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PubChem: a public chemical information resource for big data chemistry
- 1. PubChem: a Public Chemical Information Resource for Big Data Chemistry Sunghwan Kim, Ph.D., M.Sc.
- 2. Outline 1.What is PubChem? 2.What does PubChem have? 3.Navigating PubChem 4.Programmatic access to PubChem 5.Showcase: bioactivity prediction model building 6.Summary 2
- 3. 1. What is PubChem? 3
- 4. 4 https://pubchem.ncbi.nlm.nih.gov Chemical information resource at NIH. Serves scientific communities as well as the general public.
- 5. 5 ~5 million unique monthly users at peak (Apr. 2020). interactive users only No bots Similar amount of web traffic from programmatic users. One of the top 5 most visited chemistry websites in the world. (https://www.alexa.com/topsites/ category/Top/Science/Chemistry).
- 6. 6 PubChem is a data aggregator. PubChem Sources: https://pubchem.ncbi.nlm.nih.gov/sources Gov’t agencies Academic institutions Publishers Pharma companies Chemical vendors Scientific databases 750+ Data sources Public o Research communities • Chemical biology • Medicinal chemistry • Drug design & discovery • Cheminformatics o Patent agents/examiners o Chemical safety officers o Educators/Librarians o Students o ……
- 7. 2. What does PubChem have? 7
- 8. 8 PubChem contains (as August 2020): • 103-M unique chemical structures. • 268-M bioactivity outcomes • 1.2-M bioassay experiments • 91-K genes & 95-K proteins (from 4-K organisms). • 237-K pathways • 31-M scientific articles about chemicals • 3-M patent documents PubChem Statistics: https://pubchemdocs.ncbi.nlm.nih.gov/statistics Arguably, PubChem contains the largest amount of chemical information in the public domain.
- 9. Drug information • Drug labeling • Drug indications • Mechanism of action • Target genes/proteins • ADMET (Absorption, Distribution, Metabolism, Excretion & Toxicity) Clinical trials information • ClinicalTrials.gov (https://clinicaltrials.gov/) • EU Clinical Trials Register (https://www.clinicaltrialsregister.eu/) • NIPH Clinical Trials Search of Japan (https://rctportal.niph.go.jp/en/) 9 PubChem data for drug discovery
- 10. Regulatory information o FDA • Orange book • Unique ingredient identifiers, • Pharmacologic Classes o EPA • Substance Registry Services • Chemical data collected under the: • Toxic Substance Control Act • Clean Air Act 10 Patent information (USPTO, EPO, WIPO, JPO) Journal articles (PubMed & Non-PubMed) PubChem data for drug discovery
- 11. Structural information • 2-D chemical structures • Line notations for 2-Dchemical structures (SMILES, InChI, InChIKey) • Computationally-generated 3-D structures • Experimental 3-D structures (from Crystallography Open Database) • Links to 3-D structures in PDB/CSD Chemical properties (solubility, pKa, molecular weight, logP, …) Spectral information (NMR, IR, UV, MS, GC-MS, LC-MS, …) Chemical vendor Synthesis …… 11 PubChem data for drug discovery
- 12. Bioactivity data • High-throughput screening (HTS) data (NCATS, EPA, Broad Institute, Sanford-Burnham, Scripps, …) • Literature-extracted data from scientific articles and patent documents through text mining & manual curation (ChEMBL, IUPHAR/BPS Guide to PHARMACOLOGY, BindingDB, …) PubChem data for drug discovery 12
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- 32. 32 Gene/Protein Target Page Suppose that you want to: o Retrieve ALL active compounds against a given protein/gene target (e.g., HMGCR=3-hydroxy-3-methylglutaryl-CoA reductase). • To identify common chemical scaffolds responsible for bioactivity. • To build a quantitative structure-activity relationship (QSAR) model. Gene/Protein Target page • Provides a target-centric view of PubChem data. • Organizes all data available in PubChem for a given gene/protein.
- 40. 40 Patent View Page Suppose that you want to: o Retrieve ALL chemicals mentioned in a given patent document. Patent View page • Provides a list of chemicals “mentioned” in the patent application/grant. • No information on why they are mentioned. (e.g., as a subject matter or as a prior art?) • Other information, including: - Title, abstract, date, inventor, … - International patent classification (IPC) codes
- 47. 4. Programmatic Access to PubChem 47
- 48. 48 PubChem users have very diverse backgrounds/interests. PubChem’s web interfaces are optimized to perform commonly requested tasks interactively.
- 49. 49 PubChem users have very diverse backgrounds/interests. PubChem’s web interfaces are optimized to perform commonly requested tasks interactively. Everything you can do with PubChem through the web browser can be automated through PubChem’s programmatic interfaces.
- 50. 50 PubChem users have very diverse backgrounds/interests. PubChem’s web interfaces are optimized to perform commonly requested tasks interactively. Everything you can do with PubChem through the web browser can be automated through PubChem’s programmatic interfaces. Programmatic access enables one to do much more complicated tasks that cannot be done through the web browser.
- 51. 51 Multiple programmatic access routes Two major programmatic access methods o PUG-REST (primarily for computed properties). https://pubchemdocs.ncbi.nlm.nih.gov/pug-rest o PUG-View (primarily for text information). https://pubchemdocs.ncbi.nlm.nih.gov/pug-view Request volume limitation: o No more than 5 requests per second (See more at: https://pubchemdocs.ncbi.nlm.nih.gov/programmatic- access$_RequestVolumeLimitations) o Violators/abusers may be blocked for a certain period of time.
- 52. 52 Bulk Download • Structure Download Service (up to 500,000 compounds) https://pubchem.ncbi.nlm.nih.gov/pc_fetch/pc_fetch.cgi • Assay Download Service (up to 1,000 assays) https://pubchem.ncbi.nlm.nih.gov/assay/assaydownload.cgi • PubChem FTP Site ftp://ftp.ncbi.nlm.nih.gov/pubchem • PubChem RDF https://pubchemdocs.ncbi.nlm.nih.gov/rdf RDF: Resource Description Network
- 53. 5. Showcase: Bioactivity Prediction Model Building 53
- 54. Involved in regulation of gene expression in various biological processes. Potential roles in: • metabolic signaling pathways • skin alopecia (spot baldness) • dermal cysts • cardiac development • insulin sensitization • …… Retinoid X Receptor (RXRA) PDB ID: 1FBY 54
- 55. Tox21 (AID 1159531) • Quantitative HTS (qHTS) data for 10K compounds • Predominantly inactive Data sets 55
- 56. Tox21 (AID 1159531) Training (4916 compounds) Test (547 compounds) • 471 actives • 4,445 inactives • 53 actives • 494 inactives Preprocessing • Quantitative HTS (qHTS) data for 10K compounds • Predominantly inactive Data sets 90% 10% 56
- 57. Tox21 (AID 1159531) ChEMBL (45 Assays) NCGC (2 Assays) Training (4916 compounds) Test (547 compounds) External 1 (222 compounds) External 2 (489 compounds) • 471 actives • 4,445 inactives • 53 actives • 494 inactives • 205 actives • 17 inactives • 20 actives • 469 inactives Preprocessing • Quantitative HTS (qHTS) data for 10K compounds • Predominantly inactive • Data extracted from journal articles • Predominantly active • qHTS data • Predominantly inactive • Some overlap w/ Tox21 Data sets Preprocessing Preprocessing 90% 10% 57
- 58. Tox21 (AID 1159531) ChEMBL (45 Assays) NCGC (2 Assays) Training (4916 compounds) Test (547 compounds) External 1 (222 compounds) External 2 (489 compounds) • 471 actives • 4,445 inactives • 53 actives • 494 inactives • 205 actives • 17 inactives • 20 actives • 469 inactives Preprocessing • Quantitative HTS (qHTS) data for 10K compounds • Predominantly inactive • Data extracted from journal articles • Predominantly active • qHTS data • Predominantly inactive • Some overlap w/ Tox21 Data sets Preprocessing Preprocessing 90% 10% 58
- 59. Tox21 (AID 1159531) ChEMBL (45 Assays) NCGC (2 Assays) Training (4916 compounds) Test (547 compounds) External 1 (222 compounds) External 2 (489 compounds) • 471 actives • 4,445 inactives • 53 actives • 494 inactives • 205 actives • 17 inactives • 20 actives • 469 inactives Preprocessing • Quantitative HTS (qHTS) data for 10K compounds • Predominantly inactive • Data extracted from journal articles • Predominantly active • qHTS data • Predominantly inactive • Some overlap w/ Tox21 Data sets Preprocessing Preprocessing 90% 10% 471 59
- 60. Molecular descriptors • Generated using PaDEL [Yap CW (2011). J. Comput. Chem., 32 (7): 1466-1474] Model Building Abbreviation Name Length AP AtomPairs 2D Fingerprint 780 ESTAT Estate fingerprint 79 EXTFP* CDK Extended Fingerprint 1,024 FP* CDK fingerprint 1,024 GOFP* CDK graph only fingerprint 1,024 KR Klekota-Roth fingerprint 4,860 MACCS MACCS fingerprint 166 PUB PubChem fingerprint 881 SUB Substructure fingerprint 307 * Hashed fingerprints 60
- 61. Machine-learning algorithms (implemented in scikit-learn) Model Building Abbreviation Name Hyperparameters optimized NB Naïve Bayes (10-10 ~ 1) DT Decision tree max_depth_range (3 ~ 7) min_samples_split_range (3 ~ 7) min_samples_leaf_range (2 ~ 6) kNN K-Nearest neighbors weights (uniform, minkowski, jaccard) n_neighbors (1 ~ 25) RF Random forest n_estimators (10 ~ 200) SVM Support vector machine C ( 2-10 ~ 210); ( 2-10 210) NN Neural network solver (lbfgs or adam); (10-7 107) 10-fold cross-validation was used for hyperparameter optimization. 61
- 62. Model Performance Evaluation Area under the Receiver operating characteristic curve (AUC) Used for hyperparameter optimization. 𝐵𝑎𝑙𝑎𝑛𝑐𝑒𝑑 𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦 𝐵𝐴𝐶𝐶 = 1 2 𝑇𝑃 𝑇𝑃 + 𝐹𝑁 + 𝑇𝑁 𝑇𝑁 + 𝐹𝑃 = 1 2 𝑆𝐸𝑁𝑆 + 𝑆𝑃𝐸𝐶 𝑆𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦 (𝑆𝐸𝑁𝑆) = 𝑇𝑃 𝑇𝑃+𝐹𝑁 𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐𝑖𝑡𝑦 𝑆𝑃𝐸𝐶 = 𝑇𝑁 𝑇𝑁+𝐹𝑃 62
- 63. Performance of the models AUC scores of 0.7 were observed for models developed using: PubChem/MACCS/CDK-FP with NN/SVM/RF/kNN Maximum AUC score (0.77): PubChem fingerprint with RF Similar trend was observed for the performance in terms of BACC scores (not shown here). Area under ROC curve (AUC) 63
- 64. General applicability of the models Area under ROC curve (AUC), Inactive-to-active ratio = 1 NCGCChEMBL 64
- 65. Summary 65
- 66. • PubChem is the largest source of publicly available chemical information, collected from more than 750 data sources. • PubChem contains a wide range of annotated information for chemicals, including the gene/protein targets, toxicity, chemical vendors, patents, ……) • PubChem contains a large amount of high-throughput screening data as well as literature-extracted bioactivity data. 66
- 67. • PubChem supports various types of searches (e.g., keyword search, identity/similarity search, substructure/superstructure searches, ……). • PubChem supports programmatic access to its data, allowing for building an automated workflow. • PubChem’s bioactivity data can be used to develop predictive models for bioactivity of small molecules. 67
- 68. Acknowledgements Evan Bolton Jie Chen Tiejun Cheng Asta Gindulyte Jia He Siqian He Qingliang Li Benjamin Shoemaker Thiessen Paul Bo Yu Leonid Zaslavsky Jian Zhang The PubChem Team PubChem users, depositors, and collaborators Funded by the National Library of Medicine 68
- 69. 69 Thank you! Questions? Sunghwan Kim Email: sunghwan.kim@nih.gov SlideShare: https://www.slideshare.net/SunghwanKim95/presentations