Results 131 to 140 of about 227,395 (295)
Machine Learning Accelerates Crystallization for Structure Determination
Angewandte Chemie, EarlyView.Single‐crystal x‐ray diffraction (SCXRD) is often constrained by the difficulty of obtaining suitable crystals. Here, a machine learning‐accelerated co‐crystal discovery workflow is established for a crystalline mate strategy that achieves over 95% prediction accuracy and experimentally delivers 114 co‐crystals from 120 candidates.
Cui‐Zhou Luan +10 more
wiley +2 more sources
Frontiers in Aging NeuroscienceThe maintenance of protein homeostasis is essential for neuronal survival and function; however, it progressively declines with age, predisposing the brain to neurodegenerative diseases.
Noureddine Ben Khalaf
doaj +1 more source
Advanced Science, EarlyView.The integration of ROS‐generating systems with H2S depletion strategies effectively overcomes the limitations imposed by endogenous antioxidant defenses on ROS‐based antimicrobial therapies. In this study, the Cu‐MOF is incorporated into pillararene‐embedded COF, achieving a “three‐in‐one” antimicrobial effect that markedly alleviated periodontal ...
Shuang Liang +9 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz +2 more
wiley +1 more source
The dynamic triage interplay of Hsp90 with its chaperone cycle and client binding
Nature CommunicationsHsp90, a crucial molecular chaperone, regulates diverse client proteins, impacting both normal biology and disease. Central to its function is its conformational plasticity, driven by ATPase activity and client interactions.
Xiaozhan Qu +5 more
doaj +1 more source
Protein evolution speed depends on its stability and abundance and on chaperone concentrations. [PDF]
, 2018 Proteins evolve at different rates. What drives the speed of protein sequence changes? Two main factors are a protein's folding stability and aggregation propensity. By combining the hydrophobic-polar (HP) model with the Zwanzig-Szabo-Bagchi rate theory,
Agozzino, Luca, Dill, Ken A
core +1 more source
Chaperone-assisted translocation of flexible polymers in three dimensions
, 2016 Polymer translocation through a nanometer-scale pore assisted by chaperones binding to the polymer is a process encountered in vivo for proteins. Studying the relevant models by computer simulations is computationally demanding.
Linna, R. P., Suhonen, P. M.
core +1 more source
Advanced Intelligent Discovery, EarlyView.This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah +3 more
wiley +1 more source
The refolding activity of the yeast heat shock proteins Ssa1 and Ssa2 defines their role in protein translocation. [PDF]
, 1996 Ssa1/2p, members of one of the yeast cytosolic hsp70 subfamilies, have been implicated in the translocation of secretory proteins into the lumen of the ER.
Bush, GL, Meyer, DI
core
Advanced Intelligent Discovery, EarlyView.scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta +3 more
wiley +1 more source