Results 141 to 150 of about 291,222 (247)

Deep GIST: Deep Learning Models for Predicting the Distribution of Hydration Thermodynamics around Proteins. [PDF]

J Chem Inf Model
Fukushima Y, Yoshidome T.
europepmc   +1 more source

Amyloid PDB structure set

, 2019
Amyloids are insoluble proteins of a cross-β structure found as deposits in many diseases. They are largely examined structurally, but there is a lack of a unique structural database for amyloid proteins resolved with atomic resolution. Here, we present a constructed set of amyloid structures found in the Protein Data Bank based on keyword criterion as
Stanković, Ivana M., Hall, Michael B., Zarić, Snežana D.   +2 more
openaire   +1 more source

Genetic Control of Tissue Remodeling by a Non‐Coding SNP in ITGA8 Explains Carotenoid‐Based Color Polymorphism in Marine Mollusks

Advanced Science, EarlyView.
In this study, the orange‐muscle giant abalone (Haliotis gigantea) is used as a model to identify a non‐coding SNP that disrupts the interaction between ITGA8 pre‐mRNA and the splicing factor ILF2, leading to altered ITGA8 splicing. These splicing changes promote carotenoid accumulation in abalone muscle through the regulation of tissue remodeling ...
Xiaohui Wei, Wenzhu Peng, Zekun Huang, Bingye Yang, Yiyu Wu, Minzhen Han, Yi Wang, Bingling Peng, Guosheng Hu, Jiawei Hong, Guijia Liu, Linwei Nie, Yang Gan, Miaoqin Huang, Xuan Luo, Weiwei You, Wen Liu, Caihuan Ke   +17 more
wiley   +1 more source

Development and Structural Characterization of UTE‐156, a Covalent Inhibitor of the VCP/p97 AAA+ ATPase

Advanced Science, EarlyView.
The AAA+ ATPase Valosin‐containing protein (VCP/p97) regulates protein homeostasis by unfolding ubiquitinated substrates. Here, we describe UTE‐156, a novel irreversible covalent inhibitor that modifies Cys522 in the D2 ATPase motor domain. Although its pharmacochemical limitations preclude immediate therapeutic use, UTE‐156 serves as a valuable ...
Daniela Tamayo‐Jaramillo, Subramanya Hegde, Xuan Jia, Kimberly Coffman, Hariprasad Vankayalapati, David Bearss, Kevin B. Jones, Alex W. Stark, Peter S. Shen   +8 more
wiley   +1 more source

CHARMM-GUI Hybrid ML/MM Builder for Hybrid Machine Learning and Molecular Mechanical Modeling and Simulations. [PDF]

J Chem Inf Model
Szczepaniak F, Suh D, Im W.
europepmc   +1 more source

Machine Learning‐Guided Engineering of Protein Phase Separation Properties in Immune Regulation

Advanced Science, EarlyView.
PScalpel, a machine learning model integrating protein structure extraction, graph contrastive learning, and a genetic algorithm, guides the engineering of protein phase separation ability. It adopts transfer learning methods to provide predictive recommendations for protein phase separation ability changes through single amino acid mutations in a ...
Chenqiu Zhang, Jia Wang, Zhe Wang, Liyan Zhu, Sihui Cai, Luzhi Zhan, Haorui Liang, Yaoxing Wu, Jianqiang Li, Jun Cui   +9 more
wiley   +1 more source

Structural and Functional Validation of Pseudomonas Savastanoi Ethylene Forming Enzymes Reveals Flexibility in 2-Oxoglutarate Binding Mode and Conformation. [PDF]

Chembiochem
Sun Y, Dhingra S, Allen MD, Cheng ESZ, Zhang Z, Schofield CJ, Brewitz L.   +6 more
europepmc   +1 more source

The ITGB2‐COPS3‐SOX2 Axis and SOX2 Liquid‐Liquid Phase Separation: Dual Mechanisms Governing Osteosarcoma Stemness

Advanced Science, EarlyView.
Osteosarcoma stemness is driven by the ITGB2‐COPS3‐SOX2 signaling axis. This study reveals that nuclear COPS3 stabilizes SOX2, which in turn undergoes liquid‐liquid phase separation to promote stemness. Based on this mechanism, a novel COPS3 inhibitor, Z‐5891, was developed, effectively suppressing tumor growth and stemness in vivo, offering a ...
Lei Guo, Zhiqing Zhao, Wei Wang, Jianfang Niu, Bing Wang, Yunfei Lin, Wei Guo, Taiqiang Yan   +7 more
wiley   +1 more source

Characterizing the Conformational Dynamics of the Ribose Transporter B Protein in <i>Escherichia coli</i>: Enhanced Sampling via Multiple Force Fields. [PDF]

J Chem Theory Comput
Juraschko N, Rocha FK, Khalid S.
europepmc   +1 more source

Selectivity Filter Dynamics Define Ion Conductance and Selectivity Differences in CNG and HCN Channels

Advanced Science, EarlyView.
Cyclic nucleotide‐gated (CNG) and hyperpolarization‐activated cyclic nucleotide‐gated (HCN) channels share substantial sequence and structural similarity but differ markedly in ion conductance and K+ selectivity. Microsecond‐scale atomistic MD simulations qualitatively reproduced the conductance differences observed in single‐channel recordings and ...
Haoran Liu, Klaus Benndorf, Yessenbek K. Aldakul, Han Sun   +3 more
wiley   +1 more source