A Combined Molecular Dynamics and Hydropathic INTeraction (HINT) Approach to Investigate Protein Flexibility: The PPARγ Case Study.

Molecular Dynamics (MD) is a computational technique widely used to evaluate a molecular system's thermodynamic properties and conformational behavior over time. In particular, the energy analysis of a protein conformation ensemble produced though MD simulations plays a crucial role in explaining the relationship between protein dynamics and its mechanism of action. In this research work, the HINT (Hydropathic INTeractions) LogP-based scoring function was first used to handle MD trajectories and investigate the molecular basis behind the intricate PPARγ mechanism of activation. The Peroxisome Proliferator-Activated Receptor γ (PPARγ) is an emblematic example of a highly flexible protein due to the extended ω-loop delimiting the active site, and it is responsible for the receptor's ability to bind chemically different compounds. In this work, we focused on the PPARγ complex with Rosiglitazone, a common anti-diabetic compound and analyzed the molecular basis of the flexible ω-loop stabilization effect produced by the Oleic Acid co-binding. The HINT-based analysis of the produced MD trajectories allowed us to account for all of the energetic contributions involved in interconverting between conformational states and describe the intramolecular interactions between the flexible ω-loop and the helix H3 triggered by the allosteric binding mechanism.

A Computational Workflow to Predict Biological Target Mutations: The Spike Glycoprotein Case Study.

The biological target identification process, a pivotal phase in the drug discovery workflow, becomes particularly challenging when mutations affect proteins' mechanisms of action. COVID-19 Spike glycoprotein mutations are known to modify the affinity toward the human angiotensin-converting enzyme ACE2 and several antibodies, compromising their neutralizing effect. Predicting new possible mutations would be an efficient way to develop specific and efficacious drugs, vaccines, and antibodies. In this work, we developed and applied a computational procedure, combining constrained logic programming and careful structural analysis based on the Structural Activity Relationship (SAR) approach, to predict and determine the structure and behavior of new future mutants. "Mutations rules" that would track statistical and functional types of substitutions for each residue or combination of residues were extracted from the GISAID database and used to define constraints for our software, having control of the process step by step. A careful molecular dynamics analysis of the predicted mutated structures was carried out after an energy evaluation of the intermolecular and intramolecular interactions using the HINT (Hydrophatic INTeraction) force field. Our approach successfully predicted, among others, known Spike mutants.

An insight about the mechanism of action (MoA) of R-bicalutamide on the androgen receptor homodimer using molecular dynamic.

R-bicalutamide is a first-line therapy used to treat prostate cancer (PCa) inhibiting the androgen receptor (AR) which plays an important role in the development and the progression of PCa. However, after a protracted drug administration, many patients develop a form of androgen insensitivity since R-bicalutamide starts to exhibit some agonistic properties lead by the W741L AR mutation in the ligand-binding pocket even if the mechanism of the antagonist-agonist switch is still not clear. To study the drug-resistant mechanism, we explored the structural effects of the antagonist R-bicalutamide on the homodimer stability considering both the AR wild-type and W741L employing molecular dynamic (MD) simulations. The results obtained indicate that the binding of R-bicalutamide in the two AR monomers induces a great instability in the homodimer, which may determine the monomer's dissociation preventing AR migration into the nucleus and avoiding the transcriptional activity. If the W741L mutation occurs, the homodimer tends to have a behaviour close to the agonistic system where the two monomers are tightly bound, which may explain the effect of the W741L in drug insensitivity from a structural point of view.

A synergism of in silico and statistical approaches to discover new potential endocrine disruptor mycotoxins.

Mycotoxins are secondary metabolites produced by pathogenic fungi. They are found in a variety of different products, such as spices, cocoa, and cereals, and they can contaminate fields before and/or after harvest and during storage. Mycotoxins negatively impact human and animal health, causing a variety of adverse effects, ranging from acute poisoning to long-term effects. Given a large number of mycotoxins (currently more than 300 are known), it is impossible to use in vitro/in vivo methods to detect the potentially harmful effects to human health of all of these. To overcome this problem, this work aims to present a new robust computational approach, based on a combination of in silico and statistical methods, in order to screen a large number of molecules against the nuclear receptor family in a cost and time-effective manner and to discover the potential endocrine disruptor activity of mycotoxins. The results show that a high number of mycotoxins is predicted as a potential binder of nuclear receptors. In particular, ochratoxin A, zearalenone, α- and ß-zearalenol, aflatoxin B1, and alternariol have been shown to be putative endocrine disruptors chemicals for nuclear receptors.

From oncoproteins to spike proteins: the evaluation of intramolecular stability using hydropathic force field.

Evaluation of the intramolecular stability of proteins plays a key role in the comprehension of their biological behavior and mechanism of action. Small structural alterations such as mutations induced by single nucleotide polymorphism can impact biological activity and pharmacological modulation. Covid-19 mutations, that affect viral replication and the susceptibility to antibody neutralization, and the action of antiviral drugs, are just one example. In this work, the intramolecular stability of mutated proteins, like Spike glycoprotein and its complexes with the human target, is evaluated through hydropathic intramolecular energy scoring originally conceived by Abraham and Kellogg based on the "Extension of the fragment method to calculate amino acid zwitterion and side-chain partition coefficients" by Abraham and Leo in Proteins: Struct. Funct. Genet. 1987, 2:130 - 52. HINT is proposed as a fast and reliable tool for the stability evaluation of any mutated system. This work has been written in honor of Prof. Donald J. Abraham (1936-2021).

The Application of In Silico Methods on Umami Taste Receptor.

The umami taste receptor is a heterodimer composed of two members of the T1R taste receptor family: T1R1 (taste receptor type 1 member 1) and T1R3 (taste receptor type 1 member 3). Taste receptor T1R1-T1R3 can be activated, or modulated, by binding to several natural ligands, such as L-glutamate, inosine-5'-monophosphate (IMP), and guanosine-5'-monophosphate (GMP). Because no structure of the umami taste receptor has been solved until now, in silico techniques, such as homology modelling, molecular docking, and molecular dynamics (MD) simulations, are used to generate a 3D structure model of this receptor and to understand its molecular mechanisms. The purpose of this chapter is to highlight how computational methods can provide a better deciphering of the mechanisms of action of umami ligands in activating the umami taste receptors leading to advancements in the taste research field.

Food contact materials as possible endocrine disruptors for PPARs: a consensus scoring analysis.

Peroxisome proliferator-activated receptors (PPARs), with the α, ß/δ and γ isoforms, are nuclear receptors that control the expression of genes involved in glucose and lipids' metabolism and into inflammatory processes and play a central role in metabolic syndrome. PPARs are a particular class of nuclear receptors because of their larger and more flexible ligand-binding domain with a particular Y shape. As nuclear receptors, PPARs are sensitive to exposure to xenobiotic compounds, called endocrine disruptions, even at low concentrations that could alter their homeostasis. Among these, food contact materials (FCMs), like phthalates, are synthetic compounds able to migrate from packaging to food and represent a significant source of exposure because of the increased use of plastic in the packaging in the last years. Through multiple docking and consensus scoring, we can analyse the ligand-binding domain's chemical and physical features, understand the mechanism of activation and predict the interaction with possible endocrine disruptions with an evaluation of their effects.

In Silico Prediction of the Mechanism of Action of Pyriproxyfen and 4'-OH-Pyriproxyfen against A. mellifera and H. sapiens Receptors.

BACKGROUND: Poisoning from pesticides can be extremely hazardous for non-invasive species, such as bees, and humans causing nearly 300,000 deaths worldwide every year. Several pesticides are recognized as endocrine disruptors compounds that alter the production of the normal hormones mainly by acting through their interaction with nuclear receptors (NRs). Among the insecticides, one of the most used is pyriproxyfen. As analogous to the juvenile hormone, the pyriproxyfen acts in the bee's larval growth and creates malformations at the adult organism level. METHODS: This work aims to investigate the possible negative effects of pyriproxyfen and its metabolite, the 4'-OH-pyriproxyfen, on human and bee health. We particularly investigated the mechanism of binding of pyriproxyfen and its metabolite with ultraspiracle protein/ecdysone receptor (USP-EcR) dimer of A. mellifera and the relative heterodimer farnesoid X receptor/retinoid X receptor alpha (FXR-RXRα) of H. sapiens using molecular dynamic simulations. RESULTS: The results revealed that pyriproxyfen and its metabolite, the 4'-OH- pyriproxyfen, stabilize each dimer and resulted in stronger binders than the natural ligands. CONCLUSION: We demonstrated the endocrine interference of two pesticides and explained their possible mechanism of action. Furthermore, in vitro studies should be carried out to evaluate the biological effects of pyriproxyfen and its metabolite.

Rational Design of a User-Friendly Aptamer/Peptide-Based Device for the Detection of Staphylococcus aureus.

The urgent need to develop a detection system for Staphylococcus aureus, one of the most common causes of infection, is prompting research towards novel approaches and devices, with a particular focus on point-of-care analysis. Biosensors are promising systems to achieve this aim. We coupled the selectivity and affinity of aptamers, short nucleic acids sequences able to recognize specific epitopes on bacterial surface, immobilized at high density on a nanostructured zirconium dioxide surface, with the rational design of specifically interacting fluorescent peptides to assemble an easy-to-use detection device. We show that the displacement of fluorescent peptides upon the competitive binding of S. aureus to immobilized aptamers can be detected and quantified through fluorescence loss. This approach could be also applied to the detection of other bacterial species once aptamers interacting with specific antigens will be identified, allowing the development of a platform for easy detection of a pathogen without requiring access to a healthcare environment.

New in Silico Trends in Food Toxicology.

Ever growing numbers of chemicals in food and drinking water make it impossible to address safety by classical approaches in toxicology. In silico chemical methods could be a first-line for hazard characterization, requiring food toxicology to expand the use of approaches currently well applied in medicinal chemistry.

In silico pharmacogenetic approach: The natalizumab case study.

Natalizumab is a humanized monoclonal antibody to α4ß1 integrin and is approved for the treatment of Multiple Sclerosis. In patients there is a great variation in drug response and there is much evidence that genetic contributors play an important role in defining an individual's susceptibility. Natalizumab binds to α4-residues Gln-152, Lys-201, Lys256, and these seem to be essential for its activity. Studies on a range of species in disease model have showed a loss of reactivity when any one of those three residues were different to human. Based on these animal studies, we thought that the single nucleotide polymorphism in the ITGA4 human gene causing a lysine to arginine transversion at amino acid position 256 require further investigations in the context of individual drug susceptibility. So, the aim of our study was to investigate the association between this genetic polymorphism and the resistance to natalizumab. We had applied molecular dynamics simulation to study the possible conformational changes induced by Lys256Arg transversion on the overall structure of integrin and we have analyzed the binding affinities of natalizumab in the non-mutated and mutated structures through HINT score. We found that this SNP does not affect the VLA4-natalizumab interaction. Instead, the binding affinities are slightly higher in the mutated complex than in the wild-type. We reported one of the first work in which MD simulation was applied in the pharmacogenetic context, and this approach is rapid and cost effective, since a population survey is carried out only after the positive prediction of simulation.

Development and validation of hydrophobic molecular fields derived from the quantum mechanical IEF/PCM-MST solvation models in 3D-QSAR.

Since the development of structure-activity relationships about 50 years ago, 3D-QSAR methods belong to the most refined ligand-based in silico techniques for prediction of biological data using physicochemical molecular fields. In this scenario, this study reports the development and validation of quantum mechanical (QM)-based hydrophobic descriptors derived from the parametrized MST continuum solvation model to be used in 3D-QSAR studies within the framework of the Hydrophobic Pharmacophore (HyPhar) method. To this end, five sets of compounds reported in the literature (dopamine D2/D4 antagonists, antifungal 2-aryl-4-chromanones, and inhibitors of GSK-3, cruzain and thermolysin) have been revisited. The results derived from the QM/MST-based hydrophobic descriptors have been compared with previous CoMFA and CoMSIA studies, and examined in light of the available X-ray crystallographic structures of the targets. The analysis reveals that the combination of electrostatic and nonelectrostatic components of the octanol/water partition coefficient yields pharmacophoric models fully comparable with the predictive potential of standard 3D-QSAR techniques. Moreover, the graphical representation of the hydrophobic maps provides a direct linkage with the pattern of interactions found in crystallographic structures. Overall, the introduction of the QM/MST-based descriptors, which could be easily adapted to other continuum solvation formalisms, paves the way to novel computational strategies for disclosing structure-activity relationships in drug design. © 2016 Wiley Periodicals, Inc.

Expanding the chemical space of human serine racemase inhibitors.

Serine racemase, the enzyme responsible for d-serine synthesis in the central nervous system, has been identified as a potential therapeutic target to treat N-methyl-d-aspartate receptors-related pathologies. The search for specific inhibitors of the enzyme has revealed that serine racemase is a difficult target, with the best inhibitor currently identified, 2,2-dichloromalonate, showing a Ki of 19 µM. In order to expand the chemical space of hit compounds, we have performed an in silico structure-based screening campaign on a filtered ZINC library applying the FLAP software. The identified hits were docked with GOLD and re-scored with HINT, and the most promising molecules experimentally evaluated on recombinant human serine racemase. Two inhibitors, with chemical structures totally unrelated to inhibitors described so far showed Ki values of about 1.5 mM.

Fine tuning of the active site modulates specificity in the interaction of O-acetylserine sulfhydrylase isozymes with serine acetyltransferase.

O-acetylserine sulfhydrylase (OASS) catalyzes the synthesis of l-cysteine in the last step of the reductive sulfate assimilation pathway in microorganisms. Its activity is inhibited by the interaction with serine acetyltransferase (SAT), the preceding enzyme in the metabolic pathway. Inhibition is exerted by the insertion of SAT C-terminal peptide into the OASS active site. This action is effective only on the A isozyme, the prevalent form in enteric bacteria under aerobic conditions, but not on the B-isozyme, the form expressed under anaerobic conditions. We have investigated the active site determinants that modulate the interaction specificity by comparing the binding affinity of thirteen pentapeptides, derived from the C-terminal sequences of SAT of the closely related species Haemophilus influenzae and Salmonella typhimurium, towards the corresponding OASS-A, and towards S. typhimurium OASS-B. We have found that subtle changes in protein active sites have profound effects on protein-peptide recognition. Furthermore, affinity is strongly dependent on the pentapeptide sequence, signaling the relevance of P3-P4-P5 for the strength of binding, and P1-P2 mainly for specificity. The presence of an aromatic residue at P3 results in high affinity peptides with K(diss) in the micromolar and submicromolar range, regardless of the species. An acidic residue, like aspartate at P4, further strengthens the interaction and results in the higher affinity ligand of S. typhimurium OASS-A described to date. Since OASS knocked-out bacteria exhibit a significantly decreased fitness, this investigation provides key information for the development of selective OASS inhibitors, potentially useful as novel antibiotic agents.

Preliminary hazard evaluation of androgen receptor-mediated endocrine-disrupting effects of thioxanthone metabolites through structure-based molecular docking.

Foodstuff could be a vector for naturally occurring and/or unwanted dangerous substances that can act either as they are or after their bioactivation. The scientific community agrees that the metabolic activity of chemicals should be taken into account for proper risk assessment. Unfortunately, the in vitro evaluation of a metabolic panel and analytical/biochemical detection in food-safety assessment are very expensive and challenging because of the abundance of data to analyze. In this context, properly validated computational protocols could be a useful tool for making metabolic and binding/activity predictions. This strategy has been applied to thioxanthone photoinitiators (TX), identified as food contaminants, especially in infant formulas, as reported by the European Food Safety Authority in 2005. Their lipophilicity suggests rapid hepatic metabolism, but the currently available data only concern 2-ITX. We have predicted phase I metabolites for the TX class of compounds and defined their binding affinity for the AR ligand-binding pocket using a local model based on available information about metabolism and AR activity. Some metabolites should undergo further in vitro or/and in vivo toxicological evaluations because they have proved to be suitable as ligands for AR.

Chemogenomics of pyridoxal 5'-phosphate dependent enzymes.

Pyridoxal 5'-phosphate (PLP) dependent enzymes comprise a large family that plays key roles in amino acid metabolism and are acquiring an increasing interest as drug targets. For the identification of compounds inhibiting PLP-dependent enzymes, a chemogenomics-based approach has been adopted in this work. Chemogenomics exploits the information coded in sequences and three-dimensional structures to define pharmacophore models. The analysis was carried out on a dataset of 65 high-resolution PLP-dependent enzyme structures, including representative members of four-fold types. Evolutionarily conserved residues relevant to coenzyme or substrate binding were identified on the basis of sequence-structure comparisons. A dataset was obtained containing the information on conserved residues at substrate and coenzyme binding site for each representative PLP-dependent enzyme. By linking coenzyme and substrate pharmacophores, bifunctional pharmacophores were generated that will constitute the basis for future development of small inhibitors targeting specific PLP-dependent enzymes.

Hint approach on Transthyretin folding/unfolding mechanism comprehension.

Non-covalent intramolecular interactions play a key role in the protein folding process. Aminoacidic mutations or changes in physiological conditions such as pH and/or temperature variations can compromise intramolecular stability generating misfolding or unfolding proteins with consequent impairment of functionality and the triggering of pathological states. The intramolecular HINT scoring function recently implemented and validated, is proposed as a rapid and sensitive method for the evaluation of different conformational states characterizing destabilization processes. In this work, the stability of Transthyretin, whose denaturation is related to amyloid fibril formation, is evaluated by generating multiple structural mutated models under different pH conditions in comparison with experimental data. These results suggest that the HINT scoring function can be used for an accurate and rapid evaluation and computational prediction of the effects of structural changes on any protein system.

How a Blockchain Approach Can Improve Data Reliability in the COVID-19 Pandemic.

The rapid spread of COVID-19 made it necessary to quickly collect and share viral genomic sequences, sometimes making quantity prevail over the quality of information. Can research pay this price? Blockchain technology, based on the concept of a ledger that guarantees the authenticity and traceability of information, could be the best applicable solution.

Computational methods on food contact chemicals: Big data and in silico screening on nuclear receptors family.

According to Eurostat, the EU production of chemicals hazardous to health reached 211 million tonnes in 2019. Thus, the possibility that some of these chemical compounds interact negatively with the human endocrine system has received, especially in the last decade, considerable attention from the scientific community. It is obvious that given the large number of chemical compounds it is impossible to use in vitro/in vivo tests for identifying all the possible toxic interactions of these chemicals and their metabolites. In addition, the poor availability of highly curated databases from which to retrieve and download the chemical, structure, and regulative information about all food contact chemicals has delayed the application of in silico methods. To overcome these problems, in this study we use robust computational approaches, based on a combination of highly curated databases and molecular docking, in order to screen all food contact chemicals against the nuclear receptor family in a cost and time-effective manner.

Risk-benefit in food safety and nutrition - Outcome of the 2019 Parma Summer School.

Risk-benefit assessment is the comparison of the risk of a situation to its related benefits, i.e. a comparison of scenarios estimating the overall health impact. The risk-benefit analysis paradigm mirrors the classical risk analysis one: risk-benefit assessment goes hand-in-hand with risk-benefit management and risk-benefit communication. The various health effects associated with food consumption, together with the increasing demand for advice on healthy and safe diets, have led to the development of different research disciplines in food safety and nutrition. In this sense, there is a clear need for a holistic approach, including and comparing all of the relevant health risks and benefits. The risk-benefit assessment of foods is a valuable approach to estimate the overall impact of food on health. It aims to assess together the negative and positive health effects associated with food intake by integrating chemical and microbiological risk assessment with risk and benefit assessment in food safety and nutrition. The 2019 Parma Summer School on risk-benefit in food safety and nutrition had the objective was to provide an opportunity to learn from experts in the field of risk-benefit approach in food safety and nutrition, including theory, case studies, and communication of risk-benefit assessments plus identify challenges for the future. It was evident that whereas tools and approaches have been developed, more and more case studies have been performed which can form an inherent validation of the risk-benefit approach. Executed risk-benefit assessment case studies apply the steps and characteristics developed: a problem formulation (with at least 2 scenarios), a tiered approach until a decision can be made, one common currency to describe both beneficial and adverse effects (DALYs in most instances). It was concluded that risk-benefit assessment in food safety and nutrition is gaining more and more momentum, while also many challenges remain for the future. Risk-benefit is on the verge of really enrolling into the risk assessment and risk analysis paradigm. The interaction between risk-benefit assessors and risk-benefit managers is pivotal in this, as is the interaction with risk-benefit communicators.