Deciphering Cellular Intricacies for Drug Discovery: A Synergistic Approach Combining Cryo-CLEM, Electromechanical Modeling, and AI-Guided Simulations.

IF 1.7 4区 医学 Q4 BIOCHEMICAL RESEARCH METHODS
Sijia Zhang, Jingsong Ai, Jiasheng Zhao, Zhiwei Yang
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引用次数: 0

Abstract

Biological membranes and their vesicular derivatives constitute dynamic nanoscale architectures critical to cellular function. Their electromechanical properties and molecular diversity govern processes ranging from vesicle trafficking and signal transduction to pathogen entry and organelle morphogenesis. While decades of foundational research have advanced our understanding of lipid bilayer assembly and membrane protein interactions, achieving a comprehensive, multiscale understanding of membrane dynamics, spanning molecular interactions to cellular-scale behavior, remains a paramount challenge in modern cell biology. This editorial presents recent breakthroughs at the intersection of three transformative domains: cryo- correlative light and electron microscopy (cryo-CLEM), electromechanical theory, and AI-driven simulation, to elucidate their collective impact on resolving membrane complexity. By integrating structural insights, the innovations are revolutionizing the drug discovery pipelines by accelerating candidate screening, reducing false-positive rates, optimizing assay design, and implementing high-density library strategies. It also critically evaluates technical challenges while proposing an actionable roadmap to unify these modalities into cohesive workflows, advancing both basic membrane research and translational therapeutic development.

破译细胞的复杂性药物发现:一个协同方法结合冷冻clem,机电建模,和人工智能指导的模拟。
生物膜及其囊泡衍生物构成了对细胞功能至关重要的动态纳米级结构。它们的机电特性和分子多样性控制着从囊泡运输和信号转导到病原体进入和细胞器形态发生的过程。虽然几十年的基础研究已经提高了我们对脂质双分子层组装和膜蛋白相互作用的理解,但实现对膜动力学的全面,多尺度的理解,从分子相互作用到细胞尺度的行为,仍然是现代细胞生物学的首要挑战。这篇社论介绍了三个变革领域交叉点的最新突破:低温相关光学和电子显微镜(cryo- clem),机电理论和人工智能驱动的模拟,以阐明它们对解决膜复杂性的共同影响。通过整合结构见解,这些创新通过加速候选筛选、降低假阳性率、优化分析设计和实施高密度文库策略,正在彻底改变药物发现管道。它还批判性地评估了技术挑战,同时提出了一个可行的路线图,将这些模式统一到有凝聚力的工作流程中,推进基础膜研究和转化治疗开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.10
自引率
5.60%
发文量
327
审稿时长
7.5 months
期刊介绍: Combinatorial Chemistry & High Throughput Screening (CCHTS) publishes full length original research articles and reviews/mini-reviews dealing with various topics related to chemical biology (High Throughput Screening, Combinatorial Chemistry, Chemoinformatics, Laboratory Automation and Compound management) in advancing drug discovery research. Original research articles and reviews in the following areas are of special interest to the readers of this journal: Target identification and validation Assay design, development, miniaturization and comparison High throughput/high content/in silico screening and associated technologies Label-free detection technologies and applications Stem cell technologies Biomarkers ADMET/PK/PD methodologies and screening Probe discovery and development, hit to lead optimization Combinatorial chemistry (e.g. small molecules, peptide, nucleic acid or phage display libraries) Chemical library design and chemical diversity Chemo/bio-informatics, data mining Compound management Pharmacognosy Natural Products Research (Chemistry, Biology and Pharmacology of Natural Products) Natural Product Analytical Studies Bipharmaceutical studies of Natural products Drug repurposing Data management and statistical analysis Laboratory automation, robotics, microfluidics, signal detection technologies Current & Future Institutional Research Profile Technology transfer, legal and licensing issues Patents.
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