Cytotoxic Evaluation, Molecular Docking, and 2D-QSAR Studies of Dihydropyrimidinone Derivatives as Potential Anticancer Agents

Formation of morpholine-acetamide derivatives as potent anti-tumor drug candidates: Pharmacological evaluation and molecular docking studies

Heterocyclic amines and acetamide derivatives are known for their chemotherapeutic potential. Hence, in the present study, morpholine was taken as a principal product and novel morpholine derivatives were designed, formulated, characterized, and screened for the mechanism of inhibition of carbonic anhydrase and their anticancer potential. In addition, in vitro inhibition of hypoxia-inducible factor-1 (HIF-1) protein was also investigated. Results revealed that compounds 1c, 1d, and 1h possessed significant inhibitory activities against carbonic anhydrase with IC50 of 8.80, 11.13, and 8.12 μM, respectively. Interestingly, the carbonic anhydrase inhibitory activity of compound 1h was comparable with that of standard acetazolamide (IC50 7.51 μM). The compounds 1h and 1i significantly inhibited the proliferation of ovarian cancer cell line ID8 with IC50 of 9.40, and 11.2 μM, respectively while the standard cisplatin exhibited an IC50 8.50 μM. In addition, compounds 1c, 1b, 1h and 1i also exhibited significant inhibitory effects on HIF-1α. In conclusion, we report first time the biological potential of morpholine based compounds against ovarian cancer and HIF-1α that may serve as lead molecules for drug discovery.

Identification and validation of differentially expressed genes for targeted therapy in NSCLC using integrated bioinformatics analysis

Background

Despite the high prevalence of lung cancer, with a five-year survival rate of only 23%, the underlying molecular mechanisms of non-small cell lung cancer (NSCLC) remain unknown. There is a great need to identify reliable candidate biomarker genes for early diagnosis and targeted therapeutic strategies to prevent cancer progression.

Methods

In this study, four datasets obtained from the Gene Expression Omnibus were evaluated for NSCLC- associated differentially expressed genes (DEGs) using bioinformatics analysis. About 10 common significant DEGs were shortlisted based on their p-value and FDR (DOCK4, ID2, SASH1, NPR1, GJA4, TBX2, CD24, HBEGF, GATA3, and DDR1). The expression of significant genes was validated using experimental data obtained from TCGA and the Human Protein Atlas database. The human proteomic data for post- translational modifications was used to interpret the mutations in these genes.

Results

Validation of DEGs revealed a significant difference in the expression of hub genes in normal and tumor tissues. Mutation analysis revealed 22.69%, 48.95%, and 47.21% sequence predicted disordered regions of DOCK4, GJA4, and HBEGF, respectively. The gene-gene and drug-gene network analysis revealed important interactions between genes and chemicals suggesting they could act as probable drug targets. The system-level network showed important interactions between these genes, and the drug interaction network showed that these genes are affected by several types of chemicals that could serve as potential drug targets.

Conclusions

The study demonstrates the importance of systemic genetics in identifying potential drug- targeted therapies for NSCLC. The integrative system- level approach should contribute to a better understanding of disease etiology and may accelerate drug discovery for many cancer types.

Virtual screening and drug repositioning of FDA-approved drugs from the ZINC database to identify the potential hTERT inhibitors

The length of the telomeres is maintained with the help of the enzyme telomerase constituting of two components, namely, a core reverse transcriptase protein (hTERT) and RNA (hTR). It serves as a significant and universal cancer target. In silico approaches play a crucial role in accelerating drug development processes, especially cancer drug repurposing is an attractive approach. The current study is aimed at the repurposing of FDA-approved drugs for their potential role as hTERT inhibitors. Accordingly, a library of 2,915 sets of FDA-approved drugs was generated from the ZINC database in order to screen for novel hTERT inhibitors; later on, these were subjected to molecular docking analysis. The top two hits, ZINC03784182 and ZINC01530694, were shortlisted for molecular dynamic simulation studies at 100 ns based on their binding scores. The RMSD, RMSF, Rg, SASA, and interaction energies were calculated for a 100-ns simulation period. The hit compounds were also analyzed for antitumor activity, and the results revealed promising cytotoxic activities of these compounds. The study has revealed the potential application of these drugs as antitumor agents that can be useful in treating cancer and can serve as lead compounds for further in vivo, in vitro, and clinical studies.

In-silico investigation of a novel inhibitors against the antibiotic-resistant Neisseria gonorrhoeae bacteria

Antibiotics are drugs that are used to treat or prevent bacterial infections. They work by either killing or stopping bacteria from spreading. Nevertheless, it appeared in the last decade, Antibiotic-resistant bacteria are bacteria resistant to antibiotics and cannot be controlled or killed by them. In the presence of an antibiotic, they can live and even reproduce. The Neisseria gonorrhoeae bacteria is appearing to be a multidrug-resistant pathogen. Many factors contribute to antibiotic resistance, including unfettered access to antimicrobials, incorrect drug selection, misuse, and low-quality antibiotics. Here, we investigated in-silico docking screening and analysis for ten natural marine fungus extracted compounds. The resulted data were examined for the best binding affinity, toxicity, and chemical interactions. The most superior compound was elipyrone A with six hydrogen bonds, −8.5 of binding affinity, and preferable results in the SWISS-ADME examination. It is well known that “Declining corporate investment and a lack of innovation in the development of new antibiotics are weakening efforts to battle drug-resistant illnesses,” according to the World Health Organization (WHO). So, we extended our effort to predict a new natural compound to overcome the resistance of this bacteria.

In-silico modelling studies of 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase inhibitors via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions

Influenza virus disease is one of the most infectious diseases responsible for many human deaths, and the high mutability of the virus causes drug resistance effects in recent times. As such, it became necessary to explore more inhibitors that could avert future influenza pandemics. The present research utilized some in-silico modelling concepts such as 2D-QSAR, 3D-QSAR, molecular docking simulation, and ADMET predictions on some 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase (NA) inhibitors. The 2D-QSAR modelling results revealed GFA-MLR (R train 2 =0.8414, Q2 = 0.7680) and GFA-ANN (R train ​ 2 =0.8754, Q2 = 0.8753) models with the most relevant descriptors (MATS3i, SpMax5_Bhe, minsOH and VE3_D) for predicting the inhibitory activities of the molecules which has passed the global criteria of accepting QSAR models. The results of the 3D-QSAR modelling results showed that CoMFA_ES (R train ​ 2 =0.9030, Q2 = 0.5390) and CoMSIA_EA (R train 2 =0.880, Q2 = 0.547) models are having good predicting ability among other developed models. The molecules were virtually screened via molecular docking simulation with the active site of NA protein receptor (pH1N1) which confirms their resilient potency when compared with zanamivir standard drug. Molecule 11 as the most potent molecule formed more H-bond interactions with the key residues such as TRP178, ARG152, ARG292, ARG371, and TYR406 that triggered the catalytic reactions for NA inhibition. Furthermore, six (6) molecules (9, 10, 11, 17, 22, and 31) with relatively high inhibitory activities and docking scores were identified as the possible leads for in-silico exploration of novel NA inhibitors. The drug-likeness and ADMET predictions of the lead molecules revealed non-violation of Lipinski's rule and good pharmacokinetic profiles respectively, which are important guidelines for rational drug design. Hence, the outcome of this study overlaid a solid foundation for the in-silico design and exploration of novel NA inhibitors with improved potency.

Investigation of anti-diabetic potential and molecular simulation studies of dihydropyrimidinone derivatives

In an attempt to find new targets for α-amylase and α-glucosidase for the treatment of type 2 diabetes mellitus, the present study aims in determining the anti-diabetic potential of synthesized dihydropyrimidinone derivatives. The in vitro α-glucosidase and α-amylase inhibitory activity was performed and the molecular docking analysis of the ligand in the active binding site of target protein was determined. The results revealed significant percent inhibition of α-glucosidase by the compound 6-benzyl-4-(4-hydroxyphenyl)-3,4,6,7-tetrahydro-1H-pyrrolo[3,4-d]pyrimidine-2,5-dione (compound A). The active compound showed 81.99% inhibition when compared to standard ascorbic acid having percent inhibition 81.18%. The IC₅₀ of active compound (A) showed to be 1.02 µg/ml. The molecular docking analysis revealed that the ligand bound to the active binding site of protein with the lowest binding energy of -7.9 kcal/mol that was also significantly similar to standard having -7.8 kcal/mol binding energy. The molecular dynamic simulation studies also revealed stable binding of ligand in the active binding site of protein with low RMSD of 1.7 Å similar to the protein RMSD 1.6Å In conclusion, the study revealed a potential new target against α-glucosidase to treat type 2 diabetes mellitus.