Mutation induced structural variation in membrane proteins

[1]  Yinan Wei,et al.  Expression, purification and characterization of the Escherichia coli integral membrane protein YajC. , 2011, Protein and peptide letters.

[2]  Sebastian Kelm,et al.  MEDELLER: homology-based coordinate generation for membrane proteins , 2010, Bioinform..

[3]  Yaoqi Zhou,et al.  Structure-based prediction of DNA-binding proteins by structural alignment and a volume-fraction corrected DFIRE-based energy function , 2010, Bioinform..

[4]  Jianwen Fang,et al.  Distance-dependent statistical potentials for discriminating thermophilic and mesophilic proteins. , 2010, Biochemical and biophysical research communications.

[5]  Yang Zhang,et al.  HAAD: A Quick Algorithm for Accurate Prediction of Hydrogen Atoms in Protein Structures , 2009, PloS one.

[6]  Yang Zhang,et al.  REMO: A new protocol to refine full atomic protein models from C‐alpha traces by optimizing hydrogen‐bonding networks , 2009, Proteins.

[7]  Gang Chen,et al.  Robust prediction of mutation-induced protein stability change by property encoding of amino acids. , 2008, Protein engineering, design & selection : PEDS.

[8]  Liliana Wroblewska,et al.  Protein model refinement using an optimized physics-based all-atom force field , 2008, Proceedings of the National Academy of Sciences.

[9]  Liliana Wroblewska,et al.  Development of a physics-based force field for the scoring and refinement of protein models. , 2008, Biophysical journal.

[10]  Krzysztof Palczewski,et al.  Vertebrate Membrane Proteins: Structure, Function, and Insights from Biophysical Approaches , 2008, Pharmacological Reviews.

[11]  A. Paiardini,et al.  Mutational analysis and homology modelling of SyrC, the aminoacyltransferase in the biosynthesis of syringomycin. , 2007, Biochemical and biophysical research communications.

[12]  Cen Gao,et al.  Scoring function accuracy for membrane protein structure prediction , 2007, Proteins.

[13]  Dominik Gront,et al.  BMC Structural Biology BioMed Central , 2007 .

[14]  Michael Levitt,et al.  Near-native structure refinement using in vacuo energy minimization , 2007, Proceedings of the National Academy of Sciences.

[15]  Dietmar Schomburg,et al.  Structural analysis and prediction of protein mutant stability using distance and torsion potentials: Role of secondary structure and solvent accessibility , 2006, Proteins.

[16]  Marc N. Offman,et al.  Developing a move-set for protein model refinement , 2006, Bioinform..

[17]  Mike Tyers,et al.  Evolutionary and Physiological Importance of Hub Proteins , 2006, PLoS Comput. Biol..

[18]  J. Skolnick,et al.  Structure Modeling of All Identified G Protein–Coupled Receptors in the Human Genome , 2006, PLoS Comput. Biol..

[19]  Barry Honig,et al.  An assessment of the accuracy of methods for predicting hydrogen positions in protein structures , 2005, Proteins.

[20]  G Klebe,et al.  Cooperative effects in hydrogen‐bonding of protein secondary structure elements: A systematic analysis of crystal data using Secbase , 2005, Proteins.

[21]  O. Schueler‐Furman,et al.  Progress in Modeling of Protein Structures and Interactions , 2005, Science.

[22]  Dietmar Schomburg,et al.  Prediction of protein thermostability with a direction‐ and distance‐dependent knowledge‐based potential , 2005, Protein science : a publication of the Protein Society.

[23]  A. Watts.  Solid-state NMR in drug design and discovery for membrane-embedded targets , 2005, Nature Reviews Drug Discovery.

[24]  Léo Degrève,et al.  LMProt: an efficient algorithm for Monte Carlo sampling of protein conformational space. , 2004, Biophysical journal.

[25]  Yu-Dong Cai,et al.  Prediction of Saccharomyces cerevisiae protein functional class from functional domain composition , 2004, Bioinform..

[26]  Mark Gerstein,et al.  Computational analysis of membrane proteins: genomic occurrence, structure prediction and helix interactions , 2004, Quarterly Reviews of Biophysics.

[27]  Song Liu,et al.  Accurate and efficient loop selections by the DFIRE‐based all‐atom statistical potential , 2004, Protein science : a publication of the Protein Society.

[28]  Hao Fan,et al.  Refinement of homology‐based protein structures by molecular dynamics simulation techniques , 2004, Protein science : a publication of the Protein Society.

[29]  Hui Lu,et al.  Application of statistical potentials to protein structure refinement from low resolution ab initio models , 2003, Biopolymers.

[30]  Thomas B Woolf,et al.  Discrimination of native loop conformations in membrane proteins: Decoy library design and evaluation of effective energy scoring functions , 2003, Proteins.

[31]  Kuo-Chen Chou,et al.  Nearest neighbour algorithm for predicting protein subcellular location by combining functional domain composition and pseudo-amino acid composition. , 2003, Biochemical and biophysical research communications.

[32]  Hongyi Zhou,et al.  Distance‐scaled, finite ideal‐gas reference state improves structure‐derived potentials of mean force for structure selection and stability prediction , 2002, Protein science : a publication of the Protein Society.

[33]  Raphael Guerois,et al.  Energy estimation in protein design. , 2002, Current opinion in structural biology.

[34]  J. Skolnick,et al.  Local energy landscape flattening: Parallel hyperbolic Monte Carlo sampling of protein folding , 2002, Proteins.

[35]  Velin Z. Spassov,et al.  Introducing an Implicit Membrane in Generalized Born/Solvent Accessibility Continuum Solvent Models , 2002 .

[36]  L. Serrano,et al.  Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations. , 2002, Journal of molecular biology.

[37]  P. Kollman,et al.  Exhaustive mutagenesis in silico: Multicoordinate free energy calculations on proteins and peptides , 2000, Proteins.

[38]  Y. Sugita,et al.  Replica-exchange molecular dynamics method for protein folding , 1999 .

[39]  D. Baker,et al.  Clustering of low-energy conformations near the native structures of small proteins. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[40]  Alexander D. MacKerell,et al.  All-atom empirical potential for molecular modeling and dynamics studies of proteins. , 1998, The journal of physical chemistry. B.

[41]  R. Samudrala,et al.  An all-atom distance-dependent conditional probability discriminatory function for protein structure prediction. , 1998, Journal of molecular biology.

[42]  W. L. Jorgensen,et al.  Development and Testing of the OPLS All-Atom Force Field on Conformational Energetics and Properties of Organic Liquids , 1996 .

[43]  S J Wodak,et al.  Contribution of the hydrophobic effect to protein stability: analysis based on simulations of the Ile-96----Ala mutation in barnase. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[44]  E. Myers,et al.  Basic local alignment search tool. , 1990, Journal of molecular biology.

[45]  W. Kabsch,et al.  Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features , 1983, Biopolymers.

[46]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[47]  Michael S Lee,et al.  Assessment of Detection and Refinement Strategies for de novo Protein Structures Using Force Field and Statistical Potentials. , 2007, Journal of chemical theory and computation.