{"title":"Understanding fibroblast growth factor-heparan sulfate recognition by molecular dynamics approaches.","authors":"Sergey A Samsonov, Adam Sieradzan, Avner Yayon","doi":"10.1093/glycob/cwag067","DOIUrl":null,"url":null,"abstract":"<p><p>Glycosaminoglycans, linear periodic anionic polysaccharides composed of repeating disaccharide units, are highly heterogeneous with respect to their chemical composition, sulfation patterns, conformational, dynamic and functional properties. The \"sulfation code,\" which links specific sulfation patterns of these molecules to their biological function, is a key concept for understanding their structure-function relationships. However, both experimental and computational approaches face significant challenges in deciphering this code. In this computational study, we focus on fibroblast growth factor-glycosaminoglycan interactions, which play crucial roles in numerous biologically relevant processes. First, we evaluate the sensitivity and predictive power of currently available computational protocols for studying these systems. We then rigorously investigate the effects of heparin 6-O-desulfation on its interactions with several fibroblast growth factors. We conclude that, depending on the 6-O-sulfation pattern and the length of the oligosaccharide, either predominantly electrostatic interactions or a more complex interplay between electrostatic and hydrophobic interactions determines the specificity of the resulting protein-glycosaminoglycan complex. Finally, we demonstrate that a previously developed coarse-grained model successfully reproduces both the structural and thermodynamic properties of the analysed molecular systems. The results obtained in this study may contribute to the understanding of the fundamental mechanisms underlying protein-glycosaminoglycan interactions and represent a further step toward deciphering the glycosaminoglycan \"sulfation code.\"</p>","PeriodicalId":12766,"journal":{"name":"Glycobiology","volume":" ","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2026-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Glycobiology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/glycob/cwag067","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Glycosaminoglycans, linear periodic anionic polysaccharides composed of repeating disaccharide units, are highly heterogeneous with respect to their chemical composition, sulfation patterns, conformational, dynamic and functional properties. The "sulfation code," which links specific sulfation patterns of these molecules to their biological function, is a key concept for understanding their structure-function relationships. However, both experimental and computational approaches face significant challenges in deciphering this code. In this computational study, we focus on fibroblast growth factor-glycosaminoglycan interactions, which play crucial roles in numerous biologically relevant processes. First, we evaluate the sensitivity and predictive power of currently available computational protocols for studying these systems. We then rigorously investigate the effects of heparin 6-O-desulfation on its interactions with several fibroblast growth factors. We conclude that, depending on the 6-O-sulfation pattern and the length of the oligosaccharide, either predominantly electrostatic interactions or a more complex interplay between electrostatic and hydrophobic interactions determines the specificity of the resulting protein-glycosaminoglycan complex. Finally, we demonstrate that a previously developed coarse-grained model successfully reproduces both the structural and thermodynamic properties of the analysed molecular systems. The results obtained in this study may contribute to the understanding of the fundamental mechanisms underlying protein-glycosaminoglycan interactions and represent a further step toward deciphering the glycosaminoglycan "sulfation code."
糖胺聚糖是由重复双糖单元组成的线性周期性阴离子多糖,在化学组成、硫酸化模式、构象、动力学和功能性质方面具有高度的异质性。“磺化密码”将这些分子的特定磺化模式与其生物功能联系起来,是理解其结构-功能关系的关键概念。然而,实验和计算方法都面临着破译这种密码的重大挑战。在这项计算研究中,我们关注成纤维细胞生长因子-糖胺聚糖的相互作用,这在许多生物学相关过程中起着至关重要的作用。首先,我们评估了目前可用的用于研究这些系统的计算协议的灵敏度和预测能力。然后,我们严格研究了肝素6- o -脱硫对其与几种成纤维细胞生长因子相互作用的影响。我们得出结论,根据6- o -硫酸化模式和低聚糖的长度,主要是静电相互作用或静电和疏水相互作用之间更复杂的相互作用决定了所产生的蛋白质-糖胺聚糖复合物的特异性。最后,我们证明了先前开发的粗粒度模型成功地再现了分析分子系统的结构和热力学性质。本研究获得的结果可能有助于理解蛋白质-糖胺聚糖相互作用的基本机制,并代表着破解糖胺聚糖“磺化密码”的进一步步骤。
期刊介绍:
Established as the leading journal in the field, Glycobiology provides a unique forum dedicated to research into the biological functions of glycans, including glycoproteins, glycolipids, proteoglycans and free oligosaccharides, and on proteins that specifically interact with glycans (including lectins, glycosyltransferases, and glycosidases).
Glycobiology is essential reading for researchers in biomedicine, basic science, and the biotechnology industries. By providing a single forum, the journal aims to improve communication between glycobiologists working in different disciplines and to increase the overall visibility of the field.