (2011) 30, 3217–3231 | & 2011 European Molecular Biology Organization | All Rights Reserved 0261-4189/11 www.embojournal.org TTHEH E EEMBOMBO JJOURNALOURN AL Static retention of the lumenal monotopic membrane protein torsinA in the endoplasmic reticulum Abigail B Vander Heyden1, despite the fact that it has been a decade since the protein was Teresa V Naismith1, Erik L Snapp2 and first described and linked to dystonia (Breakefield et al, Phyllis I Hanson1,* 2008). Based on its membership in the AAA þ family of ATPases (Ozelius et al, 1997; Hanson and Whiteheart, 2005), 1Department of Cell Biology and Physiology, Washington University School of Medicine, St Louis, MO, USA and 2Department of Anatomy it is likely that torsinA disassembles or changes the confor- and Structural Biology, Albert Einstein College of Medicine, Bronx, mation of a protein or protein complex in the ER or NE. The NY, USA DE mutation is thought to compromise this function (Dang et al, 2005; Goodchild et al, 2005). TorsinA is a membrane-associated enzyme in the endo- TorsinA is targeted to the ER lumen by an N-terminal plasmic reticulum (ER) lumen that is mutated in DYT1 signal peptide. Analyses of torsinA’s subcellular localization, dystonia. How it remains in the ER has been unclear. We processing, and glycosylation show that the signal peptide is report that a hydrophobic N-terminal domain (NTD) di- cleaved and the mature protein resides in the lumen of the ER rects static retention of torsinA within the ER by excluding (Kustedjo et al, 2000; Hewett et al, 2003; Liu et al, 2003), it from ER exit sites, as has been previously reported for where it is a stable protein (Gordon and Gonzalez-Alegre, short transmembrane domains (TMDs). -
Common Variants in SOX-2 and Congenital Cataract Genes Contribute to Age-Related Nuclear Cataract
ARTICLE https://doi.org/10.1038/s42003-020-01421-2 OPEN Common variants in SOX-2 and congenital cataract genes contribute to age-related nuclear cataract Ekaterina Yonova-Doing et al.# 1234567890():,; Nuclear cataract is the most common type of age-related cataract and a leading cause of blindness worldwide. Age-related nuclear cataract is heritable (h2 = 0.48), but little is known about specific genetic factors underlying this condition. Here we report findings from the largest to date multi-ethnic meta-analysis of genome-wide association studies (discovery cohort N = 14,151 and replication N = 5299) of the International Cataract Genetics Consortium. We confirmed the known genetic association of CRYAA (rs7278468, P = 2.8 × 10−16) with nuclear cataract and identified five new loci associated with this dis- ease: SOX2-OT (rs9842371, P = 1.7 × 10−19), TMPRSS5 (rs4936279, P = 2.5 × 10−10), LINC01412 (rs16823886, P = 1.3 × 10−9), GLTSCR1 (rs1005911, P = 9.8 × 10−9), and COMMD1 (rs62149908, P = 1.2 × 10−8). The results suggest a strong link of age-related nuclear cat- aract with congenital cataract and eye development genes, and the importance of common genetic variants in maintaining crystalline lens integrity in the aging eye. #A list of authors and their affiliations appears at the end of the paper. COMMUNICATIONS BIOLOGY | (2020) 3:755 | https://doi.org/10.1038/s42003-020-01421-2 | www.nature.com/commsbio 1 ARTICLE COMMUNICATIONS BIOLOGY | https://doi.org/10.1038/s42003-020-01421-2 ge-related cataract is the leading cause of blindness, structure (meta-analysis genomic inflation factor λ = 1.009, accounting for more than one-third of blindness Supplementary Table 4 and Supplementary Fig. -
CCP4 Molecular Graphics Documentation Contents Documentation On-Line Documentation Tutorials Ccp4mg Home Contents Quick Reference Print Version Contact References
CCP4 Molecular Graphics file:///E:/ccp4mg-win/help/index.html CCP4 Molecular Graphics Documentation Contents Documentation On-line Documentation Tutorials CCP4mg Home Contents Quick Reference Print version Contact References Documentation Contents General Graphics Window - mouse bindings and short cuts The Tools menu The View menu Projects - data organisation Installation of support programs Molecular models Reading coordinate files and atom typing The Coordinate Model Interface Atom selection Structure Analysis Surfaces and Electrostatic Potentials Symmetry Related Models Animations Other types of data Electron density maps Vectors Electron density in GAUSSIAN cube format Text and imported images Applications Superpose automatic protein superposition and interactive superposition of any structures Presentation Graphics Picture Wizard set up complex pictures quickly Movies Presentations Geometry Run Coot Other utilities Web tools History and Scripting Editing and Saving Files PDF Creator - PDF4Free v2.0 http://www.pdf4free.com 1 of 3 01/11/2007 18:42 CCP4 Molecular Graphics file:///E:/ccp4mg-win/help/index.html Lighting Saving the program status Picture Definition Files (also Object attributes and Introduction to Python) Making presentations Quick Reference See Display Table for general overview of the display table. For information on specific type of data click the appropriate data type in the File list below. File Tools View Applications Coordinate Files General tools General tools Movies Downloading Coordinate .. .. Superpose Files Read electron density Picture Save/restore view Lighting map/MTZ Wizard Read QM maps Save/restore status Transparency Geometry Add vectors/labels Picture definition files View from Rotate,translate,align Add image History and Scripting view Add legend Presentation/Notebook RocknRoll Add crystal List monomer definition Model definition file Preferences Open presentation Tutorials Output screen image Windows Bring a 'lost' window to the front. -
Coot: Model-Building Tools for Molecular Graphics Crystallography ISSN 0907-4449
research papers Acta Crystallographica Section D Biological Coot: model-building tools for molecular graphics Crystallography ISSN 0907-4449 Paul Emsley* and Kevin Cowtan CCP4mg is a project that aims to provide a general-purpose Received 26 February 2004 tool for structural biologists, providing tools for X-ray Accepted 4 August 2004 structure solution, structure comparison and analysis, and York Structural Biology Laboratory, University of York, Heslington, York YO10 5YW, England publication-quality graphics. The map-®tting tools are avail- able as a stand-alone package, distributed as `Coot'. Correspondence e-mail: [email protected] 1. Introduction Molecular graphics still plays an important role in the deter- mination of protein structures using X-ray crystallographic data, despite on-going efforts to automate model building. Functions such as side-chain placement, loop, ligand and fragment ®tting, structure comparison, analysis and validation are routinely performed using molecular graphics. Lower Ê resolution (dmin worse than 2.5 A) data in particular need interactive ®tting. The introduction of FRODO (Jones, 1978) and then O (Jones et al., 1991) to the ®eld of protein crystallography was in each case revolutionary, each in their time breaking new ground in demonstrating what was possible with the current hardware. These tools allowed protein crystallographers to enjoy what is widely held to be the most thrilling part of their work: giving birth (as it were) to a new protein structure. The CCP4 program suite (Collaborative Computational Project, Number 4, 1994) is an integrated collection of software for macromolecular crystallography, with a scope ranging from data processing to structure re®nement and validation. -
PROTEOMICS the Human Proteome Takes the Spotlight
RESEARCH HIGHLIGHTS PROTEOMICS The human proteome takes the spotlight Two papers report mass spectrometry– big data. “We then thought, include some surpris- based draft maps of the human proteome ‘What is a potentially good ing findings. For example, and provide broadly accessible resources. illustration for the utility Kuster’s team found protein For years, members of the proteomics of such a database?’” says evidence for 430 long inter- community have been trying to garner sup- Kuster. “We very quickly genic noncoding RNAs, port for a large-scale project to exhaustively got to the idea, ‘Why don’t which have been thought map the normal human proteome, including we try to put together the not to be translated into pro- identifying all post-translational modifica- human proteome?’” tein. Pandey’s team refined tions and protein-protein interactions and The two groups took the annotations of 808 genes providing targeted mass spectrometry assays slightly different strategies and also found evidence and antibodies for all human proteins. But a towards this common goal. for the translation of many Nik Spencer/Nature Publishing Group Publishing Nik Spencer/Nature lack of consensus on how to exactly define Pandey’s lab examined 30 noncoding RNAs and pseu- Two groups provide mass the proteome, how to carry out such a mis- normal tissues, including spectrometry evidence for dogenes. sion and whether the technology is ready has adult and fetal tissues, as ~90% of the human proteome. Obtaining evidence for not so far convinced any funding agencies to well as primary hematopoi- the last roughly 10% of pro- fund on such an ambitious project.