Impact of the Cationic Moiety of Ionic Liquids on Chemoselective Artificial Olfaction.

Ionogels and derived materials are assemblies of polymers and ionic liquids characterized by high stability and ionic conductivity, making them interesting choices as gas sensors. In this work, we assessed the effect of the ionic liquid moiety to generate ionogels and hybrid gels as electrical and optical gas sensors. Six ionic liquids consisting of a constant anion (chloride) and distinct cationic head groups were used to generate ionogels and hybrid gels and further tested as gas sensors in customized electronic nose devices. In general, ionogel-based sensors yielded higher classification accuracies of standard volatile organic compounds when compared to hybrid material-based sensors. In addition, the high chemical diversity of ionic liquids is further translated to a high functional diversity in analyte molecular recognition and sensing.

Hierarchical self-assembly of a reflectin-derived peptide.

Reflectins are a family of intrinsically disordered proteins involved in cephalopod camouflage, making them an interesting source for bioinspired optical materials. Understanding reflectin assembly into higher-order structures by standard biophysical methods enables the rational design of new materials, but it is difficult due to their low solubility. To address this challenge, we aim to understand the molecular self-assembly mechanism of reflectin's basic unit-the protopeptide sequence YMDMSGYQ-as a means to understand reflectin's assembly phenomena. Protopeptide self-assembly was triggered by different environmental cues, yielding supramolecular hydrogels, and characterized by experimental and theoretical methods. Protopeptide films were also prepared to assess optical properties. Our results support the hypothesis for the protopeptide aggregation model at an atomistic level, led by hydrophilic and hydrophobic interactions mediated by tyrosine residues. Protopeptide-derived films were optically active, presenting diffuse reflectance in the visible region of the light spectrum. Hence, these results contribute to a better understanding of the protopeptide structural assembly, crucial for the design of peptide- and reflectin-based functional materials.

Native, engineered and de novo designed ligands targeting the SARS-CoV-2 spike protein.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the deadly coronavirus disease 2019 (Covid-19) and is a concerning hazard to public health. This virus infects cells by establishing a contact between its spike protein (S-protein) and host human angiotensin-converting enzyme 2 (hACE2) receptor, subsequently initiating viral fusion. The inhibition of the interaction between the S-protein and hACE2 has immediately drawn attention amongst the scientific community, and the S-protein was considered the prime target to design vaccines and to develop affinity ligands for diagnostics and therapy. Several S-protein binders have been reported at a fast pace, ranging from antibodies isolated from immunised patients to de novo designed ligands, with some binders already yielding promising in vivo results in protecting against SARS-CoV-2. Natural, engineered and designed affinity ligands targeting the S-protein are herein summarised, focusing on molecular recognition aspects, whilst identifying preferred hot spots for ligand binding. This review serves as inspiration for the improvement of already existing ligands or for the design of new affinity ligands towards SARS-CoV-2 proteins. Lessons learnt from the Covid-19 pandemic are also important to consolidate tools and processes in protein engineering to enable the fast discovery, production and delivery of diagnostic, prophylactic, and therapeutic solutions in future pandemics.

Discovery of phosphotyrosine-binding oligopeptides with supramolecular target selectivity.

We demonstrate phage-display screening on self-assembled ligands that enables the identification of oligopeptides that selectively bind dynamic supramolecular targets over their unassembled counterparts. The concept is demonstrated through panning of a phage-display oligopeptide library against supramolecular tyrosine-phosphate ligands using 9-fluorenylmethoxycarbonyl-phenylalanine-tyrosine-phosphate (Fmoc-FpY) micellar aggregates as targets. The 14 selected peptides showed no sequence consensus but were enriched in cationic and proline residues. The lead peptide, KVYFSIPWRVPM-NH2 (P7) was found to bind to the Fmoc-FpY ligand exclusively in its self-assembled state with K D = 74 ± 3 µM. Circular dichroism, NMR and molecular dynamics simulations revealed that the peptide interacts with Fmoc-FpY through the KVYF terminus and this binding event disrupts the assembled structure. In absence of the target micellar aggregate, P7 was further found to dynamically alternate between multiple conformations, with a preferred hairpin-like conformation that was shown to contribute to supramolecular ligand binding. Three identified phages presented appreciable binding, and two showed to catalyze the hydrolysis of a model para-nitro phenol phosphate substrate, with P7 demonstrating conformation-dependent activity with a modest k cat/K M = 4 ± 0.3 × 10-4 M-1 s-1.

Seeing the Unseen: The Role of Liquid Crystals in Gas-Sensing Technologies.

Fast, real-time detection of gases and volatile organic compounds (VOCs) is an emerging research field relevant to most aspects of modern society, from households to health facilities, industrial units, and military environments. Sensor features such as high sensitivity, selectivity, fast response, and low energy consumption are essential. Liquid crystal (LC)-based sensors fulfill these requirements due to their chemical diversity, inherent self-assembly potential, and reversible molecular order, resulting in tunable stimuliresponsive soft materials. Sensing platforms utilizing thermotropic uniaxial systems-nematic and smectic-that exploit not only interfacial phenomena, but also changes in the LC bulk, are demonstrated. Special focus is given to the different interaction mechanisms and tuned selectivity toward gas and VOC analytes. Furthermore, the different experimental methods used to transduce the presence of chemical analytes into macroscopic signals are discussed and detailed examples are provided. Future perspectives and trends in the field, in particular the opportunities for LC-based advanced materials in artificial olfaction, are also discussed.

Affinity-Triggered Assemblies Based on a Designed Peptide-Peptide Affinity Pair.

Affinity-triggered assemblies rely on affinity interactions as the driving force to assemble physically crosslinked networks. WW domains are small hydrophobic proteins binding to proline-rich peptides that are typically produced in the insoluble form. Previous works attempted the biological production of the full WW domain in tandem to generate multivalent components for affinity-triggered hydrogels. In this work, an alternative approach is followed by engineering a 13-mer minimal version of the WW domain that retains the ability to bind to target proline-rich peptides. Both ligand and target peptides are produced chemically and conjugated to multivalent polyethylene glycol, yielding two components. Upon mixing together, they form soft biocompatible affinity-triggered assemblies, stable in stem cell culture media, and display mechanical properties in the same order of magnitude as for those hydrogels formed with the full WW protein in tandem.

Free Marine Natural Products Databases for Biotechnology and Bioengineering.

Marine organisms and micro-organisms are a source of natural compounds with unique chemical features. These chemical properties are useful for the discovery of new functions and applications of marine natural products (MNPs). To extensively exploit the potential implementations of MNPs, they are gathered in chemical databases that allow their study and screening for applications of biotechnological interest. However, the classification of MNPs is currently poor in generic chemical databases. The present availability of free-access-focused MNP databases is scarce and the molecular diversity of these databases is still very low when compared to the paid-access ones. In this review paper, the current scenario of free-access MNP databases is presented as well as the hindrances involved in their development, mainly compound dereplication. Examples and opportunities for using freely accessible MNP databases in several important areas of biotechnology are also assessed. The scope of this paper is, as well, to notify the latent potential of these information sources for the discovery and development of new MNPs in biotechnology, and push future efforts to develop a public domain MNP database freely available for the scientific community.

Designed affinity ligands to capture human serum albumin.

Human serum albumin (HSA) in an important therapeutic agent and disease biomarker, with an increasing market demand. By proteins and drugs that bind to HSA as inspiration, a combinatorial library of 64 triazine-based ligands was rationally designed and screened for HSA binding at physiological conditions. Two triazine-based lead ligands (A3A2 and A6A5), presenting more than 50% HSA bound and high enrichment factors, were selected for further studies. Binding and elution conditions for HSA purification from human plasma were optimized for both ligands. The A6A5 adsorbent yielded a purified HSA sample with 98% purity at 100% recovery yield under mild binding and elution conditions.

Discovery of new FXR agonists based on 6-ECDCA binding properties by virtual screening and molecular docking.

FXR is a member of the nuclear receptor superfamily, which regulates the expression of various genes involved in bile acid, lipid and glucose metabolism. Targeting FXR with small molecules has been exploited to treat lipid-related disorders and diseases such as cholestasis, gallstones and hepatic disorders. In this work, we expand the existing pool of known FXR agonists using a fast hit-to-lead structure-based pharmacophore and docking screening protocol. A set of 25 molecules was selected after screening a large database of commercial chemicals, and experimental tests were carried out to demonstrate their ability to activate FXR. Three novel FXR agonists are reported, namely, one full agonist, more efficient than the endogenous ligand chenodeoxycholic acid, and two partial agonists.

Protein- and Peptide-Based Biosensors in Artificial Olfaction.

Animals' olfactory systems rely on proteins, olfactory receptors (ORs) and odorant-binding proteins (OBPs), as their native sensing units to detect odours. Recent advances demonstrate that these proteins can also be employed as molecular recognition units in gas-phase biosensors. In addition, the interactions between odorant molecules and ORs or OBPs are a source of inspiration for designing peptides with tunable odorant selectivity. We review recent progress in gas biosensors employing biological units (ORs, OBPs, and peptides) in light of future developments in artificial olfaction, emphasizing examples where biological components have been employed to detect gas-phase analytes.

Integration of Molecular Dynamics Based Predictions into the Optimization of De Novo Protein Designs: Limitations and Benefits.

Recent advances in de novo protein design have gained considerable insight from the intrinsic dynamics of proteins, based on the integration of molecular dynamics simulations protocols on the state-of-the-art de novo protein design protocols used nowadays. With this protocol we illustrate how to set up and run a molecular dynamics simulation followed by a functional protein dynamics analysis. New users will be introduced to some useful open-source computational tools, including the GROMACS molecular dynamics simulation software package and ProDy for protein structural dynamics analysis.

A SMYD3 Small-Molecule Inhibitor Impairing Cancer Cell Growth.

SMYD3 is a histone lysine methyltransferase that plays an important role in transcriptional activation as a member of an RNA polymerase complex, and its oncogenic role has been described in different cancer types. We studied the expression and activity of SMYD3 in a preclinical model of colorectal cancer (CRC) and found that it is strongly upregulated throughout tumorigenesis both at the mRNA and protein level. Our results also showed that RNAi-mediated SMYD3 ablation impairs CRC cell proliferation indicating that SMYD3 is required for proper cancer cell growth. These data, together with the importance of lysine methyltransferases as a target for drug discovery, prompted us to carry out a virtual screening to identify new SMYD3 inhibitors by testing several candidate small molecules. Here we report that one of these compounds (BCI-121) induces a significant reduction in SMYD3 activity both in vitro and in CRC cells, as suggested by the analysis of global H3K4me2/3 and H4K5me levels. Of note, the extent of cell growth inhibition by BCI-121 was similar to that observed upon SMYD3 genetic ablation. Most of the results described above were obtained in CRC; however, when we extended our observations to tumor cell lines of different origin, we found that SMYD3 inhibitors are also effective in other cancer types, such as lung, pancreatic, prostate, and ovarian. These results represent the proof of principle that SMYD3 is a druggable target and suggest that new compounds capable of inhibiting its activity may prove useful as novel therapeutic agents in cancer treatment.

Inhibition of human dyskerin as a new approach to target ribosome biogenesis.

The product of the DKC1 gene, dyskerin, is required for both ribosome biogenesis and telomerase complex stabilization. Targeting these cellular processes has been explored for the development of drugs to selectively or preferentially kill cancer cells. Presently, intense research is conducted involving the identification of new biological targets whose modulation may simultaneously interfere with multiple cellular functions that are known to be hyper-activated by neoplastic transformations. Here, we report, for the first time, the computational identification of small molecules able to inhibit dyskerin catalytic activity. Different in silico techniques were applied to select compounds and analyze the binding modes and the interaction patterns of ligands in the human dyskerin catalytic site. We also describe a newly developed and optimized fast real-time PCR assay that was used to detect dyskerin pseudouridylation activity in vitro. The identification of new dyskerin inhibitors constitutes the first proof of principle that the pseudouridylation activity can be modulated by means of small molecule agents. Therefore, the presented results, obtained through the usage of computational tools and experimental validation, indicate an alternative therapeutic strategy to target ribosome biogenesis pathway.

ADP-ribosylated proteins as old and new drug targets for anticancer therapy: the example of ARF6.

Post-translational modifications of cellular proteins by mono- or poly-ADP-ribosylation are associated with numerous cellular processes. ADP-ribosylation reactions are important in the nucleus, and in mitochondrial activity, stress response signaling, intracellular trafficking, and cell senescence and apoptosis decisions. These reversible reactions add ADP-ribose to target proteins via specific enzymes to form the ADP-ribosylated protein; the cleaveage of this covalent bond is performed via hydrolases. Deficiencies in these enzymatic activities lead to cell death or tumor formation, thus defining their functional roles and impact on human disease. Unlike mono- ADP-ribosyltransferases, poly-ADP-ribose polymerases (PARPs) have been at the frontline of drug discovery since the 1980s. PARP1 is a valuable therapeutic target, with a central role in responses to DNA damage. With mono-ADP-ribosylation now linked to human diseases, such as inflammation, diabetes, neurodegeneration and cancer metastasis, novel and equally important functions of mono-ADPribosylation in cell signaling pathways can now be defined. Recently, we reported mono-ADP-ribosylation of ADP-ribosylation factor 6 (ARF6), a small G-protein of the Ras superfamily. In addition to its involvement in actin remodeling, plasma membrane reorganization and vesicular transport, ARF6 contributes to cancer progression through activation of cell motility and invasion. Consequently, targeting this modification will counteract the pro-invasive effects of ARF6, providing innovative anti-tumor therapy. This review summarizes our present knowledge of the enzymes and targets involved in ADP-ribosylation reactions, and describes in silico approaches to visualize their site of interaction and to identify the precise site for ADP-ribosylation. This should ultimately improve pharmacological strategies to enhance both anti-tumor efficacy and treatment of a number of inflammatory and neurodegenerative disorders.

Modulation of epigenetic targets for anticancer therapy: clinicopathological relevance, structural data and drug discovery perspectives.

Research on cancer epigenetics has flourished in the last decade. Nevertheless growing evidence point on the importance to understand the mechanisms by which epigenetic changes regulate the genesis and progression of cancer growth. Several epigenetic targets have been discovered and are currently under validation for new anticancer therapies. Drug discovery approaches aiming to target these epigenetic enzymes with small-molecules inhibitors have produced the first pre-clinical and clinical outcomes and many other compounds are now entering the pipeline as new candidate epidrugs. The most studied targets can be ascribed to histone deacetylases and DNA methyltransferases, although several other classes of enzymes are able to operate post-translational modifications to histone tails are also likely to represent new frontiers for therapeutic interventions. By acknowledging that the field of cancer epigenetics is evolving with an impressive rate of new findings, with this review we aim to provide a current overview of pre-clinical applications of smallmolecules for cancer pathologies, combining them with the current knowledge of epigenetic targets in terms of available structural data and drug design perspectives.

Comparative analysis of pharmacophore screening tools.

The pharmacophore concept is of central importance in computer-aided drug design (CADD) mainly because of its successful application in medicinal chemistry and, in particular, high-throughput virtual screening (HTVS). The simplicity of the pharmacophore definition enables the complexity of molecular interactions between ligand and receptor to be reduced to a handful set of features. With many pharmacophore screening softwares available, it is of the utmost interest to explore the behavior of these tools when applied to different biological systems. In this work, we present a comparative analysis of eight pharmacophore screening algorithms (Catalyst, Unity, LigandScout, Phase, Pharao, MOE, Pharmer, and POT) for their use in typical HTVS campaigns against four different biological targets by using default settings. The results herein presented show how the performance of each pharmacophore screening tool might be specifically related to factors such as the characteristics of the binding pocket, the use of specific pharmacophore features, and the use of these techniques in specific steps/contexts of the drug discovery pipeline. Algorithms with rmsd-based scoring functions are able to predict more compound poses correctly as overlay-based scoring functions. However, the ratio of correctly predicted compound poses versus incorrectly predicted poses is better for overlay-based scoring functions that also ensure better performances in compound library enrichments. While the ensemble of these observations can be used to choose the most appropriate class of algorithm for specific virtual screening projects, we remarked that pharmacophore algorithms are often equally good, and in this respect, we also analyzed how pharmacophore algorithms can be combined together in order to increase the success of hit compound identification. This study provides a valuable benchmark set for further developments in the field of pharmacophore search algorithms, e.g., by using pose predictions and compound library enrichment criteria.

The extracellular subunit interface of the 5-HT3 receptors: a computational alanine scanning mutagenesis study.

The functional serotonin 5-HT type-3 (5-HT(3)) receptor, the target of many neuroactive drugs, is known to be a pseudo-symmetric pentamer made either of five identical subunits A (homomeric 5-HT(3A)-R) or of subunits A and B (heteromeric 5-HT(3A/B)-R) in a still debated arrangement. The serotonin binding site is located in the extracellular region, at the interface between two monomers, called the principal and the complementary subunits. The results of molecular dynamics simulations and computational alanine scanning mutagenesis studies applied here to the homomeric human 5-HT(3A)-R disclose an aromatic "hot" cluster in the centre of the interface formed by residues W178 (principal subunit), Y68, Y83, W85 and Y148 (complementary subunit). Moreover, investigation of the coupling of agonist/antagonist binding to channel activation/inactivation points out the presence of two putative functional pathways at the subunit interface: W116-H180-L179-W178-E124-F125 (principal subunit) and Y136-Y138-Y148-W85-(P150) (complementary subunit), where W178 and Y148 appear to be critical residues for the binding/activation mechanism. Finally, direct comparison of the main features shown by the AA interface in the human 5-HT(3A)-R with those of the BB interface in the homopentameric human 5-HT(3B)-R provides interesting clues about the possible reasons that cause the 5-HT(3B)-R not to be functional.

Freely accessible databases of commercial compounds for high- throughput virtual screenings.

In the last decades computer-aided drug design techniques have been successfully used to guide the selection of new hit compounds with biological activity. These methods, that include a broad range of chemoinformatic and computational chemistry algorithms, are still disciplines in full bloom. In particular, virtual screening procedures have celebrated a great popularity for the rapid and cost-effective assessment of large chemical libraries of commercial compounds. While the usage of in silico techniques promises an effective speed-up at the early-stage of the development of new active compounds, computational projects starting from scratch with raw chemical data are often associated with resource- and time-consuming preparation protocols, almost blunting the advantages of using these techniques. In order to help facing these difficulties, in the last years several chemoinformatic projects and tools have emerged in literature and have been useful in preparing curated databases of chemical compounds for high-throughput virtual screening purposes. The review will focus on the detailed analysis of free databases of commercial chemical compounds that are currently employed in virtual screening campaigns for drug design. The scope of this review is to compare such databases and suggest the reader on how and in which conditions the usage of these databases could be recommended.

CoCoCo: a free suite of multiconformational chemical databases for high-throughput virtual screening purposes.

In the last few decades, virtual screening has proved to be able to guide the selection of new hit compounds with predefined biological activity. However, the usage of these computational techniques is often associated with resource- and time-consuming preparation protocols. In this work we present Commercial Compound Collection (CoCoCo), a suite of free and ready-to-use chemical databases to help setting up in silico screening projects. CoCoCo collects molecular structural information of commercial compounds from various chemical vendors by merging them in a unique, non-redundant format. CoCoCo databases are prepared with transparent and straightforward routines based on state-of-the-art computational tools that introduce comprehensive structural information about tautomers, stereoisomers and conformational states of each compound. CoCoCo suite is especially conceived as a set of valuable tools that may help a wide range of researchers who wish to initiate their own project in the field of computational drug design. CoCoCo suite is available free of charge at the website .

Computational analysis of ligand recognition sites of homo- and heteropentameric 5-HT3 receptors.

Inhibition of the 5-hydroxytryptamine receptor (5-HT(3)R), a member of the Cys-loop superfamily of Ligand-Gated Ion Channels (LGICs), has been recognized to have important antiemetic effects. With respect to the many other drugs already in use, such as the first generation 5-HT(3)R antagonist granisetron, palonosetron, a second generation antagonist, clearly demonstrates superior inhibition potency towards the 5-HT(3)Rs. Five different receptor monomers, the 5-HT(3)R A-E, have been identified although the A and B subunits are the only known to build functional receptors, the homopentameric 5-HT(3A)R and the heteropentameric 5-HT(3B-A)R (with BBABA subunit arrangement). At present, however, no three-dimensional structure has been reported for any of the 5-HT(3)R subunits. To understand the binding properties of agonists and antagonists, models of the extracellular portion of the 5-HT(3)R A and B subunits are built and assembled into the receptor (homo- and hetero-) pentameric structure on the basis of the known three-dimensional structure of the nicotinic-acetylcholine receptor (nACh-R). The results of docking studies of the natural agonist serotonin and the antagonists palonosetron and granisetron into the modelled homomeric and heteromeric 5-HT(3)R binding interfaces, provide a possible rationalization both of the higher potency of palonosetron with respect to other antagonists, and of its previously reported allosteric binding and positive cooperativity properties.