生物矿化
生物信息学
破译
管道(软件)
岩松珠母贝
计算生物学
蛋白质组学
分子动力学
模块化设计
计算机科学
纳米技术
化学
生物信息学
生物
材料科学
珍珠牡蛎
基因
计算化学
珍珠
操作系统
生物化学
程序设计语言
哲学
神学
古生物学
作者
Wentao Dong,Liping Xie,Rongqing Zhang
标识
DOI:10.3389/fmars.2024.1362131
摘要
Mollusk shells contain biominerals with remarkable mechanical properties enabled by a small fraction of embedded organic matrix proteins. However, the specific molecular functions of most shell proteins have remained elusive. Traditional genomics and functional studies are extremely laborious to identify key components. To address this, we developed an in-silico pipeline integrating protein structure modeling, molecular dynamics simulations, and machine learning to elucidate the critical ion protein interactions governing shell formation. Using the pearl oyster Pinctada fucata as a test case, our framework successfully recapitulated known protein functions and predicted roles of uncharacterized proteins to guide future experiments. Moreover, the pipeline’s modular design enables versatile applications for rapidly elucidating structure-function relationships in diverse biomineralization systems, complementing conventional wet-lab methods. Overall, this computational approach leverages automatic simulations and analytics to unlock molecular insights into shell protein ion dynamics, accelerating the discovery of key crystallization regulators for bioinspired materials design.
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