[PPT] - Ligand Dynamics in Heme Proteins Ligand Dynamics in Heme Proteins PowerPoint Presentation

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ICERM Workshop 2012

Markus Meuwly Department of Chemistry University of Basel

Ligand Dynamics in Heme Proteins Ligand Dynamics in Heme Proteins

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ICERM Workshop 2012

Overview Overview

Introduction and Computational Techniques
Applications
Smoluchowski Treatment
Transition Networks
Protein- and Ligand-Motion
Spatial Averaging
Summary

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ICERM Workshop 2012

Overview Overview Small ligands play important functional roles in proteins. Heme-proteins (Mb, Hb, Ngb, trHb, etc.) bind ligands such as O2, NO, CO with various purposes:

Transport
Removal of NO
Neurotransmission, Vasodilation

Fundamental questions:

How do these molecules enter their host proteins
How do they move (cavities)
How do they bind (allostery)

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ICERM Workshop 2012

Overview Overview

The goal is to understand in general terms the processes of ligand dissociation, rebinding, recognition, and discrimination, and to explore ligand entrance and exit pathways in the framework of protein structure and dynamics, using myoglobin as a specific example. Comprehensive studies have been carried out over the time scale from femtoseconds to seconds, under a broad range of experimental conditions such as temperature, pressure, solvent viscosity, and pH, for several species of wild-type myoglobins and for variants of important amino acid residues. [Moffat, Biochem. (2001)] Our experiment shows that the pathway of a small molecule in its trajectory through a protein may be modified by site-directed mutagenesis, and that migration within the protein matrix to the active site involves a limited number of pre-existing cavities identified in the interior space of the protein. [Schlichting, PNAS (2000)]

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ICERM Workshop 2012

Ligand Dynamics in Heme-Proteins: The Bohr-effect Ligand Dynamics in Heme-Proteins: The Bohr-effect

Affinity (binding capacity) of Hb depends on pH and [CO2]. Low pH/high [CO2] leads to reduced O2 affinity; i.e. regulation R-state: relaxed, 6- coordinated structure, high- O2-affinity T-state: tense, 5- coordinated structure, low- O2-affinity

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ICERM Workshop 2012

Ligand Dynamics in Heme-Proteins Ligand Dynamics in Heme-Proteins Time scales for ligand motion “Logic” of ligand migration Comparison with experiment Protein- and ligand-motion

Schulten et al., Biophys. J. (2006) Maragliano et al., JACS (2010)

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ICERM Workshop 2012

Introduction: Protein Structure and Ligand Diffusion Introduction: Protein Structure and Ligand Diffusion

F. Schotte et al., Science 300, 1944 (2003)

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Introduction: Role of Simulations Introduction: Role of Simulations Understanding of, providing insights into and making predictions about mechanisms at molecular level. MD with improved/modified FFs

Relationship between structure, dynamics and spectroscopy?
What do ligands tell us about protein interiors?

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ICERM Workshop 2012

Introduction and Computational Techniques Introduction and Computational Techniques Intermolecular interactions Diffusive Dynamics Chemical Reactions

Fluctuating Charge Models
Multipolar Force Fields
Dissociative Force Fields
Morphing Potentials
Solving Smoluchowski

Equations on Rough Surfaces

Transition Networks
Reactive MD
Dissociative Force Fields

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ICERM Workshop 2012

Computational Techniques: Force Fields Computational Techniques: Force Fields

Force Field:

Atom-based energy expression Etot=Ebond+Enonbond

Bonded Terms

Bond Energies E = ½ k (x-xe)2 Angle Energies E = ½ k (-e)2 Torsion Energies E = Vn cos(n-e)2

Nonbonded Terms

Coulomb Eij = qiqj/40r Van der Waals Eij = 4ij (ij

12-ij 6)

ij= sqrt(i j ) ij=(rij/ij) ij=1/2(i +j) x   qi qi qj

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ICERM Workshop 2012

Molecular Simulations Molecular Simulations

Given a way to compute the interaction energy V (e.g. force field, quantum, semiempirical)

f a system it is then possible to determine physico-chemical properties from a molecular

simulation. The result will be a trajectory Using statistical mechanics, numerous experimental observables can be computed: Accuracy of the intermolecular interactions and the degree of sampling of the configurational space determine the quality of a simulation (and the observables derived from it).

   

x x F V t m     

   

t t v x ;

Temperature Specific heat Diffusion coefficient Infrared spectrum

NVT B V

E T k C

2 2

1  





 

N i i i B B

m Nk Nk K T

1 2

3 1 3 2 p

   





 3 1 t dt D

i i

v v

       

t t i dt I μ μ 0



  

    exp

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ICERM Workshop 2012

Mb: Ligand Rebinding in MbCO (100 ns rebinding) Mb: Ligand Rebinding in MbCO (100 ns rebinding)

10 8 6 4 2 5 – 5 – 10 – 15 – 20 DP A Xe4(2) Xe4(1) R/A G(kcal/mol) DP Xe4(1) Xe4(2) A Fe 4 1 –2 –3 10 6 2 – 6 – 4 – 2 4 8 v/A 2 10 6 2 – 6 – 4 – 2 4 8 v/A X X Fe 5 – 13 – 9 – 5 – 1 1 3 u/A

Banushkina and Meuwly, JCTC, 2, 208 (2005); JPCB, 109, 16911 (2005); JCP (2007)

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ICERM Workshop 2012

Smoluchowski simulation of protein folding based on pre-calculated FES.

U F

Sheinerman and Brooks, PNAS (1998) Roder et al., Nat. Struc. Biol. (1999)

MD simulations of protein G in explicit solvent. Experimental folding times: 600 – 700 s 2-30 ms (denaturant dependent)

Solving Smoluchowski Equations on Rough Potentials

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SE difficult to solve on rough PESs Use of Hierarchical Discrete Approximation:1 Introduce a hierarchy of grids

1 Banushkina and Meuwly, JCTC, 2, 218 (2005)

Solving Smoluchowski Equations on Rough Potentials

ICERM Workshop 2012

Having a procedure to solve SEs on rough PESs we can no pre-compute the free energy surface for ligand motion and avoid the long-time scale problem present in explicit sampling. From several independent trajectories this FES can be constructed efficiently.

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ICERM Workshop 2012

10 8 6 4 2 5 – 5 – 10 – 15 – 20 DP A Xe4(2) Xe4(1) R/A G(kcal/mol) DP Xe4(1) Xe4(2) A Fe 4 1 –2 –3 10 6 2 – 6 – 4 – 2 4 8 v/A 2 10 6 2 – 6 – 4 – 2 4 8 v/A X X Fe 5 – 13 – 9 – 5 – 1 1 3 u/A

Solving Smoluchowski Equations on Rough Potentials

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ICERM Workshop 2012