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Species included in PlantTFDB 4.0 covers the main lineages of green plants. Therefore, PlantTFDB provides genomic TF repertoires across Viridiplantae. To provide comprehensive information for the TF family, a brief introduction and key references are presented for each family. Comprehensive annotations are made for each identified TF, including functional domains, 3D structures, gene ontology (GO), plant ontology (PO), expression information, expert-curated functional description, regulation information, interaction, conserved elements, references, and annotations in various databases such as UniProt, RefSeq, TransFac, STRING, and VISTA. By inferring orthologous groups and constructing phylogenetic trees, evolutionary relationships among identified TFs were inferred. In addition, PlantTFDB has a simple and user-friendly interface to allow users to query based on combined conditions or make sequence similarity search using BLAST. The new version PlantTFDB 5.0 has been incorporated into PlantRegMap http://plantregmap.gao-lab.org/.
The Structure database provides three-dimensional structures of macromolecules for a variety of research purposes and allows the user to retrieve structures for specific molecule types as well as structures for genes and proteins of interest. Three main databases comprise Structure-The Molecular Modeling Database; Conserved Domains and Protein Classification; and the BioSystems Database. Structure also links to the PubChem databases to connect biological activity data to the macromolecular structures. Users can locate structural templates for proteins and interactively view structures and sequence data to closely examine sequence-structure relationships.
The RESID Database of Protein Modifications is a comprehensive collection of annotations and structures for protein modifications including amino-terminal, carboxyl-terminal and peptide chain cross-link post-translational modifications.
ChEMBL is a database of bioactive drug-like small molecules, it contains 2-D structures, calculated properties (e.g. logP, Molecular Weight, Lipinski Parameters, etc.) and abstracted bioactivities (e.g. binding constants, pharmacology and ADMET data). The data is abstracted and curated from the primary scientific literature, and cover a significant fraction of the SAR and discovery of modern drugs We attempt to normalise the bioactivities into a uniform set of end-points and units where possible, and also to tag the links between a molecular target and a published assay with a set of varying confidence levels. Additional data on clinical progress of compounds is being integrated into ChEMBL at the current time.