Search

RNA-protein interactions play an important regulatory role in several biological processes. For example, the RNA-binding protein HuR (human antigen R) binds to its target mRNAs and regulates their translation, stability, and subcellular localization. HuR is involved in the pathogenic processes of various diseases. Thus, small molecules blocking RNA-binding of HuR may be useful in a variety of diseases. Previously, we identified STK018404 as a small molecule targeting the HuR-RNA interaction. Based on this study we identified optimized compounds by exploiting combined structure-based and ligand-based computational approaches. To test a series of these compounds, we developed a novel readout system for the HuR-RNA interaction. Traditional methods to detect RNA-protein interaction come with some disadvantages: they require significant reagent optimization and may be difficult to optimize for weakly expressed RNA molecules. The readout often requires amplification. Thus, these methods are not well suited for quantitative analysis of RNA-protein interactions. To achieve an easy-to-perform, rapid, and robust detection of RNA-protein binding, we applied a split luciferase reporter system, to detect the interaction between HuR and its target RNA. We expressed one luciferase fragment as a fusion protein with HuR. The second luciferase fragment was Streptavidin-coated and coupled to a biotinylated RNA-oligo comprising an AU-rich HuR-binding element. The binding between HuR and its target RNA-oligo then allowed reconstitution of the functional luciferase that was detectable by luminescence. Using the split luciferase reporter system, we present here a series of optimized compounds that we developed.

Marjault et al. report two crystal structures of a drug molecule bound to NEET proteins mNT and NAF-1 and the effects of this molecule on diabetic mice, suggesting an approach for reducing mitochondrial iron and ROS levels in diabetic patients.

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.

The seamless integration of human disease-related mutation data into protein structures is an essential component of any attempt to correctly assess the impact of the mutation. The key step preliminary to any structural modelling is the identification of the isoforms onto which mutations should be mapped due to there being several functionally different protein isoforms from the same gene. To handle large sets of data coming from omics techniques, this challenging task needs to be automatized. Here we present the MoNvIso (Modelling eNvironment for Isoforms) code, which identifies the most useful isoform for computational modelling, balancing the coverage of mutations of interest and the availability of templates to build a structural model of both the wild-type isoform and the related variants.

Abstract Objectives Genetic variant classification is a challenge in rare adult‐onset disorders as in SCA‐PRKCG (prior spinocerebellar ataxia type 14) with mostly private conventional mutations and nonspecific phenotype. We here propose a refined approach for clinicogenetic diagnosis by including protein modeling and provide for confirmed SCA‐PRKCG a comprehensive phenotype description from a German multi‐center cohort, including standardized 3D MR imaging. Methods This cross‐sectional study prospectively obtained neurological, neuropsychological, and brain imaging data in 33 PRKCG variant carriers. Protein modeling was added as a classification criterion in variants of uncertain significance (VUS). Results Our sample included 25 cases confirmed as SCA‐PRKCG (14 variants, thereof seven novel variants) and eight carriers of variants assigned as VUS (four variants) or benign/likely benign (two variants). Phenotype in SCA‐PRKCG included slowly progressive ataxia (onset at 4–50 years), preceded in some by early‐onset nonprogressive symptoms. Ataxia was often combined with action myoclonus, dystonia, or mild cognitive‐affective disturbance. Inspection of brain MRI revealed nonprogressive cerebellar atrophy. As a novel finding, a previously not described T2 hyperintense dentate nucleus was seen in all SCA‐PRKCG cases but in none of the controls. Interpretation In this largest cohort to date, SCA‐PRKCG was characterized as a slowly progressive cerebellar syndrome with some clinical and imaging features suggestive of a developmental disorder. The observed non‐ataxia movement disorders and cognitive‐affective disturbance may well be attributed to cerebellar pathology. Protein modeling emerged as a valuable diagnostic tool for variant classification and the newly described T2 hyperintense dentate sign could serve as a supportive diagnostic marker of SCA‐PRKCG.

The dissociation rate (koff) associated with ligand unbinding events from proteins is a parameter of fundamental importance in drug design. Here we review recent major advancements in molecular simulation methodologies for the prediction of koff. Next, we discuss the impact of the potential energy function models on the accuracy of calculated koff values. Finally, we provide a perspective from high-performance computing and machine learning which might help improve such predictions.

Human NEET proteins, such as NAF-1 and mitoNEET, are homodimeric, redox iron-sulfur proteins characterized by triple cysteine and one histidine-coordinated [2Fe-2S] cluster. They exist in an oxidized and reduced state. Abnormal release of the cluster is implicated in a variety of diseases, including cancer and neurodegeneration. The computer-aided and structure-based design of ligands affecting cluster release is of paramount importance from a pharmaceutical perspective. Unfortunately, experimental structural information so far is limited to only one ligand/protein complex. This is the X-ray structure of furosemide bound to oxidized mitoNEET. Here we employ an enhanced sampling approach, Localized Volume-based Metadynamics, developed by some of us, to identify binding poses of furosemide to human mitoNEET protein in solution. The binding modes show a high variability within the same shallow binding pocket on the protein surface identified in the X-ray structure. Among the different binding conformations, one of them is in agreement with the crystal structure’s one. This conformation might have been overstabilized in the latter because of the presence of crystal packing interactions, absent in solution. The calculated binding affinity is compatible with experimental data. Our protocol can be used in a straightforward manner in drug design campaigns targeting this pharmaceutically important family of proteins.

We present an approach that, by integrating structural data with Direct Coupling Analysis, is able to pinpoint most of the interaction hotspots (i.e. key residues for the biological activity) across very sparse protein families in a single run. An application to the Class A G-protein coupled receptors (GPCRs), both in their active and inactive states, demonstrates the predictive power of our approach. The latter can be easily extended to any other kind of protein family, where it is expected to highlight most key sites involved in their functional activity.

Hybrid Molecular Mechanics/Coarse-Grained (MM/CG) simulations help predict ligand poses in human G protein-coupled receptors (hGPCRs), the most important protein superfamily for pharmacological applications. This approach allows the description of the ligand, the binding cavity, and the surrounding water molecules at atomistic resolution, while coarse-graining the rest of the receptor. Here, we present the Hybrid MM/CG Webserver (mmcg.grs.kfa-juelich.de) that automatizes and speeds up the MM/CG simulation setup of hGPCR/ligand complexes. Initial structures for such complexes can be easily and efficiently generated with other webservers. The Hybrid MM/CG server also allows for equilibration of the systems, either fully automatically or interactively. The results are visualized online (using both interactive 3D visualizations and analysis plots), helping the user identify possible issues and modify the setup parameters accordingly. Furthermore, the prepared system can be downloaded and the simulation continued locally.

Abstract Proton diffusion along biological membranes is vitally important for cellular energetics. Here we extended previous time-resolved fluorescence measurements to study the time and temperature dependence of surface proton transport. We determined the Gibbs activation energy barrier ΔG ‡ r that opposes proton surface-to-bulk release from Arrhenius plots of (i) protons’ surface diffusion constant and (ii) the rate coefficient for proton surface-to-bulk release. The large size of ΔG ‡ r disproves that quasi-equilibrium exists in our experiments between protons in the near-membrane layers and in the aqueous bulk. Instead, non-equilibrium kinetics describes the proton travel between the site of its photo-release and its arrival at a distant membrane patch at different temperatures. ΔG ‡ r contains only a minor enthalpic contribution that roughly corresponds to the breakage of a single hydrogen bond. Thus, our experiments reveal an entropic trap that ensures channeling of highly mobile protons along the membrane interface in the absence of potent acceptors.

PIN1 is a promising therapeutic target for cancer treatment. In this study, the authors identify a covalent inhibitor of PIN1 with anti-tumour and anti-metastatic properties thanks to PIN1 inactivation and to the release, after binding to PIN1, of a quinone-mimicking compound that elicits reactive oxygen generation and causes DNA damage.

Long-term potentiation and depression of synaptic activity in response to stimuli is a key factor in reinforcement learning. Strengthening of the corticostriatal synapses depends on the second messenger cAMP, whose synthesis is catalysed by the enzyme adenylyl cyclase 5 (AC5), which is itself regulated by the stimulatory Gαolf and inhibitory Gαi proteins. AC isoforms have been suggested to act as coincidence detectors, promoting cellular responses only when convergent regulatory signals occur close in time. However, the mechanism for this is currently unclear, and seems to lie in their diverse regulation patterns. Despite attempts to isolate the ternary complex, it is not known if Gαolf and Gαi can bind to AC5 simultaneously, nor what activity the complex would have. Using protein structure-based molecular dynamics simulations, we show that this complex is stable and inactive. These simulations, along with Brownian dynamics simulations to estimate protein association rates constants, constrain a kinetic model that shows that the presence of this ternary inactive complex is crucial for AC5's ability to detect coincident signals, producing a synergistic increase in cAMP. These results reveal some of the prerequisites for corticostriatal synaptic plasticity, and explain recent experimental data on cAMP concentrations following receptor activation. Moreover, they provide insights into the regulatory mechanisms that control signal processing by different AC isoforms.

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.

Aberrant RNA–protein complexes are formed in a variety of diseases. Identifying the ligands that interfere with their formation is a valuable therapeutic strategy. Molecular simulation, validated against experimental data, has recently emerged as a powerful tool to predict both the pose and energetics of such ligands. Thus, the use of molecular simulation may provide insight into aberrant molecular interactions in diseases and, from a drug design perspective, may allow for the employment of less wet lab resources than traditional in vitro compound screening approaches. With regard to basic research questions, molecular simulation can support the understanding of the exact molecular interaction and binding mode. Here, we focus on examples targeting RNA–protein complexes in neurodegenerative diseases and viral infections. These examples illustrate that the strategy is rather general and could be applied to different pharmacologically relevant approaches. We close this study by outlining one of these approaches, namely the light-controllable association of small molecules with RNA, as an emerging approach in RNA-targeting therapy.

Human bitter taste receptors (hTAS2Rs) are the second largest group of chemosensory G-protein coupled receptors (25 members). hTAS2Rs are expressed in many tissues (e.g. tongue, gastrointestinal tract, respiratory system, brain, etc.), performing a variety of functions, from bitter taste perception to hormone secretion and bronchodilation. Due to the lack of experimental structural information, computations are currently the methods of choice to get insights into ligand–receptor interactions. Here we review our efforts at predicting the binding pose of agonists to hTAS2Rs, using state-of-the-art bioinformatics approaches followed by hybrid Molecular Mechanics/Coarse-Grained (MM/CG) simulations. The latter method, developed by us, describes atomistically only the agonist binding region, including hydration, and it may be particularly suited to be used when bioinformatics predictions generate very low-resolution models, such as the case of hTAS2Rs. Our structural predictions of the hTAS2R38 and hTAS2R46 receptors in complex with their agonists turn out to be fully consistent with experimental mutagenesis data. In addition, they suggest a two-binding site architecture in hTAS2R46, consisting of the usual orthosteric site together with a “vestibular” site toward the extracellular space, as observed in other GPCRs. The presence of the vestibular site may help to discriminate among the wide spectrum of bitter ligands.

The translocator protein (TSPO) is a 18kDa transmembrane protein, ubiquitously present in human mitochondria. It is overexpressed in tumor cells and at the sites of neuroinflammation, thus representing an important biomarker, as well as a promising drug target. In mammalian TSPO, there are cholesterol–binding motifs, as well as a binding cavity able to accommodate different chemical compounds. Given the lack of structural information for the human protein, we built a model of human (h) TSPO in the apo state and in complex with PK11195, a molecule routinely used in positron emission tomography (PET) for imaging of neuroinflammatory sites. To better understand the interactions of PK11195 and cholesterol with this pharmacologically relevant protein, we ran molecular dynamics simulations of the apo and holo proteins embedded in a model membrane. We found that: (i) PK11195 stabilizes hTSPO structural fold; (ii) PK11195 might enter in the binding site through transmembrane helices I and II of hTSPO; (iii) PK11195 reduces the frequency of cholesterol binding to the lower, N–terminal part of hTSPO in the inner membrane leaflet, while this impact is less pronounced for the upper, C–terminal part in the outer membrane leaflet, where the ligand binding site is located; (iv) very interestingly, cholesterol most frequently binds simultaneously to the so-called CRAC and CARC regions in TM V in the free form (residues L150–X–Y152–X(3)–R156 and R135–X(2)–Y138–X(2)–L141, respectively). However, when the protein is in complex with PK11195, cholesterol binds equally frequently to the CRAC–resembling motif that we observed in TM I (residues L17–X(2)–F20–X(3)–R24) and to CRAC in TM V. We expect that the CRAC–like motif in TM I will be of interest in future experimental investigations. Thus, our MD simulations provide insight into the structural features of hTSPO and the previously unknown interplay between PK11195 and cholesterol interactions with this pharmacologically relevant protein.

The translocator protein (TSPO) is a transmembrane protein present across the three domains of life. Its functional quaternary structure consists of one or more subunits. In mice, the dimer-to-monomer equilibrium is shifted in vitro towards the monomer by adding cholesterol, a natural component of mammalian membranes. Here, we present a coarse-grained molecular dynamics study on the mouse protein in the presence of a physiological content and of an excess of cholesterol. The latter turns out to weaken the interfaces of the dimer by clusterizing mostly at the inter-monomeric space and pushing the contact residues apart. It also increases the compactness and the rigidity of the monomer. These two factors might play a role for the experimentally observed incremented stability of the monomeric form with increased content of cholesterol. Comparison with simulations on bacterial proteins suggests that the effect of cholesterol is much less pronounced for the latter than for the mouse protein.

The RNA recognition motif (RRM) is the most common RNA binding domain across eukaryotic proteins. It is therefore of great value to engineer its specificity to target RNAs of arbitrary sequence. This was recently achieved for the RRM in Rbfox protein, where four mutations R118D, E147R, N151S, and E152T were designed to target the precursor to the oncogenic miRNA 21. Here, we used a variety of molecular dynamics-based approaches to predict specific interactions at the binding interface. Overall, we have run approximately 50 microseconds of enhanced sampling and plain molecular dynamics simulations on the engineered complex as well as on the wild-type Rbfox·pre-miRNA 20b from which the mutated systems were designed. Comparison with the available NMR data on the wild type molecules (protein, RNA, and their complex) served to establish the accuracy of the calculations. Free energy calculations suggest that further improvements in affinity and selectivity are achieved by the S151T replacement.

Proton transport at water/membrane interfaces plays a fundamental role for a myriad of bioenergetic processes. Here we have performed ab initio molecular dynamics simulations of proton transfer along two phosphatidylcholine bilayers. As found in previous theoretical studies, the excess proton is preferably located at the water/membrane interface. Further, our simulations indicate that it interacts not only with phosphate head groups, but also with water molecules at the interfaces. Interfacial water molecules turn out to be oriented relative to the lipid bilayers, consistently with experimental evidence. Hence, the specific water-proton interaction may help explain the proton mobility experimentally observed at the membrane interface.

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.

G protein-coupled receptors (GPCRs) are the largest superfamily of signaling proteins. Their activation process is accompanied by conformational changes that have not yet been fully uncovered. Here, we carry out a novel comparative analysis of internal structural fluctuations across a variety of receptors from class A GPCRs, which currently has the richest structural coverage. We infer the local mechanical couplings underpinning the receptors' functional dynamics and finally identify those amino acids whose virtual deletion causes a significant softening of the mechanical network. The relevance of these amino acids is demonstrated by their overlap with those known to be crucial for GPCR function, based on static structural criteria. The differences with the latter set allow us to identify those sites whose functional role is more clearly detected by considering dynamical and mechanical properties. Of these sites with a genuine mechanical/dynamical character, the top ranking is amino acid 7x52, a previously unexplored, and experimentally verifiable key site for GPCR conformational response to ligand binding.

Copper is one of the metals described to bind the Parkinson disease-related protein α-synuclein (aSyn), and to promote its aggregation. Although histidine at position 50 in the aSyn sequence is one of the most studied copper-anchoring sites, its precise role in copper binding and aSyn aggregation is still unclear. Previous studies suggested that this residue does not significantly affect copper-mediated aSyn aggregation. However, our findings showed that the aggregation of the pathological H50Q aSyn mutant is enhanced by copper hints otherwise. Despite the inexistence of a model for aSyn H50Q-copper complexation, we discuss possible mechanisms by which this metal contributes to the misfolding and self-assembly of this particular aSyn mutant. Considering the genetic association of the H50Q mutation with familial forms of Parkinson disease, and the fact that copper homeostasis is deregulated in this disorder, understanding the interplay between both factors will shed light into the molecular and cellular mechanisms triggering the development and spreading of the aSyn pathology.

The binding between the HIV-1 trans-activator of transcription (Tat) and p300/(CREB-binding protein)-associated factor (PCAF) bromodomain is a crucial step in the HIV-1 life cycle. However, the structure of the full length acetylated Tat bound to PCAF has not been yet determined experimentally. Acetylation of Tat residues can play a critical role in enhancing HIV-1 transcriptional activation. Here, we have combined a fully flexible protein-protein docking approach with molecular dynamics simulations to predict the structural determinants of the complex for the common HIV-1BRU variant. This model reproduces all the crucial contacts between the Tat peptide 46SYGR(AcK)KRRQRC56 and the PCAF bromodomain previously reported by NMR spectroscopy. Additionally, inclusion of the entire Tat protein results in additional contact points at the protein-protein interface. The model is consistent with the available experimental data reported and adds novel information to our previous structural predictions of the PCAF bromodomain in complex with the rare HIVZ2 variant, which was obtained with a less accurate computational method. This improved characterization of Tat.PCAF bromodomain binding may help in defining the structural determinants of other protein interactions involving lysine acetylation.

Human G-protein coupled receptors (GPCRs) are important targets for pharmaceutical intervention against neurological diseases. Here, we use molecular simulation to investigate the key step in ligand recognition governed by the extracellular domains in the neuronal adenosine receptor type 2A (hA2AR), a target for neuroprotective compounds. The ligand is the high-affinity antagonist (4-(2-(7-amino-2-(furan-2-yl)-[1,2,4]triazolo[1,5-a][1,3,5]triazin-5-ylamino)ethyl)phenol), embedded in a neuronal membrane mimic environment. Free energy calculations, based on well-tempered metadynamics, reproduce the experimentally measured binding affinity. The results are consistent with the available mutagenesis studies. The calculations identify a vestibular binding site, where lipids molecules can actively participate to stabilize ligand binding. Bioinformatic analyses suggest that such vestibular binding site and, in particular, the second extracellular loop, might drive the ligand toward the orthosteric binding pocket, possibly by allosteric modulation. Taken together, these findings point to a fundamental role of the interaction between extracellular loops and membrane lipids for ligands’ molecular recognition and ligand design in hA2AR.

Atomistic descriptions of the μ-opioid receptor (μOR) noncovalently binding with two of its prototypical morphinan agonists, morphine (MOP) and hydromorphone (HMP), are investigated using molecular dynamics (MD) simulations. Subtle differences between the binding modes and hydration properties of MOP and HMP emerge from the calculations. Alchemical free energy perturbation calculations show qualitative agreement with in vitro experiments performed in this work: indeed, the binding free energy difference between MOP and HMP computed by forward and backward alchemical transformation is 1.2±1.1 and 0.8±0.8 kcal/mol, respectively, to be compared with 0.4±0.3 kcal/mol from experiment. Comparison with an MD simulation of μOR covalently bound with the antagonist β-funaltrexamine hints to agonist-induced conformational changes associated with an early event of the receptor's activation: a shift of the transmembrane helix 6 relative to the transmembrane helix 3 and a consequent loss of the key R165-T279 interhelical hydrogen bond. This finding is consistent with a previous proposal suggesting that the R165-T279 hydrogen bond between these two helices indicates an inactive receptor conformation.

Cation selective channels constitute the gate for ion currents through the cell membrane. Here we present an improved statistical mechanical model based on atomistic structural information, cation hydration state and without tuned parameters that reproduces the selectivity of biological Na+ and Ca2+ ion channels. The importance of the inclusion of step-wise cation hydration in these results confirms the essential role partial dehydration plays in the bacterial Na+ channels. The model, proven reliable against experimental data, could be straightforwardly used for designing Na+ and Ca2+ selective nanopores.

Sirtuin 2 (SIRT2) is a NAD+-dependent deacetylase that has been associated with neurodegeneration and cancer. SIRT2 is composed of a central catalytic domain, the structure of which has been solved, and N- and C-terminal extensions that are thought to control SIRT2 function. However structural information of these N- and C-terminal regions is missing. Here, we provide the first full-length molecular models of SIRT2 in the absence and presence of NAD+. We also predict the structural alterations associated with phosphorylation of SIRT2 at S331, a modification that inhibits catalytic activity. Bioinformatics tools and molecular dynamics simulations, complemented by in vitro deacetylation assays, provide a consistent picture based on which the C-terminal region of SIRT2 is suggested to function as an autoinhibitory region. This has the capacity to partially occlude the NAD+ binding pocket or stabilize the NAD+ in a non-productive state. Furthermore, our simulations suggest that the phosphorylation at S331 causes large conformational changes in the C-terminal region that enhance the autoinhibitory activity, consistent with our previous findings that phosphorylation of S331 by cyclin-dependent kinases inhibits SIRT2 catalytic activity. The molecular insight into the role of the C-terminal region in controlling SIRT2 function described in this study may be useful for future design of selective inhibitors targeting SIRT2 for therapeutic applications.

Protein electrospray ionization (ESI) mass spectrometry (MS)-based techniques are widely used to provide insight into structural proteomics under the assumption that non-covalent protein complexes being transferred into the gas phase preserve basically the same intermolecular interactions as in solution. Here we investigate the applicability of this assumption by extending our previous structural prediction protocol for single proteins in ESI-MS to protein complexes. We apply our protocol to the human insulin dimer (hIns2) as a test case. Our calculations reproduce the main charge and the collision cross section (CCS) measured in ESI-MS experiments. Molecular dynamics simulations for 0.075 ms show that the complex maximizes intermolecular non-bonded interactions relative to the structure in water, without affecting the cross section. The overall gas-phase structure of hIns2 does exhibit differences with the one in aqueous solution, not inferable from a comparison with calculated CCS. Hence, care should be exerted when interpreting ESI-MS proteomics data based solely on NMR and/or X-ray structural information.

Targeted human cytolytic fusion proteins (hCFPs) are humanized immunotoxins for selective treatment of different diseases including cancer. They are composed of a ligand specifically binding to target cells genetically linked to a human apoptosis-inducing enzyme. hCFPs target cancer cells via an antibody or derivative (scFv) specifically binding to e.g., tumor associated antigens (TAAs). After internalization and translocation of the enzyme from endocytosed endosomes, the human enzymes introduced into the cytosol are efficiently inducing apoptosis. Under in vivo conditions such enzymes are subject to tight regulation by native inhibitors in order to prevent inappropriate induction of cell death in healthy cells. Tumor cells are known to upregulate these inhibitors as a survival mechanism resulting in escape of malignant cells from elimination by immune effector cells. Cytosolic inhibitors of Granzyme B and Angiogenin (Serpin P9 and RNH1, respectively), reduce the efficacy of hCFPs with these enzymes as effector domains, requiring detrimentally high doses in order to saturate inhibitor binding and rescue cytolytic activity. Variants of Granzyme B and Angiogenin might feature reduced affinity for their respective inhibitors, while retaining or even enhancing their catalytic activity. A powerful tool to design hCFPs mutants with improved potency is given by in silico methods. These include molecular dynamics (MD) simulations and enhanced sampling methods (ESM). MD and ESM allow predicting the enzyme-protein inhibitor binding stability and the associated conformational changes, provided that structural information is available. Such “high-resolution” detailed description enables the elucidation of interaction domains and the identification of sites where particular point mutations may modify those interactions. This review discusses recent advances in the use of MD and ESM for hCFP development from the viewpoints of scientists involved in both fields.

G-protein coupled receptors (GPCRs) are a superfamily of cell signaling membrane proteins that include >750 members in the human genome alone. They are the largest family of drug targets. The vast diversity and relevance of GPCRs contrasts with the paucity of structures available: only 21 unique GPCR structures have been experimentally determined as of the beginning of 2013. User-friendly modeling and small molecule docking tools are thus in great demand. While both GPCR structural predictions and docking servers exist separately, with GOMoDo (GPCR Online Modeling and Docking), we provide a web server to seamlessly model GPCR structures and dock ligands to the models in a single consistent pipeline. GOMoDo can automatically perform template choice, homology modeling and either blind or information-driven docking by combining together proven, state of the art bioinformatic tools. The web server gives the user the possibility of guiding the whole procedure. The GOMoDo server is freely accessible at http://molsim.sci.univr.it/gomodo.

Bitter molecules in humans are detected by ∼25 G protein-coupled receptors (GPCRs). The lack of atomic resolution structure for any of them is complicating an in depth understanding of the molecular mechanisms underlying bitter taste perception. Here, we investigate the molecular determinants of the interaction of the TAS2R38 bitter taste receptor with its agonists phenylthiocarbamide (PTC) and propylthiouracil (PROP). We use the recently developed hybrid Molecular Mechanics/Coarse Grained (MM/CG) method tailored specifically for GPCRs. The method, through an extensive exploration of the conformational space in the binding pocket, allows the identification of several residues important for agonist binding that would have been very difficult to capture from the standard bioinformatics/docking approach. Our calculations suggest that both agonists bind to Asn103, Phe197, Phe264 and Trp201, whilst they do not interact with the so-called extra cellular loop 2, involved in cis-retinal binding in the GPCR rhodopsin. These predictions are consistent with data sets based on more than 20 site-directed mutagenesis and functional calcium imaging experiments of TAS2R38. The method could be readily used for other GPCRs for which experimental information is currently lacking.

Understanding how ligands bind to G-protein coupled receptors (GPCRs) provides insights into a myriad of cell processes and is crucial for drug development. Here we extend a hybrid molecular mechanics/coarse-grained (MM/CG) approach applied previously to enzymes to GPCR/ligand complexes. The accuracy of this method for structural predictions is established by comparison with recent atomistic molecular dynamics simulations on the human β2 adrenergic receptor, a member of the GPCRs superfamily. The results obtained with the MM/CG methodology show a good agreement with previous all-atom classical dynamics simulations, in particular in the structural description of the ligand binding site. This approach could be used for high-throughput predictions of ligand poses in a variety of GPCRs.

Bacteria express beta-lactamases to counteract the beneficial action of antibiotics. Benzo[b]-thiophene-2-boronic acid (BZB) derivatives are β-lactamase inhibitors and, as such, promising compounds to be associated with β-lactam antibacterial therapies. The uncharged form of BZB, in particular, is suggested to diffuse through the outer membrane of gram negative bacteria. In this study, through the combination of electrophysiological experiments across reconstituted PC/n-decane bilayers and metadynamics-based free energy calculations, we investigate the permeation mechanism of boronic compounds. Our experimental data establish that BZB passes through the membrane, while computer simulations provide hints for the existence of an aqueous, water-filled monomolecular channel. These findings provide new perspectives for the design of boronic acid derivatives with high membrane permeability.

Humans' bitter taste perception is mediated by the hTAS2R subfamily of the G protein-coupled membrane receptors (GPCRs). Structural information on these receptors is currently limited. Here we identify residues involved in the binding of phenylthiocarbamide (PTC) and in receptor activation in one of the most widely studied hTAS2Rs (hTAS2R38) by means of structural bioinformatics and molecular docking. The predictions are validated by site-directed mutagenesis experiments that involve specific residues located in the putative binding site and trans-membrane (TM) helices 6 and 7 putatively involved in receptor activation. Based on our measurements, we suggest that (i) residue N103 participates actively in PTC binding, in line with previous computational studies. (ii) W99, M100 and S259 contribute to define the size and shape of the binding cavity. (iii) W99 and M100, along with F255 and V296, play a key role for receptor activation, providing insights on bitter taste receptor activation not emerging from the previously reported computational models.

Determining the total number of charged residues corresponding to a given value of net charge for peptides and proteins in gas phase is crucial for the interpretation of mass-spectrometry data, yet it is far from being understood. Here we show that a novel computational protocol based on force field and massive density functional calculations is able to reproduce the experimental facets of well investigated systems, such as angiotensin II, bradykinin, and tryptophan-cage. The protocol takes into account all of the possible protomers compatible with a given charge state. Our calculations predict that the low charge states are zwitterions, because the stabilization due to intramolecular hydrogen bonding and salt-bridges can compensate for the thermodynamic penalty deriving from deprotonation of acid residues. In contrast, high charge states may or may not be zwitterions because internal solvation might not compensate for the energy cost of charge separation.

The action of dopamine on the aggregation of the unstructured alpha-synuclein (alpha-syn) protein may be linked to the pathogenesis of Parkinson's disease. Dopamine and its oxidation derivatives may inhibit alpha-syn aggregation by non-covalent binding. Exploiting this fact, we applied an integrated computational and experimental approach to find alternative ligands that might modulate the fibrillization of alpha-syn. Ligands structurally and electrostatically similar to dopamine were screened from an established library. Five analogs were selected for in vitro experimentation from the similarity ranked list of analogs. Molecular dynamics simulations showed they were, like dopamine, binding non-covalently to alpha-syn and, although much weaker than dopamine, they shared some of its binding properties. In vitro fibrillization assays were performed on these five dopamine analogs. Consistent with our predictions, analyses by atomic force and transmission electron microscopy revealed that all of the selected ligands affected the aggregation process, albeit to a varying and lesser extent than dopamine, used as the control ligand. The in silico/in vitro approach presented here emerges as a possible strategy for identifying ligands interfering with such a complex process as the fibrillization of an unstructured protein.

Trans/cis prolyl isomerisation is involved in several biological processes, including the development of numerous diseases. In the HIV-1 capsid protein (CA), such a process takes place in the uncoating and recruitment of the virion and is catalyzed by cyclophilin A (CypA). Here, we use metadynamics simulations to investigate the isomerization of CA's model substrate HAGPIA in water and in its target protein CypA. Our results allow us to propose a novel mechanistic hypothesis, which is finally consistent with all of the available molecular biology data.

Bestrophins are a recently discovered family of Cl(-) channels, for which no structural information is available. Some family members are activated by increased intracellular Ca2+ concentration. Bestrophins feature a well conserved Asp-rich tract in their COOH terminus (Asp-rich domain), which is homologous to Ca2+-binding motifs in human thrombospondins and in human big-conductance Ca2+- and voltage-gated K+ channels (BK(Ca)). Consequently, the Asp-rich domain is also a candidate for Ca2+ binding in bestrophins. Based on these considerations, we constructed homology models of human bestrophin-1 (Best1) Asp-rich domain using human thrombospondin-1 X-ray structure as a template. Molecular dynamics simulations were used to identify Asp and Glu residues binding Ca2+ and to predict the effects of their mutations to alanine. We then proceeded to test selected mutations in the Asp-rich domain of the highly homologous mouse bestrophin-2. The mutants expressed in HEK-293 cells were investigated by electrophysiological experiments using the whole-cell voltage-clamp technique. Based on our molecular modeling results, we predicted that Asp-rich domain has two defined binding sites and that D301A and D304A mutations may impact the binding of the metal ions. The experiments confirmed that these mutations do actually affect the function of the protein causing a large decrease in the Ca2+-activated Cl(-) current, fully consistent with our predictions. In addition, other studied mutations (E306A, D312A) did not decrease Ca2+-activated Cl(-) current in agreement with modeling results.

The interplay between dopamine and alpha-synuclein (AS) plays a central role in Parkinson's disease (PD). PD results primarily from a severe and selective devastation of dopaminergic neurons in substantia nigra pars compacta. The neuropathological hallmark of the disease is the presence of intraneuronal proteinaceous inclusions known as Lewy bodies within the surviving neurons, enriched in filamentous AS. In vitro, dopamine inhibits AS fibril formation, but the molecular determinants of this inhibition remain obscure. Here we use molecular dynamic (MD) simulations to investigate the binding of dopamine and several of its derivatives onto conformers representative of an NMR ensemble of AS structures in aqueous solution. Within the limitations inherent to MD simulations of unstructured proteins, our calculations suggest that the ligands bind to the (125)YEMPS(129) region, consistent with experimental findings. The ligands are further stabilized by long-range electrostatic interactions with glutamate 83 (E83) in the NAC region. These results suggest that by forming these interactions with AS, dopamine may affect AS aggregation and fibrillization properties. To test this hypothesis, we investigated in vitro the effects of dopamine on the aggregation of mutants designed to alter or abolish these interactions. We found that point mutations in the (125)YEMPS(129) region do not affect AS aggregation, which is consistent with the fact that dopamine interacts non-specifically with this region. In contrast, and consistent with our modeling studies, the replacement of glutamate by alanine at position 83 (E83A) abolishes the ability of dopamine to inhibit AS fibrillization.