Ddt2000 Database -

While it may not have the name recognition of UniProt or the sheer size of the PDB, its focused approach to domain-domain interactions makes it an indispensable resource for hypothesis generation and computational benchmarking. As with any scientific tool, the key is knowing when and how to use it.

Whether you are a seasoned researcher studying protein domain evolution or a graduate student just beginning to explore structural motifs, understanding the utility of the ddt2000 database can drastically accelerate your work. This article provides a comprehensive deep dive into what the ddt2000 database is, its core features, how it compares to other resources, and the practical ways it can be leveraged for cutting-edge research. At its core, the ddt2000 database is a curated collection focused on protein structures, specifically designed to analyze and classify Domain-Domain Interactions (DDIs) . The "ddt" in its name stands for "Domain Domain Table," and "2000" historically refers to the initial release year or the versioning schema that marked a significant expansion in its coverage.

Suppose your protein of interest is p53 (TP53). You know its DNA-binding domain interacts with its tetramerization domain. Enter "p53" or the specific PDB ID (e.g., 1AIE) into the search bar. ddt2000 database

In the rapidly evolving landscape of bioinformatics, researchers are constantly searching for reliable, specialized resources that bridge the gap between raw genomic data and functional protein analysis. While broad-spectrum databases like GenBank, UniProt, and the Protein Data Bank (PDB) are household names, niche repositories often hold the key to answering highly specific scientific questions. One such specialized resource that has garnered significant attention among structural biologists and protein chemists is the ddt2000 database .

Furthermore, with the rise of cryo-electron microscopy (cryo-EM), we are now solving massive macromolecular complexes (ribosomes, spliceosomes, nuclear pores). These structures contain hundreds of domain-domain interactions. The ddt2000 database is uniquely positioned to catalog these interactions, helping to untangle the complex wiring of the cellular machinery. The ddt2000 database is a powerful, specialized tool that should be in every structural bioinformatician’s arsenal. If your research involves protein engineering, domain evolution, interface design, or mutational analysis of multi-domain proteins, this database offers curated, non-redundant, and physically accurate interaction data that you simply cannot get from generic sequence databases. While it may not have the name recognition

The ddt2000 database often complements these tools. A typical strategy is: use 3did to find interaction templates, use the ddt2000 database to generate a non-redundant benchmark, and use PISA to calculate free energies. As structural biology enters the era of AI-powered prediction (e.g., AlphaFold, RoseTTAFold), the role of databases like ddt2000 is evolving. They are no longer just repositories; they are training sets . The high-quality, non-redundant interaction data in the ddt2000 database is ideal for training machine learning models to predict domain interfaces from sequence alone.

Unlike generalist databases that simply store structural coordinates, the ddt2000 database specializes in the interfaces between protein domains. A single protein often consists of multiple domains—semi-independent folding units that carry out specific functions. The way these domains interact with each other (intramolecularly) or with domains from other proteins (intermolecularly) dictates nearly all biological processes, from signal transduction to immune recognition. This article provides a comprehensive deep dive into