FLIPDock: A Flexible Receptor Docking ProgramYong Zhaoand Michel Sanner, Dept. of Molecular Biology, The Scripps Research Institute, La Jolla, CA 92037

Induced Fit: conformation change upon binding with a ligand. �local rearrangement of side chains and small loops�large scale backbone movement.

FLIPDock (Flexible LIgand – Protein Dock) is a protein-ligand docking program. It predicts the binding mode between a flexible ligand an a flexible receptor. FLIPDock differs from the most current docking programs in that the conformational changes in the receptor is searched during the docking process . No pre- or post-docking procedure is required.

Introduction and Background

Methods

Current approaches of handling "induced - fit" in docking study:

3 Case Studies

* Cavasotto CN, Abagyan RA. J Mol Biol 2004;337(1):209-225.* Wong CF, Kua J, Zhang Y, Straatsma TP, McCammon JA. Proteins, 61, 850-858 (2005)

Problem to solve:balanol cannot dock to the rigid adenosine-bound conformation, due to the

bad contact with GLY rich flap (GLY50-VAL57) *

adenosine bound conformation

balanol bound conformation

Case 1:Protein Kinase A

Case 2: HIV protease Cross docking

Case 3: β3: β3: β3: β-secretase (BACE)

apo conformationholo conformation

1fkn 1m4h 1tqf 1w51 1xn2 1xs7 1ym2 1ym4 2b8l 2b8v 2fdp1sgz 2.08 1.44 3.53 3.07 2.43 1.94 0.77 1.48 1.18 0.60 1.181w50 2.16 1.55 3.66 1.57 2.69 3.11 1.43 1.75 1.39 0.77 1.53

<2.0 Å 2.0 - 4.0 Å >4.0 Å

dark blocks : where AutoDock was unable to cross dock

Not all cross docking can succeed when using rigid receptor representation. � The induced conformational changes depend on the li gand.

� In 1HVI, 1HVJ, 1HVK, 1HVL and 1HVS:

–Larger ligands clash with ARG8 in most receptor conformationsOsterberg et al. Proteins: Structure, Function, and Genetics, 46, 1, 34-40.

�component based design

�searching schemes (genetic algorithm)

�scoring functions (AutoDock3)

�receptor flexibility part of search

�two FTs to represent a ligand-protein complexes

variable searching & scoring function

Acknowledgment � Dr. William Lindstrom, Dr. Ruth Huey and Prof. Art. Olson Molecular Graphics Lab. @ Scripps � NIH Grant BISTI,R21/R33GM65609

Recursively partition the molecules into fragments and describe their motionsAdvantage: represent a conformational subspace with limited number of variables .

Flexibility Tree data structureWe use two flexibility tree data structures to represent a docking complex. FLIPDock searches the motion variables to optimize the given scoring function.

FLIPDock program

Highlight

� Pros: Can still make use of the rigid receptor based docking software

� Cons:

� False positives when using soft potentials

� Highly depends on the the sampling of receptor conformation

� Expensive if depending on two step simulation

Protein – ligand docking study: computational techni que for predicting whether and how a small molecule binds t o an enzyme /receptor. It has been widely used in structure base d drug design.

�Using multiple protein structures

� NMR, X-ray crystal

� Molecular Dynamics

�Combining various conformations into an average structure

�weighted average

� The representation of a receptor

� atomic representations, grid maps, volumetric representations, etc.

� The search algorithm

� genetic algorithms, coarse-grained molecular dynamics, etc.

� The scoring function.

� empirical, knowledge based, force field based.

Pros and Cons of current approaches

� Hierarchical, tree-like data structure

� Combines a variety of types of motions:

�Domain motions: hinge, screw, translation, etc.

�Backbone flexibility: normal modes, essential dynamics, etc.

�Sidechains flexibility: rotamer library, freely rotatable bonds, etc.

� Every set of motion variables corresponds a random conformation.

� Nested multi-resolution motion.

other A

HIV protease dimer

interpolationopen-close

normal modes

ARG8 ASP29 ILE84 other B ARG8 ASP29 ILE84

chain B

core B flap B

interpolationopen-close

chain A

core A flap A

R R R R R R

R Rotamer Library=

normal mode param interpolation param (2) rotamer index (6)

www.scripps.edu/~sanner/FLIPDock/

Our approach:Here we allow the GLY-rich flap to move following a hinge.Several sidechains near the active site are allowed to choose alternative conformations.

Result:The balanol docked into PKAwith RMSD=1.40 Å14 variables: 4 (receptor) + 3 (ligand torsion) + 7 (ligand position and orientation)

Problem to solve:

Crystal structures of 20 HIV protease-inhibitors complexes are available. Can these 20 dock into the other 19 alternative receptor conformations (cross docking) ?

� 8 flexible sidechains in receptor (rotamers)

� 20 ligands are flexible:

–same rotatable bonds as in Osterberg

–6Å × 6Å × 6Å docking box

� scoring function:

–AutoDock 3.05 force field

� search engine:

–genetic algorithm (GA)

Result: 93.5% vs 72%, ligand RMSD < 2Å

Result:

1) Identify flexible sidechains near the active site.

�Compute geometric constraints using Dist (from CONCOORD suite)

�Identifies ARG8, ASP29, ASP30 and VAL82 from both chains as top ranking residues

Our approach:

Our approach:� apply a hinge to the VAL67-GLY78 flap.� flexible sidechains on TYR71, THR72, GLN73

Problem to solve:Can we dock BACE inhibitors to apo receptor conformation?

The challenge: Search the receptor's conformation DURING the docking

� Too many degrees of freedom

� computational intractable

�"Soft" potentials

�reduce van der waals radii

�temporarily mutation of the active residues with ALA

�Two-stage simulation

�docking ligand into rigid protein

�followed by optimization

< 2 Å 2Å ~ 4 Å > 4 Å

1H

BV

1H

EF

1H

EG

1H

IH

1H

IV

1H

PS

1H

TE

1H

TF

1H

TG

1H

VI

1H

VJ

1H

VK

1H

VL

1H

VS

1S

BG

4H

VP

4P

HV

5H

VP

8H

VP

9H

VP

1HBV 1.1 1.0 0.6 0.8 1.4 0.6 0.6 6.8 0.8 0.9 1.3 0.9 0.9 0.8 0.8 1.9 1.01.1 1.5 0.51HEF 1.7 0.9 1.5 0.9 0.6 0.9 0.8 0.7 0.5 0.8 0.9 1.1 0.8 0.5 0.6 1.5 1.21.0 1.6 0.81HEG 1.2 0.8 0.8 1.1 0.5 1.0 0.6 0.5 0.9 1.3 1.2 0.9 1.2 0.8 0.8 3.0 0.61.0 1.6 0.41HIH 0.9 0.7 1.9 1.0 1.3 1.0 0.6 0.6 0.5 0.9 0.9 0.9 1.0 0.5 0.8 3.8 0.81.1 2.1 1.01HIV 1.5 2.0 1.2 1.2 0.6 0.9 1.2 0.9 0.7 1.3 1.0 0.8 1.3 0.8 1.2 3.3 0.51.1 2.0 1.31HPS 1.6 1.3 2.2 1.1 0.7 0.4 0.5 0.6 0.4 1.1 1.3 1.2 1.1 0.8 0.7 1.3 0.90.8 1.5 0.81HTE 2.5 1.9 1.1 1.2 1.4 0.7 0.5 1.2 0.4 0.9 1.2 0.9 0.9 0.9 1.2 3.3 1.21.1 2.0 0.91HTF 1.4 1.3 0.6 1.1 1.4 1.0 0.2 1.0 0.7 1.2 1.3 1.1 0.9 0.7 0.4 1.6 1.01.2 1.5 0.61HTG 1.4 0.8 0.9 0.5 0.7 0.5 0.6 1.1 0.5 0.8 1.1 0.9 1.1 0.8 0.8 1.6 0.41.0 1.3 0.61HVI 1.7 1.1 1.0 1.2 1.4 0.4 0.6 0.5 1.0 0.8 0.8 1.1 1.0 0.7 1.0 2.3 1.11.1 1.7 1.21HVJ 2.1 1.2 0.7 1.2 1.3 1.2 0.8 2.1 1.0 1.1 1.1 1.1 0.9 0.4 1.3 2.6 1.11.2 1.7 1.11HVK 2.5 1.3 1.5 0.9 0.3 0.4 0.6 0.6 0.5 0.7 1.0 0.9 0.7 0.6 1.1 3.2 0.61.2 2.0 1.31HVL 2.1 1.6 1.4 1.1 1.3 1.3 0.6 3.0 0.6 1.3 1.0 0.5 0.9 0.8 1.2 1.7 1.01.2 2.4 1.41HVS 1.6 1.1 1.6 1.2 1.3 1.3 0.5 1.0 0.7 0.8 1.2 0.7 0.8 0.8 1.2 1.7 1.01.3 1.8 0.81SBG 1.1 1.1 0.9 0.7 0.9 0.4 0.5 1.1 0.4 0.9 0.8 1.0 1.1 1.0 0.6 1.6 0.91.2 1.5 0.64HVP 1.6 1.2 1.4 1.0 0.8 0.7 0.8 1.8 2.5 0.8 1.2 0.7 1.1 0.8 1.3 3.6 0.70.8 1.6 0.94PHV 0.9 1.0 1.4 0.9 0.5 0.8 0.5 0.4 0.4 1.3 1.0 1.0 1.1 1.2 0.3 2.8 1.10.7 1.4 0.85HVP 2.2 0.9 1.5 1.2 0.9 0.8 0.7 6.1 0.3 1.2 1.4 0.8 0.9 0.9 0.8 1.6 0.80.8 1.9 0.88HVP 2.1 1.2 0.8 0.7 0.5 0.9 0.6 4.9 0.9 1.1 0.9 1.2 1.1 1.1 1.3 1.9 1.11.2 1.7 1.39HVP 0.9 1.7 1.0 1.2 1.4 0.8 0.4 0.9 0.6 1.2 1.1 1.1 1.0 0.8 0.7 1.3 0.80.7 1.5 0.8

Ligands

Rec

epto

rs

2) FLIPDock searches 19 - 33 variables.

flexiblecoreflexibleligandcore-ligand

core rigidreceptor flexibleligand

E E E

IE IEIE score

−− +++

++=

Bioinformatics 2006 22(22):2768-2774

Manuscript accepted by Proteins. 2007

yongzhao@scripps.edu