QSAR and pharmacophore modeling of diverse aminothiazoles and aminopyridines for antimalarial potency against multidrug-resistant Plasmodium falciparum

Identification of potential antivirals against 3CLpro enzyme for the treatment of SARS-CoV-2: A multi-step virtual screening study

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) outbreak is posing a serious public health threat worldwide in the form of COVD-19. Herein, we have performed two-dimensional quantitative structure-activity relationship (2D-QSAR) and three-dimensional pharmacophore modelling analysis employing inhibitors of 3-chymotrypsin-like protease (3CLpro), the leading protease that is crucial for the replication of SARS-CoV-2. The investigation aims to identify the important structural features responsible for the enzyme inhibition and the search for novel 3CLpro enzyme inhibitors as effective therapeutics for treating SARS-CoV-2. Furthermore, we carried out molecular docking studies using the most and least active compounds in the dataset, aiming to validate the contributions of various features as appeared in the QSAR models. Later, the stringently validated 2D-QSAR model was used to estimate the 3CLpro inhibitory activity of compounds from five chemical databases. Compounds with the significant predicted activity were then subjected to pharmacophore-based virtual screening to screen the top-rated compounds, which were then further subjected to molecular docking analysis, absorption, distribution, metabolism, excretion - toxicity (ADMET) profiling, and molecular dynamics (MD) simulation. The multi-step virtual screening analyses suggested that compounds CASAntiV-865453-58-3, CASAntiV-865453-40-3, and CASAntiV-2043031-84-9 could be used as effective therapeutic agents for the treatment of SARS-CoV-2.

A Combined approach of Pharmacophore Modeling, QSAR Study, Molecular Docking and in silico ADME/Tox prediction of 4-Arylthio & 4- Aryloxy-3- Iodopyridine-2(1H)-one analogs to identify potential Reverse Transcriptase inhibitor: Anti-HIV agents

BACKGROUND

Reverse transcriptase is an important therapeutic target to treat AIDS caused by the Human Immunodeficiency Virus (HIV). Despite many effective anti-HIV drugs, reverse transcriptase (RT) inhibitors remain the cornerstone of the drug regimen to treat AIDS. In the present work, we have expedited the use of different computational modules and presented an easy, cost-effective and high throughput screening method to identify potential reverse transcriptase inhibitors.

METHODS

A congeneric series of 4-Arylthio & 4-Aryloxy-3- Iodopyridine-2(1H)-one analogs having anti-HIV activity were subjected to structure-based 2D, 3D QSAR, Pharmacophore Modeling, and Molecular Docking to elucidate the structural properties required for the design of potent HIV-RT inhibitors. Prediction of preliminary Pharmacokinetic and the Drug Likeliness profile was performed for these compounds by in silico ADME study.

RESULTS

The 2D and 3D- QSAR models were developed by correlating two and three-dimensional descriptors with activity (pIC50) by sphere exclusion method and k-nearest neighbor molecular field analysis approach, respectively. The significant 2D- QSAR model developed by Partial Least Square associated with the Sphere Exclusion method (PLS-SE) having r2 and q2 values 0.9509 and 0.8038 respectively. The 3D-QSAR model by Step Wise variable selection method (SW-kNN MFA) is more significant which has a cross-validated squared correlation coefficient q2= 0.8509 and a non-cross-validated correlation coefficient pred_r2= 0.8102. The pharmacophore hypothesis was developed which comprised 5 features includes 3 aliphatic regions (Ala), 1 H-bond donor (HDr) and 1 H-bond acceptor (HAc). Docking studies of the selected inhibitors with the active site of reverse transcriptase enzyme showed hydrogen bond and π - π interaction with LYS-101, LYS-103, TYR- 181, TYR-188 and TRP-229 residues present at the active site. All the candidates with good bioavailability and ADMET drug likeliness properties.

CONCLUSION

The results of the present work provide more useful information and important structural insights for the discovery, design of novel and potent reverse transcriptase inhibitors with high therapeutic windows in the future.

Biological Evaluation of 2-aminothiazole Hybrid as Antimalarial and Antitrypanosomal Agents: Design and Synthesis

Background:

A series of 2-aminothiazole schiff’s bases (1-24) were synthesized and screened against a few neglected tropical disorders (NTDs). Compounds 12 and 14 were found to have antitrypanosidal activity, whereas compound 14 was found to be more effective than standard benznidazole. The antiplasmodial assay provided three specific and effective compounds (9, 12 and 24) than standard chloroquine. Compound (21) inhibited Leishmania infantum, almost similar to Miltefosine.

Methods:

All the compounds were subjected to cytotoxicity assay and none of the compounds were found to be cytotoxicity. Molecular docking simulations revealed that four compounds (1, 9, 12 and 21) were found to similarly occupy the hydrophobic active site of trans-2-enoyl acyl carrier protein reductase of P. falciparum (PfENR) as triclosan and outcomes were closely related to their anti-malarial potencies.

Results and Conclusion:

The screening results against T. cruzi, T. brucei, L. donovani, L. infantum, P. falciferum and cytotoxicity assays provided a few significant to most potent compounds; two variant class of NTDs.

Exploring 2D-QSAR for prediction of beta-secretase 1 (BACE1) inhibitory activity against Alzheimer's disease

We have developed a robust quantitative structure-activity relationship (QSAR) model employing a dataset of 98 heterocycle compounds to identify structural features responsible for BACE1 (beta-secretase 1) enzyme inhibition. We have used only 2D descriptors for model development purpose thus avoiding the conformational complications arising due to 3D geometry considerations. Following the strict Organization for Economic Co-operation and Development (OECD) guidelines, we have developed models using stepwise regression analysis followed by the best subset selection, while the final model was developed by partial least squares regression technique. The model was validated using various internationally accepted stringent validation parameters. From the insights obtained from the developed model, we have concluded that heteroatoms (nitrogen, oxygen, etc.) present within to an aromatic nucleus and the structural features such as hydrophobic, ring aromatic and hydrogen bond acceptor/donor are responsible for the enhancement of the BACE1 enzyme inhibitory activity. Moreover, we have performed the pharmacophore modelling to unveil the structural requirements for the inhibitory activity against the BACE1 enzyme. Furthermore, molecular docking studies were carried out to understand the molecular interactions involved in binding, and the results are then correlated with the requisite structural features obtained from the QSAR and pharmacophore models.