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Abstract / Description of output
Understanding multicomponent binding interactions in protein–ligand, protein–protein, and competition systems is essential for fundamental biology and drug discovery. Hand-deriving equations quickly become unfeasible when the number of components is increased, and direct analytical solutions only exist to a certain complexity. To address this problem and allow easy access to simulation, plotting, and parameter fitting to complex systems at equilibrium, we present the Python package PyBindingCurve. We apply this software to explore homodimer and heterodimer formations culminating in the discovery that under certain conditions, homodimers are easier to break with an inhibitor than heterodimers and may also be more readily depleted. This is a potentially valuable and overlooked phenomenon of great importance to drug discovery. PyBindingCurve may be expanded to operate on any equilibrium binding system and allows definition of custom systems using a simple syntax. PyBindingCurve is available under the MIT license at https://github.com/stevenshave/pybindingcurve as the Python source code accompanied by examples and as an easily installable package within the Python Package Index.
Original language | English |
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Number of pages | 5 |
Journal | Journal of Chemical Information and Modeling |
Early online date | 18 May 2021 |
DOIs | |
Publication status | E-pub ahead of print - 18 May 2021 |
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Understanding bacterial host adaptation to combat infectious diseases
Fitzgerald, R., Auer, M. & Hume, D.
1/01/17 → 31/12/21
Project: Research