Homology Modeling in the Twilight Zone: Improved Accuracy by Sequence Space Analysis.

The analysis of the relationship between sequence and structure similarities during the evolution of a protein family has revealed a limit of sequence divergence for which structural conservation can be confidently assumed and homology modeling is reliable. Below this limit, the twilight zone corresponds to sequence divergence for which homology modeling becomes increasingly difficult and requires specific methods. Either with conventional threading methods or with recent deep learning methods, such as AlphaFold, the challenge relies on the identification of a template that shares not only a common ancestor (homology) but also a conserved structure with the query. As both homology and structural conservation are transitive properties, mining of sequence databases followed by multidimensional scaling (MDS) of the query sequence space can reveal intermediary sequences to infer homology and structural conservation between the query and the template. Here, as a case study, we studied the plethodontid receptivity factor isoform 1 (PRF1) from Plethodon jordani, a member of a pheromone protein family present only in lungless salamanders and weakly related to cytokines of the IL6 family. A variety of conventional threading methods led to the cytokine CNTF as a template. Sequence mining, followed by phylogenetic and MDS analysis, provided missing links between PRF1 and CNTF and allowed reliable homology modeling. In addition, we compared automated models obtained from web servers to a customized model to show how modeling can be improved by expert information.

Evolutionary information helps understand distinctive features of the angiotensin II receptors AT1 and AT2 in amniota.

In vertebrates, the octopeptide angiotensin II (AngII) is an important in vivo regulator of the cardiovascular system. It acts mainly through two G protein-coupled receptors, AT1 and AT2. To better understand distinctive features of these receptors, we carried out a phylogenetic analysis that revealed a mirror evolution of AT1 and AT2, each one split into two clades, separating fish from terrestrial receptors. It also revealed that hallmark mutations occurred at, or near, the sodium binding site in both AT1 and AT2. Electrostatics computations and molecular dynamics simulations support maintained sodium binding to human AT1 with slow ingress from the extracellular side and an electrostatic component of the binding free energy around -3kT, to be compared to around -2kT for human AT2 and the δ opioid receptor. Comparison of the sodium binding modes in wild type and mutated AT1 and AT2 from humans and eels indicates that the allosteric control by sodium in both AT1 and AT2 evolved during the transition from fish to amniota. The unusual S7.46N mutation in AT1 is mirrored by a L3.36M mutation in AT2. In the presence of sodium, the N7.46 pattern in amniota AT1 stabilizes the inward orientation of N3.35 in the apo receptor, which should contribute to efficient N3.35 driven biased signaling. The M3.36 pattern in amniota AT2 favours the outward orientation of N3.35 and the receptor promiscuity. Both mutations have physiological consequences for the regulation of the renin-angiotensin system.

Homology Modeling of Class A G-Protein-Coupled Receptors in the Age of the Structure Boom.

With 700 members, G protein-coupled receptors (GPCRs) of the rhodopsin family (class A) form the largest membrane receptor family in humans and are the target of about 30% of presently available pharmaceutical drugs. The recent boom in GPCR structures led to the structural resolution of 57 unique receptors in different states (39 receptors in inactive state only, 2 receptors in active state only and 16 receptors in different activation states). In spite of these tremendous advances, most computational studies on GPCRs, including molecular dynamics simulations, virtual screening and drug design, rely on GPCR models obtained by homology modeling. In this protocol, we detail the different steps of homology modeling with the MODELLER software, from template selection to model evaluation. The present structure boom provides closely related templates for most receptors. If, in these templates, some of the loops are not resolved, in most cases, the numerous available structures enable to find loop templates with similar length for equivalent loops. However, simultaneously, the large number of putative templates leads to model ambiguities that may require additional information based on multiple sequence alignments or molecular dynamics simulations to be resolved. Using the modeling of the human bradykinin receptor B1 as a case study, we show how several templates are managed by MODELLER, and how the choice of template(s) and of template fragments can improve the quality of the models. We also give examples of how additional information and tools help the user to resolve ambiguities in GPCR modeling.

Evolution of chemokine receptors is driven by mutations in the sodium binding site.

Chemokines and their receptors (members of the GPCR super-family) are involved in a wide variety of physiological processes and diseases; thus, understanding the specificity of the chemokine receptor family could help develop new receptor specific drugs. Here, we explore the evolutionary mechanisms that led to the emergence of the chemokine receptors. Based on GPCR hierarchical classification, we analyzed nested GPCR sets with an eigen decomposition approach of the sequence covariation matrix and determined three key residues whose mutation was crucial for the emergence of the chemokine receptors and their subsequent divergence into homeostatic and inflammatory receptors. These residues are part of the allosteric sodium binding site. Their structural and functional roles were investigated by molecular dynamics simulations of CXCR4 and CCR5 as prototypes of homeostatic and inflammatory chemokine receptors, respectively. This study indicates that the three mutations crucial for the evolution of the chemokine receptors dramatically altered the sodium binding mode. In CXCR4, the sodium ion is tightly bound by four protein atoms and one water molecule. In CCR5, the sodium ion is mobile within the binding pocket and moves between different sites involving from one to three protein atoms and two to five water molecules. Analysis of chemokine receptor evolution reveals that a highly constrained sodium binding site characterized most ancient receptors, and that the constraints were subsequently loosened during the divergence of this receptor family. We discuss the implications of these findings for the evolution of the chemokine receptor functions and mechanisms of action.