Skip to content
#protein folding Open access

Structure-guided design of Anaplasma P44 protein-based chimeric antigens for serodiagnosis of anaplasmosis in dogs

Sep 2026 · Infection and Immunity · 0 citations · 38 references
Medicine

TL;DR

The sensitivity and specificity of ADC1 support its potential use as a diagnostic Ag for anaplasmosis and are consistent with AlphaFold v2 predictions, which further predict the core of P44 to be an eight-stranded β-barrel.

Abstract

ABSTRACT Canine and human anaplasmosis are tick-borne diseases caused by the obligate intracellular bacteria, Anaplasma phagocytophilum and Anaplasma platys, respectively. In veterinary medicine, peptides derived from the immunodominant P44 protein are used to detect antibodies in serological point-of-care tests for anaplasmosis. To inform efforts to develop improved chimeric diagnostic proteins for anaplasmosis, the structure of the predicted surface-exposed domain (residues 151–308) of P44 was determined at a resolution of 1.65 Å. This domain comprises six α-helices and six short β-strands connected by loop regions. A structural similarity search of the P44151–308 domain using the Distance Matrix Alignment server against the AlphaFold Database revealed that the domain represents a previously uncharacterized protein fold. The determined structure is consistent with AlphaFold v2 predictions, which further predict the core of P44 to be an eight-stranded β-barrel. Using P44 fragments, immunodominant epitopes were mapped within residues 151–308. Four chimeric genes (ADC1, ADC2, ADC3, and ADC4) were designed that incorporate the analogous immunodominant P44 domains from A. phagocytophilum and A. platys. The recombinant ADC chimerics were assessed for sensitivity and specificity by screening with serum from dogs diagnosed with anaplasmosis, Lyme disease, or ehrlichiosis, with sera from specific pathogen-free dogs serving as negative controls. Accuracy was further demonstrated by screening characterized serum samples from coyotes (Canis latrans; wild canids). The ADC1 chimeric provided 100% sensitivity and 98.04% specificity. The sensitivity and specificity of ADC1 support its potential use as a diagnostic Ag for anaplasmosis.

Read PDF

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.