Artificial intelligence identified peptides modulate inflammation in healthy adults

Rein, Dietrich; Ternes, Philipp; Demin, Rodion; Gierke, Jürgen; Helgason, Thrandur; Schön, Christiane

doi:10.1039/c9fo01398a

Cited by 25 publications

(24 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Further studies are necessary on the application of data mining techniques like the expert system to classify the peptide-like inhibitors, cluster analysis by self-organizing map (SOM) to make a group of inhibitors, and to understand similarity and dissimilarity should (Yan et al, 2013, Rein et al, 2019 (Zhavoronkov et al, 2020). Molecules screened from FDA approved drugs may undergo directly for clinical trials against Covid-19 disease.…”

Section: Interaction H-bond and Interaction Stability Analysismentioning

confidence: 99%

Peptide-like and small-molecule inhibitors against Covid-19

Pant

Singh

Ravichandiran

et al. 2020

Journal of Biomolecular Structure and Dynamics

255

219

View full text Add to dashboard Cite

Coronavirus disease strain (SARS-CoV-2) was discovered in 2019, and it is spreading very fast around the world causing the disease Covid-19. Currently, more than 1.6 million individuals are infected, and several thousand are dead across the globe because of Covid-19. Here, we utilized the in-silico approaches to identify possible protease inhibitors against SARS-CoV-2. Potential compounds were screened from the CHEMBL database, ZINC database, FDA approved drugs and molecules under clinical trials. Our study is based on 6Y2F and 6W63 co-crystallized structures available in the protein data bank (PDB). Seven hundred compounds from ZINC/CHEMBL databases and fourteen hundred compounds from drug-bank were selected based on positive interactions with the reported binding site. All the selected compounds were subjected to standard-precision (SP) and extra-precision (XP) mode of docking. Generated docked poses were carefully visualized for known interactions within the binding site. Molecular mechanics-generalized born surface area (MM-GBSA) calculations were performed to screen the best compounds based on docking scores and binding energy values. Molecular dynamics (MD) simulations were carried out on four selected compounds from the CHEMBL database to validate the stability and interactions. MD simulations were also performed on the PDB structure 6YF2F to understand the differences between screened molecules and co-crystallized ligand. We screened 300 potential compounds from various databases, and 66 potential compounds from FDA approved drugs. Cobicistat, ritonavir, lopinavir, and darunavir are in the top screened molecules from FDA approved drugs. The screened drugs and molecules may be helpful in fighting with SARS-CoV-2 after further studies. ARTICLE HISTORY

show abstract

Section: Interaction H-bond and Interaction Stability Analysismentioning

confidence: 99%

Peptide-like and small-molecule inhibitors against Covid-19

Pant

Singh

Ravichandiran

et al. 2020

Journal of Biomolecular Structure and Dynamics

255

219

View full text Add to dashboard Cite

show abstract

“…[31][32][33] Artificial Intelligence and machine learning approaches are increasingly seen as notable methodologies for discovery34with recent novel functional hydrolysates and peptides being described in the areas of inflammation and anti-aging. [24][25][26] For example, Kennedy and Cal et al Described for the first time the successful application of a deep learning approach for the discovery of a Pisum sativum (pea)-derived peptide with clinically proven functional skin anti-ageingproperties. 26 O. sativa, the staple food for approximately 3.5 billion people, 35 is a documented source of various functional anti-ageing ingredients36-38.…”

Section: Discussionmentioning

confidence: 99%

“…5,21,22 Computational approaches for bioactive peptide discovery have the potential to greatly accelerate the identification of novel functional ingredients. 23 Artificial intelligence (AI and machine learning methods have been used recently to successfully discover a novel anti-inflammatory ingredient derived from rice 24,25 and a natural peptide with anti-aging properties derived from the pea proteome. 26 Here, we present in vitro and ex vivo evidence validating the efficacy of pep_35E7UW, a natural peptide identified in the proteome of Oryza sativa with anti-aging activity.…”

Section: Introductionmentioning

confidence: 99%

pep_35E7UW, a natural peptide with cutaneous anti-ageing effects discovered within the Oryza sativa proteome through machine learning

Wall¹

2020

JDC

View full text Add to dashboard Cite

Background: The effects of both chronological and exogenous skin ageing have a profound impact on components of the extracellular matrix (ECM), leading to visible changes in appearance over time. Natural ingredients aimed at alleviating and counteracting the effects of cutaneous ageing are of great interest. Here, we investigate the anti-ageing potential ofpep_35E7UW, a peptide within the rice proteome identified by machine learning. Aim: To examine the in vitro and ex vivo efficacy of pep_35E7UWon ECM neosynthesis in human dermal cells and skin explants. Methods: Using machine learning, pep_35E7UW was identified and its anti-ageing effects were evaluated in human dermal fibroblasts (HDF's) and keratinocytes (HaCaTs) by means of cell culture and wound healing assays. This was further assessed by real time qPCR, where the influence on key genes in the collagen and elastin synthesis pathways was examined. Finally, the ex vivo effect of pep_35E7UW was determined by immunostaining of human skin explants. Results: Cell collagen and elastin assays of HDF's treated with pep_35E7UWreported a 32% and 51% increase in each protein respectively. Gene expression analysis determined that pep_35E7UW significantly increased collagen and elastin expression at multiple time points following treatment. Cell migration was significantly increased with pep_35E7UW treatment in the wound healing assay. pep_35E7UW topical application resulted in significant increase in elastin expression (43%) in human skin explants. Conclusion: Here, we demonstrate that pep_35E7UW, an artificial intelligence (AI) discovered peptide, has the capacity to be both an in vitro and ex vivo stimulator of fundamental ECM components. Our results position pep_35E7UWas a functional ingredient for attenuating the effects of cutaneous ageing.

show abstract

“…However, the functional food-based approach has benefitted from the recent advancements of various "omics" techniques. The use of bioinformatics has proven influential in the discovery of bioactive peptides from natural sources [23][24][25], with health benefits being associated with the presence of multiple bioactive peptides in a single natural peptide network (NPN)/hydrolysate discovered through artificial intelligence (AI) [26]. While there is an opportunity for functional food in immunomodulatory preventative strategies [27,28], there has been limited clinical data to suggest that functional foods can promote good health [29].…”

Section: Introductionmentioning

confidence: 99%

An Artificial Intelligence Characterised Functional Ingredient, Derived from Rice, Inhibits TNF-α and Significantly Improves Physical Strength in an Inflammaging Population

Kennedy

Keogh

Lopez

et al. 2020

Foods

View full text Add to dashboard Cite

Food-derived bioactive peptides offer great potential for the treatment and maintenance of various health conditions, including chronic inflammation. Using in vitro testing in human macrophages, a rice derived functional ingredient natural peptide network (NPN) significantly reduced Tumour Necrosis Factor (TNF)-α secretion in response to lipopolysaccharides (LPS). Using artificial intelligence (AI) to characterize rice NPNs lead to the identification of seven potentially active peptides, the presence of which was confirmed by liquid chromatography tandem mass spectrometry (LC-MS/MS). Characterization of this network revealed the constituent peptides displayed anti-inflammatory properties as predicted in vitro. The rice NPN was then tested in an elderly “inflammaging” population with a view to subjectively assess symptoms of digestive discomfort through a questionnaire. While the primary subjective endpoint was not achieved, analysis of objectively measured physiological and physical secondary readouts showed clear significant benefits on the ability to carry out physical challenges such as a chair stand test that correlated with a decrease in blood circulating TNF-α. Importantly, the changes observed were without additional exercise or specific dietary alterations. Further health benefits were reported such as significant improvement in glucose control, a decrease in serum LDL concentration, and an increase in HDL concentration; however, this was compliance dependent. Here we provide in vitro and human efficacy data for a safe immunomodulatory functional ingredient characterized by AI.

show abstract

Artificial intelligence identified peptides modulate inflammation in healthy adults

Abstract: Dietary bioactive peptides have been, among many functionalities, associated with immune modulation and thereby may improve resolution of inflammation.

Cited by 25 publications

References 52 publications

Peptide-like and small-molecule inhibitors against Covid-19

Peptide-like and small-molecule inhibitors against Covid-19

pep_35E7UW, a natural peptide with cutaneous anti-ageing effects discovered within the Oryza sativa proteome through machine learning

An Artificial Intelligence Characterised Functional Ingredient, Derived from Rice, Inhibits TNF-α and Significantly Improves Physical Strength in an Inflammaging Population

Contact Info

Product

Resources

About