Interpreting the structural mechanism of action for MT7 and human muscarinic acetylcholine receptor 1 complex by modeling protein–protein interaction

Targeting the muscarinic M1 receptor with a selective, brain-penetrant antagonist to promote remyelination in multiple sclerosis

Multiple sclerosis (MS) is a chronic and debilitating neurological disease that results in inflammatory demyelination. While endogenous remyelination helps to recover function, this restorative process tends to become less efficient over time. Currently, intense efforts aimed at the mechanisms that promote remyelination are being considered promising therapeutic approaches. The M1 muscarinic acetylcholine receptor (M1R) was previously identified as a negative regulator of oligodendrocyte differentiation and myelination. Here, we validate M1R as a target for remyelination by characterizing expression in human and rodent oligodendroglial cells (including those in human MS tissue) using a highly selective M1R probe. As a breakthrough to conventional methodology, we conjugated a fluorophore to a highly M1R selective peptide (MT7) which targets the M1R in the subnanomolar range. This allows for exceptional detection of M1R protein expression in the human CNS. More importantly, we introduce PIPE-307, a brain-penetrant, small-molecule antagonist with favorable drug-like properties that selectively targets M1R. We evaluate PIPE-307 in a series of in vitro and in vivo studies to characterize potency and selectivity for M1R over M2-5R and confirm the sufficiency of blocking this receptor to promote differentiation and remyelination. Further, PIPE-307 displays significant efficacy in the mouse experimental autoimmune encephalomyelitis model of MS as evaluated by quantifying disability, histology, electron microscopy, and visual evoked potentials. Together, these findings support targeting M1R for remyelination and support further development of PIPE-307 for clinical studies.

Site-directed modification of multifunctional lignocellulose-degrading enzymes of straw based on homologous modeling

Studying the straw lignocellulose strengthening mechanism during simultaneous degradation has important practical significance for improving resource utilization and reducing environmental pollution. In this paper, the degradation ability of four straw lignocellulose-degrading enzymes was evaluated by molecular docking and molecular dynamics. Using the significantly binds to straw lignocellulose-degrading enzyme as a template, a multifunctional lignocellulose-degrading enzyme 3CBH-1KS5-4XQD-1B85 was constructed based on amino acid recombination and homologous modeling. Five efficient degrading enzymes (3CBH-1, 3CBH-2, 3CBH-3, 3CBH-4, and 3CBH-5) were designed by site-directed mutagenesis of 3CBH-1KS5-4XQD-1B85 amino acid at position 346. Molecular dynamics showed that the degradation ability of 3CBH-1 was significant and it was 1.45 times higher than 3CBH-1KS5-4XQD-1B85. Moreover, the mechanism of enhanced degradability and the stability of the enzymes were explored. With the aid of Taguchi experiments, the suitable external environment for degrading straw was determined. In the presence of inhibitors (organic acids and phenolic compounds), the binding energy of 3CBH-1 (238.46 ± 30.96 kJ/mol) is 36.42% higher than that of 3CBH-1KS5-4XQD-1B85 (174.79 ± 20.35 kJ/mol) without external environmental stimulation. Based on homology modeling, this paper constructed a site-directed mutagenesis scheme of multifunctional enzymes, and the aim was to obtain multifunctional and efficient straw lignocellulose-degrading enzymes through protein engineering, which provided a feasible scheme for straw biodegradation.

A Computational Study on the Interaction of NSP10 and NSP14: Unraveling the RNA Synthesis Proofreading Mechanism in SARS-CoV-2, SARS-CoV, and MERS-CoV

The interaction of exoribonuclease (ExoN) nonstructural protein (NSP14) with NSP10 co-factors is crucial for high-fidelity proofreading activity of coronavirus replication and transcription. Proofreading function is critical for maintaining the large genomes to ensure replication proficiency; therefore, while maintaining the viral replication fitness, quick resistance has been reported to the nucleotide analogue (NA) drugs. Therefore, targeting the NSP14 and NSP10 interacting interface with small molecules or peptides could be a better strategy to obstruct replication processes of coronaviruses (CoVs). A comparative study on the binding mechanism of NSP10 with the NSP14 ExoN domain of SARS-CoV-2, SARS-CoV, MERS-CoV, and four SARS-CoV-2 NSP14mutant complexes has been carried out. Protein-protein interaction (PPI) dynamics, per-residue binding free energy (BFE) analyses, and the identification of interface hotspot residues have been studied using molecular dynamics simulations and various computational tools. The BFE of the SARS-CoV NSP14-NSP10 complex was higher when compared to novel SARS-CoV-2 and MERS. However, SARS-CoV-2 NSP14mutant systems display a higher BFE as compared to the wild type (WT) but lower than SARS-CoV and MERS. Despite the high BFE, the SARS-CoV NSP14-NSP10 complex appears to be structurally more flexible in many regions especially the catalytic site, which is not seen in SARS-CoV-2 and its mutant or MERS complexes. The significantly high residue energy contribution of key interface residues and hotspots reveals that the high binding energy between NSP14 and NSP10 may enhance the functional activity of the proofreading complex, as the NSP10-NSP14 interaction is essential in maintaining the stability of the ExoN domain for the replicative fitness of CoVs. The factors discussed for SARS-CoV-2 complexes may be responsible for NSP14 ExoN having a high replication proficiency, significantly leading to the evolution of new variants of SARS-CoV-2. The NSP14 residues V66, T69, D126, and I201and eight residues of NSP10 (L16, F19, V21, V42, M44, H80, K93, and F96) are identified as common hotspots. Overall, the interface area, hotspot locations, bonded/nonbonded contacts, and energies between NSP14 and NSP10 may pave a way in designing potential inhibitors to disrupt NSP14-NSP10 interactions of CoVs especially SARS-CoV-2.

Protein-protein interaction of RdRp with its co-factor NSP8 and NSP7 to decipher the interface hotspot residues for drug targeting: A comparison between SARS-CoV-2 and SARS-CoV

In this study we explored the molecular mechanism of RdRp (Non-Structural Protein, NSP12) interaction with its co-factors NSP7 and NSP8 which is the main toolbox for RNA replication and transcription of SARS-CoV-2 and SARS-CoV. The replication complex is a heterotetramer consists of one NSP12, one NSP7 and two NSP8. Extensive molecular dynamics (MD) simulations were applied on both the heterotetramer complexes to generate the conformations and were used to estimate the MMPBSA binding free energy (BFE) and per-residue energy decomposition of NSP12-NSP8 and NSP12-NSP7 and NSP7-NSP8 complexes. The BFE of SARS-CoV-2 heterotetramer complex with its corresponding partner protein was significantly higher as compared to SARS-CoV. Interface hotspot residues were predicted using different methods implemented in KFC (Knowledge-based FADA and Contracts), HotRegion and Robetta web servers. Per-residue energy decomposition analysis showed that the predicted interface hotspot residues contribute more energy towards the formation of complexes and most of the predicted hotspot residues are clustered together. However, there is a slight difference in the residue-wise energy contribution in the interface NSPs on heterotetramer viral replication complex of both coronaviruses. While the overall replication complex of SARS-CoV-2 was found to be slightly flexible as compared to SARS-CoV. This difference in terms of structural flexibility/stability and energetic characteristics of interface residues including hotspots at PPI interface in the viral replication complexes may be the reason of higher rate of RNA replication of SARS-CoV-2 as compared to SARS-CoV. Overall, the interaction profile at PPI interface such as, interface area, hotspot residues, nature of bonds and energies between NSPs, may provide valuable insights in designing of small molecules or peptide/peptidomimetic ligands which can fit into the PPI interface to disrupt the interaction.

Direct SUMOylation of M1 muscarinic acetylcholine receptor increases its ligand-binding affinity and signal transduction

SUMOylation is a significant post-translational modification (PTM) by the small ubiquitin-related modifier (SUMO). Increasing evidence shows SUMOylation regulates GPCR signaling; however, very few GPCRs have been shown to be SUMOylation targets to date. In this study, we identified M1 muscarinic acetylcholine receptor (M1 mAChR), a member of the GPCRs, as a new SUMO substrate. When the mAChR was activated by the agonist carbachol, the colocalization of the M1 mAChR and SUMO-1 protein markedly decreased in immunoprecipitation and immunofluorescence assays. SUMOylation of the M1 mAChR played an important role in increasing the ligand-binding affinity to M1 mAChR, signaling efficiencies, and receptor endocytosis. Through the site-directed mutagenesis approach, K327 was identified as the SUMOylation site of the M1 mAChR. Mutation of the consensus SUMOylation site of the M1 mAChR reduces not only the colocalization of SUMO-1, but also the ligand-binding affinity and signal transduction. The function of M1 mAChR was regulated by SUMOylation through the stabilization of active-state conformation revealed by molecular dynamics simulations. Our results provide evidence that M1 SUMOylation is an important PTM involved in regulation of the affinity for agonists and for activation of signaling pathways.-Xu, J., Tan, P., Li, H., Cui, Y., Qiu, Y., Wang, H., Zhang, X., Li, J., Zhu, L., Zhou, W., Chen, H. Direct SUMOylation of M1 muscarinic acetylcholine receptor increases its ligand-binding affinity and signal transduction.

Structural determinants for the interactions between muscarinic toxin 7 and muscarinic acetylcholine receptors

Muscarinic acetylcholine receptors (mAChRs) have five subtypes and play crucial roles in various physiological functions and pathophysiological processes. Poor subtype specificity of mAChR modulators has been an obstacle to discover new therapeutic agents. Muscarinic toxin 7 (MT7) is a natural peptide toxin with high selectivity for the M1 receptor. With three to five residues substituted, M3, M4, and M5 receptor mutants could bind to MT7 at nanomolar concentration as the M1 receptor. However, the structural mechanisms explaining MT7-mAChRs binding are still largely unknown. In this study, we constructed 10 complex models of MT7 and each mAChR subtype or its mutant, performed molecular dynamics simulations, and calculated the binding energies to investigate the mechanisms. Our results suggested that the structural determinants for the interactions on mAChRs were composed of some critical residues located separately in the extracellular loops of mAChRs, such as Glu4.56, Leu4.60, Glu/Gln4.63, Tyr4.65, Glu/Asp6.67, and Trp7.35. The subtype specificity of MT7 was attributed to the non-conserved residues at positions 4.56 and 6.67. These structural mechanisms could facilitate the discovery of novel mAChR modulators with high subtype specificity and enhance the understanding of the interactions between ligands and G-protein-coupled receptors.

Homology modeling of human muscarinic acetylcholine receptors

We have developed homology models of the acetylcholine muscarinic receptors M₁R-M₅R, based on the β₂-adrenergic receptor crystal as the template. This is the first report of homology modeling of all five subtypes of acetylcholine muscarinic receptors with binding sites optimized for ligand binding. The models were evaluated for their ability to discriminate between muscarinic antagonists and decoy compounds using virtual screening using enrichment factors, area under the ROC curve (AUC), and an early enrichment measure, LogAUC. The models produce rational binding modes of docked ligands as well as good enrichment capacity when tested against property-matched decoy libraries, which demonstrates their unbiased predictive ability. To test the relative effects of homology model template selection and the binding site optimization procedure, we generated and evaluated a naïve M₂R model, using the M₃R crystal structure as a template. Our results confirm previous findings that binding site optimization using ligand(s) active at a particular receptor, i.e. including functional knowledge into the model building process, has a more pronounced effect on model quality than target-template sequence similarity. The optimized M₁R-M₅R homology models are made available as part of the Supporting Information to allow researchers to use these structures, compare them to their own results, and thus advance the development of better modeling approaches.