Post on 06-Jan-2016
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Chemoinformatics
P. Baldi, J. Chen, and S. J. SwamidassSchool of Information and Computer Sciences
Institute for Genomics and BioinformaticsUniversity of California, Irvine
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Overall Outline
1. Introduction2. Molecular Representations 3. Chemical Data and Databases4. Molecular Similarity5. Chemical Reactions6. Machine Learning and Other Predictive
Methods7. Molecular Docking and Drug Discovery
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1. Introduction
• What is Chemoinformatics
• Resources
• Brief Historical Perspective
• Chemical Space: Small Molecules
• Overview of Problems and Methods
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What is Chemoinformatics?
• chemoinformatics encompasses the design, creation, organisation, management, retrieval, analysis, dissemination, visualization and use of chemical information
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What is Chemoinformatics?
• "the mixing of information resources to transform data into information and information into knowledge, for the intended purpose of making better decisions faster in the arena of drug lead identification and optimizaton"
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What is Chemoinformatics?
• “the set of computer algorithms and tools to store and analyse chemical data in the context of drug discovery and design projects”
• However: drug design/discovery is to chemoinformatics like DNA/RNA/ protein sequencing is to bioinformatics
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Resources
Books:
J. Gasteiger, T. E. and Engel, T. (Editors) (2003). Chemoinformatics: A Textbook. Wiley.
A.R. Leach and V. J. Gillet (2005). An Introduction to Chemoinformatics. Springer.
Journal:
Journal of Chemical Information and Modeling
Web:
http://cdb.ics.uci.edu
and many more………
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Brief Historical Perspective
• Historical perspective: physics, chemistry and biology
• Theorem:
computers/biology or computers/physics>> computers/chemistry
• Proof:
Genbank, Swissprot, PDB, Web (CERN), etc..
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Caveat: Long Tradition
• Quantum Mechanics• Docking• Beilstein• ACS• Etc…
Gasteiger, J. (2006). "Chemoinformatics: a new field with a long tradition." Anal Bioanal Chem(384): 57-64.
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Possible Causes
• Alchemy• Industrial age and early commercial
applications of chemistry• Concurrent development of modern
computers and modern biology• Scientific differences (theory/process)• Psychological perceptions (life/inert)• ACM
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Chemical Space: Small Molecules in Organic Chemistry
• Understanding chemical space• Small molecules:
– chemical synthesis– drug design – chemical genomics,– systems biology– nanotechnology– etc
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“A mathematician is a machine that converts coffee into theorems” P. Erdos
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Cholesterol
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Aspirin
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“A chemoinformatician is a machine …..…”
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Chemical Space
Stars Small Mol.
Existing 1022 107
Virtual 0 1060 (?)
Mode Real Virtual
Access Difficult “Easy”
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Chemoinformatics
• Historical perspective: physics, chemistry and biology• Understanding chemical space• Small molecules (chemical synthesis, drug design,
chemical genomics, systems biology, nanotechnology)• Predict physical, chemical, biological properties
(classification/regression)• Build filters/tools to efficiently navigate chemical space to
discover new drugs, new reactions, new “galaxies”, etc.
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Chemo/Bio Informatics
Two Key Ingredients
1. Data
2. Similarity Measures
Bioinformatics analogy and differences:– Data (GenBank, Swissprot, PDB)– Similarity (BLAST)
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Computational/Predictive Methods
• Spetrum of methods:
– Quantum Mechanics– ….– Molecular Mechanics– ….– Machine Learning
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Quantum Mechanics
Schrodinger’s Equation (time independent)
Hψ=EψH=(-h2/8π2m)∂2+V = Hamiltonian Operator
E= Energy
V =external potential (time independent)ψ= ψ(x,t) =(complex) wave function = ψ(x)T(t)
(time independent case) Ψ2 = Ψ* Ψ =probability density function (particle at
position x)
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Schrodinger Equation
• Partial differential eigenvalue equation• Where are the electrons and nuclei of a molecule in
space?• Uncer a given set of conditions, what are their energies?• Difficult to solve exactly as number of particle grows
(electron-electron interactions, etc)• Approximate methods
– Ab initio– Semi empirical
• 3D structures• Reaction mechanisms, rates
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Ab Initio
• Limited to tens of atoms and best performed using a cluster or supercomputer
• Can be applied to organics, organo-metallics, and molecular fragments (e.g. catalytic components of an enzyme)
• Vacuum or implicit solvent environment• Can be used to study ground, transition, and
excited states (certain methods)• Specific implementations include: GAMESS,
GAUSSIAN, etc.
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Semiempirical Methods• Semiempirical methods use parameters that
compensate for neglecting some of the time consuming mathematical terms in Schrodinger's equation, whereas ab initio methods include all such terms.
• The parameters used by semiempirical methods can be derived from experimental measurements or by performing ab initio calculations on model systems.Limited to hundreds of atoms
• Can be applied to organics, organo-metallics, and small oligomers (peptide, nucleotide, saccharide)
• Can be used to study ground, transition, and excited states (certain methods).
• Specific implementations include: AMPAC, MOPAC, and ZINDO.
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Molecular Mechanics
• Force field approximation
• Ignore electrons
• Calculate energy of a system as a function of nuclear positions
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Molecular Mechanics
Energy = Stretching Energy + Bending Energy + Torsion Energy + Non-Bonded Interactions Energy
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Stretching Energy
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Bending Energy
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Torsion Energy
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Non-Bonded Energy
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Statistical/Machine Learning Methods
NNs and recursive NNsGASGsGraphical ModelsKernels………Representations are essential. Must either (1) deal
with non-standard data structures of variable size; or (2) represent the data in a standard vector format.