computers in chemistry dr john mitchell university of st andrews
TRANSCRIPT
Computers in Chemistry
Dr John MitchellUniversity of St Andrews
1. Why?
• Working with experiment to test our theories.
• Computer uses theory to calculate an answer that can be compared with experiment.
• If prediction and experiment don’t agree, something has to give.
Atoms in molecules are not spherical
To Test Our Theories
• The theory that lies beneath chemistry is ultimately quantum physics.
• To turn this into a prediction of the rate of a chemical reaction or the frequency of a transition in an IR spectrum requires a lot of computation.
To Test Our Theories
• Computation’s ability to make accurate predictions of experimental measurements is a good test of the validity of a theory.
• We only understand if we can predict.
Crystal Structure Prediction
• Given the structural diagram of an organic molecule, predict the 3D crystal structure.
S NBr
OO
Slide after SL Price, Int. Sch. Crystallography, Erice, 2004
To Access Data that Experiment can’t
• Computational chemistry also provides a way of obtaining information that would be very difficult, expensive or time-consuming to get experimentally.
• Behaviour at very high temperature or pressure.
• Details of structure of liquids at atomic scale.• Dynamics of proteins.
Phase Changes of Iron in the Earth’s Core
et al.,
Structure of Liquid Water and Water Clusters
Computer simulations are an important source of evidence, since atomic scale details of an irregular structure are hard to obtain by experiment.
Dynamic Motions of Proteins
X-ray crystallography gives a single static structure
Dynamic Motions of Proteins
Simulation can show how the protein flexes
2. The Power to Compute
Development of Computer Power
University of Manchester SSEM, 1948
Development of Computer Power
IBM Roadrunner, 2008
Computer Power: Moore’s Law
Computer power doubles every two years: exponential growth
Computer Power: Moore’s Law
Logarithmic scale
Computer Power: Moore’s Law
This growth will, eventually, slow down as components reach atomic scale … we think!
The Size of the Problem
Scaling• Nonetheless, theoretical chemistry is expensive• Often cost scales as the fourth power of molecule size
0 10 20 30 40 50 600
100000
200000
300000
400000
500000
600000
700000Scaling of the Expense of a Typical Quantum Chemical Calculation
Atoms in Molecule
Time (seconds)
Typical scaling is ~N4. For the foreseeable future, there will be chemical problems at the limit of our computing power.
3. Philosophies of Computational Chemistry
The Two Faces of Computational Chemistry
TheoreticalChemistryInformatics
“The problem is difficult, but by making suitable approximations we can solve it at reasonable cost based on our understanding of physics and chemistry.”
Philosophy of Theoretical Chemistry
Theoretical Chemistry
• Calculations and simulations based on real physics.
• Calculations are either quantum mechanical or use numbers derived from quantum mechanics.
• Attempt to model or simulate reality. • Usually Low Throughput.
What Kinds of Theoretical Chemistry can be Done?
Prof. Eitan Geva
(1) Quantum Chemistry
What Kinds of Theoretical Chemistry can be Done?
(1) Quantum Chemistry
Using quantum mechanics to solve the structures and energetics of molecules; everything depends on the distribution of electrons.
What Kinds of Theoretical Chemistry can be Done?
(1) Quantum Chemistry
Although quantum chemistry involves solving Schrödinger’s equation, it is not fully exact. There are some approximations involved.
What Kinds of Theoretical Chemistry can be Done?
(1) Quantum Chemistry
Wavefunction Distribution of electrons within the molecule
What Kinds of Theoretical Chemistry can be Done?
(1) Quantum Chemistry
Distribution of electrons Physical and chemical behaviour of the molecule
What Kinds of Theoretical Chemistry can be Done?
(1) Quantum Chemistry
There are two main kinds of quantum chemistry: • Ab initio• Density Functional Theory
What Kinds of Theoretical Chemistry can be Done?
(1) Quantum Chemistry
Ab initio “from first principles”.
• Solve Schrödinger equation to get wavefunction.• In principle rigorous – we know what we calculate.• But the standard “Hartree-Fock” method contains
significant approximations.• Expensive to adjust for these and get more accuracy.
What Kinds of Theoretical Chemistry can be Done?
(1) Quantum Chemistry
Density Functional Theory
• Makes use of the theorem that all properties of interest can be determined directly from the electron density.
• True in principle, but the correct “functional” is unknown.• Less rigorous than ab initio, but usually more accurate for
an equivalent cost (or cheaper for similar accuracy).
What Kinds of Theoretical Chemistry can be Done?
(2) Molecular Simulation
What Kinds of Theoretical Chemistry can be Done?
(2) Molecular Simulation
There are various techniques for simulating molecules, the most significant is probably Molecular Dynamics.
Molecular Dynamics makes a “balls-and-springs” model of the molecule in the computer, and follows its behaviour over time.
What Kinds of Theoretical Chemistry can be Done?
(2) Molecular Simulation
Light-harvesting protein subunit.
What Kinds of Theoretical Chemistry can be Done?
(2) Molecular Simulation
Time steps need to be very, very short (~10-15 seconds), so it takes a million steps to simulate one nanosecond of real time and a billion steps to simulate a microsecond.
So it is hard to directly simulate relatively slow or rare events, such as protein folding.
What Kinds of Theoretical Chemistry can be Done?
(2) Molecular Simulation
Also, a balls-and-springs model lacks the quantum mechanics needed to simulate a chemical reaction.
Nonetheless, molecular dynamics is very important for understanding shape changes, interactions and energetics of large molecules.
The Two Faces of Computational Chemistry
TheoreticalChemistryInformatics
Philosophy of Informatics“The problem is too difficult to solve at reasonable cost based on real physics and chemistry, so instead we will build a purely empirical model to predict the required molecular properties from chemical structure, using the available data.”
Informatics
• In general, informatics methods represent phenomena mathematically, but not in a physics-based way.
• Inputs and output model are based on an empirically parameterised equation or more elaborate mathematical model.
• Do not attempt to simulate reality. • Usually High Throughput.
What is Cheminformatics?
Calculating or predicting molecular properties without using a physics-based approach. Rather than modelling how the molecular world really works, cheminformatics is an empirical discipline, using available data to find correlations between chemical structure and properties.
Cheminformatics techniques are often used in drug discovery and pharmaceutical research, and the requirements of the pharmaceutical industry have dominated the development of the subject.
Modelling in Chemistry
Density Functional Theoryab initio
Molecular Dynamics
Monte Carlo
Docking
PHYSICS-BASED
EMPIRICAL
AT
OM
IST
IC
Car-Parrinello
NO
N-A
TO
MIS
TIC
DPD
CoMFA
2-D QSAR/QSPR
Machine Learning
AM1, PM3 etc.Fluid Dynamics
LOW THROUGHPUT
HIGH THROUGHPUT
4. How Best to Compute Solubility?
Which would you Prefer ...
or ?
Solubility in water (and other biological fluids) is highly desirable for pharmaceuticals!
Solubility is an important issue in drug discovery and a major cause of failure of drug development projects
This is expensive for the industry
A good computational model for predicting the solubility of druglike molecules would be very valuable.
Drug Disc.Today, 10 (4), 289 (2005)
Our Methods …
(A) Thermodynamic Cycle (Theoretical chemistry)
We want to construct a theoretical model that will predict solubility for druglike molecules …
We expect our model to use real physics and chemistry and to give some insight …
We don’t expect it to be fast by informatics standards, but it should be reasonably accurate …
Our Thermodynamic Cycle method …
Can we use theoretical chemistry to calculate solubility via a thermodynamic cycle?
Gsub comes from lattice energy minimisation based on the experimental crystal structure.
Calculate Energy of Infinite Periodic Lattice
Unit cell
Calculate Energy of Infinite Periodic Lattice
• Take one molecule• Solve its Schrödinger equation• Calculate its interactions• Allow unit cell to change• Find best size, shape, packing• Find energy of infinite lattice
This is the same methodology as used in crystal structure prediction.
Gsub comes from lattice energy minimisation based on the experimental crystal structure.
Gsolv comes from a computational solvation model, RISM
Model of Solvent-Solute Interaction
Calculate energy of interaction between solute and solvent
Model is called RISM
Gsolv comes from model of solvent-solute interaction
Theoretical Chemistry: Solubility Results
Theoretical Chemistry: Solubility Results
These results are OK, but we would hope to do better
Our Methods …
(B) Random Forest (informatics)
We want to construct a model that will predict solubility for druglike molecules …
We don’t expect our model either to use real physics and chemistry or to be easily interpretable …
We do expect it to be fast and reasonably accurate …
Our Random Forest Model …
Random ForestThis is a decision tree.
We use lots of them to make a forest!
A Machine Learning Method
Random ForestThis is a decision tree.
Random ForestGenerate more trees randomly.(1) By randomly sampling with replacement to make different “bootstrap
samples” of the data for each tree.
Random ForestGenerate more trees randomly.(2) By randomly choosing the pool of questions to ask of the data for each
node (junction) of each tree.
Random Forest● Machine Learning method introduced by Briemann and Cutler (2001)● Development of Decision Trees (Recursive Partitioning):
● Dataset is partitioned into consecutively smaller subsets
● Each partition is based upon the value of one descriptor
● The descriptor used at each split is selected so as to optimise splitting
● Bootstrap sample of N objects chosen from the N available objects with replacement
Random ForestGenerate more trees randomly.
Random ForestGenerate more trees randomly.
Random ForestGenerate more trees randomly.
Random ForestGenerate more trees randomly.
We use lots of them to make a forest!
Random Forest for Solubility Prediction
A Forest of Regression Trees
Each leaf contains a group of molecules with similar solubility.
Random Forest
• The molecules whose solubility is to be predicted are run through every tree (~ flow chart) in the forest.
• Each tree predicts a solubility for each molecule.
• We average the predictions over hundreds of different trees.
Random Forest
Random Forest: Solubility Results
RMSE(te)=0.69r2(te)=0.89Bias(te)=-0.04
RMSE(tr)=0.27r2(tr)=0.98Bias(tr)=0.005
RMSE(oob)=0.68r2(oob)=0.90Bias(oob)=0.01
DS Palmer et al., J. Chem. Inf. Model., 47, 150-158 (2007)
RMSE(te)=0.69r2(te)=0.89Bias(te)=-0.04
RMSE(tr)=0.27r2(tr)=0.98Bias(tr)=0.005
RMSE(oob)=0.68r2(oob)=0.90Bias(oob)=0.01
DS Palmer et al., J. Chem. Inf. Model., 47, 150-158 (2007)
These results are competitive with the best solubility prediction methods
What Have we Learned?
• For this particular problem, informatics does a bit better than pure theoretical chemistry.
How to Utilise Informatics
• Fast informatics models can be integrated into drug discovery to compute solubilities for molecules before deciding whether to synthesise them.
• Saving much time and money on making useless compounds.
Fits into drug discovery pipeline here
Why Pursue Theory?
• Theory promises to give a greater understanding of why some molecules are more soluble than others.
• Advances in theory can be transferable to other contexts.
• Theoretical models can be systematically improved.
