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- Introduction to Protein Folding and Misfolding
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1. Protein folding and misfolding: from theory to therapy
- Prof. Christopher Dobson
- Stability and Kinetics of Protein Folding
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2. Mechanisms of protein folding reactions
- Prof. Thomas Kiefhaber
- Protein Folding Theory
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3. Mapping disordered proteins with single-molecule FRET
- Dr. Hagen Hofmann
- Protein Folding Simulations
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4. Protein folding
- Prof. Eugene Shakhnovich
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5. Simulating protein folding with full atomistic detail
- Prof. Vijay Pande
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6. Molecular dynamics simulations of protein dynamics, unfolding and misfolding
- Prof. Valerie Daggett
- Protein Folding Inside the Cell: Chaperones
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7. Protein folding Inside the cell: macromolecular crowding and protein aggregation
- Prof. Emeritus R. John Ellis
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8. Chaperone mechanisms in cellular protein folding
- Prof. Dr. F. Ulrich Hartl
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9. Quality control of proteins mislocalized to the cytosol
- Dr. Ramanujan Hegde
- Protein Misfolding and Disease
- Protein Design
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11. Designing proteins with life sustaining activities 1
- Prof. Michael Hecht
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12. Designing proteins with life sustaining activities 2
- Prof. Michael Hecht
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13. Folding and design of helical repeat proteins
- Prof. Lynne Regan
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14. Design and engineering of zinc-finger domains
- Prof. Jacqui Matthews
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15. Prediction and design of protein structures and interactions
- Prof. David Baker
- Amyloid Fibrils: Structure, Formation and Nanotechnology
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16. Amyloid fibrils as functional nanomaterials
- Prof. Juliet Gerrard
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17. Functional amyloid fibrils from fungi and viruses
- Prof. Margaret Sunde
- Intrinsically disordered Proteins
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18. Fuzzy protein theory for disordered proteins
- Prof. Monika Fuxreiter
- Intersection of RNA, translation and protein aggregation.
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19. Expanding roles of RNA-binding proteins in neurodegenerative diseases
- Prof. Aaron D. Gitler
- Proteostasis
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20. Adapting proteostasis to ameliorate aggregation-associated amyloid diseases
- Dr. Jeffery W. Kelly
- Archived Lectures *These may not cover the latest advances in the field
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21. Amyloidosis: disease caused by amyloid
- Prof. Mark Pepys
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22. Protein folding and dynamics from single molecule spectroscopy
- Prof. Dr. Benjamin Schuler
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23. Prion diseases
- Prof. Fred Cohen
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25. Titin I27: a protein with a complex folding landscape
- Dr. Jane Clarke
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26. Novel proteins from designed combinatorial libraries
- Prof. Michael Hecht
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28. The sequence determinants of amyloid fibril formation
- Prof. Fabrizio Chiti
Printable Handouts
Navigable Slide Index
- Introduction
- Structural biology should be computable
- The computer program - Rosetta
- Model of macromolecular interactions
- Example: hydrogen bonding
- Formamide dimer
- Conformational sampling
- Docking low-resolution search
- Rosetta high resolution refinement (1)
- Docking protocol
- Side chain flexibility
- Details of T12 interface
- Example of target 15
- Accurate side chain modeling
- Details of T15 interface
- Example of target 14
- Details of T14 interface
- Backbone changes
- Modeling backbone movement
- CASP6 T0198: PhoU domain repeat
- CASP6 T0272_1
- CASP6 T0212
- Automated domain parsing: CASP6 T0248
- Rosetta high resolution refinement (2)
- Movie of refinement process
- Sharp decrease in free energy close to native state
- T0281 ab initio prediction
- High resolution search figure of 1R69
- Prediction of 1R69
- High resolution search figure of 1ubq
- Prediction of 1ubq
- High resolution search figure of 1b72
- Prediction of 1b72
- High resolution search figure of 2REB
- Prediction of 2REB
- High resolution search figure of 1DTJ
- Prediction of 1DTJ
- Inadequate sampling causes mistake in prediction
- High resolution refinement of CASP target 199
- High resolution refinement of CASP target 263
- Computing structural biology
- Computational protein design
- A novel backbone and topology
- Possible low energy arrangement of side chains
- Flexible backbone protein design
- TOP7 is highly stable and well-folded
- TOP7 x-ray structure has correct topology
- TOP7 folding landscape
- Protein interface design
- E-DreI structure versus design
- Design of novel H bond network
- High resolution modeling is starting to work
- High resolution prediction: why does it work?
- Macromolecules free energy landscares
- Properties of free energy landscapes
- Acknowledgements
Topics Covered
- Modeling of macromolecular interactions
- Conformational sampling
- Docking low-resolution search
- High resolution refinement
- Docking protocol
- Side chain flexibility and modeling
- Ab initio structure prediction
- Computational protein design
- Simultaneous sequence-structure optimization
- Protein interface design
- Properties of free energy landscapes of macromolecules
Talk Citation
Baker, D. (2015, July 16). Prediction and design of protein structures and interactions [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved November 22, 2024, from https://doi.org/10.69645/CSAV1785.Export Citation (RIS)
Publication History
Financial Disclosures
- Prof. David Baker has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.
A selection of talks on Biochemistry
Transcript
Please wait while the transcript is being prepared...
0:04
Structural biology should be computable.
It's been known for over 40 years that
protein structures are completely determined by their amino acid sequences.
For almost all protein structures and all protein-protein complexes,
the experimentally observed structures and
conformations are almost certain to correspond to global free energy minima.
So, it should be possible to predict the structures of proteins and
protein-protein complexes readily by
identifying the global free energy minima for a polypeptide chain,
in case of protein structure prediction,
or identifying the global free energy minima for two proteins coming together,
which will be the prediction of protein complexes problem.
If we could do this, it would both be a fundamental test of
our understanding of macromolecular and interactions,
and it would also be huge practical relevance as
the cost of determining protein structures computationally,
would be a small fraction of the cost of
current experimental methods such as X-ray crystallography, and NMR spectroscopy.
But, as you know, today,
structural biology is not computed,
it is primarily experimental science.
And what I'm going to tell you about today is progress
towards making structural biology computable.
1:13
The work I'm going to tell you about today is carried out
with a computer program being developed in my group,
and groups of people left my group in
the last seven years that has the following structure.
We have a model of the energetics of inter and intramolecular interactions,
which allows us to compute the energy of
conformation of a protein or a protein- protein complex.
And given that model,
we can do one of two things.
We can either do a prediction problem,
in which we're given for example,
the sequence of a protein and asked to find
the lowest energy structure for that sequence,
that would correspond to the Ab initio structure prediction problem.
We can also take the structures of two proteins,
and try and find the lowest energy docked arrangement,
that would be the protein-protein docking problem.
In these cases, we're given the sequence or
the structures and trying to find the lowest energy conformation.
Now, the inverse problem is the design problem,
where we're given a structure and we want to find the lowest energy sequence.
So for example, that would be the problem designing a new protein structure,
a sequence that would fold to give a new structure or the problem of
given a protein-protein complex designing an interface between the two proteins,
which will allow them to bind to each other tightly.
This approach has been extended to protein ligand interactions.
So for example, ligand docking,
the design of new enzymes and to protein DNA interactions.
In particular, the design of new DNA binding proteins with new specificities,
which is something that we've had a fair amount of success with lately.
However in this lecture, I'm going to focus on the prediction and design of
protein structure and protein-protein interactions.