PyBindingCurve, simulation, and curve fitting to complex binding systems at equilibrium

Steven Shave, Yan-Kai Chen, Nhan T. Pham, Manfred Auer

Research output: Contribution to journalArticlepeer-review

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 as the Python source code accompanied by examples and as an easily installable package within the Python Package Index.
Original languageEnglish
Number of pages5
JournalJournal of Chemical Information and Modeling
Early online date18 May 2021
Publication statusE-pub ahead of print - 18 May 2021


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