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A detailed picture of a protein-carbohydrate hydrogen-bonding network revealed by NMR and MD simulations.

ABSTRACT: Cyanovirin-N (CV-N) is a cyanobacterial lectin with antiviral activity towards HIV and several other viruses. Here, we identify mannoside hydroxyl protons that are hydrogen bonded to the protein backbone of the CV-N domain B binding site, using NMR spectroscopy. For the two carbohydrate ligands Manα(1→2)ManαOMe and Manα(1→2) Manα(1→6)ManαOMe five hydroxyl protons are involved in hydrogen-bonding networks. Comparison with previous crystallographic results revealed that four of these hydroxyl protons donate hydrogen bonds to protein backbone carbonyl oxygens in solution and in the crystal. Hydrogen bonds were not detected between the side chains of Glu41 and Arg76 with sugar hydroxyls, as previously proposed for CV-N binding of mannosides. Molecular dynamics simulations of the CV-N/Manα(1→2)Manα(1→6)ManαOMe complex confirmed the NMR-determined hydrogen-bonding network. Detailed characterization of CV-N/mannoside complexes provides a better understanding of lectin-carbohydrate interactions and opens up to the use of CV-N and similar lectins as antiviral agents.

SUBMITTER: Nestor G

PROVIDER: S-EPMC8091458 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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A detailed picture of a protein-carbohydrate hydrogen-bonding network revealed by NMR and MD simulations.

Nestor Gustav G Ruda Alessandro A Anderson Taigh T Oscarson Stefan S Widmalm Göran G Gronenborn Angela M AM

Glycobiology 20210501 4

Cyanovirin-N (CV-N) is a cyanobacterial lectin with antiviral activity towards HIV and several other viruses. Here, we identify mannoside hydroxyl protons that are hydrogen bonded to the protein backbone of the CV-N domain B binding site, using NMR spectroscopy. For the two carbohydrate ligands Manα(1→2)ManαOMe and Manα(1→2) Manα(1→6)ManαOMe five hydroxyl protons are involved in hydrogen-bonding networks. Comparison with previous crystallographic results revealed that four of these hydroxyl prot ...[more]

PMID: 32902635

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Project description:BACKGROUND:The role of dynamics in protein functions including signal transduction is just starting to be deciphered. Eph receptors with 16 members divided into A- and B- subclasses are respectively activated by 9 A- and B-ephrin ligands. EphA4 is the only receptor capable of binding to all 9 ephrins and small molecules with overlapped interfaces. RESULTS:We first determined the structures of the EphA4 ligand binding domain (LBD) in two crystals of P1 space group. Noticeably, 8 EphA4 molecules were found in one asymmetric unit and consequently from two crystals we obtained 16 structures, which show significant conformational variations over the functionally critical A-C, D-E, G-H and J-K loops. The 16 new structures, together with previous 9 ones, can be categorized into two groups: closed and open forms which resemble the uncomplexed and complexed structures of the EphA4 LBD respectively. To assess whether the conformational diversity over the loops primarily results from the intrinsic dynamics, we initiated 30-ns molecular dynamics (MD) simulations for both closed and open forms. The results indicate that the loops do have much higher intrinsic dynamics, which is further unravelled by NMR H/D exchange experiments. During simulations, the open form has the RMS deviations slightly larger than those of the closed one, suggesting the open form may be less stable in the absence of external contacts. Furthermore, no obvious exchange between two forms is observed within 30 ns, implying that they are dynamically separated. CONCLUSIONS:Our study provides the first experimental and computational result revealing that the intrinsic dynamics are most likely underlying the conformational diversity observed for the EphA4 LBD loops mediating the binding affinity and specificity. Interestingly, the open conformation of the EphA4 LBD is slightly unstable in the absence of it natural ligand ephrins, implying that the conformational transition from the closed to open has to be driven by the high-affinity interaction with ephrins because the weak interaction with small molecule was found to be insufficient to trigger the transition. Our results therefore highlight the key role of protein dynamics in Eph-ephrin signalling and would benefit future design of agonists/antagonists targeting Eph receptors.

Project description:Hydrogen exchange (HX) studies have provided critical insight into our understanding of protein folding, structure, and dynamics. More recently, hydrogen exchange mass spectrometry (HX-MS) has become a widely applicable tool for HX studies. The interpretation of the wealth of data generated by HX-MS experiments as well as other HX methods would greatly benefit from the availability of exchange predictions derived from structures or models for comparison with experiment. Most reported computational HX modeling studies have employed solvent-accessible-surface-area based metrics in attempts to interpret HX data on the basis of structures or models. In this study, a computational HX-MS prediction method based on classification of the amide hydrogen bonding modes mimicking the local unfolding model is demonstrated. Analysis of the NH bonding configurations from molecular dynamics (MD) simulation snapshots is used to determine partitioning over bonded and nonbonded NH states and is directly mapped into a protection factor (PF) using a logistics growth function. Predicted PFs are then used for calculating deuteration values of peptides and compared with experimental data. Hydrogen exchange MS data for fatty acid synthase thioesterase (FAS-TE) collected for a range of pHs and temperatures was used for detailed evaluation of the approach. High correlation between prediction and experiment for observable fragment peptides is observed in the FAS-TE and additional benchmarking systems that included various apo/holo proteins for which literature data were available. In addition, it is shown that HX modeling can improve experimental resolution through decomposition of in-exchange curves into rate classes, which correlate with prediction from MD. Successful rate class decompositions provide further evidence that the presented approach captures the underlying physical processes correctly at the single residue level. This assessment is further strengthened in a comparison of residue resolved protection factor predictions for staphylococcal nuclease with NMR data, which was also used to compare prediction performance with other algorithms described in the literature. The demonstrated transferable and scalable MD based HX prediction approach adds significantly to the available tools for HX-MS data interpretation based on available structures and models.

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A detailed picture of a protein-carbohydrate hydrogen-bonding network revealed by NMR and MD simulations.

Publications

A detailed picture of a protein-carbohydrate hydrogen-bonding network revealed by NMR and MD simulations.

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