Atomistic adsorption of PETase onto large-scale PET 3D-models that mimic reality.

Polyethylene terephthalate (PET) has been widely used in plastic products, leading to massive PET waste accumulation in ecosystems worldwide. Efforts to find greener processes for dealing with post-consumer PET waste led to the discovery of PET-degrading enzymes such as PETase (PETase). studies have provided valuable contributions to this field, shedding light on the catalytic mechanisms and substrate interactions in many PET hydrolase enzymes.

Functional dynamics of G protein-coupled receptors reveal new routes for drug discovery.

G protein-coupled receptors (GPCRs) are the largest human membrane protein family that transduce extracellular signals into cellular responses. They are major pharmacological targets, with approximately 26% of marketed drugs targeting GPCRs, primarily at their orthosteric binding site. Despite their prominence, predicting the pharmacological effects of novel GPCR-targeting drugs remains challenging due to the complex functional dynamics of these receptors.

Molecular basis of the CYFIP2 and NCKAP1 autism-linked variants in the WAVE regulatory complex.

The WAVE regulatory pentameric complex regulates actin remodeling. Two components of it (CYFIP2 and NCKAP1) are encoded by genes whose genetic mutations increase the risk for autism spectrum disorder (ASD) and related neurodevelopmental disorders. Here, we use a newly developed computational protocol and hotspot analysis to uncover the functional impact of these mutations at the interface of the correct isoforms of the two proteins into the complex.

Impact of Phosphorylation on the Physiological Form of Human alpha-Synuclein in Aqueous Solution.

Serine 129 can be phosphorylated in pathological inclusions formed by the intrinsically disordered protein human α-synuclein (AS), a key player in Parkinson's disease and other synucleinopathies. Here, molecular simulations provide insight into the structural ensemble of phosphorylated AS. The simulations allow us to suggest that phosphorylation significantly impacts the structural content of the physiological AS conformational ensemble in aqueous solution, as the phosphate group is mostly solvated.

Transport mechanism of DgoT, a bacterial homolog of SLC17 organic anion transporters.

The solute carrier 17 (SLC17) family contains anion transporters that accumulate neurotransmitters in secretory vesicles, remove carboxylated monosaccharides from lysosomes, or extrude organic anions from the kidneys and liver. We combined classical molecular dynamics simulations, Markov state modeling and hybrid first principles quantum mechanical/classical mechanical (QM/MM) simulations with experimental approaches to describe the transport mechanisms of a model bacterial protein, the D-galactonate transporter DgoT, at atomic resolution. We found that protonation of D46 and E133 precedes galactonate binding and that substrate binding induces closure of the extracellular gate, with the conserved R47 coupling substrate binding to transmembrane helix movement.

MiMiC: A high-performance framework for multiscale molecular dynamics simulations.

MiMiC is a framework for performing multiscale simulations in which loosely coupled external programs describe individual subsystems at different resolutions and levels of theory. To make it highly efficient and flexible, we adopt an interoperable approach based on a multiple-program multiple-data (MPMD) paradigm, serving as an intermediary responsible for fast data exchange and interactions between the subsystems. The main goal of MiMiC is to avoid interfering with the underlying parallelization of the external programs, including the operability on hybrid architectures (e.

Impact of quantum and neuromorphic computing on biomolecular simulations: Current status and perspectives.

New high-performance computing architectures are becoming operative, in addition to exascale computers. Quantum computers (QC) solve optimization problems with unprecedented efficiency and speed, while neuromorphic hardware (NMH) simulates neural network dynamics. Albeit, at the moment, both find no practical use in all atom biomolecular simulations, QC might be exploited in the not-too-far future to simulate systems for which electronic degrees of freedom play a key and intricate role for biological function, whereas NMH might accelerate molecular dynamics simulations with low energy consumption.

Unlocking the elemental signature of European tea gardens: Implications for tea traceability.

This study presents a comprehensive analysis of the elemental profiles of tea leaves coming from plants grown in several European gardens, with a focus on the bioaccumulation of essential and potentially toxic trace elements in relation to processing and location of tea garden. Samples were collected from various gardens across Europe, including Portugal, the Azores, Germany, the Netherlands, and Switzerland. Elemental analysis was conducted on fresh tea leaves, dried leaves, and leaves processed for the production of green and black tea, along with soil samples from the root zones of tea plants.

Effective data-driven collective variables for free energy calculations from metadynamics of paths.

A variety of enhanced sampling (ES) methods predict multidimensional free energy landscapes associated with biological and other molecular processes as a function of a few selected collective variables (CVs). The accuracy of these methods is crucially dependent on the ability of the chosen CVs to capture the relevant slow degrees of freedom of the system. For complex processes, finding such CVs is the real challenge.

All-Atom Biomolecular Simulation in the Exascale Era.

Exascale supercomputers have opened the door to dynamic simulations, facilitated by AI/ML techniques, that model biomolecular motions over unprecedented length and time scales. This new capability holds the potential to revolutionize our understanding of fundamental biological processes. Here we report on some of the major advances that were discussed at a recent CECAM workshop in Pisa, Italy, on the topic with a primary focus on atomic-level simulations.

First ATR-FTIR Characterization of Black, Green and White Teas () from European Tea Gardens: A PCA Analysis to Differentiate Leaves from the In-Cup Infusion.

ATR-FTIR (Attenuated Total Reflectance Fourier Transform InfraRed) spectroscopy, combined with chemometric, represents a rapid and reliable approach to obtain information about the macromolecular composition of food and plant materials. With a single measurement, the chemical fingerprint of the analyzed sample is rapidly obtained. Hence, this technique was used for investigating 13 differently processed tea leaves (green, black and white) all grown and processed in European tea gardens, and their vacuum-dried tea brews, prepared using both hot and cold water, to observe how the components differ from tea leaf to the in-cup infusion.

Unexpected Single-Ligand Occupancy and Negative Cooperativity in the SARS-CoV-2 Main Protease.

Many homodimeric enzymes tune their functions by exploiting either negative or positive cooperativity between subunits. In the SARS-CoV-2 Main protease (Mpro) homodimer, the latter has been suggested by symmetry in most of the 500 reported protease/ligand complex structures solved by macromolecular crystallography (MX). Here we apply the latter to both covalent and noncovalent ligands in complex with Mpro.

Insights on the Nutraceutical Properties of Different Specialty Teas Grown and Processed in a German Tea Garden.

European countries have recently started experimenting with growing and producing their own teas in small quantities, mainly for the specialty tea sector. To characterize European teas, this study investigated a set of five tea types obtained from different varieties/cultivars, representing various oxidation grades (green, white, yellow, oolong, black), all grown and processed in the only tea garden in Europe (in Germany) that focuses on all five types. Hot and cold brews were studied by measuring the total phenolic (TPC) and flavonoid contents (TFC), the antioxidant capacity and UV-Vis spectra, also with the objective of discriminating between the different tea types and the different plant varieties.

Physical Chemistry of Chloroquine Permeation through the Cell Membrane with Atomistic Detail.

We provide a molecular-level description of the thermodynamics and mechanistic aspects of drug permeation through the cell membrane. As a case study, we considered the antimalaria FDA approved drug chloroquine. Molecular dynamics simulations of the molecule (in its neutral and protonated form) were performed in the presence of different lipid bilayers, with the aim of uncovering key aspects of the permeation process, a fundamental step for the drug's action.

Free energies at QM accuracy from force fields via multimap targeted estimation.

Accurate predictions of ligand binding affinities would greatly accelerate the first stages of drug discovery campaigns. However, using highly accurate interatomic potentials based on quantum mechanics (QM) in free energy methods has been so far largely unfeasible due to their prohibitive computational cost. Here, we present an efficient method to compute QM free energies from simulations using cheap reference potentials, such as force fields (FFs).

Kinetic and structural details of urease inactivation by thiuram disulphides.

This paper reports on the molecular details of the reactivity of urease, a nickel-dependent enzyme that catalyses the last step of organic nitrogen mineralization, with thiuram disulphides, a class of molecules known to inactivate the enzyme with high efficacy but for which the mechanism of action had not been yet established. IC values of tetramethylthiuram disulphide (TMTD or Thiram) and tetraethylthiuram disulphide (TETD or Disulfiram) in the low micromolar range were determined for plant and bacterial ureases. The X-ray crystal structure of Sporosarcina pasteurii urease inactivated by Thiram, determined at 1.

A community effort in SARS-CoV-2 drug discovery.

The COVID-19 pandemic continues to pose a substantial threat to human lives and is likely to do so for years to come. Despite the availability of vaccines, searching for efficient small-molecule drugs that are widely available, including in low- and middle-income countries, is an ongoing challenge. In this work, we report the results of an open science community effort, the "Billion molecules against COVID-19 challenge", to identify small-molecule inhibitors against SARS-CoV-2 or relevant human receptors.

Performance of Family Health Strategy Nurses in LGBT+ Healthcare.

Objective: To analyze the role of Family Health Strategy (FHS) nurses in the health care of LGBT+ individuals.

Methods: This qualitative study is based on Institutional Analysis. Data was collected in August 2021 through semi-structured interviews with 14 Family Health Strategy nurses from municipalities in the state of São Paulo.

Low Molecular Weight Inhibitors Targeting the RNA-Binding Protein HuR.

The RNA-binding protein human antigen R (HuR) regulates stability, translation, and nucleus-to-cytoplasm shuttling of its target mRNAs. This protein has been progressively recognized as a relevant therapeutic target for several pathologies, like cancer, neurodegeneration, as well as inflammation. Inhibitors of mRNA binding to HuR might thus be beneficial against a variety of diseases.

Fluoride permeation mechanism of the Fluc channel in liposomes revealed by solid-state NMR.

Solid-state nuclear magnetic resonance (ssNMR) methods can probe the motions of membrane proteins in liposomes at the atomic level and propel the understanding of biomolecular processes for which static structures cannot provide a satisfactory description. In this work, we report our study on the fluoride channel Fluc-Ec1 in phospholipid bilayers based on ssNMR and molecular dynamics simulations. Previously unidentified fluoride binding sites in the aqueous vestibules were experimentally verified by F-detected ssNMR.

AI-based identification of therapeutic agents targeting GPCRs: introducing ligand type classifiers and systems biology.

Identifying ligands targeting G protein coupled receptors (GPCRs) with novel chemotypes other than the physiological ligands is a challenge for screening campaigns. Here we present an approach that identifies novel chemotype ligands by combining structural data with a random forest agonist/antagonist classifier and a signal-transduction kinetic model. As a test case, we apply this approach to identify novel antagonists of the human adenosine transmembrane receptor type 2A, an attractive target against Parkinson's disease and cancer.

Comparative Analysis of Hot and Cold Brews from Single-Estate Teas () Grown across Europe: An Emerging Specialty Product.

Tea is grown around the world under extremely diverse geographic and climatic conditions, namely, in China, India, the Far East and Africa. However, recently, growing tea also appears to be feasible in many regions of Europe, from where high-quality, chemical-free, organic, single-estate teas have been obtained. Hence, the aim of this study was to characterize the health-promoting properties in terms of the antioxidant capacity of traditional hot brews as well as cold brews of black, green and white teas produced across the European territory using a panel of antioxidant assays.

Survey of Oral Hygiene Habits and Knowledge among School Children: a cross-sectional study from Italy.

Aim: This study is aimed to investigate the oral hygiene practice, knowledge and attitude of young adults, assessing their awareness about the impact of a certain "risk" behaviour on their oral and dental health.

Materials: This is a cross-sectional survey study conducted on 829 students (350 males and 479 females, mean age 13-20 years) attending high school in Milan and surrounding areas. They were asked to complete anonymous questionnaire during the first semester of the 2019-2020 school year, under the supervision of a teacher and/or an assigned interviewer.

Drug Design in the Exascale Era: A Perspective from Massively Parallel QM/MM Simulations.

The initial phases of drug discovery - drug design - could benefit from first principle Quantum Mechanics/Molecular Mechanics (QM/MM) molecular dynamics (MD) simulations in explicit solvent, yet many applications are currently limited by the short time scales that this approach can cover. Developing scalable first principle QM/MM MD interfaces fully exploiting current exascale machines - so far an unmet and crucial goal - will help overcome this problem, opening the way to the study of the thermodynamics and kinetics of ligand binding to protein with first principle accuracy. Here, taking two relevant case studies involving the interactions of ligands with rather large enzymes, we showcase the use of our recently developed massively scalable Multiscale Modeling in Computational Chemistry (MiMiC) QM/MM framework (currently using DFT to describe the QM region) to investigate reactions and ligand binding in enzymes of pharmacological relevance.