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Biology subjects

Keri, D.

Publications and source records attributed to Keri, D..

2 recordsLinked to original sources

Computational rewiring of allosteric pathways reprograms GPCR selective responses to ligands

G-protein-coupled receptors (GPCRs) are the largest class of cell surface receptors and drug targets, and respond to a wide variety of chemical stimuli to activate diverse cellular functions. Understanding and predicting how ligand binding triggers a specific signaling response is critical for drug discovery and design but remains a major challenge. Here, computational design of GPCR allosteric functions is used to uncover the mechanistic relationships between agonist ligand chemistry, receptor sequence, structure, dynamics and allosteric signaling in the dopamine D2 receptor. Designed gain of function D2 variants for dopamine displayed very divergent G-protein signaling responses to other ligand agonists that strongly correlated with ligand structural similarity. Consistent with these observations, computational analysis revealed distinct topologies of allosteric signal transduction pathways for each ligand-bound D2 pair that were perturbed differently by the designs. We leveraged these findings by rewiring ligand-specific pathways and designed receptors with highly selective ligand responses. Overall, our study suggests that distinct ligand agonists can activate a given signaling effector through specific "allosteric activator" moieties that engage partially independent signal transmission networks in GPCRs. The results provide a mechanistic framework for understanding and predicting the impact of sequence polymorphism on receptor pharmacology, informing selective drug design and rationally designing receptors with highly selective ligand responses for basic and therapeutic applications.

bioengineering↗

Computationally-guided tuning of ligand sensitivity in a GPCR-based sensor

Genetically-encoded fluorescent sensors for neuromodulators are increasingly used molecular tools in neuroscience. However, these protein-based biosensors are often limited by the sensitivity of the protein scaffold towards endogenous ligands. Here, we explored the possibility of applying computational design approaches for enhancing sensor sensitivity. Using the dopamine sensor dLight1 as proof of concept, we designed two variants that boost the sensors potency (EC50) for dopamine and norepinephrine by up to 5- and 15-fold, respectively. Interestingly, the largest effects were obtained through improved designed allosteric transmission in the transmembrane region of the sensor. Our approach should prove generally useful for enhancing sensing capabilities of a large variety of neuromodulator sensors.

bioengineering↗