18.417: Introduction to Computational Molecular Biology

Syllabus

Computational structural biology aims to model and predict the structure of biomolecules (e.g., proteins, DNA, RNA). The topics covered will range from the classic techniques in the field (e.g. molecular dynamics, Monte Carlo, dynamic programming) to more recent advances in analyzing and predicting RNA and protein structure, ranging from Hidden Markov Models and 3D lattice models to attribute Grammars and tree Grammars.

The class is intended for grad students, senior and junior undergrads interested in the application of mathematical and computational methods to structural biology and also for biologists and biochemists interested in the algorithmic foundations of the approaches used in this field. Prerequisites: Basic understanding of algorithms. No biological background required. The class will provide background for any advanced methods discussed. The evaluation will consist of a mid-term exam and a final project.

Topics

RNAs:

Secondary structure prediction,
Multiple alignment,
Equilibrium statistical mechanics of RNAs,
Saturated structures and RNA shapes,
RNA mutants and RNA design,
RNA-RNA interaction,
RNA 3D structure and alignment,
RNA folding kynetics.

Proteins:

Secondary structure prediction,
Threading, side-chain packing,
Molecular mechanics, motion planning,
Protein folding on 3D lattice,
Structure template methods,
NMR related algorithms,
Folding pathways.

Image produced with RNAmovies

Course informations

Instructor: Jérôme Waldispühl
Co-Lecturer: Charles W. O'Donnell

Lectures: Tuesday-Thursday 9:30am - 11:00pm in 2-135.

Office hours: By appointment.

Report guidelines:

The length of report is expected to range between 2 and 4 pages. The document should contain the following sections:

Title and abstract (max. 10 lines).
Introduction including a brief statement of the motivations and a description of the structure of the document.
Methods (describe the algorithms).
Results (present the results of experiments).
Discussion (your conclusions and opinion).

Talks will be 20 minutes long followed by 10 minutes of open questions.

Schedule and Material

Lecture 1 (Feb. 3rd, 2009):
Introduction to Computational Structural Biology, Databases & Viewer. [Slides]

Lecture 2 (Feb. 5th, 2009):
Introduction to RNAs. Classical secondary structure prediction algorithms. [Slides]

Lecture 3 (Feb. 10th, 2009):
RNA sequence/structure alignment. [Slides]

Lecture 4 (Feb. 12th, 2009):
Stochastic RNA Secondary Structure Prediction (and brief comeback on Sankoff Algorithm). [Slides]

Lecture 5 (Feb. 19th, 2009):
Modeling RNA 3D structures. [Slides]

Lecture 6 (Feb. 25th, 2009):
Special Lecture by F. Major (joint with 18.418. Room 32-G575 at 11:30).

Lecture 7 (Feb. 26th, 2009):
RNA pseudo-knotted secondary structures. [Slides]

Lecture 8 (Mar. 3rd, 2009):
RNA-RNA Interaction Predictions. [Slides]

Lecture 9 (Mar. 5th, 2009):
RNA Sequence/Structure Maps and Neutral Networks. [Slides]

Lecture 10 (Mar. 9th, 2009): (lecture by C.W. O'Donnell)
Introduction to Protein Structure. [Slides]

Lecture 11 (Mar. 12th, 2009): (lecture by C.W. O'Donnell)
Molecular Dynamics. [Slides]

Lecture 12 (Mar. 17th, 2009):
Grammatical Modeling of RNA Secondary Structures. [Slides]

Lecture 13 (Mar. 19th, 2009):
Integrating experimental observations for RNA structure intermediates prediction.

Lecture 14 (Mar. 30th, 2009):
Protein Secondary Structure Prediction. [Slides]

Lecture 15 (Apr. 2nd, 2009):
Complement on Grammatical Modeling of RNA and Protein Structures. [Slides]

Lecture 16 (Apr. 7th, 2009):
Modeling and Predicting Transmembrane Protein Structures. [Slides]

Lecture 17 (Apr. 9th, 2009):
Residue Contact Prediction and NMR assignment. [Slides]

Lecture 18 (Apr. 14th, 2009):
Transmembrane β-barrel Super-Secondary Structure Prediction (Part II). [Slides]

Lecture 19 (Apr. 16th, 2009):
Protein folding on HP lattice models. [Slides]

Lecture 20 (Apr. 23th, 2009): (lecture by C.W. O'Donnell)
Comparative modeling and side-chain packing. [Slides]

Lecture 21 (Apr. 28th, 2009):
Folding routes on HP lattice models. [Slides]

Lecture 22 (Apr. 30th, 2009):
RNAMutants: Exploring the RNA mutation landscape. [Slides]

Lecture 23 (May 5th, 2009):
Protein structure prediction using NMR spectra. [Slides]

May 7th, 2009: No class.

May 12th, 2009: Project presentations. Class starts at 9am.

May 14th, 2009: Project presentations. Class starts at 9am.

References

Computational Molecular Biology: An Introduction
Peter Clote, Rolf Backofen
Wiley Series in Mathematical and Computational Biology

Credits

Notes have been released using material kindly provided by Peter Clote, Ivo Hofacker, David Mathews, Alain Laederach, Thomas Simonson and Jinbo Xu.