Computational Biology Part 1: Biomolecular Modeling

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Computational BiologyPart 1 Biomolecular
Modeling
Instructor Prof. Jesus Izaguirre Textbook Tamar
Schlick, Molecular Modeling and Simulation An
Interdisciplinary Guide, Springer-Verlag,
Berlin-New York, in press, 2002 Reference C.
Brooks, M. Karplus, B. Pettitt, Proteins A
Theoretical Perspective of Dynamics, Structure,
and Thermodynamics, Wiley, 1988
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Outline

• What is biomolecular modeling?
• Historical perspective
• Theory and experiments
• Protein characterization
• Computational successes
• Remaining challenges

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What is biomolecular modeling?

• Application of computational models to understand
  the structure, dynamics, and thermodynamics of
  biological molecules
• The models must be tailored to the question at
  hand Schrodinger equation is not the answer to
  everything! Reductionist view bound to fail!
• This implies that biomolecular modeling must be
  both multidisciplinary and multiscale

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Historical Perspective

• 1946 MD calculation
• 1960 force fields
• 1969 Levinthals paradox on protein folding
• 1970 MD of biological molecules
• 1971 protein data bank
• 1998 ion channel protein crystal structure
• 1999 IBM announces blue gene project

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Theoretical Foundations

• Born-Oppenheimer approximation (fixed nuclei)
• Force field parameters for families of chemical
  compounds
• System modeled using Newtons equations of motion
• Examples hard spheres simulations (alder and
  Wainwright, 1959) Liquid water (Rahman and
  Stillinger, 1970) BPTI (McCammon and Karplus)
  Villin headpiece (Duan and Kollman, 1998)

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Experimental Foundations I

• X-ray crystallography
• Analysis of the X-ray diffraction pattern
  produced when a beam of X-rays is directed onto a
  well-ordered crystal. The phase has to be
  reconstructed.
• Phase problem solved by direct method for small
  molecules
• For larger molecules, sophisticated Multiple
  Isomorphous Replacement (MIR) technique used
• Current resolution below 2 \AA
• Protein crystallography
• Difficult to grow well-ordered crystals
• Early success in predicting alpha helices and
  beta sheets (Pauling, 1950s)

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Experimental Foundations II

• NMR Spectroscopy
• Nuclear Magnetic Resonance provides structural
  and dynamic information about molecules. It is
  not as detailed as X-ray, limited to masses of 35
  kDa
• Distances between neighboring hydrogens are used
  to reconstruct the 3D structure using global
  optimization

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Proteins I

• Polypeptide chains made up of amino acids or
  residues linked by peptide bonds
• 20 aminoacids
• 50-500 residues, 1000-10000 atoms
• Native structure believed to correspond to energy
  minimum, since proteins unfold when temperature
  is increased

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Proteins II

• Secondary structure alpha helices, beta sheets,
  turns
• Tertiary structure proteins are tightly packed,
  with hydrophobic groups in the core and charged
  sidechains in the surface
• Quaternary structure protein domains may
  assemble into so called quaternary structures

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Proteins III

• Protein motions of importance are torsional
  oscillations about the bonds that link groups
  together
• Substantial displacements of groups occur over
  long time intervals
• Collective motions either local (cage structure)
  or rigid-body (displacement of different regions)
• What is the importance of these fluctuations for
  biological function?

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Proteins IV

• Effect of fluctuations
• Thermodynamics equilibrium behavior important
  examples, energy of ligand binding
• Dynamics displacements from average structure
  important example, local sidechain motions that
  act as conformational gates in oxygen transport
  myoglobin, enzymes, ion channels

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Proteins V Local Motions

• 0.01-5 AA, 1 fs -0.1s
• Atomic fluctuations
• Small displacements for substrate binding in
  enzymes
• Energy source for barrier crossing and other
  activated processes (e.g., ring flips)
• Sidechain motions
• Opening pathways for ligand (myoglobin)
• Closing active site
• Loop motions
• Disorder-to-order transition as part of virus
  formation

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Proteins VI Rigid-Body Motions

• 1-10 AA, 1 ns 1 s
• Helix motions
• Transitions between substrates (myoglobin)
• Hinge-bending motions
• Gating of active-site region (liver alcohol
  dehydroginase)
• Increasing binding range of antigens (antibodies)

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Proteins VII Large Scale Motion

• gt 5 AA, 1 microsecond 10000 s
• Helix-coil transition
• Activation of hormones
• Protein folding transition
• Dissociation
• Formation of viruses
• Folding and unfolding transition
• Synthesis and degradation of proteins
• Role of motions sometimes only inferred from two
  or more conformations in structural studies

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Study of Dynamics I

• The computational study of atomic fluctuations in
  BPTI and other proteins has shown that
• Directional character of active-site fluctuations
  in enzymes contributes to catalysis
• Small amplitude fluctuations are lubricant
• It may be possible to extrapolate from short time
  fluctuations to larger-scale protein motions

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Study of Dynamics II

• Collective motions particularly important for
  biological function, e.g., displacements for
  transition from inactive to active
• Extended nature of these motions makes them
  sensitive to environment great difference
  between vacuum and solution simulations
• Collective motions transmit external solvent
  effects to protein interior

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Study of Dynamics III

• For the related storage protein, myoglobin
• Fluctuations in the globin are essential to
  binding the protein matrix in X-ray is so
  tightly packed that there is no low energy path
  for the ligand to enter or leave the heme pocket
• Only through structural fluctuations can the
  barriers be lowered sufficiently
• Demonstrated through energy minimization and
  molecular dynamics

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Study of Dynamics IV

• For the transport protein hemoglobin there are
  several important motions
• Oxygen binding produces tertiary structural
  change
• A quaternary structural change from deoxy (low
  oxygen affinity) to oxy configuration takes
  place. This transmits information over a long
  distance
• From the X-ray deoxy and oxy structures, a
  stochastic reaction path has been found. Detailed
  ligand binding has been performed using MD. A
  statistical mechanical model has provided
  coupling between these two processes

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Study of Dynamics VI

• Three open problems are the following
• Ion channel gating highly correlated
  fluctuations are likely to be of great
  importance. Long time dynamics problem
• Flexible docking for MMP, enzymes, etc.,
  fluctuations enter into thermodynamics and
  kinetic of reactions. Sampling problem
• Protein folding too complicated for full
  treatment but for smallest proteins, beyond
  current methodology. Coarsening problem

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Lengthening scales DPD

• Dissipative Particle Dynamics combines coarsening
  of atoms into fluid packages with dissipative
  pair interactions, and a stochastic pair
  interaction
• Total momentum conserved

• Self-organization of lipid bilayer,
  self-assembled aggregates formed by amphiphilic
  lipid molecules in water.

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Lengthening of Scales SRP

• Enzyme simulation of a ms using stochastic
  reaction path disadvantage need initial and
  final configuration
• Finds a trajectory where global energy is
  minimized

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Lengthening of Scales MUSICO

• Multiscale molecular dynamics combining
• Symplectic splitting into nearly linear and
  nonlinear parts
• Implicit integration of linear part (similar to
  SRP) with constraining of internal d.o.f
• Explicit treatment of highly nonlinear part
• Optional pairwise stochasticity for stability
• No coarsening yet

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Scalable Parallelization of ProtoMol
ProtoMol--parallel software framework for the
simulation of bio-molecules

• OBJECTIVE Make ProtoMol a more scalable parallel
  program
• Hundreds of nodes
• Heterogeneous platforms

• APPROACH
• Abstract parallel layer
• Dynamic load balancing
• Multithreading
• More scalable algorithms

ProtoMol is open source and available at
http//www.cse.nd.edu/lcls/Protomol.html
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Web-based Simulation Services
Simulation Request
Results via XML
ProtoMol Parallel Server

• OBJECTIVE Make ProtoMol a web application
• Web service for molecular and cellular
  simulations
• Component that provides data and simulation
  capabilities through the web

• APPROACH
• .NET platform for Windows and Linux
• .NETMicrosofts platform for XML Web services

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Interactive Simulation Interfaces

• OBJECTIVE Interactive interfaces for ProtoMol
• User friendly interface to setup, monitor, and
  steer simulations
• Ability to quickly experiment with molecules and
  cells
• APPROACH
• 3-D Visualization using OpenGL
• Sockets interface between ProtoMol and
  visualization component
• Haptic Device interface

A haptic device interface was demonstrated at
SuperComputing 2000, and will be again at the
2001 event.
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Acknowledgements

• The LCLS would like to thank the following--
• National Science Foundation Biocomplexity grant
  PHY-0083653
• Department of Computer Science and Engineering,
  Univ. of Notre Dame
• and our Collaborators
• Dr. Mark Alber, Mathematics and Center for
  Applied Mathematics, Notre Dame
• Dr. Petter E. Bjorstad, Institutt for
  Informatikk, U. of Bergen, Norway
• Dr. Gabor Forgacs, Physics and Biology,
  University of Missouri-Columbia
• Dr. James A. Glazier, Physics, Notre Dame
• Dr. George Hentschel, Physics, Emory University
• Dr. Edward Maginn, Chemical Engineering, Notre
  Dame
• Dr. J. Andrew McCammon, Chemistry Biochemistry,
  University of California, San Diego
• Dr. Stuart Newman, Cell Biology and Anatomy, New
  York Medical College
• Dr. Martin Tenniswood, Biological Sciences and
  Walther Cancer Institute, Notre Dame
• Dr. Robert Skeel, Computer Science and Beckman
  Institute, University of Illinois at
  Urbana-Champaign