Forces and prediction of protein structure
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Forces and Prediction of Protein Structure. Ming-Jing Hwang ( 黃明經 ) Institute of Biomedical Sciences Academia Sinica. http://gln.ibms.sinica.edu.tw/. Sequence - Structure - Function.

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Forces and prediction of protein structure

Forces and Prediction of Protein Structure

Ming-Jing Hwang (黃明經)

Institute of Biomedical Sciences

Academia Sinica

http://gln.ibms.sinica.edu.tw/


Sequence structure function

Sequence - Structure - Function

MADWVTGKVTKVQNWTDALFSLTVHAPVLPFTAGQFTKLGLEIDGERVQRAYSYVNSPDNPDLEFYLVTVPDGKLSPRLAALKPGDEVQVVSEAAGFFVLDEVPHCETLWMLATGTAIGPYLSILR


Sequence structure gap

Sequence/Structure Gap

Current (May 26, 2005) entries in protein sequence and structure database:

  • SWISS-PROT/TREMBL : 181,821/1,748,002

  • PDB : 31,059

Sequence

Structure


Structure prediction methods

Structure Prediction Methods

Homology modeling

Fold recognition

ab initio

0 10 20 30 40 50 60 70 80 90 100

% sequence identity


Levinthal s paradox 1969

Levinthal’s paradox (1969)

  • If we assume three possible states for every flexible dihedral angle in the backbone of a 100-residue protein, the number of possible backbone configurations is 3200. Even an incredibly fast computational or physical sampling in 10-15 s would mean that a complete sampling would take 1080 s, which exceeds the age of the universe by more than 60 orders of magnitude.

  • Yet proteins fold in seconds or less!

Berendsen


Energy landscapes of protein folding

Energy landscapes of protein folding

Borman, C&E News, 1998


Forces and prediction of protein structure

Levitt’s lecture for S*


Forces and prediction of protein structure

Levitt


Forces and prediction of protein structure

Levitt


Other factors

Other factors

  • Formation of 2nd elements

  • Packing of 2nd elements

  • Topologies of fold

  • Metal/co-factor binding

  • Disulfide bond


Ab initio new fold prediction

Ab initio/new fold prediction

  • Physics-based (laws of physics)

  • Knowledge-based (rules of evolution)


Forces and prediction of protein structure

Levitt


Forces and prediction of protein structure

Levitt


Forces and prediction of protein structure

Levitt


Forces and prediction of protein structure

Levitt


Forces and prediction of protein structure

Levitt


Forces and prediction of protein structure

Levitt


Forces and prediction of protein structure

Levitt


Forces and prediction of protein structure

Levitt


Forces and prediction of protein structure

Levitt


Forces and prediction of protein structure

Levitt


Forces and prediction of protein structure

Levitt


Forces and prediction of protein structure

Levitt


Forces and prediction of protein structure

Levitt


Molecular mechanics force field

Molecular Mechanics (Force Field)


Forces and prediction of protein structure

Levitt


1 microsecond md simulation

1-microsecond MD simulation

980ns

  • villin headpiece

  • 36 a.a.

  • 3000 H2O

  • 12,000 atoms

  • 256 CPUs (CRAY)

  • ~4 months

  • single trajectory

Duan & Kollman, 1998


Protein folding by md

Protein folding by MD

PROTEIN FOLDING:A Glimpse of the Holy Grail?

Herman J. C. Berendsen*

"The Grail had many different manifestations throughout its long history, and many have claimed to possess it or its like". We might have seen a glimpse of it, but the brave knights must prepare for a long pursuit.


Massively distributed computing

Massively distributed computing

  • [email protected]:

  • [email protected]

  • Distributed folding

  • Sengent’s drug design

  • [email protected]


Forces and prediction of protein structure

Massively distributed computing

Letters to nature (2002)

  • engineered protein (BBA5)

  • zinc finger fold (w/o metal)

  • 23 a.a.

  • solvation model

  • thousands of trajectories each of 5-20 ns, totaling 700 ms

  • [email protected]

  • 30,000 internet volunteers

  • several months, or ~a million CPU days of simulation


Energy landscapes of protein folding1

Energy landscapes of protein folding

Borman, C&E News, 1998


Protein folding prediction technique

Protein-folding prediction technique

CGU: Convex Global

Underestimation

- K. Dill’s group


Challenges of physics based methods

Challenges of physics-based methods

  • Simulation time scale

  • Computing power

  • Sampling

  • Accuracy of energy functions


Structure prediction methods1

Structure Prediction Methods

Homology modeling

Fold recognition

ab initio

0 10 20 30 40 50 60 70 80 90 100

% sequence identity


Flowchart of homology comparative modeling

Flowchart of homology (comparative) modeling

From Marti-Renom et al.


Fold recognition

Fold recognition

Find, from a library of folds, the 3D template

that accommodates the target sequence best.

Also known as “threading” or “inverse folding”

Useful for twilight-zone sequences


Fold recognition aligning sequence to structure

Fold recognition (aligning sequence to structure)

(David Shortle, 2000)


Forces and prediction of protein structure

3D->1D score


Forces and prediction of protein structure

On X-ray, NMR, and computed models


Forces and prediction of protein structure

(Rost, 1996)


Forces and prediction of protein structure

Reliability and uses of comparative models

Marti-Renom et al. (2000)


Pitfalls of comparative modeling

Pitfalls of comparative modeling

  • Cannot correct alignment errors

  • More similar to template than to true structure

  • Cannot predict novel folds


Ab initio new fold prediction1

Ab initio/new fold prediction

  • Physics-based (laws of physics)

  • Knowledge-based (rules of evolution)


From 1d 2d 3d

From 1D  2D  3D

Primary

LGINCRGSSQCGLSGGNLMVRIRDQACGNQGQTWCPGERRAKVCGTGNSISAYVQSTNNCISGTEACRHLTNLVNHGCRVCGSDPLYAGNDVSRGQLTVNYVNSC

seq. to str. mapping

Secondary(fragment)

Tertiary

fragment assembly


Casp experiments

CASP Experiments


One lab dominated in casp4

One group dominates the ab initio (knowledge-based) prediction

One lab dominated in CASP4


Some casp4 successes

Some CASP4 successes

Baker’s group


Ab initio structure prediction server

Ab initio structure prediction server


Forces and prediction of protein structure

Science 2003


A computer designed protein 93 aa with 1 2 a resolution

A computer-designed protein (93 aa) with 1.2 A resolution


Structure prediction servers

Structure prediction servers

http://bioinfo.pl/cafasp/list.html


Thank you

Thank You!


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