Explicit solvation thermodynamics in ionic solution: extending grid inhomogeneous solvation theory to solvation free energy of salt–water mixtures

Hydration thermodynamics play a fundamental role in fields ranging from the pharmaceutical industry to environmental research. Numerous methods exist to predict solvation thermodynamics of compounds ranging from small molecules to large biomolecules. Arguably the most precise methods are those based on molecular dynamics (MD) simulations in explicit solvent. One theory that has seen increased use is inhomogeneous solvation theory (IST). However, while many applications require accurate description of salt–water mixtures, no implementation of IST is currently able to estimate solvation properties involving more than one solvent species. Here, we present an extension to grid inhomogeneous solvation theory (GIST) that can take salt contributions into account. At the example of carbazole in 1 M NaCl solution, we compute the solvation energy as well as first and second order entropies. While the effect of the first order ion entropy is small, both the water–water and water–ion entropies contribute strongly. We show that the water–ion entropies are efficiently approximated using the Kirkwood superposition approximation. However, this approach cannot be applied to the water–water entropy. Furthermore, we test the quantitative validity of our method by computing salting-out coefficients and comparing them to experimental data. We find a good correlation to experimental salting-out constants, while the absolute values are overpredicted due to the approximate second order entropy. Since ions are frequently used in MD, either to neutralize the system or as a part of the investigated process, our method greatly extends the applicability of GIST. The use-cases range from biopharmaceuticals, where many assays require high salt concentrations, to environmental research, where solubility in sea water is important to model the fate of organic substances.

Effects of Temperature and Grain Size on Diffusivity of Aluminium: Electromigration Experiment and Molecular Dynamic Simulation

Understanding the atomic diffusion features in metallic material is significant to explain the diffusion-controlled physical processes. In this paper, using electromigration experiments and molecular dynamic (MD) simulations, we investigate the effects of grain size and temperature on the self-diffusion of polycrystalline aluminum (Al). The mass transport due to electromigration are accelerated by increasing temperature and decreasing grain size. Magnitudes of effective diffusivity (Deff) and grain boundary diffusivity (DGBs) are experimentally determined, in which the Deff changes as a function of grain size and temperature, but DGBs is independent of the grain size, only affected by the temperature. Moreover, MD simulations of atomic diffusion in polycrystalline Al demonstrate those observations from experiments. Based on MD results, the Arrhenius equation of DGBs and empirical formula of the thickness of grain boundaries at various temperatures are obtained. In total, Deff and DGBs obtained in the present study agree with literature results, and a comprehensive result of diffusivities related to the grain size is presented.

Continuous B- to A- Transition in Protein-DNA Binding - How Well Is It Described by Current AMBER Force Fields?

When DNA interacts with a protein, its structure often undergoes significant conformational adaptation. Perhaps the most common is the transition from canonical B-DNA towards the A-DNA form, which is not a two-state, but rather a continuous transition. The A- and B- forms differ mainly in sugar pucker P (north/south) and glycosidic torsion χ (high-anti/anti). The combination of A-like P and B-like χ (and vice versa) represents the nature of the intermediate states lying between the pure A- and B- forms. In this work, we study how the A/B equilibrium and in particular the A/B intermediate states, which are known to be over-represented at protein-DNA interfaces, are modeled by current AMBER force fields. Eight protein-DNA complexes and their naked (unbound) DNAs were simulated with OL15 and bsc1 force fields as well as an experimental combination OL15χOL3. We found that while the geometries of the A-like intermediate states in the molecular dynamics (MD) simulations agree well with the native X-ray geometries found in the protein-DNA complexes, their populations (stabilities) are significantly underestimated. Different force fields predict different propensities for A-like states growing in the order OL15 < bsc1 < OL15χOL3, but the overall populations of the A-like form are too low in all of them. Interestingly, the force fields seem to predict the correct sequence-dependent A-form propensity, as they predict larger populations of the A-like form in naked (unbound) DNA in those steps that acquire A-like conformations in protein-DNA complexes. The instability of A-like geometries in current force fields may significantly alter the geometry of the simulated protein-DNA complex, destabilize the binding motif, and reduce the binding energy, suggesting that refinement is needed to improve description of protein-DNA interactions in AMBER force fields.

Computational Design of Miniproteins as SARS-CoV-2 Therapeutic Inhibitors

A rational therapeutic strategy is urgently needed for combating SARS-CoV-2 infection. Viral infection initiates when the SARS-CoV-2 receptor-binding domain (RBD) binds to the ACE2 receptor, and thus, inhibiting RBD is a promising therapeutic for blocking viral entry. In this study, the structure of lead antiviral candidate binder (LCB1), which has three alpha-helices (H1, H2, and H3), is used as a template to design and simulate several miniprotein RBD inhibitors. LCB1 undergoes two modifications: structural modification by truncation of the H3 to reduce its size, followed by single and double amino acid substitutions to enhance its binding with RBD. We use molecular dynamics (MD) simulations supported by ab initio density functional theory (DFT) calculations. Complete binding profiles of all miniproteins with RBD have been determined. The MD investigations reveal that the H3 truncation results in a small inhibitor with a −1.5 kcal/mol tighter binding to RBD than original LCB1, while the best miniprotein with higher binding affinity involves D17R or E11V + D17R mutation. DFT calculations provide atomic-scale details on the role of hydrogen bonding and partial charge distribution in stabilizing the minibinder:RBD complex. This study provides insights into general principles for designing potential therapeutics for SARS-CoV-2.

cpSRP43 is both highly flexible and stable: Structural insights using a combined experimental and computational approach

The novel multidomain protein, cpSRP43, is a unique subunit of the post-translational chloroplast signal recognition particle (cpSRP) targeting pathway in higher plants. The cpSRP pathway is responsible for targeting and insertion of light-harvesting chlorophyll a/b binding proteins (LHCPs) to the thylakoid membrane. Nuclear-encoded LHCPs are synthesized in the cytoplasm then imported into the chloroplast. Upon emergence into the stroma, LHCPs form a soluble transit complex with the cpSRP heterodimer, which is composed of cpSRP43 and cpSRP54, a 54 kDa subunit homologous to the universally conserved GTPase in cytosolic SRP pathways. cpSRP43 is irreplaceable as a chaperone to LHCPs in their translocation to the thylakoid membrane and remarkable in its ability to dissolve aggregates of LHCPs without the need for external energy input. In previous studies, cpSRP43 has demonstrated significant flexibility and interdomain dynamics. However, the high flexibility and structural dynamics of cpSRP43 is yet unexplained by current crystal structures of cpSRP43. This is due, in part, to the fact that free full length cpSRP43 is so flexible that it is unable to crystalize. In this study, we explore the structural stability of cpSRP43 under different conditions using various biophysical techniques and find that this protein is concurrently highly stable and flexible. This conclusion is interesting considering that stable proteins typically possess a non-dynamic structure. Molecular dynamics (MD) simulations which correlated with data from biophysical experimentation were used to explain the basis of the extraordinary stability of cpSRP43. This combination of biophysical data and microsecond-level MD simulations allows us to obtain a detailed perspective of the conformational landscape of these proteins.

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.

Molecular dynamics simulations of the delta and omicron SARS-CoV-2 spike – ACE2 complexes reveal distinct changes between both variants

SARS-CoV-2, the virus which causes the COVID-19 pandemic, changes frequently through the ap-pearance of mutations constantly leading to new variants. However, only few variants evolve as dominating and will be considered as “Variants of Concern” (VOCs) by the world health organization (WHO). At the end of 2020 the alpha (B.1.1.7) variant appeared in the United Kingdom and domi-nated the pandemic situation until mid of 2021 when it was substituted by the delta variant (B.1.617.2) that first appeared in India as predominant variant. At the end of 2021, SARS-CoV-2 omi-cron (B.1.1.529) evolved as the dominating variant. Here, we use in silico modeling and molecular dynamics (MD) simulations of the receptor-binding domain of the viral spike protein and the host cell surface receptor ACE2 to analyze and compare the interaction pattern between the wild type, delta and omicron variants. We identified residue 493 in delta (glutamine) and omicron (arginine) with altered binding properties towards ACE2.