1
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Wang S, Reeve SM, Holt GT, Ojewole AA, Frenkel MS, Gainza P, Keshipeddy S, Fowler VG, Wright DL, Donald BR. Chiral evasion and stereospecific antifolate resistance in Staphylococcus aureus. PLoS Comput Biol 2022; 18:e1009855. [PMID: 35143481 PMCID: PMC8865654 DOI: 10.1371/journal.pcbi.1009855] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 02/23/2022] [Accepted: 01/21/2022] [Indexed: 11/19/2022] Open
Abstract
Antimicrobial resistance presents a significant health care crisis. The mutation F98Y in Staphylococcus aureus dihydrofolate reductase (SaDHFR) confers resistance to the clinically important antifolate trimethoprim (TMP). Propargyl-linked antifolates (PLAs), next generation DHFR inhibitors, are much more resilient than TMP against this F98Y variant, yet this F98Y substitution still reduces efficacy of these agents. Surprisingly, differences in the enantiomeric configuration at the stereogenic center of PLAs influence the isomeric state of the NADPH cofactor. To understand the molecular basis of F98Y-mediated resistance and how PLAs' inhibition drives NADPH isomeric states, we used protein design algorithms in the osprey protein design software suite to analyze a comprehensive suite of structural, biophysical, biochemical, and computational data. Here, we present a model showing how F98Y SaDHFR exploits a different anomeric configuration of NADPH to evade certain PLAs' inhibition, while other PLAs remain unaffected by this resistance mechanism.
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Affiliation(s)
- Siyu Wang
- Department of Computer Science, Duke University, Durham, North Carolina, United States of America
- Program in Computational Biology and Bioinformatics, Duke University, Durham, North Carolina, United States of America
| | - Stephanie M. Reeve
- Department of Pharmaceutical Sciences, University of Connecticut, Storrs, Connecticut, United States of America
| | - Graham T. Holt
- Department of Computer Science, Duke University, Durham, North Carolina, United States of America
- Program in Computational Biology and Bioinformatics, Duke University, Durham, North Carolina, United States of America
| | - Adegoke A. Ojewole
- Department of Computer Science, Duke University, Durham, North Carolina, United States of America
- Program in Computational Biology and Bioinformatics, Duke University, Durham, North Carolina, United States of America
| | - Marcel S. Frenkel
- Department of Biochemistry, Duke University Medical Center, Durham, North Carolina, United States of America
| | - Pablo Gainza
- Department of Computer Science, Duke University, Durham, North Carolina, United States of America
| | - Santosh Keshipeddy
- Department of Pharmaceutical Sciences, University of Connecticut, Storrs, Connecticut, United States of America
| | - Vance G. Fowler
- Division of Infections Diseases, Department of Medicine, Duke University Medical Center, Durham, North Carolina, United States of America
| | - Dennis L. Wright
- Department of Pharmaceutical Sciences, University of Connecticut, Storrs, Connecticut, United States of America
- Department of Chemistry, University of Connecticut, Storrs, Connecticut, United States of America
| | - Bruce R. Donald
- Department of Computer Science, Duke University, Durham, North Carolina, United States of America
- Department of Biochemistry, Duke University Medical Center, Durham, North Carolina, United States of America
- Department of Mathematics, Duke University, Durham, North Carolina, United States of America
- Department of Chemistry, Duke University, Durham, North Carolina, United States of America
- * E-mail:
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2
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Koga N, Koga R, Liu G, Castellanos J, Montelione GT, Baker D. Role of backbone strain in de novo design of complex α/β protein structures. Nat Commun 2021; 12:3921. [PMID: 34168113 PMCID: PMC8225619 DOI: 10.1038/s41467-021-24050-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 05/28/2021] [Indexed: 12/24/2022] Open
Abstract
We previously elucidated principles for designing ideal proteins with completely consistent local and non-local interactions which have enabled the design of a wide range of new αβ-proteins with four or fewer β-strands. The principles relate local backbone structures to supersecondary-structure packing arrangements of α-helices and β-strands. Here, we test the generality of the principles by employing them to design larger proteins with five- and six- stranded β-sheets flanked by α-helices. The initial designs were monomeric in solution with high thermal stability, and the nuclear magnetic resonance (NMR) structure of one was close to the design model, but for two others the order of strands in the β-sheet was swapped. Investigation into the origins of this strand swapping suggested that the global structures of the design models were more strained than the NMR structures. We incorporated explicit consideration of global backbone strain into the design methodology, and succeeded in designing proteins with the intended unswapped strand arrangements. These results illustrate the value of experimental structure determination in guiding improvement of de novo design, and the importance of consistency between local, supersecondary, and global tertiary interactions in determining protein topology. The augmented set of principles should inform the design of larger functional proteins.
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Affiliation(s)
- Nobuyasu Koga
- University of Washington, Department of Biochemistry and Howard Hughes Medical Institute, Seattle, Washington, WA, USA. .,Research Center of Integrative Molecular Systems, Institute for Molecular Science, National Institutes of Natural Sciences, Okazaki, Aichi, Japan. .,Protein Design Group, Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Okazaki, Aichi, Japan. .,SOKENDAI, The Graduate University for Advanced Studies, Hayama, Kanagawa, Japan.
| | - Rie Koga
- University of Washington, Department of Biochemistry and Howard Hughes Medical Institute, Seattle, Washington, WA, USA.,Protein Design Group, Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Okazaki, Aichi, Japan
| | - Gaohua Liu
- Nexomics Biosciences, Rocky Hill, NJ, USA
| | - Javier Castellanos
- University of Washington, Department of Biochemistry and Howard Hughes Medical Institute, Seattle, Washington, WA, USA
| | - Gaetano T Montelione
- Department of Chemistry and Chemical Biology, and Center for Biotechnology and Interdisciplinary Sciences, Rensselaer Polytechnic Institute, Troy, New York, NY, USA.
| | - David Baker
- University of Washington, Department of Biochemistry and Howard Hughes Medical Institute, Seattle, Washington, WA, USA.
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3
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Abstract
Online citizen science projects such as GalaxyZoo1, Eyewire2 and Phylo3 have been very successful for data collection, annotation, and processing, but for the most part have harnessed human pattern recognition skills rather than human creativity. An exception is the game EteRNA4, in which game players learn to build new RNA structures by exploring the discrete two-dimensional space of Watson-Crick base pairing possibilities. Building new proteins, however, is a more challenging task to present in a game, as both the representation and evaluation of a protein structure are intrinsically three-dimensional. We posed the challenge of de novo protein design in the online protein folding game Foldit5. Players were presented with a fully extended peptide chain and challenged to craft a folded protein structure with an amino acid sequence encoding that structure. After many iterations of player design, analysis of the top scoring solutions, and subsequent game improvement, Foldit players can now, starting from an extended polypeptide chain, generate a diversity of protein structures and sequences which encode them in silico. 146 Foldit player designs with sequences unrelated to naturally occurring proteins were encoded in synthetic genes; 56 were found to be expressed in E. coli with good solubility and to adopt stable monomeric folded structures in solution. The diversity of these structures is unprecedented in de novo protein design, representing 20 different folds—including a new fold not observed in natural proteins. High resolution structures were determined for four of the designs, and are nearly identical to the player models. This work makes explicit the considerable implicit knowledge contributing to success in de novo protein design, and shows that citizen scientists can discover creative new solutions to outstanding scientific challenges, such as the protein design problem.
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4
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Gibbs AC, Steele R, Liu G, Tounge BA, Montelione GT. Inhibitor Bound Dengue NS2B-NS3pro Reveals Multiple Dynamic Binding Modes. Biochemistry 2018; 57:1591-1602. [PMID: 29447443 DOI: 10.1021/acs.biochem.7b01127] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Dengue virus poses a significant global health threat as the source of increasingly deleterious dengue fever, dengue hemorrhagic fever, and dengue shock syndrome. As no specific antiviral treatment exists for dengue infection, considerable effort is being applied to discover therapies and drugs for maintenance and prevention of these afflictions. The virus is primarily transmitted by mosquitoes, and infection occurs following viral endocytosis by host cells. Upon entering the cell, viral RNA is translated into a large multisubunit polyprotein which is post-translationally cleaved into mature, structural and nonstructural (NS) proteins. The viral genome encodes the enzyme to carry out cleavage of the large polyprotein, specifically the NS2B-NS3pro cofactor-protease complex-a target of high interest for drug design. One class of recently discovered NS2B-NS3pro inhibitors is the substrate-based trifluoromethyl ketone containing peptides. These compounds interact covalently with the active site Ser135 via a hemiketal adduct. A detailed picture of the intermolecular protease/inhibitor interactions of the hemiketal adduct is crucial for rational drug design. We demonstrate, through the use of protein- and ligand-detected solution-state 19F and 1H NMR methods, an unanticipated multibinding mode behavior of a representative of this class of inhibitors to dengue NS2B-NS3pro. Our results illustrate the highly dynamic nature of both the covalently bound ligand and protease protein structure, and the need to consider these dynamics when designing future inhibitors in this class.
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Affiliation(s)
- Alan C Gibbs
- Janssen Research and Development LLC , Welsh & McKean Roads , Spring House , Pennsylvania 19477 , United States
| | - Ruth Steele
- Janssen Research and Development LLC , Welsh & McKean Roads , Spring House , Pennsylvania 19477 , United States
| | - Gaohua Liu
- Nexomics Biosciences, Inc. , 1200 Florence Columbus Road , Bordentown , New Jersey 08505 , United States
| | - Brett A Tounge
- Janssen Research and Development LLC , Welsh & McKean Roads , Spring House , Pennsylvania 19477 , United States
| | - Gaetano T Montelione
- Nexomics Biosciences, Inc. , 1200 Florence Columbus Road , Bordentown , New Jersey 08505 , United States
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5
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Čalyševa J, Vihinen M. PON-SC - program for identifying steric clashes caused by amino acid substitutions. BMC Bioinformatics 2017; 18:531. [PMID: 29187139 PMCID: PMC5707825 DOI: 10.1186/s12859-017-1947-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2017] [Accepted: 11/21/2017] [Indexed: 11/10/2022] Open
Abstract
Background Amino acid substitutions due to DNA nucleotide replacements are frequently disease-causing because of affecting functionally important sites. If the substituting amino acid does not fit into the protein, it causes structural alterations that are often harmful. Clashes of amino acids cause local or global structural changes. Testing structural compatibility of variations has been difficult due to the lack of a dedicated method that could handle vast amounts of variation data produced by next generation sequencing technologies. Results We developed a method, PON-SC, for detecting protein structural clashes due to amino acid substitutions. The method utilizes side chain rotamer library and tests whether any of the common rotamers can be fitted into the protein structure. The tool was tested both with variants that cause and do not cause clashes and found to have accuracy of 0.71 over five test datasets. Conclusions We developed a fast method for residue side chain clash detection. The method provides in addition to the prediction also visualization of the variant in three dimensional structure. Electronic supplementary material The online version of this article (10.1186/s12859-017-1947-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jelena Čalyševa
- Protein Structure and Bioinformatics, Department of Experimental Medical Science, Lund University, BMC B13, SE-22 184, Lund, Sweden.,Present address: EMBL Heidelberg, Meyerhofstraße 1, 69117, Heidelberg, Germany
| | - Mauno Vihinen
- Protein Structure and Bioinformatics, Department of Experimental Medical Science, Lund University, BMC B13, SE-22 184, Lund, Sweden.
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6
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Wei W, Monard G, Gauld J. Computational insights into substrate binding and catalytic mechanism of the glutaminase domain of glucosamine-6-phosphate synthase (GlmS). RSC Adv 2017. [DOI: 10.1039/c7ra04906d] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
The mechanistic cysteinyl of GlmS can activate its thiol using its own α-amine without the need for a bridging water.
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Affiliation(s)
- Wanlei Wei
- Department of Chemistry and Biochemistry
- University of Windsor
- Windsor
- Canada
| | - Gerald Monard
- Université de Lorraine
- UMR 7565 SRSMC
- F-54506 Vandoeuvre-les-Nancy
- France
| | - James W. Gauld
- Department of Chemistry and Biochemistry
- University of Windsor
- Windsor
- Canada
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7
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Basanta B, Chan KK, Barth P, King T, Sosnick TR, Hinshaw JR, Liu G, Everett JK, Xiao R, Montelione GT, Baker D. Introduction of a polar core into the de novo designed protein Top7. Protein Sci 2016; 25:1299-307. [PMID: 26873166 PMCID: PMC4918430 DOI: 10.1002/pro.2899] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2015] [Revised: 02/04/2016] [Accepted: 02/08/2016] [Indexed: 01/26/2023]
Abstract
Design of polar interactions is a current challenge for protein design. The de novo designed protein Top7, like almost all designed proteins, has an entirely nonpolar core. Here we describe the replacing of a sizable fraction (5 residues) of this core with a designed polar hydrogen bond network. The polar core design is expressed at high levels in E. coli, has a folding free energy of 10 kcal/mol, and retains the multiphasic folding kinetics of the original Top7. The NMR structure of the design shows that conformations of three of the five residues, and the designed hydrogen bonds between them, are very close to those in the design model. The remaining two residues, which are more solvent exposed, sample a wide range of conformations in the NMR ensemble. These results show that hydrogen bond networks can be designed in protein cores, but also highlight challenges that need to be overcome when there is competition with solvent.
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Affiliation(s)
- Benjamin Basanta
- Department of Biochemistry, University of Washington, Seattle, Washington, 98195
- Institute for Protein Design, University of Washington, Seattle, Washington, 98195
- Graduate Program in Biological Physics, Structure and Design, University of Washington, Seattle, Washington, 98195, USA
| | - Kui K Chan
- Enzyme Engineering, EnzymeWorks, California, 92121
| | - Patrick Barth
- Structural and Computational Biology and Molecular Biophysics Graduate Program, Baylor College of Medicine, Houston, Texas 77030
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas, 77030
- Department of Pharmacology Baylor College of Medicine, Houston, Texas, 77030
| | - Tiffany King
- Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois, 60637
| | - Tobin R Sosnick
- Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois, 60637
- Institute for Biophysical Dynamics, University of Chicago, Chicago, Illinois, 60637
| | - James R Hinshaw
- Department of Chemistry, University of Chicago, Chicago, Illinois, 60637
| | - Gaohua Liu
- Department of Molecular Biology and Biochemistry, Center of Advanced Biotechnology and Medicine, The State University of New Jersey, Piscataway, New Jersey, 08854
- Northeast Structural Genomics Consortium, Rutgers, The State University of New Jersey, Piscataway, New Jersey, 08854
| | - John K Everett
- Department of Molecular Biology and Biochemistry, Center of Advanced Biotechnology and Medicine, The State University of New Jersey, Piscataway, New Jersey, 08854
- Northeast Structural Genomics Consortium, Rutgers, The State University of New Jersey, Piscataway, New Jersey, 08854
| | - Rong Xiao
- Department of Molecular Biology and Biochemistry, Center of Advanced Biotechnology and Medicine, The State University of New Jersey, Piscataway, New Jersey, 08854
- Northeast Structural Genomics Consortium, Rutgers, The State University of New Jersey, Piscataway, New Jersey, 08854
| | - Gaetano T Montelione
- Department of Molecular Biology and Biochemistry, Center of Advanced Biotechnology and Medicine, The State University of New Jersey, Piscataway, New Jersey, 08854
- Northeast Structural Genomics Consortium, Rutgers, The State University of New Jersey, Piscataway, New Jersey, 08854
- Department of Biochemistry and Molecular Biology, Robert Wood Johnson Medical School, Rutgers, the State University of New Jersey, Piscataway, New Jersey, 08854
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle, Washington, 98195
- Institute for Protein Design, University of Washington, Seattle, Washington, 98195
- Howard Hughes Medical Institute, University of Washington, Seattle, Washington, 98195
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8
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Lukacik P, Lobley CMC, Bumann M, Arena de Souza V, Owens RJ, O’Toole PW, Walsh MA. High-resolution structures of Lactobacillus salivarius transketolase in the presence and absence of thiamine pyrophosphate. Acta Crystallogr F Struct Biol Commun 2015; 71:1327-34. [PMID: 26457526 PMCID: PMC4601599 DOI: 10.1107/s2053230x1501657x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2015] [Accepted: 09/04/2015] [Indexed: 11/12/2023] Open
Abstract
Probiotic bacterial strains have been shown to enhance the health of the host through a range of mechanisms including colonization, resistance against pathogens, secretion of antimicrobial compounds and modulation of the activity of the innate immune system. Lactobacillus salivarius UCC118 is a well characterized probiotic strain which survives intestinal transit and has many desirable host-interaction properties. Probiotic bacteria display a wide range of catabolic activities, which determine their competitiveness in vivo. Some lactobacilli are heterofermentative and can metabolize pentoses, using a pathway in which transketolase and transaldolase are key enzymes. L. salivarius UCC118 is capable of pentose utilization because it encodes the key enzymes on a megaplasmid. The crystal structures of the megaplasmid-encoded transketolase with and without the enzyme cofactor thiamine pyrophosphate have been determined. Comparisons with other known transketolase structures reveal a high degree of structural conservation in both the catalytic site and the overall conformation. This work extends structural knowledge of the transketolases to the industrially and commercially important Lactobacillus genus.
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Affiliation(s)
- Petra Lukacik
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, England
- Research Complex at Harwell, R92 Rutherford Appleton Laboratories, Harwell OX11 0FA, England
| | - Carina M. C. Lobley
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, England
| | - Mario Bumann
- MRC France, BM14, c/o ESRF, 6 Rue Jules Horowitz, BP 220, 38043 Grenoble, France
| | - Victoria Arena de Souza
- Oxford Protein Production Facility UK, Research Complex at Harwell, R92 Rutherford Appleton Laboratories, Harwell OX11 0FA, England
| | - Raymond J. Owens
- Oxford Protein Production Facility UK, Research Complex at Harwell, R92 Rutherford Appleton Laboratories, Harwell OX11 0FA, England
| | - Paul W. O’Toole
- MRC France, BM14, c/o ESRF, 6 Rue Jules Horowitz, BP 220, 38043 Grenoble, France
- Department of Microbiology, Alimentary Pharmabiotic Centre, University College Cork, Cork, Ireland
| | - Martin A. Walsh
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, England
- Research Complex at Harwell, R92 Rutherford Appleton Laboratories, Harwell OX11 0FA, England
- MRC France, BM14, c/o ESRF, 6 Rue Jules Horowitz, BP 220, 38043 Grenoble, France
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9
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Owen CD, Lukacik P, Potter JA, Sleator O, Taylor GL, Walsh MA. Streptococcus pneumoniae NanC: STRUCTURAL INSIGHTS INTO THE SPECIFICITY AND MECHANISM OF A SIALIDASE THAT PRODUCES A SIALIDASE INHIBITOR. J Biol Chem 2015; 290:27736-48. [PMID: 26370075 PMCID: PMC4646021 DOI: 10.1074/jbc.m115.673632] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2015] [Indexed: 12/26/2022] Open
Abstract
Streptococcus pneumoniae is an important human pathogen that causes a range of disease states. Sialidases are important bacterial virulence factors. There are three pneumococcal sialidases: NanA, NanB, and NanC. NanC is an unusual sialidase in that its primary reaction product is 2-deoxy-2,3-didehydro-N-acetylneuraminic acid (Neu5Ac2en, also known as DANA), a nonspecific hydrolytic sialidase inhibitor. The production of Neu5Ac2en from α2–3-linked sialosides by the catalytic domain is confirmed within a crystal structure. A covalent complex with 3-fluoro-β-N-acetylneuraminic acid is also presented, suggesting a common mechanism with other sialidases up to the final step of product formation. A conformation change in an active site hydrophobic loop on ligand binding constricts the entrance to the active site. In addition, the distance between the catalytic acid/base (Asp-315) and the ligand anomeric carbon is unusually short. These features facilitate a novel sialidase reaction in which the final step of product formation is direct abstraction of the C3 proton by the active site aspartic acid, forming Neu5Ac2en. NanC also possesses a carbohydrate-binding module, which is shown to bind α2–3- and α2–6-linked sialosides, as well as N-acetylneuraminic acid, which is captured in the crystal structure following hydration of Neu5Ac2en by NanC. Overall, the pneumococcal sialidases show remarkable mechanistic diversity while maintaining a common structural scaffold.
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Affiliation(s)
- C David Owen
- From the Biomedical Sciences Research Complex, University of St. Andrews, St. Andrews, Fife KY16 9ST, United Kingdom
| | - Petra Lukacik
- Diamond Light Source and Research Complex at Harwell, Harwell Science and Innovation Campus, Didcot, Oxfordshire OX11 0FA, United Kingdom, and
| | - Jane A Potter
- From the Biomedical Sciences Research Complex, University of St. Andrews, St. Andrews, Fife KY16 9ST, United Kingdom
| | - Olivia Sleator
- the Medical Research Council France, c/o European Synchrotron Radiation Facility, BP 220, 38043 Grenoble, France
| | - Garry L Taylor
- From the Biomedical Sciences Research Complex, University of St. Andrews, St. Andrews, Fife KY16 9ST, United Kingdom,
| | - Martin A Walsh
- Diamond Light Source and the Medical Research Council France, c/o European Synchrotron Radiation Facility, BP 220, 38043 Grenoble, France
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10
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Liu G, Poppe L, Aoki K, Yamane H, Lewis J, Szyperski T. High-quality NMR structure of human anti-apoptotic protein domain Mcl-1(171-327) for cancer drug design. PLoS One 2014; 9:e96521. [PMID: 24789074 PMCID: PMC4008586 DOI: 10.1371/journal.pone.0096521] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2013] [Accepted: 04/08/2014] [Indexed: 12/18/2022] Open
Abstract
A high-quality NMR solution structure is presented for protein hMcl-1(171–327) which comprises residues 171–327 of the human anti-apoptotic protein Mcl-1 (hMcl-1). Since this construct contains the three Bcl-2 homology (BH) sequence motifs which participate in forming a binding site for inhibitors of hMcl-1, it is deemed to be crucial for structure-based design of novel anti-cancer drugs blocking the Mcl1 related anti-apoptotic pathway. While the coordinates of an NMR solution structure for a corresponding construct of the mouse homologue (mMcl-1) are publicly available, our structure is the first atomic resolution structure reported for the ‘apo form’ of the human protein. Comparison of the two structures reveals that hMcl-1(171–327) exhibits a somewhat wider ligand/inhibitor binding groove as well as a different charge distribution within the BH3 binding groove. These findings strongly suggest that the availability of the human structure is of critical importance to support future design of cancer drugs.
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Affiliation(s)
- Gaohua Liu
- Department of Chemistry, State University of New York at Buffalo, Buffalo, New York, United States of America
| | - Leszek Poppe
- Molecular Structure, Amgen, Thousand Oaks, California, United States of America
| | - Ken Aoki
- Protein Science, Amgen, Thousand Oaks, California, United States of America
| | - Harvey Yamane
- Protein Science, Amgen, Thousand Oaks, California, United States of America
| | - Jeffrey Lewis
- Protein Science, Amgen, Thousand Oaks, California, United States of America
| | - Thomas Szyperski
- Department of Chemistry, State University of New York at Buffalo, Buffalo, New York, United States of America
- * E-mail:
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11
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Christensen T, Hassouneh W, Trabbic-Carlson K, Chilkoti A. Predicting transition temperatures of elastin-like polypeptide fusion proteins. Biomacromolecules 2013; 14:1514-9. [PMID: 23565607 DOI: 10.1021/bm400167h] [Citation(s) in RCA: 96] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Elastin-like polypeptides (ELPs) are thermally sensitive peptide polymers that undergo thermally triggered phase separation and this behavior is imparted to soluble proteins when they are fused to an ELP. The transition temperature of the ELP fusion protein is observed to be different than that of a free ELP, indicating that the surface properties of the fused protein modulate the thermal behavior of ELPs. Understanding this effect is important for the rational design of applications that exploit the phase transition behavior of ELP fusion proteins. We had previously developed a biophysical model that explained the effect of hydrophobic proteins on depressing the transition temperature of ELP fusion proteins relative to free ELP. Here, we extend the model to elucidate the effect of hydrophilic proteins on the thermal behavior of ELP fusion proteins. A linear correlation was found between overall residue composition of accessible protein surface weighted by a characteristic transition temperature for each residue and the difference in transition temperatures between the ELP protein fusion and the corresponding free ELP. In breaking down the contribution of residues to polar, nonpolar, and charged, the model revealed that charged residues are the most important parameter in altering the transition temperature of an ELP fusion relative to the free ELP.
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Affiliation(s)
- Trine Christensen
- Department of Biomedical Engineering, Campus Box 90281 and Center for Biologically Inspired Materials and Material Systems, Duke University, Durham, North Carolina 27708, United States
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12
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Principles for designing ideal protein structures. Nature 2013; 491:222-7. [PMID: 23135467 DOI: 10.1038/nature11600] [Citation(s) in RCA: 418] [Impact Index Per Article: 34.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2012] [Accepted: 09/19/2012] [Indexed: 02/03/2023]
Abstract
Unlike random heteropolymers, natural proteins fold into unique ordered structures. Understanding how these are encoded in amino-acid sequences is complicated by energetically unfavourable non-ideal features--for example kinked α-helices, bulged β-strands, strained loops and buried polar groups--that arise in proteins from evolutionary selection for biological function or from neutral drift. Here we describe an approach to designing ideal protein structures stabilized by completely consistent local and non-local interactions. The approach is based on a set of rules relating secondary structure patterns to protein tertiary motifs, which make possible the design of funnel-shaped protein folding energy landscapes leading into the target folded state. Guided by these rules, we designed sequences predicted to fold into ideal protein structures consisting of α-helices, β-strands and minimal loops. Designs for five different topologies were found to be monomeric and very stable and to adopt structures in solution nearly identical to the computational models. These results illuminate how the folding funnels of natural proteins arise and provide the foundation for engineering a new generation of functional proteins free from natural evolution.
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13
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Talavera D, Williams SG, Norris MG, Robertson DL, Lovell SC. Evolvability of Yeast Protein–Protein Interaction Interfaces. J Mol Biol 2012; 419:387-96. [DOI: 10.1016/j.jmb.2012.03.021] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2011] [Revised: 03/24/2012] [Accepted: 03/27/2012] [Indexed: 01/27/2023]
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14
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Headd JJ, Echols N, Afonine PV, Grosse-Kunstleve RW, Chen VB, Moriarty NW, Richardson DC, Richardson JS, Adams PD. Use of knowledge-based restraints in phenix.refine to improve macromolecular refinement at low resolution. ACTA CRYSTALLOGRAPHICA. SECTION D, BIOLOGICAL CRYSTALLOGRAPHY 2012; 68:381-90. [PMID: 22505258 PMCID: PMC3322597 DOI: 10.1107/s0907444911047834] [Citation(s) in RCA: 201] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2011] [Accepted: 11/10/2011] [Indexed: 11/10/2022]
Abstract
Traditional methods for macromolecular refinement often have limited success at low resolution (3.0-3.5 Å or worse), producing models that score poorly on crystallographic and geometric validation criteria. To improve low-resolution refinement, knowledge from macromolecular chemistry and homology was used to add three new coordinate-restraint functions to the refinement program phenix.refine. Firstly, a `reference-model' method uses an identical or homologous higher resolution model to add restraints on torsion angles to the geometric target function. Secondly, automatic restraints for common secondary-structure elements in proteins and nucleic acids were implemented that can help to preserve the secondary-structure geometry, which is often distorted at low resolution. Lastly, we have implemented Ramachandran-based restraints on the backbone torsion angles. In this method, a ϕ,ψ term is added to the geometric target function to minimize a modified Ramachandran landscape that smoothly combines favorable peaks identified from nonredundant high-quality data with unfavorable peaks calculated using a clash-based pseudo-energy function. All three methods show improved MolProbity validation statistics, typically complemented by a lowered R(free) and a decreased gap between R(work) and R(free).
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Affiliation(s)
- Jeffrey J Headd
- Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
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15
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Qiu JA, Wilson HL, Rajagopalan KV. Structure-based alteration of substrate specificity and catalytic activity of sulfite oxidase from sulfite oxidation to nitrate reduction. Biochemistry 2012; 51:1134-47. [PMID: 22263579 DOI: 10.1021/bi201206v] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Eukaryotic sulfite oxidase is a dimeric protein that contains the molybdenum cofactor and catalyzes the metabolically essential conversion of sulfite to sulfate as the terminal step in the metabolism of cysteine and methionine. Nitrate reductase is an evolutionarily related molybdoprotein in lower organisms that is essential for growth on nitrate. In this study, we describe human and chicken sulfite oxidase variants in which the active site has been modified to alter substrate specificity and activity from sulfite oxidation to nitrate reduction. On the basis of sequence alignments and the known crystal structure of chicken sulfite oxidase, two residues are conserved in nitrate reductases that align with residues in the active site of sulfite oxidase. On the basis of the crystal structure of yeast nitrate reductase, both positions were mutated in human sulfite oxidase and chicken sulfite oxidase. The resulting double-mutant variants demonstrated a marked decrease in sulfite oxidase activity but gained nitrate reductase activity. An additional methionine residue in the active site was proposed to be important in nitrate catalysis, and therefore, the triple variant was also produced. The nitrate reducing ability of the human sulfite oxidase triple mutant was nearly 3-fold greater than that of the double mutant. To obtain detailed structural data for the active site of these variants, we introduced the analogous mutations into chicken sulfite oxidase to perform crystallographic analysis. The crystal structures of the Mo domains of the double and triple mutants were determined to 2.4 and 2.1 Å resolution, respectively.
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Affiliation(s)
- James A Qiu
- Department of Biochemistry, Duke University Medical Center, Durham, North Carolina 27710, United States
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16
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Williams SG, Madan R, Norris MGS, Archer J, Mizuguchi K, Robertson DL, Lovell SC. Using knowledge of protein structural constraints to predict the evolution of HIV-1. J Mol Biol 2011; 410:1023-34. [PMID: 21763504 DOI: 10.1016/j.jmb.2011.04.037] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2011] [Revised: 04/12/2011] [Accepted: 04/13/2011] [Indexed: 10/18/2022]
Abstract
The high levels of sequence diversity and rapid rates of evolution of HIV-1 represent the main challenges for developing effective therapies. However, there are constraints imposed by the three-dimensional protein structure that affect the sequence space accessible to the evolution of HIV-1. Here, we present a strategy for predicting the set of possible amino acid replacements in HIV. Our approach is based on the identification of likely amino acid changes in the context of these structural constraints using environment-specific substitution matrices as well as considering the physical constraints imposed by local structure. Assessment of the power of various published algorithms in predicting the evolution of HIV-1 Gag P17 shows that it is possible to use these methods to make accurate predictions of the sequence diversity. Our own method, SubFit, uses knowledge of local structural constraints; it achieves similar prediction success with the best-performing methods. We also show that erroneous predictions are largely due to infrequently occurring amino acids that will probably have severe fitness costs for the protein. Future improvements; for example, incorporating covariation and immunological constraints will permit more reliable prediction of viral evolution.
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Affiliation(s)
- Simon G Williams
- Faculty of Life Sciences, University of Manchester, Oxford Road, Manchester M13 9PT, UK
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17
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Mani R, Vorobiev S, Swapna GVT, Neely H, Janjua H, Ciccosanti C, Xiao R, Acton TB, Everett JK, Hunt J, Montelione GT. Solution NMR and X-ray crystal structures of membrane-associated Lipoprotein-17 domain reveal a novel fold. JOURNAL OF STRUCTURAL AND FUNCTIONAL GENOMICS 2011; 12:27-32. [PMID: 21153711 PMCID: PMC3636556 DOI: 10.1007/s10969-010-9099-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/22/2010] [Accepted: 11/04/2010] [Indexed: 10/18/2022]
Abstract
The conserved Lipoprotein-17 domain of membrane-associated protein Q9PRA0_UREPA from Ureaplasma parvum was selected for structure determination by the Northeast Structural Genomics Consortium, as part of the Protein Structure Initiative's program on structure-function analysis of protein domains from large domain sequence families lacking structural representatives. The 100-residue Lipoprotein-17 domain is a "domain of unknown function" (DUF) that is a member of Pfam protein family PF04200, a large domain family for which no members have characterized biochemical functions. The three-dimensional structure of the Lipoprotein-17 domain of protein Q9PRA0_UREPA was determined by both solution NMR and by X-ray crystallography at 2.5 Å. The two structures are in good agreement with each other. The domain structure features three α-helices, α1 through α3, and five β-strands. Strands β1/β2, β3/β4, β4/β5 are anti-parallel to each other. Strands β1and β2 are orthogonal to strands β3, β4, β5, while helix α3 is formed between the strands β3 and β4. One-turn helix α2 is formed between the strands β1 and β2, while helix α1 occurs in the N-terminal polypeptide segment. Searches of the Protein Data Bank do not identify any other protein with significant structural similarity to Lipoprotein-17 domain of Q9PRA0_UREPA, indicating that it is a novel protein fold.
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Affiliation(s)
- Rajeswari Mani
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, and Northeast Structural Genomics Consortium (NESG), Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Sergey Vorobiev
- Department of Biological Sciences, Northeast Structural Genomics Consortium, Columbia University, New York, NY 10027, USA
| | - G. V. T. Swapna
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, and Northeast Structural Genomics Consortium (NESG), Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Helen Neely
- Department of Biological Sciences, Northeast Structural Genomics Consortium, Columbia University, New York, NY 10027, USA
| | - Haleema Janjua
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, and Northeast Structural Genomics Consortium (NESG), Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Colleen Ciccosanti
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, and Northeast Structural Genomics Consortium (NESG), Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Rong Xiao
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, and Northeast Structural Genomics Consortium (NESG), Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Thomas B. Acton
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, and Northeast Structural Genomics Consortium (NESG), Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - John K. Everett
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, and Northeast Structural Genomics Consortium (NESG), Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - John Hunt
- Department of Biological Sciences, Northeast Structural Genomics Consortium, Columbia University, New York, NY 10027, USA
| | - Gaetano T. Montelione
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, and Northeast Structural Genomics Consortium (NESG), Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Robert Wood Johnson Medical School, University of Medicine and Dentistry of New Jersey, Piscataway, NJ 08854, USA
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18
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Liu G, Huang YJ, Xiao R, Wang D, Acton TB, Montelione GT. Solution NMR structure of the ARID domain of human AT-rich interactive domain-containing protein 3A: a human cancer protein interaction network target. Proteins 2010; 78:2170-5. [PMID: 20455271 PMCID: PMC2869213 DOI: 10.1002/prot.22718] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
The AT-rich interactive domain (ARID) of human AT-rich interactive domain-containing protein 3A (ARID3A) has been selected for structural characterization by Northeast Structural Genomics Consortium (residues 218-351 NESG ID HR4394C) as part of our Human Cancer Protein Interaction Network (HCPIN) project. Protein ARID3A belongs to the ARID family DNA-binding protein and is known to play important roles in embryonic patterning, cell lineage gene regulation, and cell cycle control, chromatin remodeling and transcriptional regulations. The solution NMR structure of ARID3A ARID domain consists of eight α-helices α0-α7 and a short β hairpin. Helix α0 and α1 form a V shape, helix α2-α4 and helix α5-α7 form two U shapes, and the V and two U shapes packed orthogonal to each other. The NMR structure of the ARID domain of human ARID3A reported here provides a structural basis for elucidating the regulatory mechanisms of ARID3A function, and the molecular mechanism of ARID3A interactions with DNA. It also has potential value in future drug discovery and design.
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Affiliation(s)
- Gaohua Liu
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, and Northeast Structural Genomics Consortium (NESG), Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854
| | - Yuanpeng J. Huang
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, and Northeast Structural Genomics Consortium (NESG), Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854
| | - Rong Xiao
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, and Northeast Structural Genomics Consortium (NESG), Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854
| | - Dongyan Wang
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, and Northeast Structural Genomics Consortium (NESG), Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854
| | - Thomas B. Acton
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, and Northeast Structural Genomics Consortium (NESG), Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854
| | - Gaetano T. Montelione
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, and Northeast Structural Genomics Consortium (NESG), Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854
- Robert Wood Johnson Medical School, University of Medicine and Dentistry of New Jersey, Piscataway, New Jersey 08854
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19
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Weijers RN. Three-dimensional structure of beta-cell-specific zinc transporter, ZnT-8, predicted from the type 2 diabetes-associated gene variant SLC30A8 R325W. Diabetol Metab Syndr 2010; 2:33. [PMID: 20525392 PMCID: PMC2890542 DOI: 10.1186/1758-5996-2-33] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2010] [Accepted: 06/05/2010] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND We examined the effects of the R325W mutation on the three-dimensional (3D) structure of the beta-cell-specific Zn2+ (zinc) transporter ZnT-8. METHODS A model of the C-terminal domain of the human ZnT-8 protein was generated by homology modeling based on the known crystal structure of the Escherichia coli (E. coli) zinc transporter YiiP at 3.8 A resolution. RESULTS The homodimer ZnT-8 protein structure exists as a Y-shaped architecture with Arg325 located at the ultimate bottom of this motif at approximately 13.5 A from the transmembrane domain juncture. The C-terminal domain sequences of the human ZnT-8 protein and the E. coli zinc transporter YiiP share 12.3% identical and 39.5% homologous residues resulting in an overall homology of 51.8%. Validation statistics of the homology model showed a reasonable quality of the model. The C-terminal domain exhibited an alphabetabetaalphabeta fold with Arg325 as the penultimate N-terminal residue of the alpha2-helix. The side chains of both Arg325 and Trp325 point away from the interface with the other monomer, whereas the epsilon-NH3+ group of Arg325 is predicted to form an ionic interaction with the beta-COO- group of Asp326 as well as Asp295. An amino acid alignment of the beta2-alpha2 C-terminal loop domain revealed a variety of neutral amino acids at position 325 of different ZnT-8 proteins. CONCLUSIONS Our validated homology models predict that both Arg325 and Trp325, amino acids with a helix-forming behavior, and penultimate N-terminal residues in the alpha2-helix of the C-terminal domain, are shielded by the planar surface of the three cytoplasmic beta-strands and hence unable to affect the sensing capacity of the C-terminal domain. Moreover, the amino acid residue at position 325 is too far removed from the docking and transporter parts of ZnT-8 to affect their local protein conformations. These data indicate that the inherited R325W abnormality in SLC30A8 may be tolerated and results in adequate zinc transfer to the correct sites in the pancreatic islet cells and are consistent with the observation that the SLC30A8 gene variant R325W has a low predicted value for future type 2 diabetes at population-based level.
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Affiliation(s)
- Rob Nm Weijers
- Teaching Hospital OLVG, Onze Lieve Vrouwe Gasthuis, Amsterdam, The Netherlands.
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20
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Qiu JA, Wilson HL, Pushie MJ, Kisker C, George GN, Rajagopalan KV. The structures of the C185S and C185A mutants of sulfite oxidase reveal rearrangement of the active site. Biochemistry 2010; 49:3989-4000. [PMID: 20356030 DOI: 10.1021/bi1001954] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Sulfite oxidase (SO) catalyzes the physiologically critical conversion of sulfite to sulfate. Enzymatic activity is dependent on the presence of the metal molybdenum complexed with a pyranopterin-dithiolene cofactor termed molybdopterin. Comparison of the amino acid sequences of SOs from a variety of sources has identified a single conserved Cys residue essential for catalytic activity. The crystal structure of chicken liver sulfite oxidase indicated that this residue, Cys185 in chicken SO, coordinates the Mo atom in the active site. To improve our understanding of the role of this residue in the catalytic mechanism of sulfite oxidase, serine and alanine variants at position 185 of recombinant chicken SO were generated. Spectroscopic and kinetic studies indicate that neither variant is capable of sulfite oxidation. The crystal structure of the C185S variant was determined to 1.9 A resolution and to 2.4 A resolution in the presence of sulfite, and the C185A variant to 2.8 A resolution. The structures of the C185S and C185A variants revealed that neither the Ser or Ala side chains appeared to closely interact with the Mo atom and that a third oxo group replaced the usual cysteine sulfur ligand at the Mo center, confirming earlier extended X-ray absorption fine structure spectroscopy (EXAFS) work on the human C207S mutant. An unexpected result was that in the C185S variant, in the absence of sulfite, the active site residue Tyr322 became disordered as did the loop region flanking it. In the C185S variant crystallized in the presence of sulfite, the Tyr322 residue relocalized to the active site. The C185A variant structure also indicated the presence of a third oxygen ligand; however, Tyr322 remained in the active site. EXAFS studies of the Mo coordination environment indicate the Mo atom is in the oxidized Mo(VI) state in both the C185S and C185A variants of chicken SO and show the expected trioxodithiolene active site. Density functional theory calculations of the trioxo form of the cofactor reasonably reproducd the Mo horizontal lineO distances of the complex; however, the calculated Mo-S distances were slightly longer than either crystallographic or EXAFS measurements. Taken together, these results indicate that the active sites of the C185S and C185A variants are essentially catalytically inactive, the crystal structures of C185S and C185A variants contain a fully oxidized, trioxo form of the cofactor, and Tyr322 can undergo a conformational change that is relevant to the reaction mechanism. Additional DFT calculations demonstrated that such methods can reasonably reproduce the geometry and bond lengths of the active site.
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Affiliation(s)
- James A Qiu
- Department of Biochemistry, Duke University Medical Center, Durham, North Carolina 27710, USA
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21
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Liu G, Huang YJ, Xiao R, Wang D, Acton TB, Montelione GT. NMR structure of F-actin-binding domain of Arg/Abl2 from Homo sapiens. Proteins 2010; 78:1326-30. [PMID: 20077570 DOI: 10.1002/prot.22656] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Gaohua Liu
- Department of Molecular Biology and Biochemistry, Center for Advanced Biotechnology and Medicine, and Northeast Structural Genomics Consortium (NESG), Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854, USA.
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22
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Singarapu KK, Mills JL, Xiao R, Acton T, Punta M, Fischer M, Honig B, Rost B, Montelione GT, Szyperski T. Solution NMR structures of proteins VPA0419 from
Vibrio parahaemolyticus
and yiiS from
Shigella flexneri
provide structural coverage for protein domain family PFAM 04175. Proteins 2010; 78:779-84. [PMID: 19927321 PMCID: PMC2860719 DOI: 10.1002/prot.22630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Affiliation(s)
- Kiran Kumar Singarapu
- Department of Chemistry, State University of New York at Buffalo, Buffalo, New York 14260
- Northeast Structural Genomics Consortium
| | - Jeffrey L. Mills
- Department of Chemistry, State University of New York at Buffalo, Buffalo, New York 14260
- Northeast Structural Genomics Consortium
| | - Rong Xiao
- Northeast Structural Genomics Consortium
- Center of Advanced Biotechnology and Medicine, Rutgers University, Piscataway, New Jersey 08854
- Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, New Jersey 08854
| | - Thomas Acton
- Northeast Structural Genomics Consortium
- Center of Advanced Biotechnology and Medicine, Rutgers University, Piscataway, New Jersey 08854
- Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, New Jersey 08854
| | - Marco Punta
- Northeast Structural Genomics Consortium
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York 10032
- Computational Biology and Bioinformatics (C2B2), Columbia University, New York, New York 10032
| | - Markus Fischer
- Northeast Structural Genomics Consortium
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York 10032
| | - Barry Honig
- Northeast Structural Genomics Consortium
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York 10032
- Howard Hughes Medical Institute, Center for Computational Biology and Bioinformatics, Columbia University, New York, New York 10032
| | - Burkhard Rost
- Northeast Structural Genomics Consortium
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York 10032
- Computational Biology and Bioinformatics (C2B2), Columbia University, New York, New York 10032
| | - Gaetano T. Montelione
- Northeast Structural Genomics Consortium
- Center of Advanced Biotechnology and Medicine, Rutgers University, Piscataway, New Jersey 08854
- Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, New Jersey 08854
| | - Thomas Szyperski
- Department of Chemistry, State University of New York at Buffalo, Buffalo, New York 14260
- Northeast Structural Genomics Consortium
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23
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Chen VB, Davis IW, Richardson DC. KING (Kinemage, Next Generation): a versatile interactive molecular and scientific visualization program. Protein Sci 2010; 18:2403-9. [PMID: 19768809 DOI: 10.1002/pro.250] [Citation(s) in RCA: 123] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Proper visualization of scientific data is important for understanding spatial relationships. Particularly in the field of structural biology, where researchers seek to gain an understanding of the structure and function of biological macromolecules, it is important to have access to visualization programs which are fast, flexible, and customizable. We present KiNG, a Java program for visualizing scientific data, with a focus on macromolecular visualization. KiNG uses the kinemage graphics format, which is tuned for macromolecular structures, but is also ideal for many other kinds of spatially embedded information. KiNG is written in cross-platform, open-source Java code, and can be extended by end users through simple or elaborate "plug-in" modules. Here, we present three such applications of KiNG to problems in structural biology (protein backbone rebuilding), bioinformatics of high-dimensional data (e.g., protein sidechain chi angles), and classroom education (molecular illustration). KiNG is a mature platform for rapidly creating and capitalizing on scientific visualizations. As a research tool, it is invaluable as a test bed for new methods of visualizing scientific data and information. It is also a powerful presentation tool, whether for structure browsing, teaching, direct 3D display on the web, or as a method for creating pictures and videos for publications. KiNG is freely available for download at http://kinemage.biochem.duke.edu.
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Affiliation(s)
- Vincent B Chen
- Biochemistry Department, Duke University Medical Center, Durham, NC 27710, USA
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24
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Eletsky A, Sukumaran DK, Xiao R, Acton T, Rost B, Montelione GT, Szyperski T. NMR structure of protein YvyC from Bacillus subtilis reveals unexpected structural similarity between two PFAM families. Proteins 2009; 76:1037-41. [PMID: 19455708 PMCID: PMC2735722 DOI: 10.1002/prot.22459] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Alexander Eletsky
- Department of Chemistry, State University of New York at Buffalo, Buffalo, New York 14260
- Northeast Structural Genomics Consortium
| | - Dinesh K. Sukumaran
- Department of Chemistry, State University of New York at Buffalo, Buffalo, New York 14260
- Northeast Structural Genomics Consortium
| | - Rong Xiao
- Center of Advanced Biotechnology and Medicine and Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, New Jersey 08854
- Northeast Structural Genomics Consortium
| | - Tom Acton
- Center of Advanced Biotechnology and Medicine and Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, New Jersey 08854
- Northeast Structural Genomics Consortium
| | - Burkhard Rost
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York 10032
- Northeast Structural Genomics Consortium
| | - Gaetano T. Montelione
- Center of Advanced Biotechnology and Medicine and Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, New Jersey 08854
- Northeast Structural Genomics Consortium
| | - Thomas Szyperski
- Department of Chemistry, State University of New York at Buffalo, Buffalo, New York 14260
- Northeast Structural Genomics Consortium
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25
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Thusberg J, Vihinen M. Pathogenic or not? And if so, then how? Studying the effects of missense mutations using bioinformatics methods. Hum Mutat 2009; 30:703-14. [PMID: 19267389 DOI: 10.1002/humu.20938] [Citation(s) in RCA: 180] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Many gene defects are relatively easy to identify experimentally, but obtaining information about the effects of sequence variations and elucidation of the detailed molecular mechanisms of genetic diseases will be among the next major efforts in mutation research. Amino acid substitutions may have diverse effects on protein structure and function; thus, a detailed analysis of the mutations is essential. Experimental study of the molecular effects of mutations is laborious, whereas useful and reliable information about the effects of amino acid substitutions can readily be obtained by theoretical methods. Experimentally defined structures and molecular modeling can be used as a basis for interpretation of the mutations. The effects of missense mutations can be analyzed even when the 3D structure of the protein has not been determined, although structure-based analyses are more reliable. Structural analyses include studies of the contacts between residues, their implication for the stability of the protein, and the effects of the introduced residues. Investigations of steric and stereochemical consequences of substitutions provide insights on the molecular fit of the introduced residue. Mutations that change the electrostatic surface potential of a protein have wide-ranging effects. Analyses of the effects of mutations on interactions with ligands and partners have been performed for elucidation of functional mutations. We have employed numerous methods for predicting the effects of amino acid substitutions. We discuss the applicability of these methods in the analysis of genes, proteins, and diseases to reveal protein structure-function relationships, which is essential to gain insights into disease genotype-phenotype correlations.
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Affiliation(s)
- Janita Thusberg
- Institute of Medical Technology, FI-33014 University of Tampere, Finland
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26
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Liu G, Forouhar F, Eletsky A, Atreya HS, Aramini JM, Xiao R, Huang YJ, Abashidze M, Seetharaman J, Liu J, Rost B, Acton T, Montelione GT, Hunt JF, Szyperski T. NMR and X-RAY structures of human E2-like ubiquitin-fold modifier conjugating enzyme 1 (UFC1) reveal structural and functional conservation in the metazoan UFM1-UBA5-UFC1 ubiquination pathway. JOURNAL OF STRUCTURAL AND FUNCTIONAL GENOMICS 2009; 10:127-36. [PMID: 19101823 PMCID: PMC2850604 DOI: 10.1007/s10969-008-9054-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 04/22/2008] [Accepted: 11/28/2008] [Indexed: 11/25/2022]
Abstract
For cell regulation, E2-like ubiquitin-fold modifier conjugating enzyme 1 (Ufc1) is involved in the transfer of ubiquitin-fold modifier 1 (Ufm1), a ubiquitin like protein which is activated by E1-like enzyme Uba5, to various target proteins. Thereby, Ufc1 participates in the very recently discovered Ufm1-Uba5-Ufc1 ubiquination pathway which is found in metazoan organisms. The structure of human Ufc1 was solved by using both NMR spectroscopy and X-ray crystallography. The complementary insights obtained with the two techniques provided a unique basis for understanding the function of Ufc1 at atomic resolution. The Ufc1 structure consists of the catalytic core domain conserved in all E2-like enzymes and an additional N-terminal helix. The active site Cys(116), which forms a thio-ester bond with Ufm1, is located in a flexible loop that is highly solvent accessible. Based on the Ufc1 and Ufm1 NMR structures, a model could be derived for the Ufc1-Ufm1 complex in which the C-terminal Gly(83) of Ufm1 may well form the expected thio-ester with Cys(116), suggesting that Ufm1-Ufc1 functions as described for other E1-E2-E3 machineries. alpha-helix 1 of Ufc1 adopts different conformations in the crystal and in solution, suggesting that this helix plays a key role to mediate specificity.
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Affiliation(s)
- Gaohua Liu
- Department of Chemistry, Northeast Structural Genomics Consortium, The State University of New York at Buffalo, Buffalo, NY 14260, USA
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27
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Parish D, Benach J, Liu G, Singarapu KK, Xiao R, Acton T, Su M, Bansal S, Prestegard JH, Hunt J, Montelione GT, Szyperski T. Protein chaperones Q8ZP25_SALTY from Salmonella typhimurium and HYAE_ECOLI from Escherichia coli exhibit thioredoxin-like structures despite lack of canonical thioredoxin active site sequence motif. JOURNAL OF STRUCTURAL AND FUNCTIONAL GENOMICS 2008; 9:41-9. [PMID: 19039680 PMCID: PMC2850599 DOI: 10.1007/s10969-008-9050-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/25/2008] [Accepted: 11/10/2008] [Indexed: 10/21/2022]
Abstract
The structure of the 142-residue protein Q8ZP25_SALTY encoded in the genome of Salmonella typhimurium LT2 was determined independently by NMR and X-ray crystallography, and the structure of the 140-residue protein HYAE_ECOLI encoded in the genome of Escherichia coli was determined by NMR. The two proteins belong to Pfam (Finn et al. 34:D247-D251, 2006) PF07449, which currently comprises 50 members, and belongs itself to the 'thioredoxin-like clan'. However, protein HYAE_ECOLI and the other proteins of Pfam PF07449 do not contain the canonical Cys-X-X-Cys active site sequence motif of thioredoxin. Protein HYAE_ECOLI was previously classified as a [NiFe] hydrogenase-1 specific chaperone interacting with the twin-arginine translocation (Tat) signal peptide. The structures presented here exhibit the expected thioredoxin-like fold and support the view that members of Pfam family PF07449 specifically interact with Tat signal peptides.
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Affiliation(s)
- David Parish
- David Parish · Gaohua Liu · Kiran Kumar Singarapu · Thomas Szyperski, Department of Chemistry, Northeast Structural Genomics Consortium, The State University of New York at Buffalo, Buffalo, NY 14260,
- Jordi Benach · Min Su · John F. Hunt, Department of Biological Sciences, Northeast Structural Genomics Consortium, Columbia University, New York, NY 10027
- Rong Xiao · Thomas Acton · Gaetano T. Montelione, The Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, Northeast Structural Genomics Consortium, Rutgers University and Robert Wood Johnson Medical School, Piscataway, NJ 08854
- Sonal Bansal · James H. Prestegard, Complex Carbohydrate Research Center and Department of Chemistry, University of Georgia, Athens, Georgia, 30602-4712
| | - Jordi Benach
- David Parish · Gaohua Liu · Kiran Kumar Singarapu · Thomas Szyperski, Department of Chemistry, Northeast Structural Genomics Consortium, The State University of New York at Buffalo, Buffalo, NY 14260,
- Jordi Benach · Min Su · John F. Hunt, Department of Biological Sciences, Northeast Structural Genomics Consortium, Columbia University, New York, NY 10027
- Rong Xiao · Thomas Acton · Gaetano T. Montelione, The Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, Northeast Structural Genomics Consortium, Rutgers University and Robert Wood Johnson Medical School, Piscataway, NJ 08854
- Sonal Bansal · James H. Prestegard, Complex Carbohydrate Research Center and Department of Chemistry, University of Georgia, Athens, Georgia, 30602-4712
| | - Goahua Liu
- David Parish · Gaohua Liu · Kiran Kumar Singarapu · Thomas Szyperski, Department of Chemistry, Northeast Structural Genomics Consortium, The State University of New York at Buffalo, Buffalo, NY 14260,
- Jordi Benach · Min Su · John F. Hunt, Department of Biological Sciences, Northeast Structural Genomics Consortium, Columbia University, New York, NY 10027
- Rong Xiao · Thomas Acton · Gaetano T. Montelione, The Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, Northeast Structural Genomics Consortium, Rutgers University and Robert Wood Johnson Medical School, Piscataway, NJ 08854
- Sonal Bansal · James H. Prestegard, Complex Carbohydrate Research Center and Department of Chemistry, University of Georgia, Athens, Georgia, 30602-4712
| | - Kiran Kumar Singarapu
- David Parish · Gaohua Liu · Kiran Kumar Singarapu · Thomas Szyperski, Department of Chemistry, Northeast Structural Genomics Consortium, The State University of New York at Buffalo, Buffalo, NY 14260,
- Jordi Benach · Min Su · John F. Hunt, Department of Biological Sciences, Northeast Structural Genomics Consortium, Columbia University, New York, NY 10027
- Rong Xiao · Thomas Acton · Gaetano T. Montelione, The Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, Northeast Structural Genomics Consortium, Rutgers University and Robert Wood Johnson Medical School, Piscataway, NJ 08854
- Sonal Bansal · James H. Prestegard, Complex Carbohydrate Research Center and Department of Chemistry, University of Georgia, Athens, Georgia, 30602-4712
| | - Rong Xiao
- David Parish · Gaohua Liu · Kiran Kumar Singarapu · Thomas Szyperski, Department of Chemistry, Northeast Structural Genomics Consortium, The State University of New York at Buffalo, Buffalo, NY 14260,
- Jordi Benach · Min Su · John F. Hunt, Department of Biological Sciences, Northeast Structural Genomics Consortium, Columbia University, New York, NY 10027
- Rong Xiao · Thomas Acton · Gaetano T. Montelione, The Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, Northeast Structural Genomics Consortium, Rutgers University and Robert Wood Johnson Medical School, Piscataway, NJ 08854
- Sonal Bansal · James H. Prestegard, Complex Carbohydrate Research Center and Department of Chemistry, University of Georgia, Athens, Georgia, 30602-4712
| | - Thomas Acton
- David Parish · Gaohua Liu · Kiran Kumar Singarapu · Thomas Szyperski, Department of Chemistry, Northeast Structural Genomics Consortium, The State University of New York at Buffalo, Buffalo, NY 14260,
- Jordi Benach · Min Su · John F. Hunt, Department of Biological Sciences, Northeast Structural Genomics Consortium, Columbia University, New York, NY 10027
- Rong Xiao · Thomas Acton · Gaetano T. Montelione, The Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, Northeast Structural Genomics Consortium, Rutgers University and Robert Wood Johnson Medical School, Piscataway, NJ 08854
- Sonal Bansal · James H. Prestegard, Complex Carbohydrate Research Center and Department of Chemistry, University of Georgia, Athens, Georgia, 30602-4712
| | - Min Su
- David Parish · Gaohua Liu · Kiran Kumar Singarapu · Thomas Szyperski, Department of Chemistry, Northeast Structural Genomics Consortium, The State University of New York at Buffalo, Buffalo, NY 14260,
- Jordi Benach · Min Su · John F. Hunt, Department of Biological Sciences, Northeast Structural Genomics Consortium, Columbia University, New York, NY 10027
- Rong Xiao · Thomas Acton · Gaetano T. Montelione, The Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, Northeast Structural Genomics Consortium, Rutgers University and Robert Wood Johnson Medical School, Piscataway, NJ 08854
- Sonal Bansal · James H. Prestegard, Complex Carbohydrate Research Center and Department of Chemistry, University of Georgia, Athens, Georgia, 30602-4712
| | - Sonal Bansal
- David Parish · Gaohua Liu · Kiran Kumar Singarapu · Thomas Szyperski, Department of Chemistry, Northeast Structural Genomics Consortium, The State University of New York at Buffalo, Buffalo, NY 14260,
- Jordi Benach · Min Su · John F. Hunt, Department of Biological Sciences, Northeast Structural Genomics Consortium, Columbia University, New York, NY 10027
- Rong Xiao · Thomas Acton · Gaetano T. Montelione, The Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, Northeast Structural Genomics Consortium, Rutgers University and Robert Wood Johnson Medical School, Piscataway, NJ 08854
- Sonal Bansal · James H. Prestegard, Complex Carbohydrate Research Center and Department of Chemistry, University of Georgia, Athens, Georgia, 30602-4712
| | - James H. Prestegard
- David Parish · Gaohua Liu · Kiran Kumar Singarapu · Thomas Szyperski, Department of Chemistry, Northeast Structural Genomics Consortium, The State University of New York at Buffalo, Buffalo, NY 14260,
- Jordi Benach · Min Su · John F. Hunt, Department of Biological Sciences, Northeast Structural Genomics Consortium, Columbia University, New York, NY 10027
- Rong Xiao · Thomas Acton · Gaetano T. Montelione, The Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, Northeast Structural Genomics Consortium, Rutgers University and Robert Wood Johnson Medical School, Piscataway, NJ 08854
- Sonal Bansal · James H. Prestegard, Complex Carbohydrate Research Center and Department of Chemistry, University of Georgia, Athens, Georgia, 30602-4712
| | - John Hunt
- David Parish · Gaohua Liu · Kiran Kumar Singarapu · Thomas Szyperski, Department of Chemistry, Northeast Structural Genomics Consortium, The State University of New York at Buffalo, Buffalo, NY 14260,
- Jordi Benach · Min Su · John F. Hunt, Department of Biological Sciences, Northeast Structural Genomics Consortium, Columbia University, New York, NY 10027
- Rong Xiao · Thomas Acton · Gaetano T. Montelione, The Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, Northeast Structural Genomics Consortium, Rutgers University and Robert Wood Johnson Medical School, Piscataway, NJ 08854
- Sonal Bansal · James H. Prestegard, Complex Carbohydrate Research Center and Department of Chemistry, University of Georgia, Athens, Georgia, 30602-4712
| | - Gaetano T. Montelione
- David Parish · Gaohua Liu · Kiran Kumar Singarapu · Thomas Szyperski, Department of Chemistry, Northeast Structural Genomics Consortium, The State University of New York at Buffalo, Buffalo, NY 14260,
- Jordi Benach · Min Su · John F. Hunt, Department of Biological Sciences, Northeast Structural Genomics Consortium, Columbia University, New York, NY 10027
- Rong Xiao · Thomas Acton · Gaetano T. Montelione, The Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, Northeast Structural Genomics Consortium, Rutgers University and Robert Wood Johnson Medical School, Piscataway, NJ 08854
- Sonal Bansal · James H. Prestegard, Complex Carbohydrate Research Center and Department of Chemistry, University of Georgia, Athens, Georgia, 30602-4712
| | - Thomas Szyperski
- David Parish · Gaohua Liu · Kiran Kumar Singarapu · Thomas Szyperski, Department of Chemistry, Northeast Structural Genomics Consortium, The State University of New York at Buffalo, Buffalo, NY 14260,
- Jordi Benach · Min Su · John F. Hunt, Department of Biological Sciences, Northeast Structural Genomics Consortium, Columbia University, New York, NY 10027
- Rong Xiao · Thomas Acton · Gaetano T. Montelione, The Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, Northeast Structural Genomics Consortium, Rutgers University and Robert Wood Johnson Medical School, Piscataway, NJ 08854
- Sonal Bansal · James H. Prestegard, Complex Carbohydrate Research Center and Department of Chemistry, University of Georgia, Athens, Georgia, 30602-4712
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Lappalainen I, Thusberg J, Shen B, Vihinen M. Genome wide analysis of pathogenic SH2 domain mutations. Proteins 2008; 72:779-92. [PMID: 18260110 DOI: 10.1002/prot.21970] [Citation(s) in RCA: 45] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
The authors have made a genome-wide analysis of mutations in Src homology 2 (SH2) domains associated with human disease. Disease-causing mutations have been detected in the SH2 domains of cytoplasmic signaling proteins Bruton tyrosine kinase (BTK), SH2D1A, Ras GTPase activating protein (RasGAP), ZAP-70, SHP-2, STAT1, STAT5B, and the p85alpha subunit of the PIP3. Mutations in the BTK, SH2D1A, ZAP70, STAT1, and STAT5B genes have been shown to cause diverse immunodeficiencies, whereas the mutations in RASA1 and PIK3R1 genes lead to basal carcinoma and diabetes, respectively. PTPN11 mutations cause Noonan sydrome and different types of cancer, depending mainly on whether the mutation is inherited or sporadic. We collected and analyzed all known pathogenic mutations affecting human SH2 domains by bioinformatics methods. Among the investigated protein properties are sequence conservation and covariance, structural stability, side chain rotamers, packing effects, surface electrostatics, hydrogen bond formation, accessible surface area, salt bridges, and residue contacts. The majority of the mutations affect positions essential for phosphotyrosine ligand binding and specificity. The structural basis of the SH2 domain diseases was elucidated based on the bioinformatic analysis.
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Affiliation(s)
- Ilkka Lappalainen
- Department of Biological and Environmental Sciences, Division of Biochemistry, FI-00014 University of Helsinki, Finland
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29
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Cui F, Jernigan R, Wu Z. Knowledge-based versus experimentally acquired distance and angle constraints for NMR structure refinement. J Bioinform Comput Biol 2008; 6:283-300. [PMID: 18464323 DOI: 10.1142/s0219720008003448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2007] [Revised: 10/30/2007] [Accepted: 11/17/2007] [Indexed: 11/18/2022]
Abstract
Nuclear Overhauser effects (NOE) distance constraints and torsion angle constraints are major conformational constraints for nuclear magnetic resonance (NMR) structure refinement. In particular, the number of NOE constraints has been considered as an important determinant for the quality of NMR structures. Of course, the availability of torsion angle constraints is also critical for the formation of correct local conformations. In our recent work, we have shown how a set of knowledge-based short-range distance constraints can also be utilized for NMR structure refinement, as a complementary set of conformational constraints to the NOE and torsion angle constraints. In this paper, we show the results from a series of structure refinement experiments by using different types of conformational constraints--NOE, torsion angle, or knowledge-based constraints--or their combinations, and make a quantitative assessment on how the experimentally acquired constraints contribute to the quality of structural models and whether or not they can be combined with or substituted by the knowledge-based constraints. We have carried out the experiments on a small set of NMR structures. Our preliminary calculations have revealed that the torsion angle constraints contribute substantially to the quality of the structures, but require to be combined with the NOE constraints to be fully effective. The knowledge-based constraints can be functionally as crucial as the torsion angle constraints, although they are statistical constraints after all and are not meant to be able to replace the latter.
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Affiliation(s)
- Feng Cui
- Laboratory of Cell Biology, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
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30
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Singarapu KK, Xiao R, Acton T, Rost B, Montelione GT, Szyperski T. NMR structure of the peptidyl-tRNA hydrolase domain from Pseudomonas syringae expands the structural coverage of the hydrolysis domains of class 1 peptide chain release factors. Proteins 2008; 71:1027-31. [PMID: 18247350 DOI: 10.1002/prot.21947] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Kiran Kumar Singarapu
- Department of Chemistry, State University of New York at Buffalo, Buffalo, New York 14260-3000, USA
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31
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Consistent blind protein structure generation from NMR chemical shift data. Proc Natl Acad Sci U S A 2008; 105:4685-90. [PMID: 18326625 DOI: 10.1073/pnas.0800256105] [Citation(s) in RCA: 669] [Impact Index Per Article: 39.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Protein NMR chemical shifts are highly sensitive to local structure. A robust protocol is described that exploits this relation for de novo protein structure generation, using as input experimental parameters the (13)C(alpha), (13)C(beta), (13)C', (15)N, (1)H(alpha) and (1)H(N) NMR chemical shifts. These shifts are generally available at the early stage of the traditional NMR structure determination process, before the collection and analysis of structural restraints. The chemical shift based structure determination protocol uses an empirically optimized procedure to select protein fragments from the Protein Data Bank, in conjunction with the standard ROSETTA Monte Carlo assembly and relaxation methods. Evaluation of 16 proteins, varying in size from 56 to 129 residues, yielded full-atom models that have 0.7-1.8 A root mean square deviations for the backbone atoms relative to the experimentally determined x-ray or NMR structures. The strategy also has been successfully applied in a blind manner to nine protein targets with molecular masses up to 15.4 kDa, whose conventional NMR structure determination was conducted in parallel by the Northeast Structural Genomics Consortium. This protocol potentially provides a new direction for high-throughput NMR structure determination.
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32
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Singarapu KK, Xiao R, Sukumaran DK, Acton T, Montelione GT, Szyperski T. NMR structure of protein Cgl2762 from Corynebacterium glutamicum implicated in DNA transposition reveals a helix-turn-helix motif attached to a flexibly disordered leucine zipper. Proteins 2008; 70:1650-4. [PMID: 18175328 DOI: 10.1002/prot.21840] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Kiran Kumar Singarapu
- Department of Chemistry, State University of New York at Buffalo, Buffalo, New York 14260-3000, USA
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33
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Bhattacharya A, Wunderlich Z, Monleon D, Tejero R, Montelione GT. Assessing model accuracy using the homology modeling automatically software. Proteins 2007; 70:105-18. [PMID: 17640066 DOI: 10.1002/prot.21466] [Citation(s) in RCA: 33] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Homology modeling is a powerful technique that greatly increases the value of experimental structure determination by using the structural information of one protein to predict the structures of homologous proteins. We have previously described a method of homology modeling by satisfaction of spatial restraints (Li et al., Protein Sci 1997;6:956-970). The Homology Modeling Automatically (HOMA) web site, <http://www-nmr.cabm.rutgers.edu/HOMA>, is a new tool, using this method to predict 3D structure of a target protein based on the sequence alignment of the target protein to a template protein and the structure coordinates of the template. The user is presented with the resulting models, together with an extensive structure validation report providing critical assessments of the quality of the resulting homology models. The homology modeling method employed by HOMA was assessed and validated using twenty-four groups of homologous proteins. Using HOMA, homology models were generated for 510 proteins, including 264 proteins modeled with correct folds and 246 modeled with incorrect folds. Accuracies of these models were assessed by superimposition on the corresponding experimentally determined structures. A subset of these results was compared with parallel studies of modeling accuracy using several other automated homology modeling approaches. Overall, HOMA provides prediction accuracies similar to other state-of-the-art homology modeling methods. We also provide an evaluation of several structure quality validation tools in assessing the accuracy of homology models generated with HOMA. This study demonstrates that Verify3D (Luthy et al., Nature 1992;356:83-85) and ProsaII (Sippl, Proteins 1993;17:355-362) are most sensitive in distinguishing between homology models with correct or incorrect folds. For homology models that have the correct fold, the steric conformational energy (including primarily the Van der Waals energy), MolProbity clashscore (Word et al., Protein Sci 2000;9:2251-2259), and the PROCHECK G-factors (Laskowski et al., J Biomol NMR 1996;8:477-486) provide sensitive and consistent methods for assessing accuracy and can distinguish between homology models of higher and lower accuracy. As demonstrated in the accompanying paper (Bhattacharya et al., accompanying paper), combinations of these scores for models generated with HOMA provide a basis for distinguishing low from high accuracy models.
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Affiliation(s)
- Aneerban Bhattacharya
- Center for Advanced Biotechnology and Medicine (CABM), Rutgers University and Robert Wood Johnson Medical School (UMDNJ), Piscataway, New Jersey 08854, USA
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34
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Singarapu KK, Liu G, Xiao R, Bertonati C, Honig B, Montelione GT, Szyperski T. NMR structure of protein yjbR from Escherichia coli reveals 'double-wing' DNA binding motif. Proteins 2007; 67:501-4. [PMID: 17266124 DOI: 10.1002/prot.21297] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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35
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Bhattacharya A, Tejero R, Montelione GT. Evaluating protein structures determined by structural genomics consortia. Proteins 2007; 66:778-95. [PMID: 17186527 DOI: 10.1002/prot.21165] [Citation(s) in RCA: 603] [Impact Index Per Article: 33.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Structural genomics projects are providing large quantities of new 3D structural data for proteins. To monitor the quality of these data, we have developed the protein structure validation software suite (PSVS), for assessment of protein structures generated by NMR or X-ray crystallographic methods. PSVS is broadly applicable for structure quality assessment in structural biology projects. The software integrates under a single interface analyses from several widely-used structure quality evaluation tools, including PROCHECK (Laskowski et al., J Appl Crystallog 1993;26:283-291), MolProbity (Lovell et al., Proteins 2003;50:437-450), Verify3D (Luthy et al., Nature 1992;356:83-85), ProsaII (Sippl, Proteins 1993;17: 355-362), the PDB validation software, and various structure-validation tools developed in our own laboratory. PSVS provides standard constraint analyses, statistics on goodness-of-fit between structures and experimental data, and knowledge-based structure quality scores in standardized format suitable for database integration. The analysis provides both global and site-specific measures of protein structure quality. Global quality measures are reported as Z scores, based on calibration with a set of high-resolution X-ray crystal structures. PSVS is particularly useful in assessing protein structures determined by NMR methods, but is also valuable for assessing X-ray crystal structures or homology models. Using these tools, we assessed protein structures generated by the Northeast Structural Genomics Consortium and other international structural genomics projects, over a 5-year period. Protein structures produced from structural genomics projects exhibit quality score distributions similar to those of structures produced in traditional structural biology projects during the same time period. However, while some NMR structures have structure quality scores similar to those seen in higher-resolution X-ray crystal structures, the majority of NMR structures have lower scores. Potential reasons for this "structure quality score gap" between NMR and X-ray crystal structures are discussed.
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Affiliation(s)
- Aneerban Bhattacharya
- Center for Advanced Biotechnology and Medicine, Northeast Structural Genomics Consortium, Rutgers University and Robert Wood Johnson Medical School, Piscataway, New Jersey 08854, USA
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36
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Thusberg J, Vihinen M. The structural basis of hyper IgM deficiency – CD40L mutations. Protein Eng Des Sel 2007; 20:133-41. [PMID: 17307885 DOI: 10.1093/protein/gzm004] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
X-linked hyper-IgM syndrome (XHIGM) is a primary immunodeficiency characterised by an inability to produce immunoglobulins of the IgG, IgA and IgE isotypes. It is caused by mutations of CD40 ligand (CD40L, CD154), expressed on T-lymphocytes. The interaction of CD40L on T-cells and its receptor CD40 on B-cells is essential for lymphocyte signalling leading to immunoglobulin class switching and B-cell maturation. To understand the structural basis for XHIGM, we utilised bioinformatics methods to analyse all the known CD40L missense mutations at both the sequence and structural level. Our results demonstrate that the 35 different missense mutations have diverse effects on CD40L structure and function, affecting structural disorder and aggregation tendencies, stability maintaining contacts and electrostatic properties. Several mutations also affect residues essential in receptor binding and trimerisation. Experimental study of effects of mutations is laborious and time-consuming and at the structural level often almost impossible. By contrast, precise and useful information about effects of mutations on protein structure and function can readily be obtained by theoretical methods. In this study, all the XHIGM causing missense mutations could be explained in terms of CD40L structure and function. Thus, the molecular basis of the syndrome could be elucidated.
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Affiliation(s)
- J Thusberg
- Institute of Medical Technology, FI-33014, University of Tampere, Finland
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37
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Lin YC, Liu G, Shen Y, Bertonati C, Yee A, Honig B, Arrowsmith CH, Szyperski T. NMR structure of protein PA2021 from Pseudomonas aeruginosa. Proteins 2007; 65:767-70. [PMID: 16927296 DOI: 10.1002/prot.21098] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Yu-Chieh Lin
- Department of Chemistry, University at Buffalo, The State University of New York, Buffalo, New York 14260, USA
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38
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Thusberg J, Vihinen M. Bioinformatic analysis of protein structure-function relationships: case study of leukocyte elastase (ELA2) missense mutations. Hum Mutat 2006; 27:1230-43. [PMID: 16986121 DOI: 10.1002/humu.20407] [Citation(s) in RCA: 43] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Cyclic and congenital neutropenia are caused by mutations in the human neutrophil elastase (HNE) gene (ELA2), leading to an immunodeficiency characterized by decreased or oscillating levels of neutrophils in the blood. The HNE mutations presumably cause loss of enzyme activity, consequently leading to compromised immune system function. To understand the structural basis for the disease, we implemented methods from bioinformatics to analyze all the known HNE missense mutations at both the sequence and structural level. Our results demonstrate that the 32 different mutations have diverse effects on HNE structure and function, affecting structural disorder and aggregation tendencies, stability maintaining contacts, and electrostatic properties. A large proportion of the mutations are located at conserved amino acids, which are usually essential in determining protein structure and function. The majority of the disease-causing HNE missense mutations lead to major structural changes and loss of stability in the protein. A few mutations also affect functional residues, leading into decreased catalytic activity or altered ligand binding. Our analysis reveals the putative effects of all known missense mutations in HNE, thus allowing the structural basis of cyclic and congenital neutropenia to be elucidated. We have employed and analyzed a set of some 30 different methods for predicting the effects of amino acid substitutions. We present results and experience from the analysis of the applicability of these methods in the analysis of numerous genes, proteins, and diseases to reveal protein structure-function relationships and disease genotype-phenotype correlations.
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Affiliation(s)
- Janita Thusberg
- Institute of Medical Technology, University of Tampere, Finland
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39
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Kapustina M, Carter CW. Computational studies of tryptophanyl-tRNA synthetase: activation of ATP by induced-fit. J Mol Biol 2006; 362:1159-80. [PMID: 16949606 DOI: 10.1016/j.jmb.2006.06.078] [Citation(s) in RCA: 46] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2005] [Revised: 05/24/2006] [Accepted: 06/30/2006] [Indexed: 11/21/2022]
Abstract
Catalysis of amino acid activation by Bacillus stearothermophilus tryptophanyl-tRNA synthetase involves three allosteric states: (1) Open; (2) closed pre-transition state (PreTS); and (3) closed products (Product). The interconversions of these states entail significant domain motions driven by ligand binding. We explore the application of molecular dynamics simulations to investigate ligand-linked conformational stability changes associated with this catalytic cycle. Multiple molecular dynamics trajectories (5 ns) for 11 distinct liganded and unliganded monomer configurations show that the PreTS conformation is unstable in the absence of ATP, reverting within approximately 600 ps nearly to the Open conformation. In contrast, Open and Product state trajectories were stable, even without ligands, confirming the previous suggestion that catalysis entails destabilization of the protein conformation, driven by ATP-binding energies developed as the PreTS state assembles during induced-fit. The simulations suggest novel mechanistic details associated with both induced-fit (Open-PreTS) and catalysis (PreTS-Product). Notably, Mg2+ -ATP interactions are coupled to interactions between ATP and active-site lysine side-chains via mechanisms that cannot be captured under the molecular mechanics approximations, and which therefore require restraining potentials for stable simulation. Simulations of Mg2+. ATP-bound PreTS complexes with restraining potentials and with a virtual K111A mutant confirm that these coupling interactions are necessary to sustain the PreTS conformation and, in turn, provide a new model for how the PreTS conformation activates ATP for catalysis. These results emphasize the central role of the PreTS state as a high-energy intermediate structure along the catalytic pathway and suggest that Mg2+ and the KMSKS loop function cooperatively during catalysis.
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Affiliation(s)
- Maryna Kapustina
- Department of Biochemistry and Biophysics, CB 7260, University of North Carolina, Chapel Hill, NC 27599-7260, USA
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40
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Davis IW, Arendall WB, Richardson DC, Richardson JS. The backrub motion: how protein backbone shrugs when a sidechain dances. Structure 2006; 14:265-74. [PMID: 16472746 DOI: 10.1016/j.str.2005.10.007] [Citation(s) in RCA: 202] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2005] [Revised: 10/10/2005] [Accepted: 10/12/2005] [Indexed: 11/16/2022]
Abstract
Surprisingly, the frozen structures from ultra-high-resolution protein crystallography reveal a prevalent, but subtle, mode of local backbone motion coupled to much larger, two-state changes of sidechain conformation. This "backrub" motion provides an influential and common type of local plasticity in protein backbone. Concerted reorientation of two adjacent peptides swings the central sidechain perpendicular to the chain direction, changing accessible sidechain conformations while leaving flanking structure undisturbed. Alternate conformations in sub-1 angstroms crystal structures show backrub motions for two-thirds of the significant Cbeta shifts and 3% of the total residues in these proteins (126/3882), accompanied by two-state changes in sidechain rotamer. The Backrub modeling tool is effective in crystallographic rebuilding. For homology modeling or protein redesign, backrubs can provide realistic, small perturbations to rigid backbones. For large sidechain changes in protein dynamics or for single mutations, backrubs allow backbone accommodation while maintaining H bonds and ideal geometry.
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Affiliation(s)
- Ian W Davis
- Department of Biochemistry, Duke University, Durham, North Carolina 27710, USA
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41
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Arendall WB, Tempel W, Richardson JS, Zhou W, Wang S, Davis IW, Liu ZJ, Rose JP, Carson WM, Luo M, Richardson DC, Wang BC. A test of enhancing model accuracy in high-throughput crystallography. ACTA ACUST UNITED AC 2006; 6:1-11. [PMID: 15965733 DOI: 10.1007/s10969-005-3138-4] [Citation(s) in RCA: 42] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2005] [Accepted: 02/10/2005] [Indexed: 11/30/2022]
Abstract
The high throughput of structure determination pipelines relies on increased automation and, consequently, a reduction of time spent on interactive quality control. In order to meet and exceed current standards in model accuracy, new approaches are needed for the facile identification and correction of model errors during refinement. One such approach is provided by the validation and structure-improvement tools of the MOL: PROBITY: web service. To test their effectiveness in high-throughput mode, a large subset of the crystal structures from the SouthEast Collaboratory for Structural Genomics (SECSG) has used protocols based on the MOL: PROBITY: tools. Comparison of 29 working-set and 19 control-set SECSG structures shows that working-set outlier scores for updated Ramachandran-plot, sidechain rotamer, and all-atom steric criteria have been improved by factors of 5- to 10-fold (relative to the control set or to a Protein Data Bank sample), while quality of covalent geometry, R(work), R(free), electron density and difference density are maintained or improved. Some parts of this correction process are already fully automated; other parts involve manual rebuilding of conformations flagged by the tests as trapped in the wrong local minimum, often altering features of functional significance. The ease and effectiveness of this technique shows that macromolecular crystal structures from either traditional or high-throughput determinations can feasibly reach a new level of excellence in conformational accuracy and reliability.
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Affiliation(s)
- W Bryan Arendall
- Department of Biochemistry, Duke University Medical Center, Durham, NC 27710-3711, USA
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42
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Liu G, Shen Y, Xiao R, Acton T, Ma LC, Joachimiak A, Montelione GT, Szyperski T. NMR structure of protein yqbG from Bacillus subtilis reveals a novel α-helical protein fold. Proteins 2005; 62:288-91. [PMID: 16281282 DOI: 10.1002/prot.20666] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Gaohua Liu
- Department of Chemistry, University at Buffalo, The State University of New York, Buffalo, New York 14260, USA
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43
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Liu G, Shen Y, Atreya HS, Parish D, Shao Y, Sukumaran DK, Xiao R, Yee A, Lemak A, Bhattacharya A, Acton TA, Arrowsmith CH, Montelione GT, Szyperski T. NMR data collection and analysis protocol for high-throughput protein structure determination. Proc Natl Acad Sci U S A 2005; 102:10487-92. [PMID: 16027363 PMCID: PMC1180791 DOI: 10.1073/pnas.0504338102] [Citation(s) in RCA: 89] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2004] [Indexed: 11/18/2022] Open
Abstract
A standardized protocol enabling rapid NMR data collection for high-quality protein structure determination is presented that allows one to capitalize on high spectrometer sensitivity: a set of five G-matrix Fourier transform NMR experiments for resonance assignment based on highly resolved 4D and 5D spectral information is acquired in conjunction with a single simultaneous 3D 15N,13C(aliphatic),13C(aromatic)-resolved [1H,1H]-NOESY spectrum providing 1H-1H upper distance limit constraints. The protocol was integrated with methodology for semiautomated data analysis and used to solve eight NMR protein structures of the Northeast Structural Genomics Consortium pipeline. The molecular masses of the hypothetical target proteins ranged from 9 to 20 kDa with an average of approximately 14 kDa. Between 1 and 9 days of instrument time were invested per structure, which is less than approximately 10-25% of the measurement time routinely required to date with conventional approaches. The protocol presented here effectively removes data collection as a bottleneck for high-throughput solution structure determination of proteins up to at least approximately 20 kDa, while concurrently providing spectra that are highly amenable to fast and robust analysis.
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Affiliation(s)
- Gaohua Liu
- Department of Chemistry, University at Buffalo, State University of New York, Buffalo, NY 14260, USA
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44
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Snyder DA, Bhattacharya A, Huang YJ, Montelione GT. Assessing precision and accuracy of protein structures derived from NMR data. Proteins 2005; 59:655-61. [PMID: 15822105 DOI: 10.1002/prot.20499] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Huang YJ, Moseley HNB, Baran MC, Arrowsmith C, Powers R, Tejero R, Szyperski T, Montelione GT. An integrated platform for automated analysis of protein NMR structures. Methods Enzymol 2005; 394:111-41. [PMID: 15808219 DOI: 10.1016/s0076-6879(05)94005-6] [Citation(s) in RCA: 55] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Recent developments provide automated analysis of NMR assignments and three-dimensional (3D) structures of proteins. These approaches are generally applicable to proteins ranging from about 50 to 150 amino acids. In this chapter, we summarize progress by the Northeast Structural Genomics Consortium in standardizing the NMR data collection process for protein structure determination and in building an integrated platform for automated protein NMR structure analysis. Our integrated platform includes the following principal steps: (1) standardized NMR data collection, (2) standardized data processing (including spectral referencing and Fourier transformation), (3) automated peak picking and peak list editing, (4) automated analysis of resonance assignments, (5) automated analysis of NOESY data together with 3D structure determination, and (6) methods for protein structure validation. In particular, the software AutoStructure for automated NOESY data analysis is described in this chapter, together with a discussion of practical considerations for its use in high-throughput structure production efforts. The critical area of data quality assessment has evolved significantly over the past few years and involves evaluation of both intermediate and final peak lists, resonance assignments, and structural information derived from the NMR data. Methods for quality control of each of the major automated analysis steps in our platform are also discussed. Despite significant remaining challenges, when good quality data are available, automated analysis of protein NMR assignments and structures with this platform is both fast and reliable.
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Affiliation(s)
- Yuanpeng Janet Huang
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, New Jersey 08854, USA
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46
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Baran MC, Huang YJ, Moseley HNB, Montelione GT. Automated analysis of protein NMR assignments and structures. Chem Rev 2004; 104:3541-56. [PMID: 15303826 DOI: 10.1021/cr030408p] [Citation(s) in RCA: 74] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Michael C Baran
- Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry, and Northeast Structural Genomics Consortium, Rutgers University, 679 Hoes Lane, Piscataway, NJ 08854, USA
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47
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Persaud-Sawin DA, McNamara JO, Rylova S, Vandongen A, Boustany RMN. A galactosylceramide binding domain is involved in trafficking of CLN3 from Golgi to rafts via recycling endosomes. Pediatr Res 2004; 56:449-63. [PMID: 15240864 DOI: 10.1203/01.pdr.0000136152.54638.95] [Citation(s) in RCA: 56] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Juvenile neuronal ceroid lipofuscinosis (JNCL) is due to mutations in the CLN3 gene. We previously determined that CLN3 protein harbors a highly conserved motif, VYFAE, necessary for its impact on cell growth and apoptosis. Using molecular modeling we demonstrated that this motif is embedded in a stretch of amino acids that is homologous to and structurally compatible with a galactosylceramide (GalCer) binding domain. This domain is present in the V3 loop of the HIV-1 gp120 envelope protein, beta-amyloid protein, and the infectious form of prionic protein, and defines a binding site for lipid rafts. We determined the subcellular localization of CLN3 in different cell systems including human neurons, primary rat hippocampal neurons, normal human fibroblasts, and JNCL fibroblasts homozygous for the 1.02 kb deletion in genomic DNA. Wild-type CLN3 protein was present within Golgi, lipid rafts in the plasma membrane, and early recycling endosomes, but not late endosomes/lysosomes. Wild-type CLN3 internalized from the plasma membrane to the Golgi via Rab4- and Rab11-positive recycling endosomes. Wild-type CLN3 co-localized with GalCer in the Golgi and in lipid rafts at the plasma membrane in normal cells. Neither mutant CLN3 protein nor GalCer were found at the plasma membrane in JNCL fibroblasts. Mutant CLN3p was retained within the Golgi and partially mis-localized to lysosomes, failing to reach recycling endosomes, plasma membrane, or lipid rafts. These studies identify a novel CLN3 domain that may dictate localization and function of CLN3.
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48
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Wales TE, Richardson JS, Fitzgerald MC. Facile chemical synthesis and equilibrium unfolding properties of CopG. Protein Sci 2004; 13:1918-26. [PMID: 15169951 PMCID: PMC2279938 DOI: 10.1110/ps.04671804] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
The 45-amino acid polypeptide chain of the homodimeric transcriptional repressor, CopG, was chemically synthesized by stepwise solid phase peptide synthesis (SPPS) using a protocol based on Boc-chemistry. The product obtained from the synthesis was readily purified by reversed-phase HPLC to give a good overall yield (21% by weight). Moreover, the synthetic CopG constructs prepared in this work folded into three-dimensional structures similar to the wild-type protein prepared using conventional recombinant methods as judged by far UV-CD spectroscopy. A fluorescent CopG analog, (Y39W)CopG, was also designed and chemically synthesized to facilitate biophysical studies of CopG's protein folding and assembly reaction. The guanidinium chloride-induced equilibrium unfolding properties of the wild-type CopG and (Y39W)CopG constructs in this work were characterized and used to develop a model for CopG's equilibrium unfolding reaction. Our results indicate that CopG's folding and assembly reaction is well modeled by a two-state process involving folded dimer and unfolded monomer. Using this model, DeltaG(f) and m-values of -13.42 +/- 0.04 kcal/mole dimer and 1.92 +/- 0.01 kcal/(mole M) were calculated for CopG.
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Affiliation(s)
- Thomas E Wales
- Department of Chemistry, Box 90346, Duke University, Durham, NC 27708-0346, USA
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49
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Richardson JS, Bryan WA, Richardson DC. New tools and data for improving structures, using all-atom contacts. Methods Enzymol 2004; 374:385-412. [PMID: 14696383 DOI: 10.1016/s0076-6879(03)74018-x] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Affiliation(s)
- Jane S Richardson
- Department of Biochemistry, Duke University, Duke Building, Durham, North Carolina 27708, USA
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50
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Abstract
Despite the importance of local structural detail to a mechanistic understanding of RNA catalysis and binding functions, RNA backbone conformation has been quite recalcitrant to analysis. There are too many variable torsion angles per residue, and their raw empirical distributions are poorly clustered. This study applies quality-filtering techniques (using resolution, crystallographic B factor, and all-atom steric clashes) to the backbone torsion angle distributions from an 8,636-residue RNA database. With noise levels greatly reduced, clear signal appears for the underlying angle preferences. Half-residue torsion angle distributions for alpha-beta-gamma and for delta-epsilon-zeta are plotted and contoured in 3D; each shows about a dozen distinct peaks, which can then be combined in pairs to define complete RNA backbone conformers. Traditional nucleic acid residues are defined from phosphate to phosphate, but here we use a base-to-base (or sugar-to-sugar) division into "suites" to parse the RNA backbone repeats, both because most backbone steric clashes are within suites and because the relationship of successive bases is both reliably determined and conformationally important. A suite conformer has seven variables, with sugar pucker specified at both ends. Potential suite conformers were omitted if not represented by at least a small cluster of convincing data points after application of quality filters. The final result is a small library of 42 RNA backbone conformers, which should provide valid conformations for nearly all RNA backbone encountered in experimental structures.
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Affiliation(s)
- Laura J W Murray
- Department of Biochemistry, Duke University, Durham, NC 27710-3711, USA
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