Modeling and Understanding Complex Biomolecular Systems and Processes.
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Modeling and Understanding Complex Biomolecular Systems and Processes. Application in Nanosciences, Biotechnology and Biomedicine. Bogdan Lesyng ICM and Faculty of Physiscs, Warsaw University (http://www.icm.edu.pl/~lesyng/) and European Centre of Excellence for

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Modeling and understanding complex biomolecular systems and processes

Modeling and Understanding Complex Biomolecular Systems and Processes.

Application in Nanosciences, Biotechnology and Biomedicine

Bogdan Lesyng

ICM and Faculty of Physiscs, Warsaw University (http://www.icm.edu.pl/~lesyng/)

and

European Centre of Excellence for

Multiscale Biomolecular Modelling,

Bioinformatics and Applications

(http://www.icm.edu.pl/mamba)

Trento, 16-17 December, 2004


Modeling and understanding complex biomolecular systems and processes

Sequences

at the protein &

nucleic acids levels

3D & electronic

structure

Function

Dynamics, classical and/or quantum one in the real molecular environment

1 RPDFCLEPPY 10 11 TGPCKARIIR 20 21 YFYNAKAGLC 30 31 QTFVYGGCRA 40 41 KRNNFKSAED 50 51 CMRTCGGA 58

Cell(s), structure(s) & functions

Metabolic pathways & signalling

Sub-cellular

structures & processes


Modeling and understanding complex biomolecular systems and processes

In our organisms

we have ~ 103

protein kinases

and phosphatases

which

phosphorylate/

dephosphorylate

other proteins

activating or

disactivating

them.

These are

controllers

of most of

methabolic

pathways.


Modeling and understanding complex biomolecular systems and processes

A Protein Kinase Molecule with ATP (catalytic domain)


Modeling and understanding complex biomolecular systems and processes

Designing inhibitors

Information, conference on

”Inhibitors of Protein Kinases”,

and workshops on

”Molecular Recognition Processes”

June 26-30, 2005 Warsaw

http://www.icm.edu.pl/

ipk2005/


Limitations of conventional bioinformatics approaches in structure predicion

Limitations of conventional bioinformatics approachesin structure predicion

  • Homology based structure prediction methods are effective for those families of proteins which crystallize. They fail, for example, for membrane proteins.

  • Methods developed for proteins fail for nucleic acids.

  • Folding of nucleic acids, like folding of single-stranded RNA, could be even more important than protein folding (to learn what is the role of noncoding regions)


Multi scale modeling classes of models

Multi-scale modeling. Classes of models

Microscopic models

Mesoscopic models


Modeling and understanding complex biomolecular systems and processes

Recently I participated in the Robert Welch Foundation Conference on „Chemistry of Self-Organizing Hybrid Materials”, Houston, Oct.25- 26, 2004. Selected topics below:

  • Biologically Active Self-Assembling Peptide Nanotubes

  • Conditional Control of BiopolymerSelf Assembly and Activity

  • Electroactive Functional Polymers and Nanocomposites

  • Nanotechnology : Carbon Nanotubes, Nanomachines and Molecular Computers

  • Using Self-Assembly to Create Electronic Materials

Objects and processes listed above require, amongst others, the knowledge

of effective iteraction potentials – refer to the following port of my talk.


Modeling and understanding complex biomolecular systems and processes

Microscopic generators of the potential energy function

AVB – (quantum)

AVB/GROMOS - (quantum-classical)

SCC-DFTB - (quantum)

SCC-DFTB/GROMOS - (quantum-classical)

SCC-DFTB/CHARMM - (quantum -classical)

....

Dynamics

MD (classical)

QD (quantum)

QCMD (quantum-classical)

....

  • Mesoscopic potential energy functions

  • Poisson-Boltzmann (PB)

  • Generalized Born (GB)

  • ....


Modeling and understanding complex biomolecular systems and processes

SCC-DFTB Method

(Self Consistent Charge Density Functional Based Tight Binding Method,

SCC DFTB, Frauenheim et al. Phys Stat. Sol. 217, 41, 2000)

basic DFT concepts:

total electron

density

1-electron orbitals

1-electron

Hamiltonian

(Kohn-Sham equation)


Modeling and understanding complex biomolecular systems and processes

New generation of charges capable reproducing electrostatic properties, in particular molecular dipole moments.

J.Li, T.Zhu, C.Cramer, D.Truhlar, J. Phys. Chem. A, 102, 1821(1998)

CM3/SCC-DFTB charges

J.A. Kalinowski, B.Lesyng, J.D. Thompson, Ch.J. Cramer, D.G. Truhlar,Class IV Charge Model for the Self-Consistent Charge Density-Functional Tight-Binding Method, J. Phys. Chem. A, 108, 2545-2549 (2004)


Modeling and understanding complex biomolecular systems and processes

  • Looking for very fast algorithms to compute the mean-field (mesoscopic) electrostatic energy.

  • Born models:

  • M.Born, Z.Phys., 1,45(1920)

  • R.Constanciel and R.Contreas, Theor.Chim.Acta, 65,111(1984)

  • W.C.Still, A.Tempczyk,R.C.Hawlely,T.Hendrikson, J.Am.Chem.Soc.,112,6127(1990)

  • D.Bashford, D.Case, Annu.Rev.Phys.Chem., 51,129(2000)

  • If we know, so called Born-radii of atoms, we can very quickly compute the electrostatic energy. A Born radius is a geometrical property !


Modeling and understanding complex biomolecular systems and processes

Coulomb Field appr.

(I)

Kirkwood Model

(II)

(III)

M.Feig, W.Im, C.L.Brooks, J.Chem.Phys.,120,903-911(2004)

(IV)


Modeling and understanding complex biomolecular systems and processes

Ratio of the GB solvation enery to the Kirkwood solvation energy


Modeling and understanding complex biomolecular systems and processes

There are non-solved problems (like hydrophobic potentials), but it looks likein the near future we will have a new generation of effective (mean-field, mesoscopic) molecular interaction potentials, which can be applied to structure prediction problems (regardless of the type of biopolymers !)or ligand – biomolecule interactions.


Modeling and understanding complex biomolecular systems and processes

Acknowledgements:

PhD students:

Jarek Kalinowski

Piotr Kmieć

Magda Gruziel

Michał Wojciechowski

Collaboration:

Prof. T. FrauenheimSCC-DFTB, University of Paderborn, Germany

Dr. M. Elstner

Prof. D. TruhlarCM3-charges, Minnesota Solvation Data Base

Dr. J. ThompsonUniversity of Minnesota, USA

Dr. C. Cramer

Prof. J.A.McCammonTitration of proteins

University of California at San Diego, USA

Studies supported in part by ”European CoE for Multiscale Biomolecular Modelling, Bioinformatics and Applications” , ICM, Warsaw University.


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