Kumar Shubham, Mohan Anand, Sharma Neeta Raj, Kumar Anil, Girdhar Madhuri, Malik Tabarak, Verma Awadhesh Kumar
School of Bioengineering and Biosciences, Lovely Professional University, Phagwara, Punjab 144001, India.
Gene Regulation Laboratory, National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India.
ACS Omega. 2024 Jun 10;9(25):26838-26862. doi: 10.1021/acsomega.4c02466. eCollection 2024 Jun 25.
In the rapidly evolving landscape of nanomedicine, aptamers have emerged as powerful molecular tools, demonstrating immense potential in targeted therapeutics, diagnostics, and drug delivery systems. This paper explores the computational features of aptamers in nanomedicine, highlighting their advantages over antibodies, including selectivity, low immunogenicity, and a simple production process. A comprehensive overview of the aptamer development process, specifically the Systematic Evolution of Ligands by Exponential Enrichment (SELEX) process, sheds light on the intricate methodologies behind aptamer selection. The historical evolution of aptamers and their diverse applications in nanomedicine are discussed, emphasizing their pivotal role in targeted drug delivery, precision medicine and therapeutics. Furthermore, we explore the integration of artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), Internet of Medical Things (IoMT), and nanotechnology in aptameric development, illustrating how these cutting-edge technologies are revolutionizing the selection and optimization of aptamers for tailored biomedical applications. This paper also discusses challenges in computational methods for advancing aptamers, including reliable prediction models, extensive data analysis, and multiomics data incorporation. It also addresses ethical concerns and restrictions related to AI and IoT use in aptamer research. The paper examines progress in computer simulations for nanomedicine. By elucidating the importance of aptamers, understanding their superiority over antibodies, and exploring the historical context and challenges, this review serves as a valuable resource for researchers and practitioners aiming to harness the full potential of aptamers in the rapidly evolving field of nanomedicine.
在快速发展的纳米医学领域,适配体已成为强大的分子工具,在靶向治疗、诊断和药物递送系统中展现出巨大潜力。本文探讨了适配体在纳米医学中的计算特性,强调了它们相对于抗体的优势,包括选择性、低免疫原性和简单的生产过程。对适配体开发过程,特别是指数富集配体系统进化(SELEX)过程的全面概述,揭示了适配体选择背后的复杂方法。讨论了适配体的历史演变及其在纳米医学中的多种应用,强调了它们在靶向药物递送、精准医学和治疗中的关键作用。此外,我们还探讨了人工智能(AI)、机器学习(ML)、物联网(IoT)、医疗物联网(IoMT)和纳米技术在适配体开发中的整合,说明了这些前沿技术如何正在彻底改变适配体的选择和优化,以实现定制化生物医学应用。本文还讨论了推进适配体的计算方法面临的挑战,包括可靠的预测模型、广泛的数据分析和多组学数据整合。它还涉及与适配体研究中使用AI和IoT相关的伦理问题和限制。本文考察了纳米医学计算机模拟方面的进展。通过阐明适配体的重要性、理解它们相对于抗体的优势,并探索历史背景和挑战,本综述为旨在在快速发展的纳米医学领域充分发挥适配体潜力的研究人员和从业者提供了宝贵资源。