Results 31 to 40 of about 3,106 (176)

Diffusion‐Based Generative Model With Scaffold‐Hopping Strategy Yields Highly Potent Bioactive Molecules

Advanced Science, EarlyView.
SMarT‐Diff introduces a multi‐objective generative paradigm that integrates scaffold hopping with structure‐aware scoring to enable controlled exploration beyond the training distribution. The framework consistently balances drug‐likeness, synthesizes accessibility and bioactivity, yielding chemically diverse candidates with enhanced properties.
Yuwei Yang, Xiaoqing Gong, Shukai Gu, Jing Li, Bo Liu, Yanan Tian, Qianqian Zhang, Xiaojun Yao, Huanxiang Liu   +8 more
wiley   +1 more source

A Data‐Driven Inverse Design Methodology for Magnetic Soft Millirobots Navigating in Confined Spaces

Advanced Science, EarlyView.
A data‐efficient inverse design framework automates the optimization of magnetic soft millirobots for confined‐space navigation. Integrating a physics‐based Cosserat rod model with Bayesian optimization efficiently identifies high‐performance geometries.
Ziyu Ren, Hong Wang, Chak Wang Tse, Yi Zheng, Xi Chen, Wenqi Hu   +5 more
wiley   +1 more source

Discriminator‐Guided Inverse Folding for Multi‐Property Protein Design

Advanced Science, EarlyView.
Discriminator‐Guided Inverse Folding (DGIF) integrates multiple property predictors trained from single‐property datasets to guide protein sequence generation from a backbone structure. DGIF enables simultaneous improvement of thermostability and solubility without requiring multi‐property annotated datasets and generates designs that move toward the ...
Yuchuan Zheng, Chuyi Liu, Zhaoming Liu, Mao Su, Chenyu Tang, Xiang Zheng, Hao Zhang, Jingyuan Li   +7 more
wiley   +1 more source

Synergistic HMGN1 and VP64 Fusions Potentiate High‐Precision and PAM‐Flexible Base Editing

Advanced Science, EarlyView.
A novel CDA1Δ‐SpRY architecture fused with HMGN1 and VP64 yields a nearly PAM‐less base editing platform. By focusing cytosine conversion predominantly at position −18, this synergistic complex ensures highly precise targeting. Demonstrating enhanced efficiency across diverse models, including yeast and rice, the platform offers a robust solution for ...
Xi Luo, Yuyao Qu, Zhengyan Ye, Zheng Li, Yuanyan Zhang, Longjiong Luo, Shaokang Li, Wei Zhao, Ming Wang, Ralph Bock, Jianmin Wan, Junjie Tan   +11 more
wiley   +1 more source

A Phase‐Resolved Geometric Deep Learning Framework Maps Structural Determinants of Disease‐Associated Protein Aggregation and Guides Suppressor Design

Advanced Science, EarlyView.
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio, Wei Xuan Wilson Loo, Yan Shan Loo, Wen Xin Tan, Hui Xuan Lim, Huitao Liu, Chen Seng Ng   +6 more
wiley   +1 more source

An exciting Approach to Theoretical Spectroscopy

Advanced Science, EarlyView.
ABSTRACT Theoretical spectroscopy, and more generally, electronic‐structure theory, are powerful concepts for describing the complex many‐body interactions in materials. They cover methods from ground‐state properties to lattice excitations and light‐matter interaction, including time‐resolved variants.
Martí Raya‐Moreno, Alexander Buccheri, Noah Alexy Dasch, Nasrin Farahani, Ignacio Gonzalez Oliva, Andris Gulans, Seokhyun Hong, Manoar Hossain, Hannah Kleine, Martin Kuban, Sven Lubeck, Benedikt Maurer, Pasquale Pavone, Fabian Peschel, Daria Popova‐Gorelova, Lu Qiao, Elias Richter, Santiago Rigamonti, Ronaldo Rodrigues Pela, Maximilian Schebek, Kshitij Sinha, Daniel T. Speckhard, Jan Stutz, Sebastian Tillack, Dmitry Tumakov, Jānis Užulis, Mara Voiculescu, Cecilia Vona, Mao Yang, Claudia Draxl   +29 more
wiley   +1 more source

Exact Discrete Stochastic Simulation With Deep‐Learning‐Scale Gradient Optimization

Advanced Science, EarlyView.
A 203,796‐parameter gene regulatory network classifies handwritten digits with 98.4% accuracy using exact stochastic dynamics. The framework decouples forward simulation from backward differentiation, making continuous‐time Markov chain models compatible with deep‐learning optimization.
Jose M. G. Vilar, Leonor Saiz
wiley   +1 more source

Machine‐Learning Framework for Designing Stable Interfaces in All‐Solid‐State Lithium‐Ion Batteries

Advanced Science, EarlyView.
A data‐driven strategy is developed to discover coating materials for all‐solid‐state lithium batteries. Using calculations of interfacial reactivity, unsupervised pattern recognition, and machine‐learning prediction, the study identifies low‐reactivity compositional patterns and screens new lithium‐based oxide and polyanion candidates, extending ...
Sehyeok Park, Myeongcho Jang, Hun‐Gi Jung, Kyung Yoon Chung, Seungho Yu   +4 more
wiley   +1 more source

Engineering Strategies to Suppress Thermal Runaway Propagation in Lithium‐Ion Battery: Mechanisms, Metrics, Materials, and Evaluation Methods

Advanced Science, EarlyView.
Thermal runaway propagation can transform a single‐cell failure into a system‐level hazard in lithium‐ion battery packs. This review clarifies how heat transfer, gas venting, combustion, and configuration govern cell‐to‐cell failure, and links measurable metrics, pathway‐oriented suppression materials, and experimental/modeling tools to guide safer ...
Jinrong Su, Anna DiFelice, Jayani Mawela, Jianing Gan, Shuai Che, Wonhee Cho, Hanghang Yan, Yaohong Xiao, Xinxin Yao, Xiangwei Guo, Rui Wang, Dingchuan Xue, Hanlong Liu, Solomon Adera, Zhan Chen, Lei Chen   +15 more
wiley   +1 more source

Multiscale Coupling From Mastication to Retronasal Aroma Perception: The PG‐DTCFN Model and Multiphysics Simulation

Advanced Science, EarlyView.
Using grilled lamb skewers as a model system, this work builds a multiscale coupling framework from oral processing to retronasal aroma perception, reveals dual‐kinetic release patterns and Electroencephalogram‐characterized central encoding features, and proposes an interpretable physics‐guided deep learning model validated by multiphysics simulation,
Che Shen, Xiongfeng He, Zihao Li, Zidong Chen, Jiajin Sun, Xinyu Jiang, Yunhui Zhang, Lizhang Wu, Ran Wang, Jingnan Lu, Bo Wang, Kezhou Cai, Baocai Xu   +12 more
wiley   +1 more source