“Dividing and Conquering” and “Caching” in Molecular Modeling

Molecular modeling is widely utilized in subjects including but not limited to physics, chemistry, biology, materials science and engineering. Impressive progress has been made in development of theories, algorithms and software packages. To divide and conquer, and to cache intermediate results have been long standing principles in development of algorithms. Not surprisingly, most important methodological advancements in more than half century of molecular modeling are various implementations of these two fundamental principles. In the mainstream classical computational molecular science, tremendous efforts have been invested on two lines of algorithm development. The first is coarse graining, which is to represent multiple basic particles in higher resolution modeling as a single larger and softer particle in lower resolution counterpart, with resulting force fields of partial transferability at the expense of some information loss. The second is enhanced sampling, which realizes “dividing and conquering” and/or “caching” in configurational space with focus either on reaction coordinates and collective variables as in metadynamics and related algorithms, or on the transition matrix and state discretization as in Markov state models. For this line of algorithms, spatial resolution is maintained but results are not transferable. Deep learning has been utilized to realize more efficient and accurate ways of “dividing and conquering” and “caching” along these two lines of algorithmic research. We proposed and demonstrated the local free energy landscape approach, a new framework for classical computational molecular science. This framework is based on a third class of algorithm that facilitates molecular modeling through partially transferable in resolution “caching” of distributions for local clusters of molecular degrees of freedom. Differences, connections and potential interactions among these three algorithmic directions are discussed, with the hope to stimulate development of more elegant, efficient and reliable formulations and algorithms for “dividing and conquering” and “caching” in complex molecular systems.     

Oxidative Folding of Proteins: The “Smoking Gun” of Glutathione

Glutathione has long been suspected to be the primary low molecular weight compound present in all cells promoting the oxidative protein folding, but twenty years ago it was found “not guilty”. Now, new surprising evidence repeats its request to be the “smoking gun” which reopens the criminal trial revealing the crucial involvement of this tripeptide.     

The Anti-Inflammatory Role of Bilirubin on “Two-Hit” Sepsis Animal Model

Introduction: Bilirubin is a product of the heme catabolism pathway, and it is excreted in bile and removed from the body through the urine. Bilirubin has potent antioxidant properties but also plays a role in anti-inflammation by protecting the body against endotoxin-induced lung inflammation, down-regulating the expression of adhesion molecules, and inhibiting the infiltration of inflammatory cells. Thus, bilirubin is a promising agent that could use in inflammation disease treatment. The application of bilirubin on the “two-hit” sepsis animal model has been, to date, unknown. Methods: we used lipopolysaccharide to induce initial insults in C57BL/6 mice. After 24 h, mice underwent cecal ligation and puncture to induce the “two-hit” sepsis model. Next, mice were administered 30 mg/kg bilirubin and we observed an improvement. Results: We observed that bilirubin inhibited the expression of pro-inflammatory cytokines, while the levels of anti-inflammatory cytokines were significantly augmented in the lung. Bilirubin improved the survival rate in the sepsis model. Furthermore, we suggest that bilirubin can modulate the accumulation of T-regulatory cells and myeloid-derived suppressor cells. Notably, bilirubin suppressed the activation and functions of T-cells. Conclusions: These results clarified that bilirubin might improve tissue injury in sepsis through anti-inflammatory mechanisms.     

Editorial for Special Issue “Genetic Basis and Epidemiology of Myopathies”

We are pleased to announce a Special Issue on the Genetic Basis and Epidemiology of Myopathies. This Special Issue is collecting papers pertaining to various lines of research focusing on the genetic basis and the epidemiology of myopathies. The Guest Editors’ note combines the contributing authors’ reviews and findings of relevant research, and we hope that future studies on myopathies will attempt to confirm these findings and, additionally, evaluate supplementary phenotypic and histological expressions of myopathies, as well as genetic factors in their pathogenesis.     

Editorial of Special Issue “Regulatory Roles of Inflammasomes in Human Diseases”

Inflammation is an innate immunity protecting the body from pathogens and cellular damages and comprises two steps; 1) priming (preparatory step) and triggering (activation step). The key feature of the triggering step is the activation of inflammasomes that are intracellular protein complexes consisting of pattern recognition receptors and inflammatory molecules. Inflammasomes are activated in response to various ligands, leading to the caspase-1-mediated maturation and secretion of pro-inflammatory cytokines, IL-1β and IL-18 and the gasdermin D-mediated pyroptosis, an inflammatory form of cell death. Previous studies have demonstrated that inflammasome activation is a key determinant of inflammatory responses and many human diseases; therefore, inflammasomes have been attracted much attention as critical drug targets to prevent and treat various human diseases.     

Dynamic “Molecular Portraits” of Biomembranes Drawn by Their Lateral Nanoscale Inhomogeneities

To date, it has been reliably shown that the lipid bilayer/water interface can be thoroughly characterized by a sophisticated so-called “dynamic molecular portrait”. The latter reflects a combination of time-dependent surface distributions of various physicochemical properties, inherent in both model lipid bilayers and natural multi-component cell membranes. One of the most important features of biomembranes is their mosaicity, which is expressed in the constant presence of lateral inhomogeneities, the sizes and lifetimes of which vary in a wide range—from 1 to 10³ nm and from 0.1 ns to milliseconds. In addition to the relatively well-studied macroscopic domains (so-called “rafts”), the analysis of micro- and nanoclusters (or domains) that form an instantaneous picture of the distribution of structural, dynamic, hydrophobic, electrical, etc., properties at the membrane-water interface is attracting increasing interest. This is because such nanodomains (NDs) have been proven to be crucial for the proper membrane functioning in cells. Therefore, an understanding with atomistic details the phenomena associated with NDs is required. The present mini-review describes the recent results of experimental and in silico studies of spontaneously formed NDs in lipid membranes. The main attention is paid to the methods of ND detection, characterization of their spatiotemporal parameters, the elucidation of the molecular mechanisms of their formation. Biological role of NDs in cell membranes is briefly discussed. Understanding such effects creates the basis for rational design of new prospective drugs, therapeutic approaches, and artificial membrane materials with specified properties.