Identifying RAGE inhibitors as potential therapeutics for Alzheimer’s disease via integrated in-silico approaches

Abstract

Alzheimer’s disease is a neurodegenerative disorder characterized by two hallmarks: amyloid beta plaques and neurofibrillary tangles. The receptor for advanced glycation end products (RAGE) is a multi-ligand receptor involved in the pathophysiology of various diseases including cancer, diabetes, cardiovascular diseases, and Alzheimer’s disease (AD). Therefore, targeting RAGE could be an effective strategy to block RAGE signaling pathways. The present study aims to identify potential RAGE inhibitors against AD through comprehensive in-silico approaches. A total of 708,580 compounds were screened from numerous databases using structure-based virtual screening and ADMET evaluation. Further, the molecules with good glide scores were assessed by molecular docking studies. Subsequently, the top six ligands were subjected to molecular dynamic (MD) simulations for 100 ns and binding free energy calculations to check their stability with RAGE (PDB: 6XQ3). The per-residue decomposition analysis revealed that specific residues namely, GLY_20, ALA_21, LYS_39, GLU_50, LYS_52, ARG_98, GLN_100, LYS_110, ASN_112, and ARG_198 played a key role in the binding process. Furthermore, the trajectory analysis (DCCM and PCA) analyzed the dominant motions of residues and predicted the stability of protein-ligand complexes. In conclusion, the Hit-6 compound could be a promising candidate for targeting RAGE and deserves further consideration as an anti-Alzheimer drug.Alzheimer’s disease is a neurodegenerative disorder characterized by two hallmarks: amyloid beta plaques and neurofibrillary tangles. The receptor for advanced glycation end products (RAGE) is a multi-ligand receptor involved in the pathophysiology of various diseases including cancer, diabetes, cardiovascular diseases, and Alzheimer’s disease (AD). Therefore, targeting RAGE could be an effective strategy to block RAGE signaling pathways. The present study aims to identify potential RAGE inhibitors against AD through comprehensive in-silico approaches. A total of 708,580 compounds were screened from numerous databases using structure-based virtual screening and ADMET evaluation. Further, the molecules with good glide scores were assessed by molecular docking studies. Subsequently, the top six ligands were subjected to molecular dynamic (MD) simulations for 100 ns and binding free energy calculations to check their stability with RAGE (PDB: 6XQ3). The per-residue decomposition analysis revealed that specific residues namely, GLY_20, ALA_21, LYS_39, GLU_50, LYS_52, ARG_98, GLN_100, LYS_110, ASN_112, and ARG_198 played a key role in the binding process. Furthermore, the trajectory analysis (DCCM and PCA) analyzed the dominant motions of residues and predicted the stability of protein-ligand complexes. In conclusion, the Hit-6 compound could be a promising candidate for targeting RAGE and deserves further consideration as an anti-Alzheimer drug.