Areas of Emphasis: Web infrastructure, freely available QSAR modeling and assessment

1. ECCR at North Carolina State UniversityComparative and Web-Enabled Virtual ScreeningJoint MLSCN-ECCR Meeting: April 2007 Areas of Emphasis: Web infrastructure, freely available QSAR modeling and assessment PowerMV http://eccr.stat.ncsu.edu/TSWeb/Default.aspx ChemModLab http://eccr.stat.ncsu.edu/ChemModLab/Description.aspx Screening studies from the MLSCN Prediction from stored QSAR models Scaling via distributed computing and specialized hardware Methodological development for QSAR modeling Designs for screening studies, e.g., pooling studies

2. PowerMV Menu-driven web software: • Molecular viewer • Compute descriptor sets • Similarity searching • Some analysis methods • Links to R, an open-source statistical software system • Planning links to SAS JMP • Will be a major tool for us to share new modeling methods • No need to install software on user machine • Can use PowerMV functions even if not on Windows platform

3. Compounds displayed in a grid User controls Cell size # columns Tabular information also displayed Logistical control on left PowerMV

4. ChemModLab : Cheminformatics Modeling Laboratory • Build QSAR models • Currently 80 available • Automated tuning • Already includes many MLSCN assays • Includes assays submitted by independent users • Assess QSAR models • Accumulation Curves, Diversity Maps, Enhancement Measures, etc. • Select a handful of models based on • Adjustments for multiple testing • Recognition of natural variations • Best statistical practices • Store and retrieve QSAR models • Apply stored QSAR models to new sets of compounds http://eccr.stat.ncsu.edu a research enabling platform & planning tool

5. ChemModLab Take detailed looks at which models? AID348 (NCGC): KNN – Ph ENet – CAP RF – B# RF – CAP RF – FF Tree – CAP Tree – Ph Tree – FF PLS – CAP

6. ChemModLab • Methods include: • Trees: randomForest, rpart, tree • Neural networks • k-nearest neighbors • Support vector machines • Partial least squares • Partial least squares with linear discriminant analysis • Least angle regression • Ridge regression • Elastic net • Principal components regression • Family ensemble of k-nearest neighbors, using 70% selection • Family ensemble of tree, using 70% selection • Family ensemble of rpart, using 70% selection • randomForest using 70% selection

7. ChemModLab Descriptors currently come from PowerMV: • Infrastructure: • Grid computing • Open-source statistical software, R • Scalable service • Web-based service (offers computationally intensive methods)

8. ChemModLab • MLSCN assays studied: • AID362:NMMLSC—formylpeptide receptor ligand binding (60+4219=4279) • AID364: ScrippsMLSC—cell proliferation & viability (50+3262=3311) • AID348: NCGC—glucocerebrosidase for Gaucher disease (48+4898=4946) • AID371: SRMLSC—human A549 lung tumor cell growth (278+3036=3314) • AID377: NIMH-PDS—multidrug-resistance transporter (353+239+185=777) • AID360: NCGC—glucocerebrosidase for Gaucher disease (549+45730+1840) • Other PubChem assay studied: • AID377: NIMH-PDS—multidrug-resistance transporter (353+239+185=777)

9. Methodological Development (Theory & Practice) • Ensembles • Sufficient dimension reduction • Non-negative matrix factorization (NMF) Highpoints of NMF Workshop: • Held at NISS, 23-24 Feb 2007 • 56 people (12 speakers, 36/8 actual/web attendees) • Major universities – NCSU, Wake Forest, U Texas, U Tenn • Student/Faculty/Government/Industry We now have access to world’s experts See www.niss.org/irMF