Johnson Quentin R, Lindsay Richard J, Petridis Loukas, Shen Tongye
UT-ORNL Graduate School of Genome Science and Technology, Knoxville, TN 37996, USA.
Department of Biochemistry and Cellular & Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA.
Molecules. 2015 Apr 28;20(5):7700-18. doi: 10.3390/molecules20057700.
Carbohydrate recognition by proteins, such as lectins and other (bio)molecules, can be essential for many biological functions. Recently, interest has arisen due to potential protein and drug design and future bioengineering applications. A quantitative measurement of carbohydrate-protein interaction is thus important for the full characterization of sugar recognition. We focus on the aspect of utilizing computer simulations and biophysical models to evaluate the strength and specificity of carbohydrate recognition in this review. With increasing computational resources, better algorithms and refined modeling parameters, using state-of-the-art supercomputers to calculate the strength of the interaction between molecules has become increasingly mainstream. We review the current state of this technique and its successful applications for studying protein-sugar interactions in recent years.
蛋白质（如凝集素和其他生物分子）对碳水化合物的识别对于许多生物学功能至关重要。最近，由于潜在的蛋白质和药物设计以及未来的生物工程应用，人们对此产生了兴趣。因此，对碳水化合物-蛋白质相互作用进行定量测量对于全面表征糖识别非常重要。在本综述中，我们重点关注利用计算机模拟和生物物理模型来评估碳水化合物识别的强度和特异性这一方面。随着计算资源的增加、算法的改进和建模参数的细化，使用最先进的超级计算机来计算分子间相互作用的强度已变得越来越主流。我们回顾了该技术的当前状态及其近年来在研究蛋白质-糖相互作用方面的成功应用。
