利用绝对结合自由能计算分析糖蛋白 A 的识别能力

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL Journal of Chemical Information and Modeling Pub Date : 2024-10-16 DOI:10.1021/acs.jcim.4c01088
Sondos Musleh, Irfan Alibay, Philip C. Biggin, Richard A. Bryce
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引用次数: 0

摘要

碳水化合物是分子识别和信号传递过程的关键生物媒介。在本案例研究中,我们探讨了绝对结合自由能(ABFE)计算预测一组五种相关碳水化合物配体对凝集素蛋白凝集素 A 的亲和力的能力,这些配体从 27 个原子的单糖到 120 个原子的复合型 N-连接聚糖核心五糖不等。ABFE 计算对配体的亲和力进行了定量排序和估算,与微量热测定法相比,结合自由能的平均符号误差为 -0.63 ± 0.04 kcal/mol。因此,较大碳水化合物配体的较低结合效率得到了很好的再现:等温滴定量热法得出的糖核五糖及其组成的三糖和单糖化合物的配体效率值分别为-0.14、-0.22 和 -0.41千卡/摩尔/重原子。ABFE 计算预测这些配体效率分别为-0.14 ± 0.02、-0.24 ± 0.03 和 -0.46 ± 0.06 kcal/mol/重原子。因此,ABFE 方法正确识别了关键锚定甘露糖残基的高亲和力,以及五糖两个 β-GlcNAc 臂对结合的微不足道的贡献。虽然对这些极性、柔性和弱结合配体的构象和相互作用进行取样仍存在挑战,但我们发现 ABFE 方法在该凝集素系统中表现良好。这种方法有望成为预测和分解碳水化合物-蛋白质相互作用的定量工具,并有可能应用于治疗、疫苗和诊断的设计。
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Analysis of Glycan Recognition by Concanavalin A Using Absolute Binding Free Energy Calculations
Carbohydrates are key biological mediators of molecular recognition and signaling processes. In this case study, we explore the ability of absolute binding free energy (ABFE) calculations to predict the affinities of a set of five related carbohydrate ligands for the lectin protein, concanavalin A, ranging from 27-atom monosaccharides to a 120-atom complex-type N-linked glycan core pentasaccharide. ABFE calculations quantitatively rank and estimate the affinity of the ligands in relation to microcalorimetry, with a mean signed error in the binding free energy of −0.63 ± 0.04 kcal/mol. Consequently, the diminished binding efficiencies of the larger carbohydrate ligands are closely reproduced: the ligand efficiency values from isothermal titration calorimetry for the glycan core pentasaccharide and its constituent trisaccharide and monosaccharide compounds are respectively −0.14, −0.22, and −0.41 kcal/mol per heavy atom. ABFE calculations predict these ligand efficiencies to be −0.14 ± 0.02, −0.24 ± 0.03, and −0.46 ± 0.06 kcal/mol per heavy atom, respectively. Consequently, the ABFE method correctly identifies the high affinity of the key anchoring mannose residue and the negligible contribution to binding of both β-GlcNAc arms of the pentasaccharide. While challenges remain in sampling the conformation and interactions of these polar, flexible, and weakly bound ligands, we nevertheless find that the ABFE method performs well for this lectin system. The approach shows promise as a quantitative tool for predicting and deconvoluting carbohydrate–protein interactions, with potential application to design of therapeutics, vaccines, and diagnostics.
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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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