Fragmental modeling of hPepT2 and analysis of its binding features by docking studies and pharmacophore mapping

2011 ◽  
Vol 19 (15) ◽  
pp. 4544-4551 ◽  
Author(s):  
Alessandro Pedretti ◽  
Laura De Luca ◽  
Cristina Marconi ◽  
Luca Regazzoni ◽  
Giancarlo Aldini ◽  
...  
Keyword(s):  
Docking Studies ◽  
Pharmacophore Mapping

Identification of High-affinity Small Molecules Targeting Gamma Secretase for the Treatment of Alzheimer’s Disease

2019 ◽  
Vol 19 (13) ◽  
pp. 1173-1187 ◽  
Author(s):  
Meer Asif Ali ◽  
Sugunakar Vuree ◽  
Himshikha Goud ◽  
Tajamul Hussain ◽  
Anuraj Nayarisseri ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Amyloid Plaques ◽  
Docking Studies ◽  
Screening Methods ◽  
Docking Site ◽  
Gamma Secretase ◽  
Pharmacophore Mapping ◽  
High Affinity ◽  
Main Component

Background: Alzheimers Disease (AD) is a neurodegenerative disease which is characterized by the deposition of amyloid plaques in the brain- a concept supported by most of the researchers worldwide. The main component of the plaques being amyloid-beta (Aβ42) results from the sequential cleavage of Amyloid precursor protein (APP) by beta and gamma secretase. This present study intends to inhibit the formation of amyloid plaques by blocking the action of gamma secretase protein with Inhibitors (GSI). Methods: A number of Gamma Secretase Inhibitors (GSI) were targeted to the protein by molecular docking. The inhibitor having the best affinity was used as a subject for further virtual screening methods to obtain similar compounds. The generated compounds were docked again at the same docking site on the protein to find a compound with higher affinity to inhibit the protein. The highlights of virtually screened compound consisted of Pharmacophore Mapping of the docking site. These steps were followed by comparative assessments for both the compounds, obtained from the two aforesaid docking studies, which included interaction energy descriptors, ADMET profiling and PreADMET evaluations. Results: 111 GSI classified as azepines, sulfonamides and peptide isosteres were used in the study. By molecular docking an amorpholino-amide, compound (22), was identified to be the high affinity compound GSI along with its better interaction profiles.The virtually screened pubchem compound AKOS001083915 (CID:24462213) shows the best affinity with gamma secretase. Collective Pharmacophore mapping (H bonds, electrostatic profile, binding pattern and solvent accesibility) shows a stable interaction. The resulting ADMETand Descriptor values were nearly equivalent. Conclusion: These compounds identified herein hold a potential as Gamma Secretase inhibitors.According to PreADMET values the compound AKOS001083915 is effective and specific to the target protein. Its BOILED-egg plot analysis infers the compound permeable to blood brain barrier.Comparative study for both the compounds resulted in having nearly equivalent properties. These compounds have the capacity to inhibit the protein which is indirectly responsible for the formation of amyloid plaques and can be further put to in vitro pharmacokinetic and dynamic studies.

Homology Modeling of Mus Musculus CDK5 and Molecular Docking Studies with Flavonoids

2017 ◽  
Vol 9 (6) ◽  
Author(s):  
Sowmya Suri ◽  
Rumana Waseem ◽  
Seshagiri Bandi ◽  
Sania Shaik
Keyword(s):  
Molecular Docking ◽  
3D Model ◽  
Structural Features ◽  
Docking Studies ◽  
Amino Acid Residues ◽  
Cyclin Dependent Kinase ◽  
Ligand Complex ◽  
Ligand Interaction ◽  
Molecular Docking Studies ◽  
Cyclin Dependent Kinase 5

A 3D model of Cyclin-dependent kinase 5 (CDK5) (Accession Number: Q543f6) is generated based on crystal structure of P. falciparum PFPK5-indirubin-5-sulphonate ligand complex (PDB ID: 1V0O) at 2.30 Å resolution was used as template. Protein-ligand interaction studies were performed with flavonoids to explore structural features and binding mechanism of flavonoids as CDK5 (Cyclin-dependent kinase 5) inhibitors. The modelled structure was selected on the basis of least modeler objective function. The model was validated by PROCHECK. The predicted 3D model is reliable with 93.0% of amino acid residues in core region of the Ramachandran plot. Molecular docking studies with flavonoids viz., Diosmetin, Eriodictyol, Fortuneletin, Apigenin, Ayanin, Baicalein, Chrysoeriol and Chrysosplenol-D with modelled protein indicate that Diosmetin is the best inhibitor containing docking score of -8.23 kcal/mol. Cys83, Lys89, Asp84. The compound Diosmetin shows interactions with Cys83, Lys89, and Asp84.

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