PubChem (https://pubchem.ncbi.nlm.nih.gov) is a public repository for information on chemical substances and their biological activities, launched in 2004 as a component of the Molecular Libraries Roadmap Initiatives of the US National Institutes of Health (NIH). For the past 11 years, PubChem has grown to a sizable system, serving as a chemical information resource for the scientific research community. PubChem consists of three inter-linked databases, Substance, Compound and BioAssay. The Substance database contains chemical information deposited by individual data contributors to PubChem, and the Compound database stores unique chemical structures extracted from the Substance database. Biological activity data of chemical substances tested in assay experiments are contained in the BioAssay database. This paper provides an overview of the PubChem Substance and Compound databases, including data sources and contents, data organization, data submission using PubChem Upload, chemical structure standardization, web-based interfaces for textual and non-textual searches, and programmatic access. It also gives a brief description of PubChem3D, a resource derived from theoretical three-dimensional structures of compounds in PubChem, as well as PubChemRDF, Resource Description Framework (RDF)-formatted PubChem data for data sharing, analysis and integration with information contained in other databases.

NCBI's Conserved Domain Database (CDD) aims at annotating biomolecular sequences with the location of evolutionarily conserved protein domain footprints, and functional sites inferred from such footprints. An archive of pre-computed domain annotation is maintained for proteins tracked by NCBI's Entrez database, and live search services are offered as well. CDD curation staff supplements a comprehensive collection of protein domain and protein family models, which have been imported from external providers, with representations of selected domain families that are curated in-house and organized into hierarchical classifications of functionally distinct families and sub-families. CDD also supports comparative analyses of protein families via conserved domain architectures, and a recent curation effort focuses on providing functional characterizations of distinct subfamily architectures using SPARCLE: Subfamily Protein Architecture Labeling Engine. CDD can be accessed at https://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml.

The NCBI BioSystems database, found at http://www.ncbi.nlm.nih.gov/biosystems/, centralizes and cross-links existing biological systems databases, increasing their utility and target audience by integrating their pathways and systems into NCBI resources. This integration allows users of NCBI’s Entrez databases to quickly categorize proteins, genes and small molecules by metabolic pathway, disease state or other BioSystem type, without requiring time-consuming inference of biological relationships from the literature or multiple experimental datasets.

Prediction of protein function is of significance in studying biological processes. One approach for function prediction is to classify a protein into functional family. Support vector machine (SVM) is a useful method for such classification, which may involve proteins with diverse sequence distribution. We have developed a web-based software, SVMProt, for SVM classification of a protein into functional family from its primary sequence. SVMProt classification system is trained from representative proteins of a number of functional families and seed proteins of Pfam curated protein families. It currently covers 54 functional families and additional families will be added in the near future. The computed accuracy for protein family classification is found to be in the range of 69.1-99.6%. SVMProt shows a certain degree of capability for the classification of distantly related proteins and homologous proteins of different function and thus may be used as a protein function prediction tool that complements sequence alignment methods. SVMProt can be accessed at http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi.