Calcium-Driven In Silico Inactivation of a Human Olfactory Receptor.

Conformational changes as well as molecular determinants related to the activation and inactivation of olfactory receptors are still poorly understood due to the intrinsic difficulties in the structural determination of this GPCR family. Here, we perform, for the first time, the in silico inactivation of human olfactory receptor OR51E2, highlighting the possible role of calcium in this receptor state transition. Using molecular dynamics simulations, we show that a divalent ion in the ion binding site, coordinated by two acidic residues at positions 2.50 and 3.39 conserved across most ORs, stabilizes the receptor in its inactive state. In contrast, protonation of the same two acidic residues is not sufficient to drive inactivation within the microsecond timescale of our simulations. Our findings suggest a novel molecular mechanism for OR inactivation, potentially guiding experimental validation and offering insights into the possible broader role of divalent ions in GPCR signaling.

Structure-function relationships of the disease-linked A218T oxytocin receptor variant.

Various single nucleotide polymorphisms (SNPs) in the oxytocin receptor (OXTR) gene have been associated with behavioral traits, autism spectrum disorder (ASD) and other diseases. The non-synonymous SNP rs4686302 results in the OXTR variant A218T and has been linked to core characteristics of ASD, trait empathy and preterm birth. However, the molecular and intracellular mechanisms underlying those associations are still elusive. Here, we uncovered the molecular and intracellular consequences of this mutation that may affect the psychological or behavioral outcome of oxytocin (OXT)-treatment regimens in clinical studies, and provide a mechanistic explanation for an altered receptor function. We created two monoclonal HEK293 cell lines, stably expressing either the wild-type or A218T OXTR. We detected an increased OXTR protein stability, accompanied by a shift in Ca2+ dynamics and reduced MAPK pathway activation in the A218T cells. Combined whole-genome and RNA sequencing analyses in OXT-treated cells revealed 7823 differentially regulated genes in A218T compared to wild-type cells, including 429 genes being associated with ASD. Furthermore, computational modeling provided a molecular basis for the observed change in OXTR stability suggesting that the OXTR mutation affects downstream events by altering receptor activation and signaling, in agreement with our in vitro results. In summary, our study provides the cellular mechanism that links the OXTR rs4686302 SNP with genetic dysregulations associated with aspects of ASD.

Machine Learning-Based Modeling of Olfactory Receptors in Their Inactive State: Human OR51E2 as a Case Study.

Atomistic-level investigation of olfactory receptors (ORs) is a challenging task due to the experimental/computational difficulties in the structural determination/prediction for members of this family of G-protein coupled receptors. Here, we have developed a protocol that performs a series of molecular dynamics simulations from a set of structures predicted de novo by recent machine learning algorithms and apply it to a well-studied receptor, the human OR51E2. Our study demonstrates the need for simulations to refine and validate such models. Furthermore, we demonstrate the need for the sodium ion at a binding site near D2.50 and E3.39 to stabilize the inactive state of the receptor. Considering the conservation of these two acidic residues across human ORs, we surmise this requirement also applies to the other ∼400 members of this family. Given the almost concurrent publication of a CryoEM structure of the same receptor in the active state, we propose this protocol as an in silico complement to the growing field of ORs structure determination.

Low Molecular Weight Inhibitors Targeting the RNA-Binding Protein HuR.

The RNA-binding protein human antigen R (HuR) regulates stability, translation, and nucleus-to-cytoplasm shuttling of its target mRNAs. This protein has been progressively recognized as a relevant therapeutic target for several pathologies, like cancer, neurodegeneration, as well as inflammation. Inhibitors of mRNA binding to HuR might thus be beneficial against a variety of diseases. Here, we present the rational identification of structurally novel HuR inhibitors. In particular, by combining chemoinformatic approaches, high-throughput virtual screening, and RNA-protein pulldown assays, we demonstrate that the 4-(2-(2,4,6-trioxotetrahydropyrimidin-5(2H)-ylidene)hydrazineyl)benzoate ligand exhibits a dose-dependent HuR inhibition effect in binding experiments. Importantly, the chemical scaffold is new with respect to the currently known HuR inhibitors, opening up a new avenue for the design of pharmaceutical agents targeting this important protein.

Fluoride Transport and Inhibition Across CLC Transporters.

The Chloride Channel (CLC) family includes proton-coupled chloride and fluoride transporters. Despite their similar protein architecture, the former exchange two chloride ions for each proton and are inhibited by fluoride, whereas the latter efficiently transport one fluoride in exchange for one proton. The combination of structural, mutagenesis, and functional experiments with molecular simulations has pinpointed several amino acid changes in the permeation pathway that capitalize on the different chemical properties of chloride and fluoride to fine-tune protein function. Here we summarize recent findings on fluoride inhibition and transport in the two prototypical members of the CLC family, the chloride/proton transporter from Escherichia coli (CLC-ec1) and the fluoride/proton transporter from Enterococcus casseliflavus (CLCF-eca).

Robust principal component analysis-based prediction of protein-protein interaction hot spots.

Proteins often exert their function by binding to other cellular partners. The hot spots are key residues for protein-protein binding. Their identification may shed light on the impact of disease associated mutations on protein complexes and help design protein-protein interaction inhibitors for therapy. Unfortunately, current machine learning methods to predict hot spots, suffer from limitations caused by gross errors in the data matrices. Here, we present a novel data pre-processing pipeline that overcomes this problem by recovering a low rank matrix with reduced noise using Robust Principal Component Analysis. Application to existing databases shows the predictive power of the method.

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

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.

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.

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.

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.

Oxazoline or Oxazolinium Ion? The Protonation State and Conformation of the Reaction Intermediate of Chitinase Enzymes Revisited.

The enzymatic hydrolysis of chitin, one of the most abundant carbohydrates in nature, is achieved by chitinases, enzymes of increasing importance in biomedicine and industry. Unlike most retaining glycosidases, family GH18 chitinases follow a substrate-assisted mechanism in which the 2-acetamido group of one N-acetylglucosamine monomer, rather than a basic residue of the enzyme, reacts with the sugar anomeric carbon, forming an intermediate that has been described as an oxazolinium ion. Based on QM/MM metadynamics simulations on chitinase B from Serratia marcescens, we show that the reaction intermediate of GH18 chitinases features instead a neutral oxazoline in a 4 C1 /4 H5 conformation, with an oxazolinium ion being formed on the pathway towards the reaction products. The role of a well-defined hydrogen-bond network that operates around the N-acetyl group, orchestrating catalysis by protonation events, is discussed.

High-resolution structures of the M2 channel from influenza A virus reveal dynamic pathways for proton stabilization and transduction.

The matrix 2 (M2) protein from influenza A virus is a proton channel that uses His37 as a selectivity filter. Here we report high-resolution (1.10 Å) cryogenic crystallographic structures of the transmembrane domain of M2 at low and high pH. These structures reveal that waters within the pore form hydrogen-bonded networks or "water wires" spanning 17 Å from the channel entrance to His37. Pore-lining carbonyl groups are well situated to stabilize hydronium via second-shell interactions involving bridging water molecules. In addition, room temperature crystallographic structures indicate that water becomes increasingly fluid with increasing temperature and decreasing pH, despite the higher electrostatic field. Complementary molecular dynamics simulations reveal a collective switch of hydrogen bond orientations that can contribute to the directionality of proton flux as His37 is dynamically protonated and deprotonated in the conduction cycle.

Catalytic metal ions and enzymatic processing of DNA and RNA.

CONSPECTUS: Two-metal-ion-dependent nucleases cleave the phosphodiester bonds of nucleic acids via the two-metal-ion (2M) mechanism. Several high-resolution X-ray structures portraying the two-metal-aided catalytic site, together with mutagenesis and kinetics studies, have demonstrated a functional role of the ions for catalysis in numerous metallonucleases. Overall, the experimental data confirm the general mechanistic hypothesis for 2M-aided phosphoryl transfer originally reported by Steitz and Steitz ( Proc. Natl. Acad. Sci. U.S.A. 1993 , 90 ( 14 ), 6498 - 6502 ). This seminal paper proposed that one metal ion favors the formation of the nucleophile, while the nearby second metal ion facilitates leaving group departure during RNA hydrolysis. Both metals were suggested to stabilize the enzymatic transition state. Nevertheless, static X-ray structures alone cannot exhaustively unravel how the two ions execute their functional role along the enzymatic reaction during processing of DNA or RNA strands when moving from reactants to products, passing through metastable intermediates and high-energy transition states. In this Account, we discuss the role of multiscale molecular simulations in further disclosing mechanistic insights of 2M-aided catalysis for two prototypical enzymatic targets for drug discovery, namely, ribonuclease H (RNase H) and type II topoisomerase (topoII). In both examples, first-principles molecular simulations, integrated with structural data, emphasize a cooperative motion of the bimetal motif during catalysis. The coordinated motion of both ions is crucial for maintaining a flexible metal-centered structural architecture exquisitely tailored to accommodate the DNA or RNA sugar-phosphate backbone during phosphodiester bond cleavage. Furthermore, our analysis of RNase H and the N-terminal domain (PAN) of influenza polymerase shows that classical molecular dynamics simulations coupled with enhanced sampling techniques have contributed to describe the modulatory effect of metal ion concentration and metal uptake on the 2M mechanism and efficiency. These aspects all point to the emerging and intriguing role of additional adjacent ions potentially involved in the modulation of phosphoryl transfer reactions and enzymatic turnover in 2M-catalysis, as recently observed experimentally in polymerase η and homing endonuclease I-DmoI. These computational results, integrated with experimental findings, describe and reinforce the nascent concept of a functional and cooperative dynamics of the catalytic metal ions during the 2M-dependent enzymatic processing of DNA and RNA. Encouraged by the insights provided by computational approaches, we foresee further experiments that will feature the functional and joint dynamics of the catalytic metal ions for nucleic acid processing. This could impact the de novo design of artificial metallonucleases and the rational design of potent metal-chelating inhibitors of pharmaceutically relevant enzymes.

An integrated biological approach to guide the development of metal-chelating inhibitors of influenza virus PA endonuclease.

The influenza virus PA endonuclease, which cleaves capped cellular pre-mRNAs to prime viral mRNA synthesis, is a promising target for novel anti-influenza virus therapeutics. The catalytic center of this enzyme resides in the N-terminal part of PA (PA-Nter) and contains two (or possibly one or three) Mg(2+) or Mn(2+) ions, which are critical for its catalytic function. There is great interest in PA inhibitors that are optimally designed to occupy the active site and chelate the metal ions. We focused here on a series of ß-diketo acid (DKA) and DKA-bioisosteric compounds containing different scaffolds, and determined their structure-activity relationship in an enzymatic assay with PA-Nter, in order to build a three-dimensional pharmacophore model. In addition, we developed a molecular beacon (MB)-based PA-Nter assay that enabled us to compare the inhibition of Mn(2+) versus Mg(2+), the latter probably being the biologically relevant cofactor. This real-time MB assay allowed us to measure the enzyme kinetics of PA-Nter or perform high-throughput screening. Several DKA derivatives were found to cause strong inhibition of PA-Nter, with IC50 values comparable to that of the prototype L-742,001 (i.e., below 2 µM). Among the different compounds tested, L-742,001 appeared unique in having equal activity against either Mg(2+) or Mn(2+). Three compounds ( 10: , with a pyrrole scaffold, and 40: and 41: , with an indole scaffold) exhibited moderate antiviral activity in cell culture (EC99 values 64-95 µM) and were proven to affect viral RNA synthesis. Our approach of integrating complementary enzymatic, cellular, and mechanistic assays should guide ongoing development of improved influenza virus PA inhibitors.

Combined computational and experimental analysis of a complex of ribonuclease III and the regulatory macrodomain protein, YmdB.

Ribonuclease III is a conserved bacterial endonuclease that cleaves double-stranded(ds) structures in diverse coding and noncoding RNAs. RNase III is subject to multiple levels of control that in turn confer global post-transcriptional regulation. The Escherichia coli macrodomain protein YmdB directly interacts with RNase III, and an increase in YmdB amount in vivo correlates with a reduction in RNase III activity. Here, a computational-based structural analysis was performed to identify atomic-level features of the YmdB-RNase III interaction. The docking of monomeric E. coli YmdB with a homology model of the E. coli RNase III homodimer yields a complex that exhibits an interaction of the conserved YmdB residue R40 with specific RNase III residues at the subunit interface. Surface Plasmon Resonance (SPR) analysis provided a KD of 61 nM for the complex, corresponding to a binding free energy (ΔG) of -9.9 kcal/mol. YmdB R40 and RNase III D128 were identified by in silico alanine mutagenesis as thermodynamically important interacting partners. Consistent with the prediction, the YmdB R40A mutation causes a 16-fold increase in K(D) (ΔΔG = +1.8 kcal/mol), as measured by SPR, and the D128A mutation in both RNase III subunits (D128A/D128'A) causes an 83-fold increase in KD (ΔΔG = +2.7 kcal/mol). The greater effect of the D128A/D128'A mutation may reflect an altered RNase III secondary structure, as revealed by CD spectroscopy, which also may explain the significant reduction in catalytic activity in vitro. The features of the modeled complex relevant to potential RNase III regulatory mechanisms are discussed.

The Molecular Mechanism of the Catalase-like Activity in Horseradish Peroxidase.

Horseradish peroxidase (HRP) is one of the most relevant peroxidase enzymes, used extensively in immunochemistry and biocatalysis applications. Unlike the closely related catalase enzymes, it exhibits a low activity to disproportionate hydrogen peroxide (H2O2). The origin of this disparity remains unknown due to the lack of atomistic information on the catalase-like reaction in HRP. Using QM(DFT)/MM metadynamics simulations, we uncover the mechanism for reduction of the HRP Compound I intermediate by H2O2 at atomic detail. The reaction begins with a hydrogen atom transfer, forming a peroxyl radical and a Compound II-like species. Reorientation of the peroxyl radical in the active site, concomitant with the transfer of the second hydrogen atom, is the rate-limiting step, with a computed free energy barrier (18.7 kcal/mol, ∼ 6 kcal/mol higher than the one obtained for catalase) in good agreement with experiments. Our simulations reveal the crucial role played by the distal pocket residues in accommodating H2O2, enabling formation of a Compound II-like intermediate, similar to catalases. However, out of the two pathways for Compound II reduction found in catalases, only one is operative in HRP. Moreover, the hydrogen bond network in the distal side of HRP compensates less efficiently than in catalases for the energetic cost required to reorient the peroxyl radical at the rate-determining step. The distal Arg and a water molecule in the "wet" active site of HRP have a substantial impact on the reaction barrier, compared to the "dry" active site in catalase. Therefore, the lower catalase-like efficiency of heme peroxidases compared to catalases can be directly attributed to the different distal pocket architecture, providing hints to engineer peroxidases with a higher rate of H2O2 disproportionation.

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.

Fluoride permeation mechanism of the Fluc channel in liposomes revealed by solid-state NMR.

Solid-state nuclear magnetic resonance (ssNMR) methods can probe the motions of membrane proteins in liposomes at the atomic level and propel the understanding of biomolecular processes for which static structures cannot provide a satisfactory description. In this work, we report our study on the fluoride channel Fluc-Ec1 in phospholipid bilayers based on ssNMR and molecular dynamics simulations. Previously unidentified fluoride binding sites in the aqueous vestibules were experimentally verified by 19F-detected ssNMR. One of the two fluoride binding sites in the polar track was identified as a water molecule by 1H-detected ssNMR. Meanwhile, a dynamic hotspot at loop 1 was observed by comparing the spectra of wild-type Fluc-Ec1 in variant buffer conditions or with its mutants. Therefore, we propose that fluoride conduction in the Fluc channel occurs via a "water-mediated knock-on" permeation mechanism and that loop 1 is a key molecular determinant for channel gating.

Neprilysin-dependent neuropeptide Y cleavage in the liver promotes fibrosis by blocking NPY-receptor 1.

Development of liver fibrosis is paralleled by contraction of hepatic stellate cells (HSCs), the main profibrotic hepatic cells. Yet, little is known about the interplay of neprilysin (NEP) and its substrate neuropeptide Y (NPY), a potent enhancer of contraction, in liver fibrosis. We demonstrate that HSCs are the source of NEP. Importantly, NPY originates majorly from the splanchnic region and is cleaved by NEP in order to terminate contraction. Interestingly, NEP deficiency (Nep-/-) showed less fibrosis but portal hypertension upon liver injury in two different fibrosis models in mice. We demonstrate the incremental benefit of Nep-/- in addition to AT1R blocker (ARB) or ACE inhibitors for fibrosis and portal hypertension. Finally, oral administration of Entresto, a combination of ARB and NEP inhibitor, decreased hepatic fibrosis and portal pressure in mice. These results provide a mechanistic rationale for translation of NEP-AT1R-blockade in human liver fibrosis and portal hypertension.