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Protein actions : principles and modeling / Ivet Bahar, Robert L. Jernigan, Ken A. Dill. -- New York, NY : Garland Science, c2017. – (58.17421/B151) |
Contents
Chapter 1
Proteins Are Polymers That Fold into Specific Structures
PROTEINS
ARE THE MACHINES THAT PERFORM CELLULAR FUNCTIONS
PROTEINS
HAVE SEQUENCE-STRUCTURE-FUNCTION RELATIONSHIPS
AMINO
ACIDS ARE THE REPEAT UNITS OF PROTEINS
NATIVE
PROTEINS HAVE COMPACT WELL-DEFINED 3D STRUCTURES
PROTEINS
HAVE HIERARCHIES OF STRUCTURE
SOME
PROTEINS ARE STABLE AND FUNCTION IN THE MEMBRANE ENVIRONMENT
SOME
PROTEINS HAVE FIBROUS STRUCTURES
NATIVE
PROTEINS ARE CONFORMATIONAL ENSEMBLES
SUMMARY
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Chapter
2 Proteins Perform Cellular Functions
PROTEINS
CARRY OUT MANY ACTIVITIES IN THE CELL
A PROTEIN'S
FUNCTIONALITY IS ENCODED IN ITS STRUCTURE AND DYNAMICS
PROTEINS
ARE BORN
PROTEINS
WORK FOR A LIVING
PROTEINS
ARE HEALTHY OR SICK OR DIE
SUMMARY
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Chapter
3 Proteins Have Stable Equilibrium Conformations
NATIVE
AND DENATURED STATES ARE STABLE STATES OF PROTEINS
STATISTICAL
MECHANICS IS THE LANGUAGE FOR DESCRIBING PROTEIN STABILITIES
SIMPLE
PROTEINS DENATURE WITH TWO-STATE THERMODYNAMICS
PROTEINS
TEND TO UNFOLD IN ACIDIC OR BASIC SOLUTIONS
A
DENATURED STATE IS A DISTRIBUTION OF CONFORMATIONS
SUMMARY
APPENDIX
3A: A SIMPLE ELECTROSTATIC MODEL OF DENATURATION BY ACIDS AND BASES
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Chapter 4 Protein Binding Leads
to Biological Actions
INTRODUCTION
BINDING
CAN BE MODELED USING BINDING POLYNOMIALS
IN
ALLOSTERY, BINDING IS COUPLED TO CONFORMATIONAL CHANGE
INHIBITORS
AND ACTIVATORS CAN MODULATE OTHER BINDING ACTIONS
COUPLED
BINDING IS KEY TO REGULATION, SIGNALING, AND ENERGY TRANSDUCTION
BROWNIAN
RATCHETS PRODUCE DIRECTED MOTION FROM COUPLED BINDING EVENTS
SUMMARY
APPENDIX
4A: TYPICAL DISSOCIATION CONSTANTS FOR PROTEINS
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Chapter
5 Folding and Aggregation Are Cooperative Transitions 1
PROTEINS
CAN UNDERGO SHARP TRANSITIONS IN THEIR STRUCTURES OR PROPERTIES
PROTEINS
AND PEPTIDES CAN UNDERGO A COOPERATIVE HELIX-COIL TRANSITION
PROTEIN
FOLDING COOPERATIVITY ARISES FROM SECONDARY AND TERTIARY INTERACTIONS
PROTEINS
CAN ASSEMBLE COOPERATIVELY INTO AGGREGATES, FIBRILS, OR CRYSTALS
SUMMARY
APPENDIX
5A: ADVANCED HELIX-COIL THEORIES
APPENDIX
5B: AMYLOID AGGREGATION THEORY
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Chapter
6 The Principles of Protein Folding Kinetics
THE
LEVINTHAL PARADOX MOTIVATED THE SEARCH FOR A PROTEIN FOLDING MECHANISM
FOLDING
RATE EXPERIMENTS ARE CAPTURED BY MASS-ACTION MODELS
RATE
MEASUREMENTS GIVE INSIGHTS INTO THE PATHWAYS OF PROTEIN FOLDING
HOW DO
PROTEINS FOLD SO FAST?. THEY FOLD ON FUNNEL-SHAPED ENERGY LANDSCAPES
DIFFERENT
PROTEINS CAN FOLD AT VERY DIFFERENT RATES
SUMMARY
APPENDIX
6A: MASTER EQUATIONS DESCRIBE DYNAMICS
APPENDIX
6B: THE ZWANZIG-SZABO-BAGCHI MODEL SHOWS HOW FUNNELS ACCELERATE FOLDING
APPENDIX
6C: PROTEIN FOLDING FUNNELS CAN BE BUMPY: THE SPIN-GLASS MODEL
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Chapter
7 Proteins Evolve 1
PROTEINS
CHANGE THROUGH EVOLUTIONARY PROCESSES
MANY
DIFFERENT SEQUENCES FOLD INTO THE SAME NATIVE STRUCTURE
EVOLUTION
IS NOT AN ABSTRACTION. IT'S REAL. IT'S HAPPENING NOW
SUMMARY
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Chapter
8 Bioinformatics: Insights from Protein Sequences
COMPARING
AMINO ACID SEQUENCES GIVES INSIGHT INTO PROTEIN STRUCTURE AND FUNCTION
HOW DO
YOU DETERMINE THE RELATEDNESS BETWEEN SEQUENCES?
TO
COMPARE SEQUENCES, YOU START WITH GOOD ALIGNMENTS
HOW DO
YOU CONSTRUCT A PHYLOGENETIC TREE?
EVOLUTION
CONSERVES SOME AMINO ACIDS AND CHANGES OTHERS
SUMMARY
APPENDIX
8A: EXAMPLE OF A BLAST RUN
APPENDIX
8B: ESTIMATING EVOLUTIONARY RATES USING A MARKOV MODEL FOR RESIDUE
SUBSTITUTIONS
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Chapter
9 Protein Geometries and Energetics
YOU CAN
REPRESENT A PROTEIN STRUCTURE BY ITS ATOMIC COORDINATES
TO
SIMULATE PROTEIN PHYSICS ON A COMPUTER, YOU NEED A MODEL OF INTERATOMIC
ENERGIES
SUMMARY
APPENDIX
9A: HOW TO COMPUTE CARTESIAN COORDINATES FROM INTERNAL COORDINATES
APPENDIX
9B: HOW TO OPTIMALLY SUPERIMPOSE TWO STRUCTURES
APPENDIX
9C: THE POISSON-BOLTZMANN EQUATION TREATS ELECTROSTATIC INTERACTIONS
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Chapter
10 Molecular Simulations and Conformational Sampling
YOU CAN
FIND STATES OF LOW ENERGY BY ENERGY MINIMIZATION
MOLECULAR
DYNAMICS SIMULATIONS SOLVE NEWTON'S EQUATIONS OF MOTION ITERATIVELY
METROPOLIS
MONTE CARLO SIMULATION IS A STOCHASTIC METHOD OF SAMPLING CONFORMATIONS
ADDITIONAL
PRINCIPLES LEAD TO IMPROVED COMPUTATIONAL SAMPLING
SUMMARY
APPENDIX
10A: THE VERLET AND LEAPFROG ALGORITHMS GENERATE MD TRAJECTORIES
APPENDIX
10B: PERIODIC BOUNDARY CONDITIONS ARE USED IN MD SIMULATIONS
APPENDIX
10C: SOME METHODS FOR ENHANCED SAMPLING
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Chapter
11 Predicting Protein Structures from Sequences
SOME
PROTEINS HAVE COMPUTABLE NATIVE STRUCTURES
COMPARATIVE
MODELING IS A MAIN TOOL FOR STRUCTURE PREDICTION
STATISTICAL
POTENTIALS ARE "ENERGY-LIKE" SCORING FUNCTIONS FOR SELECTING
NATIVE-LIKE PROTEIN STRUCTURES
OTHER
COMPUTATIONAL TOOLS CAN ALSO HELP YOU PREDICT NATIVE STRUCTURES
CASP: A
COMMUNITY-WIDE EVENT EVALUATES STRUCTURE-PREDICTION METHODS
ATOMISTIC
PHYSICAL SIMULATIONS CAN PREDICT THE STRUCTURES OF SOME SMALL PROTEINS
METHODS
ARE AVAILABLE FOR PREDICTING THE STRUCTURES OF PROTEIN COMPLEXES, MULTIMERS,
AND ASSEMBLIES
SUMMARY
APPENDIX
11A: THE MIYAZAWA-JERNIGAN CONTACT-POTENTIAL MATRIX
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Chapter
12 Biological Actions Arise from Protein Motions
NATIVE
PROTEINS HAVE CORRELATED MOTIONS
ELASTIC
NETWORK MODELS USE BEADS AND SPRINGS TO DESCRIBE PROTEIN MOTIONS
PROTEIN
MOTIONS CAN BE OBSERVED IN EXPERIMENTS AND PREDICTED BY THE GNM
PROTEIN
MOTIONS ARE RELEVANT TO MECHANISMS OF ACTION
MULTIPROTEIN
ASSEMBLIES CAN BE STUDIED BY ELASTIC NETWORK MODELS
SUMMARY
APPENDIX
12A: HERE'S HOW TO EXPRESS THE ELASTIC FREE ENERGY IN TERMS OF THE ADJACENCY
MATRIX
APPENDIX
12B: HOW IS r RELATED TO LOCAL PACKING DENSITIES?
APPENDIX
12C: HOW DO YOU DETERMINE THE GNM MODES?
APPENDIX
12D: NORMAL MODE ANALYSIS
APPENDIX
12E: MEAN-SQUARE FLUCTUATIONS IN INTERNAL DISTANCES DEPEND ON THE NETWORK
CONNECTIVITY
APPENDIX
12F: HOW CAN YOU COMPARE ONE MOTION WITH ANOTHER?
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Chapter
13 Molecular Modeling for Drug Discovery
DRUGS
OFTEN ACT BY BINDING TO PROTEINS
PHARMACEUTICAL
DISCOVERY IS A MULTISTAGE PIPELINE PROCESS
DESIGNING
A DRUG REQUIRES OPTIMIZING MULTIPLE PROPERTIES
LIGAND-BASED
DISCOVERY USES KNOWN LIGANDS TO DESIGN NEW ONES
TARGET-BASED
DISCOVERY DESIGNS DRUGS BY USING THE STRUCTURE OF A TARGET PROTEIN
A MAJOR
CLASS OF DRUGS IS THE BIOLOGICS
CHALLENGES
AND RECENT DEVELOPMENTS IN DRUG DISCOVERY
SUMMARY
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INDEX
