“Mirror”-like Protein Dimers Stabilized by Local Heterogeneity at Protein Surfaces

Specific Ion Effects in Lanthanide-Amphiphile Structures at the Air-Water Interface and Their Implications for Selective Separation

The use of surfactants to attract dissolved ions to water surfaces and interfaces is an essential step in both solvent-based and solvent-free separation processes. We have studied the interactions of lanthanide ions in the aqueous subphase with monolayers of dihexadecyl phosphate at air-water interfaces. With heavier lanthanides (atomic number Z ≥ 65) in the subphase, the floating layer can be compressed to an area/molecule of about half the molecular cross section, indicating bilayer formation. X-ray fluorescence and reflectivity data support this conclusion. In the presence of lighter lanthanides (Z < 65), only monolayers are observed. Subphase-concentration-dependent studies using Er³⁺ (heavier) and Nd³⁺ (lighter) lanthanides show a stepwise progression, with ions attaching to the monolayer only when the solution concentration is >3 × 10^-7 M. Above ∼10^-5 M, bilayers form but only in the presence of the heavier lanthanide. Grazing incidence X-ray diffraction shows evidence of lateral ion-ion correlations in the bilayer structure but not in monolayers. Explicit solvent all-atom molecular dynamics simulations confirm the elevated ion-ion correlation in the bilayer system. This bilayer structure isolates heavier lanthanides but not lighter lanthanides from an aqueous solution and is therefore a potential mechanism for the selective separation of heavier lanthanides.

Protein Surface Printer for Exploring Protein Domains

The surface of proteins is vital in determining protein functions. Herein, a program, Protein Surface Printer (PSP), is built that performs multiple functions in quantifying protein surface domains. Two proteins, PETase and cytochrome P450, are used to validate that the program supports atomistic simulations with different combinations of programs and force fields. A case study is conducted on the structural analysis of the spike proteins of SARS-CoV-2 and SARS-CoV and the human cell receptor ACE2. Although the surface domains of both spike proteins are highly similar, their receptor-binding domains (RBDs) and the O-linked glycan domains are structurally different. The O-linked glycan domain of SARS-CoV-2 is highly positively charged, which may promote binding to negatively charged human cells.

Enhanced Binding of SARS-CoV-2 Spike Protein to Receptor by Distal Polybasic Cleavage Sites

The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein plays a crucial role in binding the human cell receptor ACE2 that is required for viral entry. Many studies have been conducted to target the structures of RBD-ACE2 binding and to design RBD-targeting vaccines and drugs. Nevertheless, mutations distal from the SARS-CoV-2 RBD also impact its transmissibility and antibody can target non-RBD regions, suggesting the incomplete role of the RBD region in the spike protein-ACE2 binding. Here, in order to elucidate distant binding mechanisms, we analyze complexes of ACE2 with the wild-type spike protein and with key mutants via large-scale all-atom explicit solvent molecular dynamics simulations. We find that though distributed approximately 10 nm away from the RBD, the SARS-CoV-2 polybasic cleavage sites enhance, via electrostatic interactions and hydration, the RBD-ACE2 binding affinity. A negatively charged tetrapeptide (GluGluLeuGlu) is then designed to neutralize the positively charged arginine on the polybasic cleavage sites. We find that the tetrapeptide GluGluLeuGlu binds to one of the three polybasic cleavage sites of the SARS-CoV-2 spike protein lessening by 34% the RBD-ACE2 binding strength. This significant binding energy reduction demonstrates the feasibility to neutralize RBD-ACE2 binding by targeting this specific polybasic cleavage site. Our work enhances understanding of the binding mechanism of SARS-CoV-2 to ACE2, which may aid the design of therapeutics for COVID-19 infection.

Thermodynamic Integration in 3n Dimensions without Biases or Alchemy for Protein Interactions

Thermodynamic integration (TI), a powerful formalism for computing Gibbs free energy, has been implemented for many biophysical processes with alchemical schemes that require delicate human efforts to choose/design biasing potentials for sampling the desired biophysical events and to remove their artifactitious consequences afterwards. Theoretically, an alchemical scheme is exact but practically, an unsophisticated implementation of this exact formula can cause error amplifications. Small relative errors in the input parameters can be amplified many times in their propagation into the computed free energy [due to subtraction of similar numbers such as (105 ± 5)‒(100 ± 5) = 5 ± 7]. In this paper, we present an unsophisticated implementation of TI in 3n dimensions (3nD) (n=1,2,3…) for the potential of mean force along a 3nD path connecting one state in the bound state ensemble to one state in the unbound state ensemble. Fluctuations in these 3nD are integrated in the bound and unbound state ensembles but not along the 3nD path. Using TI3nD, we computed the standard binding free energies of three protein complexes: trometamol in Salmonella effector SpvD (n=1), biotin-avidin (n=2), and Colicin E9 endonuclease with cognate immunity protein Im9 (n=3). We employed three different protocols in three independent computations of E9-Im9 to show TI3nD's robustness. We also computed the hydration energies of ten biologically relevant compounds (n=1 for water, acetamide, urea, glycerol, trometamol, ammonium and n=2 for erythritol, 1,3-propanediol, xylitol, biotin). Each of the 15 computations is accomplishable within one (for hydration) to ten (for E9-Im9) days on an inexpensive GPU workstation. The computed results all agree with the available experimental data.

Water follows polar and nonpolar protein surface domains

The conformation of water around proteins is of paramount importance, as it determines protein interactions. Although the average water properties around the surface of proteins have been provided experimentally and computationally, protein surfaces are highly heterogeneous. Therefore, it is crucial to determine the correlations of water to the local distributions of polar and nonpolar protein surface domains to understand functions such as aggregation, mutations, and delivery. By using atomistic simulations, we investigate the orientation and dynamics of water molecules next to 4 types of protein surface domains: negatively charged, positively charged, and charge-neutral polar and nonpolar amino acids. The negatively charged amino acids orient around 98% of the neighboring water dipoles toward the protein surface, and such correlation persists up to around 16 Å from the protein surface. The positively charged amino acids orient around 94% of the nearest water dipoles against the protein surface, and the correlation persists up to around 12 Å. The charge-neutral polar and nonpolar amino acids are also orienting the water neighbors in a quantitatively weaker manner. A similar trend was observed in the residence time of the nearest water neighbors. These findings hold true for 3 technically important enzymes (PETase, cytochrome P450, and organophosphorus hydrolase). Our results demonstrate that the water-amino acid degree of correlation follows the same trend as the amino acid contribution in proteins solubility, namely, the negatively charged amino acids are the most beneficial for protein solubility, then the positively charged amino acids, and finally the charge-neutral amino acids.