Bioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, Corfu, Greece.
Adv Exp Med Biol. 2023;1423:201-206. doi: 10.1007/978-3-031-31978-5_18.
Protein folding is the process by which a polypeptide chain self-assembles into the correct three-dimensional structure, so that it ends up in the biologically active, native state. Under conditions of proteotoxic stress, mutations, or cellular aging, proteins can begin to aggregate into non-native structures such as ordered amyloid fibrils and plaques. Many neurodegenerative diseases involve the misfolding and aggregation of specific proteins into abnormal, toxic species. Experimental approaches including crystallography and AFM (atomic force microscopy)-based force spectroscopy are used to exploit the folding and structural characterization of protein molecules. At the same time, computational techniques through molecular dynamics, fold recognition, and structure prediction are widely applied in this direction. Benchmarking analysis for combining and comparing computational methodologies with functional studies can decisively unravel robust interactions between the side groups of the amino acid sequence and monitor alterations in intrinsic protein dynamics with high precision as well as adequately determine potent conformations of the folded patterns formed in the polypeptide structure.
蛋白质折叠是指多肽链自行组装成正确的三维结构的过程，从而使其达到具有生物活性的天然状态。在蛋白毒性应激、突变或细胞衰老的条件下，蛋白质可能开始聚集形成非天然结构，如有序的淀粉样纤维和斑块。许多神经退行性疾病涉及特定蛋白质错误折叠和聚集成为异常的、有毒的物质。实验方法包括晶体学和基于原子力显微镜（AFM）的力谱学，用于研究蛋白质分子的折叠和结构特征。同时，通过分子动力学、折叠识别和结构预测等计算技术也被广泛应用于这一方向。通过基准分析，将计算方法与功能研究相结合和比较，可以有效地揭示氨基酸序列侧基之间的稳健相互作用，并以高精度监测内在蛋白质动力学的变化，以及充分确定多肽结构中形成的折叠模式的有效构象。
