Exploring the ability of the MD+FoldX method to predict SARS-CoV-2 antibody escape mutations using large-scale data.

Antibody escape mutations pose a significant challenge to the effectiveness of vaccines and antibody-based therapies. The ability to predict these escape mutations with computer simulations would allow us to detect threats early and develop effective countermeasures, but a lack of large-scale experimental data has hampered the validation of these calculations. In this study, we evaluate the ability of the MD+FoldX molecular modeling method to predict escape mutations by leveraging a large deep mutational scanning dataset, focusing on the SARS-CoV-2 receptor binding domain. Our results show a positive correlation between predicted and experimental data, indicating that mutations with reduced predicted binding affinity correlate moderately with higher experimental escape fractions. We also demonstrate that better performance can be achieved using affinity cutoffs tailored to distinct antibody-antigen interactions rather than a one-size-fits-all approach. We find that 70% of the systems surpass the 50% precision mark, and demonstrate success in identifying mutations present in significant variants of concern and variants of interest. Despite promising results for some systems, our study highlights the challenges in comparing predicted and experimental values. It also emphasizes the need for new binding affinity methods with improved accuracy that are fast enough to estimate hundreds to thousands of antibody-antigen binding affinities.

Unveiling the G4-PAMAM capacity to bind and protect Ang-(1-7) bioactive peptide by molecular dynamics simulations.

Angiotensin-(1-7) re-balance the Renin-Angiotensin system affected during several pathologies, including the new COVID-19; cardiovascular diseases; and cancer. However, one of the limiting factors for its therapeutic use is its short half-life, which might be overcome with the use of dendrimers as nanoprotectors. In this work, we addressed the following issues: (1) the capacity of our computational protocol to reproduce the experimental structural features of the (hydroxyl/amino)-terminated PAMAM dendrimers as well as the Angiotensin-(1-7) peptide; (2) the coupling of Angiotensin-(1-7) to (hydroxyl/amino)-terminated PAMAM dendrimers in order to gain insight into the structural basis of its molecular binding; (3) the capacity of the dendrimers to protect Angiotensin-(1-7); and (4) the effect of pH changes on the peptide binding and covering. Our Molecular-Dynamics/Metadynamics-based computational protocol well modeled the structural experimental features reported in the literature and our double-docking approach was able to provide reasonable initial structures for stable complexes. At neutral pH, PAMAM dendrimers with both terminal types were able to interact stably with 3 Angiotensin-(1-7) peptides through ASP1, TYR4 and PRO7 key amino acids. In general, they bind on the surface in the case of the hydroxyl-terminated compact dendrimer and in the internal zone in the case of the amino-terminated open dendrimer. At acidic pH, PAMAM dendrimers with both terminal groups are still able to interact with peptides either internalized or in its periphery, however, the number of contacts, the percentage of coverage and the number of hydrogen bonds are lesser than at neutral pH, suggesting a state for peptide release. In summary, amino-terminated PAMAM dendrimer showed slightly better features to bind, load and protect Angiotensin-(1-7) peptides.

Fluoride Transport and Inhibition Across CLC Transporters.

The Chloride Channel (CLC) family includes proton-coupled chloride and fluoride transporters. Despite their similar protein architecture, the former exchange two chloride ions for each proton and are inhibited by fluoride, whereas the latter efficiently transport one fluoride in exchange for one proton. The combination of structural, mutagenesis, and functional experiments with molecular simulations has pinpointed several amino acid changes in the permeation pathway that capitalize on the different chemical properties of chloride and fluoride to fine-tune protein function. Here we summarize recent findings on fluoride inhibition and transport in the two prototypical members of the CLC family, the chloride/proton transporter from Escherichia coli (CLC-ec1) and the fluoride/proton transporter from Enterococcus casseliflavus (CLCF-eca).

In silico design of peptides as potential ligands to resistin.

Resistin is a hormone of biological interest due to its connection with several diseases of worldwide concern. This work aims to design a series of cyclic peptides as "lead compounds" to identify potential ligands to resistin. To this end, we propose an approach based on a peptide design algorithm plus a two-stage selection which accounts for selectivity, one of the most forgotten steps in the design of ligands. Following this approach, we have been able to identify several peptides as strong candidates for the design of elements of bio-recognition. Those peptides present low scoring binding energy to albumin, good water solubility, stability in water at 300 K, and high scoring binding energy to resistin. Among those peptides, two were chosen, to perform a more rigorous calculation of binding free energy based on the Alchemical Absolute Binding Free Energy method. We were able to establish a methodological route for the development of strong candidates for the design of ligands to resistin. Graphical Abstract Combined MD + MC + AABFE approach to design and screening of high-affinity binders to resistin.