Sree, H. | bioRxiv Science

bioRxiv2024

Benzamidine-Mediated Inhibition of Human Lysozyme Aggregation: Differential Ligand Binding in Homologous Proteins

Amyloid fibril formation is a hallmark of several protein misfolding diseases, including systemic hereditary amyloidosis (SHA), in which lysozyme aggregates into plaques, causing inflammation in various tissues. SHA is a rare disease with no current drug treatment options. In our efforts to identify potential therapeutics for SHA, we investigated the inhibitory effects of benzamidine (BEN) on the fibrillation of human lysozyme (HL). Multiple biophysical assays demonstrated BENs ability to effectively prevent amyloid formation. Intrinsic fluorescence measurements highlighted BENs interaction with HL. We inferred the binding mode of BEN to HL through ITC experiments, molecular docking, and molecular dynamics simulations, confirmed BENs binding at the active site, particularly near stretch-2 (residues 52-64), a key region in its anti-amyloidogenic activity. This interaction differed from the previously reported interaction with HEWL. Further, microscopy analyses, including scanning electron microscopy (SEM) and transmission electron microscopy (TEM), further supported these findings by showing reduced fibril formation and alterations in fibril morphology in the presence of BEN. Importantly, BEN exhibited no cytotoxic effects in HEK-293 cells, reinforcing its potential as a therapeutic candidate for amyloidosis. These results provide strong evidence of BENs anti-amyloidogenic activity and offer a foundation for future drug development targeting lysozyme amyloidosis.

bioinformatics↗

bioRxiv2024

Improving the accuracy of pose prediction by incorporating symmetry-related molecules

Accurate prediction of biologically relevant binding poses is crucial for the success of computer-aided drug development. In this study, we describe a general strategy to enhance the precision of pose prediction in molecular docking by incorporating symmetry-related molecules (SRMs). Our objective was to demonstrate the significant impact of SRMs on the accuracy of pose prediction. To achieve this, we evaluated our method on high-quality protein-ligand complex structures, focusing on the presence and absence of SRMs during molecular docking studies. We have extracted the co-crystal ligands from the selected crystal structure and were redocked in presence and absence of SRM to assess their influence. Additionally, we calculated the free energy of the docked poses using the Molecular Mechanics Generalized Born Surface Area (MM-GBSA) method, comparing the results in the presence and absence of SRMs. The findings revealed that redocking performed in the presence of SRMs significantly improved the prediction of biologically significant/crystallographically relevant poses. Consequently, our proposed strategy offers a robust method for enhancing pose prediction in current molecular docking programs, potentially leading to more effective and reliable drug development processes.

bioinformatics↗