Jaspreet Kaur Dhanjal

Development of Dual Inhibitors against Alzheimer’s Disease Using Fragment-Based QSAR and Molecular Docking

Alzheimers (AD) is the leading cause of dementia among elderly people. Considering the complex heterogeneous etiology of AD, there is an urgent need to develop multitargeted drugs for its suppression. β-amyloid cleavage enzyme (BACE-1) and acetylcholinesterase (AChE), being important for AD progression, have been considered as promising drug targets. In this study, a robust and highly predictive group-based QSAR (GQSAR) model has been developed based on the descriptors calculated for the fragments of 20 1,4-dihydropyridine (DHP) derivatives. A large combinatorial library of DHP analogues was created, the activity of each compound was predicted, and the top compounds were analyzed using refined molecular docking. A detailed interaction analysis was carried out for the top two compounds (EDC and FDC) which showed significant binding affinity for BACE-1 and AChE. This study paves way for consideration of these lead molecules as prospective drugs for the effective dual inhibition of BACE-1 and AChE. The GQSAR model provides site-specific clues about the molecules where certain modifications can result in increased biological activity. This information could be of high value for design and development of multifunctional drugs for combating AD.

Fragment based group QSAR and molecular dynamics mechanistic studies on arylthioindole derivatives targeting the α-β interfacial site of human tubulin.

BackgroundA number of microtubule disassembly blocking agents and inhibitors of tubulin polymerization have been elements of great interest in anti-cancer therapy, some of them even entering into the clinical trials. One such class of tubulin assembly inhibitors is of arylthioindole derivatives which results in effective microtubule disorganization responsible for cell apoptosis by interacting with the colchicine binding site of the β-unit of tubulin close to the interface with the α unit. We modelled the human tubulin β unit (chain D) protein and performed docking studies to elucidate the detailed binding mode of actions associated with their inhibition. The activity enhancing structural aspects were evaluated using a fragment-based Group QSAR (G-QSAR) model and was validated statistically to determine its robustness. A combinatorial library was generated keeping the arylthioindole moiety as the template and their activities were predicted.ResultsThe G-QSAR model obtained was statistically significant with r2 value of 0.85, cross validated correlation coefficient q2 value of 0.71 and pred_r2 (r2 value for test set) value of 0.89. A high F test value of 65.76 suggests robustness of the model. Screening of the combinatorial library on the basis of predicted activity values yielded two compounds HPI (predicted pIC50 = 6.042) and MSI (predicted pIC50 = 6.001) whose interactions with the D chain of modelled human tubulin protein were evaluated in detail. A toxicity evaluation resulted in MSI being less toxic in comparison to HPI.ConclusionsThe study provides an insight into the crucial structural requirements and the necessary chemical substitutions required for the arylthioindole moiety to exhibit enhanced inhibitory activity against human tubulin. The two reported compounds HPI and MSI showed promising anti cancer activities and thus can be considered as potent leads against cancer. The toxicity evaluation of these compounds suggests that MSI is a promising therapeutic candidate. This study provided another stepping stone in the direction of evaluating tubulin inhibition and microtubule disassembly degeneration as viable targets for development of novel therapeutics against cancer.

Structural insights into mode of actions of novel natural Mycobacterium protein tyrosine phosphatase B inhibitors

BackgroundTuberculosis has become a major health problem being the second leading cause of death worldwide. Mycobacterium tuberculosis secretes a virulence factor, protein tyrosine phosphatase B (mPTPB) in the cytoplasm of host macrophage which suppresses its natural innate immune response and helps the pathogen survive and proliferate in the phagosome. The present study aims at indentifying potent inhibitors of mPTPB by using computational approaches of ligand based molecular modeling and docking studies.ResultsA 3D QSAR model was developed using a set of benzofuran salicylic acid based mPTPB inhibitors with experimentally known IC50 values. The model was generated using the statistical method of principle component regression analysis in combination with step wise forward variable selection algorithm. It was observed that steric and hydrophobic descriptors positively contribute towards the inhibitory activity of the ligands. The developed model had a robust internal as well as external predictive power as indicated by the q2 value of 0.8920 and predicted r2 value of 0.8006 respectively. Hence, the generated model was used to screen a large set of naturally occurring chemical compounds and predict their biological activity to identify more potent natural compounds targeting mPTPB. The two top potential hits (with pIC50 value of 1.459 and 1.677 respectively) had a similar interaction pattern as that of the most potent compound (pIC50 = 1.42) of the congeneric series.ConclusionThe contour plot provided a better understanding of the relationship between structural features of substituted benzofuran salicylic acid derivatives and their activities which would facilitate design of novel mPTPB inhibitors. The QSAR modeling was used to obtain an equation, correlating the important steric and hydrophobic descriptors with the pIC50 value. Thus, we report two natural compounds of inhibitory nature active against mPTPB enzyme of Mycobacterium tuberculosis. These inhibitors have the potential to evolve as lead molecules in the development of drugs for the treatment of tuberculosis.

Mechanistic analysis elucidating the relationship between Lys96 mutation in Mycobacterium tuberculosis pyrazinamidase enzyme and pyrazinamide susceptibility

Background Pyrazinamide (PZA) is one of the most effective first line treatments against tuberculosis disease. The drug generally has bacteriostatic action. It also acts on bacterial spores which eliminates the chances of resurfacing of the infection. However, in recent years there has been a major increase in the occurrence of drug resistant bacterial strains. Resistance against PZA is caused by mutations in pyrazinamidase (PncA) protein which is the activator of the prodrug PZA. In the present study, we have tried to gain insights into the mechanism by which resistance develops due to K96R mutation occurring in the PncA catalytic region Results The binding cavity analysis showed an increase of 762.3 A 3 in the volume of the mutant protein. Docking studies revealed that PZA has a greater binding affinity for the native protein in comparison to the mutant protein. Molecular dynamics simulations further showed the role of flap region, which is present in PncA protein, in development of resistance to the drug. Conclusion The residues of flap region acquire more flexibility in mutant form of protein and thus move away from the active site. This leads to weak binding of the drug to the target residues which might interfere with the activation of the drug to functional form thereby giving rise to drug resistant bacterial strains. Background

Mechanistic insights into mode of action of novel natural cathepsin L inhibitors

BackgroundDevelopment of a cancerous cell takes place when it ceases to respond to growth-inhibiting signals and multiplies uncontrollably and can detach and move to other parts of the body; the process called as metastasis. A particular set of cysteine proteases are very active during cancer metastasis, Cathepsins being one of them. They are involved in tumor growth and malignancy and have also been reported to be overexpressed in tumor cell lines. In the present study, a combinatorial approach comprising three-dimensional quantitative structure-activity relationship (3D QSAR), ligand-based pharmacophore modelling and search followed by cathepsin L structure-based high throughput screening was carried out using an initial set of 28 congeneric thiosemicarbazone derivatives as cathepsin L inhibitors. A 3D QSAR was derived using the alignment of a common thiosemicarbazone substructure. Essential structural features responsible for biological activity were taken into account for development of a pharmacophore model based on 29 congeneric thiosemicarbazone derivatives. This model was used to carry out an exhaustive search on a large dataset of natural compounds. A further cathepsin L structure-based screen identified two top scoring compounds as potent anti-cancer leads.ResultsThe generated 3D QSAR model showed statistically significant results with an r2 value of 0.8267, cross-validated correlation coefficient q2 of 0.7232, and a pred_r2 (r2 value for test set) of 0.7460. Apart from these, a high F test value of 30.2078 suggested low probability of the models failure. The pharmacophoric hypothesis chosen for searching the natural compound libraries was identified as DDHRR, where two Ds denote 2 hydrogen donors, H represents a hydrophobic group and two Rs represent aromatic rings, all of which are essential for the biological activity. We report two potential drug leads ZINC08764437 (NFP) and ZINC03846634 (APQ) obtained after a combined approach of pharmacophore-based search and structure-based virtual screen. These two compounds displayed extra precision docking scores of -7.972908 and -7.575686 respectively suggesting considerable binding affinity for cathepsin L. High activity values of 5.72 and 5.75 predicted using the 3D QSAR model further substantiated the inhibitory potential of these identified leads.ConclusionThe present study attempts to correlate the structural features of thiosemicarbazone group with their biological activity by development of a robust 3D QSAR model. Being statistically valid, this model provides near accurate values of the activities predicted for the congeneric set on which it is based. These predicted activities are good for the test set compounds making it indeed a statistically sound 3D QSAR model. The identified pharmacophore model DDHRR.8 comprised of all the essential features required to interact with the catalytic triad of cathepsin L. A search for natural compounds based on this pharmacophore followed by docking studies further screened out two top scoring candidates: NFP and AFQ. The high binding affinity and presence of essential structural features in these two compounds make them ideal for consideration as natural anti-tumoral agents. Activity prediction using 3D QSAR model further validated their potential as worthy drug candidates against cathepsin L for treatment of cancer.

Novel Fragment‐Based QSAR Modeling and Combinatorial Design of Pyrazole‐Derived CRK3 Inhibitors as Potent Antileishmanials

The CRK3 cyclin‐dependent kinase of Leishmania plays an important role in regulating the cell‐cycle progression at the G2/M phase checkpoint transition, proliferation, and viability inside the host macrophage. In this study, a novel fragment‐based QSAR model has been developed using 22 pyrazole‐derived compounds exhibiting inhibitory activity against Leishmanial CRK3. Unlike other QSAR methods, this fragment‐based method gives flexibility to study the relationship between molecular fragments of interest and their contribution for the variation in the biological response by evaluating cross‐term fragment descriptors. Based on the fragment‐based QSAR model, a combinatorial library was generated, and top two compounds were reported after predicting their activity. The QSAR model showed satisfactory statistical parameters for the data set (r2 = 0.8752, q2 = 0.6690, F‐ratio = 30.37, and pred_r2 = 0.8632) with four descriptors describing the nature of substituent groups and the environment of the substitution site. Evaluation of the model implied that electron‐rich substitution at R1 position improves the inhibitory activity, while decline in inhibitory activity was observed in presence of nitrogen at R2 position. The analysis carried out in this study provides a substantial basis for consideration of the designed pyrazole‐based leads as potent antileishmanial drugs.

Group-based QSAR and molecular dynamics mechanistic analysis revealing the mode of action of novel piperidinone derived protein–protein inhibitors of p53-MDM2

Tumour suppressor p53 is known to play a central role in prevention of tumour development, DNA repair, senescence and apoptosis which is in normal cells maintained by negative feedback regulator MDM2 (Murine Double Minute 2). In case of dysfunctioning of this regulatory loop, tumour development starts thus resulting in cancerous condition. Inhibition of p53-MDM2 binding would result in activation of the tumour suppressor. In this study, a novel robust fragment-based QSAR model has been developed for piperidinone derived compounds experimentally known to inhibit p53-MDM2 interaction. The QSAR model developed showed satisfactory statistical parameters for the experimentally reported dataset (r(2)=0.9415, q(2)=0.8958, pred_r(2)=0.8894 and F-test=112.7314), thus judging the robustness of the model. Low standard error values (r(2)_se=0.3003, q(2)_se=0.4009 and pred_r(2)_se=0.3315) confirmed the accuracy of the developed model. The regression equation obtained constituted three descriptors (R2-DeltaEpsilonA, R1-RotatableBondCount and R2-SssOCount), two of which had positive contribution while third showed negative correlation. Based on the developed QSAR model, a combinatorial library was generated and activities of the compounds were predicted. These compounds were docked with MDM2 and two top scoring compounds with binding affinities of -10.13 and -9.80kcal/mol were selected. The binding modes of actions of these complexes were analyzed using molecular dynamics simulations. Analysis of the developed fragment-based QSAR model revealed that addition of unsaturated electronegative groups at R2 site and groups with more rotatable bonds at R1 improved the inhibitory activity of these potent lead compounds. The detailed analysis carried out in this study provides a considerable basis for the design and development of novel piperidinone-based lead molecules against cancer and also provides mechanistic insights into their mode of actions.

Mechanistic insights into mode of action of potent natural antagonists of BACE-1 for checking Alzheimer's plaque pathology.

Alzheimers is a neurodegenerative disorder resulting in memory loss and decline in cognitive abilities. Accumulation of extracellular beta amyloidal plaques is one of the major pathology associated with this disease. β-Secretase or BACE-1 performs the initial and rate limiting step of amyloidic pathway in which 37-43 amino acid long peptides are generated which aggregate to form plaques. Inhibition of this enzyme offers a viable prospect to check the growth of these plaques. Numerous efforts have been made in recent years for the generation of BACE-1 inhibitors but many of them failed during the preclinical or clinical trials due to drug related or drug induced toxicity. In the present work, we have used computational methods to screen a large dataset of natural compounds to search for small molecules having BACE-1 inhibitory activity with low toxicity to normal cells. Molecular dynamics simulations were performed to analyze molecular interactions between the screened compounds and the active residues of the enzyme. Herein, we report two natural compounds of inhibitory nature active against β-secretase enzyme of amyloidic pathway and are potent lead molecules against Alzheimers disease.

Embelin inhibits TNF-α converting enzyme and cancer cell metastasis: molecular dynamics and experimental evidence

BackgroundEmbelin, a quinone derivative, is found in the fruits of Embelia ribes Burm (Myrsinaceae). It has been shown to have a variety of therapeutic potentials including anthelmintic, anti-tumor, anti-diabetic, anti-bacterial and anti-inflammation. Inflammation is an immunological response to external harmful stimuli and is regulated by an endogenous pyrogen and pleiotropic pro-inflammatory cytokine, tumor necrosis factor alpha (TNF-α). TNF-α production has been implicated in a variety of other human pathologies including neurodegeneration and cancer. Several studies have shown that the anti-inflammatory activity of embelin is mediated by reduction in TNF-α. The latter is synthesized as a membrane anchored protein (pro-TNF-α); the soluble component of pro-TNF-α is then released into the extracellular space by the action of a protease called TNF-α converting enzyme (TACE). TACE, hence, has been proposed as a therapeutic target for inflammation and cancer.MethodsWe used molecular docking and experimental approaches to investigate the docking potential and molecular effects of embelin to TACE and human cancer cell characteristics, respectively.ResultsWe demonstrate that embelin is a potential inhibitor of TACE. Furthermore, in vitro studies revealed that it inhibits malignant properties of cancer cells through inactivation of metastatic signaling molecules including MMPs, VEGF and hnRNP-K in breast cancer cells.ConclusionBased on the molecular dynamics and experimental data, embelin is proposed as a natural anti-inflammatory and anticancer drug.

Computational identification of novel natural inhibitors of glucagon receptor for checking type II diabetes mellitus

BackgroundInteraction of the small peptide hormone glucagon with glucagon receptor (GCGR) stimulates the release of glucose from the hepatic cells during fasting; hence GCGR performs a significant function in glucose homeostasis. Inhibiting the interaction between glucagon and its receptor has been reported to control hepatic glucose overproduction and thus GCGR has evolved as an attractive therapeutic target for the treatment of type II diabetes mellitus.ResultsIn the present study, a large library of natural compounds was screened against 7 transmembrane domain of GCGR to identify novel therapeutic molecules that can inhibit the binding of glucagon with GCGR. Molecular dynamics simulations were performed to study the dynamic behaviour of the docked complexes and the molecular interactions between the screened compounds and the ligand binding residues of GCGR were analysed in detail. The top scoring compounds were also compared with already documented GCGR inhibitors- MK-0893 and LY2409021 for their binding affinity and other ADME properties. Finally, we have reported two natural drug like compounds PIB and CAA which showed good binding affinity for GCGR and are potent inhibitor of its functional activity.ConclusionThis study contributes evidence for application of these compounds as prospective small ligand molecules against type II diabetes. Novel natural drug like inhibitors against the 7 transmembrane domain of GCGR have been identified which showed high binding affinity and potent inhibition of GCGR