Graphs of Hydrogen-Bond Networks to Dissect Protein Conformational Dynamics

Design of deep eutectic solvents for multiple perfluoroalkyl substances removal: Energy-based screening and mechanism elucidation

The current landscape of perfluoroalkyl substances (PFAS) extraction methodologies presents significant challenges, particularly for multiple PFAS with different carbon chain lengths. This study introduced an energy-driven strategic approach for screening deep eutectic solvents (DESs) to effectively remove a diverse range of PFAS, including perfluoroalkylcarboxylic acids (PFCAs), perfluoroalkanesulfonic acids (PFSAs), and perfluoroalkyl amides (FAAs), from contaminated environments (total 13 target compounds). Utilizing energy-based screening, we identified DES candidates with high affinity for a spectrum of PFAS compounds from 1234 potential starting materials of eutectic systems. Key findings revealed the superior removal efficiency of tributylphosphineoxide/2-methylpiperazine system, exceeding 99 % for various PFAS with different carbon chain lengths in real environmental water samples. Additionally, we elucidated the molecular interactions between DESs and PFAS through ab initio molecular dynamics (AIMD) simulations, providing valuable insights into the mechanisms governing the removal process. The mechanism of extraction involves hydrogen bond network topology and structural organization, with DESs capable of extracting PFAS while maintaining a weakly aggregated state of target molecules and minimizing the impact on the intrinsic structures of DES. The proposed system forms a dynamic, complementary, and flexible non-covalent interaction network structure with PFAS. The study advances the understanding of DES as a designable, effective, and sustainable alternative to conventional solvents for PFAS remediation, offering a significant contribution to environmental chemistry and green technology.

Graph-based analysis of H-bond networks and unsupervised learning reveal conformational coupling in prion peptide segments

In this study, we employed a comprehensive computational approach to investigate the physical chemistry of the water networks surrounding hydrated peptide segments, as derived from molecular dynamics simulations. Our analysis uncovers a complex interplay of direct and water-mediated hydrogen bonds that intricately weave through the peptides. We demonstrate that these hydrogen bond networks encode critical information about the peptides' conformational behavior, with the dimensionality of these networks showing sensitivity to the peptides' conformations. Additionally, we estimated the free-energy landscape of the peptides across various conformations, revealing that their structures are predominantly characterized by unfolded, partially folded, and folded configurations, resulting in broad and rugged free-energy surfaces due to the numerous degrees of freedom contributed by the surrounding solvent. Importantly, the structured nature of this free-energy landscape becomes obscured when conventional collective variables, such as the number of hydrogen bonds, are used. Our findings provide new insights into the molecular mechanisms that couple protein and solvent degrees of freedom, highlighting their significance in the functioning of biological systems.

Interfacial Enrichment of Lauric Acid Assisted by Long-Chain Fatty Acids, Acidity and Salinity at Sea Spray Aerosol Surfaces

Surfactant monolayers at sea spray aerosol (SSA) surfaces regulate various atmospheric processes including gas transfer, cloud interactions, and radiative properties. Most experimental studies of SSA employ a simplified surfactant mixture of long-chain fatty acids (LCFAs) as a proxy for the sea surface microlayer or SSA surface. However, medium-chain fatty acids (MCFAs) make up nearly 30% of the FA fraction in nascent SSA. Given that LCFA monolayers are easily disrupted upon the introduction of chemical heterogeneity (such as mixed chain lengths), simple FA proxies are unlikely to represent realistic SSA interfaces. Integrating experimental and computational techniques, we characterize the impact that partially soluble MCFAs have on the properties of atmospherically relevant LCFA mixtures. We explore the extent to which the MCFA lauric acid (LA) is surface stabilized by varying acidity, salinity, and monolayer composition. We also discuss the impacts of pH on LCFA-assisted LA retention, where the presence of LCFAs may shift the surface-adsorption equilibria of laurate─the conjugate base─toward higher surface activities. Molecular dynamic simulations suggest a mechanism for the enhanced surface retention of laurate. We conclude that increased FA heterogeneity at SSA surfaces promotes surface activity of soluble FA species, altering monolayer phase behavior and impacting climate-relevant atmospheric processes.

A novel mutation in GPR68 causes hypomaturation amelogenesis imperfecta

OBJECTIVES

To identify the genetic cause of a Chinese family with hypomaturation amelogenesis imperfecta (AI) and to characterize the structure of GPR68 mutated enamel in order to develop a deeper understanding of the role of the GPR68 protein during the intricate process of amelogenesis.

DESIGN

One Chinese family with generalized hypomaturation AI was recruited. Two of the third molars from the proband were subjected to scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX). Whole exome sequencing (WES) was performed, and the identified mutation was confirmed by Sanger sequencing. Bioinformatics studies were further conducted to analyze the potential deleterious effects of the mutation.

RESULTS

The proband presented with a hypomaturation AI phenotype, characterized by fragile and discolored enamel surface. The AI enamel showed prismatic structure, which was sporadically obscured by areas of amorphous material and porous structure. EDX analysis showed the proband's enamel demonstrated a significant decrease in calcium and phosphorus content and a significant increase in oxygen compared with normal enamel. A novel homozygous mutation of G protein-coupled receptor 68 (GPR68) (c .149 T > A, p.Ile50Asn) was identified in the proband. Bioinformatics analysis indicated that the mutation site displayed a high level of evolutionary conservation among species, and the mutation might impact the stability and conformation of the protein.

CONCLUSION

The novel homozygous GPR68 mutation resulted in hypomaturation AI. We first described the effect of GPR68 mutation on enamel structure. Our results provide new genetic evidence that mutations involved in GPR68 contribute to hypomaturation AI.

Hydrogen-Bonding and Hydrophobic Interaction Networks as Structural Determinants of Microbial Rhodopsin Function

Microbial pump rhodopsins are highly versatile light-driven membrane proteins that couple protein conformational dynamics with ion translocation across the cell membranes. Understanding how microbial pump rhodopsins use specific amino acid residues at key functional sites to control ion selectivity and ion pumping direction is of general interest for membrane transporters, and could guide site-directed mutagenesis for optogenetics applications. To enable direct comparisons between proteins with different sequences we implement, for the first time, a unique numbering scheme for the microbial pump rhodopsin residues, NS-mrho. We use NS-mrho to show that distinct microbial pump rhodopsins typically have hydrogen-bond networks that are less conserved than anticipated from the amino acid residue conservation, whereas their hydrophobic interaction networks are largely conserved. To illustrate the role of the hydrogen-bond networks as structural elements that determine the functionality of microbial pump rhodopsins, we performed experiments, atomic-level simulations, and hydrogen bond network analyses on GR, the outward proton pump from Gloeobacter violaceus, and KR2, the outward sodium pump from Krokinobacter eikastus. The experiments indicate that multiple mutations that recover KR2 amino acid residues in GR not only fail to convert it into a sodium pump, but completely inactivate GR by abolishing photoisomerization of the retinal chromophore. This observation could be attributed to the drastically altered hydrogen-bond interaction network identified with simulations and network analyses. Taken together, our findings suggest that functional specificity could be encoded in the collective hydrogen-bond network of microbial pump rhodopsins.

Water determines the intramolecular dynamics of proteins. En example of bovine serum albumin

In this work, the terahertz time-domain spectroscopy method analyzed solutions of bovine serum albumin (BSA) in two high concentrations (50 and 334 mg/mL) at three pH values (2.5, 6.5, 8.5) and the same solvents without protein, at 25°C. The spectra of dry BSA were also recorded. For the first time, a method for determining the complex dielectric permittivity of protein molecules in aqueous solutions, without the dielectric contribution of the aqueous phase, is proposed. It is shown that the dielectric permittivity of dissolved and dry BSA (lyophilized, in the native conformation) differ significantly in the terahertz frequency range. These differences are small near 70 cm-1, but they increase greatly with decreasing frequency. It was found that the dielectric losses of protein molecules in solution are close to the dielectric losses of the aqueous environment, which in this frequency range are determined by intermolecular relaxation processes of water. Since dielectric losses are directly related to molecular dynamics, this fact shows that the intramolecular dynamics of the protein completely adjusts to the intermolecular dynamics of the aqueous environment. It also indicates that the native conformation does not determine all the fundamental characteristics of a protein molecule, in particular, it does not determine the dynamics of the protein, which significantly depends on the water environment.

Exploring the neurotoxicity of chiral dinotefuran towards nicotinic acetylcholine receptors: Enantioselective insights into species selectivity

Dinotefuran is a chiral neonicotinoid that is widely distributed in environmental matrices, but its health risks to different organisms are poorly understood. This study investigated the neurotoxic responses of honeybee/cotton aphid nicotinic acetylcholine receptors (nAChRs) to chiral dinotefuran at the enantiomeric scale and demonstrated the microscopic mechanism of species selectivity in nAChR-mediated enantioselective neurotoxicity. The findings indicated that (S)-dinotefuran had a higher affinity for honeybee nAChR than (R)-dinotefuran whereas both enantiomers exhibited similar bioactivity toward cotton aphid nAChR. The results of dynamic neurotoxic processes indicated the association of conformational changes induced by chiral dinotefuran with its macroscopic neurotoxicity, and (R)-dinotefuran, which exhibit low toxicity to honeybee, was found to induce significant conformational changes in the enantioselective neurotoxic reaction, as supported by the average root-mean-square fluctuation (0.35 nm). Energy decomposition results indicated that electrostatic contribution (ΔGele) is the critical energy term that leads to substantial enantioselectivity, and both Trp-51 (－2.57 kcal mol-1) and Arg-75 (－4.86 kcal mol-1), which form a hydrogen-bond network, are crucial residues in mediating the species selectivity for enantioselective neurotoxic responses. Clearly, this study provides experimental evidence for a comprehensive assessment of the health hazards of chiral dinotefuran.

Dynamics of Hydrogen Bonds between Water and Intrinsically Disordered and Structured Regions of Proteins

Recent studies indicate more restricted dynamics of water around intrinsically disordered proteins (IDPs) than structured proteins. We examine here the dynamics of hydrogen bonds between water molecules and two proteins, small ubiquitin-related modifier-1 (SUMO-1) and ubiquitin-conjugating enzyme E2I (UBC9), which we compare around intrinsically disordered regions (IDRs) and structured regions of these proteins. It has been recognized since some time that excluded volume effects, which influence access of water molecules to hydrogen-bonding sites, and the strength of hydrogen bonds between water and protein affect hydrogen bond lifetimes. While we find those two properties to mediate lifetimes of hydrogen bonds between water and protein residues in this study, we also find that the lifetimes are affected by the concentration of charged groups on other nearby residues. These factors are more important in determining the hydrogen bond lifetimes than whether a residue hydrogen bonding with water belongs to an IDR or to a structured region.

Protons taken hostage: Dynamic H-bond networks of the pH-sensing GPR68

Proton-sensing G Protein Coupled Receptors (GPCRs) sense changes in the extracellular pH to effect cell signaling for cellular homeostasis. They tend to be overexpressed in solid tumors associated with acidic extracellular pH, and are of direct interest as drug targets. How proton-sensing GPCRs sense extracellular acidification and activate upon protonation change is important to understand, because it may guide the design of therapeutics. Lack of publicly available experimental structures make it challenging to discriminate between conflicting mechanisms proposed for proton-binding, as main roles have been assigned to either an extracellular histidine cluster or to an internal carboxylic triad. Here we present a protocol to derive and evaluate structural models of the proton-sensing GPR68. This approach integrates state-of-the-art homology modeling with microsecond-timescale atomistic simulations, and with a detailed assessment of the compatibility of the structural models with known structural features of class A GPCRs. To decipher structural elements of potential interest for protonation-coupled conformational changes of GPR68, we used the best-compatible model as a starting point for independent atomistic simulations of GPR68 with different protonation states, and graph computations to characterize the response of GPR68 to changes in protonation. We found that GPR68 hosts an extended hydrogen-bond network that inter-connects the extracellular histidine cluster to the internal carboxylic triad, and which can even reach groups at the cytoplasmic G-protein binding site. Taken together, results suggest that GPR68 relies on dynamic, hydrogen-bond networks to inter-connect extracellular and internal proton-binding sites, and to elicit conformational changes at the cytoplasmic G-protein binding site.

3DDPDs: describing protein dynamics for proteochemometric bioactivity prediction. A case for (mutant) G protein-coupled receptors

Proteochemometric (PCM) modelling is a powerful computational drug discovery tool used in bioactivity prediction of potential drug candidates relying on both chemical and protein information. In PCM features are computed to describe small molecules and proteins, which directly impact the quality of the predictive models. State-of-the-art protein descriptors, however, are calculated from the protein sequence and neglect the dynamic nature of proteins. This dynamic nature can be computationally simulated with molecular dynamics (MD). Here, novel 3D dynamic protein descriptors (3DDPDs) were designed to be applied in bioactivity prediction tasks with PCM models. As a test case, publicly available G protein-coupled receptor (GPCR) MD data from GPCRmd was used. GPCRs are membrane-bound proteins, which are activated by hormones and neurotransmitters, and constitute an important target family for drug discovery. GPCRs exist in different conformational states that allow the transmission of diverse signals and that can be modified by ligand interactions, among other factors. To translate the MD-encoded protein dynamics two types of 3DDPDs were considered: one-hot encoded residue-specific (rs) and embedding-like protein-specific (ps) 3DDPDs. The descriptors were developed by calculating distributions of trajectory coordinates and partial charges, applying dimensionality reduction, and subsequently condensing them into vectors per residue or protein, respectively. 3DDPDs were benchmarked on several PCM tasks against state-of-the-art non-dynamic protein descriptors. Our rs- and ps3DDPDs outperformed non-dynamic descriptors in regression tasks using a temporal split and showed comparable performance with a random split and in all classification tasks. Combinations of non-dynamic descriptors with 3DDPDs did not result in increased performance. Finally, the power of 3DDPDs to capture dynamic fluctuations in mutant GPCRs was explored. The results presented here show the potential of including protein dynamic information on machine learning tasks, specifically bioactivity prediction, and open opportunities for applications in drug discovery, including oncology.

Fentanyl and the Fluorinated Fentanyl Derivative NFEPP Elicit Distinct Hydrogen-Bond Dynamics of the Opioid Receptor

The development of safe therapeutics to manage pain is of central interest for biomedical applications. The fluorinated fentanyl derivative N-(3-fluoro-1-phenethylpiperidin-4-yl)-N-phenylpropionamide (NFEPP) is potentially a safer alternative to fentanyl because unlike fentanyl─which binds to the μ-opioid receptor (MOR) at both physiological and acidic pH─NFEPP might bind to the MOR only at acidic pH typical of inflamed tissue. Knowledge of the protonation-coupled dynamics of the receptor-drug interactions is thus required to understand the molecular mechanism by which receptor activation initiates cell signaling to silence pain. To this end, here we have carried out extensive atomistic simulations of the MOR in different protonation states, in the absence of opioid drugs, and in the presence of fentanyl vs NFEPP. We used graph-based analyses to characterize internal hydrogen-bond networks that could contribute to the activation of the MOR. We find that fentanyl and NFEPP prefer distinct binding poses and that, in their binding poses, fentanyl and NFEPP partake in distinct internal hydrogen-bond networks, leading to the cytoplasmic G-protein-binding region. Moreover, the protonation state of functionally important aspartic and histidine side chains impacts hydrogen-bond networks that extend throughout the receptor, such that the ligand-bound MOR presents at its cytoplasmic G-protein-binding side, a hydrogen-bonding environment where dynamics depend on whether fentanyl or NFEPP is bound, and on the protonation state of specific MOR groups. The exquisite sensitivity of the internal protein-water hydrogen-bond network to the protonation state and to details of the drug binding could enable the MOR to elicit distinct pH- and opioid-dependent responses at its cytoplasmic G-protein-binding site.

Radial distribution and hydrogen bonded network graphs of alcohol-aniline binary mixture

CONTEXT

Hydrogen bonds play a vital role in the stability and functioning of biomolecules. Suitable binary liquids are often used as prototypes for the study of biologically significant hydrogen bond studies and their intricate networks. Often, such systems show deviations in their physico-chemical properties from ideal conditions. As a continuation of our research interest in biologically important hydrogen-bonded systems, this paper reports the classical molecular dynamic studies on mixtures of aniline with 8 primary alcohols (C_RH_2R+1-OH, R = 1 to 8) for the complete concentration range. The energetics results indicate the predominance of OH--O interactions over other hydrogen bonds. Structures in the network are analyzed using radial distribution function (RDF), hydrogen bond statistics, and graph theoretical analysis (GTA). Coordination numbers, hydrogen bond statistics, and GTA show a bunching of alcohol-alcohol hydrogen bonds for lower aniline concentrations, while the aniline-aniline interactions are not affected by changes in the concentration.

METHODS

Interaction energies are calculated using B3LYP/6-311G++(d, p) density functional theory using Gaussian-09. The molecular dynamics simulations are carried out using GROMACS (V 2020.6) with the OPLS/AA force field and the simulation box is visualized using VMD. The NetworkX Python package is used for GTA calculation.

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.