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SynPharm: A Guide to PHARMACOLOGY Database Tool for Designing Drug Control into Engineered Proteins
Author(s) -
Sam M Ireland,
Christopher Southan,
Alazne Domínguez-Monedero,
Simon D Harding,
Joanna L Sharman,
Jamie A. Davies
Publication year - 2018
Publication title -
acs omega
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.779
H-Index - 40
ISSN - 2470-1343
DOI - 10.1021/acsomega.8b00659
Subject(s) - computational biology , tetr , synthetic biology , small molecule , repressor , drug discovery , protein data bank (rcsb pdb) , biology , database , transcription factor , genetics , computer science , bioinformatics , biochemistry , gene
A major challenge in synthetic biology, particularly for mammalian systems, is the inclusion of adequate external control for the synthetic system activities. Control at the transcriptional level can be achieved by adaptation of bacterial repressor-operator systems (e.g., TetR), but altering the activity of a protein by controlling transcription is indirect and for longer half-life mRNAs, decreasing activity this way can be inconveniently slow. Where possible, direct modulation of protein activity by soluble ligands has many advantages, including rapid action. Decades of drug discovery and pharmacological research have uncovered detailed information on the interactions between large numbers of small molecules and their primary protein targets (as well as off-target secondary interactions), many of which have been well studied in mammals, including humans. In principle, this accumulated knowledge would be a powerful resource for synthetic biology. Here, we present SynPharm, a tool that draws together information from the pharmacological database GtoPdb and the structural database, PDB, to help synthetic biologists identify ligand-binding domains of natural proteins. Consequently, as sequence cassettes, these may be suitable for building into engineered proteins to confer small-molecule modulation on them. The tool has ancillary utilities which include assessing contact changes among different ligands in the same protein, predicting possible effects of genetic variants on binding residues, and insights into ligand cross-reactivity among species.

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