Skip to content
#protein folding Open access

Systematic screening of Citri reticulatae pericarpium polysaccharides reveals uronic acid–associated anti-SARS-CoV-2 activity

Sep 2026 · Figshare
Polysaccharides and Plant Cell Walls

Abstract

Citri reticulatae pericarpium (CP), the dried peel of Citrus reticulata Blanco (Rutaceae), is a common traditional Chinese medicine and edible material with effects of regulating Qi, strengthening the spleen, and resolving phlegm. While its flavonoids have been extensively studied, the polysaccharides, which are the major components of its aqueous extract, remain systematically unexplored. In this study, a crude polysaccharide fraction (C142) was extracted from CP and fractionated by DEAE Sepharose™ Fast Flow column to obtain secondary polysaccharides. Analyses showed they had high total carbohydrate and galacturonic acid (19–39%), low protein, molecular weights of 20–25 kDa, main monosaccharides of galactose, galacturonic acid, and arabinose, and both α- and β-glycosidic linkages (FT-IR). Antiviral assays showed that C142, C144, and C146 significantly inhibited SARS-CoV-2 replication: at 1 mg/mL, they reduced viral RNA by over 100-fold, with clear inhibition even at 200 μg/mL, stronger than that of Remdesivir. Higher galacturonic acid content may be associated with antiviral activity, but this relationship is likely influenced by multiple structural and compositional factors. This study elucidates the physicochemical and preliminary structural characteristics of CP polysaccharides, as well as their anti-SARS-CoV-2 properties, linking their uronic acid-rich fractions to CP’s traditional lung-protective effects, providing scientific evidence for CP’s pharmacological material basis and antiviral mechanisms.

View source

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

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. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

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. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

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 · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

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 · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

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 seque...

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

Google DeepMind Blog Sep 30, 2026

Introducing SynthID Bio

Proof of concept for watermarking AI-generated proteins while preserving biological function.

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

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.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.