What is it about?
Interactions between proteins and small organic compounds play a crucial role in regulating protein functions. These interactions can modulate various aspects of protein behavior, including enzymatic activity, signaling cascades, and structural stability. By binding to specific sites on proteins, small organic compounds can induce conformational changes, alter protein-protein interactions, or directly affect catalytic activity. Therefore, many drugs available on the market today are small molecules (72% of all approved drugs in the last 5 years). Proteins are composed of one or more domains: evolutionary units that convey function or fitness either singly or in concert with others. Understanding which domain(s) of the target protein binds to a drug can lead to additional opportunities for discovering novel targets. The evolutionary classification of protein domains (ECOD) classifies domains into an evolutionary hierarchy that focuses on distant homology. Previously, no structure-based protein domain classification existed that included information about both the interaction between small molecules or drugs and the structural domains of a target protein. This data is especially important for multidomain proteins and large complexes. Here, we present the DrugDomain database that reports the interaction between ECOD of human target proteins and DrugBank molecules and drugs. The pilot version of DrugDomain describes the interaction of 5160 DrugBank molecules associated with 2573 human proteins. It describes domains for all experimentally determined structures of these proteins and incorporates AlphaFold models when such structures are unavailable. The DrugDomain database is available online: http://prodata.swmed.edu/DrugDomain/.
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Why is it important?
Drug discovery and development are lengthy and expensive, whereas computer-aided drug discovery provides shortcuts. DrugDomain database is a valuable tool for identifying potential targets for drug repurposing based on evolutionary classification of the target proteins using AlphaFold models
Perspectives
The DrugDomain database version 1.0 represents the initial step of its development. We plan to significantly expand the range of represented molecules and include all DrugBank entities in our database. Considering the conservation rate of residue positions will enhance the accuracy of predicting amino acids that interact with small molecules. Finally, based on ECOD evolutionary classification and homologous evidence between proteins we anticipate to suggest new potential targets for known drugs. By focusing on evolutionarily conserved domains, we can prioritize targets that are likely to be functionally essential. Homologous proteins exhibit highly similar active sites, capable of accommodating similar chemical compounds. Better understanding along these lines opens up opportunities for discovering novel targets.
Dr Kirill E Medvedev
University of Texas Southwestern Medical Center
Read the Original
This page is a summary of: DrugDomain: The evolutionary context of drugs and small molecules bound to domains, Protein Science, July 2024, Wiley,
DOI: 10.1002/pro.5116.
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