Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Department of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
ACS Appl Bio Mater. 2024 Feb 19;7(2):617-625. doi: 10.1021/acsabm.2c01023. Epub 2023 Mar 27.
Computer-aided molecular design and protein engineering emerge as promising and active subjects in bioengineering and biotechnological applications. On one hand, due to the advancing computing power in the past decade, modeling toolkits and force fields have been put to use for accurate multiscale modeling of biomolecules including lipid, protein, carbohydrate, and nucleic acids. On the other hand, machine learning emerges as a revolutionary data analysis tool that promises to leverage physicochemical properties and structural information obtained from modeling in order to build quantitative protein structure-function relationships. We review recent computational works that utilize state-of-the-art computational methods to engineer peptides and proteins for various emerging biomedical, antimicrobial, and antifreeze applications. We also discuss challenges and possible future directions toward developing a roadmap for efficient biomolecular design and engineering.
计算机辅助分子设计和蛋白质工程在生物工程和生物技术应用中成为有前途和活跃的学科。一方面,由于过去十年计算能力的提高,建模工具包和力场已经被用于对包括脂质、蛋白质、碳水化合物和核酸在内的生物分子进行精确的多尺度建模。另一方面,机器学习作为一种革命性的数据分析工具出现,有望利用建模获得的物理化学性质和结构信息来构建定量的蛋白质结构-功能关系。我们综述了最近利用最先进的计算方法来设计肽和蛋白质以用于各种新兴的生物医学、抗菌和抗冻应用的计算工作。我们还讨论了开发有效的生物分子设计和工程路线图所面临的挑战和可能的未来方向。