GPCR Allosteric Site Mapping from Deep Mutational Scanning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The complexity of G-protein coupled receptor (GPCR) activation and signaling makes effective targeting challenging, and the lack of knowledge about allosteric networks hampers the development of new or improved drugs that modulate GPCR activity.
Innovation Solution
Identification of allosteric sites on the β2-adrenergic receptor (β2AR) through a multidimensional deep mutational scanning approach, which involves obtaining training data sets, fitting models to correlate surface expression and functional measures, and identifying target sites based on residuals and statistical analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If orthosteric site targeting is used, then drug-GPCR interaction is achieved, but specificity is limited
Solution Approach 1:
The patent introduces allosteric modulators as intermediary molecules that bind to distinct allosteric sites on the GPCR rather than the orthosteric site. These modulators indirectly influence receptor activation by stabilizing specific conformations, providing a mediating mechanism that enhances drug specificity while maintaining reliable GPCR interaction
Solution Approach 2:
The patent identifies and targets specific local regions (allosteric sites) on the GPCR structure that are distinct from the orthosteric binding site. By focusing drug design on these localized regions with unique conformational properties, the approach achieves improved specificity through localized molecular interactions rather than generic orthosteric binding
2Loss of information
If comprehensive GPCR conformational sampling is studied, then understanding of signaling pathways is improved, but complexity of analysis increases
Solution Approach 1:
The patent segments the complex GPCR conformational landscape into discrete, identifiable conformational states and associated allosteric networks. By dividing the continuous conformational sampling into distinct segments or clusters, the analysis becomes more manageable while preserving comprehensive understanding of signaling pathway diversity
Solution Approach 2:
The patent employs computational methods that incorporate feedback loops, where predicted conformational states and allosteric networks are tested against experimental data, and results feed back into refined predictions. This iterative feedback process manages analytical complexity by systematically converging on accurate models of GPCR signaling
Data Source
Figure 1a
Figure 1b
Figure 2a~2e
AI summary
A method for identifying one or more target sites of a G-protein coupled receptor (GPCR) comprises: obtaining a training data set specifying, for each of a plurality of variants of the GPCR having different combinations of one or more mutations, a surface expression measure and a functional measure for that variant. The functional measure quantifies an extent to which the variant is functional for a given purpose. A model is fitted to the training data set, to obtain a set of model parameters indicative of a correlation between the surface expression measure and the functional measure for the variants of the GPCR. The one or more target sites of the GPCR are identified based on the set of model parameters.