Effect of grape seed extract (Vitis vinifera L.) on downregulation of heat shock protein 90 alpha class A1 to attenuate psoriasis- a molecular docking simulation, in vitro and in vivo evaluation
Psoriasis is a chronic inflammatory skin disorder marked by skin hyperproliferation and rapid inflammation. Effective therapies should be immunomodulatory, anti-inflammatory and antioxidant in nature. This study evaluates the therapeutic potential of grape seed extract (GSE) (Vitis vinifera L.) in managing psoriasis by investigating its ability to inhibit the biomarker heat shock protein 90 alpha class A1 (HSP90AA1). Gas chromatography (GC) revealed the phytoconstituents of grape seed extract and anti-inflammatory and antioxidant properties were evaluated to determine its therapeutic potential. A docking simulation study of the important bioactives of GSE was screened for their binding activity against HSP90AA1 which was identified as a psoriasis marker gene through network pharmacology in a previous study. The antiproliferation effect was determined by cell viability assay. A psoriasis model was established in HaCaT cells with inflammatory cytokines and qRT-PCR estimated the HSP90AA1 expression. An imiquimod-induced psoriasis mice model was used to evaluate the effectiveness of GSE on splenomegaly. Gas chromatography analysis revealed that GSE contains a significant concentration of flavonoids, which could substantiate its bioactivity. It consists of 40 different compounds making it diverse in therapeutic potential. Grape seed extract demonstrated potent antioxidant activity with IC50 values of 2.38 ± 0.06 mg/mL for DPPH (2,2-diphenyl-1-picrylhydrazyl) scavenging and 1.24 ± 0.07 mg/mL for nitric oxide (NO) scavenging and effective protection against inflammatory protein denaturation, with an IC50 value of 1.16 ± 0.02 mg/mL. Molecular studies revealed that key bioactives, Epicatechin-3-gallate and Procyanidin B4, possess a high binding affinity for the psoriasis marker protein HSP90AA1. Domain analysis of HSP90AA1 and the nature of its amino acids that interacted with the bioactives of grape seed were observed. Grape seed extract exhibited cell viability of 59.51 % against HaCaT keratinocyte cell lines, indicating the presence of antiproliferative activity. It also showed significant 0.2-fold downregulation of HSP90AA1 gene expression in human keratinocytes. Its systemic immunomodulatory potential was validated by its ability to reverse splenomegaly in an imiquimod-induced psoriasis mouse model, supporting its potential for adjunct anti-psoriatic therapy.
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.
D. Graziotin, Xiaofeng Wang, P. Abrahamsson· SSE@SIGSOFT FSE· 56 citations· ⚡4
This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.
Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson· International Conference on...· 44 citations· ⚡5
It is demonstrated that linker-free PROTACs can outperform traditional designs, marking a paradigm shift in PROTAC development for targeted protein degradation.
Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or sequence constraints.
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.