The phase diagrams of beryllium and magnesium oxide at megabar pressures

We perform ab initio simulations of beryllium (Be) and magnesium oxide (MgO) at megabar pressures and compare their structural and thermodynamic properties. We make a detailed comparison of our two recently derived phase diagrams of Be [Wu et al., Phys. Rev. B 104, 014103 (2021)] and MgO [Soubiran and Militzer, Phys. Rev. Lett. 125, 175701 (2020)] using the thermodynamic integration technique, as they exhibit striking similarities regarding their shape. We explore whether the Lindemann criterion can explain the melting temperatures of these materials through the calculation of the Debye temperature at high pressure. From our free energy calculations, we obtained a melting curve for Be that is well represented by the fit Tm(P) = 1564K*[1 + P/(15.8037 GPa)]^0.414 , and a melting line of MgO, which can be well reproduced by the fit Tm(P) = 3010K*(1 + P/a)^(1/c) with a = 10.5797 GPa and c = 2.8683 for the B1 phase and a = 26.1163 GPa and c = 2.2426 for the B2 phase. Both materials exhibit negative Clapeyron slopes on the boundaries between the two solid phases that are strongly affected by anharmonic effects, which also influences the location of the solid-solid-liquid triple point. We find that the quasi-harmonic approximation underestimates the stability range of the low-pressure phases, namely hcp for Be and B1 for MgO. We also compute the phonon dispersion relations at low and high pressure for each of the phases of these materials, and also explore how the phonon density of states is modified by temperature. Finally, we derive secondary shock Hugoniot curves in addition to the principal Hugoniot curve for both materials, and study their offsets in pressure between solid and liquid branches.

Measuring the free energy of hard-sphere colloidal glasses

Free energy is a key thermodynamic observable that controls the elusive physics of the glass transition. However, measuring the free energy of colloidal glasses from microscopy images is challenging due to the difficulty of measuring the individual particle size in the slightly polydisperse glassy systems. In this paper, we carry out experiments and numerical simulations of colloidal glasses with the aim to find a practical approach to measure the free energy from colloidal particles at mild polydispersity. We propose a novel method which requires only the particle coordinates from a few confocal microscopy snapshots to estimate the average particle diameter and use it as an input for our experimental free energy measurements. We verify our free energy calculations from Cell Theory with the free energy obtained by Thermodynamic Integration. The excellent agreement between the free energies measured using the two methods close to the glass transition packing fraction highlights the dominant role played by \emph{vibrational} entropy in determining a colloidal glass's free energy. Finally, the noticeable free energy difference calculated from uniform and conjectured particle sizes emphasizes the sensitivity on particle free volumes when measuring free energy in the slightly polydisperse colloidal glass.

Identification of Some Dietary Flavonoids as Potential Inhibitors of TMPRSS2 Through Protein-ligand Interaction Studies and Binding Free Energy Calculations

The alarming increase in COVID-19 cases and deaths calls for an urgent cost-effective pharmacological approach. Here, we examine the inhibitory activity of a group of dietary bioactive flavonoids against the human protease TMPRSS2, which plays a major role in SARS CoV-2 viral entry. After the molecular docking studies of a large number of flavonoids, four compounds with high binding scores were selected and studied in detail. The binding affinities of these four ligands, Amentoflavone, Narirutin, Eriocitrin, and Naringin, at the active site of TMPRSS2 target were investigated using MD simulations followed by MM-PBSA binding energy calculations. From the studies, a number of significant hydrophobic and hydrogen bonding interactions between the ligands and binding site amino residues of TMPRSS2 are identified which showcase their excellent inhibitory activity against TMPRSS2. Among these ligands, Amentoflavone and Narirutin showed MM-PBSA binding energy values of -155.48 and -138.13 kJ/mol respectively. Our previous studies of the inhibitory activity of these compounds against main protease of SARS-COV2 and the present study on TMPRSS2 strongly highlighted that Amentoflavone and Naringin can exhibit promising multi-target activity against SARS-CoV-2. Moreover, due to their wide availability, no side effects and low cost, these compounds could be recommended as dietary supplements for COVID patients or for the development of SARS-CoV-2 treatments.

Relative free-energy calculations for scaffold hopping-type transformations with an automated RE-EDS sampling procedure

The calculation of relative free-energy differences between different compounds plays an important role in drug design to identify potent binders for a given protein target. Most rigorous methods based on molecular dynamics simulations estimate the free-energy difference between pairs of ligands. Thus, the comparison of multiple ligands requires the construction of a “state graph”, in which the compounds are connected by alchemical transformations. The computational cost can be optimized by reducing the state graph to a minimal set of transformations. However, this may require individual adaptation of the sampling strategy if a transformation process does not converge in a given simulation time. In contrast, path-free methods like replica-exchange enveloping distribution sampling (RE-EDS) allow the sampling of multiple states within a single simulation without the pre-definition of alchemical transition paths. To optimize sampling and convergence, a set of RE-EDS parameters needs to be estimated in a pre-processing step. Here, we present an automated procedure for this step that determines all required parameters, improving the robustness and ease of use of the methodology. To illustrate the performance, the relative binding free energies are calculated for a series of checkpoint kinase 1 inhibitors containing challenging transformations in ring size, opening/closing, and extension, which reflect changes observed in scaffold hopping. The simulation of such transformations with RE-EDS can be conducted with conventional force fields and, in particular, without soft bond-stretching terms.

Improved binding affinity of the Omicron's spike protein with hACE2 receptor is the key factor behind its increased virulence

The new variant of SARS-CoV-2, Omicron, has been quickly spreading in many countries worldwide. Compared to the original virus, Omicron is characterized by several mutations in its genomic region, including spike protein's receptor-binding domain (RBD). We have computationally investigated the interaction between RBD of both wild-type and omicron variants with hACE2 receptor using molecular dynamics and MM-GBSA based binding free energy calculations. The mode of the interaction between Omicron's RBD to the human ACE2 (hACE2) receptor is similar to the original SARS-CoV-2 RBD except for a few key differences. The bind-ing free energy difference shows that the spike protein of Omicron has increased binding affinity for the hACE-2 receptor. The mutated residues in the RBD showed strong interactions with a few amino acid residues of the hACE2. More specifically, strong electrostatic interactions (salt bridges) and hydrogen bonding were observed between R493 and R498 residues of the Omicron RBD with D30/E35 and D38 residues of the hACE2, respectively. Other mutated amino acids in the Omicron RBD, e.g. S496 and H505, also exhibited hydrogen bonding with the hACE2 receptor. The pi-stacking interaction was also observed between tyrosine residues (RBD-Tyr501: hACE2-Tyr41) in the complex, which contributes majorly to binding free energies suggesting this as one of the key interactions stabilizing the complex formation. The structural insights of RBD:hACE2 complex, their binding mode information and residue wise contributions to binding free energy provide insight on the increased transmissibility of Omicron and pave the way to design and optimize novel antiviral agents.

Large Scale Study of Ligand-Protein Relative Binding Free Energy Calculations: Actionable Predictions from Statistically Robust Protocols

The accurate and reliable prediction of protein-ligand binding affinities can play a central role in the drug discovery process as well as in personalised medicine. Of considerable importance during lead optimisation are the alchemical free energy methods that furnish estimation of relative binding free energies (RBFE) of similar molecules. Recent advances in these methods have increased their speed, accuracy and precision. This is evident from the increasing number of retrospective as well as prospective studies employing them. However, such methods still have limited applicability in real-world scenarios due to a number of important yet unresolved issues. Here, we report the findings from a large dataset comprising over 500 ligand transformations spanning over 300 ligands binding to a diverse set of 14 different protein targets which furnish statistically robust results on the accuracy, precision and reproducibility of RBFE calculations. We use ensemble-based methods which are the only way to provide reliable uncertainty quantification given that the underlying molecular dynamics is chaotic. These are implemented using TIES (Thermodynamic Integration with Enhanced Sampling) but are equally applicable to free energy perturbation calculations for which we expect essentially very similar results. Results achieve chemical accuracy in all cases. Ensemble simulations also furnish information on the statistical distributions of the free energy calculations which exhibit non-normal behaviour. We find that the “enhanced sampling” method known as replica exchange with solute tempering degrades RBFE predictions. We also report definitively on numerous associated alchemical factors including the choice of ligand charge method, flexibility in ligand structure and the size of the alchemical region including the number of atoms involved in transforming one ligand into another. Our findings provide a key set of recommendations that should be adopted for the reliable application of RBFE methods.

Compared with SARS-CoV2 wild type's spike protein, the SARS-CoV2 omicron's receptor binding motif has adopted a more SARS-CoV1 and/or bat/civet-like structure.

Our study focuses on free energy calculations of SARS-Cov2 spike protein receptor binding motives (RBMs) from wild type and variants-of-concern with particular emphasis on currently emerging SARS- CoV2 omicron variants of concern (VOC). Our computational free energy analysis underlines the occurrence of positive selection processes that specify omicron host adaption and bring changes on the molecular level into context with clinically relevant observations. Our free energy calculations studies regarding the interaction of omicron's RBM with human ACE2 shows weaker binding to ACE2 than alpha's, delta's, or wild type's RBM. Thus, less virus is predicted to be generated in time per infected cell. Our mutant analyses predict with focus on omicron variants a reduced spike-protein binding to ACE2--receptor protein possibly enhancing viral fitness / transmissibility and resulting in a delayed induction of danger signals as trade-off. Finally, more virus is produced but less per cell accompanied with delayed Covid-19 immunogenicity and pathogenicity. Regarding the latter, more virus is assumed to be required to initiate inflammatory immune responses.