The peels extracted from various citrus species are major source of phenols, flavonoids and anti-microbial agents. The purpose of this study was a detailed investigation of the phytochemical and pharmacological character of the ethanolic (80%), methanolic and acetone extracts of the peel of local variants of orange (lemon, grape fruit, mousami, fruiter, and shikri malta). The extracts were studied to find out the total phenolic contents (TPC), and total flavonoids (TF) present. The antioxidant activities were assessed by 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging effect, and the reducing power was determined through free radical scavenging activity (FRAP) assays. The sensitivity of four bacterial strains to peels extracts was examined by applying the diffusion disc on agar medium method. It was found that ethanol was the best extracting agent for TPC and TF in fruit peels under study. The highest TPC (21.33 ± 0.06 mg GAE/g) was quantified in orange peels, whereas fruiter contained the lowest TPC (20.40 ± 0.03 mg GAE/g) in ethanolic extract. The highest amount of TF (2.02 ± 0.08 mg QE/g) was quantified in lemon peels, whereas shikri malta contained lowest quantity of TF (1.04 ± 0.02 mg QE/g). The highest free radical scavenging activity (93.1%) of DPPH was exhibited by lemon peels, whereas the least activity (78.6%) was shown by mousami peels. Ethanolic extract of orange peels demonstrated more reducing power while showing an absorption of 1.98, followed by methanolic (1.11) and acetone (0.81) extracts. The inhibition effect of methanolic extract of lemon peels (inhibition zone = 18 mm) against B. subtilis was considerable and comparable to that of ciprofloxacin. Gas chromatography/mass spectrometry (GC/MS) was used to detect the compounds in ethanolic extract and up to 14 compounds were detected. These compounds were also assessed for their docking scores. Plausible binding modes with polyphenol oxidase and four best compounds were selected for molecular dynamics (MD) simulation to analyze their structural stability with receptor.

Tyrosine threonine kinase (TTK) is the key component of the spindle assembly checkpoint (SAC) that ensures correct attachment of chromosomes to the mitotic spindle and thereby their precise segregation into daughter cells by phosphorylating specific substrate proteins. The overexpression of TTK has been associated with various human malignancies, including breast, colorectal and thyroid carcinomas. TTK has been validated as a target for drug development, and several TTK inhibitors have been discovered. In this study, ligand and structure-based alignment as well as various partial charge models were used to perform 3D-QSAR modelling on 1H-Pyrrolo[3,2-c] pyridine core containing reported inhibitors of TTK protein using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches to design better active compounds. Different statistical methods i.e., correlation coefficient of non-cross validation (r²), correlation coefficient of leave-one-out cross-validation (q²), Fisher’s test (F) and bootstrapping were used to validate the developed models. Out of several charge models and alignment-based approaches, Merck Molecular Force Field (MMFF94) charges using structure-based alignment yielded highly predictive CoMFA (q² = 0.583, Predr² = 0.751) and CoMSIA (q² = 0.690, Predr² = 0.767) models. The models exhibited that electrostatic, steric, HBA, HBD, and hydrophobic fields play a key role in structure activity relationship of these compounds. Using the contour maps information of the best predictive model, new compounds were designed and docked at the TTK active site to predict their plausible binding modes. The structural stability of the TTK complexes with new compounds was confirmed using MD simulations. The simulation studies revealed that all compounds formed stable complexes. Similarly, MM/PBSA method based free energy calculations showed that these compounds bind with reasonably good affinity to the TTK protein. Overall molecular modelling results suggest that newly designed compounds can act as lead compounds for the optimization of TTK inhibitors.