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. Computed RBD-ACE2-binding affinities were higher for two ACE2 polymorphisms (rs142984500 and rs4646116) typically found in Europeans which indicates a genetic susceptibility. This is amplified for Omicron (BA.1) and its sublineages BA.2 and BA.3. The antibody landscape was computationally investigated with the largest set of mAbs so far in the literature. From the 32 studied binders, groups of mAbs were identified from weak to strong binding affinities (e.g. S2K146). These mAbs with strong binding capacity and especially their combination are amenable to experimentation and clinical trials because of their high predicted binding affinities and possible neutralization potential for current known virus mutations and a universal coronavirus.Communicated by Ramaswamy H. Sarma.

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. In the present study, we have used a computational approach to explore the dynamical properties of the nonstructural protein 1 from two strains of Zika virus. Our results show that despite a high sequence similarity, the two viral proteins from different origins can exhibit significant dissimilar structural dynamics, which complement their reported differential virulence. The present study opens up new ways in the understanding of the infectivity for these biological entities.

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. A combination of theoretical methods was employed. Constant-pH Monte Carlo simulations were carried out to quantify the stability of several spike trimeric structures at different conformational states and the free energy of interactions between the receptor-binding domain (RBD) and angiotensin-converting enzyme II (ACE2) for the most worrying variants. Electrostatic epitopes were mapped using the PROCEEDpKa method. These analyses showed that the increased virulence is more likely to be due to the improved stability to the S trimer in the opened state, in which the virus can interact with the cellular receptor, ACE2, rather than due to alterations in the complexation RBD-ACE2, since the difference observed in the free energy values was small (although more attractive in general). Conversely, the South African/Beta variant (B.1.351), compared with the SARS-CoV-2 wild type (wt), is much more stable in the opened state with one or two RBDs in the up position than in the closed state with three RBDs in the down position favoring the infection. Such results contribute to understanding the natural history of disease and indicate possible strategies for developing new therapeutic molecules and adjusting the vaccine doses for higher B-cell antibody production.

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. This review highlights several examples of advanced computer simulations at molecular, mesoscale, and multiscale levels that shed light on the mechanisms at play in foods, thereby facilitating their control. It includes a practical simulation toolbox for those new to in silico modeling.

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. By means of the coupling between the successful OPEP force field for proteins with the fast proton titration scheme, we proposed a new protocol for constant-pH molecular dynamics simulations that takes advantage of both coarse-grained approaches to circumvent sampling difficulties faced by other numerical schemes and also to be able to properly describe electrostatic and structural properties at lower CPU costs. Here, we introduce this new protocol that defines now OPEP6 and its p Ka's benchmark for a set of representative proteins (HP36, BBL, HEWL, NTL9, and a protein G variant). In comparison with experimental measurements, our calculated p Ka values have the average, maximum absolute, and root-mean-square deviations of [0.3-1.1], [0.6-2.5], and [0.4-1.3] pH units, respectively, for these five studied proteins. These numbers are within the ones commonly observed when similar comparisons are done among different theoretical models and are slightly better than the accuracy obtained by a rigid model using the same titration engine. For BBL, the predicted p Ka are closer to experimental results than other analyzed theoretical data. Structural properties were tested for insulin where separation distances between the groups were compared and found in agreement with experimental crystallographic data obtained at different pH conditions. These indicate the ability of the new OPEP to properly describe the system physics and open up more possibilities to study pH-mediated biological processes.

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. This charge regulation mechanism due to titrating amino acid and nucleotides residues is discussed here in a purely electrostatic framework. By means of constant-pH Monte Carlo simulations based on a fast coarse-grained titration proton scheme, a new computer molecular model was devised to study protein-RNA interactions. The complexation between the RNA silencing suppressor p19 viral protein and the 19-bp small interfering RNA was investigated at different solution pH and salt conditions. The outcomes illustrate the importance of the charge regulation mechanism that enhances the association between these macromolecules in a similar way as observed for other protein-polyelectrolyte systems typically found in colloidal science. Due to the highly negative charge of RNA, the effect is more pronounced in this system as predicted by the Kirkwood-Shumaker theory. Our results contribute to the general physico-chemical understanding of macromolecular complexation and shed light on the extensive role of RNA in the cell's life.

Computationally Mapping pKa 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. Colloid Interface Sci. 2004 , 9 , 340 ; De Vries et al. J. Chem. Phys. 2003 , 118 , 4649 ; Grymonpre et al. Biomacromolecules 2001 , 2 , 422 ; Hattori et al. Langmuir 2000 , 16 , 9738 ). This attractive phenomenon has often been described as "complexation on the wrong side of pI". While one theory assumes the existence of "charged patches" on the protein surface from ion-dipole interactions, thus allowing a polyelectrolyte to bind to an oppositely heterogeneous charged protein region, another theoretical view considers the induced-charge interactions to be the dominant factor in these complexations. This charge regulation mechanism can be described by proton fluctuations resulting from mutual rearrangements of the distributions of the charged groups, due to perturbations of the acid-base equilibrium. Using constant-pH Monte Carlo simulations and several quantitative and visual analysis tools, we investigate the significance of each of these interactions for two whey proteins, α-lactalbumin (α-LA) and lysozyme (LYZ). Through physical chemistry parameters, free energies of interactions, and the mapping of amino acid pKa shifts and polyelectrolyte trajectories, we show the charge regulation mechanism to be the most important contributor in protein-polyelectrolyte complexation regardless of pH, dipole moment, and protein capacitance in a low salt regime.

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. Predicting the structure of large proteins and complexes remains a great challenge experimentally, industrially, and theoretically, despite the variety of numerical schemes available ranging from Poisson-Boltzmann approaches to explicit solvent based methods. In this work we benchmark a fast proton titration scheme against experiment and several theoretical methods on the following set of representative proteins: [HP36, BBL, HEWL (triclinic and orthorhombic), RNase, SNASE (V66K/WT, V66K/PHS, V66K/Δ+PHS, L38D/Δ+PHS, L38E/Δ+PHS, L38K/Δ+PHS), ALAC, and OMTKY3]; routinely used in similar tests due to the diversity of their structural features. Our scheme is rooted in the classical Tanford-Kirkwood model of impenetrable spheres, where salt is treated at the Debye-Hückel level. Treating salt implicitly dramatically reduces the computation time, thereby circumventing sampling difficulties faced by other numerical schemes. In comparison with experimental measurements, our calculated pKa values have the average, maximum absolute, and root-mean-square deviations of 0.4-0.9, 1.0-5.2, and 0.5-1.2 pH units, respectively. These values are within the ranges commonly observed in theoretical models. They are also in the large majority of the cases studied here more accurate than the NULL model. For BBL, ALAC, and OMTKY3, the predicted pKa are closer to experimental results than other analyzed theoretical data. Despite the intrinsic approximations of the fast titration scheme, its robustness and ability to properly describe the main system physics is confirmed.

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 pKa shifts. In comparison with other theoretical approaches, similar or even better outcomes are achieved at much lower computational costs. The model was tested on the lead-dependent ribozyme, the branch-point helix, and the domain 5 from Azotobacter vinelandii Intron 5.

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. A detailed analysis of the electrostatic properties and free energy derivatives for the NTD homoassociation was carried out at different pH values and salt concentrations for the protein wild type and for several mutants. We observed an enhancement of dipole-dipole interactions at pH 6 due to the ionization of key amino acids, a process identified as the main driving force for dimerization. Analytical estimates based on the DVLO theory framework corroborate our findings. Molecular dynamics simulations using the OPEP coarse-grained force field for proteins show that the mutant E17Q is subject to larger structural fluctuations when compared to the wild type. Estimates of the association rate constants for this mutant were evaluated by the Debye-Smoluchowski theory and are in agreement with the experimental data when thermally relaxed structures are used instead of the crystallographic data. Our results can contribute to the design of new mutants with specific association properties.

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 ß-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. Thus, very small variations in salt concentration strongly influence the origin of complexation.