Using ChemAxon Toolkits in the Lead Discovery Database at GNF Genomics Institute of the Novartis Research Foundation Genomics Institute of the Novartis Research Foundation Hayk Asatryan, Dimitri Petrov, S. Frank Yan, Andrey Santrosyan, Kaisheng Chen, Shumei Jiang, Jeff Janes, Yingyao Zhou May, 2005 Budapest, Hungry

Scope of the Lead Discovery Database - LDDB Compound Management Center HTS Center Program Management Quality Control Hit Picking Hit to Lead Tracking MedChem QSAR Analytical Chemistry ADME/Tox PK/PD Data Processing Optimized Leads Genomics Institute of the Novartis Research Foundation Genomics Institute of the Novartis Research Foundation

Data Mining Oracle + DayCart Web Browser Marvin Applet Tomcat Apache CGI, Servlet Compound Registration Normalization (Novartis) Mol2smi (Daylight) Desktop Edit/Visualization Tools ChemDraw ISIS Draw Accord for Excel Architecture of LDDB JChem API Daylight Toolkits Genomics Institute of the Novartis Research Foundation Genomics Institute of the Novartis Research Foundation

Problems of the Heterogeneous Setup Molsmart solution for [H]N([H])c1ccccc1 Instead of [H]N([H])c1ccccc1 [N;!H0;!H1]c1ccccc1 Mol2Smi – aromatization & chirality Nitrogen E/Z isomerism: C\C(=N/O)c1ccccc1.C\C(=N\O)c1ccccc1 Mol2Smi – aromatization & chirality Nitrogen E/Z isomerism: C\C(=N/O)c1ccccc1.C\C(=N\O)c1ccccc1 ChemDraw & Marvin ChemDraw & Marvin MolSmart – chirality MolSmart – chirality Uncompleted Asymmetric Center (fixed in the latest Marvin), draw Input: C\C=C/C Output: [#6]C=C[#6] Genomics Institute of the Novartis Research Foundation

Daylight & ChemAxon (discuss later) Daylight & ChemAxon (discuss later) Accord: chirality, display Accord: chirality, display Pricing considerations Pricing considerations Problems of the Heterogeneous Setup (cont.) ChemDraw Accord for Excel Marvin Genomics Institute of the Novartis Research Foundation

JChem Cartridge – initial testing (July 2004) Daylight's substructure search: 5-6 seconds JCart substructure search: sec (caching the whole structure table in Oracle) Similarity search is approximately minutes (1.76million) JChem results: 10.6 minutes for 3 million structures (3 GHz Pentium 4) SmilesCount Time (ms) NC(=O)C(=NOC)c1csc(N)n OC(=O)c1cc(O)c(O)c(O)c OC1CC(C)(N)C(O)C(C)O c1ccc(OS(=O)(=O)O)cc C2OC(n1ccc(=O)[nH]c1=O)C(O)C2O Cc1ccc(N(CCCl)CCCl)cc OC1OC(C)C(O)C(OC)C1OC C1OC(CO)C(O)C(OC(N)=O)C1O NC(=O)C(N)Cc1cnc[nH] OC(=O)c1cc(OC)c(OC)c(OC)c OC1OC(CO)C(O)C(OC(N)=O)C1O c1c(C)[nH]c(=O)[nH]c1=O C(=O)NC(C=O)CCCNC(=N)N Genomics Institute of the Novartis Research Foundation

Brainstorming Initial attempts Reduce SOAP's overhead Tuning on fingerprint parameters when creating the structure table Observation SELECT statement that is used in screening: 16-17s select cd_id, cd_smiles from SCOTT.NCI_3M where BITAND(cd_fp1, ) = AND BITAND(cd_fp2, ) = AND … During screening, the CPU usage is only 30-40%, mainly I/O activity. Second attempts Fail to PIN the fingerprints column alone into memory in Oracle. Solution Preliminary studies show that the substructure search drops below 1 sec. The cache will consume only around 100MB/million, more scalable. Challenge: structure-synchronization issues. Genomics Institute of the Novartis Research Foundation

Performance Testing – Substructure Search JChem Cartridge (sec) DayCart (sec) JCart (sec) DayCart (sec) Genomics Institute of the Novartis Research Foundation

0.2 sec screening ms/hit Performance Testing – Substructure Search (cont.) Genomics Institute of the Novartis Research Foundation

New Cartridge Features – SQL Filtering Genomics Institute of the Novartis Research Foundation Use filtering can dramatically improve performance SQL Cost: 240sec select count(*) from cpd where jc_compare(jc_smiles,'c1ccccc1','sep=! t:s')=1 SQL Cost: 0.25sec select * from cpd where jc_compare(jc_smiles,'c1ccccc1','sep=! t:s! filterQuery:select c.rowid from cpd_instance i, cpd c where i.plate_sid= and i.cpd_sid=c.cpd_sid')=1 Challenge: when SQL-filtering is appropriate? SQL Cost: 25sec select * from cpd where jc_compare(jc_smiles,'CCCCCCOc1cccc(C=NOCC(O)COc2cccc(c2)C(C)C) c1','sep=! t:s!filterQuery:select c.rowid from cpd c where cpd_sid>0')=1 SQL Cost: 0.25sec select count(*) from cpd where jc_contains(jc_smiles,'CCCCCCOc1cccc(C=NOCC(O)COc2cccc(c2)C(C)C)c 1')=1

DayCart to JCart Migration Challenges Identical structures or not? Two identical structures considered by Daylight ideally remains identical by JChem, and vice versa. Identical structures or not? Two identical structures considered by Daylight ideally remains identical by JChem, and vice versa. Example 1: Aromatic Sulfur Example 1: Aromatic Sulfur COC1=NC(=NS(=N1)C2CCCCC2)ClC Oc1nc(Cl)ns(n1)C2CCCCC2 Genomics Institute of the Novartis Research Foundation Solution: Jchem support Daylight rules

Challenges – Identical Structures? (cont.) Example 2: Isotope Bug Example 2: Isotope Bug Example 3: Standardization Example 3: Standardization CC1=CC=N(C)C=C1 Cc1cc[n+](C)cc1 Genomics Institute of the Novartis Research Foundation

Challenges – Identical Structures? (cont.) Brc1ccc2[N]c3nc4ccccc4nc3-c2c1 Brc1ccc2Nc3nc4ccccc4nc3- c2c1 Example 4: Non-standard Bond Example 4: Non-standard Bond Example 4: Chirality Example 4: Chirality *c1ccc(COCC2CCC=CO2)cc1 or NULL (not supported by JCart) Incomplete Structures in Database Incomplete Structures in Database Genomics Institute of the Novartis Research Foundation

Migration Challenges - LogP 50% compounds have both values agreed within 30% Genomics Institute of the Novartis Research Foundation

Applications in LDDB Structure Display Instead of using Marvin applets for structure display, LDDB uses a structure image servlet. This strategy improves display speed, overcomes undesirable browser caching. Structure Search In-house and vendor collection, followed by hit analysis. Click on an image for Marvin applet pop-up. Genomics Institute of the Novartis Research Foundation

Ongoing Developments … Other applications R-group analysis Most-common substructure analysis Database-wise clustering analysis Thank You! Genomics Institute of the Novartis Research Foundation