Ligand entry pathways control the chemical space recognized by GPR183.

The G protein-coupled receptor GPR183 is a chemotactic receptor with an important function in the immune system and association with a variety of diseases. It recognizes ligands with diverse physicochemical properties as both the endogenous oxysterol ligand 7α,25-OHC and synthetic molecules can activate the G protein pathway of the receptor. To better understand the ligand promiscuity of GPR183, we utilized both molecular dynamics simulations and cell-based validation experiments. Our work reveals that the receptor possesses two ligand entry channels: one lateral between transmembrane helices 4 and 5 facing the membrane, and one facing the extracellular environment. Using enhanced sampling, we provide a detailed structural model of 7α,25-OHC entry through the lateral membrane channel. Importantly, the first ligand recognition point at the receptor surface has been captured in diverse experimentally solved structures of different GPCRs. The proposed ligand binding pathway is supported by in vitro data employing GPR183 mutants with a sterically blocked lateral entrance, which display diminished binding and signaling. In addition, computer simulations and experimental validation confirm the existence of a polar water channel which might serve as an alternative entrance gate for less lipophilic ligands from the extracellular milieu. Our study reveals knowledge to understand GPR183 functionality and ligand recognition with implications for the development of drugs for this receptor. Beyond, our work provides insights into a general mechanism GPCRs may use to respond to chemically diverse ligands.

Genotype and Phenotype Characterization of Rhinolophus sp. Sarbecoviruses from Vietnam: Implications for Coronavirus Emergence.

Bats are a major reservoir of zoonotic viruses, including coronaviruses. Since the emergence of SARS-CoV in 2002/2003 in Asia, important efforts have been made to describe the diversity of Coronaviridae circulating in bats worldwide, leading to the discovery of the precursors of epidemic and pandemic sarbecoviruses in horseshoe bats. We investigated the viral communities infecting horseshoe bats living in Northern Vietnam, and report here the first identification of sarbecoviruses in Rhinolophus thomasi and Rhinolophus siamensis bats. Phylogenetic characterization of seven strains of Vietnamese sarbecoviruses identified at least three clusters of viruses. Recombination and cross-species transmission between bats seemed to constitute major drivers of virus evolution. Vietnamese sarbecoviruses were mainly enteric, therefore constituting a risk of spillover for guano collectors or people visiting caves. To evaluate the zoonotic potential of these viruses, we analyzed in silico and in vitro the ability of their RBDs to bind to mammalian ACE2s and concluded that these viruses are likely restricted to their bat hosts. The workflow applied here to characterize the spillover potential of novel sarbecoviruses is of major interest for each time a new virus is discovered, in order to concentrate surveillance efforts on high-risk interfaces.

Determination of the Structure and Dynamics of the Fuzzy Coat of an Amyloid Fibril of IAPP Using Cryo-Electron Microscopy.

In recent years, major advances in cryo-electron microscopy (cryo-EM) have enabled the routine determination of complex biomolecular structures at atomistic resolution. An open challenge for this approach, however, concerns large systems that exhibit continuous dynamics. To address this problem, we developed the metadynamic electron microscopy metainference (MEMMI) method, which incorporates metadynamics, an enhanced conformational sampling approach, into the metainference method of integrative structural biology. MEMMI enables the simultaneous determination of the structure and dynamics of large heterogeneous systems by combining cryo-EM density maps with prior information through molecular dynamics, while at the same time modeling the different sources of error. To illustrate the method, we apply it to elucidate the dynamics of an amyloid fibril of the islet amyloid polypeptide (IAPP). The resulting conformational ensemble provides an accurate description of the structural variability of the disordered region of the amyloid fibril, known as fuzzy coat. The conformational ensemble also reveals that in nearly half of the structural core of this amyloid fibril, the side chains exhibit liquid-like dynamics despite the presence of the highly ordered network backbone of hydrogen bonds characteristic of the cross-ß structure of amyloid fibrils.

Clustering Heterogeneous Conformational Ensembles of Intrinsically Disordered Proteins with t-Distributed Stochastic Neighbor Embedding.

Intrinsically disordered proteins (IDPs) populate a range of conformations that are best described by a heterogeneous ensemble. Grouping an IDP ensemble into "structurally similar" clusters for visualization, interpretation, and analysis purposes is a much-desired but formidable task, as the conformational space of IDPs is inherently high-dimensional and reduction techniques often result in ambiguous classifications. Here, we employ the t-distributed stochastic neighbor embedding (t-SNE) technique to generate homogeneous clusters of IDP conformations from the full heterogeneous ensemble. We illustrate the utility of t-SNE by clustering conformations of two disordered proteins, Aß42, and α-synuclein, in their APO states and when bound to small molecule ligands. Our results shed light on ordered substates within disordered ensembles and provide structural and mechanistic insights into binding modes that confer specificity and affinity in IDP ligand binding. t-SNE projections preserve the local neighborhood information, provide interpretable visualizations of the conformational heterogeneity within each ensemble, and enable the quantification of cluster populations and their relative shifts upon ligand binding. Our approach provides a new framework for detailed investigations of the thermodynamics and kinetics of IDP ligand binding and will aid rational drug design for IDPs.

Virus Pop-Expanding Viral Databases by Protein Sequence Simulation.

The improvement of our knowledge of the virosphere, which includes unknown viruses, is a key area in virology. Metagenomics tools, which perform taxonomic assignation from high throughput sequencing datasets, are generally evaluated with datasets derived from biological samples or in silico spiked samples containing known viral sequences present in public databases, resulting in the inability to evaluate the capacity of these tools to detect novel or distant viruses. Simulating realistic evolutionary directions is therefore key to benchmark and improve these tools. Additionally, expanding current databases with realistic simulated sequences can improve the capacity of alignment-based searching strategies for finding distant viruses, which could lead to a better characterization of the "dark matter" of metagenomics data. Here, we present Virus Pop, a novel pipeline for simulating realistic protein sequences and adding new branches to a protein phylogenetic tree. The tool generates simulated sequences with substitution rate variations that are dependent on protein domains and inferred from the input dataset, allowing for a realistic representation of protein evolution. The pipeline also infers ancestral sequences corresponding to multiple internal nodes of the input data phylogenetic tree, enabling new sequences to be inserted at various points of interest in the group studied. We demonstrated that Virus Pop produces simulated sequences that closely match the structural and functional characteristics of real protein sequences, taking as an example the spike protein of sarbecoviruses. Virus Pop also succeeded at creating sequences that resemble real sequences not included in the databases, which facilitated the identification of a novel pathogenic human circovirus not included in the input database. In conclusion, Virus Pop is helpful for challenging taxonomic assignation tools and could help improve databases to better detect distant viruses.

SARS-CoV-2-related bat virus behavior in human-relevant models sheds light on the origin of COVID-19.

Bat sarbecovirus BANAL-236 is highly related to SARS-CoV-2 and infects human cells, albeit lacking the furin cleavage site in its spike protein. BANAL-236 replicates efficiently and pauci-symptomatically in humanized mice and in macaques, where its tropism is enteric, strongly differing from that of SARS-CoV-2. BANAL-236 infection leads to protection against superinfection by a virulent strain. We find no evidence of antibodies recognizing bat sarbecoviruses in populations in close contact with bats in which the virus was identified, indicating that such spillover infections, if they occur, are rare. Six passages in humanized mice or in human intestinal cells, mimicking putative early spillover events, select adaptive mutations without appearance of a furin cleavage site and no change in virulence. Therefore, acquisition of a furin site in the spike protein is likely a pre-spillover event that did not occur upon replication of a SARS-CoV-2-like bat virus in humans or other animals. Other hypotheses regarding the origin of the SARS-CoV-2 should therefore be evaluated, including the presence of sarbecoviruses carrying a spike with a furin cleavage site in bats.

Describing inhibitor specificity for the amino acid transporter LAT1 from metainference simulations.

The human L-type amino acid transporter 1 (LAT1; SLC7A5) is a membrane transporter of amino acids, thyroid hormones, and drugs such as the Parkinson's disease drug levodopa (L-Dopa). LAT1 is found in the blood-brain barrier, testis, bone marrow, and placenta, and its dysregulation has been associated with various neurological diseases, such as autism and epilepsy, as well as cancer. In this study, we combine metainference molecular dynamics simulations, molecular docking, and experimental testing, to characterize LAT1-inhibitor interactions. We first conducted a series of molecular docking experiments to identify the most relevant interactions between LAT1's substrate-binding site and ligands, including both inhibitors and substrates. We then performed metainference molecular dynamics simulations using cryoelectron microscopy structures in different conformations of LAT1 with the electron density map as a spatial restraint, to explore the inherent heterogeneity in the structures. We analyzed the LAT1 substrate-binding site to map important LAT1-ligand interactions as well as newly described druggable pockets. Finally, this analysis guided the discovery of previously unknown LAT1 ligands using virtual screening and cellular uptake experiments. Our results improve our understanding of LAT1-inhibitor recognition, providing a framework for rational design of future lead compounds targeting this key drug target.

Exploring the conformational diversity of proteins.

An artificial intelligence-based method can predict distinct conformational states of membrane transporters and receptors.

Bat coronaviruses related to SARS-CoV-2 and infectious for human cells.

The animal reservoir of SARS-CoV-2 is unknown despite reports of SARS-CoV-2-related viruses in Asian Rhinolophus bats1-4, including the closest virus from R. affinis, RaTG13 (refs. 5,6), and pangolins7-9. SARS-CoV-2 has a mosaic genome, to which different progenitors contribute. The spike sequence determines the binding affinity and accessibility of its receptor-binding domain to the cellular angiotensin-converting enzyme 2 (ACE2) receptor and is responsible for host range10-12. SARS-CoV-2 progenitor bat viruses genetically close to SARS-CoV-2 and able to enter human cells through a human ACE2 (hACE2) pathway have not yet been identified, although they would be key in understanding the origin of the epidemic. Here we show that such viruses circulate in cave bats living in the limestone karstic terrain in northern Laos, in the Indochinese peninsula. We found that the receptor-binding domains of these viruses differ from that of SARS-CoV-2 by only one or two residues at the interface with ACE2, bind more efficiently to the hACE2 protein than that of the SARS-CoV-2 strain isolated in Wuhan from early human cases, and mediate hACE2-dependent entry and replication in human cells, which is inhibited by antibodies that neutralize SARS-CoV-2. None of these bat viruses contains a furin cleavage site in the spike protein. Our findings therefore indicate that bat-borne SARS-CoV-2-like viruses that are potentially infectious for humans circulate in Rhinolophus spp. in the Indochinese peninsula.

Rational design of ASCT2 inhibitors using an integrated experimental-computational approach.

ASCT2 (SLC1A5) is a sodium-dependent neutral amino acid transporter that controls amino acid homeostasis in peripheral tissues. In cancer, ASCT2 is up-regulated where it modulates intracellular glutamine levels, fueling cell proliferation. Nutrient deprivation via ASCT2 inhibition provides a potential strategy for cancer therapy. Here, we rationally designed stereospecific inhibitors exploiting specific subpockets in the substrate binding site using computational modeling and cryo-electron microscopy (cryo-EM). The final structures combined with molecular dynamics simulations reveal multiple pharmacologically relevant conformations in the ASCT2 binding site as well as a previously unknown mechanism of stereospecific inhibition. Furthermore, this integrated analysis guided the design of a series of unique ASCT2 inhibitors. Our results provide a framework for future development of cancer therapeutics targeting nutrient transport via ASCT2, as well as demonstrate the utility of combining computational modeling and cryo-EM for solute carrier ligand discovery.

Multi-replica biased sampling for photoswitchable π-conjugated polymers.

In recent years, π-conjugated polymers are attracting considerable interest in view of their light-dependent torsional reorganization around the π-conjugated backbone, which determines peculiar light-emitting properties. Motivated by the interest in designing conjugated polymers with tunable photoswitchable pathways, we devised a computational framework to enhance the sampling of the torsional conformational space and, at the same time, estimate ground- to excited-state free-energy differences. This scheme is based on a combination of Hamiltonian Replica Exchange Method (REM), parallel bias metadynamics, and free-energy perturbation theory. In our scheme, each REM samples an intermediate unphysical state between the ground and the first two excited states, which are characterized by time-dependent density functional theory simulations at the B3LYP/6-31G* level of theory. We applied the method to a 5-mer of 9,9-dioctylfluorene and found that upon irradiation, this system can undergo a dihedral inversion from -155° to 155°, crossing a barrier that decreases from 0.1 eV in the ground state (S0) to 0.05 eV and 0.04 eV in the first (S1) and second (S2) excited states. Furthermore, S1 and even more S2 were predicted to stabilize coplanar dihedrals, with a local free-energy minimum located at ±44°. The presence of a free-energy barrier of 0.08 eV for the S1 state and 0.12 eV for the S2 state can trap this conformation in a basin far from the global free-energy minimum located at 155°. The simulation results were compared with the experimental emission spectrum, showing a quantitative agreement with the predictions provided by our framework.

Small-molecule sequestration of amyloid-ß as a drug discovery strategy for Alzheimer's disease.

Disordered proteins are challenging therapeutic targets, and no drug is currently in clinical use that modifies the properties of their monomeric states. Here, we identify a small molecule (10074-G5) capable of binding and sequestering the intrinsically disordered amyloid-ß (Aß) peptide in its monomeric, soluble state. Our analysis reveals that this compound interacts with Aß and inhibits both the primary and secondary nucleation pathways in its aggregation process. We characterize this interaction using biophysical experiments and integrative structural ensemble determination methods. We observe that this molecule increases the conformational entropy of monomeric Aß while decreasing its hydrophobic surface area. We also show that it rescues a Caenorhabditis elegans model of Aß-associated toxicity, consistent with the mechanism of action identified from the in silico and in vitro studies. These results illustrate the strategy of stabilizing the monomeric states of disordered proteins with small molecules to alter their behavior for therapeutic purposes.

A Practical Guide to the Simultaneous Determination of Protein Structure and Dynamics Using Metainference.

Accurate protein structural ensembles can be determined with metainference, a Bayesian inference method that integrates experimental information with prior knowledge of the system and deals with all sources of uncertainty and errors as well as with system heterogeneity. Furthermore, metainference can be implemented using the metadynamics approach, which enables the computational study of complex biological systems requiring extensive conformational sampling. In this chapter, we provide a step-by-step guide to perform and analyse metadynamic metainference simulations using the ISDB module of the open-source PLUMED library, as well as a series of practical tips to avoid common mistakes. Specifically, we will guide the reader in the process of learning how to model the structural ensemble of a small disordered peptide by combining state-of-the-art molecular mechanics force fields with nuclear magnetic resonance data, including chemical shifts, scalar couplings and residual dipolar couplings.

Effects of α-tubulin acetylation on microtubule structure and stability.

Acetylation of K40 in α-tubulin is the sole posttranslational modification to mark the luminal surface of microtubules. It is still controversial whether its relationship with microtubule stabilization is correlative or causative. We have obtained high-resolution cryo-electron microscopy (cryo-EM) reconstructions of pure samples of αTAT1-acetylated and SIRT2-deacetylated microtubules to visualize the structural consequences of this modification and reveal its potential for influencing the larger assembly properties of microtubules. We modeled the conformational ensembles of the unmodified and acetylated states by using the experimental cryo-EM density as a structural restraint in molecular dynamics simulations. We found that acetylation alters the conformational landscape of the flexible loop that contains αK40. Modification of αK40 reduces the disorder of the loop and restricts the states that it samples. We propose that the change in conformational sampling that we describe, at a location very close to the lateral contacts site, is likely to affect microtubule stability and function.

Solid-State NMR and MD Study of the Structure of the Statherin Mutant SNa15 on Mineral Surfaces.

Elucidation of the structure and interactions of proteins at native mineral interfaces is key to understanding how biological systems regulate the formation of hard tissue structures. In addition, understanding how these same proteins interact with non-native mineral surfaces has important implications for the design of medical and dental implants, chromatographic supports, diagnostic tools, and a host of other applications. Here, we combine solid-state NMR spectroscopy, isotherm measurements, and molecular dynamics simulations to study how SNa15, a peptide derived from the hydroxyapatite (HAP) recognition domain of the biomineralization protein statherin, interacts with HAP, silica (SiO2), and titania (TiO2) mineral surfaces. Adsorption isotherms are used to characterize the binding affinity of SNa15 to HAP, SiO2, and TiO2. We also apply 1D 13C CP MAS, 1D 15N CP MAS, and 2D 13C-13C DARR experiments to SNa15 samples with uniformly 13C- and 15N-enriched residues to determine backbone and side-chain chemical shifts. Different computational tools, namely TALOS-N and molecular dynamics simulations, are used to deduce secondary structure from backbone and side-chain chemical shift data. Our results show that SNa15 adopts an α-helical conformation when adsorbed to HAP and TiO2, but the helix largely unravels upon adsorption to SiO2. Interactions with HAP are mediated in general by acidic and some basic amino acids, although the specific amino acids involved in direct surface interaction vary with surface. The integrated experimental and computational approach used in this study is able to provide high-resolution insights into adsorption of proteins on interfaces.

Determination of protein structural ensembles using cryo-electron microscopy.

Achieving a comprehensive understanding of the behaviour of proteins is greatly facilitated by the knowledge of their structures, thermodynamics and dynamics. All this information can be provided in an effective manner in terms of structural ensembles. A structural ensemble can be obtained by determining the structures, populations and interconversion rates for all the main states that a protein can occupy. To reach this goal, integrative methods that combine experimental and computational approaches provide powerful tools. Here we focus on cryo-electron microscopy, which has become over recent years an invaluable resource to bridge the gap from order to disorder in structural biology. In this review, we provide a perspective of the current challenges and opportunities in determining protein structural ensembles using integrative approaches that can combine cryo-electron microscopy data with other available sources of information, along with an overview of the tools available to the community.

Bayesian Weighing of Electron Cryo-Microscopy Data for Integrative Structural Modeling.

Cryo-electron microscopy (cryo-EM) has become a mainstream technique for determining the structures of complex biological systems. However, accurate integrative structural modeling has been hampered by the challenges in objectively weighing cryo-EM data against other sources of information due to the presence of random and systematic errors, as well as correlations, in the data. To address these challenges, we introduce a Bayesian scoring function that efficiently and accurately ranks alternative structural models of a macromolecular system based on their consistency with a cryo-EM density map as well as other experimental and prior information. The accuracy of this approach is benchmarked using complexes of known structure and illustrated in three applications: the structural determination of the GroEL/GroES, RNA polymerase II, and exosome complexes. The approach is implemented in the open-source Integrative Modeling Platform (http://integrativemodeling.org), thus enabling integrative structure determination by combining cryo-EM data with other sources of information.