Atjaunināt sīkdatņu piekrišanu

Thermodynamics and Statistical Mechanics of Macromolecular Systems [Hardback]

(University of Georgia)
  • Formāts: Hardback, 354 pages, height x width x depth: 252x193x20 mm, weight: 960 g, 63 Halftones, unspecified; 86 Line drawings, unspecified
  • Izdošanas datums: 24-Apr-2014
  • Izdevniecība: Cambridge University Press
  • ISBN-10: 1107014476
  • ISBN-13: 9781107014473
Citas grāmatas par šo tēmu:
  • Hardback
  • Cena: 75,52 €
  • Grāmatu piegādes laiks ir 3-4 nedēļas, ja grāmata ir uz vietas izdevniecības noliktavā. Ja izdevējam nepieciešams publicēt jaunu tirāžu, grāmatas piegāde var aizkavēties.
  • Daudzums:
  • Ielikt grozā
  • Piegādes laiks - 4-6 nedēļas
  • Pievienot vēlmju sarakstam
Thermodynamics and Statistical Mechanics of Macromolecular SystemsPalielināt
  • Formāts: Hardback, 354 pages, height x width x depth: 252x193x20 mm, weight: 960 g, 63 Halftones, unspecified; 86 Line drawings, unspecified
  • Izdošanas datums: 24-Apr-2014
  • Izdevniecība: Cambridge University Press
  • ISBN-10: 1107014476
  • ISBN-13: 9781107014473
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781107014473.html
Keywords:
The structural mechanics of proteins that fold into functional shapes, polymers that aggregate and form clusters, and organic macromolecules that bind to inorganic matter can only be understood through statistical physics and thermodynamics. This book reviews the statistical mechanics concepts and tools necessary for the study of structure formation processes in macromolecular systems that are essentially influenced by finite-size and surface effects. Readers are introduced to molecular modeling approaches, advanced Monte Carlo simulation techniques, and systematic statistical analyses of numerical data. Applications to folding, aggregation, and substrate adsorption processes of polymers and proteins are discussed in great detail. Particular emphasis is placed on the reduction of complexity by coarse-grained modeling, which allows for the efficient, systematic investigation of structural phases and transitions. Providing insight into modern research at this interface between physics, chemistry, biology, and nanotechnology, this book is an excellent reference for graduate students and researchers.

Recenzijas

'The clarity of exposition supports the author's goal with respect to his view. In fact, as stated in the preface and outline of his work, he wished to overcome the frustration for the present contradicting and inconclusive literature in this field. The richness of specific examples also supports the book scope. The approach to modelling is also clearly described. this book could be suitable also for non-experts in the field, due to its precise exposition of the subjects. I would recommend this book to people from different scientific backgrounds: starting from physics to biology, biochemistry and many others. The work by Bachmann should also be considered as an acquisition, whose value is long-lasting. Finally, the exhaustive treatment contained in [ this book] might also constitute a good support for defining future research paths and projects, which have now a wide spectrum of applications.' Marco Casazza, Contemporary Physics

Papildus informācija

Reviewing statistical mechanics concepts for analysis of macromolecular structure formation processes, for graduate students and researchers in physics and biology.
Preface and outline xiii
1 Introduction
1(30)
1.1 Relevance of biomolecular research
1(2)
1.2 Proteins
3(6)
1.2.1 The trinity of amino acid sequence, structure, and function
3(3)
1.2.2 Ribosomal synthesis of proteins
6(1)
1.2.3 From sequence to function: The protein folding process
7(2)
1.3 Molecular modelling
9(3)
1.3.1 Covalent bonds
9(2)
1.3.2 Effective noncovalent interactions and nanoscopic modeling: Toward a semiclassical all-atom representation
11(1)
1.4 All-atom peptide modelling
12(2)
1.5 The mesoscopic perspective
14(6)
1.5.1 Why coarse-graining...? The origin of the hydrophobic force
15(2)
1.5.2 Coarse-grained hydrophobic--polar modelling
17(3)
1.6 Polymers
20(11)
1.6.1 DNA and RNA
20(2)
1.6.2 Modeling free DNA
22(1)
1.6.3 Flexible, attractively self-interacting polymers
23(4)
1.6.4 Elastic polymers
27(4)
2 Statistical mechanics: A modern review
31(36)
2.1 The theory of everything
31(2)
2.2 Thermodynamics and statistical mechanics
33(10)
2.2.1 The thermodynamic limit
33(1)
2.2.2 Thermodynamics of closed systems: The canonical ensemble
34(2)
2.2.3 Thermodynamic equilibrium and the statistical nature of entropy
36(7)
2.3 Thermal fluctuations and the statistical path integral
43(3)
2.4 Phase and pseudophase transitions
46(2)
2.5 Relevant degrees of freedom
48(3)
2.5.1 Coarse-grained modeling on mesoscopic scales
48(1)
2.5.2 Macroscopic relevant degrees of freedom: The free-energy landscape
49(2)
2.6 Kinetic free-energy barrier and transition state
51(2)
2.7 Microcanonical statistical analysis
53(14)
2.7.1 Temperature as a derived quantity
54(1)
2.7.2 Identification of first-order transitions by Maxwell construction
55(7)
2.7.3 Systematic classification of transitions by inflection-point analysis
62(5)
3 The complexity of minimalistic lattice models for protein folding
67(14)
3.1 Evolutionary aspects
67(1)
3.2 Self-avoiding walks and contact matrices
68(1)
3.3 Exact statistical analysis of designing sequences
69(7)
3.4 Exact density of states and thermodynamics
76(5)
4 Monte Carlo and chain growth methods for molecular simulations
81(56)
4.1 Introduction
81(1)
4.2 Conventional Markov-chain Monte Carlo sampling
82(11)
4.2.1 Ergodicity and finite time series
82(2)
4.2.2 Statistical error and bias
84(4)
4.2.3 Binning--jackknife error analysis
88(5)
4.3 Systematic data smoothing by using Bezier curves
93(7)
4.3.1 Construction of a Bezier curve
93(3)
4.3.2 Smooth Bezier functions for discrete noisy data sets
96(4)
4.4 Markov processes and stochastic sampling strategies
100(4)
4.4.1 Master equation
100(1)
4.4.2 Selection and acceptance probabilities
101(1)
4.4.3 Simple sampling
102(1)
4.4.4 Metropolis sampling
103(1)
4.5 Reweighting methods
104(4)
4.5.1 Single-histogram reweighting
104(1)
4.5.2 Multiple-histogram reweighting
105(3)
4.6 Generalized-ensemble Monte Carlo methods
108(10)
4.6.1 Replica-exchange Monte Carlo method: Parallel tempering
108(1)
4.6.2 Simulated tempering
109(1)
4.6.3 Multicanonical sampling
109(8)
4.6.4 Wang--Landau method
117(1)
4.7 Elementary Monte Carlo updates
118(5)
4.8 Lattice polymers: Monte Carlo sampling vs. Rosenbluth chain growth
123(3)
4.9 Pruned-enriched Rosenbluth method: Go with the winners
126(1)
4.10 Canonical chain growth with PERM
127(2)
4.11 Multicanonical chain-growth algorithm
129(4)
4.11.1 Multicanonical sampling of Rosenbluth-weighted chains
129(1)
4.11.2 Iterative determination of the density of states
130(3)
4.12 Random number generators
133(1)
4.13 Molecular dynamics
134(3)
5 First insights to freezing and collapse of flexible polymers
137(12)
5.1 Conformational transitions of flexible homopolymers
137(1)
5.2 Energetic fluctuations of finite-length polymers
138(6)
5.2.1 Peak structure of the specific heat
138(1)
5.2.2 Simple-cubic lattice polymers
139(2)
5.2.3 Polymers on the face-centered cubic lattice
141(3)
5.3 The transition
144(3)
5.4 Freezing and collapse in the thermodynamic limit
147(2)
6 Crystallization of elastic polymers
149(26)
6.1 Lennard-Jones clusters
149(1)
6.2 Perfect icosahedra
150(2)
6.3 Liquid--solid transitions of elastic flexible polymers
152(12)
6.3.1 Finitely extensible nonlinear elastic Lennard-Jones polymers
152(1)
6.3.2 Classification of geometries
153(2)
6.3.3 Ground states
155(1)
6.3.4 Thermodynamics of liquid--solid transitions toward complete icosahedra
156(2)
6.3.5 Liquid--solid transitions of elastic polymers
158(4)
6.3.6 Long-range effects
162(2)
6.4 Systematic analysis of compact phases
164(1)
6.5 Dependence of structural phases on the range of nonbonded interactions
165(10)
7 Structural phases of semiflexible polymers
175(6)
7.1 Structural hyperphase diagram
175(5)
7.2 Variation of chain length
180(1)
8 Generic tertiary folding properties of proteins on mesoscopic scales
181(10)
8.1 A simple model for a parallel β helix lattice protein
181(3)
8.2 Protein folding as a finite-size effect
184(1)
8.3 Hydrophobic--polar off-lattice heteropolymers
185(6)
9 Protein folding channels and kinetics of two-state folding
191(26)
9.1 Similarity measure and order parameter
192(3)
9.2 Identification of characteristic folding channels
195(3)
9.3 Go kinetics of folding transitions
198(11)
9.3.1 Coarse-grained Go modeling
199(2)
9.3.2 Thermodynamics
201(3)
9.3.3 Kinetics
204(4)
9.3.4 Mesoscopic heteropolymers vs. real proteins
208(1)
9.4 Microcanonical effects
209(4)
9.5 Two-state cooperativity in helix-coil transitions
213(4)
10 Inducing generic secondary structures by constraints
217(10)
10.1 The intrinsic nature of secondary structures
217(1)
10.2 Polymers with thickness constraint
218(5)
10.2.1 Global radius of curvature
218(1)
10.2.2 Modeling flexible polymers with constraints
219(1)
10.2.3 Thickness-dependent ground-state properties
220(2)
10.2.4 Structural phase diagram of tube-like polymers
222(1)
10.3 Secondary-structure phases of a hydrophobic--polar heteropolymer model
223(4)
11 Statistical analyses of aggregation processes
227(16)
11.1 Pseudophase separation in nucleation processes of polymers
227(1)
11.2 Mesoscopic hydrophobic--polar aggregation model
228(1)
11.3 Order parameter of aggregation and fluctuations
229(1)
11.4 Statistical analysis in various ensembles
230(9)
11.4.1 Multicanonical results
230(3)
11.4.2 Canonical perspective
233(2)
11.4.3 Microcanonical interpretation: The backbending effect
235(4)
11.5 Aggregation transition in larger heteropolymer systems
239(4)
12 Hierarchical nature of phase transitions
243(12)
12.1 Aggregation of semiflexible polymers
243(1)
12.2 Structural transitions of semiflexible polymers with different bending rigidities
244(3)
12.3 Hierarchies of subphase transitions
247(2)
12.4 Hierarchical peptide aggregation processes
249(3)
12.5 Hierarchical aggregation of GNNQQNY
252(3)
13 Adsorption of polymers at solid substrates
255(38)
13.1 Structure formation at hybrid interfaces of soft and solid matter
255(1)
13.2 Minimalistic modeling and simulation of hybrid interfaces
256(2)
13.3 Contact-density chain-growth algorithm
258(1)
13.4 Pseudophase diagram of a flexible polymer near an attractive substrate
259(5)
13.4.1 Solubility--temperature pseudophase diagram
260(1)
13.4.2 Contact-number fluctuations
261(2)
13.4.3 Anisotropic behavior of gyration tensor components
263(1)
13.5 Alternative view: The free-energy landscape
264(5)
13.6 Continuum model of adsorption
269(8)
13.6.1 Off-lattice modeling
269(1)
13.6.2 Energetic and structural quantities for phase characterization by canonical statistical analysis
270(1)
13.6.3 Comparative discussion of structural fluctuations
271(2)
13.6.4 Adsorption parameters
273(1)
13.6.5 The pseudophase diagram of the hybrid system in continuum
274(3)
13.7 Comparison with lattice results
277(2)
13.8 Systematic microcanonical analysis of adsorption transitions
279(7)
13.8.1 Dependence on the surface attraction strength
280(2)
13.8.2 Chain-length dependence
282(2)
13.8.3 Translational entropy
284(2)
13.9 Polymer adsorption at a nanowire
286(7)
13.9.1 Modeling the polymer--nanowire complex
287(1)
13.9.2 Structural phase diagram
288(5)
14 Hybrid protein--substrate interfaces
293(26)
14.1 Steps toward bionanotechnology
293(1)
14.2 Substrate-specific peptide adsorption
294(7)
14.2.1 Hybrid lattice model
294(1)
14.2.2 Influence of temperature and solubility on substrate-specific peptide adsorption
295(6)
14.3 Semiconductor-binding synthetic peptides
301(2)
14.4 Thermodynamics of semiconductor-binding peptides in solution
303(4)
14.5 Modeling a hybrid peptide--silicon interface
307(5)
14.5.1 Introduction
307(1)
14.5.2 Si(100), oxidation, and the role of water
308(1)
14.5.3 The hybrid model
309(3)
14.6 Sequence-specific peptide adsorption at silicon (100) surface
312(7)
14.6.1 Thermal fluctuations and deformations upon binding
312(1)
14.6.2 Secondary-structure contents of the peptides
313(2)
14.6.3 Order parameter of adsorption and nature of adsorption transition
315(4)
15 Concluding remarks and outlook
319(4)
References 323(14)
Index 337
Michael Bachmann is Associate Professor in the Department of Physics and Astronomy at the University of Georgia. His major fields of interest include theoretical physics, computational physics, statistical physics, biophysics, and chemical physics.