Differences between Omicron SARS-CoV-2 RBD and other variants in their ability to interact with cell receptors and monoclonal antibodies.

SARS-CoV-2 remains a health threat with the continuous emergence of new variants. This work aims to expand the knowledge about the SARS-CoV-2 receptor-binding domain (RBD) interactions with cell receptors and monoclonal antibodies (mAbs). By using constant-pH Monte Carlo simulations, the free energy of interactions between the RBD from different variants and several partners (Angiotensin-Converting Enzyme-2 (ACE2) polymorphisms and various mAbs) were predicted.

Up State of the SARS-COV-2 Spike Homotrimer Favors an Increased Virulence for New Variants.

The COVID-19 pandemic has spread worldwide. However, as soon as the first vaccines-the only scientifically verified and efficient therapeutic option thus far-were released, mutations combined into variants of SARS-CoV-2 that are more transmissible and virulent emerged, raising doubts about their efficiency. This study aims to explain possible molecular mechanisms responsible for the increased transmissibility and the increased rate of hospitalizations related to the new variants.

How the Strain Origin of Zika Virus NS1 Protein Impacts Its Dynamics and Implications to Their Differential Virulence.

Viruses can impact and affect human populations in a severe way. The appropriate differentiation among several species or strains of viruses is one of the biggest challenges for virology and infectiology studies. The detection of measurables-quantified discrepancies allows for more accurate clinical diagnoses and treatments for viral diseases.

Understanding and Controlling Food Protein Structure and Function in Foods: Perspectives from Experiments and Computer Simulations.

The structure and interactions of proteins play a critical role in determining the quality attributes of many foods, beverages, and pharmaceutical products. Incorporating a multiscale understanding of the structure-function relationships of proteins can provide greater insight into, and control of, the relevant processes at play. Combining data from experimental measurements, human sensory panels, and computer simulations through machine learning allows the construction of statistical models relating nanoscale properties of proteins to the physicochemical properties, physiological outcomes, and tastes of foods.

OPEP6: A New Constant-pH Molecular Dynamics Simulation Scheme with OPEP Coarse-Grained Force Field.

The great importance of pH for molecular processes has motivated the continuous development of numerical methods to improve the physical description of molecular mechanisms in computer simulations. Although rigid titration models are able to provide several pieces of useful information, the coupling between the molecular conformational changes and the acid-base equilibrium is necessary to more completely model the pH effects in biomolecules. Previously reported convergence issues with atomistic simulations indicated that a promising approach would require coarse-grained models.

Development of constant-pH simulation methods in implicit solvent and applications in biomolecular systems.

pH is a critical parameter for biological and technological systems directly related with electrical charges. It can give rise to peculiar electrostatic phenomena, which also makes them more challenging. Due to the quantum nature of the process, involving the forming and breaking of chemical bonds, quantum methods should ideally by employed.

Computationally Mapping pK Shifts Due to the Presence of a Polyelectrolyte Chain around Whey Proteins.

Experimental studies have shown the formation of soluble complexes in the pure repulsive Coulombic regime even when the net charges of the protein and the polyelectrolyte have the same sign ( De Kruif et al. Curr. Opin.

Protein-RNA complexation driven by the charge regulation mechanism.

Electrostatic interactions play a pivotal role in many (bio)molecular association processes. The molecular organization and function in biological systems are largely determined by these interactions from pure Coulombic contributions to more peculiar mesoscopic forces due to ion-ion correlation and proton fluctuations. The latter is a general electrostatic mechanism that gives attraction particularly at low electrolyte concentrations.

Benchmarking a Fast Proton Titration Scheme in Implicit Solvent for Biomolecular Simulations.

pH is a key parameter for technological and biological processes, intimately related to biomolecular charge. As such, it controls biomolecular conformation and intermolecular interactions, for example, protein/RNA stability and folding, enzyme activity, regulation through conformational switches, protein-polyelectrolyte association, and protein-RNA interactions. pH also plays an important role in technological systems in food, brewing, pharma, bioseparations, and biomaterials in general.

Fast coarse-grained model for RNA titration.

A new numerical scheme for RNA (ribonucleic acid) titration based on the Debye-Hückel framework for the salt description is proposed in an effort to reduce the computational costs for further applications to study protein-RNA systems. By means of different sets of Monte Carlo simulations, we demonstrated that this new scheme is able to correctly reproduce the experimental titration behavior and salt pK shifts. In comparison with other theoretical approaches, similar or even better outcomes are achieved at much lower computational costs.

Electrostatics analysis of the mutational and pH effects of the N-terminal domain self-association of the major ampullate spidroin.

Spider silk is a fascinating material combining mechanical properties such as maximum strength and high toughness comparable or better than man-made materials, with biocompatible degradability characteristics. Experimental measurements have shown that pH triggers the dimer formation of the N-terminal domain (NTD) of the major ampullate spidroin 1 (MaSp 1). A coarse-grained model accounting for electrostatics, van der Waals and pH-dependent charge-fluctuation interactions, by means of Monte Carlo simulations, gave us a more comprehensive view of the NTD dimerization process.

Effect of charge regulation and ion-dipole interactions on the selectivity of protein-nanoparticle binding.

We investigate the role of different mesoscopic interactions (Coulomb, charge regulation, and ion-dipole "surface patch" effects) on the binding of bovine serum albumin (BSA) and β-lactoglobulin (BLG) to a cationic gold nanoparticle (TTMA+). The results demonstrate that the charge-regulation mechanism plays a vital role for selectivity of protein-nanoparticle complexation at low salt concentration. At slightly higher ionic strengths, charge-dipole effects are the dominating driving force.

Multiobjective evolutionary algorithm with many tables for purely ab initio protein structure prediction.

This article focuses on the development of an approach for ab initio protein structure prediction (PSP) without using any earlier knowledge from similar protein structures, as fragment-based statistics or inference of secondary structures. Such an approach is called purely ab initio prediction. The article shows that well-designed multiobjective evolutionary algorithms can predict relevant protein structures in a purely ab initio way.

Fast Proton Titration Scheme for Multiscale Modeling of Protein Solutions.

Proton exchange between titratable amino acid residues and the surrounding solution gives rise to exciting electric processes in proteins. We present a proton titration scheme for studying acid-base equilibria in Metropolis Monte Carlo simulations where salt is treated at the Debye-Hückel level. The method, rooted in the Kirkwood model of impenetrable spheres, is applied on the three milk proteins α-lactalbumin, β-lactoglobulin, and lactoferrin, for which we investigate the net-charge, molecular dipole moment, and charge capacitance.

Protein-ion binding process on finite macromolecular concentration. A Poisson-Boltzmann and Monte Carlo study.

Electrostatic interactions are one of the key driving forces for protein-ligands complexation. Different levels for the theoretical modeling of such processes are available on the literature. Most of the studies on the Molecular Biology field are performed within numerical solutions of the Poisson-Boltzmann Equation and the dielectric continuum models framework.

Monte Carlo and modified Tanford-Kirkwood results for macromolecular electrostatics calculations.

The understanding of electrostatic interactions is an essential aspect of the complex correlation between structure and function of biological macromolecules. It is also important in protein engineering and design. Theoretical studies of such interactions are predominantly done within the framework of Debye-Hückel theory.