Italian guidelines for the management of irritable bowel syndrome in children and adolescents : Joint Consensus from the Italian Societies of: Gastroenterology, Hepatology and Pediatric Nutrition (SIGENP), Pediatrics (SIP), Gastroenterology and Endoscopy (SIGE) and Neurogastroenterology and Motility (SINGEM).

The irritable bowel syndrome (IBS) is a functional gastrointestinal disorder (FGID), whose prevalence has widely increased in pediatric population during the past two decades. The exact pathophysiological mechanism underlying IBS is still uncertain, thus resulting in challenging diagnosis and management. Experts from 4 Italian Societies participated in a Delphi consensus, searching medical literature and voting process on 22 statements on both diagnosis and management of IBS in children. Recommendations and levels of evidence were evaluated according to the grading of recommendations, assessment, development, and evaluation (GRADE) criteria. Consensus was reached for all statements. These guidelines suggest a positive diagnostic strategy within a symptom-based approach, comprehensive of psychological comorbidities assessment, alarm signs and symptoms' exclusion, testing for celiac disease and, under specific circumstances, fecal calprotectin and C-reactive protein. Consensus also suggests to rule out constipation in case of therapeutic failure. Conversely, routine stool testing for enteric pathogens, testing for food allergy/intolerance or small intestinal bacterial overgrowth are not recommended. Colonoscopy is recommended only in patients with alarm features. Regarding treatment, the consensus strongly suggests a dietary approach, psychologically directed therapies and, in specific conditions, gut-brain neuromodulators, under specialist supervision. Conditional recommendation was provided for both probiotics and specific fibers supplementation. Polyethylene glycol achieved consensus recommendation for specific subtypes of IBS. Secretagogues and 5-HT4 agonists are not recommended in children with IBS-C. Certain complementary alternative therapies, antispasmodics and, in specific IBS subtypes, loperamide and rifaximin could be considered.

AMALPHI: A Machine Learning Platform for Predicting Drug-Induced PhospholIpidosis.

Drug-induced phospholipidosis (PLD) involves the accumulation of phospholipids in cells of multiple tissues, particularly within lysosomes, and it is associated with prolonged exposure to druglike compounds, predominantly cationic amphiphilic drugs (CADs). PLD affects a significant portion of drugs currently in development and has recently been proven to be responsible for confounding antiviral data during drug repurposing for SARS-CoV-2. In these scenarios, it has become crucial to identify potential safe drug candidates in advance and distinguish them from those that may lead to false in vitro antiviral activity. In this work, we developed a series of machine learning classifiers with the aim of predicting the PLD-inducing potential of drug candidates. The models were built on a high-quality chemical collection comprising 545 curated small molecules extracted from ChEMBL v30. The most effective model, obtained using the balanced random forest algorithm, achieved high performance, including an AUC value computed in validation as high as 0.90. The model was made freely available through a user-friendly web platform named AMALPHI (https://www.ba.ic.cnr.it/softwareic/amalphiportal/), which can represent a valuable tool for medicinal chemists interested in conducting an early evaluation of PLD inducer potential.

Peptoids: Smart and Emerging Candidates for the Diagnosis of Cancer, Neurological and Autoimmune Disorders.

Early detection of fatal and disabling diseases such as cancer, neurological and autoimmune dysfunctions is still desirable yet challenging to improve quality of life and longevity. Peptoids (N-substituted glycine oligomers) are a relatively new class of peptidomimetics, being highly versatile and capable of mimicking the architectures and the activities of the peptides but with a marked resistance to proteases and a propensity to cross the cellular membranes over the peptides themselves. For these properties, they have gained an ever greater interest in applications in bioengineering and biomedical fields. In particular, the present manuscript is to our knowledge the only review focused on peptoids for diagnostic applications and covers the last decade's literature regarding peptoids as tools for early diagnosis of pathologies with a great impact on human health and social behavior. The review indeed provides insights into the peptoid employment in targeted cancer imaging and blood-based screening of neurological and autoimmune diseases, and it aims to attract the scientific community's attention to continuing and sustaining the investigation of these peptidomimetics in the diagnosis field considering their promising peculiarities.

The Biological Action and Structural Characterization of Eryngitin 3 and 4, Ribotoxin-like Proteins from Pleurotus eryngii Fruiting Bodies.

Ribotoxin-like proteins (RL-Ps) are specific ribonucleases found in mushrooms that are able to cleave a single phosphodiester bond located in the sarcin-ricin loop (SRL) of the large rRNA. The cleaved SRL interacts differently with some ribosomal proteins (P-stalk). This action blocks protein synthesis because the damaged ribosomes are unable to interact with elongation factors. Here, the amino acid sequences of eryngitin 3 and 4, RL-Ps isolated from Pleurotus eryngii fruiting bodies, were determined to (i) obtain structural information on this specific ribonuclease family from edible mushrooms and (ii) explore the structural determinants which justify their different biological and antipathogenic activities. Indeed, eryngitin 3 exhibited higher toxicity with respect to eryngitin 4 against tumoral cell lines and model fungi. Structurally, eryngitin 3 and 4 consist of 132 amino acids, most of them identical and exhibiting a single free cysteinyl residue. The amino acidic differences between the two toxins are (i) an additional phenylalanyl residue at the N-terminus of eryngitin 3, not retrieved in eryngitin 4, and (ii) an additional arginyl residue at the C-terminus of eryngitin 4, not retrieved in eryngitin 3. The 3D models of eryngitins show slight differences at the N- and C-terminal regions. In particular, the positive electrostatic surface at the C-terminal of eryngitin 4 is due to the additional arginyl residue not retrieved in eryngitin 3. This additional positive charge could interfere with the binding to the SRL (substrate) or with some ribosomal proteins (P-stalk structure) during substrate recognition.

ALPACA: A machine Learning Platform for Affinity and selectivity profiling of CAnnabinoids receptors modulators.

The development of small molecules that selectively target the cannabinoid receptor subtype 2 (CB2R) is emerging as an intriguing therapeutic strategy to treat neurodegeneration, as well as to contrast the onset and progression of cancer. In this context, in-silico tools able to predict CB2R affinity and selectivity with respect to the subtype 1 (CB1R), whose modulation is responsible for undesired psychotropic effects, are highly desirable. In this work, we developed a series of machine learning classifiers trained on high-quality bioactivity data of small molecules acting on CB2R and/or CB1R extracted from ChEMBL v30. Our classifiers showed strong predictive power in accurately determining CB2R affinity, CB1R affinity, and CB2R/CB1R selectivity. Among the built models, those obtained using random forest as algorithm proved to be the top-performing ones (AUC in validation ≥0.96) and were made freely accessible through a user-friendly web platform developed ad hoc and called ALPACA (https://www.ba.ic.cnr.it/softwareic/alpaca/). Due to its user-friendly interface and robust predictive power, ALPACA can be a valuable tool in saving both time and resources involved in the design of selective CB2R modulators.

Disclosing the Preferential Mercury Chelation by SeCys Containing Peptides over Their Cys Analogues.

Methylmercury, mercury (II), and mercury (I) chlorides were found to react with vasopressin, a nonapeptide hormone cyclized by two cysteine residues, and its mono- and diselenium analogues to form several mercury-peptide adducts. The replacement of Cys by SeCys in vasopressin increased the reactivity toward methylmercury, with the predominant formation of -Se/S-Hg-Se-bridged structures and the consequent demethylation of methylmercury. In competitive experiments, CH3HgCl reacted preferentially with the diselenium analogue rather than with vasopressin. The diselenium peptide also showed the capability to displace the CH3Hg moiety bound to S in vasopressin. These results open a promising perspective for the use of selenopeptides for methylmercury chelation and detoxification strategies.

New Insights into the Behavior of NHC-Gold Complexes in Cancer Cells.

Among the non-platinum antitumor agents, gold complexes have received increased attention owing to their strong antiproliferative effects, which generally occur through non-cisplatin-like mechanisms of action. Several studies have revealed that many cytotoxic gold compounds, such as N-heterocyclic carbene (NHC)-gold(I) complexes, are potent thioredoxin reductase (TrxR) inhibitors. Many other pathways have been supposed to be altered by gold coordination to protein targets. Within this frame, we have selected two gold(I) complexes based on aromatic ligands to be tested on cancer cells. Differently from bis [1,3-diethyl-4,5-bis(4-methoxyphenyl)imidazol-2-ylidene]gold(I) bromide (Au4BC), bis [1-methyl-3-acridineimidazolin-2-ylidene]gold(I) tetrafluoroborate (Au3BC) inhibited TrxR1 activity in vitro. Treatment of Huh7 hepatocellular carcinoma (HCC) cells, and MDA-MB-231 triple-negative breast cancer (TNBC) cells, with Au4BC inhibited cell viability, increased reactive oxygen species (ROS) levels, caused DNA damage, and induced autophagy and apoptosis. Notably, we found that, although Au3BC inhibited TrxR1 activity, no effect on the cell viabilities of HCC and BC cells was observed. At the molecular level, Au3BC induced a protective response mechanism in Huh7 and MDA-MB-231 cells, by inducing up-regulation of RAD51 and p62 protein expression, two proteins involved in DNA damage repair and autophagy, respectively. RAD51 gene knock-down in HCC cells increased cell sensitivity to Au3BC by significant reduction of cell viability, induction of DNA damage, and induction of apoptosis and autophagy. All together, these results suggest that the tested NHC-Gold complexes, Au3BC and Au4BC, showed different mechanisms of action, either dependent or independent of TrxR1 inhibition. As a result, Au3BC and Au4BC were found to be promising candidates as anticancer drugs for the treatment of HCC and BC.

High-Resolution Conformational Analysis of RGDechi-Derived Peptides Based on a Combination of NMR Spectroscopy and MD Simulations.

The crucial role of integrin in pathological processes such as tumor progression and metastasis formation has inspired intense efforts to design novel pharmaceutical agents modulating integrin functions in order to provide new tools for potential therapies. In the past decade, we have investigated the biological proprieties of the chimeric peptide RGDechi, containing a cyclic RGD motif linked to an echistatin C-terminal fragment, able to specifically recognize αvß3 without cross reacting with αvß5 and αIIbß3 integrin. Additionally, we have demonstrated using two RGDechi-derived peptides, called RGDechi1-14 and ψRGDechi, that chemical modifications introduced in the C-terminal part of the peptide alter or abolish the binding to the αvß3 integrin. Here, to shed light on the structural and dynamical determinants involved in the integrin recognition mechanism, we investigate the effects of the chemical modifications by exploring the conformational space sampled by RGDechi1-14 and ψRGDechi using an integrated natural-abundance NMR/MD approach. Our data demonstrate that the flexibility of the RGD-containing cycle is driven by the echistatin C-terminal region of the RGDechi peptide through a coupling mechanism between the N- and C-terminal regions.

Exploring the Molecular Interactions of Symmetrical and Unsymmetrical Selenoglycosides with Human Galectin-1 and Galectin-3.

Galectins (Gals) are small cytosolic proteins that bind ß-galactoside residues via their evolutionarily conserved carbohydrate recognition domain. Their dysregulation has been shown to be associated with many diseases. Consequently, targeting galectins for clinical applications has become increasingly relevant to develop tailored inhibitors selectively for one galectin. Accordingly, binding studies providing the molecular details of the interaction between galectin and inhibitor may be useful for the rational design of potent and selective antagonists. Gal-1 and Gal-3 are among the best-studied galectins, mainly for their roles in cancer progression; therefore, the molecular details of their interaction with inhibitors are demanded. This work gains more value by focusing on the interaction between Gal-1 and Gal-3 with the selenylated analogue of the Gal inhibitor thiodigalactose, characterized by a selenoglycoside bond (SeDG), and with unsymmetrical diglycosyl selenides (unsym(Se). Gal-1 and Gal-3 were produced heterologously and biophysically characterized. Interaction studies were performed by ITC, NMR spectroscopy, and MD simulation, and thermodynamic values were discussed and integrated with spectroscopic and computational results. The 3D complexes involving SeDG when interacting with Gal-1 and Gal-3 were depicted. Overall, the collected results will help identify hot spots for the design of new, better performing, and more specific Gal inhibitors.

A Comparative Molecular Dynamics Study of Selected Point Mutations in the Shwachman-Bodian-Diamond Syndrome Protein SBDS.

The Shwachman-Diamond Syndrome (SDS) is an autosomal recessive disease whose majority of patients display mutations in a ribosome assembly protein named Shwachman-Bodian-Diamond Syndrome protein (SBDS). A specific therapy for treating this rare disease is missing, due to the lack of knowledge of the molecular mechanisms responsible for its pathogenesis. Starting from the observation that SBDS single-point mutations, localized in different domains of the proteins, are responsible for an SDS phenotype, we carried out the first comparative Molecular Dynamics simulations on three SBDS mutants, namely R19Q, R126T and I212T. The obtained 450-ns long trajectories were compared with those returned by both the open and closed forms of wild type SBDS and strongly indicated that two distinct conformations (open and closed) are both necessary for the proper SBDS function, in full agreement with recent experimental observations. Our study supports the hypothesis that the SBDS function is governed by an allosteric mechanism involving domains I and III and provides new insights into SDS pathogenesis, thus offering a possible starting point for a specific therapeutic option.

New Advances in Short Peptides: Looking Forward.

It is beyond doubt that short peptides hold significant promise in bio-medicine, as the most versatile molecules, both structurally and functionally [...].

Fluorescence Studies: A9 Peptide, Functionalized with a Fluorogenic Probe, Interacts with Its Receptor Model HER2-DIVMP.

A recently developed synthetic protocol allowed for the functionalization of the active peptide A9 with a fluorogenic probe, which is useful for studying biomolecular interactions. Essentially, a nucleophilic attack on a halo-substituted benzofurazan is selectively performed by a cysteine sulfhydryl group. The process is assisted by the basic catalysis of activated zeolites (4 Å molecular sieves) and promoted by microwave irradiation. Fluorescence studies revealed that a donor-acceptor pair within the peptide sequence was introduced, thus allowing a deeper investigation on the interaction process between the peptide ligand and its receptor fragment. The obtained results allowed us to come full circle for all the currently understood structural determinants that were found to be involved in the binding process.

DeLA-Drug: A Deep Learning Algorithm for Automated Design of Druglike Analogues.

In this paper, we present a deep learning algorithm for automated design of druglike analogues (DeLA-Drug), a recurrent neural network (RNN) model composed of two long short-term memory (LSTM) layers and conceived for data-driven generation of similar-to-bioactive compounds. DeLA-Drug captures the syntax of SMILES strings of more than 1 million compounds belonging to the ChEMBL28 database and, by employing a new strategy called sampling with substitutions (SWS), generates molecules starting from a single user-defined query compound. Remarkably, the algorithm preserves druglikeness and synthetic accessibility of the known bioactive compounds present in the ChEMBL28 repository. The absence of any time-demanding fine-tuning procedure enables DeLA-Drug to perform a fast generation of focused libraries for further high-throughput screening and makes it a suitable tool for performing de novo design even in low-data regimes. To provide a concrete idea of its applicability, DeLA-Drug was applied to the cannabinoid receptor subtype 2 (CB2R), a known target involved in different pathological conditions such as cancer and neurodegeneration. DeLA-Drug, available as a free web platform (http://www.ba.ic.cnr.it/softwareic/deladrugportal/), can help medicinal chemists interested in generating analogues of compounds already available in their laboratories and, for this reason, good candidates for an easy and low-cost synthesis.

Design, Synthesis, and Anticancer Activity of a Selenium-Containing Galectin-3 and Galectin-9N Inhibitor.

Galectins are soluble ß-D-galactoside-binding proteins whose implication in cancer progression and disease outcome makes them prominent targets for therapeutic intervention. In this frame, the development of small inhibitors that block selectively the activity of galectins represents an important strategy for cancer therapy which is, however, still relatively underdeveloped. To this end, we designed here a rationally and efficiently novel diglycosylated compound, characterized by a selenoglycoside bond and the presence of a lipophilic benzyl group at both saccharide residues. The relatively high binding affinity of the new compound to the carbohydrate recognition domain of two galectins, galectin 3 and galectin 9, its good antiproliferative and anti-migration activity towards melanoma cells, as well as its anti-angiogenesis properties, pave the way for its further development as an anticancer agent.

Natural and Synthetic Halogenated Amino Acids-Structural and Bioactive Features in Antimicrobial Peptides and Peptidomimetics.

The 3D structure and surface characteristics of proteins and peptides are crucial for interactions with receptors or ligands and can be modified to some extent to modulate their biological roles and pharmacological activities. The introduction of halogen atoms on the side-chains of amino acids is a powerful tool for effecting this type of tuning, influencing both the physico-chemical and structural properties of the modified polypeptides, helping to first dissect and then rationally modify features that affect their mode of action. This review provides examples of the influence of different types of halogenation in amino acids that replace native residues in proteins and peptides. Examples of synthetic strategies for obtaining halogenated amino acids are also provided, focusing on some representative compounds and their biological effects. The role of halogenation in native and designed antimicrobial peptides (AMPs) and their mimetics is then discussed. These are in the spotlight for the development of new antimicrobial drugs to counter the rise of antibiotic-resistant pathogens. AMPs represent an interesting model to study the role that natural halogenation has on their mode of action and also to understand how artificially halogenated residues can be used to rationally modify and optimize AMPs for pharmaceutical purposes.

PHA-680626 Is an Effective Inhibitor of the Interaction between Aurora-A and N-Myc.

Neuroblastoma is a severe childhood disease, accounting for ~10% of all infant cancers. The amplification of the MYCN gene, coding for the N-Myc transcription factor, is an essential marker correlated with tumor progression and poor prognosis. In neuroblastoma cells, the mitotic kinase Aurora-A (AURKA), also frequently overexpressed in cancer, prevents N-Myc degradation by directly binding to a highly conserved N-Myc region. As a result, elevated levels of N-Myc are observed. During recent years, it has been demonstrated that some ATP competitive inhibitors of AURKA also cause essential conformational changes in the structure of the activation loop of the kinase that prevents N-Myc binding, thus impairing the formation of the AURKA/N-Myc complex. In this study, starting from a screening of crystal structures of AURKA in complexes with known inhibitors, we identified additional compounds affecting the conformation of the kinase activation loop. We assessed the ability of such compounds to disrupt the interaction between AURKA and N-Myc in vitro, using Surface Plasmon Resonance competition assays, and in tumor cell lines overexpressing MYCN, by performing Proximity Ligation Assays. Finally, their effects on N-Myc cellular levels and cell viability were investigated. Our results identify PHA-680626 as an amphosteric inhibitor both in vitro and in MYCN overexpressing cell lines, thus expanding the repertoire of known conformational disrupting inhibitors of the AURKA/N-Myc complex and confirming that altering the conformation of the activation loop of AURKA with a small molecule is an effective strategy to destabilize the AURKA/N-Myc interaction in neuroblastoma cancer cells.

Microwave Heating Promotes the S-Alkylation of Aziridine Catalyzed by Molecular Sieves: A Post-Synthetic Approach to Lanthionine-Containing Peptides.

Aziridine derivatives involved in nucleophilic ring-opening reactions have attracted great interest, since they allow the preparation of biologically active molecules. A chemoselective and mild procedure to convert a peptide cysteine residue into lanthionine via S-alkylation on aziridine substrates is presented in this paper. The procedure relies on a post-synthetic protocol promoted by molecular sieves to prepare lanthionine-containing peptides and is assisted by microwave irradiation. In addition, it represents a valuable alternative to the stepwise approach, in which the lanthionine precursor is incorporated into peptides as a building block.

Structure-Based Prediction of hERG-Related Cardiotoxicity: A Benchmark Study.

Drug-induced blockade of the human ether-à-go-go-related gene (hERG) channel is today considered the main cause of cardiotoxicity in postmarketing surveillance. Hence, several ligand-based approaches were developed in the last years and are currently employed in the early stages of a drug discovery process for in silico cardiac safety assessment of drug candidates. Herein, we present the first structure-based classifiers able to discern hERG binders from nonbinders. LASSO regularized support vector machines were applied to integrate docking scores and protein-ligand interaction fingerprints. A total of 396 models were trained and validated based on: (i) high-quality experimental bioactivity information returned by 8337 curated compounds extracted from ChEMBL (version 25) and (ii) structural predictor data. Molecular docking simulations were performed using GLIDE and GOLD software programs and four different hERG structural models, namely, the recently published structures obtained by cryoelectron microscopy (PDB codes: 5VA1 and 7CN1) and two published homology models selected for comparison. Interestingly, some classifiers return performances comparable to ligand-based models in terms of area under the ROC curve (AUCMAX = 0.86 ± 0.01) and negative predictive values (NPVMAX = 0.81 ± 0.01), thus putting forward the herein proposed computational workflow as a valuable tool for predicting hERG-related cardiotoxicity without the limitations of ligand-based models, typically affected by low interpretability and a limited applicability domain. From a methodological point of view, our study represents the first example of a successful integration of docking scores and protein-ligand interaction fingerprints (IFs) through a support vector machine (SVM) LASSO regularized strategy. Finally, the study highlights the importance of using hERG structural models accounting for ligand-induced fit effects and allowed us to select the best-performing protein conformation (made available in the Supporting Information, SI) to be employed for a reliable structure-based prediction of hERG-related cardiotoxicity.

An Overview of Peptide-Based Molecules as Potential Drug Candidates for Multiple Sclerosis.

Multiple sclerosis (MS) belongs to demyelinating diseases, which are progressive and highly debilitating pathologies that imply a high burden both on individual patients and on society. Currently, several treatment strategies differ in the route of administration, adverse events, and possible risks. Side effects associated with multiple sclerosis medications range from mild symptoms, such as flu-like or irritation at the injection site, to serious ones, such as progressive multifocal leukoencephalopathy and other life-threatening events. Moreover, the agents so far available have proved incapable of fully preventing disease progression, mostly during the phases that consist of continuous, accumulating disability. Thus, new treatment strategies, able to halt or even reverse disease progression and specific for targeting solely the pathways that contribute to the disease pathogenesis, are highly desirable. Here, we provide an overview of the recent literature about peptide-based systems tested on experimental autoimmune encephalitis (EAE) models. Since peptides are considered a unique therapeutic niche and important elements in the pharmaceutical landscape, they could open up new therapeutic opportunities for the treatment of MS.

Diphenylalanine Motif Drives Self-Assembling in Hybrid PNA-Peptide Conjugates.

Peptides and nucleic acids can self-assemble to give supramolecular structures that find application in different fields, ranging from the delivery of drugs to the obtainment of materials endowed with optical properties. Forces that stabilize the "suprastructures" typically are hydrogen bonds or aromatic interactions; in case of nucleic acids, Watson-Crick pairing drives self-assembly while, in case of peptides, backbone hydrogen bonds and interactions between aromatic side chains trigger the formation of structures, such as nanotubes or ribbons. Molecules containing both aromatic peptides and nucleic acids could in principle exploit different forces to self-assemble. In this work we meant to investigate the self-assembly of mixed systems, with the aim to understand which forces play a major role and determine formation/structure of aggregates. We therefore synthesized conjugates of the peptide FF to the peptide nucleic acid dimer "gc" and characterized their aggregates by different spectroscopic techniques, including NMR, CD and fluorescence.