Peptidomics and molecular docking reveal digestion-resistant IgE-binding epitopes in bovine β-lactoglobulin and α-lactalbumin from simulated infant digestion.

In silico molecular docking is used to predict how a small molecule, the ligand, interacts with a target protein, its receptor. Together with experimental methods like NMR or X-ray crystallography, industrial and academic groups use it for their investigation of compounds with the potential to modulate the protein's function and become a lead molecule for drug development. The interpretation of raw data, from NMR, mass spectrometry or crystallography, is greatly assisted by computers. Biochemists can, perhaps better than anybody else, perform individual analyses for the computational modeling of interactions. However, an extension towards virtual screening of compound libraries, i.e. the computational docking of thousands or even millions of ligands to a target receptor, is often perceived as technically challenging and computationally too expensive in the biochemical community. Here we describe how to integrate spare resources of regular desktop computers on and off campus using the Berkeley Open Infrastructure for Network Computing (BOINC) infrastructure for volunteer grid computing. We have brought both the BOINC server and the Auto Dock software suite into the Debian and Ubuntu Linux distributions, and provide detailed instructions to help render the implementation of a large-scale high-throughput docking (HTD) project straightforward. Thus, this increased availability of computational resources, protocols and source code opens up the possibility of many new self-run projects and collaborations, for those who may be adopting the technology for the first time. On the technical level, we expect to observe more contributors from the Open Source and academic communities. On the biological side, we anticipate new and faster progress on commercially less interesting and so-called 'neglected' diseases.

High-throughput molecular docking is a data-driven simulation methodology to estimate millions of molecules' position and interaction strength (ligands) when interacting with a given protein site. Because of its data-driven nature, the high-throughput molecular docking performance depends on how fast we can ingest data into the processing pipeline and how efficiently we can write molecular docking results to a shared file. This work characterizes the I/O performance of a high-performance, high-throughput molecular docking application, called Docker-HT, running on a supercomputer up to 512 computing nodes with two different parallel I/O configurations. We show that a tuned I/O configuration can improve the overall parallel efficiency from 71% to 90% on 512 nodes and identify and solve a performance degradation observed when running on 16 and 32 nodes.

Oral cancer is among the most common cancer in the world. Tobacco, alcohol, and viruses have been regarded as a well- known risk factors of OCC however, 15% of OSCC cases occurred each year without these known risk factors. Recently a myriad of studies has shown that bacterial infections lead to cancer. Accumulated shreds of evidence have demonstrated the role of Porphyromonas gingivalis (P. gingivalis) in OSCC. The virulence factor FimA ofP. gingivalisactivates the oncogenic pathways in OSCC by upregulating various cytokines. It also led to the inactivation of a tumor suppressor protein p53. The present Insilico study uses High-Throughput Virtual Screening, molecular docking, and molecular dynamics techniques to find the potential compounds against the target protein FimA. The goal of this study is to identify the anti-cancer lead compounds retrieved from natural sources that can be used to develop potent drug molecules to treat P.gingivalis-related OSCC. The anticancer natural compounds library was screened to identify the potential lead compounds. Furthermore, these lead compounds were subjected to precise docking, and based on the docking score potential lead compounds were identified. The top docked receptor-ligand complex was subjected to molecular dynamics simulation. A study of this insilico finding provides potent lead molecules which help in the development of therapeutic drugs against the target protein FimA in OSCC.

Although mothers’ milk is the ideal food for babies, infant formula has become an alternative when breastfeeding is not possible or inadequate for babies. To design a proper formula for babies, it is essential to understand the digestibility of macronutrients and their bio-accessibility in the infant gastrointestinal tract. Because in vivo gastrointestinal studies on human infants are restricted by ethical constraint, cost issues, and intensive resource, in vitro models could be a better replacement. In vitro models offer advantages with low cost, easy sampling accessibility and no ethical issues. This thesis aims to assess the digestibility of each ingredient proteins, lipids, and carbohydrates in infant formulation then compare with mothers’ milk. A static bench-top in vitro model for infant digestion was set up with infant gastric pH (4.0-4.5) and the activity of simulated digestive enzymes suitable for human infants with 60 minutes of gastric phase and 120 minutes of intestinal phase.Popular protein sources of caseins, whey, and soy proteins were employed in infant formulations. The in vitro digestion of these proteins in infant formulations was studied in the presence of enzyme proteases only (without lipolytic enzymes). Obtained results showed around 20% of caseins and no components of whey were hydrolysed after 60 minutes in the simulated stomach. In the simulated intestinal phase, 8% of α–lactalbumin was hydrolysed while caseins and β–lactoglobulin were completely digested immediately and 30 minutes respectively after addition of intestinal digestive proteases. Overall, soy proteins indicated lower level of hydrolysis than dairy proteins during in vitro infant digestion as observed by SDS-PAGE. The soy protein fractions glycinin and β-conglycinin were partially hydrolysed during the gastrointestinal phase. The observed pH drop confirms that caseins are easily digested in the intestinal phase compared to whey and soy protein. Gastric digestion resulted in a decrease of the particle size of protein aggregates, but no fat coalescence was observed during both gastric and intestinal digestion in the given conditions.The in vitro digestion of hydrolysed and non-hydrolysed dairy (casein and whey proteins) was studied under conditions without lipolytic enzymes. Results show hydrolysed proteins were completely digested in the small intestine while non-hydrolysed proteins (caseins, α-lactalbumin, β-lactoglobulin, conglycinin, glycinin) were only partially digested in the simulated gastrointestinal tract. Although observed pH-drop for non-hydrolysed protein formulations was lower, significantly higher levels of ninhydrin-reactive amino nitrogen in hydrolysed proteins suggested higher digestibility of hydrolysed proteins than their non-hydrolysed counterparts. Only formulations containing caseins showed a decrease in particle size of protein aggregates during gastric digestion. No fat globule coalescence was observed during both gastric and intestinal digestions in the given conditions.Lipid digestion of infant formula emulsions based on both hydrolysed and non-hydrolysed proteins (dairy and soy) with vegetable oils was studied under an in vitro gastrointestinal environment (with and without proteases). The size and distribution of oil droplets, released free fatty acids, and micro-structure of the digesta were monitored over the digestion period. Oil droplet coalescence was observed during gastric phase but not in the intestinal phase for most of formulations in both the matrices. Higher rate of lipolysis in infant formula emulsion stabilized by hydrolysed proteins was noted. The obtained results suggested that digestive proteases had a limited impact on lipolysis of these particular infant formula systems.The in vitro digestion of carbohydrate in infant formulations and control formulations (solution of carbohydrate without proteins and vegetable oils) suggests infant formulations with precooked starch or locust bean gum have a higher viscosity than other formulation without thickening agents. No carbohydrate was digested in stomach phase. Precooked starch is well digested in the simulated intestine, but locust bean gum in infant formula resisted in vitro digestion. Higher amount of released glucose were observed in the digesta of the formulations with lactose than in the formulations with glucose syrup.The in vitro digestion of mothers’ milk and infant formulation based on bovine proteins and vegetable oils in the presence of all the digestive enzymes showed caseins digested quicker than whey proteins in the gastrointestinal tract. Lipolysis of mothers’ milk releases free fatty acids with medium carbon chain from C10 to C14, which are very little in infant formulation. However, similar amount of total free fatty acids was obtained from the digestion of the fat in mothers’ milk and in the infant formulation. Lactose in mothers’ milk or in infant milk formulae behaved the same in the in vitro infant digestion as the same type of lactose was used which is in water soluble state without any effect of pH, thus is easily accessible to enzyme.

A micro-molecule of dimension 125 nm has caused around 479 million human infections (80 M for the USA) and 6.1 million human deaths (977,000 for the USA) worldwide and slashed the global economy by US$ 8.5 Trillion over two years period. The only other events in recent history that caused comparative human life loss through direct usage (either by human or nature, respectively) of structure-property relations of 'nano-structures' (either human-made or nature, respectively) were nuclear bomb attacks during World War II and 1918 Flu Pandemic. This molecule is called SARS-CoV-2, which causes a disease known as COVID-19. The high liability cost of the pandemic had incentivized various private, government, and academic entities to work towards finding a cure for this and emerging diseases. As an outcome, multiple vaccine candidates are discovered to avoid the infection in the first place. But so far, there has been no success in finding fully effective therapeutic candidates. In this paper, we attempted to provide multiple therapy candidates based upon a sophisticated multi-scale in-silico framework, which increases the probability of the candidates surviving an in-vivo trial. We have selected a group of ligands from the ZINC database based upon previously partially successful candidates, i.e., Hydroxychloroquine, Lopinavir, Remdesivir, Ritonavir. We have used the following robust framework to screen the ligands; Step-I: high throughput molecular docking, Step-II: molecular dynamics analysis, Step-III: density functional theory analysis. In total, we have analyzed 242,000(ligands)*9(proteins) = 2.178 million unique protein binding site/ligand combinations. The proteins were selected based on recent experimental studies evaluating potential inhibitor binding sites. Step-I had filtered that number down to 10 ligands/protein based on molecular docking binding energy, further screening down to 2 ligands/protein based on drug-likeness analysis. Additionally, these two ligands per protein were analyzed in Step-II with a molecular dynamic modeling-based RMSD filter of less than 1Å. It finally suggested three ligands (ZINC001176619532, ZINC000517580540, ZINC000952855827) attacking different binding sites of the same protein(7BV2), which were further analyzed in Step-III to find the rationale behind comparatively higher ligand efficacy.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10853-022-07195-8.

Computational methods are a powerful and consolidated tool in the early stage of the drug lead discovery process. Amongthese techniques, high-throughput molecular docking has proved to be extremely useful in identifying novel bioactive compounds within large chemical libraries. In the docking procedure, the predominant binding mode of each small molecule within a target binding site is assessed, and a docking score reflective of the likelihood of binding is assigned to them. These methods also shed light on how a given hit could be modified in order to improve protein-ligand interactions and are thus able to guide lead optimization. The possibility of reducing time and cost compared to experimental approaches made this technology highly appealing. Due to methodological developments and the increase of computational power, the application of quantum mechanical methods to study macromolecular systems has gained substantial attention in the last decade. A quantum mechanical description of the interactions involved in molecular association of biomolecules may lead to better accuracy compared to molecular mechanics, since there are many physical phenomena that cannot be correctly described within a classical framework, such as covalent bond formation, polarization effects, charge transfer, bond rearrangements, halogen bonding, and others, that require electrons to be explicitly accounted for. Considering the fact that quantum mechanics-based approaches in biomolecular simulation constitute an active and important field of research, we highlight in this work the recent developments of quantum mechanical-based molecular docking and high-throughput docking.

IgE-binding epitope mapping of tropomyosin allergen (Exo m 1) from Exopalaemon modestus, the freshwater Siberian prawn

Our previous studies have revealed that L. acidophilus possesses inhibitory effects on PCV2 proliferation in vivo, although the underlying mechanisms remain elusive. Probiotics like L. acidophilus are known to exert antiviral through their metabolites. Therefore, in this study, non-targeted metabolomics was used to detect the changes in metabolites of L. acidophilus after 24 h of proliferation. Subsequently, high-throughput molecular docking was utilized to analyze the docking scores of these metabolites with PCV2 Cap and Rep, aiming to identify compounds with potential anti-PCV2 effects. The results demonstrated that 128 compounds such as Dl-lactate were significantly increased. The results of high-throughput molecular docking indicated that compounds such as ergocristine, and telmisartan formed complexes with Cap and Rep, suggesting their potential anti-PCV2 properties. Furthermore, compounds like vitamin C, exhibit pharmacological effects consistent with L. acidophilus adding credence to the idea that L. acidophilus may exert pharmacological effects through its metabolites. These results will provide a foundation for the study of L. acidophilus.

Aflatoxins are toxic chemicals produced by Aspergillus fungi. Reports exist on the relationship of aflatoxin exposure via contaminated food and feed to hepatotoxicity and liver cancer. Aflatoxin B1 (AFB1) and Aflatoxin G1 (AFG1) are two dangerous types of aflatoxins for human health. Bovine α-lactalbumin (ALA) is the second major whey protein in milk which bear diverse biological functions. In this study, the interaction of AFB1 and AFG1 with the ALA protein was studied using fluorescence spectroscopy, molecular docking and molecular dynamic (MD) simulation. The spectroscopy experiments showed that the interaction with AFB1 and AFG1significantly quenched the intrinsic fluorescence emission of ALA via a static quenching mechanism. The free energy of binding and binding constant (Ka) obtained from the intrinsic fluorescence results were -5.32 kcal per mol and 0.80 × 104 L mol-1 for AFB1 and -5.64 kcal per mol and 1.35 × 104 l mol-1 for AFG1, respectively. Molecular docking studies were conducted before and after the MD simulation to estimate the binding sites, Ka s and binding mode. Results from the molecular docking showed that AFB1 and AFG1 bound to ALA via hydrophobic interaction and hydrogen bond. After MD simulation, the precision of the Ka obtained from the docking results was improved and it was more similar to the experimental results of fluorescence spectroscopy. Other simulation results were aligned well with the molecular docking and fluorescence spectroscopy results. Accordingly, AFB1and AFG1 could form complex with ALA, however, AFG1 showed higher affinity for binding to ALA and more compact complex structure.

The analysis by liquid chromatography coupled to tandem mass spectrometry of complex peptide mixtures, generated by proteolysis of protein samples, is the main proteomics method used today. The approach is based on the assumption that each protein present in a sample reproducibly and predictably generates a relatively small number of peptides that can be identified by mass spectrometry. In this study this assumption was examined by a targeted peptide sequencing strategy using inclusion lists to trigger peptide fragmentation attempts. It was found that the number of peptides observed from a single protein is at least one order of magnitude greater than previously assumed. This unexpected complexity of proteomics samples implies substantial technical challenges, explains some perplexing results in the proteomics literature, and prompts the need for developing alternative experimental strategies for the rapid and comprehensive analysis of proteomes.

Background: Cow’s milk is one of the most common causes of food allergy in the first years of life. We recently defined IgE and IgG binding epitopes for α_s1-casein, a major cow’s milk allergen, and found an association between recognition of certain epitopes and clinical symptoms of cow’s milk allergy (CMA). Since α-lactalbumin (ALA) and β-lactoglobulin (BLG) are suspected to be significant allergens in cow’s milk, we sought to determine the structure of sequential epitopes recognized by IgE antibodies to these proteins. We further sought to assess the pattern of epitope recognition in association with the clinical outcome of CMA. Methods: According to the known amino acid sequence of ALA and BLG, 57 and 77 overlapping decapeptides (offset by two amino acids), respectively, were synthesized on a cellulose derivatized membrane. Sera from 11 patients 4–18 years of age with persistent CMA (IgE to cow’s milk >100 kU_A/l) were used to identify IgE binding epitopes. In addition, 8 patients <3 years of age and likely to outgrow their milk allergy (IgE to cow’s milk <30 kU_A/l) were used to investigate the differences in epitope recognition between patients with ‘persistent’ and those with ‘transient’ CMA. Seven patients 4–18 years of age were used for assessing the IgG binding regions. Results: In patients with persistent allergy, four IgE binding and three IgG binding regions were identified on ALA, and seven IgE and six IgG binding epitopes were detected on BLG. The younger patients that are likely to outgrow their allergy recognized only three of these IgE binding epitopes on BLG and none on ALA. Conclusions: The presence of IgE antibodies to multiple linear allergenic epitopes may be a marker of persistent CMA. The usefulness of IgE binding to distinct epitopes on whey proteins in defining the patients that would have a lifelong CMA needs to be investigated in further studies.

Curcumin and capsaicin play a vital role in anti-inflammatory and anti-cancer mechanism as they are used as therapeutic drugs/adjuvants. Our previous study including many reports explored strong inhibitory effect of curcumin and capsaicin on lipopolysaccharide-induced polymorph blood mononuclear cells (PBMCs) and cancer cells. Therefore, a systematic study was carried out to identify the potential protein targets of curcumin and capsaicin in cancer as well as angiogenesis through network pharmacology and molecular docking approaches. In the present investigation, we employed integrative prediction of cancer targets of curcumin and capsaicin through the ChEMBL and STITCH databases, followed by network construction, network topology, gene ontology, pathway enrichment and molecular docking studies. The gene ontology analysis made it possible to identify a library of possible cancer targets of curcumin (34 targets) and capsaicin (35 targets). Based on topological analysis, the unique target of curcumin and capsaicin was proposed by identifying essential bottleneck/hub node MAPK1. Further, PANTHER gene set analysis was used to distinguish the biologically enriched pathways in top identified gene clusters (MAPK1). To validate the identified target, high-throughput molecular docking was employed as both molecules curcumin and capsaicin along with standard ulixertinib were docked against MAPK1 to understand the binding interaction. The docking results of MAPK1 with curcumin (− 7.6 kcal/mol) has shown good inhibitory effect similar to that of standard control ulixertinib (− 8.1 kcal/mol) compared with capsaicin (− 6.0 kcal/mol). Based on the molecular interaction, MAPK1 identified through the network pharmacology approach could be a probable target of curcumin and capsaicin to prevent angiogenesis in cancer.

The effect of molecular weights on the survivability of casein-derived antioxidant peptides after the simulated gastrointestinal digestion

Effects of dry heating on the cleavage of casein and whey protein into peptides under simulated infant digestion.

In vitro digestion of milk proteins including intestinal brush border membrane peptidases. Transepithelial transport of resistant casein domains