pH-induced structural changes of apo-lactoferrin and implications for its function: a molecular dynamics simulation study

Impact of Ultrafiltration on the Physicochemical Properties of Bovine Lactoferrin: Insights into Molecular Mass, Surface Morphology, and Elemental Composition

The large-scale isolation of bovine lactoferrin (bLF) typically involves using large amounts of concentrated eluents, which might introduce impurities to the final product. Sometimes, protein pre-concentration is required for the greater accuracy of experimental results. In this research, the supplied bLF sample was subjected to additional ultrafiltration (UF) to eliminate possible small impurities, such as salts and peptides of bLF. Beforehand, the basic characterization of native bLF, including surface-charge properties and the structural sensitivity to the various pH conditions, was performed. The study aimed to evaluate the difference in molecular mass, primary structure, surface morphology, and elemental composition of the protein before and after UF. The research was provided by application of spectroscopic, spectrometric, electrophoretic, and microscopic techniques. The evident changes in the surface morphology of bLF were observed after UF, while the molecular masses of both proteins were comparable. According to MALDI-TOF/MS results, UF had a positive impact on the bLF sample representation, improving the identification parameters, such as sequence coverage and intensity coverage.

Research advances of molecular docking and molecular dynamic simulation in recognizing interaction between muscle proteins and exogenous additives

During storage and processing, muscle proteins, e.g. myosin and myoglobin, will inevitably undergo degeneration, which is thus accompanied by quality deterioration of muscle foods. Some exogenous additives have been widely used to interact with muscle proteins to stabilize the quality of muscle foods. Molecular docking and molecular dynamics simulation (MDS) are regarded as promising tools for recognizing dynamic molecular information at atomic level. Molecular docking and MDS can explore chemical bonds, specific binding sites, spatial structure changes, and binding energy between additives and muscle proteins. Development and workflow of molecular docking and MDS are systematically summarized in this review. Roles of molecular simulations are, for the first time, comprehensively discussed in recognizing the interaction details between muscle proteins and exogenous additives aimed for stabilizing color, texture, flavor, and other properties of muscle foods. Finally, research directions of molecular docking and MDS for improving the qualities of muscle foods are discussed.

Molecular modeling of lactoferrin for food and nutraceutical applications: insights from in silico techniques

Lactoferrin is a protein, primarily found in milk that has attracted the interest of the food industries due to its health properties. Nevertheless, the instability of lactoferrin has limited its commercial application. Recent studies have focused on encapsulation to enhance the stability of lactoferrin. However, the molecular insights underlying the changes of structural properties of lactoferrin and the interaction with protectants remain poorly understood. Computational approaches have proven useful in understanding the structural properties of molecules and the key binding with other constituents. In this review, comprehensive information on the structure and function of lactoferrin and the binding with various molecules for food purposes are reviewed, with a special emphasis on the use of molecular dynamics simulations. The results demonstrate the application of modeling and simulations to determine key residues of lactoferrin responsible for its stability and interactions with other biomolecular components under various conditions, which are also associated with its functional benefits. These have also been extended into the potential creation of enhanced lactoferrin for commercial purposes. This review provides valuable strategies in designing novel nutraceuticals for food science practitioners and those who have interests in acquiring familiarity with the application of computational modeling for food and health purposes.

Molecular Insights into Conformational Heterogeneity and Enhanced Structural Integrity of Helicobacter pylori DNA Binding Protein Hup at Low pH

The summarized amalgam of internal relaxation modulations and external forces like pH, temperature, and solvent conditions determine the protein structure, stability, and function. In a free-energy landscape, although conformers are arranged in vertical hierarchy, there exist several adjacent parallel sets with conformers occupying equivalent energy cleft. Such conformational states are pre-requisites for the functioning of proteins that have oscillating environmental conditions. As these conformational changes have utterly small re-arrangements, nuclear magnetic resonance (NMR) spectroscopy is unique in elucidating the structure-dynamics-stability-function relationships for such conformations. Helicobacter pylori survives and causes gastric cancer at extremely low pH also. However, least is known as to how the genome of the pathogen is protected from reactive oxygen species (ROS) scavenging in the gut at low pH under acidic stress. In the current study, biophysical characteristics of H. pylori DNA binding protein (Hup) have been elucidated at pH 2 using a combination of circular dichroism, fluorescence, NMR spectroscopy, and molecular dynamics simulations. Interestingly, the protein was found to have conserved structural features, differential backbone dynamics, enhanced stability, and DNA binding ability at low pH as well. In summary, the study suggests the partaking of Hup protein even at low pH in DNA protection for maintaining the genome integrity.

The milk-derived lactoferrin inhibits V-ATPase activity by targeting its V1 domain

Lactoferrin (Lf), a bioactive milk protein, exhibits strong anticancer and antifungal activities. The search for Lf targets and mechanisms of action is of utmost importance to enhance its effective applications. A common feature among Lf-treated cancer and fungal cells is the inhibition of a proton pump called V-ATPase. Lf-driven V-ATPase inhibition leads to cytosolic acidification, ultimately causing cell death of cancer and fungal cells. Given that a detailed elucidation of how Lf and V-ATPase interact is still missing, herein we aimed to fill this gap by employing a five-stage computational approach. Molecular dynamics simulations of both proteins were performed to obtain a robust sampling of their conformational landscape, followed by clustering, which allowed retrieving representative structures, to then perform protein-protein docking. Subsequently, molecular dynamics simulations of the docked complexes and free binding energy calculations were carried out to evaluate the dynamic binding process and build a final ranking based on the binding affinities. Detailed atomist analysis of the top ranked complexes clearly indicates that Lf binds to the V₁ cytosolic domain of V-ATPase. Particularly, our data suggest that Lf binds to the interfaces between A/B subunits, where the ATP hydrolysis occurs, thus inhibiting this process. The free energy decomposition analysis further identified key binding residues that will certainly aid in the rational design of follow-up experimental studies, hence bridging computational and experimental biochemistry.

Computational Methods and Tools in Antimicrobial Peptide Research

The evolution of antibiotic-resistant bacteria is an ongoing and troubling development that has increased the number of diseases and infections that risk going untreated. There is an urgent need to develop alternative strategies and treatments to address this issue. One class of molecules that is attracting significant interest is that of antimicrobial peptides (AMPs). Their design and development has been aided considerably by the applications of molecular models, and we review these here. These methods include the use of tools to explore the relationships between their structures, dynamics, and functions and the increasing application of machine learning and molecular dynamics simulations. This review compiles resources such as AMP databases, AMP-related web servers, and commonly used techniques, together aimed at aiding researchers in the area toward complementing experimental studies with computational approaches.