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Alzheimer’s disease (AD) is a multifactorial and fatal neurodegenerative disorder. Memory loss and cognitive decline occur due to death of brain cells. Various important hallmarks of AD have reported like deposition of β-amyloid fibril, β-amyloid oligomers formation, hyperactive phosphorylated tau protein, oxidative stress in cell, low levels of acetylcholine, etc. Treatment of AD based on cholinesterase inhibitors is only symptomatic, its efficacy is limited. A multi-targeted ligand may enable therapeutic efficacy, because of being multifactorial nature of AD. Hence, this research has been focused on developing novel components that preferentially block cholinesterase and simultaneously bind with other targets like β-secretase, Monoamine oxidases, Glycogen synthase kinase, etc., which are directly or indirectly associated with AD to offer more efficient treatment than earlier. To select novel targets and therapeutic ligands, computational approaches have proved to be robust and reliable tools. To expose intermolecular binding mode of the compounds, molecular docking studies and molecular dynamics simulation studies performed and the results indicate their substantial interactions with the active sites of AChE and BCHE and other responsible targets. In silico ADME/T, study performed to estimate several pharmacokinetic parameters and toxicity profile of the selected compounds. Amongst the series, compounds 2-(2,2-dimethylchromen-6-yl)-5,7- dihydroxychromen-4-one (PCID5315395) and 7-(1,3-benzodioxol-5-yl)-5-hydroxy-2,2-dimethylpyrano [3,2-g] chromen-6-one (PCID5983661) are the most encouraging multi-targeted candidates which have the ability to increase memory, acetylcholine as well as other neurotransmitter levels and give the protection of the neurons against the cognitive deficit. In this study, we are proposing two new compounds from PubChem database as AChE as well as BCHE, MAO-A, MAO-B, Beta-secretase, GSK-3 and N-Methyl-D-aspartate (NMDA) inhibitors for further investigation and experimental validation.

Inhibition of BCR–ABL tyrosine kinase plays a crucial role in the management of chronic myelogenous leukemia (CML). The suppression of CML is getting harder because of a distinct pattern of resistance. Developing new types of ABL tyrosine kinase inhibitors along with ABL2, CSF1R, KIT, LCK, PDGFRA, and PDGFRB inhibitors is the main objective of this study that may overcome the drug resistance issue. The current study has been conducted using a kinase database containing 177,000 bioactive molecules, the top 135 molecules were selected with the best docking score and subjected to comprehensive ADMET profiling, multi-target analysis. Based on consensus molecular docking score (AutoDock, Chimera, Achilles, and Mcule), 22 molecules have been screened out which later undertaken for ADME/T profiling. After profiling of ADME/T data, selected molecules subjected to docking with multiple targets. Finally, molecular dynamics simulations had performed to screen the binding accuracy of the four lead molecules with ABL1. MD simulations of the desired complex (ABL1, ABL2, CSF1R, KIT, LCK, PDGFRA, and PDGFRB, among them ABL1 was the prime target) performed and found that PCID 10181160 and PCID 72724706 are the most promising inhibitors comparing to imatinib. These lead molecules are the potential CML inhibitors that could resolve the resistance pattern. Further chemical synthesis, wet lab analysis, and experimental validation deserve the utmost attention.