Computational Identification and Evaluation of PDK-1 Inhibitors as Potential Anticancer Drug

Abstract

Computational drug design approach has a great potential in accelerating the drug discovery process. PDK-1 is a well validated anti-cancer target and developing inhibitors for PDK-1 has the potential to be developed as the anti-cancer therapeutics. In this presented thesis I have showed the potential of computational approaches for screening of wide class of inhibitors using PDK-1 as our target. A data set of 83 compounds of selective PDK-1 inhibitors with their respective activities ranging over a wide range of magnitude has been used to generate pharmacophore hypothesis to predict the activity successfully and accurately. A highly predictive pharmacophore model was generated based on 21 training set molecules, which had hydrogenbond acceptor, hydrogen bond donor and hydrophobic aliphatic groups as chemical features which described their activities towards PDK -1 kinase. The validation of the model is based on 62 test set molecules, which finally showed that the model was able to accurately differentiate various classes of PDK-1 inhibitors with a high correlation coefficient of 0.87 between experimental and predicted activity. Further validation of Hypo1 was done by decoy set method. The Decoy set method shows the GH score of 0.73 which reflect that designed model have very high efficiency in screening the molecules from database. Hierarchical virtual screening 2 method is used to identify new potential hits against PDK-1. I have used the ligand-based screening, rigid docking, flexible docking lipinski as well ADMET as screening filters during virtual screening protocol. Hypo1 was used as a 3D query to screen the potential molecules from the NCI database as well Maybridge database. The hit compounds were filtered subsequently by Lipinski’s rule of five and ADMET filtration. Further molecules were refined by docking study. After docking studies finally 3 potential molecules (NSC_218342, NSC_24871, NSC_211930) which having different scaffold shows better docking energy as well as shows better interaction were identified as new probable molecular inhibitors against PDK-1 kinase. By using this strategy we have identified three promising new hit for the development of a novel anticancer therapeutic in future. The inhibitor identified in this study serves as a good starting compounds for designing and synthesis of new class of inhibitors as PDK-1 inhibitors. In structure-based lead drug designing approach involved a comparative evaluation of various natural flavonoids as potential anticancer compounds wherein the effectiveness has been studied with reference to PDK-1 Kinase inhibition. The molecular docking results are showing the effectiveness of three natural flavonoids among all the compounds were taken for the study. Finally best hit i.e Myricetin was subjected to molecular dynamic simulation study, evaluating the binding stability of complex during entire simulation run (10ns). Molecular dynamic 3 simulation study revealed that myricetin and PDK-1 complex was stable during entire simulation. These studies depict that myricetin can acts as potential PDK-1 inhibitor. But due to low oral bioavailability, clinical use of Myricetin is limited, an attempt was made towards structure based screening of new potential analogues deposited in PubChem database. Further Insilico ADME/ Toxicity and molecular docking studies was carried out to check the pharmacokinetics properties of as well as binding interactions of screened molecules. The binding energies of the protein-ligand interactions also confirmed that the ligands were fit into the active pockets of receptor tightly. Insilico ADMET study concluded that all the analogues were have better pharmacokinetics profiles compared to myricetin. These may hold better potential as drug candidates that inhibit the PDK-1 kinase. Further development and modification of these analogues may lead to generation of novel high potent anticancer drug in future.