Results 151 to 160 of about 600,294 (239)

3DProtDTA: a deep learning model for drug-target affinity prediction based on residue-level protein graphs. [PDF]

RSC Adv, 2023
Voitsitskyi T, Stratiichuk R, Koleiev I, Popryho L, Ostrovsky Z, Henitsoi P, Khropachov I, Vozniak V, Zhytar R, Nechepurenko D, Yesylevskyy S, Nafiiev A, Starosyla S.   +12 more
europepmc   +1 more source

Biomimetic Copper Nanoparticles Coated with ACE2‐Overexpressing Membranes for Selective SARS‐CoV‐2 Neutralization and Disinfection

Advanced Healthcare Materials, EarlyView.
By fusing ACE2‐overexpressing membrane‐integrated liposome (MIL) with copper nanoparticles, the biomimetic Cu@MIL nanostructures were created that directly hijack the SARS‐CoV‐2 entry pathway. These particles combine potent virus‐targeting precision with intrinsic antiviral activity, achieving rapid neutralization and disinfection.
Pooja Aich, Wei‐Pang Chung, Wen‐Jyun Wang, Hidenobu Takahashi, Ming‐Shun Hsieh, Ying‐Chen Lin, Oh Seok Kwon, Wei‐Peng Li, Wei‐Lun Huang   +8 more
wiley   +1 more source

DTAP: a unified graph transformer framework for joint prediction of drug-target affinity and docking pose. [PDF]

Brief Bioinform
Liu J, Ding Y, Yan Y, Zheng L, Pan Y.
europepmc   +1 more source

Nanotherapies for Atherosclerosis: Targeting, Catalysis, and Energy Transduction

Advanced Healthcare Materials, EarlyView.
Atherosclerosis management is hindered by poor drug targeting and plaque heterogeneity. Nanotechnology overcomes these barriers via three core strategies: (1) target‐engineered nanocarriers that achieve lesion‐specific precision via ligand modification, biomimetic camouflage, stimuli‐responsive release, and self‐propelling nanomotors; (2) catalytic ...
Yuqi Yang, Jingguo Qu, Tonghuan Xiao, Xinyang Han, Michael Tin‐Cheung Ying   +4 more
wiley   +1 more source

Respiratory Organ‐on‐a‐Chip for Disease Modeling: From Architecture to Functional Integration

Advanced Healthcare Materials, EarlyView.
Respiratory organ‐on‐a‐chip (ROC) models capture key mechanical and cellular cues of the human respiratory system, enabling quantitative dissection of disease mechanisms. This review links ROC architectures to disease modeling, functional integration, and commercialization, and proposes a decision framework that aligns model complexity with mechanistic
Jinzhuo Hu, Yongjie Tang, Sidi Liu, Tao Xu, Qian Liu   +4 more
wiley   +1 more source

CASTER-DTA: equivariant graph neural networks for predicting drug-target affinity. [PDF]

Brief Bioinform
Kumar R, Romano JD, Ritchie MD.
europepmc   +1 more source

Shellac‐Mediated Assembly of Nanoparticles for mRNA Delivery

Advanced Healthcare Materials, EarlyView.
A shellac‐mediated nanoparticle assembly strategy is presented, involving the complexation of mRNA and low‐molecular‐weight cationic molecules (e.g., polyethyleneimine, chitosan, lipids, and poly‐l‐lysine), followed by capping with shellac. This nanoparticle platform enables mRNA transfection following intravenous injection and facilitates gene editing
Meizhang Lu, Jingqu Chen, Zhixing Lin, Wanjun Xu, Tianzheng Wang, Shiyao Li, Die Yang, Frank Caruso   +7 more
wiley   +1 more source

MixingDTA: improved drug-target affinity prediction by extending mixup with guilt-by-association. [PDF]

Bioinformatics
Kim Y, Bang D, Koo B, Yi J, Cho C, Choi J, Kim S.   +6 more
europepmc   +1 more source

Plant‐Produced Viral Nanoparticles Decorated with Nanobodies Against HER2 Improve Retention and Recruitment of Immune Cells in Solid Tumors

Advanced Healthcare Materials, EarlyView.
Potato virus X is a filamentous RNA plant virus that can be engineered into a molecular tool for cancer therapy. We produced genetically‐encoded virus‐derived nanoparticles decorated with nanobodies targeting cancer cell receptors, epidermal growth factor receptor (EGFR) and human epidermal growth factor 2 (HER2).
Enrique Lozano‐Sanchez, Miguel A. Moreno‐Gonzalez, Fernando Merwaiss, Nicole F. Steinmetz, José‐Antonio Daròs   +4 more
wiley   +1 more source

UAMRL: multi-granularity uncertainty-aware multimodal representation learning for drug-target affinity prediction. [PDF]

Bioinformatics
Xu W, Liu X, Wang J, Zhang F, Hu D, Zong L.   +5 more
europepmc   +1 more source