The Potential of Molecular Docking for Predictive Toxicology.

Molecular modeling techniques are widely used in medicinal chemistry for the study of biological targets, the rational design of new drugs, or the investigation of their mechanism of action.They are also applied in toxicology to identify chemical potential harmful effects.Molecular docking is a computational technique to predict the ligand binding mode and evaluate the interaction energy with a biological target.

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.

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.

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.

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.

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.

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

Peroxisome proliferator-activated receptors (PPARs), with the , / 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.

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.

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.

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.

In Silico Prediction of the Mechanism of Action of Pyriproxyfen and 4'-OH-Pyriproxyfen against and 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.

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.

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.

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

The urgent need to develop a detection system for , 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.

Molecular modelling methods in food safety: Bisphenols as case study.

Bisphenol A (BPA), a synthetic compound widely used as a building block for polycarbonate plastics, has been declared in the European Union (EU) as a substance of very high concern (SVHC). A series of BPA alternatives and derivatives (bisphenols/BPs) with similar physical-chemical properties have been produced and used by companies for substituting it. To evaluate the estrogenic and androgenic binding activity of 26 BPs, a non-statistical in silico approach has been applied.

Simulated Gastrointestinal Digestion of Cocoa: Detection of Resistant Peptides and In Silico/In Vitro Prediction of Their Ace Inhibitory Activity.

In this study we investigated the oligopeptide pattern in fermented cocoa beans and derived products after simulated gastrointestinal digestion. Peptides in digested cocoa samples were identified based on the mass fragmentation and on the software analysis of vicilin and 21 KDa cocoa seed protein sequences, the most abundant cocoa proteins. Quantification was carried out by liquid chromatography/electrospray ionisation mass spectrometry (LC/ESI-MS) using an internal standard.

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.

Approaches Applied to the Study of Peptide Analogs of Ile-Pro-Ile in Relation to Their Dipeptidyl Peptidase IV Inhibitory Properties.

Inhibition of dipeptidyl peptidase IV (DPP-IV) may be exploited to maintain the incretin effect during the postprandial phase. As a result, glycemic regulation and energy homeostasis may be improved. Food protein-derived peptides have been identified as natural agents capable of inhibiting DPP-IV.

Molecular insights on xenoestrogenic potential of zearalenone-14-glucoside through a mixed in vitro/in silico approach.

The mycotoxin zearalenone may contaminate food and feed worldwide upon infections by Fusarium spp. of plants and raw materials intended for human and animal consumption. Currently, contamination by zearalenone and congeners pose concern for health due to xenoestrogenic effects.

In silico pharmacogenetic approach: The natalizumab case study.

Natalizumab is a humanized monoclonal antibody to αβ 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 α-residues Gln-152, Lys-201, Lys256, and these seem to be essential for its activity.

The Roles of Water in the Protein Matrix: A Largely Untapped Resource for Drug Discovery.

The value of thoroughly understanding the thermodynamics specific to a drug discovery/design study is well known. Over the past decade, the crucial roles of water molecules in protein structure, function, and dynamics have also become increasingly appreciated. This Perspective explores water in the biological environment by adopting its point of view in such phenomena.

Assessing the hydrolytic fate of the masked mycotoxin zearalenone-14-glucoside - A warning light for the need to look at the "maskedome".

Masked mycotoxins are plant metabolites of mycotoxins that contaminate food and feed. They pose health concern as the shortage of toxicological data forces the lack of regulation worldwide. The present work investigated the toxicological relevance of the masked mycotoxin zearalenone-14-glucoside.

Application of the quantum mechanical IEF/PCM-MST hydrophobic descriptors to selectivity in ligand binding.

We have recently reported the development and validation of quantum mechanical (QM)-based hydrophobic descriptors derived from the parametrized IEF/PCM-MST continuum solvation model for 3D-QSAR studies within the framework of the Hydrophobic Pharmacophore (HyPhar) method. In this study we explore the applicability of these descriptors to the analysis of selectivity fields. To this end, we have examined a series of 88 compounds with inhibitory activities against thrombin, trypsin and factor Xa, and the HyPhar results have been compared with 3D-QSAR models reported in the literature.