Computational Molecular Biology Protein - Ligand And ...molsim.sci.univr.it/2013_biocomp/Docking.pdf · Computational Molecular Biology Protein - Ligand And Protein - Protein Docking

Computational Molecular Biology

Protein - Ligand

And Protein - Protein Docking Methods

Prof. Alejandro Giorge1 Dr. Francesco Musiani

Part 1: Protein - Ligand Docking Methods

What is the protein-ligand docking (molecular docking)

Goal: Given a protein structure, predict its ligands and where they bind

Applications:

v Function prediction v Drug design v Mechanisms

Protein-ligand docking: QUESTIONS

v  Where will the ligand bind?

v  Which ligand will bind?

v  How will the ligand bind?

v  When?

v  Where?

v  Why?

In other words: given a protein and a ligand, determine the poses and conformations

of the ligand minimizing the total energy of the protein-ligand complex

In practice…

Challenges…

Predicting ligand-binding energies by searching in the space

of possible poses and conformations

Challenges…



Relative position (3 degrees of freedom) Relative orientation (3 degrees of freedom)

Rotatable bonds in ligand (N degrees of freedom)

Challenges…



Relative position (3 degrees of freedom) Relative orientation (3 degrees of freedom)

Rotatable bonds in ligand (N degrees of freedom) Rotatable bonds in protein (M degrees of freedom)

Challenges…

Searching poses & conformations v Systematic search v Molecular dynamics v Simulated annealing v Genetic algorithms

v  Incremental construction v Rotamer libraries

Scoring functions

v Molecular mechanics v Empirical functions v Knowledge-based

Results & Discussion

v Clustering

Intra- and Inter-molecular forces

Intramolecular Forces (covalent) v Bond lengths v Bond angles

v Dihedral angles

Intermolecular Forces (non covalent) v Electrostatics

v Dipolar interactions v Hydrogen bonding v Hydrophobicity v van der Waals v Pi-stacking

Intra- and Inter-molecular forces

Coulombic interactions…

Arg

Ligand

Hydrogen bonds

Trypsin and substrate Mannitol Dehydrogenase and NAD

Salt bridges

Salt bridges and ligand binding

Binding of napsagatran to thrombin

Pi-Stacking Interactions: end to face

Pi-Stacking interactions: face to face

Cation-pi interactions…

Interactions with metal ions

Hydrophobicity

Binding pocket becames «interior» upon compexa6on with ligand

Big penality: charged or polar groups buried but umpaired

Energe6c contribu6on is propor6onal to the size of the surface buried upon ligand binding (e.g. –CH3 group (25 Å2): 3 to 6 kcal/mol)

Solvation and desolvation

ΔG (binding, vacuo)

ΔG (binding, soluFon)

ΔG (soluFon (E+I))

ΔG (soluFon (EI))



v  Rupture of H-‐bonds within water matrix v  Reform H-‐bonds

v  Reorganize water molecules at surface v  Bury a hydrophobic pocket surface v  Loose degrees of freedom v  Some water molecules released

ΔG (binding, vacuo)

ΔG (binding, soluFon)

ΔG (soluFon (E+I))

ΔG (soluFon (EI))

Scoring functions

Molecular mechanics force fields: • CHARMM [Brooks83] • AMBER [Cornell95]

Empirical methods:

• ChemScore [Eldridge97] • GlideScore [Friesner04]

• AutoDock [Morris98]

Knowledge-based methods • PMF [Muegge99]

• Bleep [Mitchell99] • DrugScore [Gohlke00]

Empirical scoring functions

Empirical scoring functions

Macromolecular docking: empirical scoring function

Van der Waals

H-‐bond

ElectrostaFcs

SolvaFon

Torsional angles

VdW H-‐bond Elec

Energy

Distance Distance Distance

Computing scoring functions

Computing scoring functions

v Systematic search

v Molecular dynamics

v Simulated annealing

v Genetic algorithms

v Incremental construction

v Rotamer libraries

Searching poses & conformations

Systematic search

Uniform sampling of search space: Relative position (3 Degrees of Freedom (DoF))

Relative orientation (3 DoF) Rotable bonds in ligand (m DoF) Rotable bonds in protein (n DoF)

Search space dimensions: 3 + 3 + m + n

Systematic search

Uniform sampling of search space: Exhaustive, deterministic

Quality dependent on granularity of sampling Feasible only for low-dimensional problems

Simulated annealing

Monte Carlo search of parameter space: v Start from a random or specific state (position, orientation, conformation)

v Make a random state changes, accepting up-hill moves with probability dictated by “temperature”

v Reduce temperature after each move

v Stop after temperature gets very small

Genetic algorithm

Genetic search of parameter space: v Start with a random population of states

v Perform random crossovers and mutations to make children

v Select children with highest scores to populate the next generation

v Repeat for a number of iterations

Part 2: Protein - Protein Docking Methods

Just to fix some ideas…

Basis of protein –protein complex formation

-  Shape of the interacFon surfaces

-‐  ElectrostaFcs charaterisFcs of surface residues -‐  FuncFonal residues

Macromolecular docking

The term macromolecular docking includes several computational techniques which have the aim of calculate models of the complexes between two or more macromolecules (protein-protein, protein-DNA, protein-RNA, etc.) Objective: prediction of the tridimensional structure of a complex between two marcomolecules. Techniques: - Rigid docking - Flexible docking

Macromolecular docking

Atomic coordinates of protein A

Atomic coordinates of protein B

DOCKING

Protein complex model structure

Macromolecular docking: methods

Macromolecular docking algorithms Are characterized by four steps: 1-‐ calcula6on of an appropriate representaFon of the macromolecules together with the defini6on of the degrees of freedom of the calcula6on; 2-‐ an algorithm able to explore the space of conforma6ons with the highest possible completeness and efficiency; 3-‐ a scoring funcFon able to evaluate the quality of the predic6ons 4-‐ a clustering algorithm

Macromolecular docking: methods

Systematic search: the two macromolecules are calculated in as many orientations as possibile. Guided search: complex formation is guided by an appropriate scoring function.

Knowledge-based search: similar to guided search, but the calculation makes use of external information (i.e. experimental data, bioinformatic predictions, etc.) to guide the calculation.

Macromolecular docking: general scheme

Protein representaFon using the

molecular surface

Different probes produce Different surfaces

Coordinates of macromolecules A and B

Representations of A and B

Exploration of conformational space

Candidate complexes

AB model complex

Refining


Case 1: sistemaFc search

The conformaFonal space is divided into segments.

This can be achieved with a grid representaFon of the space




Candidate complexes

AB model complex

Refining

Macromolecular docking: scoring function

Macromolecule A (ρ << 0)

Macromolecule B (0 > δ > 1)

SCORING FUNCTION

a=1

a<<0

b=1

0>b>1

c > 0

Macromolecular docking: scoring function

a=1

a<<0

b=1

0>b>1

c << 0





Candidate complexes

AB model complex

Refining

Case 2: guided search

The search for the minima of the scoring funcFon is made inducing a

perturbaFon on the iniFal orientaFon.

This ‘move’ is accepted or refused on the basis of the employed

algorithm.

Macromolecular docking: empirical scoring function

Van der Waals

H-‐bond

ElectrostaFcs

SolvaFon

Torsional angles

VdW H-‐bond Elec

Energy

Distance Distance Distance


Both in the exploraFon of the conformaFonal space and in the refining step it is possibile to

include some external informaFon (knowledge-‐based informaFon)




Candidate complexes

AB model complex

Refining

Macromolecular docking: Haddock

Dominguez, C.; Boelens, R.; Bonvin A.M.J.J. (2003) J. Am. Chem. Soc. 125, 1731-‐1737. de Vries, S.J. et al.(2007) Proteins: Struc. Funct. & Bioinforma;c 69, 726-‐733 (2007).

Mem

bran

e

Periplasm

Cytoplasm

Photosynthe6c reac6on center from T. tepidum (1EYS)

HP1

HP2 LP1

LP2

Nogi, T. et al. (2000) Proc. Nat. Acad. Sci. USA 97:13561.

Puta6ve HiPIP interac6on site

Macromolecular docking: examples (THC – HiPIP)

Tetra-‐heme (THC)


Venturoli, G. et al. (2004) Biochemistry 43:437-‐445 Ciurli, S.; Musiani, F. (2005) Photosynth. Res. 85:115-‐131

THC HiPIP


THC

HiPIP


THC HiPIP


THC

HiPIP


Hope, H.P. (2000) Biochim. Biophis. Acta 1456:5-‐26

Macromolecular docking: examples (Cytochrome f - plastocyanin)

S(Met)

Cu S(Cys)(His)N(His)N

PC

NN

NN

OH OOH O

SS

Fe

Cys 24

Cys 21

FeN

N

N

N

NH2

NH

N

His 25

Tyr 1

Cyt f

Musiani, F.; Dikiy, A.; Semenov, A.Y.; Ciurli, S. (2005) J. Biol. Chem. 280:18833-‐18841.

Macromolecular docking: examples (Cytochrome f - plastocyanin)

Bioinformatic predictions: multi-domain protein conformations

Del Campo, C.; Agries6, F.; Danielli, A.; Roncara6, D.; Musiani, F.; Ciurli, S. ; Scalrato, V. (2012) in prepara6on

Bioinformatic predictions: protein – DNA docking

Del Campo, C.; Agries6, F.; Danielli, A.; Roncara6, D.; Musiani, F.; Ciurli, S. ; Scalrato, V. (2012) in prepara6on

Documents

Computational Molecular Biology Protein - Ligand And ...molsim.sci.univr.it/2013_biocomp/Docking.pdf · Computational Molecular Biology Protein - Ligand And Protein - Protein Docking