Evaluation of antibacterial, cytotoxicity, and apoptosis activity of novel chromene-sulfonamide hybrids synthesized under solvent-free conditions and 3D-QSAR modeling studies.

In this study, eleven novel chromene sulfonamide hybrids were synthesized by a convenient method in accordance with green chemistry. At first, chromene derivatives (1-9a) were prepared through the multi-component reaction between aryl aldehydes, malononitrile, and 3-aminophenol. Then, synthesized chromenes were reacted with appropriate sulfonyl chlorides by grinding method to give the corresponding chromene sulfonamide hybrids (1-11b). Synthesized hybrids were obtained in good to high yield and characterized by IR, 1HNMR, 13CNMR, CHN and melting point techniques. In addition, the broth microdilution assay was used to determine the minimal inhibitory concentration of newly synthesized chromene-sulfonamide hybrids. The MTT test was used to determine the cytotoxicity and apoptotic activity of the newly synthesized compounds against fibroblast L929 cells. The 3D­QSAR analysis confirmed the experimental assays, demonstrating that our predictive model is useful for developing new antibacterial inhibitors. Consequently, molecular docking studies were performed to validate the findings of the 3D-QSAR analysis, confirming the potential binding interactions of the synthesized chromene-sulfonamide hybrids with the target enzymes. Molecular docking studies were employed to support the 3D-QSAR predictions, providing insights into the binding interactions between the newly synthesized chromene-sulfonamide hybrids and their target bacterial enzymes, thereby reinforcing the potential efficacy of these compounds as antibacterial agents. Also, some of the experimental outcomes supported or conflicted with the pharmacokinetic prediction (especially about compound carcinogenicity). The performance of ADMET predictor results was assessed. The work presented here proposes a computationally driven strategy for designing and discovering a new sulfonamide scaffold for bacterial inhibition.

Computational evaluation and benchmark study of 342 crystallographic holo-structures of SARS-CoV-2 Mpro enzyme.

The coronavirus disease 19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to a global health crisis with millions of confirmed cases and related deaths. The main protease (Mpro) of SARS-CoV-2 is crucial for viral replication and presents an attractive target for drug development. Despite the approval of some drugs, the search for effective treatments continues. In this study, we systematically evaluated 342 holo-crystal structures of Mpro to identify optimal conformations for structure-based virtual screening (SBVS). Our analysis revealed limited structural flexibility among the structures. Three docking programs, AutoDock Vina, rDock, and Glide were employed to assess the efficiency of virtual screening, revealing diverse performances across selected Mpro structures. We found that the structures 5RHE, 7DDC, and 7DPU (PDB Ids) consistently displayed the lowest EF, AUC, and BEDROCK scores. Furthermore, these structures demonstrated the worst pose prediction results in all docking programs. Two structural differences contribute to variations in docking performance: the absence of the S1 subsite in 7DDC and 7DPU, and the presence of a subpocket in the S2 subsite of 7DDC, 7DPU, and 5RHE. These findings underscore the importance of selecting appropriate Mpro conformations for SBVS, providing valuable insights for advancing drug discovery efforts.

A Molecular Generative Model of COVID-19 Main Protease Inhibitors Using Long Short-Term Memory-Based Recurrent Neural Network.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a serious threat to public health and prompted researchers to find anti-coronavirus 2019 (COVID-19) compounds. In this study, the long short-term memory-based recurrent neural network was used to generate new inhibitors for the coronavirus. First, the model was trained to generate drug compounds in the form of valid simplified molecular-input line-entry system strings. Then, the structures of COVID-19 main protease inhibitors were applied to fine-tune the model. After fine-tuning, the network could generate new molecular structures as novel SARS-CoV-2 main protease inhibitors. Molecular docking exhibited that some generated compounds have the proper affinity to the active site of the protease. Molecular Dynamics simulations explored binding free energies of the compounds over simulation trajectories. In addition, in silico absorption, distribution, metabolism, and excretion studies showed that some novel compounds could be formulated as orally active agents. Based on molecular docking and molecular dynamics simulation studies, compound AADH possessed significant binding affinity and presumably inhibition against the SARS-CoV-2 main protease enzyme. Therefore, the proposed deep learning-based model was capable of generating promising anti-COVID-19 drugs.

Synthesis, Docking Study and Biological Evaluation of Amide-Based Soluble Epoxide Hydrolase Inhibitors with Novel Secondary Pharmacophore of Pyrimidin-2-ol.

Soluble epoxide hydrolase enzyme (sEH) is one of the most promising and emerging targets to develop drugs for multiple disease indications, including hypertension, diabetes, stroke, dyslipidemia, pain, etc. Most inhibitor scaffolds have a urea or amide moiety to mimic the active-site transition state. In this regard, we developed a series of amide sEH inhibitors with a pyrimidin-2-ol ring as a new secondary pharmacophore, which was subjected to in vitro evaluation. Compound 4w (4-chloro-N-{4-[6-(4-chlorophenyl)-2-hydroxypyrimidin-4-yl]phenyl}benzamide), which contains 4-chloro substituent in both terminal phenyl rings, exhibited the most inhibitory activity against sEH with an IC50 value of 1.2 nM. Molecular docking analysis of the synthesized compounds revealed that the greater number of hydrogen bonding interactions of the amide group as the primary pharmacophore with Asp-353, Tyr-383, and Tyr-466 as the key catalytic residue triad of the enzyme played a critical role and led to a more favorable binding affinity. Pharmacokinetic properties of the synthesized compounds were calculated in silico, and all ADMET indices fell within acceptable ranges. Altogether, the results of this work could provide useful information on 4,6-diphenylpyrimidin-2-olas sEH inhibitors which can be utilized in further development in this area.

Investigating the Antituberculosis Activity of Selected Commercial Essential Oils and Identification of Active Constituents Using a Biochemometrics Approach and In Silico Modeling.

Tuberculosis (TB) is a disease caused by Mycobacterium tuberculosis which has become prevalent due to the emergence of resistant M. tuberculosis strains. The use of essential oils (EOs) as potential anti-infective agents to treat microbial infections, including TB, offers promise due to their long historical use and low adverse effects. The current study aimed to investigate the in vitro anti-TB activity of 85 commercial EOs, and identify compounds responsible for the activity, using a biochemometrics approach. A microdilution assay was used to determine the antimycobacterial activity of the EOs towards some non-pathogenic Mycobacterium strains. In parallel, an Alamar blue assay was used to investigate antimycobacterial activity towards the pathogenic M. tuberculosis strain. Chemical profiling of the EOs was performed using gas chromatography-mass spectrometry (GC-MS) analysis. Biochemometrics filtered out putative biomarkers using orthogonal projections to latent structures discriminant analysis (OPLS-DA). In silico modeling was performed to identify potential therapeutic targets of the active biomarkers. Broad-spectrum antimycobacterial activity was observed for Cinnamomum zeylanicum (bark) (MICs = 1.00, 0.50, 0.25 and 0.008 mg/mL) and Levisticum officinale (MICs = 0.50, 0.5, 0.5 and 0.004 mg/mL) towards M. smegmatis, M. fortuitum, M. gordonae and M. tuberculosis, respectively. Biochemometrics predicted cinnamaldehyde, thymol and eugenol as putative biomarkers. Molecular docking demonstrated that cinnamaldehyde could serve as a scaffold for developing a novel class of antimicrobial compounds by targeting FtsZ and PknB from M. tuberculosis.

Structure-based identification of potential SARS-CoV-2 main protease inhibitors.

To address coronavirus disease (COVID-19), currently, no effective drug or vaccine is available. In this regard, molecular modeling approaches are highly useful to discover potential inhibitors of the main protease (Mpro) enzyme of SARS-CoV-2. Since, the Mpro enzyme plays key roles in mediating viral replication and transcription; therefore, it is considered as an attractive drug target to control SARS-CoV-2 infection. By using structure-based drug design, pharmacophore modeling, and virtual high throughput drug screening combined with docking and all-atom molecular dynamics simulation approach, we have identified five potential inhibitors of SARS-CoV-2 Mpro. MD simulation studies revealed that compound 54035018 binds to the Mpro with high affinity (ΔGbind -37.40 kcal/mol), and the complex is more stable in comparison with other protein-ligand complexes. We have identified promising leads to fight COVID-19 infection as these compounds fulfill all drug-likeness properties. However, experimental and clinical validations are required for COVID-19 therapy.Communicated by Ramaswamy H. Sarma.

Discovery of novel heterocyclic amide-based inhibitors: an integrative in-silico approach to targeting soluble epoxide hydrolase.

Inhibition of soluble epoxide hydrolase (sEH) is considered as an emerging druggable target to reduce blood pressure, improve insulin sensitivity, and decrease inflammation. Despite the availability of different classes of sEH small molecule inhibitors for the potential treatment of hypertension, only a few candidates have reached clinical trials, making the optimal control of blood pressure presently unattainable. This necessity motivated us to explore a series of novel quinazoline-4(3H)-one and 4,6-disubstituted pyridin-2(1H)-one derivatives targeting sEH enzyme. Herein, comprehensive computational investigations were performed to probe the inhibition efficacy of these potent compounds in terms of inhibitor-enzyme interactions against sEH. In this study, the 39 in-house with a focused library comprising 39 in-house synthesized compounds were selected. The structure-based pharmacophore modeling was developed based on the crystal structure of sEH with its co-crystallized biologically active inhibitor. The generated hypotheses were applied for virtual screening-based PHASE fitness scores. Docking-based virtual screening workflows were used to generate lead compounds using HTVS, SP and XP based GLIDE G-score values. The candidate leads were filtered using ADMET pharmacological and physicochemical properties screening. A 100-ns of molecular dynamics simulations with Molecular dynamics simulations (100 ns) were performed to explore the binding affinities of the considered compounds. Our study identified four best candidates from quinazoline-4(3H)-one derivatives, which indicated that a quinazolinone ring serves as a suitable scaffold to develop novel small molecule sEH inhibitors.

Targeting ebola virus VP40 protein through novel inhibitors: exploring the structural and dynamic perspectives on molecular landscapes.

Ebola filovirus (EBOV) is one of the deadliest known infectious agents, and a cause of Western African epidemics from 2013 to 2016. The virus has infected nearly 3000 humans and almost 1900 have died. In the past few years, various small molecules have been discovered to display efficiency against EBOV and some of them have progressed towards clinical trials. Even though continuous attempts have been made to find antiEBOV therapeutics, no potential drugs are yet approved against this viral infection. The development of small antiviral inhibitors has gained tremendous attention in the attempt to overcome EVD. With this background, we seek to offer molecular insights into EBOV VP40 protein inhibition, using all atom molecular mechanics methodology and binding free energy calculations. We have selected five novel reported inhibitors against VP40 protein, namely Comp1, Comp2, Comp3, Comp4, and Comp5, and explored their binding against the same target. It was evident from the analysis that all the inhibitors displayed stability in complex with VP40 protein; however, Comp1 exhibited enhanced stability and compactness. Comp1 unveiled favorable binding, which accounted for positive correlation motions in the active site residues. Likewise, Comp1 revealed the most promising binding (ΔGbind - 40.3504 kcal/mol) as compared to the other four inhibitors, which disclosed relatively less favorable ΔGbind. The highest binding energy of Comp1 to VP40 protein can be primarily endorsed to the upsurge in van der Waals energy by ΔEvdW - 37.1609 kcal/mol and Coulomb energy by ΔEele - 52.7332 kcal/mol. Also, the hydrogen bond network is robust in Comp1-VP40 complex, with four hydrogen bonds, whilst it is less in other inhibitors. The outcomes from this report may assist in the advancement of novel VP40 inhibitors with high selectivity and potency for EVD therapeutics.

ABBV-744 as a potential inhibitor of SARS-CoV-2 main protease enzyme against COVID-19.

A new pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide and become pandemic with thousands new deaths and infected cases globally. To address coronavirus disease (COVID-19), currently no effective drug or vaccine is available. This necessity motivated us to explore potential lead compounds by considering drug repurposing approach targeting main protease (Mpro) enzyme of SARS-CoV-2. This enzyme considered to be an attractive drug target as it contributes significantly in mediating viral replication and transcription. Herein, comprehensive computational investigations were performed to identify potential inhibitors of SARS-CoV-2 Mpro enzyme. The structure-based pharmacophore modeling was developed based on the co-crystallized structure of the enzyme with its biological active inhibitor. The generated hypotheses were applied for virtual screening based PhaseScore. Docking based virtual screening workflow was used to generate hit compounds using HTVS, SP and XP based Glide GScore. The pharmacological and physicochemical properties of the selected lead compounds were characterized using ADMET. Molecular dynamics simulations were performed to explore the binding affinities of the considered lead compounds. Binding energies revealed that compound ABBV-744 binds to the Mpro with strong affinity (ΔGbind -45.43 kcal/mol), and the complex is more stable in comparison with other protein-ligand complexes. Our study classified three best compounds which could be considered as promising inhibitors against main protease SARS-CoV-2 virus.

Anthocyanin derivatives as potent inhibitors of SARS-CoV-2 main protease: An in-silico perspective of therapeutic targets against COVID-19 pandemic.

A new pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide and become pandemic with thousands new deaths and infected cases globally. To treat the patients with coronavirus disease (COVID-19), currently no effective drug or vaccine is available. This necessity motivated us to explore potential lead compounds based natural products targeting main protease (Mpro) enzyme of SARS-CoV-2. The Mpro enzyme plays a key role in mediating viral replication and transcription and thus being considered as an attractive drug target. Herein, comprehensive computational investigations were performed to identify new lead compounds against main protease enzyme. In this study, the candidate anthocyanin-derived compounds from PubChem database were filtered considering antiviral characteristics of anthocyanins. The structure-based pharmacophore modeling was developed based on the co-crystallized structure of the enzyme with its biological active inhibitor. The generated hypotheses were applied for virtual screening-based PHASE Screen Score. Docking based virtual screening work flow was used to generate hit compounds using HTVS, SP and XP based Glide Gscore. The obtained hit compounds were filtered using ADMET pharmacological and physicochemical properties screening. Molecular dynamics simulations were performed to explore the binding affinities of the considered compounds. Our study identified six best anthocyanin-derived natural compounds which could be used as promising lead compounds against main protease SARS-CoV-2 virus.

Identification of Potential Inhibitors of Calcium/Calmodulin-Dependent Protein Kinase IV from Bioactive Phytoconstituents.

Calcium/calmodulin-dependent protein kinase IV (CaMKIV) is an upstream regulator of CaMKK-CaMKIV signaling cascade that activates various transcription factors, thereby regulating several cellular activities including, neuronal communication and immune response. Owing to the abnormal expression in cancer and neurodegenerative diseases, the CaMKIV has been considered a potential drug target. In the present study, we checked the binding affinity of plant-derived natural compounds viz., quercetin, ellagic acid (EA), simvastatin, capsaicin, ursolic acid, DL-α-tocopherol acetate, and limonin towards CaMKIV. Molecular docking and fluorescence binding studies showed that EA and quercetin bind to the CaMKIV with a considerable affinity in comparison to other compounds. Enzyme inhibition assay revealed that both EA and quercetin inhibit CaMKIV activity with their IC50 values in the micromolar range. To get atomistic insights into the mode of interactions, inhibition mechanism, and the stability of the CaMKIV-ligand complex, a 100 ns MD simulation analysis was performed. Both EA and quercetin bind to the catalytically important residues of active site pocket of CaMKIV forming enough stabilizing interactions presumably inhibiting enzyme activity. Moreover, no significant structural change in the CaMKIV was observed upon binding of EA and quercetin. In conclusion, this study illustrates the application of phytoconstituents in the development of therapeutic molecules targeting CaMKIV having implications in cancer and neurodegenerative diseases after in vivo validation.

Molecular insight on the non-covalent interactions between carbapenems and L,D-transpeptidase 2 from Mycobacterium tuberculosis: ONIOM study.

Tuberculosis remains a dreadful disease that has claimed many human lives worldwide and elimination of the causative agent Mycobacterium tuberculosis also remains elusive. Multidrug-resistant TB is rapidly increasing worldwide; therefore, there is an urgent need for improving the current antibiotics and novel drug targets to successfully curb the TB burden. L,D-Transpeptidase 2 is an essential protein in Mtb that is responsible for virulence and growth during the chronic stage of the disease. Both D,D- and L,D-transpeptidases are inhibited concurrently to eradicate the bacterium. It was recently discovered that classic penicillins only inhibit D,D-transpeptidases, while L,D-transpeptidases are blocked by carbapenems. This has contributed to drug resistance and persistence of tuberculosis. Herein, a hybrid two-layered ONIOM (B3LYP/6-31G+(d): AMBER) model was used to extensively investigate the binding interactions of LdtMt2 complexed with four carbapenems (biapenem, imipenem, meropenem, and tebipenem) to ascertain molecular insight of the drug-enzyme complexation event. In the studied complexes, the carbapenems together with catalytic triad active site residues of LdtMt2 (His187, Ser188 and Cys205) were treated at with QM [B3LYP/6-31+G(d)], while the remaining part of the complexes were treated at MM level (AMBER force field). The resulting Gibbs free energy (ΔG), enthalpy (ΔH) and entropy (ΔS) for all complexes showed that the carbapenems exhibit reasonable binding interactions towards LdtMt2. Increasing the number of amino acid residues that form hydrogen bond interactions in the QM layer showed significant impact in binding interaction energy differences and the stabilities of the carbapenems inside the active pocket of LdtMt2. The theoretical binding free energies obtained in this study reflect the same trend of the experimental  observations. The electrostatic, hydrogen bonding and Van der Waals interactions between the carbapenems and LdtMt2 were also assessed. To further examine the nature of intermolecular interactions for carbapenem-LdtMt2 complexes, AIM and NBO analysis were performed for the QM region (carbapenems and the active residues of LdtMt2) of the complexes. These analyses revealed that the hydrogen bond interactions and charge transfer from the bonding to anti-bonding orbitals between catalytic residues of the enzyme and selected ligands enhances the binding and stability of carbapenem-LdtMt2 complexes. The two-layered ONIOM (B3LYP/6-31+G(d): Amber) model was used to evaluate the efficacy of FDA approved carbapenems antibiotics towards LdtMt2.

Differential flap dynamics in l,d-transpeptidase2 from mycobacterium tuberculosis revealed by molecular dynamics.

Despite the advances in tuberculosis treatment, TB is still one the most deadly infectious diseases and remains a major global health quandary. Mycobacterium tuberculosis (Mtb) is the only known mycobacterium with a high content of 3→3 crosslinks in the biosynthesis of peptidoglycan, which is negligible in most bacterial species. An Mtb lacking LdtMt2 leads to alteration of the colony morphology and loss of virulence which makes this enzyme an attractive target. Regardless of the vital role of LdtMt2 for cell wall survival, the impact of ligand binding on the dynamics of the ß-hairpin flap is still unknown. Understanding the structural and dynamical behaviour of the flap regions provides clear insight into the design of the effective inhibitors against LdtMt2. Carbapenems, an specific class of ß-lactam family, have been shown to inactivate this enzyme. Herein a comprehensive investigation of the flap dynamics of LdtMt2 complex with substrate and three carbapenems namely, ertapenem, imipenem and meropenem is discussed and analyzed for the first account using 140 ns molecular dynamics simulations. The structural features (RMSD, RMSF and Rg) derived by MD trajectories were analyzed. Distance analysis, particularly tip-tip SER135-ASN167 index, identified conformational changes in terms of flap opening and closure within binding process. Principal component analysis (PCA) was employed to qualitatively understand the divergent effects of different inhibitors on the dominant motion of each residue. To probe different internal dynamics induced by ligand binding, dynamic cross-correlation marix (DCCM) analysis was used. The binding free energies of the selected complexes were assessed using MM-GBSA method and per residue free energy decomposition analysis were performed to characterize the contribution of the key residues to the total binding free energies.

A comparative modeling and molecular docking study on Mycobacterium tuberculosis targets involved in peptidoglycan biosynthesis.

An alarming rise of multidrug-resistant Mycobacterium tuberculosis strains and the continuous high global morbidity of tuberculosis have reinvigorated the need to identify novel targets to combat the disease. The enzymes that catalyze the biosynthesis of peptidoglycan in M. tuberculosis are essential and noteworthy therapeutic targets. In this study, the biochemical function and homology modeling of MurI, MurG, MraY, DapE, DapA, Alr, and Ddl enzymes of the CDC1551 M. tuberculosis strain involved in the biosynthesis of peptidoglycan cell wall are reported. Generation of the 3D structures was achieved with Modeller 9.13. To assess the structural quality of the obtained homology modeled targets, the models were validated using PROCHECK, PDBsum, QMEAN, and ERRAT scores. Molecular dynamics simulations were performed to calculate root mean square deviation (RMSD) and radius of gyration (Rg) of MurI and MurG target proteins and their corresponding templates. For further model validation, RMSD and Rg for selected targets/templates were investigated to compare the close proximity of their dynamic behavior in terms of protein stability and average distances. To identify the potential binding mode required for molecular docking, binding site information of all modeled targets was obtained using two prediction algorithms. A docking study was performed for MurI to determine the potential mode of interaction between the inhibitor and the active site residues. This study presents the first accounts of the 3D structural information for the selected M. tuberculosis targets involved in peptidoglycan biosynthesis.