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Leach A.R. — Molecular Modelling Principles and Applications
Leach A.R. — Molecular Modelling Principles and Applications



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Íàçâàíèå: Molecular Modelling Principles and Applications

Àâòîð: Leach A.R.

Àííîòàöèÿ:

Preface to the Second Edition The impetus for this second edition is a desire to include some of the new techniques that have emerged in recent years and also extend the scope of the book to cover certain areas that were under-represented (even neglected) in the first edition. In this second volume there are three topics that fall into the first category (density functional theory, bioinformatics/protein structure analysis and chemoinformatics) and one main area in the second category (modelling of the solid state). In addition, of course, a new edition provides an opportunity to take a critical view of the text and to re-organise and update the material. Thus whilst much remains from the first edition, and this second book follows much the same path through the subject, readers familiar with the first edition will find some changes which I hope they will agree are for the better. As with the first edition we initially consider quantum mechanics, but this is now split into two chapters. Thus Chapter 2 provides an introduction to the ab initio and semi-empirical approaches together with some examples of the uses of quantum mechanics. Chapter 3 covers more advanced aspects of the ab initio approach, density functional theory and the particular problems of the solid state. Molecular mechanics is the subject of Chapter 4 and then in Chapter 5 we consider energy minimisation and other 'static' techniques. Chapters 6, 7 and 8 deal with the two main simulation methods (molecular dynamics and Monte Carlo). Chapter 9 is devoted to the conformational analysis of 'small' molecules but also includes some topics (e.g. cluster analysis, principal components analysis) that are widely used in informatics. In Chapter 10 the problems of protein structure prediction and protein folding are considered; this chapter also contains an introduction to some of the more widely used methods in bioinformatics. In Chapter 11 we draw upon material from the previous chapters in a discussion of free energy calculations, continuum solvent models, and methods for simulating chemical reactions and defects in solids. Finally, Chapter 12 is concerned with modelling and chemoinformatics techniques for discovering and designing new molecules, including database searching, docking, de novo design, quantitative structure-activity relationships and combinatorial library design. As in the first edition, the inexorable pace of change means that what is currently considered 'cutting edge' will soon become routine. The examples are thus chosen primarily because they illuminate the underlying theory rather than because they are the first application of a particular technique or are the most recent available. In a similar vein, it is impossible in a volume such as this to even attempt to cover everything and so there are undoubtedly areas which are under-represented. This is not intended to be a definitive historical account or a review of the current state-of-the-art. Thus, whilst I have tried to include many literature references it is possible that the invention of some technique may appear to be incorrectly attributed or a 'classic' application may be missing. A general guiding principle has been to focus on those techniques that are in widespread use rather than those which are the province of one particular research group. Despite these caveats I hope that the coverage is sufficient to provide a solid introduction to the main areas and also that those readers who are 'experts' will find something new to interest them.


ßçûê: en

Ðóáðèêà: Õèìèÿ/

Ñòàòóñ ïðåäìåòíîãî óêàçàòåëÿ: Ãîòîâ óêàçàòåëü ñ íîìåðàìè ñòðàíèö

ed2k: ed2k stats

Èçäàíèå: 2-nd

Ãîä èçäàíèÿ: 2001

Êîëè÷åñòâî ñòðàíèö: 774

Äîáàâëåíà â êàòàëîã: 21.02.2007

Îïåðàöèè: Ïîëîæèòü íà ïîëêó | Ñêîïèðîâàòü ññûëêó äëÿ ôîðóìà | Ñêîïèðîâàòü ID
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Ïðåäìåòíûé óêàçàòåëü
PCM (polarisable continuum method)      596—597 598
PDB (Protein Databank)      489—490 539
Pdf (probability density function)      304 541
Pearson correlation coefficient      681
Penalty functions      483
Pentane      253 430 462 582
Pepsin      545
Peptides/polypeptides      277 423 509 515 517—518 520 691
Peptides/polypeptides, conformational analysis      459 482
Peptides/polypeptides, dynamic programming      527—528
Peptides/polypeptides, folding      552
Peptides/polypeptides, force fields      196—197 221 231
Peptides/polypeptides, free energy calculations      571 583—584
Peptides/polypeptides, loop conformations      541—542
Peptides/polypeptides, peptoids      713
Peptides/polypeptides, ‘threading’      546 (see also “Amino acids” “Proteins”)
Percentage sequence identity      524
Pericyclic reactions transition structures      292—295
Periodic boundary conditions      317—319
Perturbation and free energy      566—568 573—574 582 584 595
Perturbation and free energy, thermodynamic      564—566 569—573 577 592
Perturbation theories      36 114—117 119
Pharmacophore, keys      674—676
Pharmacophore, mapping      648
Pharmacophores      647 (see also “New molecules”)
Phase equilibria, simulation of      450—451
Phase problem, in X-ray crystallography      484
Phase space and computer simulation      312—315
Phenylalanine      169 286 511 525 542 546 556—557
Phonons and dispersion curve      298—299
Pivot algorithm      423
Plane waves      155—156
PLS (partial least squares)      702 706—711
PM3      98—99 102
PMF (potentials of mean force)      387—390 546 580—585 612—14
Point defect      622
Point-charge electrostatic models      187
Poisson equation      133
Poisson — Boltzmann equation      603—608
Polarisation/polarisable basis functions      71
Polarisation/polarisable basis functions, continuum method      596—597 598
Polarisation/polarisable basis functions, electrostatic non-bonded interactions      199—202 203
Polarisation/polarisable basis functions, energy component analysis      122
Polarisation/polarisable basis functions, force field models for simulation of water      218—219
Poling and conformational analysis      499—501
Polyatomic systems      210—212
Polyelectronic atoms and molecules      34—41
Polymers, energy minimisation methods      289—290
Polymers, free energy calculations      621 622
Polymers, molecular dynamics simulation      391 404 550 551
Polymers, Monte Carlo simulation of      423—431 (see also “Amino acids” “Peptides” “Proteins”)
Population Analysis      79—80 189
Porphyrins      197—198
Positive definite matrix      16 268
Potential      156—157 275 486 546
Potential of mean force      see “PMF”
Potential, computational quantum mechanics      74—75 83—85
Potential, computer simulation      305 319 324—334 338 341—342
Potential, electrostatic      83—85
Potential, energy      4—5 238 253
Potential, force fields      167 170—173 188—192 207—210 212—217 222—226 237—238 240—245
Potential, free energy calculations      549 579 580—585 586 612—614
Potential, ionisation      74—75
Potential, models, pairwise      240—241
Potential, molecular dynamics simulation      387—390
Potential, Monte Carlo simulation      442—443
Potential, new molecules      665 666
Potential, prediction of crystal structures      501—505
Potential, predictive residual sum of squares      701
Potential, predictor-corrector methods of molecular dynamics simulation      358—359 (see also under “Proteins”)
Preferential sampling      432
PRESS (predictive residual sum of squares)      701
Pressure      309 385—387
Principal components analysis      see “PCA”
Principal components regression      706
Probability density function      304 541
Probability matrices for proteins      556—557
Product-based monomer selection      718
Production phase in simulation      315
Profile      535
Proline      221 511 525 556—557
PROMET      502—503
Propane      167 644
Proteins      6 423
Proteins, computer simulation      329—330 338—339
Proteins, conformational analysis      475 489—490
Proteins, force fields      192 221
Proteins, free energy calculations      571
Proteins, predicting structure of      509—562
Proteins, predicting structure of, acronyms and abbreviations      553—554
Proteins, predicting structure of, basic principles      513—517
Proteins, predicting structure of, comparative model      539—545
Proteins, predicting structure of, comparison of methods      547—549
Proteins, predicting structure of, databases, list of      555
Proteins, predicting structure of, first principles methods      517—522
Proteins, predicting structure of, folding and unfolding      512 516—517 539 545—547 549—553
Proteins, predicting structure of, mutation probability matrices      556—557
Proteins, predicting structure of, sequence alignment      522—539
Proteins, predicting structure of, threading      545—547
Proteins, Protein Databank      489—490 539 “Peptides”)
Pseudo-acyclic molecules      463—464
Pseudopotentials      156—157
Pyrazine, 2—pyridone      597—598
Pyrazine/pyridine      573
Pyridine, 2—pyridone      597—598
QCISD (quadratic CISD)      113 117 119
QSAR (quantitative structure-activity relationships)      695—706 710 711
QSAR (quantitative structure-activity relationships), cross-validation      701
QSAR (quantitative structure-activity relationships), deriving equation      698—770
QSAR (quantitative structure-activity relationships), discriminant analysis      703—705
QSAR (quantitative structure-activity relationships), interpreting equation      702
QSAR (quantitative structure-activity relationships), neural networks      703—705
QSAR (quantitative structure-activity relationships), principal components regression      706
QSAR (quantitative structure-activity relationships), property relationship      695 702
QSAR (quantitative structure-activity relationships), selecting compounds for analysis      697—698
QSPR (quantitative structure-property relationship)      695 702
Quadratic region      283—284
Quadrupole      76 181 183 185—186 196
Quantitative structure-activity      see “QSAR”
Quantum mechanics and molecular mechanics combined in chemical reactions      614—616
Quantum mechanics, future role      160—161
Quantum mechanics, solvation, free energy of      594—598 (see also ab initio ”Quantum mechanics” “Advanced computational
Quasi ergodicity and Monte Carlo, simulation      433—438
Quasi-Newton energy minimisation      268—269
Quaternions      422
R groups      716—717
r-RESPA (reversible reference system propagation algorithm)      363—364
Radial distribution functions and computer simulation      310—312
Ramachandran map      459—460 514 543 547
Random number generators      418—420 453—454
Random sampling      345—347
Random search      465—467 476 517—518
Random tweak      542
Range scaling      681
Ranitidine      489 644
RANTES      475
Rapid free energy calculations, approximate      585—592
Rappe — Goddard method      193—194
RATTLE method      373—374
Rayleigh — Schrodinger perturbation theory      114
Re-entrant surface      7
Reaction, field      339—340 595—596 597
Reaction, isodemic      116
Reaction, pathways      279—295
Reaction, transform      715—716
Reaction, zone      320—321 (see also “Chemical reactions”)
Real gas contribution to virial      309 349—350
Reciprocal lattice      139—140
Recombination operator      480—481
Reduced units, in non-bonded interactions      212
Refractivity, molar      671
Regression      706
Regression, equation      698—699
Regression, linear      666 698—699 702
Relative energies      226
Relaxation time      376
Reptation      427
Repulsive forces      206 (see also “Coulomb attraction/repulsion”)
Residual sum of squares      699—700
RESP (restrained electrostatic potential fit)      191—192
Response      697
Restraints/restrained and constraints, difference between      369—370
Restraints/restrained, electrostatic potential fit      191—192
Restraints/restrained, molecular dynamics      483—484
Restraints/restrained, spatial, satisfaction of      540—541
Reversible reference system      363—364
RHF (spin-restricted Hartree — Fock theory)      108—110
Ribose phosphate      493—494
Rigid molecules, simulation of      420—422
Rigid-body method      540
Ring critical point      81
RIS (rotational isomeric state) model      429—431
RMS (root-mean-square)      273 359—360 552 667
RMSD (root-mean-square-distance)      491—493
RNA      509 512
root nodes      461
Root-mean-square      273 359—360 552 667
Roothaan — Hall equations, closed-shell systems      56—59 86—88
Roothaan — Hall equations, density functional theory      132
Roothaan — Hall equations, illustrated      62—5
Roothaan — Hall equations, solving      59—62
Rosenbluth weight      444—447
Rotational isomeric state      429—431
Rotational order      322
Roulette wheel selection      480
RSS (residual sum of squares)      699—700
Rule-based approaches to protein prediction      520—522
Saddle points      253 272—273 280 282—283 291
Saddle points, location      285—288 478
Saddle points, quadratic region      283—284
SAM1 (Semi-Ab-initio Model 1)      99 102
Sampling      345 346—347 410 432 438—442 567—568 575—576
SC24/halide system      571
Scalar product and triple product      12 14
Scaling/scaled, autoscaling      681
Scaling/scaled, coordinates      438—439
Scaling/scaled, mesoscale modelling      402—404
Scaling/scaled, particle theory      609
Scaling/scaled, range      681
SCF (self-consistent field)      117 280
SCF (self-consistent field), complete active-space      113 295
SCF (self-consistent field), computational quantum mechanics      54 64 73 75 87
SCF (self-consistent field), direct method      118—120
SCF (self-consistent field), energy component analysis      122
SCF (self-consistent field), free energy calculations      595—596 597
SCF (self-consistent field), Hartree — Fock      75 87 119
SCF (self-consistent field), multiconfiguration      113
Schottky defect      622—623 626
Schrodinger equations and solutions for Drude molecules      205 246—247
Schrodinger equations and solutions to computational quantum mechanics      27—28 29—30 32 34—37 128
Schrodinger equations and solutions to computer simulation      347—348
Schrodinger equations and solutions to density functional theory      127 128
Schrodinger equations and solutions to solid state quantum mechanics      147 148
SCOP (Structural Classification of Proteins)      539
Scoring functions for docking      664—667
SCRF (self-consistent reaction field)      595—596 597
SCRs (structurally conserved regions)      539—540
SDEP measure      709
Search, depth-first      462 663
Search, grid      459 505
Search, heuristic      531—534
Search, line      262—263
Search, low-mode      478—479
Search, multiple-copy      688
Search, new molecules (3D)      645 647 667—668
Search, random      465—467 476 517—518
Search, systematic      458—464 476 505
Search, trees      461—465 (see also under “Conformational analysis”)
Second-moment approximation      242
Secondary structure of proteins      513
Segment matching      540
Self-consistent field      see “SCF” “SCRF”
Self-penalty walk (SPW)      289—290 584
Semi-Ab-initio Model 1 (SAM1)      99 102
Semi-empirical methods of computational quantum mechanics      65 86—99 102—103
Semi-empirical molecular orbital theories      86 89—96 102—103
Semiconductors, force field potentials for      244—245
Separation of variables      36—37
Sequence alignment of proteins      522—539
Sequence identity      546—547
Sequential univariate minimisation      260—261
Series expansions      10—11
Serine      511 525 556—557
SHAKE procedure      369—374 582 618
Shape arastropy parameter      224—225
SHAPES force field      235—237
Shear viscosity      381
Shielding constant      55—56
Shifted potential      330—331
Shorthand representation of electron integrals      50
Sigmoidal dielectric model      202—204
Silica      297—298
Silicalite      449—450
Silicon      483 693
Silicon and chlorine      620—621
Silicon, force fields      237 245
Silicon, O bond      237
Silicon, phases of      159—160
Silicon, shielding constant      55—56
Silicon, valence electron density      160
Similarity and 3D properties      678—679
Similarity, calculating      676—678
Similarity, searching      668
Simple force field models for simulation of water      216—218
Simplex method of non-derivative energy, minimisation      258—260
Simpson’s rule      412—413
Simulated annealing in ab initio molecular dynamics      616—618
Simulated annealing in conformational analysis      483
Simulated annealing in X-ray refinement      484—486
Simulations      see “Computer simulation” “Conformational “Molecular “Monte
SINDOl program      99
Single-linkage cluster algorithm      493—496
Site points      689
skewness      680
Slater determinants, density functional theory      135 136
Slater determinants, general polyelectromc systems      38—41
Slater determinants, many-body perturbation      115
Slater determinants, orbitals      see “STOs”
Slater determinants, Slater’s Rules and Hartree — Fock equations      54—56
Slater functions and basis sets      67—69
Slow growth free energy calculations      568—569 577 631
Smart Monte Carlo method      432—433
Smart Region Definition      710—711
SMILES notation      643—645 715
Smith — Waterman algorithm      529—530
Sodium      181 589 626
Sodium chloride      238
Soergel distance      676—678
Solid-state, defects and free energy calculations      622—630
Solid-state, energy minimisation methods      295—300
Solid-state, force fields for      236—240
Solid-state, quantum mechanical methods for studying      138—160
Solvation/solvents      320
Solvation/solvents, dielectric models of electrostatic non-bonded interactions      202—204
Solvation/solvents, free energy of      576 592—610
Solvation/solvents, free energy of, continuum models      592—593 598—601
Solvation/solvents, free energy of, electrostatic contributions      593—608
Solvation/solvents, free energy of, non-electrostatic contributions      608—609
Solvation/solvents, free energy of, simple models      609—10
Solvation/solvents, molecular dynamics simulation      387—390
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