CS597A Structural Bioinformatics

Transcription

1 Outline CS597A Thomas Funkhouser Princeton University Fall 27 Overview of structural bioinformatics Challenges Applications Overview of course Lectures Coursework Projects Bioinformatics Definition: The collection, archiving, organization, and interpretation of biological data. [Orengo, 23] Focus on data sets with molecular structure Generally speaking: Large biological data sets Computer representations and algorithms Storage, analysis, visualization, prediction, and design Small Molecules [CCDC] RNA & DNA [NDB] Proteins [PDB] Large Structures [EMD] Motivation 1: Lots of structural data is becoming available ~45, Protein Structures Motivation 2: Structural data enables detailed understanding of molecules and their interactions Total Yearly Growth of the PDB [RCSB] [pymol.sourceforge.net] 1

2 Motivation 3: Structure provides a basis for combining and visualizing information from multiple sources Bourne Analysis Visualization Geometrical and conformational analysis of Heme Ligand (7cat) [Karmirantzou and Thornton] Adenine ring from FAD bound to 1uxy [Stockwell5] Comparison Prediction Comparison of S1 binding pockets of thrombin (blue) and trypsin (red). Cyan (yellow) regions are more favorable for trypsin (thrombin) when binding NAPAP (gray). [Katzenholtz] Simulation of inhibitor Ritonavir binding to HIV protease [Protein Explorer] 2

3 Design Conceptual design of target fold Applications: Biology Medicine Chemistry Chem Eng Agriculture Material science Nanotechnology Computationally designed protein (blue) overlaid with solved x-ray structure (red) [Kuhlman3] Example: Structure-Based Drug Design Structure determination Protein Folding Simulation [David Jones] Binding site detection Binding site modeling kcal/mole/e Surface Clefts detected in 1b14 [Surfnet] Surface potential for the Carboxypeptidase A [Continuum Dynamics] 3

4 Binding site matching Binding prediction [Shulman-Peleg4] Camphor binding to Cytochrome P-45 (2cpp) [AutoDock] Molecular design Outline Overview of structural bioinformatics Challenges Applications Overview of course Lectures Coursework Projects [CCDC] CS597A Goals Survey current methods in structural bioinformatics Investigate specific research problems in depth Build shared infrastructure for research Build links across disciplines Lectures Class meetings: One topic per meeting 5% lecture 5% discussion Speakers: Professors Guests Students 4

5 ligand napthalene biphenyl pcresol odichlorobenzene toluene 135trichlorobenzene mdichlorobenzene bromobenzene flurobenzene chlorobenzene iodobenzene 135trimethylbenzene mxylene pdichlorobenzene oxylene benzene R B 1. 6 LIPO AMBIG CLAS H PLP HB META L AROMATIC Total Lectures Student presentations: Choose topic from schedule Submit list of relevant papers/resources 15-2 minute presentation Lead discussion afterwards Related talks Seminars Colloquia Tomorrow (Sep (Sep 19) 19) at at 12:3PM in in CS CS 42: 42: Barry Barry Honig, Columbia University "Relating Cellular to to Molecular Specificity PICASso Series on on Computation and and Data Data Analysis in in Biology and and Information Sciences Readings Book P.E. Bourne, H. Weissig,, Wiley-Liss, 23. Papers Read ~1 paper for each lecture Be prepared for class discussion Description Investigate research problem Any problem(s) related to course Multi-disciplinary teams (if possible) Dates Project 1: Analysis Presentation on Oct 25 Report due Nov 15 Project 2: Prediction/Design Presentation on Dec 17 Report due ~Jan 15 Possible approaches Develop new method Evaluate/compare existing methods Combine methods in system Apply method Key elements Investigation Evaluation Example project 1: Scott McAllister: Generating Likely Distance Bounds for Efficient Protein Structure Prediction Example project 2: Jermont Chen: Binding Studies of de Novo Proteins Helix i,i+3 Distances in PDB Original Distance Bound Both Bounds Rank Energy RMSD Energy RMSD Energy RMSD Chi Angles in PDB Best De Novo Protein (824) Mutation Phe (F64A) Ala Binding affinities of small molecules computed with a docking simulation (yellow binds in NMR study, red does not) 5

6 Salient Points Considered Per Class Example project 3: Julie Chen and Phil Shilane: Protein Analysis with Geometric Distribution of Properties Sample Points Shape Descriptors Coefficient Weights NonSite Site Logistic ADTree NN NN J48 Tree RBF SVM NN Base 1.. Classification Rates Example project 4: Josh Lees and Josh Podolak: Intraclass and Interclass Electric Field Variance as a Tool for Analyzing NAD+binding Sites Aligned NAD(s) EC = Positions with High ANOVA in Charge Distribution Computed Charge P ercent Neare st N eighbors Correctly Cla ssified EC Classification Rates Using Positions with Highest ANOVA Other EC Numbers Wrap Up Students to do list: Hand in survey questionaire Send me a picture of yourself by Sign up for in-class presentations Start thinking about project topics Attend Barry Honig s talk Questions? 6