Thermodynamic architecture and conformational plasticity of GPCRs

Engineering the native ensemble to tune protein function: Diverse mutational strategies and interlinked molecular mechanisms

Natural proteins are fragile entities, intrinsically sensitive to perturbations both at the level of sequence and their immediate environment. Here, we highlight the diverse strategies available for engineering function through mutations influencing backbone conformational entropy, charge-charge interactions, and in the loops and hinge regions, many of which are located far from the active site. It thus appears that there are potentially numerous ways to microscopically vary the identity of residues and the constituent interactions to tune function. Functional modulation could occur via changes in native-state stability, altered thermodynamic coupling extents within the folded structure, redistributed dynamics, or through modulation of the population of conformational substates. As these mechanisms are intrinsically linked and given the pervasive long-range effects of mutations, it is crucial to consider the interaction network as a whole and fully map the native conformational landscape to place mutational effects in the context of allostery and protein evolution.

Molecular Determinant Underlying Selective Coupling of Primary G-Protein by Class A GPCRs

G-protein-coupled receptors (GPCRs) transmit downstream signals predominantly via G-protein pathways. However, the conformational basis of selective coupling of primary G-protein remains elusive. Histamine receptors H2R and H3R couple with Gs- or Gi-proteins respectively. Here, three cryo-EM structures of H2R-Gs and H3R-Gi complexes are presented at a global resolution of 2.6-2.7 Å. These structures reveal the unique binding pose for endogenous histamine in H3R, wherein the amino group interacts with E2065.46 of H3R instead of the conserved D1143.32 of other aminergic receptors. Furthermore, comparative analysis of the H2R-Gs and H3R-Gi complexes reveals that the structural geometry of TM5/TM6 determines the primary G-protein selectivity in histamine receptors. Machine learning (ML)-based structuromic profiling and functional analysis of class A GPCR-G-protein complexes illustrate that TM5 length, TM5 tilt, and TM6 outward movement are key determinants of the Gs and Gi/o selectivity among the whole Class A family. Collectively, the findings uncover the common structural geometry within class A GPCRs that determines the primary Gs- and Gi/o-coupling selectivity.

A finely balanced order-disorder equilibrium sculpts the folding-binding landscape of an antibiotic sequestering protein

TipA, a MerR family transcription factor from Streptomyces lividans, promotes antibiotic resistance by sequestering broad-spectrum thiopeptide-based antibiotics, thus counteracting their inhibitory effect on ribosomes. TipAS, a minimal binding motif which is expressed as an isoform of TipA, harbors a partially disordered N-terminal subdomain that folds upon binding multiple antibiotics. The extent and nature of the underlying molecular heterogeneity in TipAS that shapes its promiscuous folding-function landscape is an open question and is critical for understanding antibiotic-sequestration mechanisms. Here, combining equilibrium and time-resolved experiments, statistical modeling, and simulations, we show that the TipAS native ensemble exhibits a pre-equilibrium between binding-incompetent and binding-competent substates, with the fully folded state appearing only as an excited state under physiological conditions. The binding-competent state characterized by a partially structured N-terminal subdomain loses structure progressively in the physiological range of temperatures, swells on temperature increase, and displays slow conformational exchange across multiple conformations. Binding to the bactericidal antibiotic thiostrepton follows a combination of induced-fit and conformational-selection-like mechanisms, via partial binding and concomitant stabilization of the binding-competent substate. These ensemble features are evolutionarily conserved across orthologs from select bacteria that infect humans, underscoring the functional role of partial disorder in the native ensemble of antibiotic-sequestering proteins belonging to the MerR family.

Molecular and thermodynamic determinants of self-assembly and hetero-oligomerization in the enterobacterial thermo-osmo-regulatory protein H-NS

Environmentally regulated gene expression is critical for bacterial survival under stress conditions, including extremes in temperature, osmolarity and nutrient availability. Here, we dissect the thermo- and osmo-responsory behavior of the transcriptional repressor H-NS, an archetypal nucleoid-condensing sensory protein, ubiquitous in enterobacteria that infect the mammalian gut. Through experiments and thermodynamic modeling, we show that H-NS exhibits osmolarity, temperature and concentration dependent self-association, with a highly polydisperse native ensemble dominated by monomers, dimers, tetramers and octamers. The relative population of these oligomeric states is determined by an interplay between dimerization and higher-order oligomerization, which in turn drives a competition between weak homo- versus hetero-oligomerization of protein-protein and protein-DNA complexes. A phosphomimetic mutation, Y61E, fully eliminates higher-order self-assembly and preserves only dimerization while weakening DNA binding, highlighting that oligomerization is a prerequisite for strong DNA binding. We further demonstrate the presence of long-distance thermodynamic connectivity between dimerization and oligomerization sites on H-NS which influences the binding of the co-repressor Cnu, and switches the DNA binding mode of the hetero-oligomeric H-NS:Cnu complex. Our work thus uncovers important organizational principles in H-NS including a multi-layered thermodynamic control, and provides a molecular framework broadly applicable to other thermo-osmo sensory proteins that employ similar mechanisms to regulate gene expression.

Evaluating conserved domains and motifs of decapod gonadotropin-releasing hormone G protein-coupled receptor superfamily

G protein-coupled receptors (GPCRs) are an ancient family of signal transducers that are both abundant and consequential in metazoan endocrinology. The evolutionary history and function of the GPCRs of the decapod superfamilies of gonadotropin-releasing hormone (GnRH) are yet to be fully elucidated. As part of which, the use of traditional phylogenetics and the recycling of a diminutive set of mis-annotated databases has proven insufficient. To address this, we have collated and revised eight existing and three novel GPCR repertoires for GnRH of decapod species. We developed a novel bioinformatic workflow that included clustering analysis to capture likely GnRH receptor-like proteins, followed by phylogenetic analysis of the seven transmembrane-spanning domains. A high degree of conservation of the sequences and topology of the domains and motifs allowed the identification of species-specific variation (up to ~70%, especially in the extracellular loops) that is thought to be influential to ligand-binding and function. Given the key functional role of the DRY motif across GPCRs, the classification of receptors based on the variation of this motif can be universally applied to resolve cryptic GPCR families, as was achieved in this work. Our results contribute to the resolution of the evolutionary history of invertebrate GnRH receptors and inform the design of bioassays in their deorphanization and functional annotation.

Conformational Tuning Shapes the Balance between Functional Promiscuity and Specialization in Paralogous Plasmodium Acyl-CoA Binding Proteins

Paralogous proteins confer enhanced fitness to organisms via complex sequence-conformation codes that shape functional divergence, specialization, or promiscuity. Here, we dissect the underlying mechanism of promiscuous binding versus partial subfunctionalization in paralogues by studying structurally identical acyl-CoA binding proteins (ACBPs) from Plasmodium falciparum that serve as promising drug targets due to their high expression during the protozoan proliferative phase. Combining spectroscopic measurements, solution NMR, SPR, and simulations on two of the paralogues, A16 and A749, we show that minor sequence differences shape nearly every local and global conformational feature. A749 displays a broader and heterogeneous native ensemble, weaker thermodynamic coupling and cooperativity, enhanced fluctuations, and a larger binding pocket volume compared to A16. Site-specific tryptophan probes signal a graded reduction in the sampling of substates in the holo form, which is particularly apparent in A749. The paralogues exhibit a spectrum of binding affinities to different acyl-CoAs with A749, the more promiscuous and hence the likely ancestor, binding 1000-fold stronger to lauroyl-CoA under physiological conditions. We thus demonstrate how minor sequence changes modulate the extent of long-range interactions and dynamics, effectively contributing to the molecular evolution of contrasting functional repertoires in paralogues.

AIMD-Chig: Exploring the conformational space of a 166-atom protein Chignolin with ab initio molecular dynamics

Molecular dynamics (MD) simulations have revolutionized the modeling of biomolecular conformations and provided unprecedented insight into molecular interactions. Due to the prohibitive computational overheads of ab initio simulation for large biomolecules, dynamic modeling for proteins is generally constrained on force field with molecular mechanics, which suffers from low accuracy as well as ignores the electronic effects. Here, we report AIMD-Chig, an MD dataset including 2 million conformations of 166-atom protein Chignolin sampled at the density functional theory (DFT) level with 7,763,146 CPU hours. 10,000 conformations were initialized covering the whole conformational space of Chignolin, including folded, unfolded, and metastable states. Ab initio simulations were driven by M06-2X/6-31 G* with a Berendsen thermostat at 340 K. We reported coordinates, energies, and forces for each conformation. AIMD-Chig brings the DFT level conformational space exploration from small organic molecules to real-world proteins. It can serve as the benchmark for developing machine learning potentials for proteins and facilitate the exploration of protein dynamics with ab initio accuracy.