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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
Locally enhanced sampling      575—576
LogP      668—670
London force      204—205
Long time-tails, molecular dynamics      377
Long-range correction      327
Long-range forces and computer simulation      334—343
Loop conformations      541—542
Lorentz — Berthelot mixing rules      210
Low-mode search      478—479
Lowdin population analysis      80
Lower-energy regions      564
Lowest unoccupied molecular orbit      79 112 293—294
LR (linear response)      588—589 591 631—632
LSDFT (local spin density functional theory)      129 135
LUDI program      689
LUMO (lowest unoccupied molecular orbit)      79 112 293—294
Lysine      510 525 556—557
MACCS system      645
Maclaurin series      11
Magnesium      238 623 626
Many-body, effects in empirical potentials      212—214
Many-body, perturbation theory      114—117
Many-body, potentials      241
Mapping, adiabatic      286
Mapping, distance      651
Mapping, pharmacophore      648
Mapping, Ramachandran      459—460 514 543 547
Marker atom      329—330
Markov chain      414—415
Markov models, hidden      536—537 538
Marsaglia random number generator      420 453—454
Mass-weighted coordinates      274—275
Mathematical concepts      10—24
Mathematical concepts, complex numbers      16—18
Mathematical concepts, multiple integrals      19—20
Mathematical concepts, series expansions      10—11
Mathematical concepts, statistics      20—21 (see also “Eigenvalues” “Fourier” “Lagrange” “Matrices” “Vectors”)
Matrices      2—3 9 12—16 415
Matrices, adjacency      647
Matrices, charge density      58—59
Matrices, distance      652
Matrices, elastic constant      296—297
Matrices, PAM      524—526 531 556—557
Matrices, positive definite      16 258
Matrices, statistical weight      430
Matrices, stochastic      415 (see also “Fock matrix” “Hessian” “Z-matrix”)
Maxima      273
Maximal segment pair      531—533
Maximum dissimilarity algorithms      683—684
Maximum likelihood method      657—658
MaxSum and MaxMin      683—684 685
Maxwell — Boltzmann distribution      365 367 384
Mayer bond order      83
Mc      see “Monte Carlo”
MCSCF (multiconfiguration SCF)      113
MCSS (multiple-copy simultaneous search)      688
MDL (Molecular Design mol) format      643—644
Mean field approach      307—309
Mean square end-to-end distance, polymers      426
Mean squared displacement      322—323
Mechanics, molecular      see “Force field”
Mesoscale modelling      402—404
Messenger RNA (mRNA)      509
Met-enkephalin      517
Metals      147 589 607 626 649—650 693
Metals, force field potentials for      240—245
Methane, bond order      83
Methane, force fields      189
Methane, Monte Carlo simulation      441—442
Methane, octopole moment      76
Methane, population analysis      79
Methane, SMILES notation      644
Methanol      573
Methionine      511 525 556—555
Methyl chloride      612—63 614 676—667
Methylalanine      583—58
Methylene group      160 162 330 396 448
Methylene group, energy minimisation methods      280 291
Methylene group, force fields      181 221
Metric matrix      469
Metrisation      472
Metropolis Monte Carlo simulation      306 433 436 437 447
Metropolis Monte Carlo simulation, conformational analysis      467 505
Metropolis Monte Carlo simulation, implementation      417—420
Metropolis Monte Carlo simulation, new molecules      663 685 691
Metropolis Monte Carlo simulation, proteins      518
Metropolis Monte Carlo simulation, theoretical background      414—416
Microcanonical ensemble, definition      307
MINDO/3      86 94—96 102—103
Minima      272—273
Minimal basis set      69—70
Minimisation      see “Energy minimisation”
Minimum image convention and computer simulation      324—334
Mixing rules      210
MM2/MM3/MM4 programs      8 615
MM2/MM3/MM4 programs, force fields      169—171 173 176 179 187 211 233—234
MNDO (modified neglect of diatomic overlap)      86 96—97 98—99 102—103 192
MOD function      418—419
Modeller program      541 549
Modified INDO (MINDO/3)      86 94—96 102—103
Modified neglect      see “MNDO”
Molar refractivity      671
Molecular dynamics simulation      354—409 623
Molecular dynamics simulation of chain amphiphiles      394—404
Molecular dynamics simulation, computer simulation      305—306 307
Molecular dynamics simulation, conformational analysis      457 475—476 483—489
Molecular dynamics simulation, conformational changes from      392—393
Molecular dynamics simulation, constant pressure dynamics      385—387
Molecular dynamics simulation, constant temperature dynamics      382—385
Molecular dynamics simulation, constraint dynamics      368—374
Molecular dynamics simulation, continuous methods      355—364
Molecular dynamics simulation, energy conservation in      405—406
Molecular dynamics simulation, ensemble      653
Molecular dynamics simulation, free energy calculations      564 572 577 579 581 588 616—622 628
Molecular dynamics simulation, Monte Carlo compared with      307 387 452—453
Molecular dynamics simulation, new molecules      664
Molecular dynamics simulation, proteins      552
Molecular dynamics simulation, setting up and running      364—368
Molecular dynamics simulation, simple models      353—354
Molecular dynamics simulation, solvent effects      387—390
Molecular dynamics simulation, time-dependent properties      374—382 (see also “Computer simulation”)
Molecular field analysis      708—711
Molecular fitting      490—491
Molecular fragments      see “Fragments”
Molecular modelling      see “Advanced ab initio” “Computer concepts conformational “Energy force “Free “Molecular Monte new “Proteins” “Quantum
Molecular orbital theories, semi-empirical      86 89—96 102—103
Molecular surface      see “Surface”
Moller — Plesset      see “MP”
Moments theorem      241—2
Monomers      289—290 423 550
Monomers, new molecules      712—713 717—718
Monte Carlo simulation      410—456
Monte Carlo simulation, bias      432—433 443—450
Monte Carlo simulation, chemical potential, calculating      442—443
Monte Carlo simulation, computer      306—307
Monte Carlo simulation, conformational analysis      457 475—476 479 483 504—505
Monte Carlo simulation, density functional theory      130
Monte Carlo simulation, different ensembles, sampling from      438—442
Monte Carlo simulation, force fields      189
Monte Carlo simulation, free energy calculations      564 577 579 588
Monte Carlo simulation, free energy calculations, chemical reactions      613 616
Monte Carlo simulation, free energy calculations, PMF      581—582 584
Monte Carlo simulation, free energy calculations, solid-state defects      623 628
Monte Carlo simulation, free energy calculations, thermodynamic perturbation      572—573
Monte Carlo simulation, Gibbs ensemble      450—451
Monte Carlo simulation, integration, calculating properties by      412—414
Monte Carlo simulation, molecular dynamics compared with      307 387 452—453
Monte Carlo simulation, molecules      420—423
Monte Carlo simulation, molecules, new      662—663 685 691
Monte Carlo simulation, polymers      423—431
Monte Carlo simulation, proteins      517—519 551
Monte Carlo simulation, quasi ergodicity      433—438
Monte Carlo simulation, random number generators      418—420 453—454 Metropolis”)
Monte Carlo, configurational bias      443—450
Monte Carlo, force-bias      432
Monte Carlo, Grand canonical      440—442
Monte Carlo, smart      432
MOP AC program      8 99
Morgan algorithm      644
Morokuma analysis      122—124
Morse potential/curve      170—172 210
Motifs      522
Mott — Littleton method      623—624 625—627
MP (Moller — Plesset) perturbation theory      114 115—116 119
MR (molar refractivity)      671
MS (Murtaugh — Sargent) method      269—270
MSP (maximal segment pair)      531—533
Mthoxypromazine      678
Mulliken population analysis      79—80 189
Multicanonical Monte Carlo simulation      435—438
Multiconflguration SCF      113
Multiple integrals      19—20
Multiple linear regression      666 699 702
Multiple sequence alignment      534—537
Multiple-copy simultaneous search      688
Multipole, electric, calculation of      75—77
Multipole, fast      341—343 364
Multipole, models      195—197 219
Multivariate problems      708
Murtaugh — Sargent method      269—270
Mutation, operator      480
Mutation, probability matrices for proteins      556—557
N, N-dimethyl-ketopropanamide      230
naphthalene      233
NCC (Nieser — Corongiu — Clementi) model      219—220
NDDO (neglect of diatomic differential overlap)      86 93—94 95 96
Nearly free-electron approximation      142 147—153
Needleman — Wunsch algorithm      526—529 534
Neglect of differential overlap      86 89—96
Neighbour lists      325—327 493—496
Net (partial) atomic charges      157—159 181
Net dipole moment      378—379
Netropsin      270—271
Neural networks and QASR      703—705
New molecules      640—726
New molecules, 3D      674—675 687
New molecules, 3D, databases      659—661 679
New molecules, 3D, pharmacophores      648—659 674—675 687
New molecules, 3D, searching      645 647 667—668
New molecules, 3D, similarity      678—679 (see also “QSAR”)
New molecules, combinatorial libraries      711—719
New molecules, computer representations      642—647
New molecules, de novo structure based ligand design      687—694
New molecules, descriptors      668—679
New molecules, discovery of drugs      640—641
New molecules, diverse sets of compounds, selecting      680—687
New molecules, docking      661—668 689
New molecules, partial least squares      702 706—711
New molecules, similarity      668 676—679
Newton — Raphson energy minimisation      267—268 270 288 625
Newton’s laws      304 309 353 366 371
Niching      481
Nickel oxide      147
Nicotine/nicotinic pharmacophore      653 678
Nitrogen      490
Nitrogen, amide      660
Nitrogen, basis sets      73
Nitrogen, bond order      83
Nitrogen, charge models      187—8
Nitrogen, distributed multipole model      196
Nitrogen, electrostatic potentials      188
Nitrogen, force fields      181
Nitrogen, substituents      693
NM23      547
NMR and X-ray crystallography      316
NMR and X-ray crystallography, conformational analysis      468 474—475 483—489 490
NMR and X-ray crystallography, molecular dynamics simulation      379 383 395
NMR and X-ray crystallography, new molecules      647 659 661 667 689 691 693 704 713
NMR and X-ray crystallography, proteins      516 522 546—547 552 512 514
Nodes on graphs      642—643
Nodes on search trees      461
NOESY (nuclear Overhauser enhancement spectroscopy)      474—475 486 488
Non-bonded cutoffs      324—334
Non-bonded interactions      166 181—212 324
Non-bonded interactions, cell multipole method for      341—343
Non-bonded interactions, electrostatic      166 181—204
Non-bonded interactions, neighbour lists      325—327
Non-bonded interactions, Van der Waals      166 204—212
Non-derivative energy minimisation      258—261
Non-electrostatic contributions to solvation free energy calculations      608—609
Non-holonormc constraints      370
Non-periodic boundary methods      320—321
Normal distribution      see “Gaussian functions”
Normal mode analysis and energy minimisation      273—278
Normal vibrational modes      274
Nuclear Overhauser      see “NOESY”
Nucleic acids      196—197
o-methylacetanilide      670
Octopole      76 181
One-electron atoms      30—34
One-electron integrals      50—51
ONIOM approach      615
Onsager dipole model      593—595
Open-shell systems      108—110
Operators      28—29 53 57 114 480—481
OPLS (optimised parameters for liquid simulations)      210 228 599
Orbital approximate theories      86
Orbital calculations, molecular      26 41—51
Orbital electronegativity      192—193
Orbital energy of closed-shell system      51
Orbital energy of general polyelectronic system      46—50
Orbital hydrogen      41—46
Orbital linear combination of atomic      41—42 56 100 241
Orbital one- and two-electron integrals      50—51
Orbital semi-empirical      86 89—96 102—103
Orbital semi-empirical, total electron density      77—79 (see also “STOs”)
Orbital virtual      61 (see also “Kohn — Sham”)
Orbital-based approach to band theory      142—146
Order of integration algorithm      358
Order, bond      81—83
Order, parameters      321—322
Orientational correlation      379—380
Orthogonalisation, symmetric      60
Orthonormal wavefunctions      30
Oscillating charge      201—202
Out-of-plane bending      176—178
Outside-in Hgand design      687—688
Overlap, differential      86 88—96
Overlap, forces      see “Repulsive forces”
Overlap, integral      52
Oxides      147 238
Oxygen bonds/interactions      98 237 328 620 652
Pairwise potential models      240—241
PAM matrices      524—526 531 556—557
Parameters      567 599
Parameters, force field      221 224—225 228—232
Parameters, substituent      695—697 (see also “Verlet”)
Partial (net) atomic charges      157—159 181
Partial equalisation of orbital, electronegativity      192—193
Partial least squares (PLS)      702 706—711
Partition, coefficients      572—573 668—671
Partition, electron density      80—81
Partition, free energy      574—576
Partition/partitioning      683—685
Partitioning, coefficients      572—573 668—671
Partitioning, electron density      80—81
Partitioning, free energy      574—576
Pattern recognition      491—497
Pauli principle      206
PCA (principal components analysis)      497—499 681 686
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