Schlick T. Molecular Modeling and Simulation: An Interdisciplinary Guide
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15.5. Future Perspectives 553
Epilogue
The need for accuracy must be weighed against the need for finality.
Comments by the Justices of the U.S. Supreme Court regarding bringing to a close
the uncertain outcome, one month after the elections, of the U.S. Presidential
elections in 2000 between George W. Bush and Albert Gore (2000).
Appendix A
Molecular Modeling Sample Syllabus
Please Note: Article numbers in the Homework column refer to items in the course reading list
(Appendix B).
Class Subject Homework
1
Course and Field Overview:
• What is molecular modeling and how has it evolved?
• What are the practical applications and important
questions?
(Preface and Chapter 1)
1: Introduction to sequence
and structural databases and
to the early molecular model-
ing literature.
Read papers 1,2,3,20,33,42,
44,47,52,54,58.
2
• Continuation of the overview on biomolecular
modeling and simulation, from drug design to new
materials.
• Discussion of the 1959 paper of Alder & Wainwright
and 1971 work of Rahman & Stillinger: difficulties
then and now.
• Introduction to interesting biomolecular modeling
problems: protein folding, protein misfolding, nucleic
acid/protein interactions, and RNA folding.
(Chapter 2)
2: Retrieval of structural
information from the Protein
Data Bank (PDB), and the
display, manipulation, and
analysis of three-dimensional
biomolecular structures with
the Insight II molecular
graphics package. Explore
kinemage tutorials.
Read papers 5,8,30,31,34,37
3
• Minitutorial on protein structure: amino acid
repertoire, primary to quaternary structure, protein
structure classification.
• Kinemage tutorial demonstration: folding motifs
and major protein classes.
(Chapters 3 & 4)
3: Construction and analysis
of the pentapeptide Met-
enkephalin with the Insight II
program.
Read papers 2,4,6.
4
• Discuss homework assignments 1 and 2.
• Minitutorial on nucleic acid structure: building
blocks, backbone conformational flexibility, helical
parameters, and DNA supercoiling.
(Chapters 5–7)
4: Generation and analysis of
Ramachandran plots for pro-
teins and introduction to the
NDB.
Read papers 23,29,47,50.
5
Guest Lecturer: The Nucleic Acid Database and the
‘New Protein Databank’ (RCSB), Prof. Helen Berman
(Rutgers University, Department of Chemistry),
Director of NDB and RCSB.
5: Analysis of Protein/DNA
Complexes with Insight and
NDB.
Read papers 7, 21.
6
• Discuss homework assignment 4.
• Computational and theoretical approaches to struc-
ture prediction (from the quantum-mechanical to the
molecular mechanical description).
(Chapters 8 & 9)
6 (MIDTERM):
Sequence/Structure/Function
Relationships in Proteins,
A Contest!
Read papers 22,36,38,56.
558 Appendix A. Molecular Modeling Sample Syllabus
Table A.1: (continued)
Week Subject Homework
7
Guest Lecturer: Protein Structure Modeling,Dr.An-
drej Sali, expert in protein modeling.
7: Molecular mechanics force
fields: approximations, varia-
tions, and the assessment of
results with respect to exper-
iment and other simulations
(papers 10,11,15,16).
Read papers 13,14,17,24.
8
Amer. Chem. Soc. 1990 videotapes: Molecular Mod-
eling in Biological Systems: 1 – Peter Kollman,
“Methods in Molecular Modeling”, 4 – Panel
Discussion.
9
Guest Lecturer: Ab Initio Calculation of Protein
Structure by Global Optimization of Potential Energy,
Prof. Harold Scheraga (Cornell University, Depart-
ment of Chemistry), pioneer of protein force fields and
computation of protein structure.
8: A bit of programming:
nonbonded versus bonded
energy computations.
10
MIDTERM class presentations
11
• Continue MIDTERM presentations.
•
Force Field Debate!
9 (TERM PROJECT):
The Successes (Fail-
ures?) of Molecular Model-
ing.
Read papers 9,18,19.
12
• Molecular mechanics force fields — origin, varia-
tions, and parameterization.
• Special topics — molecular topology: book-keeping
and data structures, potential energy differentiation.
• Special issues in nonbonded energy computations
— spherical cutoffs, fast electrostatics by the multi-
pole method, periodic boundary conditions, and the
Ewald summation.
(Chapter 10)
10: Experiments in Geometry
Structure Optimization: Min-
imization of Biphenyl with
Insight II/Discover.
Read paper 12.
13
• Go over Assignment 8, including general discussion
of programming and timing strategies.
• Optimization techniques for multivariate functions
in computational chemistry.
(Chapter 11)
11: A global optimization
contest for a pentapeptide!
Read papers 25,26.
14
Monte Carlo Simulations.
(Chapter 12)
12: An exercise in Monte
Carlo.
13 (Optional): Advanced ex-
ercises in minimiza-
tion and MC.
Read papers 27,28,32,41,
53,57,59.
15
Molecular dynamics simulations —
theory and practice.
(Chapters 13 & 14)
14 (Optional): Advanced ex-
ercises in molecular dynam-
ics.
15 (Optional): Scaling of
protein conformations and
folding simulations.
Appendix B
Article Reading List
Before 1970
1. B. J. Alder and T. E. Wainwright, “Studies in Molecular Dynamics. I. General
Method”, J. Chem. Phys. 31, 459–466 (1959).
2. G. N´emethy and H. A. Scheraga, “Theoretical Determination of Sterically Allowed
Conformations of a Polypeptide Chain by a Computer Method”, Biopolymers 3,
155–184 (1965).
1970s
3. A. Rahman and F. H. Stillinger, “Molecular Dynamics Study of Liquid Water”,
J. Chem. Phys. 55, 3336–3359 (1971).
4. P. Y. Chou and G. D. Fasman, “Prediction of Protein Conformation”, Biochemistry
13, 222–245 (1974).
5. M. Levitt and A. Warshel, “Computer Simulation of Protein Folding”, Nature 253,
694–698 (1975).
6. M. Levitt and C. Chothia, “Structural Patterns in Globular Proteins”, Nature 261,
552–558 (1976).
1980s
7. S. Lifson, “Potential Energy Functions for Structural Molecular Biology”, in Meth-
ods in Structural Molecular Biology, pp. 359–385, D. B. Davies, W. Saenger, and
S. S. Danyluk, Eds., Plenum Press, London (1981).
8. M. Karplus and J. A. McCammon, “The Dynamics of Proteins”, Sci. Amer. 254,
42–51 (1986).
9. M. S. Friedrichs and P. G. Wolynes, “Toward Protein Tertiary Structure Recognition
by Means of Associative Memory Hamiltonians”, Science 246, 371–373 (1989).
10. I. K. Roterman, M. H. Lambert, K. D. Gibson, and H. A. Scheraga, “Comparison
of the CHARMM, AMBER and ECEPP Potentials for Peptides. I. Conformational
Predictions for the Tandemly Repeated Peptide (Asn-Ala-Asn-Pro)
9
”, J. Biomol.
Struct. Dyn. 7, 391–419 (1989a).
11. I.K.Roterman,M.H.Lambert,K.D.Gibson,andH.A.Scheraga,“Compari-
son of the CHARMM, AMBER and ECEPP Potentials for Peptides. II. φ–ψ Maps
for N
´
-Methyl Amide: Comparisons, Contrasts and Simple Experimental Tests”,
J. Biomol. Struct. Dyn. 7, 421–453 (1989b).
560 Appendix B. Article Reading List
1990–1992
12. M. Karplus and G. A. Petsko, “Molecular Dynamics Simulations in Biology”,
Nature 347, 631–639 (1990).
13. J. Skolnick and A. Kolinski, “Simulations of the Folding of a Globular Protein”,
Science 250, 1121–1125 (1990).
14. F. M. Richards, “The Protein Folding Problem” Sci. Amer. 264, 54–63 (1991).
15. P. A. Kollman and K. A. Dill, “Decisions in Force Field Development: An Alterna-
tive to Those Described by Roterman et al.”, J. Biomol. Struct. Dyn. 8, 1103–1107
(1991).
16. K. B. Gibson and H. A. Scheraga”, “Decisions in Force Field Development: Reply
to Kollman and Dill”, J. Biomol. Struct. Dyn. 8, 1109–1111 (1991).
17. H. A. Scheraga, “Predicting Three-Dimensional Structures of Oligopeptides”, in
Reviews in Computational Chemistry, K. B. Lipkowitz and D. B. Boyd, Editors,
Vol. 3, pp. 73–142, VCH Publishers, New York (1992).
18. T. Schlick, “Optimization Methods in Computational Chemistry”, in Reviews in
Computational Chemistry, K. B. Lipkowitz and D. B. Boyd, Editors, Vol. 3,
pp. 1–71, VCH Publishers, New York (1992). See also T. Schlick, “Geometry Opti-
mization”, in the Encyclopedia of Computational Chemistry, P. von Ragu´eSchleyer
(Editor-in-Chief) and N. L. Allinger and T. Clark and J. Gasteiger and P. A. Kollman
and Schaefer, III, H. F., Editors, Vol. 3, pp. 1136–1157, John Wiley & Sons, West
Sussex, England (1998).
1993–1995
19. R. A. Abagyan and M. M. Totrov, “Biased Probability Monte Carlo Conformational
Searches and Electrostatic Calculations for Peptides and Proteins”, J. Mol. Biol.
235, 983–1002 (1994).
20. J. A. Board, Jr., L. V. Kal´e, K. Schulten, R. D. Skeel, and T. Schlick, “Modeling
Biomolecules: Larger Scales, Longer Durations”, IEEE Comp. Sci. Eng. 1, 19–30
(Winter 1994).
21. K. B. Lipkowitz, “Abuses of Molecular Mechanics. Pitfalls to Avoid”, J. Chem.
Educ. 72, 1070–1075 (1995).
22. B. Honig and A. Nicholls, “Classical Electrostatics in Biology and Chemistry”,
Science 268, 1144–1149 (1995).
1996–1998
23. B. Cipra, “Computer Science Discovers DNA”, in What’s Happening in the Math-
ematical Sciences, pp. 26–37 (P. Zorn, Ed.), American Mathematical Society,
Colonial Printing, Cranston, RI (1996).
24. A. Neumaier, “Molecular Modeling of Proteins and Mathematical Prediction of
Protein Structure”, SIAM Review 39, 407–460 (1997).
25. K. A. Dill and H. S. Chan, “From Levinthal to Pathways to Funnels”, Nature Struc.
Biol. 4, 10–19 (1997).
Appendix B. Article Reading List 561
26. T. Lazaridis and M. Karplus, “ ‘New View’ of Protein Folding Reconciled with the
Old Through Multiple Unfolding Simulations”, Science 278, 1928–1931 (1997).
27. T. Schlick, E. Barth, and M. Mandziuk, “Biomolecular Dynamics at Long Time-
steps: Bridging the Timescale Gap Between Simulation and Experimentation”, Ann.
Rev. Biophys. Biomol. Struc. 26, 179–220 (1997).
28. E. Barth and T. Schlick, “Overcoming Stability Limitations in Biomolecular
Dynamics: I. Combining Force Splitting via Extrapolation with Langevin Dynamics
in
LN”, J. Chem. Phys. 109, 1617–1632 (1998).
29. M. Gerstein and M. Levitt, “Simulating Water and the Molecules of Life”, Sci. Amer.
279, 101–105 (1998).
30. Y. Duan and P. A. Kollman, “Pathways to a Protein Folding Intermediate Observed
in a 1-Microsecond Simulation in Aqueous Solution”, Science 282, 740–744 (1998).
31. H. J. C. Berendsen, “A Glimpse of the Holy Grail”, Science 282, 642–643 (1998).
32. L. S. D. Caves, J. D. Evanseck, and M. Karplus, “Locally Accessible Conformations
of Proteins: Multiple Molecular Dynamics Simulations of Crambin”, Prot. Sci. 7,
649–666 (1998).
33. W. F. van Gunsteren and A. E. Mark, “Validation of Molecular Dynamics
Simulation”, J. Chem. Phys. 108, 6109–6116 (1998).
34. X. Daura, B. Juan, D. Seebach, W. F. Van Gunsteren, and A. Mark, “Reversible
Peptide Folding in Solution by Molecular Dynamics Simulation”, J. Mol. Biol. 280,
925–932 (1998).
1999–2003
35. A. L. Delcher, S. Kasif, R. D. Fleischmann, J. Peterson, O. White, and S. L.
Salzberg, “Alignment of Whole Genomes”, Nuc. Acids Res. 27, 2369–2376 (1999).
36. D. Baker and A. Sali, “Protein Structure Prediction and Structural Genomics”,
Science 294, 93–96 (2001).
37. R. Bonneau and D. Baker, “Ab Initio Protein Structure Prediction: Progress and
Prospects”, Annu. Rev. Biophys. Struc. 30, 173–189 (2001).
38. J. C. Whisstock and A. M. Lesk, “Prediction of Protein Function from Protein
Sequence and Structure”, Quart. Rev. Biophys. 36, 173–189 (2001).
39. H. Kitano, “Systems Biology: A Brief Overview”, Science 295, 1662–1664 (2002).
40. R. M. Karp, “Mathematical Challenges from Genomics and Molecular Biology”,
Notices Amer. Math. Soc. 49, 544–553 (2002).
41. M. Karplus and J. A. McCammon, “Molecular Dynamics simulations of Biomole-
cules”, Nat. Struc. Biol. 9, 307–340 (2003).
42. J. Norberg and L. Nilsson, “Advances in Biomolecular Simulations: Methodology
and Applications”, Quart. Rev. Biophys. 36, 257–306 (2003).
43. J. D. Storey and R. Tibshirani, “Statistical Significance for Genomewide Studies”,
Proc. Natl. Acad. Sci. USA 100, 9440–9445 (2003).
562 Appendix B. Article Reading List
44. F. S. Collins, E. D. Green, A. E. Guttmacher, and M. S. Guyer, “A Vision for the
Future of Genomics Research”, Nature 422, 835–847 (2003).
45. T. Ideker and D. Lauffenburger, “Building with a Scaffold: Emerging Strategies for
High- to Low-Level Cellular Modeling”, Trends Biotech. 21: 255–262 (2003).
46. R. Jansen, H. Yu, D. Greenbaum, Y. Kluger, N. J. Krogan, S. Chung, A. Emili,
M. Snyder, J. F. Greenblatt, and M. Gerstein, “A Bayesian Networks Approach for
Predicting Protein-Protein Interactions from Genomic Data”, Science 17, 449–453
(2003).
2004–
47. J. E. Cohen, “Mathematics is Biology’s Next Microscope, Only Better; Biology
is Mathematics’ Next Physics, Only Better”, PLoS Biology 2 (e439), 2017–2023
(2004).
48. M. Kellis, N. Patterson, B. Birren, B. Berger, and E. S. Lander, “Methods in Com-
parative Genomics: Genome Correspondence, Gene Identification and Regulatory
Motif Discovery”, J. Comp. Biol. 11, 319–355 (2004).
49. W. C. Winkler, A. Nahvi, A. Roth, J. A. Collins and R. R. Breaker, “Control of Gene
Expression by a Natural Metabolite-Responsive Ribozyme”, Nature 428, 281–286
(2004).
50. A. Hastings et al., “Quantitative Bioscience for the 21st Century”, Bioscience 55,
511–517 (2005).
51. J. C. Phillips, R. Braun, W. Wang, J. Gumbart, E. Tajkhorshid, E. Villa, C. Chipot,
R. D. Skeel, L. Kal´e and K. Schulten, “Scalable Molecular Dynamics with NAMD”,
J. Comp. Chem. 26, 1781–1802 (2005).
52. T. Schlick, “The Critical Collaboration Between Art and Science: Applying An Ex-
perimentonaBirdinanAirPumpto the Ramifications of Genomics on Society”,
Leonardo 38 (4), 323–329 (2005).
53. M. Karplus and J. Kuriyan, “Molecular Dynamics and Protein Function”, Proc.
Natl. Acad. Sci. USA 102, 6679–6685 (2005).
54. W. F. van Gunsteren et al., “Biomolecular Modeling: Goals, Problems, Perspec-
tives”, Angew. Chem. Int. Ed. 45, 4064–4092 (2006).
55. E. Segal, Y. Fondufe-Mittendorf, L. Chen, A. Th˚astr¨om,Y.Field,I.K.Moore,
J.-P. Z. Wang, and J. Widom, “A Genomic Code for Nucleosome Positioning”,
Nature 442, 772–778 (2006).
56. J.-M. Chandonia and S. E. Brenner, “The Impact of Structural Genomics: Expecta-
tions and Outcomes”, Science 311, 347–351 (2006).
57. S. A. Adcock and J. A. McCammon, “Molecular dynamics: survey of methods for
simulating the activity of proteins”, Chem. Rev. 106: 1589–1615 (2006).
58. M. A. Gerstein et al., “What is a Gene, post ENCODE? History and Updated
Definition”, Genome Research 17, 669–681 (2007).
59. E. H. Lee, J. Hsin, M. Sotomayor, G. Comellas, and K. Schulten, “Discovery
Through the Computational Microscope”, Structure 17: 1295–1306 (2009).
Appendix C
Supplementary Course Texts
1. M. P. Allen and D. J. Tildesley. Computer Simulation of Liquids. Oxford University
Press, New York, NY, 1990.
[Good advanced reference book for molecular simulations.]
2. A. D. Bates and A. Maxwell. DNA Topology, second edition. Oxford University
Press, New York, NY, 2005.
[Beautiful paperback on the higher organizational forms of DNA.]
3. O. M. Becker, A. D. Mackerell Jr., B. Roux, and M. Watanabe, Editors. Com-
putational Biochemistry and Biophysics. Marcel Dekker Inc, New York, NY,
2001.
[Useful resource to computational chemists on various modeling techniques
such as molecular mechanics and dynamics, conformational analysis, long-
range interactions, implicit solvation, and free energy methods.]
4. J. M. Berg, J. L. Tymoczko, and L. Stryer, Biochemistry. W. H. Freeman, New York,
NY, latest edition (sixth in May 2006).
[Wonderful biochemistry textbook, up to date.]
5. H. J. C. Berendsen. Simulating the Physical World: Hierarchical Modeling from
Quantum Mechanics to Fluid Dynamics. Cambridge University Press, Cambridge,
UK, 2007.
[Introduction to fundamental theory and applications of computer modeling
and simulation, from quantum mechanics to fluid dynamics, with practical
recommendations and sample Python programs.]
6. V. A. Bloomfield, D. M. Crothers, and I. Tinoco, Jr. Nucleic Acids: Structures,
Properties, and Functions. University Science Books, Sausalito, CA, 2000.
564 Appendix C. Supplementary Course Texts
[Comprehensive account of nucleic acids at an advanced level, with
emphasis on biological function and experimental techniques. The first part
describes nucleic acid properties on the atomic and molecular levels as
deduced by various experimental techniques. The second part presents
macromolecular features of nucleic acids in solution (e.g., dynamics be-
havior, DNA supercoiling). The third part covers noncovalent interactions of
nucleic acids and other molecules (ions, drugs, proteins) and higher-order
structures due to cellular packing.]
7. C. Branden and J. Tooze. Introduction to Protein Structure, second edition. Garland
Publishing Inc., New York, NY, 1999. (www.proteinstructure.com/).
[A modern and nicely illustrated protein structure textbook dealing with basic
structural principles (part 1) and other topics (part 2, broadly grouped under
the heading of relationships among structure, function, and engineering).
Part 2 includes chapters on transcription regulation, signal transduction,
immune regulation, membrane and fibrous proteins, and virus structures.]
8. P. Bratley, B. L. Fox, and L. E. Schrage. A Guide to Simulation, second edition.
Springer, New York, NY, 1987.
[Good introduction to Monte Carlo simulations.]
9. C. L. Brooks, III, M. Karplus, and B. M. Pettitt. Proteins: A Theoretical Perspective
of Dynamics, Structure, and Thermodynamics. John Wiley & Sons Inc., New York,
NY, 1988.
[Nice collection on protein simulations.]
10. U. Burkert and N. L. Allinger. Molecular Mechanics. American Chemical Society,
Washington D.C., 1982.
[Excellent introduction to molecular mechanics.]
11. C. R. Cantor and P. R. Schimmel. Biophysical Chemistry. Parts 1,2,3. W. H.
Freeman, San Francisco, CA, 1980.
[Classic text and reference to many aspects of biophysical chemistry.]
12. D. Chandler. Introduction to Modern Statistical Mechanics. Oxford University
Press, New York, NY, 1987.
[Good introduction to Monte Carlo methods.]
13. N. C. Cohen, Editor. Guidebook on Molecular Modeling in Drug Design. Academic
Press Inc., San Diego, CA, 1996.
[Reference for molecular modeling as applied to drug design problems,
containing contributed chapters by industrial and academic scientists, on
problem formulation (database analysis, docking), modeling tools, and
medicinal chemistry applications.]
14. C. J. Cramer. Essentials of Computational Chemistry: Theories and Models, second
edition. John Wiley & Sons Inc., Hoboken, NJ, 2004.
[Good introduction to quantum mechanical and classical/quantum mechan-
ical modeling and theory.]