Evolution-guided discovery and recoding of allosteric pathway specificity determinants in psychoactive bioamine receptors

Abstract

G protein-coupled receptors for dopamine and serotonin control signaling pathways targeted by many psychoactive drugs. A puzzle is how receptors with similar functions and nearly identical binding site structures, such as D2 dopamine receptors and 5-HT2A serotonin receptors, could evolve a mechanism that discriminates stringently in their cellular responses between endogenous neurotransmitters. We used the Difference Evolutionary Trace (Difference-ET) and residue-swapping to uncover two distinct sets of specificity-determining sequence positions. One at the ligand-binding pocket determines the relative affinities for these two ligands, and a distinct, surprising set of positions outside the binding site determines whether a bound ligand can trigger the conformational rearrangement leading to G protein activation. Thus one site specifies affinity while the other encodes a filter for efficacy. These findings demonstrate that allosteric pathways linking distant interactions via alternate conformational states enforce specificity independently of the ligand-binding site, such that either one may be rationally rekeyed to different ligands. The conversion of a dopamine receptor effectively into a serotonin receptor illustrates the plasticity of GPCR signaling during evolution, or in pathological states, and suggests new approaches to drug discovery, targeting both classes of sites.

A formal perturbation equation between genotype and phenotype determines the Evolutionary Action of protein-coding variations on fitness

“…Although evolutionary importance is often conflated with conservation, in the context of differential analysis, an average, such as conservation, is less accurate than ET, which directly uses phylogenetic analysis to couple variations in sequence to variations in fitness, as a derivative should, since by definition derivatives are ratios of variations. The fact that ET measures a fundamental evolutionary quantity, =f, is consistent with its accuracy and versatility to predict, selectively block, redesign, or mimic protein function by pinpointing the amino acid determinants of specificity (Yao et al 2003;Rodriguez et al 2010;Amin et al 2013). To improve substitution odds, we likewise used phylogenetic analysis by considering the evolutionary gradient of the substituted site.…”

“…A frequent and simpler measure of evolutionary importance is residue conservation (Livingstone and Barton 1993;Pei and Grishin 2001;Valdar 2002;Mihalek et al 2004), but conservation is an average rather than a derivative and is less accurate than ET in practice. In that light, prior ET studies have already shown the broad applications of evolutionary gradients: They identify functional sites and allosteric pathway residues (Yao et al 2003), guide mutations that block or reprogram function (Rodriguez et al 2010), and define structural motifs that predict function on a large scale (Ward et al 2009;Erdin et al 2010), such as substrate specificity (Amin et al 2013).…”

“…In other words, the fitness metric and the action of a mutation are assumed to be time-invariant. This is an approximation since divergent proteins can develop new functional sites, a phenomena that leads to branch-specific evolutionary gradient variations and accounted for by differential ET (Lichtarge et al 1997), for example, to identify ligand-specific sites (Madabushi et al 2004;Rodriguez et al 2010).…”

Naturally evolved G protein-coupled receptors adopt metastable conformations

“…Among these, around 90% (an average of 6 residues per GPCR) are unsatisfied (i.e., stabilized by less than 0.2 kcal∕mol in hydrogen bond energy). Evolutionary trace analysis (48) revealed that a majority of these residues have specific locations and encode distinct physical interactions in each GPCR subfamily (SI Methods and Figs. S1-S3).…”

Sequence and structure continuity of evolutionary importance improves protein functional site discovery and annotation

“…31,67 These observations are highly reliable and can efficiently guide experiments, for example, to separate functions, 8,34 rewire specificity, 29 design peptide inhibitors, 63 or reveal the conformational trigger of an allosteric pathway and recode it to respond to a different ligand. 68 Beyond these varied experimental case studies, ETA function prediction further validated the basic premise that clusters of top-ranked ET residues point to functionally essential residues, but this time on a large scale. These prior results suggest that ET ranks highlight fundamental, general and useful patterns linking the distribution of evolutionary importance in sequence residues to their structural location and to their biological roles.…”