Computer Science 260
Algorithms in Structural Molecular Biology and Biophysics


Spring, 2008

Tu,Th 1:15 - 2:30pm
Place: D243, LSRC

Professor Bruce Randall Donald
TA: Lirong Xia (lxia at cs.duke.edu)

www.cs.duke.edu/brd/Teaching/Bio/asmb/current/

This course is cross listed as:
Structural Biology & Biophysics (SBB) 251,
and Computational Biology & Bioinformatics (CBB) 230.
If you have any difficulty registering
for the cross-listed courses please contact
the program assistant in SBB or CBB,
and Diane Riggs in Computer Science.






Overview | Schedule | Presentation Schedule | Bibliography | Some Relevant WWW Links
How to give a good talk | Projects | Reports | Grading | "The Queue"

Please Note:

This course will be offered next year with the number Comp Sci 261/CBB 230/SBB 251. For arcane technical reasons this year the number is Comp Sci 260/CBB 230/SBB 251. However, this is a different course from the course that is on the books as Comp Sci 260, and students should ignore that listing. Full information on the course is below.

Overview

Some of the most challenging and influential opportunities for computer science arise in developing and applying information technology to understand molecular interactions in the cell. Recent work shows that many algorithmic techniques may be fruitfully applied to the challenges of computational structural molecular biology. This research may lead to computer systems and algorithms that are useful in structural molecular biology, proteomics, and rational drug design.

Concomitantly, a wealth of interesting computational problems arise in proposed methods for discovering new pharmaceuticals. Among these problems are: identifying the low-energy conformations of molecules, interpreting protein NMR (nuclear magnetic resonance) and X-ray data, inferring constraints on the shape of active drug molecules based on measurements of activity of related drug molecules, and docking candidate drug molecules to known protein targets, the design of novel proteins.

Computational structural biology is at the core of scientific computation, and both solves real biological problems, and contributes back to computer science. In this course, we will use and extend computational techniques including statistical methods, provably-good approximation algorithms, AI techniques, numerical methods, SVD and PCA, computer algebra, computational geometry, optimization, branch and bound algorithms, expectation/maximization, graphical models, graph algorithms, stochastic labeling and Markov random field paradigms. In this field, computational techniques are central, and the applications present intriguing problems to computer scientists who design algorithms and implement systems. We will develop both upper and lower bounds in the setting of algorithms for biophysical problems in structural molecular biology.

Prerequisites and Background:

This course is open to graduate students, and advanced undergraduates with a background in algorithms (CS 230). A background in biology is useful but not required. Students should be interested in doing some outside reading in biochemistry and biophysics. CS and CBB graduate students may take a diagnostic placement exam, given each fall by the Computer Science Department, to determine whether they need to take CS 230. This course may be taken if you have taken CS 230, placed out of it, or have permission of the instructor.

Students with a life sciences or Biophysics background such as Biochemistry, SBB, Physics, Physical Chemistry etc. are welcome in this course; please talk with me about your background first to make sure you're comfortable with the computer science concepts we will use and learn.

You may wish to read about research at Duke in this area: http://www.cs.duke.edu/~brd/

Here is the collection of all lecture notes. The lecture notes are not comprehensive but they are designed to help you. (version 2007)


How to Give a Good Talk

If you are scheduled to give a talk, I've prepared a set of hints for giving a good talk. Follow every atom of every letter of every word of advice in these rules.

Here is a list of ways to give a terrible talk, that you should read, and then avoid, evade, elude, shun, and eschew (avoid stresses forethought and caution in keeping clear of danger or difficulty; evade implies adroitness, ingenuity, or lack of scruple in escaping or avoiding; elude implies a slippery or baffling quality in the person or thing that escapes; shun often implies an avoiding as a matter of habitual practice or policy and may imply repugnance or abhorrence; eschew implies an avoiding or abstaining from as unwise or distasteful).

For your talk, make slides (either by hand, or electronically). Do not use the board during your talk. The reason for this is that all students can learn in the course of this class, to give a good talk using slides. To give a good talk using the board -- that is, to teach board technique, is much more difficult, and beyond a scope of this course. Do not go back and forth between your slides and the board during your talk. If there's something that you need to explain that you plan to use the board for -- don't! Instead, put this material on your slides!

The one exception is that if you get a question from the audience, you may use the board to answer it. However: what you should do is try to anticipate what questions you expect from audience ahead of time, and make extra slides to answer these, to have just in case.

In your talk, try to go into some technical detail. Your goal should be to show the class something technical -- and teach them something concrete and technical rather than the skim over everything. You want to go into some depth -- describe at least two algorithms in detail, show two theorems in detail, etc. Applications are good, but only if you've covered something technical -- an algorithm, a theorem etc. -- first.

Be prepared for your talk. If there are things that you don't understand you need to read more papers on the subject to fill in the holes. This class is not just about reading the assigned papers -- you need to read some background reading if there are things that you don't understand. Basically one strategy to do this is to search for related papers that answer the question, or back-chain from the references in the papers you are assigned. The mind-set to have is: pretend this is research. If there is something you don't understand, you cannot just say 'I don't know.' You have to do some research -- i.e. reading and thinking -- to figure it out, just as you would for your thesis!

Occasionally students want to include a figure from the PDF of the paper in their talk. This is okay -- so long as it is not overdone -- but if you do this be sure to use the "snapshot tool" in Adobe Acrobat. Before using the snapshot tool, increase the size of the image to the maximum possible -- this will make sure that the resolution is sufficient so the image is not blurry in your presentation.

Under no circumstances should you use the "Mac Grab" feature available on a Macintosh -- the resulting PowerPoint will not be machine independent and will only work on a Mac.

Here is an example of how to overdo this business of grabbing images from the paper to use in your talk. Never make these errors!


Projects

Students will be required to do a project. Pick something in computational biology you are interested in, and (a) implement it, (b) analyze it, (c) improve it, (d) extend it, or (e) apply it.

A 4-5 page written project proposal is due on February 12, Tuesday.

Final projects are due on the last day of class. You must

  1. Turn in a written report,
  2. Make a web page about your project, and
  3. Prepare a short presentation for the class on what you did. Make slides for your presentation.


Reports

You may be assigned one or more reports to do during this class. This section discusses what is entailed in a report.

Your reports should:

We do not want a book report or a repeat of the paper's abstract. Rather, we want your considered opinions about the key points indicated above. Of course, if you have an insight that doesn't fit the above format, please include it as well. Your reports will be graded on content, not length. For most of the papers we read, one or two well thought-out paragraphs should be sufficient. You are, of course, welcome to write as much as you want.
If you were not assigned to do an in-class presentation, you must, in addition to the project, write a critique (report) on one of the papers we read. Your critique should be a detailed analysis of the methods presented, their flaws, strengths, and weaknesses. You should consider improvements and extensions in your critique. Reports should be about 10 pages single-spaced.

You must

  1. Turn in a written critique, and
  2. Make a web page about your critique.


Recommended Textbooks

Here is a list of recommended textbooks.

How to Exchange Files

We share a common file system so it is criminal for CS students to send enclosures. Never send enclosures for anything related to this course. If you have an account on the CS Unix Filesystems, send a pointer to the filename. Or, put it on the web and send the URL.


Grading

Grading: Grades will be based upon (a) your presentations in class, (b) your project, (c) class participation/discussion, (d) assigned homework exercises, and (e) scribing approximately two lectures. If you are not giving a presentation, "(a)" will be graded based on your report.


Schedule and Readings

Please check this webpage, and schedule frequently, since I will post new papers and new readings and new assignments frequently, as we proceed through the term.

Please note: These dates and times might move some (see "The Queue", below), as we adapt to the time required to discuss the papers, or if I am unexpectedly called to Washington, etc.

*Papers that are not available online (below) have been handed out on paper.

*RECOMB papers (Proceedings of the Nth Annual International Conference on Computational Molecular Biology (N=1,2,3,4,...)) are available online via the ACM Digital Library.

In case the links at ACM, PNAS, etc. are down, Here is a local copy of many of the papers.

A few papers will be handed out in class. If you miss class, you can copy them from a classmate.

Announcements will be made in class. I will try to post them here, so consult this website.

Here is a useful bibliography of papers (and PDFs) in the area of this course.

Begin schedule
  1. R 1/10
    Presenting: Bruce Donald.
    [Lecture Notes ]
    Introduction to Computational Biology and Chemistry.
     Administrivia.

    Assignment: Fill out and turn in this information sheet.

    Reading:

    Here are some great notes (including a primer, "Molecular Biology for Computer Scientists") written and collected by Mona Singh.

    Assignment:

      Do these tasks:
      • Read about and download RasMol and Pymol on your machine to be able to view and manipulate biopolymers.
      • To read the papers, you will need to be able to download and print PostScript files and Adobe PDF files from the WWW. Please familiarize yourself with how to do this.
  2. T 1/15
    Presenting: Bruce Donald.
    [Lecture Notes ]
    Computational Protein Design
    Abstract
    • Reading 1:
      De Novo Protein Design: Fully Automated Sequence Selection [PDF]
      Science (1997) October 3; 278 (5335):82 B. I. Dahiyat and S. L. Mayo.

    • Computational approaches to Protein Design:
      • Dead-end elimination
      • Dynamic programming
      • Branch & Bound & A* Search
      • Energy minimization
      • Parallelization
  3. R 1/17
    NMR ensemblePresenting: Bruce.
    [Lecture Notes ]
    Proteins and NMR Structural Biology I

    Reading:
    • Outline:
      • Protein structure
        • NMR Data
          • chemical shifts
          • assignment
          • nuclear Overhauser effect (NOE)
            • Algorithms:
              • distance geometry
              • NP hardness
              • simulated annealing/molecular dynamics
          • Scalar Couplings (J-Couplings)
          • Residual Dipolar Couplings (RDCs) (briefly; will cover in more detail later)
        • Algorithms:
          • NOE patterns/graphs
            • Jigsaw
          • GD (briefly; will cover later)
          • MBM/voting (briefly; will cover later)
  4. T 1/22
    NMR ensemblePresenting: Bruce.
    [Lecture Notes] [Lecture Notes ]
    Proteins and NMR Structural Biology II

    Background Reading:
    • Cavanagh et al, chapter 8.
      • Reference: Protein NMR Spectroscopy : Principles and Practice by John Cavanagh, Arthur G., III Palmer, Wayne Fairbrother (Contributor), Nick Skelton (Contributor) Hardcover - 587 pages (April 1996) Academic Pr; ISBN: 0121644901
    • Refer to Wüthrich as needed for reference
      • Reference: NMR of Proteins and Nucleic Acids by Kurt Wuthrich Hardcover - 320 pages (September 1986) John Wiley & Sons; ISBN: 0471828939
    • Online Tutorials, Notes, and References on NMR



    Reading:
    • C. Bailey-Kellogg, A. Widge, J. J. Kelley III, M. J. Berardi, J. H. Bushweller, and B. R. Donald. The NOESY Jigsaw: Automated protein secondary structure and main-chain assignment from sparse, unassigned NMR data. Jour. Comp. Biol., 3-4(7):537-558, 2000. [PDF]
    • I will motivate the algorithms in the paper above by briefly talking in the beginning of the lecture about a specific biological example, namely a combined use of NMR and computational search in drug design. Please also visualize the PDB files here. This will also cover some material on the mechanisms of transcription factors, and a primer on Cancer biology, both interesting topics for computational biologists.
      • Graph Algorithms in NMR Structural Biology
        • graph algorithms
        • NP completeness
        • randomized algorithms
        • alignment algorithms
  5. W 1/23, 5:00-6:00 pm, LSRC D344
    Presenting: Lirong Xia
    Topic: Basic concepts and notations in algorithms and computational complexity theory

    Content
    • Complexity: P and NP, NP-hard problems.
      Reading: Chapter 34 of Introduction to Algorithms, Second Edition Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein, 2001, the MIT Press.
    • Algorithm: big O notation, approximation, pruning.
      Reading: Chapter 1,2,3,35 of Introduction to Algorithms, Second Edition Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein, 2001, the MIT Press.
  6. Date: 1/24 and 1/29
    Presenting: Bruce

    Assignment 1 (Due Feb. 7)

    [Lecture Notes ]
    Topic: Nuclear Vector Replacement

    Themes:

    • Graph algorithms and matching
    • PCA
    • RDCs and Geometry
    • SVD
    Reading:
    • Handout on matching, by Subhash Suri.
    • An Expectation/Maximization Nuclear Vector Replacement Algorithm for Automated NMR Resonance Assignments. Journal of Biomolecular NMR 2004; 29(2):111-138. PDF
    • 3D Structural Homology Detection via Unassigned Residual Dipolar Couplings, Proc. IEEE Computational Systems Bioinformatics Conference (CSB), Stanford University, Palo Alto (August 10, 2003) pp. 209-217. ISBN 0-7695-2000-6. PDF
    • Implementing Munrkres' Algorithm, by Bob Pilgrim.
    • High-Throughput 3D Structural Homology Detection via NMR Resonance Assignment. The IEEE Computational Systems Bioinformatics Conference (CSB), Stanford CA, (August, 2004) pp. 278-289. PDF
  7. W 1/30, 5:00-6:00 pm, LSRC D344
    Presenting: Lirong Xia
    Topic: SVD and applications Slides
    Content
    • Definition, existence, and application of SVD.
    Reading:
  8. 1/31
    Presenting: Bruce Donald.

    Topic: Exact Solutions From Residual Dipolar Couplings
    [Lecture Notes ]
    Main Reading:
    • L. Wang and B. R. Donald.
      Exact solutions for internuclear vectors and backbone dihedral angles from NH residual dipolar couplings in two media, and their application in a systematic search algorithm for determining protein backbone structure.
      Jour. Biomolecular NMR, 29(3):223-242, 2004. [PDF]
    • A Polynomial-Time Algorithm for De Novo Protein Backbone Structure Determination from NMR Data. Journal of Computational Biology 2006; 13(7): 1276-1288.
    • Losonczi, J. A., Andrec, Michael, Fischer, Mark, Prestegard, James H. Order Matrix Analysis of Residual Dipolar Couplings Using Singular Value Decomposition. Journal of Magnetic Resonance, Vol. 138, 1999: 334-342. PDF
    • Here is a wonderful textbook that covers the Singular Value Decomposition (SVD), Penrose pseudo-inverse, and other useful numerical methods. Read chapter 3 on SVD.
    • A Data-Driven, Systematic Search Algorithm for Structure Determination of Denatured or Disordered Proteins. The Computational Systems Bioinformatics Conference (CSB), Stanford CA. (August, 2006) Pages 67-78. ISBN 1-86094-700-X.

    Background Reading:

    • Martin Blackledge, Dipolar Couplings in Partially Aligned Macromolecules - New Directions in Structure Determination using Solution State NMR. EMBO practical course 2003: Structure determination of biological macromolecules by solution NMR. PDF
    • Residual Dipolar Couplings in Structure Determination of Biomolecules, J. H. Prestegard et al, Chem Rev 2004. [PDF]
    • C. Langmead and B. R. Donald. An expectation/maximization nuclear vector replacement algorithm for automated NMR resonance assignments. Jour. Biomolecular NMR, 29(2):111-138, 2004. [PDF]
    • Annual Review of Biophysics and Biomolecular Structure, Vol. 33: 387-413 (June 2004) (doi:10.1146/annurev.biophys.33.110502.140306) Residual Dipolar Couplings In NMR Structure Analysis, Rebecca S. Lipsitz and Nico Tjandra. PDF
  9. 2/5
    Presenting: Bruce Donald.

    Topic: Protein design, and provably-good approximation algorithms for computing partition functions over molecular ensembles
    [Lecture Notes ]
    Reading:
    • A Novel Ensemble-Based Scoring and Search Algorithm for Protein Redesign, and its Application to Modify the Substrate Specificity of the Gramicidin Synthetase A Phenylalanine Adenylation Enzyme. Journal of Computational Biology 2005; 12(6-7):740-761. [PDF]
  10. Date: 2/7

    Assignment 1 is due today.

    Presenting: Serkan Apaydin
    [Slides (PPT) ] [Additional slides (PPT) ]
    Topic: Protein Flexibility (1): FIRST and NMA Basics

    Reading:

    • D.J. Jacobs, A.J.Rader, L.A. Kuhn, and M.F. Thorpe. Protein Flexibility Predictions Using Graph Theory. Proteins: Structure, Function, and Genetics 2001; 44:150-165. PDF
    • K. Hinsen. Normal Mode Theory and Harmonic Potential Approximation. PDF
  11. 2/12
    Presenting: Raluca Gordan
    [Slides] [Lecture Notes]
    Topic: Free Energy Estimates of All-atom Protein Structures Using Generalized Belief Propagation

    Project proposals are due today!
    Written project proposal is due on Feb 12.
    Reading:
    • Hetunandan K, Eric PX, Christopher JL. Free Energy Estimates of All-atom Protein Structures Using Generalized Belief Propagation. Nov 2006; CMU-CS-06-160. PDF
    • Yedidia JS, Freeman WT, Weiss Y. Constructing Free-Energy Approximations and Generalized Belief Propagation Algorithms. IEEE Trans on Information Theory. Jul 2005; 51(7): 2282-312. PDF

    Algorithms: Graphical Models, Bayesian Networks, Markov Random Fields, Factor Graphs, & Belief Propagation.

  12. 2/14
    Presenting: Tony Yan
    [Slides]
    Topic: Constraint Satisfaction, Branch-and-Bound Search, with applications to Solving the Structure Of Membrane Proteins

    Reading:
    • S. Potluri, A.K. Yan, J.J. Chou, B.R. Donald, and C. Bailey-Kellogg. Structure Determination of Symmetric Homo-oligomers by a Complete Search of Symmetry Configuration Space using NMR Restraints and van der Waals Packing. [PDF]
    • A Complete Algorithm to Resolve Ambiguity for Inter-subunit NOE Assignment in Structure Determination of Symmetric Homo-oligomersProtein Science 2007; 16(1):69-81. [PDF]
  13. 2/19
    Presenting: Ivelin Georgiev

    Topic: The Minimized Dead-End Elimination Criterion and Its Application to Computing Partition Functions over Molecular Ensembles [Slides]
    Reading:
    • The Minimized Dead-End Elimination Criterion and Its Application to Protein Redesign in a Hybrid Scoring and Search Algorithm for Computing Partition Functions over Molecular Ensembles'' Journal of Computational Chemistry 2008. [PDF]
  14. 2/21
    Presenting: Chittu

    Topic: Kinematics, RDCs, and Loop Closure [Slides] If you are in Duke, see [this]
    Reading:
    • A. A. Canutescu and R. L. Dunbrack Jr. Cyclic coordinate descent: A robotics algorithm for protein loop closure. Protein Science, 12:963-972, 2003. [PDF]
    • I. Z. Emiris, E. D. Fritzilas, and D. Manocha. Algebraic algorithms for determining structure in biological Chemistry. International Journal of Quantum Chemistry, Spec. Issue on Symbolic Methods, 2005. [PDF]
    • E. Coutsias, C. Seok, and M. Jacobson, and K. Dill. (2004). A Kinematic View of Loop Closure. Journal of Computational Chemistry, 25, 510-528. [PDF]
    • R. Kolodny, L. Guibas, M. Levitt and P. Koehl. Inverse kinematics in biology: the protein loop closure problem. International Journal of Robotics Research, 24, 151-163 (2005). [PDF]
    • L. Wang, R. Mettu, and B. R. Donald. A Polynomial-Time Algorithm for De Novo Protein Backbone Structure Determination from NMR Data. Journal of Computational Biology, 13(7):1276-1288, 2006. [PDF]
  15. Date: 2/26
    Presenting: Bruce
    Molecular Replacement and Proteomics
    Clustering Modulo a Group; PCA; LDA; SVD

    Reading:
    • How do we determine homo- or hetero-oligimeric protein crystal structures using X-ray diffraction?
      An Introduction to Molecular Replacement with Non-Crystallographic Symmetry.
      A Subgroup Algorithm to Identify Cross-Rotation Peaks Consistent with Non-Crystallographic Symmetry. Acta Crystallographica D: Biological Crystallography 2004; D60, 1057-1067. [PDF]
    • How do we discover protein targets and biomarkers?
      "Probabilistic Disease Classification of Expression-Dependent Proteomic Data from Mass Spectrometry of Human Serum," Journal of Computational Biology, 10(6) 2003, pp. 925-946.
  16. 2/28
    Presenting: Ivelin Georgiev and Cheng-Yu Chen

    Topic: "Computational Protein Redesign and the Non-Ribosomal Code: Theory, Computation, and Experiments" Slides
    Reading:
    • Progress in computational protein design. Curr Opin Biotechnol. 2007 Jul 17; PDF
    • Substrate recognition by nonribosomal peptide synthetase multi-enzymes by Sylvie Lautru and Gregory L. Challis. [PDF ]
    • Stachelhaus, Torsten, Mootz, Henning D., Marahiel, Mohamed A. The specificity-conferring code of adenylation domains in nonribosomal peptide synthetases. Chemistry & Biology, Vol. 6, No. 8, 1999: 493-505. [PDF ]
    • Challis, Gregory L., Ravel, Jacques, Townsend, Craig A. Predictive, structure-based model of amino acid recognition by nonribosomal peptide synthetase adenylation domains. Chemistry & Biology, Vol. 7, No. 3, 2000: 211-224. [PDF]
    • Altering protein specificity: techniques and applications Nina M. Antikainen and Stephen F. Martin. Bioorganic & Medicinal Chemistry 13 (2005) 2701-2716 [PDF]
    Paper presentation schedule

    Queue

    What follows below is a queue of papers we will read next. Please note: These dates and times might move some (see "The Queue", above).

      1. If you're assigned to give a talk please prepare slides and prepare your talk using all the rules above.

      2. After your talk, you should fix problems (if any) that arose during your talk and then e-mail your slides to the TA for posting (within 2 days).

      3. After your talk within 5 days, you must prepare LaTeX course notes scribing your lecture, as described above. These should be in the same style as the other course notes: brief, elegant, well-written, and wonderful in every way. You may work with the TA to do this but you are responsible for doing it. Your course notes should complement your slides and should not simply reprise your slides -- a couple of pictures is okay but it should not simply be a list/repeat of your slides. The point of your slides is pictures, that you talk over. The point of your described lecture notes is beautiful text that one could read and understand. The TA will provide you with the latex template to use. Everything must compile with pdflatex, and you must send the TA all the files necessary to successfully pdflatex your notes.

  17. Date: Mar 4
    Presenting: Kyle
    Topic: Peptide Design [Slides]

    Reading:
    • J Comput Chem. 2004 Jan 15;25(1):16-27. Peptide backbone reconstruction using dead-end elimination and a knowledge-based forcefield. Adcock SA. [PDF]
    • Nat Chem Biol. 2007 May;3(5):252-62. Foldamers as versatile frameworks for the design and evolution of function.Goodman CM, Choi S, Shandler S, DeGrado WF. [PDF, Figure S1, Figure S2]
    • Science. 2007 Mar 30;315(5820):1817-22. Computational design of peptides that target transmembrane helices.Yin H, Slusky JS, Berger BW, Walters RS, Vilaire G, Litvinov RI, Lear JD, Caputo GA, Bennett JS, DeGrado WF. [PDF]
  18. Date: Mar 5
    Presenting: Lirong
    Topic: Q5, PCA, LDA, SVD

  19. Date: Mar 6
    Presenting: Nick
    Topic: Orientational Sampling of Interatomic Vectors Slides

    Reading:
    • The Effect of Finite Sampling on the Determination of Orientational Properties: A Theoretical Treatment with Application to Interatomic Vectors in Proteins. PDF

    Background Reading:

    • A Probability-Based Similarity Measure for Saupe Alignment Tensors... PDF
  20. Date: Mar 18
    NMR ensemblePresenting: JJ (Jonathan Jou)
    Distance Geometry, Lower Bounds Slides

    Reading:
    • PDF , PDF Saxe, J. B., Embeddability of weighted graphs in k-space is strongly NP-hard. Proceedings of the 17th Allerton Conference on Communications, Control, and Computing. 1979. pages 480-489.
    • Supplementary Reading: Two papers on graph embedding problems. PDF
    Below are the contents from Garey and Johnson's book I found useful in our context of the class.

      1) Strong NP-completeness : 95 - 107 : chapter 5

      2) Applying NP-completeness to Approximation Problems: 137 - 148 : chapter 6

    [ Computers and Intractability: A guide to the Theory of of NP-Completeness - Michael R. Garey & David S. Johnson ISBN : 0-7167-1045-5]

    However, it is good to go once thru chapter 1 of the above book to be familiar with the terminologies of the book. Also, chapter 5 & 6 are overall a good resource on P/NP issues.

  21. Date: Mar 20
    NMR ensemblePresenting: Jeff
    [Slides] or [Short version]
    Distance Geometry, continued (*).

    Reading:
    • B. Hendrickson, "Conditions For Unique Graph Realizations." Siam Journal of Computing, Vol. 21, No. 1, February 1992, pp. 65--84. PDF
    • B. Hendrickson, "The Molecule Problem: Exploiting Structure in Global Optimization." Siam Journal of Computing, Vol. 5, No. 4, November 1995, pp. 835--857. PDF
    • Journal of Global Optimization 22: 365-375, 2002. A linear-time algorithm for solving the molecular distance geometry problem with exact inter-atomic distances. PDF
         NB: Only briefly mention this (Dong & Wu) paper at the end (5 minutes); do not present in detail.
    Assignment (Due today):
    • What key assumptions are necessary for the result of Dong and Wu? Will these hold in general or not? Explain.

  22. Date: 3/25
    Presenting: Joshua
    Topic: Dead-End Elimination, Advanced Topics [Slides]

    Reading:
    • J. Comput. Chem. 2007 Nov 15;28(14):2325-35. An extended dead-end elimination algorithm to determine gap-free lists of low energy states.Kloppmann E, Ullmann GM, Becker T. PDF
    • Compare to: [DACS: PDF].
    Assignment (Due today):
  23. Date: 3/27
    Presenting: Ed
    Topic: Protein Interface and Active Site Redesign [Slides]

    Reading:
    • Proc Natl Acad Sci U S A. 2007 Jul 17;104(29):11951-6. Epub 2007 Jul 9. Directed evolution can rapidly improve the activity of chimeric assembly-line enzymes. PDF
    • Angew Chem Int Ed Engl. 2007;46(18):3212-36. Minimalist active-site redesign: teaching old enzymes new tricks.Toscano MD, Woycechowsky KJ, Hilvert D. PDF
  24. Date: 4/1
    Presenting: Christopher
    Topic: Ligand configurational entropy and protein binding. [Slides]

    Reading:
    • Proc Natl Acad Sci U S A. 2007 Jan 30;104(5):1534-9. Epub 2007 Jan 22. Ligand configurational entropy and protein binding. Chang CE, Chen W, Gilson MK. PDF
    • paper 2
  25. Date: TBA
    Presenting: Weizi
    Topic: Optimization of Surface Charge Charge Interactions [Slides]

    Reading:
    • Schweiker KL, Zarrine-Afsar A, Davidson AR, Makhatadze GI.Computational design of the Fyn SH3 domain with increased stability through optimization of surface charge charge interactions. PDF
    • paper 2
  26. Date: TBA
    Presenting: Xianrui
    Topic: Molecular Replacement and NCS in X-ray crystallography

    Reading:
    • Acta Cryst. (2008). D64, 90-98 [ doi:10.1107/S0907444907053802 ] NCS-constrained exhaustive search using oligomeric models M. N. Isupov and A. A. Lebedev PDF
    • 2: Acta Crystallogr D Biol Crystallogr. 2008 Jan;64(Pt 1):40-8. Epub 2007. Dealing with structural variability in molecular replacement and crystallographic refinement through normal-mode analysis.Delarue M. et al PDF
    Background Reading:
    • Acta Cryst. (2008). D64, 1-10 An introduction to molecular replacement P. Evans and A. McCoy PDF
    • A Subgroup Algorithm to Identify Cross-Rotation Peaks Consistent with Non-Crystallographic Symmetry. Acta Crystallographica D: Biological Crystallography 2004; D60, 1057-1067. [PDF]
  27. Date: 4/10

    Topic: Project Presentations:
    Presenting:
  28. Date: T 4/15
    Dr. Donald will be at NIH on Tuesday April 15
  29. Date: 4/17

    Topic: Project Presentations:
    Presenting:
    We're still working on the schedule for after this point.

    Topics that were covered last year included the following. We may cover somewhat different topics this year. But this is to give you an idea of the kind of topics we may cover:

  30. TBA
    Discussion: Questions

    Discussion: NMR Protein Structure Determination using Residual Dipolar Couplings
    Assignment: Formulate three questions about the papers to be read for Monday 1/22, or the material presented on Monday 1/22. Email these questions to the TA by 10AM T 1/23. We will have a class discussion on these questions and on Solution Structures of Native and Denatured Proteins from Residual Dipolar Couplings. Bring your questions that we will discuss and answer them! Please come to class prepared to participate in the discussion.
  31. TBA
    NMR ensemblePresenting: Bruce.
    [Lecture Notes ]
    Proteins and NMR Structural Biology: JIGSAW and NMR

    Reading:
    • C. Bailey-Kellogg, A. Widge, J. J. Kelley III, M. J. Berardi, J. H. Bushweller, and B. R. Donald. The NOESY Jigsaw: Automated protein secondary structure and main-chain assignment from sparse, unassigned NMR data. Jour. Comp. Biol., 3-4(7):537-558, 2000. [PDF]
    • Kamichetty H, Bailey-Kellogg C, Pandurangan G. An efficient randomized algorithm for contact-based NMR backbone resonance assignment. Bioinformatics. 2005 Nov 15; PMID: 16287932 Medline, PDF
    • An algorithm for graph pattern-matching, Gabriel Valiente, Conrado Martinez PDF
    • Background Reading:
      • Cavanagh et al, chapter 8.
        • Reference: Protein NMR Spectroscopy : Principles and Practice by John Cavanagh, Arthur G., III Palmer, Wayne Fairbrother (Contributor), Nick Skelton (Contributor) Hardcover - 587 pages (April 1996) Academic Pr; ISBN: 0121644901
  32. TBA
    Discussion. Questions

    Discussion: The Non-ribosomal Code and Protein Design.

    Assignment: Formulate three questions about the papers to be read for R 2/1, or the material presented on R 2/1. Email these questions to the TA by 10AM M 2/5. We will have a class discussion on these questions. Bring your questions & we will discuss and answer them! Please come to class prepared to participate in the discussion.
  33. TBA NMR ensemblePresenting: Bruce
    [Lecture Notes ]
    Residual Dipolar Couplings (RDCs) in NMR Structural Biology

    Discussion: Questions

    Discussion: NMR Protein Structure Determination using Residual Dipolar Couplings
    We will have a class discussion on these questions and on Solution Structures of Native and Denatured Proteins from Residual Dipolar Couplings. Bring your questions & we will discuss and answer them! Please come to class prepared to participate in the discussion.

    Reading:

    • Martin Blackledge, Dipolar Couplings in Partially Aligned Macromolecules - New Directions in Structure Determination using Solution State NMR. EMBO practical course 2003: Structure determination of biological macromolecules by solution NMR. PDF
    • Residual Dipolar Couplings in Structure Determination of Biomolecules, J. H. Prestegard et al, Chem Rev 2004. [PDF]
    • C. Langmead and B. R. Donald. An expectation/maximization nuclear vector replacement algorithm for automated NMR resonance assignments. Jour. Biomolecular NMR, 29(2):111-138, 2004. [PDF]
    • Annual Review of Biophysics and Biomolecular Structure, Vol. 33: 387-413 (June 2004) (doi:10.1146/annurev.biophys.33.110502.140306) Residual Dipolar Couplings In NMR Structure Analysis, Rebecca S. Lipsitz and Nico Tjandra. PDF
    • Losonczi, J. A., Andrec, Michael, Fischer, Mark, Prestegard, James H. Order Matrix Analysis of Residual Dipolar Couplings Using Singular Value Decomposition. Journal of Magnetic Resonance, Vol. 138, 1999: 334-342. PDF
    • Here is a wonderful textbook that covers the Singular Value Decomposition (SVD), Penrose pseudo-inverse, and other useful numerical methods.
    • L. Wang and B. R. Donald.
      Exact solutions for internuclear vectors and backbone dihedral angles from NH residual dipolar couplings in two media, and their application in a systematic search algorithm for determining protein backbone structure.
      Jour. Biomolecular NMR, 29(3):223-242, 2004. [PDF]
  34. TBA
    Presenting: Bruce
    [Lecture Notes ]
    Topic: Nuclear Vector Replacement

    Reading:
    • An Expectation/Maximization Nuclear Vector Replacement Algorithm for Automated NMR Resonance Assignments. Journal of Biomolecular NMR 2004; 29(2):111-138. PDF
    • 3D Structural Homology Detection via Unassigned Residual Dipolar Couplings, Proc. IEEE Computational Systems Bioinformatics Conference (CSB), Stanford University, Palo Alto (August 10, 2003) pp. 209-217. ISBN 0-7695-2000-6. PDF
    • High-Throughput 3D Structural Homology Detection via NMR Resonance Assignment. The IEEE Computational Systems Bioinformatics Conference (CSB), Stanford CA, (August, 2004) pp. 278-289. PDF
    Queue

    What follows below is a queue of papers we will read next. Please note: These dates and times might move some (see "The Queue", above).

  35. TBA
    Presenting: John MacMaster
    [Slides (PPT)] [Lecture Notes]
    Topic: Protein Flexibility: Introduction to Inverse Kinematics & Loop Closure Problem

    Reading:
    • R. Singh, B. Berger. ChainTweak: Sampling from the Neighbourhood of a Protein Conformation. Pacific Symposium on Biocomputing 2005: 54-65. PDF
    • K. Noonan, D. O'Brien, and J. Snoeyink. Probik: Protein Backbone Motion by Inverse Kinematics. The International Journal of Robotics Research 2005; 24(11): 971 - 982. PDF
    • http://www4.cs.umanitoba.ca/~jacky/Teaching/Courses/74.795-Humanoid-Robotics/ReadingList/chap3-forward-kinematics.pdf PDF
  36. TBA
    Presenting: Ivelin Georgiev
    Topic: Dead-End Elimination with Backbone Flexibility

    Reading:
      Georgiev, I and Donald, B. Dead-End Elimination with Backbone Flexibility. Proc. International Conference on Intelligent Systems for Molecular Biology (ISMB), Vienna, Austria: July 21-25, 2007 (In Press).
  37. TBA
    Presenting: Chittaranjan Tripathy
    [Slides] [Lecture Notes]
    Topic: Modeling Protein Conformational Ensembles

    Reading:
    • Shehu A, Clementi C, Kavraki LE. Modeling protein conformational ensembles: from missing loops to equilibrium fluctuations. Proteins. 2006 Oct 1;65(1):164-79. PDF
  38. TBA
    Presenting: Cheng-Yu Chen
    [Slides (ppt)] [Slides (pdf)] [Lecture Notes]
    Topic: Kinetic studies of the Gramicidin S Synthetase initial module PheATE
    Reading:
    • Luo L, Burkart MD, Stachelhaus T, Walsh CT. Substrate recognition and selection by the initiation module PheATE of gramicidin S synthetase. J Am Chem Soc. 2001 Nov 14;123(45):11208-18. PDF
    • Luo L, Walsh CT. Kinetic Analysis of Three Activated Phenylalanyl Intermediates Generated by the Initiation Module PheATE of Gramicidin S Synthetase. Biochemistry. 2001 May 8;40(18):5329-37. PDF
  39. TBA
    Colloquia: Nina Singhal Hinrichs

    Duke computer science colloquia at D106 LSRC (11:45am - 12:45pm)

    Topic: Modeling macromolecular dynamics from simulations [see details]

    Reading:
    • Kasson PM, Kelley NW, Singhal N, Vrljic M, Brunger AT, Pande VS. Ensemble molecular dynamics yields submillisecond kinetics and intermediates of membrane fusion. Proc Natl Acad Sci U S A. 2006 Aug 8;103(32):11916-21. PDF
    • Nina Singhal and Vijay S. Pande. Error Analysis and efficient sampling in Markovian State Models for protein folding. Journal of Chemical Physics, 123, 204909-204921 (2005). PDF
    • Nina Singhal, Christopher D. Snow, and Vijay S. Pande. Using path sampling to build better Markovian state models: Predicting the folding rate and mechanism of a tryptophan zipper beta hairpin. Journal of Chemical Physics, 121(1), 415-425 (2004). PDF
  40. Date: TBA
    NMR ensemblePresenting: TBA
    [Slides]
    Distance Geometry, continued (*).

    Reading:
    • Journal of Global Optimization 22: 365-375, 2002. A linear-time algorithm for solving the molecular distance geometry problem with exact inter-atomic distances. PDF
    • B. Hendrickson, "Conditions For Unique Graph Realizations." Siam Journal of Computing, Vol. 21, No. 1, February 1992, pp. 65--84. PDF
    • B. Hendrickson, "The Molecule Problem: Exploiting Structure in Global Optimization." Siam Journal of Computing, Vol. 5, No. 4, November 1995, pp. 835--857. PDF
    • PDF , PDF 
      @inproceedings{Saxe,
author = "Saxe, J. B.",
title = "Embeddability of weighted graphs in $k$-space is strongly {NP}-hard",
booktitle = "Proceedings of the 17th Allerton Conference on Communications, Control, and Computing",
year = "1979",
pages = "480--489",
}

         Below are the contents from Garey and Johnson's book I found useful in
our context of the class.

   1) Strong NP-completeness : 95 - 107 : chapter 5

   2) Applying NP-completeness to Approximation Problems: 137 - 148 :
chapter 6

   [ Computers and Intractability
     A guide to the Theory of of NP-Completeness
     - Michael R. Garey & David S. Johnson
     ISBN : 0-7167-1045-5]

However, it is good to go once thru chapter 1 of the above book to be
familiar with the terminologies of the book. Also, chapter 5 & 6 are
overall a good resource on NP issues for interested readers.
  41. TBA
    Presenting: Parawee Lekprasert
    [Slides] [Lecture Notes]
    Topic: Carrier Protein Structure and Recognition in Polyketide and Nonribosomal Peptide Biosynthesis

    Reading:
    • Lai JR, Koglin A, Walsh CT. Carrier protein structure and recognition in polyketide and nonribosomal Peptide biosynthesis. Biochemistry. 2006 Dec 19;45(50):14869-79. PDF
    • Lai, J. Fischbach, M. A., Liu, D., and Walsh, C. T. 2006. A protein interaction surface in nonribosomal peptide synthesis mapped by combinatorial mutagenesis and selection. PNAS. 103:11. 5314-5319. PDF
    • Koglin, A. Mofid, M. R., Lohr, F., Schafer, B., Rogov, V. V., Blum, M., Mittag, T., Marahiel, M. A., Bernhard, F., and Dotsch, V. 2006. Conformational switches modulate protein interactions in peptide antibiotic synthetases. Science. 312. 273-276. PDF
  42. TBA
    Presenting: Eric Josephs
    [Slides] [Lecture Notes]
    Topic: Protein-Ligand NOE Matching: A High-Throughput Method for Binding Pose Evaluation That Does Not Require Protein NMR Resonance Assignments

    Reading:
    • Constantine KL, Davis ME, Metzler WJ, Mueller L, Claus BL. Protein-ligand NOE matching: a high-throughput method for binding pose evaluation that does not require protein NMR resonance assignments. J Am Chem Soc. 2006 Jun 7;128(22):7252-63. PDF
  43. TBA
    Presenting: Kuan-Ming Lin
    [slides (PPT) (PDF)] [Lecture Notes]
    Topic: Simultaneous Optimization on Backbone and Side Chain Flexibility in Protein Design

    Reading:
    • Desjarlais JR, Handel TM. Side-chain and backbone flexibility in protein core design. J Mol Biol. 1999 Jul 2;290(1):305-18. PDF
  44. TBA
    Presenting: Michael Zeng
    [Slides] [Lecture Notes]
    Topic: A Topology-Constrained Distance Network Algorithm for Protein Structure Determination From NOESY Data

    Reading:
    • Huang YJ, Tejero R, Powers R, Montelione GT. A topology-constrained distance network algorithm for protein structure determination from NOESY data. Proteins. 2006 Mar 15;62(3):587-603. PDF
  45. TBA
    Presenting: Xin Guo
    Topic: Mars: robust automatic backbone assignment of proteins and its extension
    [Slides] [Lecture Notes]
    Reading:
    • Jung YS, Zweckstetter M. Mars -- robust automatic backbone assignment of proteins. J Biomol NMR. 2004 Sep; 30(1): 11-23. PDF
    • Jung ZS, Zweckstetter M. Backbone assignment of proteins with known structure using residual dipolar couplings. J Biomol NMR. 2004 Sep; 30(1): 25-35. PDF
  46. TBA
    Presenting: Tiffany Chen
    Topic: Major Errors in NMR structures
    [Slides] [Lecture Notes]
    Reading:
    • Nabuurs SB, Spronk CA, Vuister GW, Vriend G. Traditional biomolecular structure determination by NMR spectroscopy allows for major errors. PLoS Comput Biol. 2006 Feb;2(2):e9. PDF
  47. TBA
    project report: Raluca [PPT], Xin [PPT], and Nicky [PPT] (Campus access only)
  48. Date: 4/17
    project report: Eric [PPT], Tiffany [PPT], Chittu [PPT], Michael [PPT] (Campus access only)
  49. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Vitek O, Bailey-Kellogg C, Craig B,Vitek J. Inferential backbone assignment for sparse data. J Biomol NMR. 2006 Jul 20. PDF
    • Vitek O, Vitek J, Craig B, Bailey-Kellogg C. Model-based assignment and inference of protein backbone Nuclear Magnetic Resonances. Stat Appl Genet Mol Biol. 2004;3:Article6. PDF
    • Vitek O, Bailey-Kellogg C, Craig B, Kuliniewicz P, Vitek J. Reconsidering complete search algorithms for protein backbone NMR assignment. Bioinformatics. 2005 Sep 1;21 Suppl 2:ii230-ii236. PDF
  50. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Kamisetty H, Bailey-Kellogg C, Pandurangan G. An efficient randomized algorithm for contact-based NMR backbone resonance assignment. Bioinformatics. 2006 Jan 15;22(2):172-80. PDF
    • Bailey-Kellogg C, Chainraj S, Pandurangan G. A random graph approach to NMR sequential assignment. J Comput Biol. 2005 Jul-Aug;12(6):569-83. PDF
  51. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Andrec M, Harano Y, Jacobson MP, Friesner RA, Levy RM. Complete protein structure determination using backbone residual dipolar couplings and sidechain rotamer prediction. J Struct Funct Genomics. 2002;2(2):103-11. PDF
    • Bouvignies G, Markwick P, Bruschweiler R, Blackledge M. Simultaneous determination of protein backbone structure and dynamics from residual dipolar couplings. J Am Chem Soc. 2006 Nov 29;128(47):15100-1. PDF
  52. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Agarwal PK, Billeter SR, Rajagopalan PT, Benkovic SJ, Hammes-Schiffer S. Network of coupled promoting motions in enzyme catalysis. Proc Natl Acad Sci U S A. 2002 Mar 5;99(5):2794-9. PDF
  53. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Mueller GA, Choy WY, Yang D, Forman-Kay JD, Venters RA, Kay LE. Global folds of proteins with low densities of NOEs using residual dipolar couplings: application to the 370-residue maltodextrin-binding protein. J Mol Biol. 2000 Jun 30;300(1):197-212. PDF
  54. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Lopez-Mendez B, Guntert P. Automated protein structure determination from NMR spectra. J Am Chem Soc. 2006 Oct 11;128(40):13112-22. PDF
  55. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Ruan K, Tolman JR. Composite alignment media for the measurement of independent sets of NMR residual dipolar couplings. J Am Chem Soc. 2005 Nov 2;127(43):15032-3. PDF
  56. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Green DF, Dennis AT, Fam PS, Tidor B, Jasanoff A. Rational design of new binding specificity by simultaneous mutagenesis of calmodulin and a target peptide. Biochemistry. 2006 Oct 17;45(41):12547-59. PDF
  57. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Korukottu J, Bayrhuber M, Montaville P, Vijayan V, Jung YS, Becker S, Zweckstetter M. Fast High-Resolution Protein Structure Determination by Using Unassigned NMR Data. Angew Chem Int Ed Engl. 2007 Jan 5. PDF
  58. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Zanghellini A, Jiang L, Wollacott AM, Cheng G, Meiler J, Althoff EA, Rothlisberger D, Baker D. New algorithms and an in silico benchmark for computational enzyme design. Protein Sci. 2006 Dec;15(12):2785-94. PDF
  59. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Foster MP, McElroy CA, Amero CD. Solution NMR of large molecules and assemblies. Biochemistry. 2007 Jan 16;46(2):331-40. PDF
  60. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Andrec M, Du P, Levy RM. Protein backbone structure determination using only residual dipolar couplings from one ordering medium. J Biomol NMR. 2001 Dec;21(4):335-47. PDF
    • Rohl CA, Baker D. De novo determination of protein backbone structure from residual dipolar couplings using Rosetta. J Am Chem Soc. 2002 Mar 20;124(11):2723-9. PDF
  61. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Clore GM, Schwieters CD. Docking of protein-protein complexes on the basis of highly ambiguous intermolecular distance restraints derived from 1H/15N chemical shift mapping and backbone 15N-1H residual dipolar couplings using conjoined rigid body/torsion angle dynamics. J Am Chem Soc. 2003 Mar 12;125(10):2902-12. PDF
  62. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Clore GM, Schwieters CD. How much backbone motion in ubiquitin is required to account for dipolar coupling data measured in multiple alignment media as assessed by independent cross-validation? J Am Chem Soc. 2004 Mar 10;126(9):2923-38. PDF
  63. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • AB E, Pugh DJ, Kaptein R, Boelens R, Bonvin AM. Direct use of unassigned resonances in NMR structure calculations with proxy residues. J Am Chem Soc. 2006 Jun 14;128(23):7566-71. PDF
  64. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Xu Y, Zheng Y, Fan JS, Yang D. A new strategy for structure determination of large proteins in solution without deuteration. Nat Methods. 2006 Nov;3(11):931-7. PDF
  65. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Mayer KL, Qu Y, Bansal S, LeBlond PD, Jenney FE Jr, Brereton PS, Adams MW, Xu Y, Prestegard JH. Structure determination of a new protein from backbone-centered NMR data and NMR-assisted structure prediction. Proteins. 2006 Nov 1;65(2):480-9. PDF
  66. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Zagrovic B, van Gunsteren WF. Comparing atomistic simulation data with the NMR experiment: how much can NOEs actually tell us? Proteins. 2006 Apr 1;63(1):210-8. PDF
  67. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Dames SA, Aregger R, Vajpai N, Bernado P, Blackledge M, Grzesiek S. Residual dipolar couplings in short peptides reveal systematic conformational preferences of individual amino acids. J Am Chem Soc. 2006 Oct 18;128(41):13508-14. PDF
  68. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Malliavin ET. Quantitative Analysis of Biomolecular NMR Spectra: A Prerequisite for the Determination of the Structure and Dynamics of Biomolecules. Current Organic Chemistry, 2006, Oct. PDF
  69. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Lindorff-Larsen K, Best RB, Depristo MA, Dobson CM, Vendruscolo M. Simultaneous determination of protein structure and dynamics. Nature. 2005 Jan 13;433(7022):128-32. PDF
  70. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Gebel EB, Ruan K, Tolman JR, Shortle D. Multiple alignment tensors from a denatured protein. J Am Chem Soc. 2006 Jul 26;128(29):9310-1. PDF
  71. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Ashworth J, Havranek JJ, Duarte CM, Sussman D, Monnat RJ Jr, Stoddard BL, Baker D. Computational redesign of endonuclease DNA binding and cleavage specificity. Nature. 2006 Jun 1;441(7093):656-9. PDF
  72. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Hilser VJ, Garcia-Moreno EB, Oas TG, Kapp G, Whitten ST. A statistical thermodynamic model of the protein ensemble. Chem Rev. 2006 May;106(5):1545-58. PDF
  73. Date: TBA
    Presenting: TBA
    Topic:

    Reading:
    • Ming D, Bruschweiler R. Reorientational contact-weighted elastic network model for the prediction of protein dynamics: comparison with NMR relaxation. Biophys J. 2006 May 15;90(10):3382-8. PDF
    Papers that we read last year included the following. We may read different papers this year but this is to give you an idea of the kind of papers we may read::

  74. Date: TBA
    Presenting: Serkan
    [Slides (PPT) ] [Lecture Notes ]
    Topic: Protein Flexibility (1): FIRST and NMA Basics

    Reading:
    • D.J. Jacobs, A.J.Rader, L.A. Kuhn, and M.F. Thorpe. Protein Flexibility Predictions Using Graph Theory. Proteins: Structure, Function, and Genetics 2001; 44:150-165. PDF
    • K. Hinsen. Normal Mode Theory and Harmonic Potential Approximation. PDF
  75. Date: TBA
    Presenting: Jianyang (Michael)
    [Slides (PPT) ] [Lecture Notes ]
    Topic: Distance Geometry with Orientational Restraints

    Reading:
    • M. Badoiu, and E.D. Demaine, and M.T. Hajiaghayi, and P. Indyk. Low-Dimensional Embedding with Extra Information. Proceedings of the twentieth annual symposium on Computational geometry 2004. PDF
    • Saxe, J. B. Embeddability of weighted graphs in $k$-space is strongly {NP}-hard. Proceedings of the 17th Allerton Conference on Communications, Control, and Computing, pages 480--489, 1979. PDF , PDF
    • L. Wang and B. R. Donald. Exact solutions for internuclear vectors and backbone dihedral angles from NH residual dipolar couplings in two media, and their application in a systematic search algorithm for determining protein backbone structure. Jour. Biomolecular NMR, 29(3):223-242, 2004. [PDF]
    • Bernard Chazelle, Carl Kingsford, Mona Singh: A Semidefinite Programming Approach to Side Chain Positioning with New Rounding Strategies. INFORMS Journal on Computing 16(4): 380-392 (2004). PDF
    • P. Biswas, T.-C. Liang, T.C. Wang and Y. Ye. Semidefinite Programming for Ad Hoc Wireless Sensor Network Localization. Appeared in IPSN 2004, to appear in ACM J on Transactions on Sensor Networks (2006). PDF
  76. Date: TBA
    Presenting: Ivelin
    [Slides (PPT) ] [See also: ~donaldclass/Bio/Slides06/GraphCuts1.ppt] [Lecture Notes ]
    Topic: Graph Cuts for Nuclear Vector Replacement and Structure-Based NMR Assignment (1)

    Reading:
    • Computing Visual Correspondence with Occlusions using Graph Cuts (Kolmogorov and Zabih, ICCV '01) PDF. See also: http://www.cs.cornell.edu/~rdz/graphcuts.html
    • Markov Random Fields with Efficient Approximations (Boykov, Veksler and Zabih, CVPR '98) PDF.
    • An Expectation/Maximization Nuclear Vector Replacement Algorithm for Automated NMR Resonance Assignments. Journal of Biomolecular NMR 2004; 29(2):111-138. PDF
  77. Date: TBA
    Presenting: Chittu
    [Slides (PPT) ] [See also: ~donaldclass/Bio/Slides06/graphCuts_chittu_v1.ppt] [Lecture Notes ]
    Topic: Graph Cuts for Nuclear Vector Replacement and Structure-Based NMR Assignment (2)

    Reading:
    • Spatially Coherent Matching and Bayesian Recognition (Boykov and Huttenlocher, CVPR '99) PDF. See also: http://www.cs.cornell.edu/~rdz/graphcuts.html
    • Spatially Coherent Clustering with Graph Cuts (Zabih and Kolmogorov, CVPR '04) PDF.
    • What Energy Functions can be Minimized via Graph Cuts? (Kolmogorov and Zabih, ECCV '02/PAMI '04) PDF.
    • An Expectation/Maximization Nuclear Vector Replacement Algorithm for Automated NMR Resonance Assignments. Journal of Biomolecular NMR 2004; 29(2):111-138. PDF
    Papers that we read last year included the following. We will read different papers this year but this is to give you an idea of the kind of papers we may read::

  78. Date: TBA
    Presenting: John Thomas
    [Slides (PPT) ] [Lecture Notes ]
    Topic: Protein Flexibility (3): Using FIRST to Explore Flexibility using ROCK (and Applications in Ligand-Protein Binding) and FRODA

    Reading:
    • M.I. Zavodszky, M. Lei, M.F. Thorpe, A.R. Day, and L.A. Kuhn. Modeling Correlated Main-Chain Motions in Proteins for Flexible Molecular Recognition. Proteins: Structure, Function, and Genetics 2004; 44:150-165. PDF
    • S. Wells, S. Menor, B. Hespenheide, and M.F. Thorpe. Constrained Geometric Simulation of Diffusive Motion in Proteins. Phys. Biol. 2 (2005) S127-S136. PDF
  79. Date: TBA
    Presenting: Fei
    [Slides (PPT) ] [Lecture Notes ]
    Topic: Protein Flexibility (4): Applications of NMA to Protein-Protein and Ligand-Protein Binding

    Reading:
    • D. Tobi and I. Bahar. Structural Changes Involved in Protein Binding Correlate with Intrinsic Motions of Proteins in the Unbound State. PNAS 2005; 102(52):18908-18913. PDF
    • C.N. Cavasotto, J.A. Kovacs, R.A. Abagyan. Representing Receptor Flexibility in Ligand Docking through Relevant Normal Modes. J Am Chem Soc. 2005 Jul 6;127(26):9632-40. PDF
  80. Date: TBA
    Presenting: Rahul
    [Slides (PPT) ] [Lecture Notes ]
    Topic: Protein Unfolding by Using Residual Dipolar Couplings

    Reading:
    • Bernado P, Bertoncini CW, Griesinger C, Zweckstetter M, Blackledge M.. Defining Long-Range Order and Local Disorder in Native alpha-Synuclein Using Residual Dipolar Couplings. J Am Chem Soc. 2005 Dec 28;127(51):17968-17969. PDF
    • Bernado P, Blanchard L, Timmins P, Marion D, Ruigrok RW, Blackledge M.. A structural model for unfolded proteins from residual dipolar couplings and small-angle x-ray scattering. Proc Natl Acad Sci U S A. 2005 Nov 22;102(47):17002-7. PDF
    • Jean-Christophe Hus, Dominique Marion, and Martin Blackledge. Determination of Protein Backbone Structure Using Only Residual Dipolar Couplings. J. Am. Chem. Soc. 123, 1541-1542, 2001. PDF
  81. Date: TBA
    Presenting: Bruce
    Molecular Replacement, Protein Design, and Proteomics

    Reading:
    • How do we determine homo- or hetero-oligimeric protein crystal structures using X-ray diffraction?
      An Introduction to Molecular Replacement with Non-Crystallographic Symmetry.
      A Subgroup Algorithm to Identify Cross-Rotation Peaks Consistent with Non-Crystallographic Symmetry. Acta Crystallographica D: Biological Crystallography 2004; D60, 1057-1067. [PDF]
    • How do we redesign enzymes to have novel function?
      A Novel Ensemble-Based Scoring and Search Algorithm for Protein Redesign, and its Application to Modify the Substrate Specificity of the Gramicidin Synthetase A Phenylalanine Adenylation Enzyme. Journal of Computational Biology 2005; 12(6-7):740-761.
    • How do we discover protein targets and biomarkers?
      "Probabilistic Disease Classification of Expression-Dependent Proteomic Data from Mass Spectrometry of Human Serum," Journal of Computational Biology, 10(6) 2003, pp. 925-946.
  82. Date: TBA
    Presenting: Lincong
    [The slides can be downloaded from the Unix file system: ~donaldclass/Bio/Slides06/cs88_Protein-Ligand01_Lincong.ppt] [Lecture Notes ]
    Topic: Protein-Ligand Binding

    Reading:
    • Davis AM, Teague SJ, Kleywegt GJ. Application and limitations of X-ray crystallographic data in structure-based ligand and drug design. Angewandte Chemie International Edition, Jun 23;42(24):2718-36, 2003. PDF
    • Erickson JA, Jalaie M, Robertson DH, Lewis RA, Vieth M. Lessons in molecular recognition: the effects of ligand and protein flexibility on molecular docking accuracy. J. Med. Chem., 47 (1), 45 -55, 2004. PDF
    • Halperin I, Ma B, Wolfson H, Nussinov R. Principles of docking: An overview of search algorithms and a guide to scoring functions. Proteins. 2002 Jun 1;47(4):409-43. PDF
    • Additional reading:
      • Claussen H, Buning C, Rarey M, Lengauer T. FlexE: efficient molecular docking considering protein structure variations. J Mol Biol. 2001 Apr 27;308(2):377-95. PDF
      • Knegtel RM, Kuntz ID, Oshiro CM. Molecular docking to ensembles of protein structures. J Mol Biol. 1997 Feb 21;266(2):424-40. PDF
      • Taylor RD, Jewsbury PJ, Essex JW. FDS: flexible ligand and receptor docking with a continuum solvent model and soft-core energy function. J Comput Chem. 2003 Oct;24(13):1637-56. PDF
      • McGann MR, Almond HR, Nicholls A, Grant JA, Brown FK. Gaussian docking functions. Biopolymers. 2003 Jan;68(1):76-90. PDF
      • Peters KP, Fauck J, Frommel C. The automatic search for ligand binding sites in proteins of known three-dimensional structure using only geometric criteria. J Mol Biol. 1996 Feb 16;256(1):201-13. PDF
      • Jones G, Willett P, Glen RC, Leach AR, Taylor R. Development and validation of a genetic algorithm for flexible docking. J Mol Biol. 1997 Apr 4;267(3):727-48. PDF
      • Simonson T, Archontis G, Karplus M. Free energy simulations come of age: protein-ligand recognition. Acc Chem Res. 2002 Jun;35(6):430-7. PDF
      • Mangoni M, Roccatano D, Di Nola A. Docking of flexible ligands to flexible receptors in solution by molecular dynamics simulation. Proteins. 1999 May 1;35(2):153- 62. PDF
      • Verkhivker GM, Bouzida D, Gehlhaar DK, Rejto PA, Arthurs S, Colson AB, Freer ST, Larson V, Luty BA, Marrone T, Rose PW. Deciphering common failures in molecular docking of ligand-protein complexes. J Comput Aided Mol Des. 2000 Nov;14(8):731-51. PDF
      • Shoichet BK, Leach AR, Kuntz ID. Ligand solvation in molecular docking. Proteins. 1999 Jan 1;34(1):4-16. PDF
  83. Date: TBA
    Presenting: Lincong
    Topic: Protein-folding and Enzyme Dynamics

    Reading:
    • L. Wang, and B.R. Donald. The Conformation Ensemble of Protein in the Denatured State. Pre-print. [The draft can be downloaded from the Unix file system: ~donaldclass/Bio/Papers/]
    • L. Wang, Y. Pang, T. Holder, J. R. Brender, A. V. Kurochkin and E. R. P. Zuiderweg (2001) Functional Dynamics in the Active Site of the Ribonuclease Binase. Proceedings of the National Academy of Sciences, USA, 98, 7684-7689. PDF
  84. Date: TBA
    Presenting: Chittu
    Topic: More on Graph Cuts for Nuclear Vector Replacement and Structure-Based NMR Assignment (2)

    Reading:
    • Spatially Coherent Matching and Bayesian Recognition (Boykov and Huttenlocher, CVPR '99) PDF. See also: http://www.cs.cornell.edu/~rdz/graphcuts.html
    • Spatially Coherent Clustering with Graph Cuts (Zabih and Kolmogorov, CVPR '04) PDF.
    • What Energy Functions can be Minimized via Graph Cuts? (Kolmogorov and Zabih, ECCV '02/PAMI '04) PDF.
    • An Expectation/Maximization Nuclear Vector Replacement Algorithm for Automated NMR Resonance Assignments. Journal of Biomolecular NMR 2004; 29(2):111-138. PDF
  85. Date: TBA
    Presenting: Igor
    [Slides (PPT) ] [See also: ~donaldclass/Bio/Slides06/CompBio2006_v2.ppt] [Lecture Notes ]
    Topic: Analyzing Protein Structure by Using Ensemble Representation

    Reading:
    • Zagrovic B, Pande VS.. How does averaging affect protein structure comparison on the ensemble level? Biophys J. 2004 Oct;87(4):2240-6. PDF
    • L. Wang, and B.R. Donald. The Conformation Ensemble of Protein in the Denatured State. Pre-print. [The draft can be downloaded from the Unix file system: ~donaldclass/Bio/Papers/]
  86. Date: TBA
    Presenting: Xiaoduan
    [Slides (PPT) ] [Lecture Notes ]
    Topic: NMR Resonance Assignment Assisted by Mass Spectrometry

    Reading:
    • Feng L, Orlando R, Prestegard JH.. Mass spectrometry assisted assignment of NMR resonances in 15N labeled proteins. J Am Chem Soc. 2004 Nov 10;126(44):14377-9. PDF
    • Megan A. Macnaughtan, Austin M. Kane, and James H. Prestegard. Mass Spectrometry Assisted Assignment of NMR Resonances in C13 Reductively 13C-Methylated Proteins. J. Am. Chem. Soc., 127 (50), 17626 -17627, 2005. PDF
  87. Date: TBA
    Presenting: John Thomas
    [Slides (PPT) ] [Lecture Notes ]
    Topic: Automated NMR Resonance Assignment

    Reading:
    • Masse JE, Keller R.. AutoLink: automated sequential resonance assignment of biopolymers from NMR data by relative-hypothesis-prioritization-based simulated logic. J Magn Reson. 2005 May;174(1):133-51. PDF
  88. Date: TBA
    Presenting: Tony
    [Slides (PPT) ] [Lecture Notes ]
    Topic: Enzyme Redesign by SVM

    Reading:
    • Christian Rausch, Tilmann Weber1, Oliver Kohlbacher, Wolfgang Wohlleben1 and Daniel H. Huson. Specificity prediction of adenylation domains in nonribosomal peptide synthetases (NRPS) using transductive support vector machines (TSVMs). Nucleic Acids Research 2005 33(18):5799-5808. PDF
  89. Date: TBA
    Presenting: John MacMaster
    [Slides (PPT) ] [Lecture Notes ]
    Topic: Flexible Ligand-Protein Docking

    Reading:
    • Murphy KP.. Predicting binding energetics from structure: looking beyond DeltaG. Med Res Rev. 1999 Jul;19(4):333-9. PDF
    • Gervasio FL, Laio A, Parrinello M.. Flexible docking in solution using metadynamics. J Am Chem Soc. 2005 Mar 2;127(8):2600-7. PDF
    Class projects are due today in class. You must turn in a hardcopy by 1:45 Weds 3/8.
  90. Date: TBA
    Presenting: Fei
    Topic: Receptor Flexibility in Ligand Design and Docking

    Reading:
    • Alberts IL, Todorov NP, Dean PM..Receptor flexibility in de novo ligand design and docking. J Med Chem. 2005 Oct 20;48(21):6585-96. PDF
  91. Date: TBA
    Presenting: Ivelin
    Topic: Computational Enzyme Design

    Reading:
    • Wilson C, Mace JE, Agard DA.. Computational method for the design of enzymes with altered substrate specificity. J Mol Biol. 1991 Jul 20;220(2):495-506. PDF
    • Chakrabarti R, Klibanov AM, Friesner RA.. Computational prediction of native protein ligand-binding and enzyme active site sequences. Proc Natl Acad Sci U S A. 2005 Jul 19;102(29):10153-8. PDF
  92. Date: TBA
    Presenting: Chittu
    Topic: Protein-Protein Docking with Multiple Residue Conformations

    Reading:
    • Lorber DM, Udo MK, Shoichet BK.. Protein-protein docking with multiple residue conformations and residue substitutions. Protein Sci. 2002 Jun;11(6):1393-408. PDF
  93. Date: TBA
    Presenting: Xiaoduan
    Topic: Molecular Motions by Using Residual Dipolar and Hydrogen-Bond Scalar Couplings

    Reading:
    • Bouvignies G, Bernado P, Meier S, Cho K, Grzesiek S, Bruschweiler R, Blackledge M.. Identification of slow correlated motions in proteins using residual dipolar and hydrogen-bond scalar couplings. Proc Natl Acad Sci U S A. 2005 Sep 19. PDF
  94. Date: TBA
    Presenting: Jianyang (Michael)
    Topic: Statistical Coil Model of the Unfolded State

    Reading:
    • Jha AK, Colubri A, Freed KF, Sosnick TR.. Statistical coil model of the unfolded state: Resolving the reconciliation problem. Proc Natl Acad Sci U S A. 2005 Aug 30. PDF
  95. Date: TBA
    Presenting: John MacMaster
    Topic: Automated NMR Assignment and Structure Determination

    Reading:
    • Grishaev A, Steren CA, Wu B, Pineda-Lucena A, Arrowsmith C, Llinas M.. SABACUS, a direct method for protein NMR structure computation via assembly of fragments. Proteins. 2005 Aug 3;61(1):36-43. PDF
    • Hamid R. Eghbalnia1, Arash Bahrami, Liya Wang, Amir Assadi and John L. Markley. Probabilistic Identification of Spin Systems and their Assignments including Coil-Helix Inference as Output (PISTACHIO). Journal of Biomolecular NMR, Volume 32, Number 3, Pages: 219 - 233, July 2005 PDF
    Papers that we read last year included the following. We will read different papers this year but this is to give you an idea of the kind of papers we may read::

  96. Date: TBA
    Medline (PubMed) Example
    NMR ensemblePresenting: TBA
    RDCs, Dynamics and Ensembles

    [Slides]
    Reading:
    • 1. Reconstruction of interatomic vectors by principle component analysis of nuclear magnetic resonance data in multiple alignments, Jean-Christophe Hus and Rafael Bruschweiler, The Journal of Chemical Physics Vol 117(3) pp. 1166-1172. July 15, 2002 [PDF]
    • Dynamic and Structural Analysis of Isotropically Distributed Molecular Ensembles, PROTEINS: Structure, Function, and Genetics 46:177-189 (2002), Jeanine J. Prompers and Rafael Bruschweiler [PDF]
    • Journal of Computational Biology, Volume 10, Numbers 3/4, 2003. Pp. 617-634. Understanding Protein Flexibility through Dimensionality Reduction Miguel L. Teodoro, George N. Phillips, Jr., And Lydia E. Kavraki [PDF]
    • Here is a wonderful textbook that covers the Singular Value Decomposition (SVD), Penrose pseudo-inverse, and other useful numerical methods.
  97. Date: TBA
    NMR ensemblePresenting: TBA
    [Slides]
    Protein Structure Determination using Residual Dipolar Couplings

    A 4-5 page written project proposal is due on Feb 8.

    Reading:

    • L. Wang and B. R. Donald.
      Exact solutions for internuclear vectors and backbone dihedral angles from NH residual dipolar couplings in two media, and their application in a systematic search algorithm for determining protein backbone structure.
      Jour. Biomolecular NMR, 29(3):223-242, 2004. [PDF]
  98. Date: TBA
    Presenting: TBA
    [Slides] DNA Self-Assembly and Computation

    Reading:
    • C. Mao, LaBean, T.H. Reif, J.H., Seeman, Logical Computation Using Algorithmic Self-Assembly of DNA Triple-Crossover Molecules, Nature, vol. 407, Sept. 28 2000, pp. 493?495; C. Erratum: Nature 408, 750-750(2000). [PDF1] [PDF2]
  99. Date: TBA
    NMR ensemblePresenting: TBA
    [Slides]
    Distance Geometry

    Reading:
    • Journal of Global Optimization 22: 365-375, 2002. A linear-time algorithm for solving the molecular distance geometry problem with exact inter-atomic distances. PDF
    • B. Hendrickson, "Conditions For Unique Graph Realizations." Siam Journal of Computing, Vol. 21, No. 1, February 1992, pp. 65--84.
    • B. Hendrickson, "The Molecule Problem: Exploiting Structure in Global Optimization." Siam Journal of Computing, Vol. 5, No. 4, November 1995, pp. 835--857.
  100. Date: TBA
    Presenting: Bruce
    Proteomics and Computatonal Structural Biology

    Reading:
    • How do we discover protein targets and biomarkers?
      "Probabilistic Disease Classification of Expression-Dependent Proteomic Data from Mass Spectrometry of Human Serum," Journal of Computational Biology, 10(6) 2003, pp. 925-946.
    • How do we determine protein crystal structures using X-ray diffraction?
      A Subgroup Algorithm to Identify Cross-Rotation Peaks Consistent with Non-Crystallographic Symmetry. Acta Crystallographica D: Biological Crystallography 2004; D60, 1057-1067. [PDF]
    • How do we redesign enzymes to have novel function?
      A Novel Ensemble-Based Scoring and Search Algorithm for Protein Redesign, and its Application to Modify the Substrate Specificity of the Gramicidin Synthetase A Phenylalanine Adenylation Enzyme. R. Lilien, B. Stevens, A. Anderson, and B. R. Donald. Journal of Computational Biology 2005; 12(6-7):740-761.
  101. Date: TBA
    NMR ensembleGuest lecture: TBA
    Note unusual place: 006 Steele
    Chiral Mutagenesis of Insulin. Foldability and Function are Inversely Regulated by a Stereospecific Switch in the B Chain

    Michael Weiss, Professor and Chairman of the Biochemistry Department at the Case Western Reserve University Medical School, will be visiting next Thursday (10/28) and giving the Chemnistry Department Colloquium. His talk is entitled: "Chiral Mutagenesis of Insulin. Foldability and Function are Inversely Regulated by a Stereospecific Switch in the B Chain". His research focuses on the structural biology of proteins and enzymes, and the regulation of gene expression. He is an expert in the use of high field NMR spectroscopy to address questions on protein structure and function. For more information, please see his CWRU website: here.
  102. Date: TBA
    Presenting: TBA
    Protein design

    [Slides]
    Reading:
    • Design of a Novel Globular Protein Fold with Atomic-Level Accuracy Brian Kuhlman, Gautam Dantas, Gregory C. Ireton, Gabriele Varani, Barry L. Stoddard, David Baker. PDF
    • Computational design of protein-protein interactions Tanja Kortemme, and David Baker. PDF
  103. Date: TBA
    Presenting: TBA
    Enzyme design

    [Slides]
    Reading:
    • J Mol Biol. 2001 Mar 16;307(1):429-45. Generalized dead-end elimination algorithms make large-scale protein side-chain structure prediction tractable: implications for protein design and structural genomics. Looger LL, Hellinga HW. PDF
    • Computational Design of a Biologically Active Enzyme Mary A. Dwyer, Loren L. Looger, Homme W. Hellinga. PDF
    • See also: Looger, Loren L., Dwyer, Mary A., Smith, James J., Hellinga, Homme W. Computational design of receptor and sensor proteins with novel functions. Nature, Vol. 423, May 8, 2003: 185-190. PDF
  104. Date: TBA
    NMR ensemblePresenting: TBA
    Bayesian Assignment and Direct Methods for NMR

    [Slides]
    Reading:
    • J Biomol NMR. 2004 Jan;28(1):1-10. BACUS: A Bayesian protocol for the identification of protein NOESY spectra via unassigned spin systems. Grishaev A, Llinas M. PDF
    • Grishaev, Alexander, Llinas, Miguel. CLOUDS, a protocol for deriving a molecular proton density via NMR. PNAS, Vol. 99, No. 10, May 14, 2002: 6707-6712. PDF
    • Grishaev, Alexander, Llinas, Miguel. Protein structure elucidation from NMR proton densities. PNAS, Vol. 99, No. 10, May 14, 2002: 6713-6718. PDF
  105. Date: TBA
    NMR ensemblePresenting: TBA
    Slides
    Rotating or Spinning Samples in order to Scale RDCs

    Reading:
    • 2004, Volume 29, Issue 3, J.Biomol.NMR.
      Lancelot et al. Measurement of Scaled Residual Dipolar Couplings in Proteins Using Variable-angle Sample Spinning PDF
    • There are 12 more papers at ~brd/Bio/Papers/NMR/Residual-dipolar-coupling/Spinning/ on the unix file system.
  106. Date: TBA
    Presenting: TBA
    Topic: Minimized DEE and using A* Search to approximate K*

    Main reading:
    • Chapter 6.5 of Ryan Lilien's Ph.D. Thesis.

      All students: Be sure to review this paper, which we read earlier:

    • A Novel Ensemble-Based Scoring and Search Algorithm for Protein Redesign, and its Application to Modify the Substrate Specificity of the Gramicidin Synthetase A Phenylalanine Adenylation Enzyme. R. Lilien, B. Stevens, A. Anderson, and B. R. Donald. R. Lilien, B. Stevens, A. Anderson, and B. R. Donald. Journal of Computational Biology 2005; 12(6-7):740-761.
  107. Date: TBA
    No Class: Holiday.
  108. Date: TBA
    NMR ensemblePresenting: TBA
    Class Project: MEMS and Nanotechnology Techniques for Aligning Proteins in Solution

    Reading:
    • Plantenga, T.M. et al, "13C NMR Molecules Partially Alligned by Electric Field: A New Method for Determining the Orientation of the Dipole Moment", Chem. Phys. 48 (1980) 359-560.
    • Gaemers S. and A. Bax, "Morphology of Three Lyotropic Liqid Crystaline Biological NMR Media Studied by Translation Diffusion Anisontropy.", J. Am. Chem. Soc. 2001, 123, 12343-12352. PDF; Supporting material
    • Also review: Residual Dipolar Couplings in Structure Determination of Biomolecules, J. H. Prestegard et al, Chem Rev 2004. [PDF]
  109. Date: TBA
    Presenting: John Thomas, John MacMaster, Xiaoduan
    Last day of class.
    Class Projects


  110. Date: TBA
    Presenting: TBA
    Topic

    Reading:
    • paper 1
    • paper 2

    Syllabus