Funding: Tackling Alchemical Free Energy Calculations · PDF fileCommand line tools Dummy...
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References: [1] Shirts, Michael R., and John D. Chodera. JCP (2008): 124105. [2] Eastman, Peter, et al. JCTC (2012): 461-469. [3] Löffler, Hannes, et al. J. Chem. Inf. Model., 2015, 55 (12), pp 2485–2490 Tackling Alchemical Free Energy Calculations with Sire/OpenMM-SOMD A. Mey ([email protected]), G. Calabro, C. Woods, J. Michel Funding: Relative Alchemical Free Energy Calculation Computing free energies of binding or hydration of small molecules is an important task in computer aided drug design. Using molecular dynamics simulations for computing binding free energies can be prohibitively long due to the timescale problem. However, it is possible to use an artificial alchemical transformation that allows to compute relative free energy differences making use of thermodynamic cycles. (See Fig.1) Relative Alchemical Free Energy Calculation HSP90 target from D3R Grand Challenge 2015 ΔF hyd = ΔF 1 - ΔF 2 The free energy difference of an alchemical transformation can for example be computed using thermodynamic integration or MBAR: SOMD SOMD allows to compute relative free energy differences. somd-freenrg -C sim.cfg -t SYSTEM.top -c SYSTEM.crd -m MORPH.pert -p CUDA Example usage: Simulation topology: e.g. AMBER Positions Defines the morphing between structures Configuration file: set integrator, thermostat barostat, etc. Name of the Sire app Platform Sire/OpenMM SOMD structure: Sire Molecular Library in C++: coordinates, topology, dynamics … Python wrapper exposing the C++ API Command line tools Dummy Dummy ΔF 1 ΔF 2 ΔF hydration alchemical transformation using λ alchemical transformation using λ Figure 1: Illustrative thermodynamic cycle for the relative free energy of hydration of ethane and methanol. OpenMM 2 somd, waterswap, analysis…, etc GPU support pymbar 1 Sire development strategies Support for AMBER topology files and compatibility with FESetup 3 to run free energy simulations. ΔF = Z 1 0 @ F @λ dλ = Z 1 0 < @ U (λ) @λ >dλ SOMD Stable master on github with development branch and features Continuous integration using Travis, with automated build testing of every commit. Deployment: siremol.org - Developer documentation - User documentation 9e 9c 9b 9d 9f ID IC50 [μM] 9b 2.32 9c 0.22 9d 34.9 9e 0.054 9f 2.53 • NPT simulation, with 4 fs time step at 298K using hydrogen mass repartitioning • Single topology. • 17 equally spaced λ windows. • 2 independent 8 ns production run. • MBAR analysis after drawing uncorrelated data from simulated dataset using the time series analysis module in pymbar 1 . • PDB ID: 3OWD taken from 4 . ΔG(9e,9b) bound ΔG(9e,9b) solvated MBAR MBAR From bootstrapping: MUE = 1.2 ± 0.1 [kcal/mol] R = 0.75 ± 0.03 Perturbation network (Fig. 3) is constructed over averaged simulations with relative binding free energies shown in [kcal/mol]. Relative free energies with respect to a target structure are computed based on sum over all possible possible paths between two structures in the networks. Errors are given by the standard deviation. ΔΔG A,B = k B T ln( IC50 B IC50 A ) Experimental: taken from 4 HSP90 Example Dataset Experimental Cycle example Simulation protocol 2.3 2.0 9c N H N O HO OH Cl N H N O HO OH 9f -2.9 -0.9 3.8 -1.5 -3.9 -1.7 1.7 1.1 N H N O HO CF 3 9b N H N O HO Cl OH 9e -4.5 0.4 4.7 -4.2 -0.4 4.5 N H N O HO OH 9d -0.2 0.2 0.3 0.4 Figure 3: Perturbation network of HSP90 ligands Figure 4: Comparison of experimental and computed free energy values. input files FESetup 3 SOMD MBAR Network X Goal: automated pipeline [4] Bioorg Med Chem Lett 20 (2010) 7503-7506 [5] A. Mey et al, Bioorg. Med. Chem., in press (2016) - HSP90 is a chaperone protein - Part of many oncological drug programs - Difficult drug target, due to: a) open and closed conformations b) water mediate ligand binding Figure 2: HSP90 + ligand
Transcript of Funding: Tackling Alchemical Free Energy Calculations · PDF fileCommand line tools Dummy...
References: [1] Shirts, Michael R., and John D. Chodera. JCP (2008): 124105.[2] Eastman, Peter, et al. JCTC (2012): 461-469.[3] Löffler, Hannes, et al. J. Chem. Inf. Model., 2015, 55 (12), pp 2485–2490
Tackling Alchemical Free Energy Calculations with Sire/OpenMM-SOMD
A. Mey ([email protected]), G. Calabro, C. Woods, J. Michel
Funding:
Rela
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Alc
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n
Computing free energies of binding or hydration of small molecules is an important task in computer aided drug design. Using molecular dynamics simulations for computing binding free energies can be prohibitively long due to the timescale problem. However, it is possible to use an artificial alchemical transformation that allows to compute relative free energy differences making use of thermodynamic cycles. (See Fig.1)
Rela
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�Fhyd = �F1 ��F2
The free energy difference of an alchemical transformation can for example be computed using thermodynamic integration or MBAR:
SO
MD
SOMD allows to compute relative free energy differences.
somd-freenrg -C sim.cfg -t SYSTEM.top -c SYSTEM.crd -m MORPH.pert -p CUDAExample usage:
Simulation topology: e.g. AMBER
Positions Defines the morphing between structures
Configuration file: set integrator, thermostat barostat, etc.
Name of the Sire app
Platform
Sire/OpenMM SOMD structure:
Sire Molecular Library in C++: coordinates, topology, dynamics …
Python wrapper exposing the C++ API
Command line tools
Dummy
Dummy
ΔF1
ΔF2
ΔF h
ydra
tion
alchemicaltransformation
using λ
alchemicaltransformation
using λ
Figure 1: Illustrative thermodynamic cycle for the relative free energy of hydration of ethane and methanol.
OpenMM2
somd, waterswap, analysis…, etc
GPU support
pymbar1
Sire development strategies
Support for AMBER topology files and compatibility with FESetup3 to run free energy simulations.
�F =
Z 1
0
@F
@�d� =
Z 1
0<
@U(�)
@�> d�
SO
MD
Stable master on github with development branch and features
Continuous integration using Travis, with automated build testing of every commit.
Deployment: siremol.org- Developer documentation - User documentation
9e
9c
9b
9d
9f
ID IC50 [μM]9b 2.329c 0.229d 34.99e 0.0549f 2.53
• NPT simulation, with 4 fs time step at 298K using hydrogen mass repartitioning
• Single topology. • 17 equally spaced λ windows. • 2 independent 8 ns production run. • MBAR analysis after drawing uncorrelated
data from simulated dataset using the time series analysis module in pymbar1.
• PDB ID: 3OWD taken from4.
ΔG(9e,9b)bound
ΔG(9e,9b)solvated
MBAR
MBAR
From bootstrapping: MUE = 1.2 ± 0.1 [kcal/mol] R = 0.75 ± 0.03
Perturbation network (Fig. 3) is constructed over averaged simulations with relative binding free energies shown in [kcal/mol]. Relative free energies with respect to a target structure are computed based on sum over all possible possible paths between two structures in the networks. Errors are given by the standard deviation.
��GA,B = kBT ln(IC50BIC50A
)Experimental: taken from4
HS
P9
0 E
xam
ple
Data
set
Experimental Cycle example Simulation protocol
2.3
2.0
9c
NH
NO
HOOH
Cl
NH
NO
HO
OH9f
-2.9
-0.9
3.8
-1.5
-3.9
-1.7
1.7
1.1
NH
NO
HOCF3
9b
NH
NO
HOCl
OH9e
-4.5
0.4
4.7
-4.2
-0.4
4.5
NH
NO
HOOH
9d
-0.2
0.2
0.3
0.4
Figure 3: Perturbation network of HSP90 ligandsFigure 4: Comparison of experimental and computedfree energy values.
input files FESetup3 SOMD MBAR Network XGoal: automated pipeline
[4] Bioorg Med Chem Lett 20 (2010) 7503-7506[5] A. Mey et al, Bioorg. Med. Chem., in press (2016)
-HSP90 is a chaperone protein
-Part of many oncological drug programs
-Difficult drug target, due to: a) open and closed conformations b) water mediate ligand binding
Figure 2: HSP90 + ligand
