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

Inkjet Printing of Pharmaceuticals

Inkjet printing (IJP) is an additive manufacturing process that selectively deposits ink materials, layer-by-layer, to create 3D objects or 2D patterns with precise control over their structure and composition. This technology has emerged as an attractive and versatile approach to address the ever-evolving demands of personalized medicine in the healthcare industry. Although originally developed for nonhealthcare applications, IJP harnesses the potential of pharma-inks, which are meticulously formulated inks containing drugs and pharmaceutical excipients. Delving into the formulation and components of pharma-inks, the key to precise and adaptable material deposition enabled by IJP is unraveled. The review extends its focus to substrate materials, including paper, films, foams, lenses, and 3D-printed materials, showcasing their diverse advantages, while exploring a wide spectrum of therapeutic applications. Additionally, the potential benefits of hardware and software improvements, along with artificial intelligence integration, are discussed to enhance IJP's precision and efficiency. Embracing these advancements, IJP holds immense potential to reshape traditional medicine manufacturing processes, ushering in an era of medical precision. However, further exploration and optimization are needed to fully utilize IJP's healthcare capabilities. As researchers push the boundaries of IJP, the vision of patient-specific treatment is on the horizon of becoming a tangible reality.

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.

Unusual Aspects of Charge Regulation in Flexible Weak Polyelectrolytes

This article reviews the state of the art of the studies on charge regulation (CR) effects in flexible weak polyelectrolytes (FWPE). The characteristic of FWPE is the strong coupling of ionization and conformational degrees of freedom. After introducing the necessary fundamental concepts, some unconventional aspects of the the physical chemistry of FWPE are discussed. These aspects are: (i) the extension of statistical mechanics techniques to include ionization equilibria and, in particular, the use of the recently proposed Site Binding-Rotational Isomeric State (SBRIS) model, which allows the calculation of ionization and conformational properties on the same foot; (ii) the recent progresses in the inclusion of proton equilibria in computer simulations; (iii) the possibility of mechanically induced CR in the stretching of FWPE; (iv) the non-trivial adsorption of FWPE on ionized surfaces with the same charge sign as the PE (the so-called "wrong side" of the isoelectric point); (v) the influence of macromolecular crowding on CR.

Towards an optimal monoclonal antibody with higher binding affinity to the receptor-binding domain of SARS-CoV-2 spike proteins from different variants

A highly efficient and robust multiple scales in silico protocol, consisting of atomistic Molecular Dynamics (MD), coarse-grain (CG) MD, and constant-pH CG Monte Carlo (MC), has been developed and used to study the binding affinities of selected antigen-binding fragments of the monoclonal antibody (mAbs) CR3022 and several of its here optimized versions against 11 SARS-CoV-2 variants including the wild type. Totally 235,000 mAbs structures were initially generated using the RosettaAntibodyDesign software, resulting in top 10 scored CR3022-like-RBD complexes with critical mutations and compared to the native one, all having the potential to block virus-host cell interaction. Of these 10 finalists, two candidates were further identified in the CG simulations to be the best against all SARS-CoV-2 variants. Surprisingly, all 10 candidates and the native CR3022 exhibited a higher affinity for the Omicron variant despite its highest number of mutations. The multiscale protocol gives us a powerful rational tool to design efficient mAbs. The electrostatic interactions play a crucial role and appear to be controlling the affinity and complex building. Studied mAbs carrying a more negative total net charge show a higher affinity. Structural determinants could be identified in atomistic simulations and their roles are discussed in detail to further hint at a strategy for designing the best RBD binder. Although the SARS-CoV-2 was specifically targeted in this work, our approach is generally suitable for many diseases and viral and bacterial pathogens, leukemia, cancer, multiple sclerosis, rheumatoid, arthritis, lupus, and more.

Electrostatic Features for the Receptor Binding Domain of SARS-COV-2 Wildtype and Its Variants. Compass to the Severity of the Future Variants with the Charge-Rule

Electrostatic intermolecular interactions are important in many aspects of biology. We have studied the main electrostatic features involved in the interaction of the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein with the human receptor Angiotensin-converting enzyme 2 (ACE2). As the principal computational tool, we have used the FORTE approach, capable to model proton fluctuations and computing free energies for a very large number of protein-protein systems under different physical-chemical conditions, here focusing on the RBD-ACE2 interactions. Both the wild-type and all critical variants are included in this study. From our large ensemble of extensive simulations, we obtain, as a function of pH, the binding affinities, charges of the proteins, their charge regulation capacities, and their dipole moments. In addition, we have calculated the pK_as for all ionizable residues and mapped the electrostatic coupling between them. We are able to present a simple predictor for the RBD-ACE2 binding based on the data obtained for Alpha, Beta, Gamma, Delta, and Omicron variants, as a linear correlation between the total charge of the RBD and the corresponding binding affinity. This "RBD charge rule" should work as a quick test of the degree of severity of the coming SARS-CoV-2 variants in the future.

Self-association features of NS1 proteins from different flaviviruses

Flaviviruses comprise a large group of arboviral species that are distributed in several countries of the tropics, neotropics, and some temperate zones. Since they can produce neurological pathologies or vascular damage, there has been intense research seeking better diagnosis and treatments for their infections in the last decades. The flavivirus NS1 protein is a relevant clinical target because it is involved in viral replication, immune evasion, and virulence. Being a key factor in endothelial and tissue-specific modulation, NS1 has been largely studied to understand the molecular mechanisms exploited by the virus to reprogram host cells. A central part of the viral maturation processes is the NS1 oligomerization because many stages rely on these protein-protein assemblies. In the present study, the self-associations of NS1 proteins from Zika, Dengue, and West Nile viruses are examined through constant-pH coarse-grained biophysical simulations. Free energies of interactions were estimated for different oligomeric states and pH conditions. Our results show that these proteins can form both dimers and tetramers under conditions near physiological pH even without the presence of lipids. Moreover, pH plays an important role mainly controlling the regimes where van der Waals interactions govern their association. Finally, despite the similarity at the sequence level, we found that each flavivirus has a well-characteristic protein-protein interaction profile. These specific features can provide new hints for the development of binders both for better diagnostic tools and the formulation of new therapeutic drugs.

Titr-DMD-A Rapid, Coarse-Grained Quasi-All-Atom Constant pH Molecular Dynamics Framework

The pH-dependence of enzyme fold stability and catalytic activity is a fundamentally dynamic, structural property which is difficult to study. The challenges and expense of investigating dynamic, atomic scale behavior experimentally means that computational methods, particularly constant pH molecular dynamics (CpHMD), are well situated tools for this. However, these methods often struggle with affordable sampling of sufficiently long time scales while also obtaining accurate pKa prediction and verifying the structures they generate. We introduce Titr-DMD, an affordable CpHMD method that combines the quasi-all-atom coarse-grained discrete molecular dynamics (DMD) method for conformational sampling with Propka for pKa prediction, to circumvent these issues. The combination enables rapid sampling on limited computational resources, while simulations are still performed on the atomic scale. We benchmark the method on a set of proteins with experimentally attested pKa and on the pH triggered conformational change in a staphylococcal nuclease mutant, a rare experimental study of such behavior. Our results show Titr-DMD to be an effective and inexpensive method to study pH-coupled protein dynamics.

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.

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.

On the interactions of the receptor-binding domain of SARS-CoV-1 and SARS-CoV-2 spike proteins with monoclonal antibodies and the receptor ACE2

A new betacoronavirus named SARS-CoV-2 has emerged as a new threat to global health and economy. A promising target for both diagnosis and therapeutics treatments of the new disease named COVID-19 is the coronavirus (CoV) spike (S) glycoprotein. By constant-pH Monte Carlo simulations and the PROCEEDpKa method, we have mapped the electrostatic epitopes for four monoclonal antibodies and the angiotensin-converting enzyme 2 (ACE2) on both SARS-CoV-1 and the new SARS-CoV-2 S receptor binding domain (RBD) proteins. We also calculated free energy of interactions and shown that the S RBD proteins from both SARS viruses binds to ACE2 with similar affinities. However, the affinity between the S RBD protein from the new SARS-CoV-2 and ACE2 is higher than for any studied antibody previously found complexed with SARS-CoV-1. Based on physical chemical analysis and free energies estimates, we can shed some light on the involved molecular recognition processes, their clinical aspects, the implications for drug developments, and suggest structural modifications on the CR3022 antibody that would improve its binding affinities for SARS-CoV-2 and contribute to address the ongoing international health crisis.

Fully Atomistic Multiscale Approach for pKa Prediction

The ionization state of titratable amino acids strongly affects proteins structure and functioning in a large number of biological processes. It is therefore essential to be able to characterize the pK_a of ionizable groups inside proteins and to understand its microscopic determinants in order to gain insights into many functional properties of proteins. A big effort has been devoted to the development of theoretical approaches for the prediction of deprotonation free energies, yet the accurate theoretical/computational calculation of pK_a values is recognized as a current challenge. A methodology based on a hybrid quantum/classical approach is here proposed for the computation of deprotonation free energies. The method is applied to calculate the pK_a of formic acid, methylammonium, and methanethiol, providing results in good agreement with the corresponding experimental estimates. The pK_a is also calculated for aspartic acid and lysine as single residues in solution and for three aspartic/glutamic acids inside a well-characterized protein: hen egg white lysozyme. While for small molecules the method is able to deal with multiple protonation states of all titratable groups, this becomes computationally very expensive for proteins. The calculated pK_a values for the single amino acids (except for the zwitterionic aspartic acid) and inside the protein display a systematic shift with respect to the experimental values that suggests that the fine balance between hydrophobic and polar interactions might be not accurately reproduced by the usual classical force-fields, thus affecting the computation of deprotonation free energies. The calculated pK_a shifts inside the protein are in good agreement with the corresponding experimental ones (within 1 pK_a unit), well reproducing the pK_a changes due to the protein environment even in the case of large pK_a shifts.

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.

A revised order of subunits in mammalian septin complexes

Septins are GTP binding proteins considered to be novel components of the cytoskeleton. They polymerize into filaments based on hexameric or octameric core particles in which two copies of either three or four different septins, respectively, assemble into a specific sequence. Viable combinations of the 13 human septins are believed to obey substitution rules in which the different septins involved must come from distinct subgroups. The hexameric assembly, for example, has been reported to be SEPT7-SEPT6-SEPT2-SEPT2-SEPT6-SEPT7. Here, we have replaced SEPT2 by SEPT5 according to the substitution rules and used transmission electron microscopy to demonstrate that the resulting recombinant complex assembles into hexameric particles which are inverted with respect that predicted previously. MBP-SEPT5 constructs and immunostaining show that SEPT5 occupies the terminal positions of the hexamer. We further show that this is also true for the assembly including SEPT2, in direct contradiction with that reported previously. Consequently, both complexes expose an NC interface, as reported for yeast, which we show to be more susceptible to high salt concentrations. The correct assembly for the canonical combination of septins 2-6-7 is therefore established to be SEPT2-SEPT6-SEPT7-SEPT7-SEPT6-SEPT2, implying the need for revision of the mechanisms involved in filament assembly.

Coarse-grained dynamic RNA titration simulations

Electrostatic interactions play a pivotal role in many biomolecular processes. The molecular organization and function in biological systems are largely determined by these interactions. Owing to the highly negative charge of RNA, the effect is expected to be more pronounced in this system. Moreover, RNA base pairing is dependent on the charge of the base, giving rise to alternative secondary and tertiary structures. The equilibrium between uncharged and charged bases is regulated by the solution pH, which is therefore a key environmental condition influencing the molecule's structure and behaviour. By means of constant-pH Monte Carlo simulations based on a fast proton titration scheme, coupled with the coarse-grained model HiRE-RNA, molecular dynamic simulations of RNA molecules at constant pH enable us to explore the RNA conformational plasticity at different pH values as well as to compute electrostatic properties as local pK _a values for each nucleotide.

Insights into the ZIKV NS1 Virology from Different Strains through a Fine Analysis of Physicochemical Properties

The flavivirus genus has several organisms responsible for generating various diseases in humans. Recently, especially in tropical regions, Zika virus (ZIKV) has raised great health concerns due to the high number of cases affecting the area during the last years that has been accompanied by a rise in the cases of the Guillain-Barré syndrome and fetal and neonatal microcephaly. Diagnosis is still difficult since the clinical symptoms between ZIKV and other flaviviruses (e.g., dengue and yellow fever) are highly similar. The understanding of their common physicochemical properties that are pH-dependent and biomolecular interaction features and their differences sheds light on the relation strain-virulence and might suggest alternative strategies toward differential serological diagnostics and therapeutic intervention. Due to their immunogenicity, the primary focus of this study was on the ZIKV nonstructural proteins 1 (NS1). By means of computational studies and semiquantitative theoretical analyses, we calculated the main physicochemical properties of this protein from different strains that are directly responsible for the biomolecular interactions and, therefore, can be related to the differential infectivity of the strains. We also mapped the electrostatic differences at both the sequence and structural levels for the strains from Uganda to Brazil, which could suggest possible molecular mechanisms for the increase of the virulence of ZIKV in Brazil. Exploring the interfaces used by NS1 to self-associate in some different oligomeric states and interact with membranes and the antibody, we could map the strategy used by the ZIKV during its evolutionary process. This indicates possible molecular mechanisms that can be correlated with the different immunological responses. By comparing with the known antibody structure available for the West Nile virus, we demonstrated that this antibody would have difficulties to neutralize the NS1 from the Brazilian strain. The present study also opens up perspectives to computationally design high-specificity antibodies.

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 pK_a 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.

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. Nevertheless, due to the very large number of ionizable sites, different macromolecular conformations, salt conditions, and all other charged species, the CPU time cost simply becomes prohibitive for computer simulations, making this a quite complex problem. Simplified methods based on Monte Carlo sampling have been devised and will be reviewed here, highlighting the updated state-of-the-art of this field, advantages, and limitations of different theoretical protocols for biomolecular systems (proteins and nucleic acids). Following a historical perspective, the discussion will be associated with the applications to protein interactions with other proteins, polyelectrolytes, and nanoparticles.

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.