Skip to content
#protein folding Open access

Droplet Microfluidic Hydrogen/Deuterium Exchange for Investigating Protein Dynamics with Millisecond Precision

Sep 2026 · Analytical Chemistry · 1 citation · 82 references
Innovative Microfluidic and Catalytic Techniques Innovation

Abstract

Hydrogen/Deuterium eXchange (HDX) methods for studying protein dynamics would benefit from millisecond-scale incubations to probe intrinsically disordered proteins, highly dynamic regions, and conformation changes. Here, we investigate droplet microfluidics for rapid mixing to trigger D2O labeling, uniform incubations, and rapid droplet merging for acid quenching in advance of mass spectrometry. A surfactant-free merging approach combining expansion elements for synchronized droplet collision proved robust. The high diffusive flux of D2O and protons enables microsecond mixing to trigger and arrest D2O labeling, respectively, affording the possibility of single millisecond incubations. Droplet HDX processors were used to measure the fast uptake characteristics of a model peptide. Forward exchange measurements demonstrate D2O labeling to be the rate-limiting step, in essence defining 10 milliseconds as the minimum practical incubation time for proteins at room temperature, pD 7.4. With the ability to access millisecond time scales, the fast dynamics of calmodulin, a model of calcium-triggered allostery with rapid conformational switching, was investigated. At 10 milliseconds, we could observe significant deuterium uptake within the well-defined EF-hand Ca2+ binding motifs. These findings demonstrate that millisecond HDX enabled by droplet microfluidics allows areas of heightened plasticity to be detected within a stably folded protein.

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.