Structural and thermodynamic properties of conserved water molecules in Mpro native: A combined approach by MD simulation and Grid Inhomogeneous Solvation Theory

The new viral strains of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) are continuously rising, becoming more virulent, and transmissible. Therefore, the development of new antiviral drugs is essential. Due to its significant role in the viral life cycle of SARS-CoV-2, the main protease (Mpro) enzyme is a leading target for antiviral drug design. The Mpro monomer consists of domain DI, DII, and DI-DII interface. Twenty-one conserved water molecules (W4-W24) are occupied at these domains according to multiple crystal structure analyses. The crystal and MD structures reveal the presence of eight conserved water sites in domain DI, DII and remaining in the DI-DII interface. Grid-based inhomogeneous fluid solvation theory (GIST) was employed on MD structures of Mpro native to predict structural and thermodynamic properties of each conserved water site for focusing to identify the specific conserved water molecules that can easily be displaced by proposed ligands. Finally, MD water W13 is emerged as a promising candidate for water mimic drug design due to its low mean interaction energy, loose binding character with the protein, and its involvement in a water-mediated H-bond with catalytic His41 via the interaction Thr25(OG)---W13---W---His41(NE2). In this context, water occupancy, relative interaction energy, entropy, and topologies of W13 are thermodynamically acceptable for the water displacement method. Therefore, the strategic use of W13's geometrical position in the DI domain may be implemented for drug discovery against COVID disease by designing new ligands with appropriately oriented chemical groups to mimic its structural, electronic, and thermodynamic properties.

Tools for analyzing protonation states and for tracing proton transfer pathways with examples from the Rb. sphaeroides photosynthetic reaction centers

Protons participate in many reactions. In proteins, protons need paths to move in and out of buried active sites. The vectorial movement of protons coupled to electron transfer reactions establishes the transmembrane electrochemical gradient used for many reactions, including ATP synthesis. Protons move through hydrogen bonded chains of waters and hydroxy side chains via the Grotthuss mechanism and by proton binding and release from acidic and basic residues. MCCE analysis shows that proteins exist in a large number of protonation states. Knowledge of the equilibrium ensemble can provide a rational basis for setting protonation states in simulations that fix them, such as molecular dynamics (MD). The proton path into the Q_B site in the bacterial reaction centers (RCs) of Rb. sphaeroides is analyzed by MD to provide an example of the benefits of using protonation states found by the MCCE program. A tangled web of side chains and waters link the cytoplasm to Q_B. MCCE analysis of snapshots from multiple trajectories shows that changing the input protonation state of a residue in MD biases the trajectory shifting the proton affinity of that residue. However, the proton affinity of some residues is more sensitive to the input structure. The proton transfer networks derived from different trajectories are quite robust. There are some changes in connectivity that are largely restricted to the specific residues whose protonation state is changed. Trajectories with Q_B^•- are compared with earlier results obtained with Q_B [Wei et. al Photosynthesis Research volume 152, pages153-165 (2022)] showing only modest changes. While introducing new methods the study highlights the difficulty of establishing the connections between protein conformation.

Classical Molecular Dynamics Simulation of Glyonic Liquids: Structural Insights and Relation to Conductive Properties

Rhamnolipids are biosurfactants that have obtained wide industrial and environmental interests with their biodegradability and great surface activity. Besides their important roles as surfactants, they are found to function as a new type of glycolipid-based protic ionic liquids (ILs)─glyonic liquids (GLs). GLs are reported to have impressive physicochemical properties, especially superionic conductivity, and it was reported in experiments that specific ion selections and the fraction of water content have a strong effect on the conductivity. Also, the shape of the conductivity curve as a function of water fraction in GLs is interesting with a sharp increase first and a long plateau. We related the conductivities to the three-dimensional (3D) networks composed of -OH inside the GLs utilizing classical molecular dynamics (MD) simulations. The amount and size of these networks vary with both ion species and water fractions. Before reaching the first hydration layer, the -OH networks with higher projection/box length ratios indicate better conductivity; after reaching the first hydration layer and forming continuous structures, the conductivity retains with more water molecules participating in the continuous networks. Therefore, networks are found to be a qualitative predictor of actual conductivity. This is explained by the analysis of the atomic structures, including radial distribution function, fraction free volume, anion conformations, and hydrogen bond occupancies, of GLs and their water mixtures under different chemical conditions.

Electrostatics in Computational Biophysics and Its Implications for Disease Effects

This review outlines the role of electrostatics in computational molecular biophysics and its implication in altering wild-type characteristics of biological macromolecules, and thus the contribution of electrostatics to disease mechanisms. The work is not intended to review existing computational approaches or to propose further developments. Instead, it summarizes the outcomes of relevant studies and provides a generalized classification of major mechanisms that involve electrostatic effects in both wild-type and mutant biological macromolecules. It emphasizes the complex role of electrostatics in molecular biophysics, such that the long range of electrostatic interactions causes them to dominate all other forces at distances larger than several Angstroms, while at the same time, the alteration of short-range wild-type electrostatic pairwise interactions can have pronounced effects as well. Because of this dual nature of electrostatic interactions, being dominant at long-range and being very specific at short-range, their implications for wild-type structure and function are quite pronounced. Therefore, any disruption of the complex electrostatic network of interactions may abolish wild-type functionality and could be the dominant factor contributing to pathogenicity. However, we also outline that due to the plasticity of biological macromolecules, the effect of amino acid mutation may be reduced, and thus a charge deletion or insertion may not necessarily be deleterious.

Comparison of proton transfer paths to the QA and QB sites of the Rb. sphaeroides photosynthetic reaction centers

The photosynthetic bacterial reaction centers from purple non-sulfur bacteria use light energy to drive the transfer of electrons from cytochrome c to ubiquinone. Ubiquinone bound in the Q_A site cycles between quinone, Q_A, and anionic semiquinone, Q_A^·-, being reduced once and never binding protons. In the Q_B site, ubiquinone is reduced twice by Q_A^·-, binds two protons and is released into the membrane as the quinol, QH₂. The network of hydrogen bonds formed in a molecular dynamics trajectory was drawn to investigate proton transfer pathways from the cytoplasm to each quinone binding site. Q_A is isolated with no path for protons to enter from the surface. In contrast, there is a complex and tangled network requiring residues and waters that can bring protons to Q_B. There are three entries from clusters of surface residues centered around HisH126, GluH224, and HisH68. The network is in good agreement with earlier studies, Mutation of key nodes in the network, such as SerL223, were previously shown to slow proton delivery. Mutational studies had also shown that double mutations of residues such as AspM17 and AspL210 along multiple paths in the network presented here slow the reaction, while single mutations do not. Likewise, mutation of both HisH126 and HisH128, which are at the entry to two paths reduce the rate of proton uptake.

Characterizing Protein Protonation Microstates Using Monte Carlo Sampling

Proteins are polyelectrolytes with acidic and basic amino acids Asp, Glu, Arg, Lys, and His, making up ≈25% of the residues. The protonation state of residues, cofactors, and ligands defines a "protonation microstate". In an ensemble of proteins some residues will be ionized and others neutral, leading to a mixture of protonation microstates rather than in a single one as is often assumed. The microstate distribution changes with pH. The protein environment also modifies residue proton affinity so microstate distributions change in different reaction intermediates or as ligands are bound. Particular protonation microstates may be required for function, while others exist simply because there are many states with similar energy. Here, the protonation microstates generated in Monte Carlo sampling in MCCE are characterized in HEW lysozyme as a function of pH and bacterial photosynthetic reaction centers (RCs) in different reaction intermediates. The lowest energy and highest probability microstates are compared. The ΔG, ΔH, and ΔS between the four protonation states of Glu35 and Asp52 in lysozyme are shown to be calculated with reasonable precision. At pH 7 the lysozyme charge ranges from 6 to 10, with 24 accepted protonation microstates, while RCs have ≈50,000. A weighted Pearson correlation analysis shows coupling between residue protonation states in RCs and how they change when the quinone in the Q_B site is reduced. Protonation microstates can be used to define input MD parameters and provide insight into the motion of protons coupled to reactions.

Ion permeation, selectivity, and electronic polarization in fluoride channels

Fluoride channels (Flucs) export toxic F^- from the cytoplasm. Crystallography and mutagenesis have identified several conserved residues crucial for fluoride transport, but the permeation mechanism at the molecular level has remained elusive. Herein, we have applied constant-pH molecular dynamics and free-energy-sampling methods to investigate fluoride permeation through a Fluc protein from Escherichia coli. We find that fluoride is facile to permeate in its charged form, i.e., F^-, by traversing through a non-bonded network. The extraordinary F^- selectivity is gained by the hydrogen-bonding capability of the central binding site and the Coulombic filter at the channel entrance. The F^- permeation rate calculated using an electronically polarizable force field is significantly more accurate compared with the experimental value than that calculated using a more standard additive force field, suggesting an essential role for electronic polarization in the F^--Fluc interactions.

Poor Person's pH Simulation of Membrane Proteins

pH conditions are central to the functioning of all biomolecules. However, implications of pH changes are nontrivial on a molecular scale. Though a rigorous microscopic definition of pH exists, its implementation in classical molecular dynamics (MD) simulations is cumbersome, and more so in large integral membrane systems. In this chapter, an integrative pipeline is described that combines Multi-Conformation Continuum Electrostatics (MCCE) computations with MD simulations to capture the effect of transient protonation states on the coupled conformational changes in transmembrane proteins. The core methodologies are explained, and all the software required to set up this pipeline are outlined with their key parameters. All associated analyses of structure and function are provided using two case studies, namely those of bioenergetic complexes: NADH dehydrogenase (complex I) and V_o domain of V-type ATPase. The hybrid MCCE-MD pipeline has allowed the discovery of hydrogen bond networks, ligand binding pathways, and disease-causing mutations.