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The entry of SARS-CoV-2 into the host cell is mediated by its S-glycoprotein (SGP). Sulfated glycans bind to the SGP receptor-binding domain (RBD), which forms a ternary complex with its receptor angiotensin converting enzyme 2. Here, we have conducted a thorough and systematic computational study of the binding of four oligosaccharide building blocks from novel marine sulfated glycans (isolated from Pentacta pygmaea and Isostichopus badionotus) to the non-glycosylated and glycosylated RBD. Blind docking studies using three docking programs identified five potential cryptic binding sites. Extensive site-targeted docking and molecular dynamics simulations using two force fields confirmed only two binding sites (Sites 1 and 5) for these novel, highly charged sulfated glycans, which were also confirmed by previously published reports. This work showed the structural features and key interactions driving ligand binding. A previous study predicted Site 2 to be a potential binding site, which was not observed here. The use of several molecular modeling approaches gave a comprehensive assessment. The detailed comparative study utilizing multiple modeling approaches is the first of its kind for novel glycan–SGP interaction characterization. This study provided insights into the key structural features of these novel glycans as they are considered for development as potential therapeutics. [ABSTRACT FROM AUTHOR]

Many proteins have small-molecule binding pockets that are not easily detectable in the ligand-free structures. These cryptic sites require a conformational change to become apparent; a cryptic site can therefore be defined as a site that forms a pocket in a holo structure, but not in the apo structure. Because many proteins appear to lack druggable pockets, understanding and accurately identifying cryptic sites could expand the set of drug targets. Previously, cryptic sites were identified experimentally by fragment-based ligand discovery and computationally by long molecular dynamics simulations and fragment docking. Here, we begin by constructing a set of structurally defined apo-holo pairs with cryptic sites. Next, we comprehensively characterize the cryptic sites in terms of their sequence, structure, and dynamics attributes. We find that cryptic sites tend to be as conserved in evolution as traditional binding pockets but are less hydrophobic and more flexible. Relying on this characterization, we use machine learning to predict cryptic sites with relatively high accuracy (for our benchmark, the true positive and false positive rates are 73% and 29%, respectively). We then predict cryptic sites in the entire structurally characterized human proteome (11,201 structures, covering 23% of all residues in the proteome). CryptoSite increases the size of the potentially "druggable" human proteome from ~40% to ~78% of disease-associated proteins. Finally, to demonstrate the utility of our approach in practice, we experimentally validate a cryptic site in protein tyrosine phosphatase 1B using a covalent ligand and NMR spectroscopy. The CryptoSite Web server is available at http://salilab.org/cryptosite.

An increasing number of structural studies reveal alternative binding sites in protein receptors that become apparent only when an inhibitor binds, and correct prediction of these situations presents a significant challenge to computer-aided drug design efforts. A striking example is provided by recent crystal structures of the p38 MAP kinase, where a 10Å movement of the Phe169 side-chain creates a new binding site adjacent to the ATP binding site that is exploited by the diaryl urea inhibitor BIRB796. Here, we show that this binding site can be successfully and repeatedly identified in explicit-solvent molecular dynamics (MD) simulations of the protein that begin from an unliganded p38 crystal structure. Ligand-docking calculations performed on 5000 different structural snapshots generated during MD indicate that the conformations sampled are often surprisingly competent to bind the inhibitor BIRB796 in the crystallographically correct position and with docked energies that are generally more favorable than those of other positions. Similar docking studies with an ATP-binding site-directed inhibitor suggest that it may be possible to develop hybrid inhibitors that target both the ATP and cryptic binding sites simultaneously. Intriguingly, both inhibitors are occasionally found to dock correctly even with p38''s “DFG” motif in the “wrong” conformation and BIRB796 can successfully dock, albeit infrequently, without significant displacement of the Phe169 side-chain; this suggests that the inhibitor might facilitate the latter''s conformational change. Finally, two quite different conformations of p38''s DFG motif are also sampled for extended periods of time during the simulations; these may provide new opportunities for inhibitor development. The MD simulations reported here, which total 390ns in length, therefore demonstrate that existing computational methods may be of surprising utility in predicting cryptic binding sites in protein receptors prior to their experimental discovery. [Copyright &y& Elsevier]