Perspective on computational simulations of glycosaminoglycans.

ABSTRACT: Glycosaminoglycans (GAGs) represent a formidable frontier for chemists, biochemists, biologists, medicinal chemists and drug delivery specialists because of massive structural complexity. GAGs are arguably the most complex, natural linear biopolymers with theoretical diversity orders of magnitude higher than proteins and nucleic acids. Yet, this diversity remains generally untapped. Computational approaches offer major routes to understand GAG structure and dynamics so as to enable novel applications of these biopolymers. In fact, computational algorithms, softwares, online tools and techniques have reached a level of sophistication that help understand atomistic details of conformational variation and protein recognition of individual GAG sequences. This review describes current approache

SUBMITTER: Nagarajan B 

PROVIDER: S-EPMC6504973 | biostudies-literature | 2019 Mar-Apr

REPOSITORIES: biostudies-literature