Computational Molecular Biology 2024, Vol.14, No.5, 182-190 http://bioscipublisher.com/index.php/cmb 182 Research Perspective Open Access Molecular Interactions in Biological Systems: Technological Applications and Innovations Liangbing Chen , Xianle Ruan, Xinyi Li, Huanling Fu College of Life Sciences and Agronomy, Zhoukou Normal University, Zhoukou, 466000, Henan, China Corresponding author: chliangbing@163.com Computational Molecular Biology, 2024, Vol.14, No.5 doi: 10.5376/cmb.2024.14.0021 Received: 15 Jul., 2024 Accepted: 26 Aug., 2024 Published: 10 Sep., 2024 Copyright © 2024 Chen et al., This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Chen et al., 2024, Molecular interactions in biological systems: technological applications and innovations, Computational Molecular Biology, 14(5): 182-190 (doi: 10.5376/cmb.2024.14.0021) Abstract This study reviews the complex interactions between proteins, DNA, RNA, lipids, and small molecules in biological systems, emphasizing the critical role of the "interactome" concept in understanding organismal functions. These interactions, including protein-protein and protein-RNA interactions, play significant roles in cellular processes such as recognition, regulation, and signaling, and have great potential in drug discovery. The research methods encompass various biophysical techniques, such as mass spectrometry (MS), nuclear magnetic resonance (NMR) spectroscopy, and surface plasmon resonance (SPR), which are used to elucidate the structure and dynamics of molecular interactions. The results demonstrate that molecular interactions are key to developmental innovation, environmental adaptation, and disease mechanisms, particularly in revealing the interactions between biological membranes and small molecules, protein complex formation, and drug target discovery. The study highlights the importance of future improvements in research methods, especially through the integration of computational and experimental approaches, to better understand the dynamic molecular interactions in biological systems. Keywords Molecular interactions; Biophysical techniques; Protein-protein interactions; Molecular dynamics simulations; Drug discovery 1 Introduction Molecular interactions in biological systems are fundamental to the understanding of cellular functions and the molecular basis of diseases. These interactions encompass a wide range of biomolecules, including proteins, DNA, RNA, lipids, and small molecules, which interact in complex and dynamic ways to regulate cellular processes such as recognition, regulation, and signaling (Ardini et al., 2022). The concept of the "interactome" highlights the complexity of these interactions, suggesting that the functionality of an organism can be better understood by examining the network of interactions among its biomolecules rather than solely its genetic content. For instance, protein-protein interactions (PPIs) are crucial for cellular functions and have been extensively studied to map out the functional proteome and understand disease mechanisms (Havugimana et al., 2017). Additionally, the interactions between proteins and RNA play significant roles in cellular processes and are emerging as important targets for drug discovery (Steinmetz et al., 2023). The study of molecular interactions has been greatly advanced by various biophysical techniques. Mass spectrometry (MS) has become a pivotal tool for characterizing protein complexes and mapping interaction networks on a global scale. Techniques such as chemical cross-linking combined with MS provide structural insights into protein interactions that are difficult to study using conventional methods (Chavez and Bruce, 2019).Nuclear magnetic resonance (NMR) spectroscopy, electron paramagnetic resonance (EPR) spectroscopy, and fluorescence-based methods are also employed to gain detailed understanding of biomolecular interactions. Moreover, molecular dynamics (MD) simulations have revolutionized our understanding of how small molecules interact with biological membranes, providing atomic-level insights into the binding and permeation processes. The advent of deep learning methods, such as AlphaFold (Parker and Pratt, 2022), has further enhanced our ability to predict protein structures and their complexes, offering new avenues for exploring molecular interactions. This study provides a comprehensive overview of the current research status of molecular interactions in biological systems, with a focus on the technological applications and innovations that have emerged in recent
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