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Ruben Abagyan Research Group Molecular Biology, TSRI 10550 North Torrey Pines Rd., TPC-28 La Jolla, CA 92037 |
T A S 2 0 1 2 2.1 2.1.1 2.1.2 2.1.3 2.2 2.2.1 2.2.2 3 3.1 3.1.1 3.1.2 3.1.3 3.1.4 3.1.5 3.1.6 3.1.7 3.1.8 3.1.9 3.1.10 3.1.11 3.1.12 3.2 3.2.1 3.2.2 3.3 3.3.1 3.3.2 3.3.3 3.4 3.4.1 3.4.2 3.4.3 3.4.4 3.4.5 3.4.6 3.4.7 3.4.8 3.4.9 4 4.1 4.2 4.3 4.4 4.5 4.6 4.7 5B S 2 Filenames main cv ruben ruben.htm#ge ruben.htm#pt ruben.htm#pr Brian Brianabs BrianPersonal research molmod energystrain3d crystalstruct1.8a mmdsb homomodelwicm mappingcd59 pewithmonoTIM rearpd hmbyicm monoTIMloops mti montecarlo monoTim8loop bioinform alignseq energcalc drgdsgn pldock tem1bl lacomp manda cd59 globularproteins countourbuild biasedmontecarlo ICMmethod icmparalel pf psc confsearch projects Abinit invprtfold mbh docking PD mopdr Cadprotmod jobC S 2 Anchors D S 2 Titles Welcome People Ruben Abagyan Graduate Education Postdoctoral Training Prior Responsibilities Brian Mardsen Brian's Abstracts Personal Info Research Molecular Modeling Energy strain Crystal structure Molecular Modeling of CED-4 Homology Modeling with ICM Mapping of CD59. CD59 Modeling seven residue loop) Large-scale Protein Domain Rearrangements ICM homology modeling Crystal structures.of monoTIM# monomeric triosephosphate isomerase% Monte Carlo for peptides and proteins eight-residue loop MonoTim Bioinformatics Aligned sequences Distantly Related Proteins Drug Design and Docking Protein Ligand Docking Beta-Lactamase binding Prediction of lysozome-antibody Methods and algorithms CD59 selective activity Globular Proteins Countour-buildup algorithm# Monte Carlo conformational searches ICM Method Parallelization for ICM Protein Folding Protein side chains Conformational Searches Projects Peptide folding Protein folding Modeling by Homology Docking Protein Design Domain Rearrangements! Protein comparison by CAD measure JobsE I 2 F S 2 Big Titles0 Welcome to the Ruben Abagyan Laboratory Homepage People Ruben Abagyan Graduate Education Postdoctoral Training Prior Responsibilities Brian Mardsen Brian's Abstracts Personal Info Research Molecular Modeling5 Energy strain in three-dimensional protein structures The 1.8 A crystal structure of the dimeric peroxisomal 3-ketoacyl-CoA thiolase of Saccharomyces cerevisiae: implications for substrate binding and reaction mechanism. Molecular Modeling of the Domain Shared Between CED-4 and its Mammalian Homologue Apaf-1: A Structural Relationship to the G-proteins. Homology Modeling with Internal Coordinate Mechanics: Deformation Zone Mapping and Improvements of Models via Conformational Search. Mapping the active site of CD59 Protein engineering with monomeric triosephosphate isomerase (monoTIM): the modelling and structure verification of a seven residue loop.G A new method for modeling large-scale rearrangements of protein domains# Homology modeling by the ICM method{ Three new crystal structures of point mutation variants of monoTIM: conformational flexibility of loop-1, loop-4 and loop-8W Design, creation, and characterization of a stable, monomeric triosephosphate isomeraseo Biased probability Monte Carlo conformational searches and electrostatic calculations for peptides and proteins The crystal structure of an engineered monomeric triosephosphate isomerase, monoTIM: the correct modelling of an eight-residue loop Bioinformatics) Do aligned sequences share the same fold?E Recognition of distantly related proteins through energy calculations Drug design and flexible dockingU Flexible protien-ligand docking by global energy optimization in internal coordinatesz Molecular docking programs successfully predict the binding of a beta-lactamase inhibitory protein to TEM-1 beta-lactamaseN Detailed ab initio prediction of lysozyme-antibody complex with 1.6 A accuracy Methods and algorithms_ Identification of the individual residues that determine human CD59 species selective activity. The hydration of globular proteins as derived from volume and compressibility measurements: cross correlating thermodynamic and structural dataK The contour-buildup algorithm to calculate the analytical molecular surfaceo Biased probability Monte Carlo conformational searches and electrostatic calculations for peptides and proteins ICM - a new method for protein modelling and design. Applications to docking and structure prediction from the distorted native conformationn Efficient parallelization of the energy, surface and derivative calculations for internal coordinate mechanics5 Towards protein folding by global energy optimizationY A method to configure protein side-chains from the main-chain trace in homology modellinga Optimal protocol and trajectory visualization for conformational searches of peptides and protein Projects7 Ab initio peptide folding by global energy optimization8 Combined Approach to the Inverse Protein Folding Problem Modeling by Homology Docking Protein Design) Modeling of protein domain rearrangementsD Structure analysis: CAD Measure for the comparison of protein models JobsG S 2 Args T A S : Aligned sequences Beta-Lactamase binding Bioinformatics Brian Mardsen Brian Personal Brian's Abstracts CD59 selective activity Claudio Cavasotto Conformational Searches Countour-buildup algorithm Crystal structure Crystal structures.of monoTIM CV list Distantly Related Proteins Docking Domain Rearrangements Drug Design and Docking Drug Design and Flexible Docking eight-residue loop MonoTim Energy strain Globular Proteins Graduate Education Homology Homology modeling Homology Modeling with ICM ICM homology modeling ICM Method Jobs Juan Fernandez-Cecio) Large-scale Protein Domain Rearrangements loop Mapping of CD59. CD59 Methods and Algorithms Modeling by Homology Modeling seven residue loop Molecular Modeling Molecular Modeling of CED-4# monomeric triosephosphate isomerase# Monte Carlo conformational searches% Monte Carlo for peptides and proteins Parallelization for ICM people Peptide folding Posdoc Postdoctoral Positions Postdoctoral Training Prediction of lysozome-antibody Prior Responsibilities Projects! Protein comparison by CAD measure Protein Design Protein Folding Protein folding Protein Ligand Docking Protein side chains Ruben Abagyan staff WelcomeB S : 3.2.1 3.3.2= 3, 3.23 2, 2.2% 2.2.2 2.2.1 3.4.1 2" 3.4.9% 3.4.3) 3.1.2$ 3.1.9 2! 3.2.2 4.4 4.6 3.3 3% 3.1.12& 3.1.1( 3.4.2 2.1 4.3 3.1% 3.1.4 3.1.8! 3.4.5 5 2 3.1.7$ 3.1.9# 3.1.59 3, 3.4 4.3% 3.1.6: 3, 3.1 3.1.3 3.1.10( 3.4.4# 3.1.11" 3.4.6 2 4.1 5 5 2.1 3.3.3 2.1 4 4.7 4.5 3.4.7 4.2 3.3.1 3.4.8 2.1 2 1C S : 3.2.1 3.3.2 3 2 2.2.2 2.2.1 3.4.1 2 3.4.9 3.4.3 3.1.2 3.1.9 2 3.2.2 4.4 4.6 3.3 3 3.1.12 3.1.1 3.4.2 2.1 4.3 3.1 3.1.4 3.1.8 3.4.5 5 2 3.1.7 3.1.9 3.1.5 3 4.3 3.1.6 3 3.1.3 3.1.10 3.4.4 3.1.11 3.4.6 2 4.1 5 5 2.1 3.3.3 2.1 4 4.7 4.5 3.4.7 4.2 3.3.1 3.4.8 2.1 2 1D S : ALIGNED SEQUENCES BETA-LACTAMASE BINDING BIOINFORMATICS BRIAN MARDSEN BRIAN PERSONAL BRIAN'S ABSTRACTS CD59 SELECTIVE ACTIVITY CLAUDIO CAVASOTTO CONFORMATIONAL SEARCHES COUNTOUR-BUILDUP ALGORITHM CRYSTAL STRUCTURE CRYSTAL STRUCTURES.OF MONOTIM CV LIST DISTANTLY RELATED PROTEINS DOCKING DOMAIN REARRANGEMENTS DRUG DESIGN AND DOCKING DRUG DESIGN AND FLEXIBLE DOCKING EIGHT-RESIDUE LOOP MONOTIM ENERGY STRAIN GLOBULAR PROTEINS GRADUATE EDUCATION HOMOLOGY HOMOLOGY MODELING HOMOLOGY MODELING WITH ICM ICM HOMOLOGY MODELING ICM METHOD JOBS JUAN FERNANDEZ-CECIO) LARGE-SCALE PROTEIN DOMAIN REARRANGEMENTS LOOP MAPPING OF CD59. CD59 METHODS AND ALGORITHMS MODELING BY HOMOLOGY MODELING SEVEN RESIDUE LOOP MOLECULAR MODELING MOLECULAR MODELING OF CED-4# MONOMERIC TRIOSEPHOSPHATE ISOMERASE# MONTE CARLO CONFORMATIONAL SEARCHES% MONTE CARLO FOR PEPTIDES AND PROTEINS PARALLELIZATION FOR ICM PEOPLE PEPTIDE FOLDING POSDOC POSTDOCTORAL POSITIONS POSTDOCTORAL TRAINING PREDICTION OF LYSOZOME-ANTIBODY PRIOR RESPONSIBILITIES PROJECTS! PROTEIN COMPARISON BY CAD MEASURE PROTEIN DESIGN PROTEIN FOLDING PROTEIN FOLDING PROTEIN LIGAND DOCKING PROTEIN SIDE CHAINS RUBEN ABAGYAN STAFF WELCOME rtop s rbot c s path s T S T K T f II s HH s GG s FFF s p FF s d EE s U DD s H CC s 9 BB s * AA s