PyPCN: protein contact networks in PyMOL.

MOTIVATION: Protein contact networks (PCNs) represent the 3D structure of a protein using network formalism. Inter-residue contacts are described as binary adjacency matrices, which are derived from the graph representation of residues (as α-carbons, ß-carbons or centroids) and Euclidean distances according to defined thresholds. Functional characterization algorithms are computed on binary adjacency matrices to unveil allosteric, dynamic, and interaction mechanisms in proteins. Such strategies are usually applied in a combinatorial manner, although rarely in seamless and user-friendly implementations. RESULTS: PyPCN is a plugin for PyMOL wrapping more than twenty PCN algorithms and metrics in an easy-to-use graphical user interface, to support PCN analysis. The plugin accepts 3D structures from the Protein Data Bank, user-provided PDBs, or precomputed adjacency matrices. The results are directly mapped to 3D protein structures and organized into interactive diagrams for their visualization. A dedicated graphical user interface combined with PyMOL visual support makes analysis more intuitive and easier, extending the applicability of PCNs. AVAILABILITY AND IMPLEMENTATION: https://github.com/pcnproject/PyPCN.

PCN-Miner: an open-source extensible tool for the analysis of Protein Contact Networks.

MOTIVATION: Protein Contact Network (PCN) is a powerful method for analysing the structure and function of proteins, with a specific focus on disclosing the molecular features of allosteric regulation through the discovery of modular substructures. The importance of PCN analysis has been shown in many contexts, such as the analysis of SARS-CoV-2 Spike protein and its complexes with the Angiotensin Converting Enzyme 2 (ACE2) human receptors. Even if there exist many software tools implementing such methods, there is a growing need for the introduction of tools integrating existing approaches. RESULTS: We present PCN-Miner, a software tool implemented in the Python programming language, able to (i) import protein structures from the Protein Data Bank; (ii) generate the corresponding PCN; (iii) model, analyse and visualize PCNs and related protein structures by using a set of known algorithms and metrics. The PCN-Miner can cover a large set of applications: from clustering to embedding and subsequent analysis. AVAILABILITY AND IMPLEMENTATION: The PCN-Miner tool is freely available at the following GitHub repository: https://github.com/hguzzi/ProteinContactNetworks. It is also available in the Python Package Index (PyPI) repository.

A Statistical Journey through the Topological Determinants of the ß2 Adrenergic Receptor Dynamics.

Activation of G-protein-coupled receptors (GPCRs) is mediated by molecular switches throughout the transmembrane region of the receptor. In this work, we continued along the path of a previous computational study wherein energy transport in the ß2 Adrenergic Receptor (ß2-AR) was examined and allosteric switches were identified in the molecular structure through the reorganization of energy transport networks during activation. In this work, we further investigated the allosteric properties of ß2-AR, using Protein Contact Networks (PCNs). In this paper, we report an extensive statistical analysis of the topological and structural properties of ß2-AR along its molecular dynamics trajectory to identify the activation pattern of this molecular system. The results show a distinct character to the activation that both helps to understand the allosteric switching previously identified and confirms the relevance of the network formalism to uncover relevant functional features of protein molecules.

The Odd Faces of Oligomers: The Case of TRAF2-C, A Trimeric C-Terminal Domain of TNF Receptor-Associated Factor.

TNF Receptor Associated Factor 2 (TRAF2) is a trimeric protein that belongs to the TNF receptor associated factor family (TRAFs). The TRAF2 oligomeric state is crucial for receptor binding and for its interaction with other proteins involved in the TNFR signaling. The monomer-trimer equilibrium of a C- terminal domain truncated form of TRAF2 (TRAF2-C), plays also a relevant role in binding the membrane, causing inward vesiculation. In this study, we have investigated the conformational dynamics of TRAF2-C through circular dichroism, fluorescence, and dynamic light scattering, performing temperature-dependent measurements. The data indicate that the protein retains its oligomeric state and most of its secondary structure, while displaying a significative increase in the heterogeneity of the tyrosines signal, increasing the temperature from ≈15 to ≈35 °C. The peculiar crowding of tyrosine residues (12 out of 18) at the three subunit interfaces and the strong dependence on the trimer concentration indicate that such conformational changes mainly involve the contact areas between each pair of monomers, affecting the oligomeric state. Molecular dynamic simulations in this temperature range suggest that the interfaces heterogeneity is an intrinsic property of the trimer that arises from the continuous, asymmetric approaching and distancing of its subunits. Such dynamics affect the results of molecular docking on the external protein surface using receptor peptides, indicating that the TRAF2-receptor interaction in the solution might not involve three subunits at the same time, as suggested by the static analysis obtainable from the crystal structure. These findings shed new light on the role that the TRAF2 oligomeric state might have in regulating the protein binding activity in vivo.

The Discovery of a Putative Allosteric Site in the SARS-CoV-2 Spike Protein Using an Integrated Structural/Dynamic Approach.

SARS-CoV-2 has caused the largest pandemic of the twenty-first century (COVID-19), threatening the life and economy of all countries in the world. The identification of novel therapies and vaccines that can mitigate or control this global health threat is among the most important challenges facing biomedical sciences. To construct a long-term strategy to fight both SARS-CoV-2 and other possible future threats from coronaviruses, it is critical to understand the molecular mechanisms underlying the virus action. The viral entry and associated infectivity stems from the formation of the SARS-CoV-2 spike protein complex with angiotensin-converting enzyme 2 (ACE2). The detection of putative allosteric sites on the viral spike protein molecule can be used to elucidate the molecular pathways that can be targeted with allosteric drugs to weaken the spike-ACE2 interaction and, thus, reduce viral infectivity. In this study, we present the results of the application of different computational methods aimed at detecting allosteric sites on the SARS-CoV-2 spike protein. The adopted tools consisted of the protein contact networks (PCNs), SEPAS (Affinity by Flexibility), and perturbation response scanning (PRS) based on elastic network modes. All of these methods were applied to the ACE2 complex with both the SARS-CoV2 and SARS-CoV spike proteins. All of the adopted analyses converged toward a specific region (allosteric modulation region [AMR]), present in both complexes and predicted to act as an allosteric site modulating the binding of the spike protein with ACE2. Preliminary results on hepcidin (a molecule with strong structural and sequence with AMR) indicated an inhibitory effect on the binding affinity of the spike protein toward the ACE2 protein.

Fishery Wastes as a Yet Undiscovered Treasure from the Sea: Biomolecules Sources, Extraction Methods and Valorization.

The search for new biological sources of commercial value is a major goal for the sustainable management of natural resources. The huge amount of fishery by-catch or processing by-products continuously produced needs to be managed to avoid environmental problems and keep resource sustainability. Fishery by-products can represent an interesting source of high added value bioactive compounds, such as proteins, carbohydrates, collagen, polyunsaturated fatty acids, chitin, polyphenolic constituents, carotenoids, vitamins, alkaloids, tocopherols, tocotrienols, toxins; nevertheless, their biotechnological potential is still largely underutilized. Depending on their structural and functional characteristics, marine-derived biomolecules can find several applications in food industry, agriculture, biotechnological (chemical, industrial or environmental) fields. Fish internal organs are a rich and underexplored source of bioactive compounds; the fish gut microbiota biosynthesizes essential or short-chain fatty acids, vitamins, minerals or enzymes and is also a source of probiotic candidates, in turn producing bioactive compounds with antibiotic and biosurfactant/bioemulsifier activities. Chemical, enzymatic and/or microbial processing of fishery by-catch or processing by-products allows the production of different valuable bioactive compounds; to date, however, the lack of cost-effective extraction strategies so far has prevented their exploitation on a large scale. Standardization and optimization of extraction procedures are urgently required, as processing conditions can affect the qualitative and quantitative properties of these biomolecules. Valorization routes for such raw materials can provide a great additional value for companies involved in the field of bioprospecting. The present review aims at collecting current knowledge on fishery by-catch or by-products, exploring the valorization of their active biomolecules, in application of the circular economy paradigm applied to the fishery field. It will address specific issues from a biorefinery perspective: (i) fish tissues and organs as potential sources of metabolites, antibiotics and probiotics; (ii) screening for bioactive compounds; (iii) extraction processes and innovative technologies for purification and chemical characterization; (iv) energy production technologies for the exhausted biomass. We provide a general perspective on the techno-economic feasibility and the environmental footprint of the production process, as well as on the definition of legal constraints for the new products production and commercial use.

Auxin minimum triggers the developmental switch from cell division to cell differentiation in the Arabidopsis root.

In multicellular organisms, a stringent control of the transition between cell division and differentiation is crucial for correct tissue and organ development. In the Arabidopsis root, the boundary between dividing and differentiating cells is positioned by the antagonistic interaction of the hormones auxin and cytokinin. Cytokinin affects polar auxin transport, but how this impacts the positional information required to establish this tissue boundary, is still unknown. By combining computational modeling with molecular genetics, we show that boundary formation is dependent on cytokinin's control on auxin polar transport and degradation. The regulation of both processes shapes the auxin profile in a well-defined auxin minimum. This auxin minimum positions the boundary between dividing and differentiating cells, acting as a trigger for this developmental transition, thus controlling meristem size.

Cardiovascular Active Peptides of Marine Origin with ACE Inhibitory Activities: Potential Role as Anti-Hypertensive Drugs and in Prevention of SARS-CoV-2 Infection.

Growing interest in hypertension-one of the main factors characterizing the cardiometabolic syndrome (CMS)-and anti-hypertensive drugs raised from the emergence of a new coronavirus, SARS-CoV-2, responsible for the COVID19 pandemic. The virus SARS-CoV-2 employs the Angiotensin-converting enzyme 2 (ACE2), a component of the RAAS (Renin-Angiotensin-Aldosterone System) system, as a receptor for entry into the cells. Several classes of synthetic drugs are available for hypertension, rarely associated with severe or mild adverse effects. New natural compounds, such as peptides, might be useful to treat some hypertensive patients. The main feature of ACE inhibitory peptides is the location of the hydrophobic residue, usually Proline, at the C-terminus. Some already known bioactive peptides derived from marine resources have potential ACE inhibitory activity and can be considered therapeutic agents to treat hypertension. Peptides isolated from marine vertebrates, invertebrates, seaweeds, or sea microorganisms displayed important biological activities to treat hypertensive patients. Here, we reviewed the anti-hypertensive activities of bioactive molecules isolated/extracted from marine organisms and discussed the associated molecular mechanisms involved. We also examined ACE2 modulation in sight of SARS2-Cov infection prevention.

GH32 family activity: a topological approach through protein contact networks.

KEY MESSAGE: The application of Protein Contact Networks methodology allowed to highlight a novel response of border region between the two domains to substrate binding. Glycoside hydrolases (GH) are enzymes that mainly hydrolyze the glycosidic bond between two carbohydrates or a carbohydrate and a non-carbohydrate moiety. These enzymes are involved in many fundamental and diverse biological processes in plants. We have focused on the GH32 family, including enzymes very similar in both sequence and structure, each having however clear specificities of substrate preferences and kinetic properties. Structural and topological differences among proteins of the GH32 family have been here identified by means of an emerging approach (Protein Contact network, PCN) based on the formalization of 3D structures as contact networks among amino-acid residues. The PCN approach proved successful in both reconstructing the already known functional domains and in identifying the structural counterpart of the properties of GH32 enzymes, which remain uncertain, like their allosteric character. The main outcome of the study was the discovery of the activation upon binding of the border (cleft) region between the two domains. This reveals the allosteric nature of the enzymatic activity for all the analyzed forms in the GH32 family, a character yet to be highlighted in biochemical studies. Furthermore, we have been able to recognize a topological signature (graph energy) of the different affinity of the enzymes towards small and large substrates.

Modules identification in protein structures: the topological and geometrical solutions.

The identification of modules in protein structures has major relevance in structural biology, with consequences in protein stability and functional classification, adding new perspectives in drug design. In this work, we present the comparison between a topological (spectral clustering) and a geometrical (k-means) approach to module identification, in the frame of a multiscale analysis of the protein architecture principles. The global consistency of an adjacency matrix based technique (spectral clustering) and a method based on full rank geometrical information (k-means) give a proof-of-concept of the relevance of protein contact networks in structure determination. The peculiar "small-world" character of protein contact graphs is established as well, pointing to average shortest path as a mesoscopic crucial variable to maximize the efficiency of within-molecule signal transmission. The specific nature of protein architecture indicates topological approach as the most proper one to highlight protein functional domains, and two new representations linking sequence and topological role of aminoacids are demonstrated to be of use for protein structural analysis. Here we present a case study regarding azurin, a small copper protein implied in the Pseudomonas aeruginosa respiratory chain. Its pocket molecular shape and its electron transfer function have challenged the method, highlighting its potentiality to catch jointly the structure and function features of protein structures through their decomposition into modules.

Computational analysis of the sequence-structure relation in SARS-CoV-2 spike protein using protein contact networks.

The structure of proteins impacts directly on the function they perform. Mutations in the primary sequence can provoke structural changes with consequent modification of functional properties. SARS-CoV-2 proteins have been extensively studied during the pandemic. This wide dataset, related to sequence and structure, has enabled joint sequence-structure analysis. In this work, we focus on the SARS-CoV-2 S (Spike) protein and the relations between sequence mutations and structure variations, in order to shed light on the structural changes stemming from the position of mutated amino acid residues in three different SARS-CoV-2 strains. We propose the use of protein contact network (PCN) formalism to: (i) obtain a global metric space and compare various molecular entities, (ii) give a structural explanation of the observed phenotype, and (iii) provide context dependent descriptors of single mutations. PCNs have been used to compare sequence and structure of the Alpha, Delta, and Omicron SARS-CoV-2 variants, and we found that omicron has a unique mutational pattern leading to different structural consequences from mutations of other strains. The non-random distribution of changes in network centrality along the chain has allowed to shed light on the structural (and functional) consequences of mutations.

Head or tail? A molecular dynamics approach to the complex structure of TNF-associated factor TRAF2.

Tumor necrosis factor receptor-associated factor proteins (TRAFs) are trimeric proteins that play a fundamental role in signaling, acting as intermediaries between the tumor necrosis factor (TNF) receptors and the proteins that transmit the downstream signal. The monomeric subunits of all the TRAF family members share a common tridimensional structure: a C-terminal globular domain and a long coiled-coil tail characterizing the N-terminal section. In this study, the dependence of the TRAF2 dynamics on the length of its tail was analyzed in silico. In particular, we used the available crystallographic structure of a C-terminal fragment of TRAF2 (168 out of 501 a.a.), TRAF2-C, and that of a longer construct, addressed as TRAF2-plus, that we have re-constructed using the AlphaFold2 code. The results indicate that the longer N-terminal tail of TRAF2-plus has a strong influence on the dynamics of the globular regions in the protein C-terminal head. In fact, the quaternary interactions among the TRAF2-C subunits change asymmetrically in time, while the movements of TRAF2-plus monomers are rather limited and more ordered than those of the shorter construct. Such findings shed a new light on the dynamics of TRAF subunits and on the protein mechanism in vivo, since TRAF monomer-trimer equilibrium is crucial for several reasons (receptor recognition, membrane binding, hetero-oligomerization).

Biophysical Insight into the SARS-CoV2 Spike-ACE2 Interaction and Its Modulation by Hepcidin through a Multifaceted Computational Approach.

At the center of the SARS-CoV2 infection, the spike protein and its interaction with the human receptor ACE2 play a central role in the molecular machinery of SARS-CoV2 infection of human cells. Vaccine therapies are a valuable barrier to the worst effects of the virus and to its diffusion, but the need of purposed drugs is emerging as a core target of the fight against COVID19. In this respect, the repurposing of drugs has already led to discovery of drugs thought to reduce the effects of the cytokine storm, but still a drug targeting the spike protein, in the infection stage, is missing. In this work, we present a multifaceted computational approach strongly grounded on a biophysical modeling of biological systems, so to disclose the interaction of the SARS-CoV2 spike protein with ACE2 with a special focus to an allosteric regulation of the spike-ACE2 interaction. Our approach includes the following methodologies: Protein Contact Networks and Network Clustering, Targeted Molecular Dynamics, Elastic Network Modeling, Perturbation Response Scanning, and a computational analysis of energy flow and SEPAS as a protein-softness and monomer-based affinity predictor. We applied this approach to free (closed and open) states of spike protein and spike-ACE2 complexes. Eventually, we analyzed the interactions of free and bound forms of spike with hepcidin (HPC), the major hormone in iron regulation, recently addressed as a central player in the COVID19 pathogenesis, with a special emphasis to the most severe outcomes. Our results demonstrate that, compared with closed and open states, the spike protein in the ACE2-bound state shows higher allosteric potential. The correspondence between hinge sites and the Allosteric Modulation Region (AMR) in the S-ACE complex suggests a molecular basis for hepcidin involvement in COVID19 pathogenesis. We verify the importance of AMR in different states of spike and then study its interactions with HPC and the consequence of the HPC-AMR interaction on spike dynamics and its affinity for ACE2. We propose two complementary mechanisms for HPC effects on spike of SARS-CoV-2; (a) HPC acts as a competitive inhibitor when spike is in a preinfection state (open and with no ACE2), (b) the HPC-AMR interaction pushes the spike structure into the safer closed state. These findings need clear molecular in vivo verification beside clinical observations.

Dynamic Network Modeling of Allosteric Interactions and Communication Pathways in the SARS-CoV-2 Spike Trimer Mutants: Differential Modulation of Conformational Landscapes and Signal Transmission via Cascades of Regulatory Switches.

The rapidly growing body of structural and biochemical studies of the SARS-CoV-2 spike glycoprotein has revealed a variety of distinct functional states with radically different arrangements of the receptor-binding domain, highlighting a remarkable function-driven conformational plasticity and adaptability of the spike proteins. In this study, we examined molecular mechanisms underlying conformational and dynamic changes in the SARS-CoV-2 spike mutant trimers through the lens of dynamic analysis of allosteric interaction networks and atomistic modeling of signal transmission. Using an integrated approach that combined coarse-grained molecular simulations, protein stability analysis, and perturbation-based modeling of residue interaction networks, we examined how mutations in the regulatory regions of the SARS-CoV-2 spike protein can differentially affect dynamics and allosteric signaling in distinct functional states. The results of this study revealed key functional regions and regulatory centers that govern collective dynamics, allosteric interactions, and control signal transmission in the SARS-CoV-2 spike proteins. We found that the experimentally confirmed regulatory hotspots that dictate dynamic switching between conformational states of the SARS-CoV-2 spike protein correspond to the key hinge sites and global mediating centers of the allosteric interaction networks. The results of this study provide a novel insight into allosteric regulatory mechanisms of SARS-CoV-2 spike proteins showing that mutations at the key regulatory positions can differentially modulate distribution of states and determine topography of signal communication pathways operating through state-specific cascades of control switch points. This analysis provides a plausible strategy for allosteric probing of the conformational equilibrium and therapeutic intervention by targeting specific hotspots of allosteric interactions and communications in the SARS-CoV-2 spike proteins.

Integrated Biophysical Modeling of the SARS-CoV-2 Spike Protein Binding and Allosteric Interactions with Antibodies.

Structural and biochemical studies of the severe acute respiratory syndrome (SARS)-CoV-2 spike glycoproteins and complexes with highly potent antibodies have revealed multiple conformation-dependent epitopes highlighting conformational plasticity of spike proteins and capacity for eliciting specific binding and broad neutralization responses. In this study, we used coevolutionary analysis, molecular simulations, and perturbation-based hierarchical network modeling of the SARS-CoV-2 spike protein complexes with a panel of antibodies targeting distinct epitopes to explore molecular mechanisms underlying binding-induced modulation of dynamics and allosteric signaling in the spike proteins. Through coevolutionary analysis of the SARS-CoV-2 spike proteins, we identified highly coevolving hotspots and functional clusters that enable a functional cross-talk between distant allosteric regions in the SARS-CoV-2 spike complexes with antibodies. Coarse-grained and all-atom molecular dynamics simulations combined with mutational sensitivity mapping and perturbation-based profiling of the SARS-CoV-2 receptor-binding domain (RBD) complexes with CR3022 and CB6 antibodies enabled a detailed validation of the proposed approach and an extensive quantitative comparison with the experimental structural and deep mutagenesis scanning data. By combining in silico mutational scanning, perturbation-based modeling, and network analysis of the SARS-CoV-2 spike trimer complexes with H014, S309, S2M11, and S2E12 antibodies, we demonstrated that antibodies can incur specific and functionally relevant changes by modulating allosteric propensities and collective dynamics of the SARS-CoV-2 spike proteins. The results provide a novel insight into regulatory mechanisms of SARS-CoV-2 S proteins showing that antibody-escaping mutations can preferentially target structurally adaptable energy hotspots and allosteric effector centers that control functional movements and allosteric communication in the complexes.

Disclosing Allostery Through Protein Contact Networks.

Proteins are located in the twilight zone between chemistry and biology, where a peculiar kind of complexity starts. Proteins are the smallest 'devices' showing a sensible adaptation to their environment by the production of appropriate behavior when facing a specific stimulus. This fact qualifies (from the 'effector' side) proteins as nanomachines working as catalysts, motors, or switches. However (from the sensor side), the need to single out the 'specific stimulus' out of thermal noise qualifies proteins as information processing devices. Allostery corresponds to the modification of the configuration (in a broad sense) of the protein molecule in response to a specific stimulus in a non-strictly local way, thereby connecting the sensor and effector sides of the nanomachine. This is why the 'disclosing' of allostery phenomenon is at the very heart of protein function; in this chapter, we will demonstrate how a network-based representation of protein structure in terms of nodes (aminoacid residues) and edges (effective contacts between residues) is the natural language for getting rid of allosteric phenomena and, more in general, of protein structure/function relationships.

Protein Assembly: Defining the Strength of Protein-Protein Interactions Coupling the Theory with Experiments.

In this paper we report a procedure to analyze protein homodimer interfaces.We approached the problem by means of a topological methodology. In particular, we analyzed the subunits interface of about 50 homodimers and we have defined a few parameters that allow to organize these proteins in six different classes. The main characteristics of each class of homodimers have been discussed also taking into account their stabilization energy, as reported in the literature from the experimental measurements. A paradigmatic example for each class has been reported and a graphical representation proposed in order to better explain the meaning of the parameters chosen.

Non-symmetrical structural behavior of a symmetric protein: the case of homo-trimeric TRAF2 (tumor necrosis factor-receptor associated factor 2).

The oligomeric state of TRAF2 (tumor necrosis factor-receptor associated factor 2), a TNF (tumor necrosis factor) receptor-associated factor, is crucial for membrane binding and probably plays a fundamental role in regulating the protein function in vivo. In this study we have combined molecular dynamics with the protein contact network approach to characterize the interaction of the three identical subunits of TRAF2. The average structure obtained after a 225 ns simulation reveals that two clusters of different size are formed, one of which includes almost completely two subunits, while the third monomer appears to be more independent. This picture is also confirmed by the estimated average number of inter-subunit contacts and by the comparison of side chains mobility in each monomer. The analysis of equilibrium pressure-induced dissociation measurements supports such findings, indicating that the dimeric-monomeric (2 + 1) might be prevalent with respect to the trimeric configuration, especially in the case of more diluted samples. These findings suggest that the formation of monomeric species, which is crucial for the formation of intra-luminal vesicles, might depend on preferential asymmetric interactions among the three subunits.Communicated by Ramaswamy H. Sarma.

Polymorphism on human aromatase affects protein dynamics and substrate binding: spectroscopic evidence.

Human aromatase is a member of the cytochrome P450 superfamily, involved in steroid hormones biosynthesis. In particular, it converts androgen into estrogens being therefore responsible for the correct sex steroids balance. Due to its capacity in producing estrogens it has also been considered as a promising target for breast cancer therapy. Two single-nucleotide polymorphisms (R264C and R264H) have been shown to alter aromatase activity and they have been associated to an increased or decreased risk for estrogen-dependent pathologies. Here, the effect of these mutations on the protein dynamics is investigated by UV/FTIR and time resolved fluorescence spectroscopy. H/D exchange rates were measured by FTIR for the three proteins in the ligand-free, substrate- and inhibitor-bound forms and the data indicate that the wild-type enzyme undergoes a conformational change leading to a more compact tertiary structure upon substrate or inhibitor binding. Indeed, the H/D exchange rates are decreased when a ligand is present. In the variants, the exchange rates in the ligand-free and -bound forms are similar, indicating that a structural change is lacking, despite the single amino acid substitution is located in the peripheral shell of the protein molecule. Moreover, the fluorescence lifetimes data show that the quenching effect on tryptophan-224 observed upon ligand binding in the wild-type, is absent in both variants. Since this residue is located in the catalytic pocket, these findings suggest that substrate entrance and/or retention in the active site is partially compromised in both mutants. A contact network analysis demonstrates that the protein structure is organized in two main clusters, whose connectivity is altered by ligand binding, especially in correspondence of helix-G, where the amino acid substitutions occur. Our findings demonstrate that SNPs resulting in mutations on aromatase surface modify the protein flexibility that is required for substrate binding and catalysis. The cluster analysis provides a rationale for such effect, suggesting helix G as a possible target for aromatase inhibition.

Novel indole derivatives targeting HuR-mRNA complex to counteract high glucose damage in retinal endothelial cells.

The ELAVL1 (or human antigen R - HuR) RNA binding protein stabilizes the mRNA, with an AU-rich element, of several genes such as growth factors (i.e. VEGF) and inflammatory cytokines (i.e. TNFα). We hereby carried out a virtual screening campaign in order to identify and test novel HuR-mRNA disruptors. Best-scored compounds were tested in an in-vitro model of diabetic retinopathy, namely human retinal endothelial cells (HRECs) challenged with high-glucose levels (25 mM). HuR, VEGF and TNFα protein contents were evaluated by western-blot analysis in total cell lysates. VEGF and TNFα released from HRECs were measured in cell medium by ELISA. We found that two derivatives bearing indole moiety, VP12/14 and VP12/110, modulated HuR expression and decreased VEGF and TNF-α release by HREC exposed to high glucose (HG) levels. VP12/14 and VP12/110 inhibited VEGF and TNF-α release in HRECs challenged with high glucose levels, similarly to dihydrotanshinone (DHTS), a small molecule known to interfere with HuR- TNFα mRNA binding. The present findings demonstrated that VP12/14 and VP12/110 are innovative molecules with anti-inflammatory and anti-angiogenic properties, suggesting their potential use as novel candidates for treatment of diabetic retinopathy.