2,5-Bis(2,2,2-trifluoroethoxy)phenyl-tethered 1,3,4-Oxadiazoles Derivatives: Synthesis, In Silico Studies, and Biological Assessment as Potential Candidates for Anti-Cancer and Anti-Diabetic Agent.

In the present work, a series of new 1-{5-[2,5-bis(2,2,2-trifluoroethoxy)phenyl]-1,3,4-oxadiazol-3-acetyl-2-aryl-2H/methyl derivatives were synthesized through a multistep reaction sequence. The compounds were synthesized by the condensation of various aldehydes and acetophenones with the laboratory-synthesized acid hydrazide, which afforded the Schiff's bases. Cyclization of the Schiff bases yielded 1,3,4-oxadiazole derivatives. By spectral analysis, the structures of the newly synthesized compounds were elucidated, and further, their anti-cancer and anti-diabetic properties were investigated. To examine the dynamic behavior of the candidates at the binding site of the protein, molecular docking experiments on the synthesized compounds were performed, followed by a molecular dynamic simulation. ADMET (chemical absorption, distribution, metabolism, excretion, and toxicity) prediction revealed that most of the synthesized compounds follow Lipinski's rule of 5. The results were further correlated with biological studies. Using a cytotoxic assay, the newly synthesized 1,3,4-Oxadiazoles were screened for their in vitro cytotoxic efficacy against the LN229 Glioblastoma cell line. From the cytotoxic assay, the compounds 5b, 5d, and 5m were taken for colony formation assay and tunnel assay have shown significant cell apoptosis by damaging the DNA of cancer cells. The in vivo studies using a genetically modified diabetic model, Drosophila melanogaster, indicated that compounds 5d and 5f have better anti-diabetic activity among the different synthesized compounds. These compounds lowered the glucose levels significantly in the tested model.

Understanding the role of water on temperature-dependent structural modifications of SARS CoV-2 main protease binding sites.

Thermally stable and labile proteases are found in microorganisms. Protease mediates the cleavage of polyproteins in the virus replication and transcription process. 6 µs MD simulations were performed for monomer/dimer SARS CoV-2 main protease system in both SPC/E and mTIP3P water model to analyse the temperature-dependent behaviour of the protein. It is found that maximum conformational changes are observed at 348 K which is near the melting temperature. Network distribution of evolved conformations shows an increase in the number of communities with the rise in the temperature. The global conformation of the protein was found to be intact whereas a local conformational space evolved due to thermal fluctuations. The global conformational change in the free energy ΔΔG value for the monomer and the dimer between 278 K and 383 K is found to be 2.51 and 2.10 kJ/mol respectively. A detailed analysis was carried out on the effect of water on the temperature-dependent structural modifications of four binding pockets of SARS CoV-2 main protease namely, catalytic dyad, substrate-binding site, dimerization site and allosteric site. It is found that the water structure around the binding sites is altered with temperature. The water around the dimer sites is more ordered than the monomer sites regardless of the rise in temperature due to structural rigidity. The energy expense of binding the small molecules at substrate binding is less compared to the allosteric site. The water-water hydrogen bond lifetime is found to be more near the cavity of His41. Also, it is observed that mTIP3P water molecules have a similar effect to that of SPC/E water molecules on the main protease.

Theoretical insights into molecular mechanism and energy criteria of PARP-2 enzyme inhibition by benzimidazole analogues.

The emergence of poly (ADP-ribose) polymerase (PARP) inhibitors targeting a class of PARP enzymes has gained a great interest in cancer therapy. Majority of the PARP inhibitors are not isoform-selective which may cause unwanted off-target effects. In the present study, we explore the molecular mechanism and energy requirements for PARP-2 inhibition. This involves docking studies, frontier molecular orbital analysis, 500 ns molecular dynamics simulation (MD), binding free energy analysis and principal component analysis. The results clearly suggest the importance of hydrogen bonding (Gly429, Gln332, Ser470, Tyr455) and π-π stacking interactions (His428, Tyr455, Tyr462, Phe463, Tyr473) between residues and the inhibitor. Presence of lowest unoccupied molecular orbitals favors π-π stacking interactions and highest occupied molecular orbital orbital favors hydrogen-bonding interactions in the ligands. The stability of most active/PARP-2 complex is confirmed by hydrogen bonding and π-π stacking interaction parameters. Molecular-mechanics Poisson-Boltzmann surface area energy calculations showed that van der Waals and nonpolar solvation energy terms are crucial components for the stable binding of the ligands. Per residue analysis showed that tyrosine, histidine, and phenyl alanine residues are responsible for hydrophobic interactions with the ligands. Four new inhibitors are designed based on this study and the stability of PARP-2/inhibitor complex is validated by MD, density functional theory studies, and ADME/toxicity properties. Information from the present study can serve as a basis for designing new isoform-selective PARP-2 inhibitors.

Effect of hydrophobic and hydrogen bonding interactions on the potency of ß-alanine analogs of G-protein coupled glucagon receptor inhibitors.

G-protein coupled glucagon receptors (GCGRs) play an important role in glucose homeostasis and pathophysiology of Type-II Diabetes Mellitus (T2DM). The allosteric pocket located at the trans-membrane domain of GCGR consists of hydrophobic (TM5) and hydrophilic (TM7) units. Hydrophobic interactions with the amino acid residues present at TM5, found to facilitate the favorable orientation of antagonist at GCGR allosteric pocket. A statistically robust and highly predictive 3D-QSAR model was developed using 58 ß-alanine based GCGR antagonists with significant variation in structure and potency profile. The correlation coefficient (R2 ) and cross-validation coefficient (Q2 ) of the developed model were found to be 0.9981 and 0.8253, respectively at the PLS factor of 8. The analysis of the favorable and unfavorable contribution of different structural features on the glucagon receptor antagonists was done by 3D-QSAR contour plots. Hydrophobic and hydrogen bonding interactions are found to be main dominating non-bonding interactions in docking studies. Presence of highest occupied molecular orbital (HOMO) in the polar part and lowest unoccupied molecular orbital (LUMO) in the hydrophobic part of antagonists leads to favorable protein-ligand interactions. Molecular mechanics/generalized born surface area (MM/GBSA) calculations showed that van der Waals and nonpolar solvation energy terms are crucial components for thermodynamically stable binding of the inhibitors. The binding free energy of highly potent compound was found to be -63.475 kcal/mol; whereas the least active compound exhibited binding energy of -41.097 kcal/mol. Further, five 100 ns molecular dynamics simulation (MD) simulations were done to confirm the stability of the inhibitor-receptor complex. Outcomes of the present study can serve as the basis for designing improved GCGR antagonists.

Vetting of New 2,5-Bis (2,2,2-trifluoroethoxy) Phenyl-Linked 1,3-Thiazolidine-4-one Derivatives as AURKA and VEGFR-2 Inhibitor Antiglioma Agents Assisted with In Vitro and In Silico Studies.

The bioactivity of 1,3-thiazolidin-4-one derivatives with a 2,5-bis (2,2,2-trifluoroethoxy) phenyl moiety was computationally developed and evaluated. All of the synthesized thiazolidin-4-one derivatives have their chemical structures characterized using a variety of methods, including nuclear magnetic resonance (NMR) (1H and 13C), high-resolution mass spectrometry (HRMS), and Fourier transform infrared (FTIR) radiation. A human glioblastoma cancer cell line (LN229) was used to investigate the purified derivatives' antiglioma cancer efficacy. By using the MTT, colony formation, and tunnel tests, respectively, the in vitro cytotoxic and apoptotic effects of these compounds were assessed. Thiazolidin-4-one derivatives 5b, 5c, and 5e were discovered to have the best efficacy against glioblastoma cells out of all of these compounds. The derivatives 5b, 5c, and 5e were determined to have respective IC50 values of 9.48, 12.16, and 6.43 g/mL. Computation results showed that the bioactivity evaluations of the compounds were quite significant. The bridging -NH group forms a hydrogen bond with Glu 260 of synthesized derivatives 5b, 5c, 5d, 5e, and 5h. The vast majority of freshly developed compounds obeyed Lipinski's rule of five, which is in line with the results that the ADMET model predicted. Additionally, molecular docking evaluation and molecular dynamics simulation investigations against the proteins AURKA and VEGFR-2 were conducted for the synthesized compounds to incorporate both in silico and in vitro data. The findings revealed that almost all of the compounds had considerable binding to AURKA and VEGFR-2 residues, with binding affinities ranging from -9.8 to -7.9 kcal/mol. Consequently, the results of the biological investigations and the docking scores demonstrated that thiazolidinone molecule 5e containing 4-chlorophenyl substituent may be considered as a potential moiety for glioblastoma cancer treatments.

Molecular mechanism of inhibition of COVID-19 main protease by ß-adrenoceptor agonists and adenosine deaminase inhibitors using in silico methods.

Novel coronavirus (COVID-19) responsible for viral pneumonia which emerged in late 2019 has badly affected the world. No clinically proven drugs are available yet as the targeted therapeutic agents for the treatment of this disease. The viral main protease which helps in replication and transcription inside the host can be an effective drug target. In the present study, we aimed to discover the potential of ß-adrenoceptor agonists and adenosine deaminase inhibitors which are used in asthma and cancer/inflammatory disorders, respectively, as repurposing drugs against protease inhibitor by ligand-based and structure-based virtual screening using COVID-19 protease-N3 complex. The AARRR pharmacophore model was used to screen a set of 22,621 molecules to obtain hits, which were subjected to high-throughput virtual screening. Extra precision docking identified four top-scored molecules such as +/--fenoterol, FR236913 and FR230513 with lower binding energy from both categories. Docking identified three major hydrogen bonds with Gly143, Glu166 and Gln189 residues. 100 ns MD simulation was performed for four top-scored molecules to analyze the stability, molecular mechanism and energy requirements. MM/PBSA energy calculation suggested that van der Waals and electrostatic energy components are the main reasons for the stability of complexes. Water-mediated hydrogen bonds between protein-ligand and flexibility of the ligand are found to be responsible for providing extra stability to the complexes. The insights gained from this combinatorial approach can be used to design more potent and bio-available protease inhibitors against novel coronavirus.Communicated by Ramaswamy H. Sarma.

Exploring the multiple conformational states of RNA genome through interhelical dynamics and network analysis.

The structural variation of RNA is often very transient and can be easily missed in experiments. Molecular dynamics simulation studies along with network analysis can be an effective tool to identify prominent conformations of such dynamic biomolecular systems. Here we describe a method to effectively sample different RNA conformations at six different temperatures based on the changes in the interhelical orientations. This method gives the information about prominent states of the RNA as well as the probability of the existence of different conformations and their interconnections during the process of evolution. In the case of the SARS-CoV-2 genome, the change of prominent structures was found to be faster at 333 K as compared to higher temperatures due to the formation of the non-native base pairs. ΔΔG calculated between 288 K and 363 K are found to be 10.31 kcal/mol (88 nt) considering the contribution from the multiple states of the RNA which agrees well with the experimentally reported denaturation energy for E. coli α mRNA pseudoknot (∼16 kcal/mol, 112 nt) determined by calorimetry/UV hyperchromicity and human telomerase RNA telomerase (4.5-6.6 kcal/mol, 54 nt) determined by FRET analysis.

Temperature-Dependent Conformational Evolution of SARS CoV-2 RNA Genome Using Network Analysis.

Understanding the dynamics of the SARS CoV-2 RNA genome and its dependence on temperature is necessary to fight the current COVID-19 crisis. Computationally, the handling of large data is a major challenge in the elucidation of the structures of RNA. This work presents network analysis as an important tool to see the conformational evolution and the most dominant structures of the RNA genome at six different temperatures. It effectively distinguished different communities of RNA having structural variation. It is found that at higher temperatures (348 K and above), 80% of the RNA structure is destroyed in both the SPC/E and mTIP3P water models. The thermal denaturation free energy change ΔΔG value calculated for the long-lived structure at higher temperatures of 348 and 363 K ranges from 2.58 to 2.78 kcal/mol for the SPC/E water model, which agrees well with the experimentally reported thermal denaturation free energy range of 2.874 kcal/mol of SARS CoV-NP at normal pH. At higher temperatures, the stability of RNA conformation is found to be due to the existence of non-native base pairs in the SPC/E water model.