Download to read offline
More Related Content
Similar to ISMB2006_Intro10099999999999999999999.ppt
ISMB2006_Intro10099999999999999999999.ppt
- 1. Chemoinformatics P. Baldi, J.Chen, and S. J. Swamidass School of Information and Computer Sciences Institute for Genomics and Bioinformatics University of California, Irvine
- 2. 2 Overall Outline 1. Introduction 2.Molecular Representations 3. Chemical Data and Databases 4. Molecular Similarity 5. Chemical Reactions 6. Machine Learning and Other Predictive Methods 7. Molecular Docking and Drug Discovery
- 3. 3 1. Introduction • Whatis Chemoinformatics • Resources • Brief Historical Perspective • Chemical Space: Small Molecules • Overview of Problems and Methods
- 4. 4 What is Chemoinformatics? •chemoinformatics encompasses the design, creation, organisation, management, retrieval, analysis, dissemination, visualization and use of chemical information
- 5. 5 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"
- 6. 6 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
- 7. 7 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………
- 8. 8 Brief Historical Perspective •Historical perspective: physics, chemistry and biology • Theorem: computers/biology or computers/physics>> computers/chemistry • Proof: Genbank, Swissprot, PDB, Web (CERN), etc..
- 9. 9 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.
- 10. 10 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
- 11. 11 Chemical Space: SmallMolecules in Organic Chemistry • Understanding chemical space • Small molecules: – chemical synthesis – drug design – chemical genomics, – systems biology – nanotechnology – etc
- 12. 12 “A mathematician isa machine that converts coffee into theorems” P. Erdos
- 13.
- 14.
- 15. 15 “A chemoinformatician isa machine …..…”
- 16. 16 Chemical Space Stars Small Mol. Existing1022 107 Virtual 0 1060 (?) Mode Real Virtual Access Difficult “Easy”
- 17. 17 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.
- 18. 18 Chemo/Bio Informatics Two KeyIngredients 1. Data 2. Similarity Measures Bioinformatics analogy and differences: – Data (GenBank, Swissprot, PDB) – Similarity (BLAST)
- 19. 19 Computational/Predictive Methods • Spetrumof methods: – Quantum Mechanics – …. – Molecular Mechanics – …. – Machine Learning
- 20. 20 Quantum Mechanics Schrodinger’s Equation(time independent) Hψ=Eψ H=(-h2 /8π2 m)∂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)
- 21. 21 Schrodinger Equation • Partialdifferential 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
- 22. 22 Ab Initio • Limitedto 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.
- 23. 23 Semiempirical Methods • Semiempiricalmethods 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.
- 24. 24 Molecular Mechanics • Forcefield approximation • Ignore electrons • Calculate energy of a system as a function of nuclear positions
- 25. 25 Molecular Mechanics Energy =Stretching Energy + Bending Energy + Torsion Energy + Non-Bonded Interactions Energy
- 26.
- 27.
- 28.
- 29.
- 30. 30 Statistical/Machine Learning Methods NNs andrecursive NNs GA SGs Graphical Models Kernels ……… 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.
Editor's Notes
- #29 6-12 Lennard Jones + coulomb 10-12 Lenard Jones for Hydrogen bonding VdW forces arise from temporal aspect and concernted fluctuatio ns C_ij missing in the Coulomb term Non bonded term applies only to atoms that are at least 3 bonds away in a molecule, or between different molecules Electrons have a non even distribution in a molecular system When distribution is summarized by one number located at the nucleus==partial atomic charges or net atomic charges Non bonded energy sum of interaction between point charges Accurate with enough point charges Assigning point charges to nuclei only is not enough No consensus on how to derive the perfect set of point charges Solvent –Poisson Boltzmann aproximation There is no such thing as a chemical bond!