Assessing Genetic Algorithm-Based Docking Protocols for Prediction of Heparin Oligosaccharide Binding Geometries onto Proteins.

Although molecular docking has evolved dramatically over the years, its application to glycosaminoglycans (GAGs) has remained challenging because of their intrinsic flexibility, highly anionic character and rather ill-defined site of binding on proteins. GAGs have been treated as either fully "rigid" or fully "flexible" in molecular docking. We reasoned that an intermediate semi-rigid docking (SRD) protocol may be better for the recapitulation of native heparin/heparan sulfate (Hp/HS) topologies. Herein, we study 18 Hp/HS-protein co-complexes containing chains from disaccharide to decasaccharide using genetic algorithm-based docking with rigid, semi-rigid, and flexible docking protocols. Our work reveals that rigid and semi-rigid protocols recapitulate native poses for longer chains (5→10 mers) significantly better than the flexible protocol, while 2→4-mer poses are better predicted using the semi-rigid approach. More importantly, the semi-rigid docking protocol is likely to perform better when no crystal structure information is available. We also present a new parameter for parsing selective versus non-selective GAG-protein systems, which relies on two computational parameters including consistency of binding (i.e., RMSD) and docking score (i.e., GOLD Score). The new semi-rigid protocol in combination with the new computational parameter is expected to be particularly useful in high-throughput screening of GAG sequences for identifying promising druggable targets as well as drug-like Hp/HS sequences.

3-O-Sulfation induces sequence-specific compact topologies in heparan sulfate that encode a dynamic sulfation code.

Heparan sulfate (HS) is arguably the most diverse linear biopolymer that is known to modulate hundreds of proteins. Whereas the configurational and conformational diversity of HS is well established in terms of varying sulfation patterns and iduronic acid (IdoA) puckers, a linear helical topology resembling a cylindrical rod is the only topology thought to be occupied by the biopolymer. We reasoned that 3-O-sulfation, a rare modification in natural HS, may induce novel topologies that contribute to selective recognition of proteins. In this work, we studied a library of 24 distinct HS hexasaccharides using molecular dynamics (MD). We discovered novel compact (C) topologies that are populated significantly by a unique group of 3-O-sulfated sequences containing IdoA residues. 3-O-sulfated sequences containing glucuronic acid (GlcA) residue and sequences devoid of 3-O-sulfate groups did not exhibit high levels of the C topology and primarily exhibited only the canonical linear (L) form. The C topology arises under dynamical conditions due to rotation around an IdoA â†’ GlcN glycosidic linkage, especially in psi (Ψ) torsion. At an atomistic level, the L â†’ C transformation is a multi-factorial phenomenon engineered to reduce like-charge repulsion, release one or more HS-bound water molecules, and organize a bi-dentate "IdoA-cation-IdoA" interaction. These forces also drive an L â†’ C transformation in a 3-O-sulfated octasaccharide, which has shown evidence of the unique C topology in the co-crystallized state. The 3-O-sulfate-based generation of unique, sequence-specific, compact topologies indicate that natural HS encodes a dynamic sulfation code that could be exploited for selective recognition of target proteins.

Molecular dynamics simulations to understand glycosaminoglycan interactions in the free- and protein-bound states.

Natural glycosaminoglycans (GAGs) are informational molecules with astounding structural diversity. Understanding the behavior of GAGs in the free and protein-bound states is critical for harnessing this diversity. Molecular dynamics (MD) offers atomistic insight into principles governing GAG recognition by proteins. Here, we discuss how MD can be used to understand local and global properties of GAGs in free solution, including torsions, puckering, hydrogen bonding, flexibility, and energetics. We discuss MD studies on GAG-protein complexes, which help elucidate the strength of interacting residues, role of water, energetics, and so on. The MD results accumulated so far suggest that GAG recognition of proteins is a continuum from the highly selective on one end to the fully non-selective on the other with intermediate levels of selectivity, including moderately selective and plastic. The advancements in MD technology, such as coarse-grained MD, coupled with really long simulations will help understand macroscale molecular movements in the future.