Why are there no clinically-approved drugs targeting disordered proteins? [0.03%]
为何没有临床批准的靶向异常蛋白的药物？
Thomas Löhr,Gogulan Karunanithy,Gabriella T Heller
Thomas Löhr
Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) are critical regulators in health and disease but remain underexploited as drug targets. Unlike folded proteins, they populate dynamic ensembles where inte...
Interpreting chemical crosslinks: Score-based approaches and deep neural networks [0.03%]
基于分数的方法和深度神经网络在解释化学交联中的应用
Xingyu Chen,Kai Steffen Stroh,Jan Erzberger et al.
Xingyu Chen et al.
Chemical cross-linking coupled with mass spectrometry (XL-MS) has become a powerful tool for probing residue-level proximities within macromolecular assemblies. By providing sparse but informative distance restraints, XL-MS can be integrate...
De novo engineering of protein interactions: Retrospective and current advances [0.03%]
从头设计蛋白质相互作用：回顾及最新进展
Alisa Khramushin,Evgenia Elizarova,Bruno E Correia
Alisa Khramushin
New deep learning-based methods for modeling and generation of protein structures have opened a new chapter in the field of protein design, transforming many previously unattainable challenges into routine tasks. Protein-binder design, an i...
Mohd Ahsan,Chinmai Pindi,Souvik Sinha et al.
Mohd Ahsan et al.
Graph neural networks (GNNs) are emerging as powerful tools for advancing molecular dynamics (MD) simulations, providing data-driven frameworks to complement traditional physics-based approaches. By representing atoms and their interactions...
Cristian Rocha-Roa,Stefano Vanni
Cristian Rocha-Roa
Nearly a quarter of the proteins encoded in most organisms are transmembrane proteins. Contrary to textbook description, many feature a hydrophilic groove which is laterally exposed to the hydrophobic region of the lipid membrane. This cavi...
Ligand-like lipid interactions with membrane proteins: Simulations and machine learning [0.03%]
类配体脂质与膜蛋白相互作用：模拟和机器学习
George Hedger,Edward Lyman,Sarah L Rouse
George Hedger
Membrane lipids can bind to specific sites on membrane proteins in a ligand-like manner and modulate protein structure and function. Molecular dynamics simulations encompass a suite of approaches to identify, characterise, and explain the a...
Moving the antibody: Molecular dynamics for molecular mechanisms and developability [0.03%]
移动抗体：分子动力学在分子机制和可开发性中的应用
Matteo Cagiada,Charlotte M Deane
Matteo Cagiada
Protein dynamics prediction by integrating biophysics and artificial intelligence [0.03%]
集生物物理和人工智能预测蛋白质动力学
Hengyan Huang,Xingyue Guan,Wenfei Li et al.
Hengyan Huang et al.
Proteins often rely on conformational dynamics to perform their biological functions. A detailed understanding of protein dynamics is fundamental to revealing the biophysical principles of life and to accelerating therapeutic discovery. How...
Recent advances in AI-driven pKa prediction for proteins and small molecules [0.03%]
近年来基于人工智能的蛋白质和小分子pKa预测研究进展
Yandong Huang
Yandong Huang
Advances in machine-learning techniques and the availability of high-quality pKa databases have promoted the development of AI-driven pKa predictors. This review surveys recent advances in AI-driven pKa prediction for both proteins and smal...
Shan Sun,Sen-Fang Sui
Shan Sun
Membrane protein complexes are essential for cellular functions, which rely on both constituent protein structures and their interactions within native membranes. While in vitro methods have successfully yielded high-resolution structures o...