Computational methods in bioinformatics (2017-2018)
Lecture 7
Fold recognition;
De novo protein modelling;
Lattice models
Aims
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To introduce fold recognition.
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To introduce the ab initio protein folding problem.
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To give an overview of the protein structure prediction method of Simons
et al. (1997).
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To give an overview of the zipping and assembly method.
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To introduce lattice models for exploring protein folding.
Objectives
After this lecture you will be able to:
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describe in outline the threading method for fold recognition;
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describe the ab initio protein folding problem;
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describe in outline the protein structure prediction algorithm of
Simons et al. (1997);
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describe in outline the zipping and assembly method;
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discuss lattice models and their use in structural bioinformatics.
Supplementary Material
Some of the lecture slides are available on-line
(1 per page,
4 per page).
A detailed description of the derivation of pairwise potentials is
given in: Sippl, M.J. (1990) Calculation of conformational ensembles from
potentials of mean force: An approach to the knowledge-based prediction of
local structures in globular proteins", 213, 859-883
(doi:10.1016/S0022-2836(05)80269-4)
The ab initio protein structure prediction algorithm introduced in this
lecture is described in:
-
Simons, K.T., Kooperberg, C., Huang, E. and Baker, D. (1997)
Assembly of Protein Tertiary Structures from
Fragments with Similar Local Sequences using
Simulated Annealing and Bayesian Scoring Functions.
J. Mol. Biol., 268, 209-225
(doi:10.1006/jmbi.1997.0959)
The zipping and assembly method is described in:
-
Dill, K.A., Lucas, A., Hockenmaier, J., Huang, L., Chiang, D. and
Joshi, A.K. (2007)
Computational linguistics: A new tool for exploring biopolymer structures
and statistical mechanics.
Polymer, 48, 4289-4300
(doi:10.1016/j.polymer.2007.05.018)
-
Hockenmaier, J., Joshi, A.K. and Dill, K.A. (2007)
Routes are trees: The parsing perspective on protein folding.
Proteins: Structure, Function, and Bioinformatics, 66, 1-15
(doi:10.1002/prot.21195)
Last Modified: 19 November 2017
by Graham Kemp