Genome-wide Membrane Protein Structure Prediction

Insights into protein structure using cryogenic light microscopy

Fluorescence microscopy has witnessed many clever innovations in the last two decades, leading to new methods such as structured illumination and super-resolution microscopies. The attainable resolution in biological samples is, however, ultimately limited by residual motion within the sample or in the microscope setup. Thus, such experiments are typically performed on chemically fixed samples. Cryogenic light microscopy (Cryo-LM) has been investigated as an alternative, drawing on various preservation techniques developed for cryogenic electron microscopy (Cryo-EM). Moreover, this approach offers a powerful platform for correlative microscopy. Another key advantage of Cryo-LM is the strong reduction in photobleaching at low temperatures, facilitating the collection of orders of magnitude more photons from a single fluorophore. This results in much higher localization precision, leading to Angstrom resolution. In this review, we discuss the general development and progress of Cryo-LM with an emphasis on its application in harnessing structural information on proteins and protein complexes.

Tris(hydroxymethyl)aminomethane Linker-Bearing Triazine-Based Triglucosides for Solubilization and Stabilization of Membrane Proteins

High-resolution membrane protein structures are essential for a fundamental understanding of the molecular basis of diverse cellular processes and for drug discovery. Detergents are widely used to extract membrane-spanning proteins from membranes and maintain them in a functional state for downstream characterization. Due to limited long-term stability of membrane proteins encapsulated in conventional detergents, development of novel agents is required to facilitate membrane protein structural study. In the current study, we designed and synthesized tris(hydroxymethyl)aminomethane linker-bearing triazine-based triglucosides (TTGs) for solubilization and stabilization of membrane proteins. When these glucoside detergents were evaluated for four membrane proteins including two G protein-coupled receptors, a few TTGs including TTG-C10 and TTG-C11 displayed markedly enhanced behaviors toward membrane protein stability relative to two maltoside detergents [DDM (n-dodecyl-β-d-maltoside) and LMNG (lauryl maltose neopentyl glycol)]. This is a notable feature of the TTGs as glucoside detergents tend to be inferior to maltoside detergents at stabilizing membrane proteins. The favorable behavior of the TTGs for membrane protein stability is likely due to the high hydrophobicity of the lipophilic groups, an optimal range of hydrophilic-lipophilic balance, and the absence of cis-trans isomerism.

Molecular determinants of acrylamide neurotoxicity through covalent docking

Acrylamide (ACR) is formed during food processing by Maillard reaction between sugars and proteins at high temperatures. It is also used in many industries, from water waste treatment to manufacture of paper, fabrics, dyes and cosmetics. Unfortunately, cumulative exposure to acrylamide, either from diet or at the workplace, may result in neurotoxicity. Such adverse effects arise from covalent adducts formed between acrylamide and cysteine residues of several neuronal proteins via a Michael addition reaction. The molecular determinants of acrylamide reactivity and its impact on protein function are not completely understood. Here we have compiled a list of acrylamide protein targets reported so far in the literature in connection with neurotoxicity and performed a systematic covalent docking study. Our results indicate that acrylamide binding to cysteine is favored in the presence of nearby positively charged amino acids, such as lysines and arginines. For proteins with more than one reactive Cys, docking scores were able to discriminate between the primary ACR modification site and secondary sites modified only at high ACR concentrations. Therefore, docking scores emerge as a potential filter to predict Cys reactivity against acrylamide. Inspection of the ACR-protein complex structures provides insights into the putative functional consequences of ACR modification, especially for non-enzyme proteins. Based on our study, covalent docking is a promising computational tool to predict other potential protein targets mediating acrylamide neurotoxicity.

Deciphering a hexameric protein complex with Angstrom optical resolution

Cryogenic optical localization in three dimensions (COLD) was recently shown to resolve up to four binding sites on a single protein. However, because COLD relies on intensity fluctuations that result from the blinking behavior of fluorophores, it is limited to cases where individual emitters show different brightness. This significantly lowers the measurement yield. To extend the number of resolved sites as well as the measurement yield, we employ partial labeling and combine it with polarization encoding in order to identify single fluorophores during their stochastic blinking. We then use a particle classification scheme to identify and resolve heterogenous subsets and combine them to reconstruct the three-dimensional arrangement of large molecular complexes. We showcase this method (polarCOLD) by resolving the trimer arrangement of proliferating cell nuclear antigen (PCNA) and six different sites of the hexamer protein Caseinolytic Peptidase B (ClpB) of Thermus thermophilus in its quaternary structure, both with Angstrom resolution. The combination of polarCOLD and single-particle cryogenic electron microscopy (cryoEM) promises to provide crucial insight into intrinsic heterogeneities of biomolecular structures. Furthermore, our approach is fully compatible with fluorescent protein labeling and can, thus, be used in a wide range of studies in cell and membrane biology.

Molecular modeling, mutational analysis and steroid specificity of the ligand binding pocket of mPRα (PAQR7): Shared ligand binding with AdipoR1 and its structural basis

The 7-transmembrane architecture of adiponectin receptors (AdipoRs), determined from their X-ray crystal structures, was used for homology modeling of another progesterone and adipoQ receptor (PAQR) family member, membrane progesterone receptor alpha (mPRα). The mPRα model identified excess positively charged residues on the cytosolic side, suggesting it has the same membrane orientation as AdipoRs with an intracellular N-terminus. The homology model showed identical amino acid residues to those forming the zinc binding pocket in AdipoRs, which strongly implies that zinc is also present in mPRα. The homology model showed a critical H-bond interaction between the glutamine (Q) residue at 206 in the binding pocket and the 20-carbonyl of progesterone. Mutational analysis showed no progesterone binding to the arginine (R) 206 mutant and modeling predicted this was due to the strong positive charge of arginine stabilizing the presence of an oleic acid (C18:1) molecule in the binding pocket, as observed in the X-rays of AdipoRs. High Zn²⁺ concentrations are predicted to form a salt with the carboxylate group of the oleic acid, thereby eliminating its binding to the free fatty acid (FFA) binding pocket, and allowing progesterone to bind. This is supported by experiments showing 100 µM Zn²⁺ addition restored [³H]-progesterone binding of the Q206R mutant to levels in WT mPRα and increased [³H]-progesterone binding to mPRγ and AdipoR1 which have arginine residues in this region. The model predicts hydrophobic interactions of progesterone with amino acid residues surrounding the binding pocket, including valine 146 in TM3, which when mutated into a polar serine resulted in a complete loss of [³H]-progesterone binding. The mPRα model showed there is no hydrogen bond donor in the vicinity of the 3-keto group of progesterone and ligand structure-activity studies with 3-deoxy steroids revealed that, unlike the nuclear progesterone receptor, the 3-carbonyl oxygen is not essential for binding to mPRα. Interestingly, the small synthetic AdipoR agonist, AdipoRon, displayed binding affinity for mPRα and mimicked progesterone signaling, whereas D-e-MAPP, a ceramidase inhibitor, blocked progesterone signaling. Thus, critical residues around the binding pocket and steroid structures that bind mPRα, as well as similarities with AdipoRs, can be predicted from the homology model.

Photopharmacology of Ion Channels through the Light of the Computational Microscope

The optical control and investigation of neuronal activity can be achieved and carried out with photoswitchable ligands. Such compounds are designed in a modular fashion, combining a known ligand of the target protein and a photochromic group, as well as an additional electrophilic group for tethered ligands. Such a design strategy can be optimized by including structural data. In addition to experimental structures, computational methods (such as homology modeling, molecular docking, molecular dynamics and enhanced sampling techniques) can provide structural insights to guide photoswitch design and to understand the observed light-regulated effects. This review discusses the application of such structure-based computational methods to photoswitchable ligands targeting voltage- and ligand-gated ion channels. Structural mapping may help identify residues near the ligand binding pocket amenable for mutagenesis and covalent attachment. Modeling of the target protein in a complex with the photoswitchable ligand can shed light on the different activities of the two photoswitch isomers and the effect of site-directed mutations on photoswitch binding, as well as ion channel subtype selectivity. The examples presented here show how the integration of computational modeling with experimental data can greatly facilitate photoswitchable ligand design and optimization. Recent advances in structural biology, both experimental and computational, are expected to further strengthen this rational photopharmacology approach.

Bitter Taste and Olfactory Receptors: Beyond Chemical Sensing in the Tongue and the Nose

Abstract

The Up-and-Coming-Scientist section of the current issue of the Journal of Membrane Biology features the invited essay by Dr. Mercedes Alfonso-Prieto, Assistant Professor at the Forschungszentrum Jülich (FZJ), Germany, and the Heinrich-Heine University Düsseldorf, Vogt Institute for Brain Research. Dr. Alfonso-Prieto completed her doctoral degree in chemistry at the Barcelona Science Park, Spain, in 2009, pursued post-doctoral research in computational molecular sciences at Temple University, USA, and then, as a Marie Curie post-doctoral fellow at the University of Barcelona, worked on computations of enzyme reactions and modeling of photoswitchable ligands targeting neuronal receptors. In 2016, she joined the Institute for Advanced Science and the Institute for Computational Biomedicine at the FZJ, where she pursues research on modeling and simulation of chemical senses. The invited essay by Dr. Alfonso-Prieto discusses state-of-the-art modeling of molecular receptors involved in chemical sensing – the senses of taste and smell. These receptors, and computational methods to study them, are the focus of Dr. Alfonso-Prieto’s research. Recently, Dr. Alfonso-Prieto and colleagues have presented a new methodology to predict ligand binding poses for GPCRs, and extensive computations that deciphered the ligand selectivity determinants of bitter taste receptors. These developments inform our current understanding of how taste occurs at the molecular level.

Graphic Abstract

In Silico Investigation of Bitter Hop-Derived Compounds and Their Cognate Bitter Taste Receptors

The typical bitter taste of beer is caused by adding hops (Humulus lupulus L.) during the wort boiling process. The bitter taste of hop-derived compounds was found to be mediated by three bitter taste receptors: TAS2R1, TAS2R14, and TAS2R40. In this work, structural bioinformatics analyses were used to characterize the binding modes of trans-isocohumulone, trans-isohumulone, trans-isoadhumulone, cis-isocohumulone, cis-isohumulone, cis-isoadhumulone, cohumulone, humulone, adhumulone, and 8-prenylnaringenin into the orthosteric binding site of their cognate receptors. A conserved asparagine in transmembrane 3 was found to be essential for the recognition of hop-derived compounds, whereas the surrounding residues in the binding site of the three receptors encode the ligand specificity. Hop-derived compounds are renowned bioactive molecules and are considered as potential hit molecules for drug discovery to treat metabolic diseases. A chemoinformatics analysis revealed that hop-derived compounds cluster in a different region of the chemical space compared to known bitter food-derived compounds, pinpointing hop-derived compounds as a very peculiar class of bitter compounds.

Ligand Pose Predictions for Human G Protein-Coupled Receptors: Insights from the Amber-Based Hybrid Molecular Mechanics/Coarse-Grained Approach

Human G protein-coupled receptors (hGPCRs) are the most frequent targets of Food and Drug Administration (FDA)-approved drugs. Structural bioinformatics, along with molecular simulation, can support structure-based drug design targeting hGPCRs. In this context, several years ago, we developed a hybrid molecular mechanics (MM)/coarse-grained (CG) approach to predict ligand poses in low-resolution hGPCR models. The approach was based on the GROMOS96 43A1 and PRODRG united-atom force fields for the MM part. Here, we present a new MM/CG implementation using, instead, the Amber 14SB and GAFF all-atom potentials for proteins and ligands, respectively. The new implementation outperforms the previous one, as shown by a variety of applications on models of hGPCR/ligand complexes at different resolutions, and it is also more user-friendly. Thus, it emerges as a useful tool to predict poses in low-resolution models and provides insights into ligand binding similarly to all-atom molecular dynamics, albeit at a lower computational cost.

Dual binding mode of "bitter sugars" to their human bitter taste receptor target

The 25 human bitter taste receptors (hTAS2Rs) are responsible for detecting bitter molecules present in food, and they also play several physiological and pathological roles in extraoral compartments. Therefore, understanding their ligand specificity is important both for food research and for pharmacological applications. Here we provide a molecular insight into the exquisite molecular recognition of bitter β-glycopyranosides by one of the members of this receptor subclass, hTAS2R16. Most of its agonists have in common the presence of a β-glycopyranose unit along with an extremely structurally diverse aglycon moiety. This poses the question of how hTAS2R16 can recognize such a large number of "bitter sugars". By means of hybrid molecular mechanics/coarse grained molecular dynamics simulations, here we show that the three hTAS2R16 agonists salicin, arbutin and phenyl-β-D-glucopyranoside interact with the receptor through a previously unrecognized dual binding mode. Such mechanism may offer a seamless way to fit different aglycons inside the binding cavity, while maintaining the sugar bound, similar to the strategy used by several carbohydrate-binding lectins. Our prediction is validated a posteriori by comparison with mutagenesis data and also rationalizes a wealth of structure-activity relationship data. Therefore, our findings not only provide a deeper molecular characterization of the binding determinants for the three ligands studied here, but also give insights applicable to other hTAS2R16 agonists. Together with our results for other hTAS2Rs, this study paves the way to improve our overall understanding of the structural determinants of ligand specificity in bitter taste receptors.

Understanding Ligand Binding to G-Protein Coupled Receptors Using Multiscale Simulations

Human G-protein coupled receptors (GPCRs) convey a wide variety of extracellular signals inside the cell and they are one of the main targets for pharmaceutical intervention. Rational drug design requires structural information on these receptors; however, the number of experimental structures is scarce. This gap can be filled by computational models, based on homology modeling and docking techniques. Nonetheless, the low sequence identity across GPCRs and the chemical diversity of their ligands may limit the quality of these models and hence refinement using molecular dynamics simulations is recommended. This is the case for olfactory and bitter taste receptors, which constitute the first and third largest GPCR groups and show sequence identities with the available GPCR templates below 20%. We have developed a molecular dynamics approach, based on the combination of molecular mechanics and coarse grained (MM/CG), tailored to study ligand binding in GPCRs. This approach has been applied so far to bitter taste receptor complexes, showing significant predictive power. The protein/ligand interactions observed in the simulations were consistent with extensive mutagenesis and functional data. Moreover, the simulations predicted several binding residues not previously tested, which were subsequently verified by carrying out additional experiments. Comparison of the simulations of two bitter taste receptors with different ligand selectivity also provided some insights into the binding determinants of bitter taste receptors. Although the MM/CG approach has been applied so far to a limited number of GPCR/ligand complexes, the excellent agreement of the computational models with the mutagenesis and functional data supports the applicability of this method to other GPCRs for which experimental structures are missing. This is particularly important for the challenging case of GPCRs with low sequence identity with available templates, for which molecular docking shows limited predictive power.

Multiscale simulations on human Frizzled and Taste2 GPCRs

Recently, molecular dynamics simulations, from all atom and coarse grained to hybrid methods bridging the two scales, have provided exciting functional insights into class F (Frizzled and Taste2) GPCRs (about 40 members in humans). Findings include: (i) The activation of one member of the Frizzled receptors (FZD4) involves a bending of transmembrane helix TM7 far larger than that in class A GPCRs. (ii) The affinity of an anticancer drug targeting another member (Smoothened receptor) decreases in a specific drug-resistant variant, because the mutation ultimately disrupts the binding cavity and affects TM6. (iii) A novel two-state recognition mechanism explains the very large agonist diversity for at least one member of the Taste2 GPCRs, hTAS2R46.

GABAA receptor family: overview on structural characterization

The pentameric γ-aminobutyric acid type A receptors are ion channels activated by ligands, which intervene in the rapid inhibitory transmission in the mammalian CNS. Due to their rich pharmacology and therapeutic potential, it is essential to understand their structure and function thoroughly. This deep characterization was hampered by the lack of experimental structural information for many years. Thus, computational techniques have been extensively combined with experimental data, in order to undertake the study of γ-aminobutyric acid type A receptors and their interaction with drugs. Here, we review the exciting journey made to assess the structures of these receptors and outline major outcomes. Finally, we discuss the brand new structure of the α1β2γ2 subtype and the amazing advances it brings to the field.

A comparative study of branched and linear mannitol-based amphiphiles on membrane protein stability

The study of membrane proteins is extremely challenging, mainly because of the incompatibility of the hydrophobic surfaces of membrane proteins with an aqueous medium. Detergents are essential agents used to maintain membrane protein stability in non-native environments. However, conventional detergents fail to stabilize the native structures of many membrane proteins. Development of new amphipathic agents with enhanced efficacy for membrane protein stabilization is necessary to address this important problem. We have designed and synthesized linear and branched mannitol-based amphiphiles (MNAs), and comparative studies showed that most of the branched MNAs had advantages over the linear agents in terms of membrane protein stability. In addition, a couple of the new MNAs displayed favorable behaviors compared to n-dodecyl-β-d-maltoside and the previously developed MNAs in maintaining the native protein structures, indicating potential utility of these new agents in membrane protein study.

New penta-saccharide-bearing tripod amphiphiles for membrane protein structure studies

Integral membrane proteins either alone or as complexes carry out a range of key cellular functions. Detergents are indispensable tools in the isolation of membrane proteins from biological membranes for downstream studies. Although a large number of techniques and tools, including a wide variety of detergents, are available, purification and structural characterization of many membrane proteins remain challenging. In the current study, a new class of tripod amphiphiles bearing two different penta-saccharide head groups, designated TPSs, were developed and evaluated for their ability to extract and stabilize a range of diverse membrane proteins. Variations in the structures of the detergent head and tail groups allowed us to prepare three sets of the novel agents with distinctive structures. Some TPSs (TPS-A8 and TPS-E7) were efficient at extracting two proteins in a functional state while others (TPS-E8 and TPS-E10L) conferred marked stability to all membrane proteins (and membrane protein complexes) tested here compared to a conventional detergent. Use of TPS-E10L led to clear visualization of a receptor-G_s complex using electron microscopy, indicating profound potential in membrane protein research.

An Engineered Lithocholate-Based Facial Amphiphile Stabilizes Membrane Proteins: Assessing the Impact of Detergent Customizability on Protein Stability

Amphiphiles are critical tools for the structural and functional study of membrane proteins. Membrane proteins encapsulated by conventional head-to-tail detergents tend to undergo structural degradation, necessitating the development of structurally novel agents with improved efficacy. In recent years, facial amphiphiles have yielded encouraging results in terms of membrane protein stability. Herein, we report a new facial detergent (i.e., LFA-C4) that confers greater stability to tested membrane proteins than the bola form analogue. Owing to the increased facial property and the adaptability of the detergent micelles in complex with different membrane proteins, LFA-C4 yields increased stability compared to n-dodecyl-β-d-maltoside (DDM). Thus, this study not only describes a novel maltoside detergent with enhanced protein-stabilizing properties, but also shows that the customizable nature of a detergent plays an important role in the stabilization of membrane proteins. Owing to both synthetic convenience and enhanced stabilization efficacy for a range of membrane proteins, the new agent has major potential in membrane protein research.

Predicting ligand binding poses for low-resolution membrane protein models: Perspectives from multiscale simulations

Membrane receptors constitute major targets for pharmaceutical intervention. Drug design efforts rely on the identification of ligand binding poses. However, the limited experimental structural information available may make this extremely challenging, especially when only low-resolution homology models are accessible. In these cases, the predictions may be improved by molecular dynamics simulation approaches. Here we review recent developments of multiscale, hybrid molecular mechanics/coarse-grained (MM/CG) methods applied to membrane proteins. In particular, we focus on our in-house MM/CG approach. It is especially tailored for G-protein coupled receptors, the largest membrane receptor family in humans. We show that our MM/CG approach is able to capture the atomistic details of the receptor/ligand binding interactions, while keeping the computational cost low by representing the protein frame and the membrane environment in a highly simplified manner. We close this review by discussing ongoing improvements and challenges of the current implementation of our MM/CG code.

Open Boundary Simulations of Proteins and Their Hydration Shells by Hamiltonian Adaptive Resolution Scheme

The recently proposed Hamiltonian adaptive resolution scheme (H-AdResS) allows the performance of molecular simulations in an open boundary framework. It allows changing, on the fly, the resolution of specific subsets of molecules (usually the solvent), which are free to diffuse between the atomistic region and the coarse-grained reservoir. So far, the method has been successfully applied to pure liquids. Coupling the H-AdResS methodology to hybrid models of proteins, such as the molecular mechanics/coarse-grained (MM/CG) scheme, is a promising approach for rigorous calculations of ligand binding free energies in low-resolution protein models. Toward this goal, here we apply for the first time H-AdResS to two atomistic proteins in dual-resolution solvent, proving its ability to reproduce structural and dynamic properties of both the proteins and the solvent, as obtained from atomistic simulations.

Agonist Binding to Chemosensory Receptors: A Systematic Bioinformatics Analysis

Human G-protein coupled receptors (hGPCRs) constitute a large and highly pharmaceutically relevant membrane receptor superfamily. About half of the hGPCRs' family members are chemosensory receptors, involved in bitter taste and olfaction, along with a variety of other physiological processes. Hence these receptors constitute promising targets for pharmaceutical intervention. Molecular modeling has been so far the most important tool to get insights on agonist binding and receptor activation. Here we investigate both aspects by bioinformatics-based predictions across all bitter taste and odorant receptors for which site-directed mutagenesis data are available. First, we observe that state-of-the-art homology modeling combined with previously used docking procedures turned out to reproduce only a limited fraction of ligand/receptor interactions inferred by experiments. This is most probably caused by the low sequence identity with available structural templates, which limits the accuracy of the protein model and in particular of the side-chains' orientations. Methods which transcend the limited sampling of the conformational space of docking may improve the predictions. As an example corroborating this, we review here multi-scale simulations from our lab and show that, for the three complexes studied so far, they significantly enhance the predictive power of the computational approach. Second, our bioinformatics analysis provides support to previous claims that several residues, including those at positions 1.50, 2.50, and 7.52, are involved in receptor activation.