Sunil Kumar Tripathi

Extra precision docking, free energy calculation and molecular dynamics simulation studies of CDK2 inhibitors.

Molecular docking, free energy calculation and molecular dynamics (MD) simulation studies have been performed, to explore the putative binding modes of 3,5-diaminoindazoles, imidazo(1,2-b)pyridazines and triazolo(1,5-a) pyridazines series of Cyclin-dependent kinase (CDK2) inhibitors. To evaluate the effectiveness of docking protocol in flexible docking, we have selected crystallographic bound compound to validate our docking procedure as evident from root mean square deviations (RMSDs). We found different binding sites namely catalytic, inhibitory phosphorylation, cyclin binding and CKS-binding site of the CDK2 contributing towards the binding of these compounds. Moreover, correlation between free energy of binding and biological activity yielded a statistically significant correlation coefficient. Finally, three representative protein-ligand complexes were subjected to molecular dynamics simulation to determine the stability of the predicted conformations. The low value of the RMSDs between the initial complex structure and the energy minimized final average complex structure suggests that the derived docked complexes are close to equilibrium. We suggest that the phenylacetyl type of substituents and cyclohexyl moiety make the favorable interactions with a number of residues in the active site, and show better inhibitory activity to improve the pharmacokinetic profile of compounds against CDK2. The structure-based drug design strategy described in this study will be highly useful for the development of new inhibitors with high potency and selectivity.

In silico screening of indinavir-based compounds targeting proteolytic activity in HIV PR: binding pocket fit approach

The intense research on small molecule inhibitors of Human immunodeficiency virus (HIV)-protease (PR) has produced a diverse class of chemical scaffolds which includes clinically available HIV PR inhibitors (PRI). Till now, these inhibitors are insignificant for targeting proteolytic activity and few drug molecules on alterations can enhance the inhibition of PR enzyme. Here, we developed a method for screening of new hits from Cambridge structural database, based on binding mode of indinavir interaction participating atoms. Knowledge-based ligand screening technique approximately informs that new hits are also having same binding mode-like indinavir interaction patterns. Considering the importance of ligand fitting in binding pocket, we developed induced-fit models for each compound and we obtained accurate energy values in terms of binding and interaction energy. We found that newly search molecules are interacting better than known drug—indinavir and these new compounds are comparatively having better drug-like property. Finally, we demonstrated that pocket specific docking, energy utilization, interactions, and ADME for screened compounds are showing new hit compounds of indinavir are better HIV PRI and these new compounds can also show better activity in in vivo and in vitro conditions.

Exploring the selectivity of a ligand complex with CDK2/CDK1: a molecular dynamics simulation approach

Cyclin‐dependent kinases (CDKs) are core components of the cell cycle machinery that govern the transition between phases during cell cycle progression. Abnormalities in CDKs activity and regulation are common features of cancer, making CDK family members attractive targets for the development of anticancer drugs. Their inhibitors have entered in clinical trials to treat cancer. Very recently, Heathcote et al. (J. Med. Chem. 2010, 53:8508–8522) have found a ligand BS194 that has a high affinity with CDK2 (IC50 = 3 nm) but shows low affinity with CDK1 (IC50 = 30 nm). To understand the selectivity, we used homology modeling, molecular docking, molecular dynamics, and free‐energy calculation to analyze the interactions. A rational three‐dimensional model of the CDK1/BS194 complex is built. We found that Leu83 is a key residue that recognizes BS194 more effectively with CDK2 with good binding free energies rather than CDK1. Energetic analysis reveals that van der Waals interaction and non‐polar contributions to solvent are favorable in the formation of complexes and amine group of the ligand, which plays a crucial role for binding selectivity between CDK2 and CDK1. Copyright

Pharmacophore modelling and atom-based 3D-QSAR studies on N-methyl pyrimidones as HIV-1 integrase inhibitors.

Pharmacophore modelling and atom-based 3D-QSAR studies were carried out for a series of compounds belonging to N-methyl pyrimidones as HIV-1 integrase inhibitors. Based on the ligand-based pharmacophore model, we got 5-point pharmacophore model AADDR, with two hydrogen bond acceptors (A), two hydrogen bond donors (D) and one aromatic ring (R). The generated pharmacophore-based alignment was used to derive a predictive atom-based 3D-QSAR model for the training set (r2 = 0.92, SD = 0.16, F = 84.8, N = 40) and for test set (Q2 = 0.71, RMSE = 0.06, Pearson R = 0.90, N = 10). From these results, AADDR pharmacophore feature was selected as best common pharmacophore hypothesis, and atom-based 3D-QSAR results also support the outcome by means of favourable and unfavourable regions of hydrophobic and electron-withdrawing groups for the most potent compound 30. These results can be useful for further design of new and potent HIV-1 IN inhibitors.

Molecular docking, QPLD, and ADME prediction studies on HIV-1 integrase leads

HIV-1 integrase (IN) is an important drug target over the years with diverse therapeutic potential with the objective of designing new chemical entities with enhanced inhibitory potencies against HIV-1 IN. We performed molecular docking, quantum polarized ligand docking (QPLD), ADME screening, and PASS biological activity prediction studies on Raltegravir, Elvitegravir, and newly searched compounds of Cambridge crystallographic database. Best docking and QPLD scores of known and unknown searched compounds were compared using docking score, docking energy, and emodel energy. Moreover, correlation between docking score, docking energy with emodel energy yielded a statistically significant correlation coefficient. The searched compounds were also evaluated with ADME properties and biological activity prediction analysis. These compounds also show good pharmacokinetic properties under the acceptable range including antiviral biological activity prediction. Hence, these compounds could be employed to design ligands with enhanced inhibitory potencies and to predict the potencies of analogs to guide synthesis/or prepare synthetic analogs for second generation drug development against HIV-1 IN.

Identification of potential HIV-1 integrase strand transfer inhibitors: In silico virtual screening and QM/MM docking studies

HIV-1 integrase (IN) is a retroviral enzyme that catalyses integration of the reverse-transcribed viral DNA into the host genome, which is necessary for efficient viral replication. In this study, we have performed an in silico virtual screening for the identification of potential HIV-1 IN strand transfer (ST) inhibitors. Pharmacophore modelling and atom-based 3D-QSAR studies were carried out for a series of compounds belonging to 3-Hydroxypyrimidine-2,4-diones. Based on the ligand-based pharmacophore model, we obtained a five-point pharmacophore with two hydrogen bond acceptors (A), one hydrogen bond donor (D), one hydrophobic group (H) and one aromatic ring (R) as pharmacophoric features. The pharmacophore hypothesis AADHR was used as a 3D query in a sequential virtual screening study to filter small molecule databases Maybridge, ChemBridge and Asinex. Hits matching with pharmacophore hypothesis AADHR were retrieved and passed progressively through Lipinski’s rule of five filtering, molecular docking and hierarchical clustering. The five compounds with best hits with novel and diverse chemotypes were subjected to QM/MM docking, which showed improved docking accuracy. We further performed molecular dynamics simulation and found three compounds that form stable interactions with key residues. These compounds could be used as a leads for further drug development and rational design of HIV-1 IN inhibitors.

Cyclin Dependent Kinase as Significant Target for Cancer Treatment

Abstract: Cyclin Dependent Kinase (CDKs) regulates cell cycle commitment and DNA synthesis. Cell division in mam-malian cells is driven by protein kinase that regulates progression through the various phases of cell cycle. The activity of cyclins and their associated CDKs are frequently deranged in human cancers. For this reason, Cyclin-CDK complexes have been considered as very promising therapeutic targets in human malignancies. An obvious concern whether, block-ing cyclin-CDK function would preferentially affects cancer cells but not normal and non-transformed cells. The cell cy-cle represents a series of tightly integrated events that allow the cell to grow and proliferate. Critical part of the cell cycle machinery is the CDK, which, when activated, provide a means for the cell to move from one phase of the cell cycle to next. The cell cycle also serves to protect the cell from DNA damage. Thus, cell cycle arrest represents a survival mecha-nism that provides tumour cell, to repair its own damaged DNA Thus, abrogation of cell cycle checkpoints, before DNA repair is complete can activate the apoptotic cascade leading to cell death. Misregulation of CDK is one of the most fre-quent alterations in human cancer. CDK are critical regulators of cell cycle progression and RNA transcription. A series of targeted agents that directly inhibit the CDKs, inhibit unrestricted cell growth, and induce growth arrest. Recent atten-tion has also focused on these drugs as inhibitors of transcription. In this review we are summarizing that why CDK is important target for cancer chemotherapy and why finding out the best and potent kinase inhibitor is essential.

Shape and pharmacophore-based virtual screening to identify potential cytochrome P450 sterol 14α-demethylase inhibitors.

Abstract Sterol 14α-demethylase (CYP51) is a cytochrome P450 heme thiolate containing enzyme involved in biosynthesis of membrane sterols, including sterol in animals, ergosterol in fungi, and a variety of C24-modified sterols in plants and protozoa. Several clinical drugs have been developed to reduce the impact of fungal diseases, but their clinical uses have been limited by the emergence of drug resistance and insufficiencies in their antifungal activity. Therefore, in order to identify potential CYP51 inhibitors, we have implemented a virtual screening (VS) protocol by using both phase shape and pharmacophore model (AHHRR) against Asinex, ChemBridge and Maybridge databases. A filtering protocol, including Lipinski filter, number of rotatable bonds and different precisions of molecular docking was applied in hits selection. The results indicated that both shape-based and pharmacophore-based screening yielded the best result with potential inhibitors. The searched compounds were also evaluated with ADME properties, which show excellent pharmacokinetic properties under the acceptable range. We identified potential CYP51 inhibitors for further investigation, they could also be employed to design ligands with enhanced inhibitory potencies and to predict the potencies of analogs to guide synthesis/or prepare synthetic antifungal analogs against CYP51.

Homology modeling, molecular dynamics, and docking studies of pattern-recognition transmembrane protein-lipopolysaccharide and β-1,3 glucan-binding protein from Fenneropenaeus indicus

Lipopolysaccharide and β-1,3 glucan-binding protein (LGBP) is a family of pattern-recognition transmembrane proteins (PRPs) which plays a vital role in the immune mechanism of crustaceans in adverse conditions. Fenneropenaeus indicus LGBP-deduced amino acid has conserved potential recognition motif for β-1,3 linkages of polysaccharides and putative RGD (Arg-Gly-Asp) cell adhesion sites for the activation of innate defense mechanism. In order to understand the stimulating activity of β-1,3 glucan (β-glucan) and its interaction with LGBP, a 3D model of LGBP is generated. Molecular docking is performed with this model, and the results indicate Arg71 with strong hydrogen bond from RGD domain of LGBP. Moreover, from the docking studies, we also suggest that Arg34, Lys68, Val135, and Ala146 in LGBP are important amino acid residues in binding as they have strong bonding interaction in the active site of LGBP. In our in vitro studies, yeast agglutination results suggest that shrimp F. indicus LGBP possesses sugar binding and recognition sites in its structure, which is responsible for agglutination reaction. Our results were synchronized with the already reported evidence both in vivo and in vitro experiments. This investigation may be valuable for further experimental investigation in the synthesis of novel immunomodulator.

Comparative analysis of various electrostatic potentials on docking precision against cyclin-dependent kinase 2 protein: a multiple docking approach.

The fundamental of molecular modeling is the interaction and binding to form a complex, because it explains the action of most drugs to a receptor active site. In the present study, different semiempirical (RM1, AM1, PM3, MNDO) and ab intio (HF, DFT) charge models were investigated for their performance in prediction of docking pose against CDK2 proteins with their respective inhibitor. Further, multiple docking approaches and Prime/MM‐GBSA calculations were applied to predict the binding mode with respective charge model against CDK2 inhibitors. A reliable docking result was obtained using RRD, which showed significance improvement on ligand binding poses and docking score accuracy to the IFD. The combined use of RRD and Prime/MM‐GBSA method could give a high correlation between the predicted binding free energy and experimental biological activity. The preliminary results point out that AM1 could be a precious charge model for design of new drugs with enhanced success rate. As a very similar result was also found for a different system of the protein–ligand binding, the suggested scoring function based on AM1 method seems to be applicable in drug design. The results from this study can provide insights into highest success rate for design of potent and selective CDK2 inhibitors.