Understanding Specificity of Glycosaminoglycan Interactions with Proteins

Glycosaminoglycans (GAGs) play key roles in virtually all biologic responses through their interaction with proteins. Generally, GAGs are believed to interact non‐specifically with proteins. The primary reason for this belief is the highly electrostatic nature of their interactions and the fact that only one homogeneous GAG sequence has reached the clinic – the anticoagulant heparin pentasaccharide sequence. Are highly specific GAG–protein interactions so rare? Does nature rely primarily on non‐specificity to mediate the biological roles of GAGs? These questions are of major significance and insights into specificity of GAG–protein interactions may lead to many more GAG sequences reaching the clinic. Yet, a major challenge in understanding these interactions is the massive structural complexity of GAGs. Computational approaches are extremely useful in navigating this challenge and, in some cases, the only avenue to gain comprehensive insight. Computationally, most basic and many advanced questions on GAG–protein interactions can be answered including 1) does my protein bind to GAGs?, 2) where does the GAG bind?, 3) does the protein preferentially recognize a particular GAG type?, 4) what is the most optimal GAG chain length?, 5) what is the structure of the most favored GAG sequence?, 6) is the GAG–protein system ‘specific’, ‘non‐specific’, or a combination of both?, etc. Recent advances in the areas of thrombosis and cancer from our laboratories have led to discoveries of GAG sequences that are highly specific for their protein targets. The results raise the promise that many proteins may recognize GAGs with high specificity and clinically relevant GAG sequences are waiting to be identified. Support or Funding Information P01 HL107152R01 HL090586R25 HL128639 This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .