QSAR, molecular docking and ADMET properties in silico studies of novel 4,5,6,7-tetrahydrobenzo[D]-thiazol-2-Yl derivatives derived from dimedone as potent anti-tumor agents through inhibition of C-Met receptor tyrosine kinase

Investigating the potent TOPO IIα inhibitors in breast cancer through the study of computational drug discovery research approaches

Breast cancer (BC) is the second-leading cause of cancer after lung cancer. The disease has affected millions of people and resulted in many deaths. In the metastasis of breast cancer cells, Topoisomerase IIα plays a vital role. Therefore, this investigation aims to identify potential flavonoid compounds against BC by inhibiting this enzyme at an early stage. Based on previous studies, we selected and screened several plant-derived flavonoid compounds with potential anti-breast cancer activity using PyRx 0.8 and Schrodinger applications for preliminary molecular docking: the highest docking scores of Myricetin (-11.6 kcal/mol) and Quercetin (-10.0 kcal/mol). Next, we evaluated the top four compounds on the Way2Drug server to complete the cytotoxicity evaluation, which demonstrated anti-cancer and anti-breast cancer activity in various cell lines. According to pharmacokinetics studies, four compounds exhibited outstanding values and functioned similar to drug-like molecules. Moreover, Myricetin, Quercetin, and Morin displayed the highest number of hydrogen bonds, with the corresponding receptor forming residues asn120, thr147, and lys168. The protein-ligand complexes were validated using the Desmond simulator, and their data were compared to the anti-breast cancer drug Doxorubicin. In the simulation analysis, various parameters were evaluated, including RMSD, RMSF, Rg, SASA, MolSA, PSA, and hydrogen bond interaction. Finally, validated our dynamic simulation result with MM-GBSA operation, and Myricetin and Quercetin had the greatest score of -72.74344651, -66.66771823 kcal/mol, which is outstanding than the control drug. Hence, the computational research approach determined that Myricetin, Quercetin, and Morin could be industrially developed for the alternative treatment of breast cancer following additional confirmation from animal and cell line studies.

Arnicolide D: a multi-targeted anticancer sesquiterpene lactone-preclinical efficacy and mechanistic insights

Arnicolide D, a potent sesquiterpene lactone from Centipeda minima, has emerged as a promising anticancer candidate, demonstrating significant efficacy in inhibiting cancer cell proliferation, inducing apoptosis, and suppressing metastasis across various cancer models. This comprehensive study delves into the molecular underpinnings of Arnicolide D's anticancer actions, emphasizing its impact on key signaling pathways such as PI3K/AKT/mTOR and STAT3, and its role in modulating cell cycle and survival mechanisms. Quantitative data from preclinical studies reveal Arnicolide D's dose-dependent cytotoxicity against cancer cell lines, including nasopharyngeal carcinoma, triple-negative breast cancer, and human colon carcinoma, showcasing its broad-spectrum anticancer potential. Given its multifaceted mechanisms and preclinical efficacy, Arnicolide D warrants further investigation in clinical settings to validate its therapeutic utility against cancer. The evidence presented underscores the need for rigorous pharmacokinetic and toxicological studies to establish safe dosing parameters for future clinical trials.

Design of new molecules against cervical cancer using DFT, theoretical spectroscopy, 2D/3D-QSAR, molecular docking, pharmacophore and ADMET investigations

Cervical cancer is a major health problem of women. Hormone therapy, via aromatase inhibition, has been proposed as a promising way of blocking estrogen production as well as treating the progression of estrogen-dependent cancer. To overcome the challenging complexities of costly drug design, in-silico strategy, integrating Structure-Based Drug Design (SBDD) and Ligand-Based Drug Design (LBDD), was applied to large representative databases of 39 quinazoline and thioquinazolinone compound derivatives. Quantum chemical and physicochemical descriptors have been investigated using density functional theory (DFT) and MM2 force fields, respectively, to develop 2D-QSAR models, while CoMSIA and CoMFA descriptors were used to build 3D-QSAR models. The robustness and predictive power of the reliable models were verified, via several validation methods, leading to the design of 6 new drug-candidates. Afterwards, 2 ligands were carefully selected using virtual screening methods, taking into account the applicability domain, synthetic accessibility, and Lipinski's criteria. Molecular docking and pharmacophore modelling studies were performed to examine potential interactions with aromatase (PDB ID: 3EQM). Finally, the ADMET properties were investigated in order to select potential drug-candidates against cervical cancer for experimental in vitro and in vivo testing.

Chemo-informatics applications in the design of novel 7-keto-sempervirol derivatives as SmCB1 inhibitors with potential for treatment of Schistosomiasis

The quest for a sound treatment on the vulnerable population suffering and dying as a result of the blood flukes, S. mansoni is on the increase because both Praziquantel and Oxamniquine widely used for the treatment of Schistosomiasis for over 51 years suffer resistance and recurrence. Here-in, chemo-informatics techniques such as QSAR modeling, pharmacokinetic, docking alongside MD simulation were harnessed in designing novel 7-keto- sempevirolsempevirol derivatives that are more competent against S. mansoni. Upon QSAR screening, compound 15, which appears to be in the model's acceptability space, emerges the best with a high predicted activity. 5 new analogues with improved activity against Schistosomiasis better than the standard drug PZQ were designed from compound 15 (template 15*) on an account of the descriptors significance from the model with robust and validated parameters. Also their pharmacokinetic profiles indicates that the designed compounds have the characteristics of a good drug. Furthermore, docking evaluation fulfilled ranges from -113.121 to -100.79 kcal/mol (moldock score), with compound U1 being the best (least moldock score of -113.121 compared to PZQ and 15* (template) having a moldock score value of (-87.21 and -83.37 kcal/mol). 100-ns MD Simulation on the U1-docked complex was run using Desmond 2019-4 package. The nature and steadiness of U1 compound within the enzyme active site was further confirmed by RMSD, RMSF, RoG and H-bond assessment. Hence, we recommend compound U1 targeting the SmCB1 enzyme (6YI7) for Schistosomiasis treatment and for further medicinal evaluation and utilization.

In silico Screening of Food and Drug Administration-approved Compounds against Trehalose 2-sulfotransferase (Rv0295c) in Mycobacterium tuberculosis: Insights from Molecular Docking and Dynamics Simulations

BACKGROUND

Tuberculosis (TB) remains a prominent global health challenge, distinguished by substantial occurrences of infection and death. The upsurge of drug-resistant TB strains underscores the urgency to identify novel therapeutic targets and repurpose existing compounds. Rv0295c is a potentially druggable enzyme involved in cell wall biosynthesis and virulence. We evaluated the inhibitory activity of Food and Drug Administration (FDA)-approved compounds against Rv0295c of Mycobacterium tuberculosis, employing molecular docking, ADME evaluation, and dynamics simulations.

METHODS

The study screened 1800 FDA-approved compounds and selected the top five compounds with the highest docking scores. Following this, we subjected the initially screened ligands to ADME analysis based on their dock scores. In addition, the compound exhibited the highest binding affinity chosen for molecular dynamics (MD) simulation to investigate the dynamic behavior of the ligand-receptor complex.

RESULTS

Dihydroergotamine (CHEMBL1732) exhibited the highest binding affinity (-12.8 kcal/mol) for Rv0295c within this set of compounds. We evaluated the stability and binding modes of the complex over extended simulation trajectories.

CONCLUSION

Our in silico analysis demonstrates that FDA-approved drugs can serve as potential Rv0295c inhibitors through repurposing. The combination of molecular docking and MD simulation offers a comprehensive understanding of the interactions between ligands and the protein target, providing valuable guidance for further experimental validation. Identifying Rv0295c inhibitors may contribute to new anti-TB drugs.

3D-QSAR and ADMET studies of morpholino-pyrimidine inhibitors of DprE1 from Mycobacterium tuberculosis

DprE1 is involved in the synthesis of Mycobacterium tuberculosis cell wall and is a potent drug target for Tuberculosis (TB) treatment. The structure and dynamics of the loops L-I and L-II flanking the inhibitor binding site was studied using molecular dynamics (MD) simulation and MMPBSA in Amber v18. Docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) of 55 Morpholino-pyrimidine (MP) inhibitors was carried out using Autodock v1.2.0 and Forge v10. ADMET analysis was done using SwissADME and pkCSM. All MP inhibitors docked in the DprE1 binding pocket, making contacts with L-II residues. MD studies showed that L-I and L-II unfold in the absence of the inhibitor but fold stably structure with reduced protein motions in the presence of MP-38, the highest affinity inhibitor. This was confirmed by k-means clustering and secondary structure analysis. L-II residues, L317, F320 and R325 contributed most towards the MMPBSA binding free energy of MP-38. A robust field-based 3D-QSAR model showed values of r2train = 0.982, r2test = 0.702 and q2 = 0.516. The MP inhibitor field points were broadly divided into negative electrostatics near the A, B rings and hydrophobic electrostatics near the D, E rings. Addition of negative groups at methanone position and ring B as well as addition of hydrophobic and bulky groups at ring E will improve activity. Highly active compounds 47, 49 and 50 of MP series exhibited highly favourable drug-like properties. SAR and ADMET insights attained from this model will help in the development of active DprE1 inhibitors in future.Communicated by Ramaswamy H. Sarma.

Dimedone nanoparticle as a promising approach against toxoplasmosis: In vitro and in vivo evaluation

Toxoplasma gondii, an intracellular parasite, has shown drug resistance and therapeutic failure in recent years. Dimedone (DIM) has been introduced as a new chemical compound with anti-bacterial and anti-cancer properties. The aim of this study was to investigate the potential protective role of DIM nanoparticles in an animal model of toxoplasmosis. Cytotoxicity of DIM on Vero cell line assessed using MTT, and the effect of DIM on Toxoplasma gondii was evaluated by counting the number of parasites compared to the control group in vitro. The rate of pathogenesis and virulence of the parasite was checked on the liver cells of the animal model using hematoxylin-eosin staining. Furthermore, various parameters indicating oxidative stress were compared in mouse liver tissue in different groups. The release of the nanoparticle form was significantly longer than the free drugs. The IC50 of Nano-DIM was 60 µM and the reduction of intracellular parasite proliferation in the group Nano-DIM and Nano-PYR (Nano-primethamine) was significantly lower than the free drugs in vitro. Histopathology examination in the groups treated with dimedone nanomedicine showed that the degree of disintegration of the epithelium of the central vein of the liver and infiltration and vacuolization of liver cells were lower compared to the toxoplasmosis group. Additionally, the level of some oxidative stress indicators was observed to be lower in the nano-treated groups compared to other groups. The results of this study showed DIM can be used as a promising compound for anti-T. gondii activity and can prevent the proliferation of it in cells.

In-vitro antibacterial, antioxidant and anti-inflammatory and In-silico ADMET, molecular docking study on Hardwickia binata phytocompunds with potential inhibitor of skin cancer protein

The new sources of antimicrobial and antioxidant agents for methanol extracts of Hardwickia binata Roxb were evaluated systematically. The present investigation is antibacterial, antioxidant, ADMET and molecular docking studies. Our results show the good polyphenol content (total phenol, total flavonoid) and antioxidant capacity of methanol extracts. The free radical scavenging activities of the methanol extracts also were highest, with the antioxidant activity becoming significantly greater. Furthermore, in-vitro antibacterial experiments against phytopathogens, Enterococcus faecalis have a high zone of inhibition (14 ± 0.54) compared with other pathogens. The functional groups of methanol extract were identified using FTIR. The active molecules from GCMS involved in ADMET and docking study for skin cancer proteins (1P7K and 5OTE) among the phytocompounds, Hexadecanoic acid, methyl ester (- 6.2; - 6.6 kcal/mol) and 5-Phenyl-2,4-pyrimidinediamine, 2TMS derivative (- 7.50; - 8.11 kcal/mol) is the best compound for the human skin cancer possessed higher binding energy. Our results indicate that the plants can provide sources of natural compounds used for moderate good anticancer drug.

The Synergistic Influence of Polyflavonoids from Citrus aurantifolia on Diabetes Treatment and Their Modulation of the PI3K/AKT/FOXO1 Signaling Pathways: Molecular Docking Analyses and In Vivo Investigations

This study was aimed at probing the modulatory influence of polyflavonoids extracted from Citrus aurantifolia, lemon peel extract (LPE-polyflavonoids), on attenuating diabetes mellitus (DM) and its complications. HPLC investigations of the LPE exhibited the incidence of five flavonoids, including diosmin, biochanin A, hesperidin, quercetin, and hesperetin. The in silico impact on ligand-phosphatidylinositol 3-kinase (PI3K) interaction was investigated in terms of polyflavonoid class to explore the non-covalent intakes and binding affinity to the known protein active site. The drug likeness properties and pharmacokinetic parameters of the LPE-polyflavonoids were investigated to assess their bioavailability in relation to Myricetin as a control. Remarkably, the molecular docking studies demonstrated a prominent affinity score of all these agents together with PI3K, implying the potency of the extract to orchestrate PI3K, which is the predominant signal for lessening the level of blood glucose. To verify these findings, in vivo studies were conducted, utilizing diabetic male albino rats treated with LPE-polyflavonoids and other groups treated with hesperidin and diosmin as single flavonoids. Our findings demonstrated that the LPE-polyflavonoids significantly ameliorated the levels of glucose, insulin, glycogen, liver function, carbohydrate metabolizing enzymes, G6Pd, and AGEs compared to the diabetic rats and those exposed to hesperidin and diosmin. Furthermore, the LPE-polyflavonoids regulated the TBARS, GSH, CAT, TNF-α, IL-1β, IL-6, and AFP levels in the pancreatic and hepatic tissues, suggesting their antioxidant and anti-inflammatory properties. In addition, the pancreatic and hepatic GLUT4 and GLUT2 were noticeably increased in addition to the pancreatic p-AKT in the rats administered with the LPE-polyflavonoids compared to the other diabetic rats. Remarkably, the administration of LPE-polyflavonoids upregulated the expression of the pancreatic and hepatic PI3K, AMPK, and FOXO1 genes, emphasizing the efficiency of the LPE in orchestrating all the signaling pathways necessitated to reduce the diabetes mellitus. Notably, the histopathological examinations of the pancreatic and hepatic tissues corroborated the biochemical results. Altogether, our findings accentuated the potential therapeutic role of LPE-polyflavonoids in controlling diabetes mellitus.

The anti-SARS-CoV-2 activity of novel 9, 10-dihydrophenanthrene derivatives: an insight into molecular docking, ADMET analysis, and molecular dynamics simulation

Originating in Wuhan, the COVID-19 pandemic wave has had a profound impact on the global healthcare system. In this study, we used a 2D QSAR technique, ADMET analysis, molecular docking, and dynamic simulations to sort and evaluate the performance of thirty-nine bioactive analogues of 9,10-dihydrophenanthrene. The primary goal of the study is to use computational approaches to create a greater variety of structural references for the creation of more potent SARS-CoV-2 3Clpro inhibitors. This strategy is to speed up the process of finding active chemicals. Molecular descriptors were calculated using 'PaDEL' and 'ChemDes' software, and then redundant and non-significant descriptors were eliminated by a module in 'QSARINS ver. 2.2.2'. Subsequently, two statistically robust QSAR models were developed by applying multiple linear regression (MLR) methods. The correlation coefficients obtained by the two models are 0.89 and 0.82, respectively. These models were then subjected to internal and external validation tests, Y-randomization, and applicability domain analysis. The best model developed is applied to designate new molecules with good inhibitory activity values against severe acute respiratory syndrome coronavirus 2 (SARS CoV-2). We also examined various pharmacokinetic properties using ADMET analysis. Then, through molecular docking simulations, we used the crystal structure of the main protease of SARS-CoV-2 (3CLpro/Mpro) in a complex with the covalent inhibitor "Narlaprevir" (PDB ID: 7JYC). We also supported our molecular docking predictions with an extended molecular dynamics simulation of a docked ligand-protein complex. We hope that the results obtained in this study can be used as good anti-SARS-CoV-2 inhibitors.

A computer-aided drug design approach to explore novel type II inhibitors of c-Met receptor tyrosine kinase for cancer therapy: QSAR, molecular docking, ADMET and molecular dynamics simulations

Small molecules such as 4-phenoxypyridine derivatives have remarkable inhibitory activity against c-Met enzymatic activity and proliferation of cancer cell lines. Since there is a relationship between structure and biological activity of these molecules, these little compounds may have great potential for clinical pharmaceutical use against various types of cancer caused by c-Met activity. The purpose of this study was to remodel the structures of 4-phenoxypyridine derivatives to achieve strong inhibitory activity against c-Met and provide favorable pharmacokinetic properties for drug design and discovery. Therefore, this paper describes the structure-activity relationship and the rationalization of appropriate pharmacophore sites to improve the biological activity of the investigated molecules, based on bioinformatics techniques represented by a computer-aided drug design approach. Accordingly, robust and reliable 3D-QSAR models were developed based on CoMFA and CoMSIA techniques. As a result, 46 lead molecules were designed and their biological and pharmacokinetic activities were predicted in silico. Screening filters by 3D-QSAR, Molecular Docking, drug-like and ADME-Tox identified the computer-designed compounds P54 and P55 as the best candidates to achieve high inhibition of c-Met enzymatic activity compared to the synthesized template compound T14. Finally, through molecular dynamics simulations, the structural properties and dynamics of c-Met free and complex (PDB code: 3LQ8) in the presence of 4-phenoxypyridine-derived compounds in an aqueous environment are discussed. Overall, the rectosynthesis of the designed drug inhibitors (P54 and P55) and their in vitro and in vivo bioactivity evaluation may be attractive for design and discovery of novel drug effective to inhibit c-Met enzymatic activity.Communicated by Ramaswamy H. Sarma.

Artificial Intelligence in Pharmaceutical Technology and Drug Delivery Design

Artificial intelligence (AI) has emerged as a powerful tool that harnesses anthropomorphic knowledge and provides expedited solutions to complex challenges. Remarkable advancements in AI technology and machine learning present a transformative opportunity in the drug discovery, formulation, and testing of pharmaceutical dosage forms. By utilizing AI algorithms that analyze extensive biological data, including genomics and proteomics, researchers can identify disease-associated targets and predict their interactions with potential drug candidates. This enables a more efficient and targeted approach to drug discovery, thereby increasing the likelihood of successful drug approvals. Furthermore, AI can contribute to reducing development costs by optimizing research and development processes. Machine learning algorithms assist in experimental design and can predict the pharmacokinetics and toxicity of drug candidates. This capability enables the prioritization and optimization of lead compounds, reducing the need for extensive and costly animal testing. Personalized medicine approaches can be facilitated through AI algorithms that analyze real-world patient data, leading to more effective treatment outcomes and improved patient adherence. This comprehensive review explores the wide-ranging applications of AI in drug discovery, drug delivery dosage form designs, process optimization, testing, and pharmacokinetics/pharmacodynamics (PK/PD) studies. This review provides an overview of various AI-based approaches utilized in pharmaceutical technology, highlighting their benefits and drawbacks. Nevertheless, the continued investment in and exploration of AI in the pharmaceutical industry offer exciting prospects for enhancing drug development processes and patient care.

Cellular and Non-cellular Antioxidant Properties of Vitamin E-Loaded Metallic-Quercetin/Polycaprolactone Nanoparticles for the Treatment of Melanogenesis

Inhibition of melanogenesis by quercetin and vitamin E is extensively reported in the literature, independently, with limitations in antioxidant potential owing to less permeation, solubility, decreased bioavailability, and reduced stability. Thus, the aim of the present study was to synthesize a novel complex of metal ions (copper and zinc) with quercetin to enhance antioxidant properties which were confirmed by docking studies. Polycaprolactone-based nanoparticles of the synthesized complex (PCL-NPs, Q-PCL-NPs, Zn-Q-PCL-NPs, Cu-Q-PCL-NPs) were made later loaded with vitamin E which made the study more interesting in enhancing antioxidant profile. Nanoparticles were characterized for zeta size, charge, and polydispersity index, while physiochemical analysis of nanoparticles was strengthened by FTIR. Cu-Q-PCL-NPs-E showed maximum in vitro release of vitamin E, i.e., 80 ± 0.54%. Non-cellular antioxidant effect by 2,2-diphenyl-1-picrylhydrazyl was observed at 93 ± 0.23% in Cu-Q-PCL-NPs-E which was twofold as compared to Zn-Q-PCL-NPs-E. Michigan Cancer Foundation-7 (MCF-7) cancer cell lines were used to investigate the anticancer and cellular antioxidant profile of loaded and unloaded nanoparticles. Results revealed reactive oxygen species activity of 90 ± 0.32% with the addition of 89 ± 0.64% of its anticancer behavior shown by Cu-Q-PCL-NPs-E after 6 and 24h. Similarly, 80 ± 0.53% inhibition of melanocyte cells and 95 ± 0.54% increase of keratinocyte cells were also shown by Cu-Q-PCL-NPs-E that confirmed the tyrosinase enzyme inhibitory effect. Conclusively, the use of zinc and copper complex in unloaded and vitamin E-loaded nanoparticles can provide enhanced antioxidant properties with inhibition of melanin, which can be used for treating diseases of melanogenesis.

Roxadustat and its failure: A comparative dynamic study

Roxadustat, a small-molecule inhibitor of hypoxia-inducible factor prolyl hydroxylase domain 2 (HIF-PHD2) has been recently overruled by the American Food and Drug Administration (FDA) in Phase 3 clinical trials. This study provides insights into the dynamics of Roxadustat with PHD2 and proposes two FDA-approved drugs; Pemetrexed and Valrubicin to treat chronic kidney disease (CKD). Role of chemical scaffolds such as synthetic pyrimidine-based antifolate is found critical for PHD2 inhibitory activity, which is concurrent with the experimental findings for stimulating Endogenous erythropoietin (EPO) gene expression. Furthermore, Fe⁺² and Mn⁺² in solution are essential for imparting structural stability to the screened carboxylic and non-carboxylic acid drugs. Comparative analysis of FDA-approved drugs namely, Roxadustat, two-hit carboxylic, and non-carboxylic-acid type compounds (Pemetrexed and Valrubicin), as well as the control ligands (KU1 and 4JR), unveil structural dynamics of Roxadustat and its failure. However, the proposed FDA compounds, Pemetrexed and Valrubicin, used to treat mesothelioma, non-small cell lung cancer, and bladder cancer should be subjected to in vitro analysis for renal anemia.

QSAR and molecular docking studies of isatin and indole derivatives as SARS 3CLpro inhibitors

The 3C-like protease (3CL^pro), known as the main protease of SARS-COV, plays a vital role in the viral replication cycle and is a critical target for the development of SARS inhibitor. Comparative sequence analysis has shown that the 3CL^pro of two coronaviruses, SARS-CoV-2 and SARS-CoV, show high structural similarity, and several common features are shared among the substrates of 3CL^pro in different coronaviruses. The goal of this study is the development of validated QSAR models by CORAL software and Monte Carlo optimization to predict the inhibitory activity of 81 isatin and indole-based compounds against SARS CoV 3CL^pro. The models were built using a newer objective function optimization of this software, known as the index of ideality correlation (IIC), which provides favorable results. The entire set of molecules was randomly divided into four sets including: active training, passive training, calibration and validation sets. The optimal descriptors were selected from the hybrid model by combining SMILES and hydrogen suppressed graph (HSG) based on the objective function. According to the model interpretation results, eight synthesized compounds were extracted and introduced from the ChEMBL database as good SARS CoV 3CL^pro inhibitor. Also, the activity of the introduced molecules further was supported by docking studies using 3CL^pro of both SARS-COV-1 and SARS-COV-2. Based on the results of ADMET and OPE study, compounds CHEMBL4458417 and CHEMBL4565907 both containing an indole scaffold with the positive values of drug-likeness and the highest drug-score can be introduced as selected leads.

Discovery of 3CLpro inhibitor of SARS-CoV-2 main protease

Coronavirus main protease (3CLpro), a special cysteine protease in coronavirus family, is highly desirable in the life cycle of coronavirus. Here, molecular docking, ADMET pharmacokinetic profiles and molecular dynamics (MD) simulation were performed to develop specific 3CLpro inhibitor. The results showed that the 137 compounds originated from Chinese herbal have good binding affinity to 3CLpro. Among these, Cleomiscosin C, (+)-Norchelidonine, Protopine, Turkiyenine, Isochelidonine and Mallotucin A possessed prominent drug-likeness properties. Cleomiscosin C and Turkiyenine exhibited excellent pharmacokinetic profiles. Furthermore, the complex of Cleomiscosin C with SARS-CoV-2 main protease presented high stability. The findings in this work indicated that Cleomiscosin C is highly promising as a potential 3CLpro inhibitor, thus facilitating the development of effective drugs for COVID-19.

Identifying non-nucleoside inhibitors of RNA-dependent RNA-polymerase of SARS-CoV-2 through per-residue energy decomposition-based pharmacophore modeling, molecular docking, and molecular dynamics simulation

BACKGROUND AND OBJECTIVE

The current coronavirus disease-2019 (COVID-19) pandemic has triggered a worldwide health and economic crisis. The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes the disease and completes its life cycle using the RNA-dependent RNA-polymerase (RdRp) enzyme, a prominent target for antivirals. In this study, we have computationally screened ∼690 million compounds from the ZINC20 database and 11,698 small molecule inhibitors from DrugBank to find existing and novel non-nucleoside inhibitors for SARS-CoV-2 RdRp.

METHODS

Herein, a combination of the structure-based pharmacophore modeling and hybrid virtual screening methods, including per-residue energy decomposition-based pharmacophore screening, molecular docking, pharmacokinetics, and toxicity evaluation were employed to retrieve novel as well as existing RdRp non-nucleoside inhibitors from large chemical databases. Besides, molecular dynamics simulation and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) method were used to investigate the binding stability and calculate the binding free energy of RdRp-inhibitor complexes.

RESULTS

Based on docking scores and significant binding interactions with crucial residues (Lys553, Arg557, Lys623, Cys815, and Ser816) in the RNA binding site of RdRp, three existing drugs, ZINC285540154, ZINC98208626, ZINC28467879, and five compounds from ZINC20 (ZINC739681614, ZINC1166211307, ZINC611516532, ZINC1602963057, and ZINC1398350200) were selected, and the conformational stability of RdRp due to their binding was confirmed through molecular dynamics simulation. The free energy calculations revealed these compounds possess strong binding affinities for RdRp. In addition, these novel inhibitors exhibited drug-like features, good absorption, distribution, metabolism, and excretion profile and were found to be non-toxic.

CONCLUSION

The compounds identified in the study by multifold computational strategy can be validated in vitro as potential non-nucleoside inhibitors of SARS-CoV-2 RdRp and holds promise for the discovery of novel drugs against COVID-19 in future.

Study of the competition between Pi and Cr (VI) for the use of Pi-transporter at Vicia faba L. using molecular modeling

Recent studies have shown that Cr uses other element transporters such as phosphate transporters to enter cells. The aim of this work is to explore the interaction between dichromate and inorganic phosphate (Pi) in the plant of Vicia faba L. To study this interaction, we used three concentrations of Dipotassium hydrogen phosphate (K₂HPO₄) 10 mM (Pi10), 50 mM (Pi50) and 100 mM (Pi100) added alone or in combination with potassium dichromate (K₂Cr₂O₇) Cr + Pi10, Cr + Pi50 and Cr + Pi100. In order to investigate the impact of this interaction on morpho-physiological parameters, the biomass, chlorophyll content, proline level, H₂O₂ level, Catalase and Ascorbate peroxidase activity and Cr-bioaccumulation has been determined. For the molecular scale, the theoretical chemistry was used via molecular docking to explore the various interactions between dichromate Cr₂O₇^2-/HPO₄^2-/H₂O₄P^- and the phosphate-transporter. We have selected the eukaryotic phosphate transporter (PDB: 7SP5) as the module. The results showed that K₂Cr₂O₇ negatively affects morpho-physiological parameters and generates oxidative damage (+84% H₂O₂ than the control), which involved the production of antioxidant enzymes (+147% Catalase and +176% Ascorbate-peroxidase) and Proline (+108%). The addition of Pi improved the growth of Vicia faba L. and induces the partial restoration of the parameters affected by Cr (VI) to the normal levels. Also, it decreased oxidative damage and reduce Cr (VI) bioaccumulation in shoots and roots. Molecular docking has shown that the dichromate structure is more compatible and establishes more bonds with the Pi-transporter which generates a very stable complex compared to HPO₄^2-/H₂O₄P^-. Overall, these results confirmed that there is a strong relationship between dichromate uptake and the Pi-transporter.

Cyclohexane-1,3-dione Derivatives as Future Therapeutic Agents for NSCLC: QSAR Modeling, In Silico ADME-Tox Properties, and Structure-Based Drug Designing Approach

The abnormal expression of the c-Met tyrosine kinase has been linked to the proliferation of several human cancer cell lines, including non-small-cell lung cancer (NSCLC). In this context, the identification of new c-Met inhibitors based on heterocyclic small molecules could pave the way for the development of a new cancer therapeutic pathway. Using multiple linear regression (MLR)-quantitative structure-activity relationship (QSAR) and artificial neural network (ANN)-QSAR modeling techniques, we look at the quantitative relationship between the biological inhibitory activity of 40 small molecules derived from cyclohexane-1,3-dione and their topological, physicochemical, and electronic properties against NSCLC cells. In this regard, screening methods based on QSAR modeling with density-functional theory (DFT) computations, in silico pharmacokinetic/pharmacodynamic (ADME-Tox) modeling, and molecular docking with molecular electrostatic potential (MEP) and molecular mechanics-generalized Born surface area (MM-GBSA) computations were used. Using physicochemical (stretch-bend, hydrogen bond acceptor, Connolly molecular area, polar surface area, total connectivity) and electronic (total energy, highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy levels) molecular descriptors, compound 6d is identified as the optimal scaffold for drug design based on in silico screening tests. The computer-aided modeling developed in this study allowed us to design, optimize, and screen a new class of 36 small molecules based on cyclohexane-1,3-dione as potential c-Met inhibitors against NSCLC cell growth. The in silico rational drug design approach used in this study led to the identification of nine lead compounds for NSCLC therapy via c-Met protein targeting. Finally, the findings are validated using a 100 ns series of molecular dynamics simulations in an aqueous environment on c-Met free and complexed with samples of the proposed lead compounds and Foretinib drug.

Synthesize palladium nanoparticles from the macroalgae Sargassum fusiforme: An eco-friendly tool in the fight against Plasmodium falciparum?

Although numerous drugs are practiced to control malaria and its vectors, more recently, eco-friendly control tools have been proposed to battle its etiologic agents. Thus, using green bionanotechnology approaches, we aimed to synthesize palladium nanoparticles (Pd NPs) from the macroalgae Sargassum fusiforme (Sf), its potential antiparasitic activity against P. falciparum, as well as its possible cytotoxicity, in HeLa cells. After the biosynthesis of the PdSf NPs, their characterization was carried out by UV-Vis, FESEM, and EDX analyses, and their hydrodynamic size, zeta potential, and surface area were determined. Furthermore, the functional groups of the PdSf NPs were analyzed by FT-IR and GC-MS. While PdSf NPs had an IC50 of 7.68 μg/mL (Chloroquine (CQ)-s) and 16.42 μg/mL, S. fusiforme extract had an IC50 of 14.38 μg/mL (CQ-s) and 35.27 μg/mL (CQ-r). With an IC50 value of 94.49 μg/mL, PdSf NPs exhibited the least toxic effect on the HeLa cells. The Lipinski rule of five and ADMET prediction were used to assess the in silico models of caffeine acid hexoside and quercetin 7-O-hexoside for the presence of drug-like properties. Pathogenic proteins, primarily responsible for motility, binding, and disease-causing, were the target of the structurally based docking studies between plant-derived compounds and pathogenic proteins. Thus, our study pioneered promising results that support the potential antiplasmodial activity of eco-friendly synthesized PdSf NPs using S. fusiforme extract against P. falciparum, opening perspectives for further exploration into the use of these NPs in malaria therapy.

Self-Assembled Maslinic Acid Attenuates Doxorobucin Induced Cytotoxicity via Nrf2 Signaling Pathway: An In Vitro and In Silico Study in Human Healthy Cells

The clinical applications of some well-known chemotherapeutic drugs for cancer treatment have been restricted nowadays owing to their adverse effects on many physiological systems. In this experimental study, maslinic acid (MA) isolated from Olea europaea (Olive) fruit extract was used to mitigate the cytotoxicity induced by Doxorubicin (DOX) in human healthy peripheral blood mononuclear cells (hPBMCs). Self-assembled maslinic acid (SA-MA) was obtained in ethanol-water mixture (35.5 mM: 4:1 v/v). The morphology of SA-MA was analyzed by various physicochemical characterization techniques, which revealed its micro-metric vesicular architecture as well as nano-vesicular appearances. In this study, treatment of hPBMCs with DOX has been found to generate severe intracellular oxidative stress, which was significantly mitigated after pre-treatment with SA-MA. Alteration of hPBMC morphologies after DOX treatment was also restored notably by pre-treatment with SA-MA. Furthermore, pentoxifylline (TNF-α inhibitor) and indomethacin (COX-2 inhibitor) were used to investigate the responsible pathway by which SA-MA protected hPBMCs from DOX-induced cellular stress. Restoration of hPBMC viability above 92% in both cases confirmed that SA-MA protected the cells by inhibiting inflammatory pathways generated by DOX treatment. Subsequently, in molecular docking study, it was also evaluated that MA could successfully bind with the pocket region of Keap1, while Nrf2 was capable of upregulating cytoprotecting genes.

3D-QSAR, ADME-Tox In Silico Prediction and Molecular Docking Studies for Modeling the Analgesic Activity against Neuropathic Pain of Novel NR2B-Selective NMDA Receptor Antagonists

A new class of selective antagonists of the N-Methyl-D-Aspartate (NMDA) receptor subunit 2B have been developed using molecular modeling techniques. The three-dimensional quantitative structure–activity relationship (3D-QSAR) study, based on comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) models, indicate that steric, electrostatic and hydrogen bond acceptor fields have a key function in the analgesic activity against neuropathic pain. The predictive accuracy of the developed CoMFA model (Q2 = 0.540, R2 = 0.980, R2 pred = 0.613) and the best CoMSIA model (Q2 = 0.665, R2 = 0.916, R2 pred = 0.701) has been successfully examined through external and internal validation. Based on ADMET in silico properties, L1, L2 and L3 ligands are non-toxic inhibitors of 1A2, 2C19 and 2C9 cytochromes, predicted to passively cross the blood–brain barrier (BBB) and have the highest probability to penetrate the central nervous system (CNS). Molecular docking results indicate that the active ligands (L1, L2 and L3) interact specifically with Phe176, Glu235, Glu236, Gln110, Asp136 and Glu178 amino acids of the transport protein encoded as 3QEL. Therefore, they could be used as analgesic drugs for the treatment of neuropathic pain.

Rational identification of small molecules derived from 9,10-dihydrophenanthrene as potential inhibitors of 3CLpro enzyme for COVID-19 therapy: a computer-aided drug design approach

Small molecules such as 9,10-dihydrophenanthrene derivatives have remarkable activity toward inhibition of SARS-CoV-2 3CL^pro and COVID-19 proliferation, which show a strong correlation between their structures and bioactivity. Therefore, these small compounds could be suitable for clinical pharmaceutical use against COVID-19. The objective of this study was to remodel the structures of 9,10-dihydrophenanthrene derivatives to achieve a powerful biological activity against 3CL^pro and favorable pharmacokinetic properties for drug design and discovery. Therefore, by the use of bioinformatics techniques, we developed robust 3D-QSAR models that are capable of describing the structure–activity relationship for 46 molecules based on 9,10-dihydrophenanthrene derivatives using CoMFA/SE (R² = 0.97, Q² = 0.81, R²_pred = 0.95, ^cR²_p = 0.71) and CoMSIA/SEHDA (R² = 0.94, Q² = 0.76, R²_pred = 0.91, ^cR²_p = 0.65) techniques. Accordingly, 96 lead compounds were generated based on a template molecule that showed the highest observed activity in vitro (T40, pIC₅₀ = 5.81) and predicted their activities and bioavailability in silico. The rational screening outputs of 3D-QSAR, Molecular docking, ADMET, and MM-GBSA led to the identification of 9 novel modeled molecules as potent noncovalent drugs against SARS-CoV-2-3CL^pro. Finally, by molecular dynamics simulations, the stability and structural dynamics of 3CL^pro free and complex (PDB code: 6LU7) were discussed in the presence of samples of 9,10-dihydrophenanthrene derivative in an aqueous environment. Overall, the retrosynthesis of the proposed drug compounds in this study and the evaluation of their bioactivity in vitro and in vivo may be interesting for designing and discovering a new drug effective against COVID-19.

QSAR, ADMET In Silico Pharmacokinetics, Molecular Docking and Molecular Dynamics Studies of Novel Bicyclo (Aryl Methyl) Benzamides as Potent GlyT1 Inhibitors for the Treatment of Schizophrenia

Forty-four bicyclo ((aryl) methyl) benzamides, acting as glycine transporter type 1 (GlyT1) inhibitors, are developed using molecular modeling techniques. QSAR models generated by multiple linear and non-linear regressions affirm that the biological inhibitory activity against the schizophrenia disease is strongly and significantly correlated with physicochemical, geometrical and topological descriptors, in particular: Hydrogen bond donor, polarizability, surface tension, stretch and torsion energies and topological diameter. According to in silico ADMET properties, the most active ligands (L6, L9, L30, L31 and L37) are the molecules having the highest probability of penetrating the central nervous system (CNS), but the molecule 32 has the highest probability of being absorbed by the gastrointestinal tract. Molecular docking results indicate that Tyr124, Phe43, Phe325, Asp46, Phe319 and Val120 amino acids are the active sites of the dopamine transporter (DAT) membrane protein, in which the most active ligands can inhibit the glycine transporter type 1 (GlyT1). The results of molecular dynamics (MD) simulation revealed that all five inhibitors remained stable in the active sites of the DAT protein during 100 ns, demonstrating their promising role as candidate drugs for the treatment of schizophrenia.

In silico investigation of phytoconstituents from Cameroonian medicinal plants towards COVID-19 treatment

In silico studies performed on the metabolites of four Cameroonian medicinal plants with a view to propose potential molecules to fight against COVID-19 were carried out. At first, molecular docking was performed for a set of 84 selected phytochemicals with SARS-CoV-2 main protease (PDB ID: 6lu7) protein. It was further followed by assessing the pharmacokinetics and pharmacological abilities of 15 compounds, which showed low binding energy values. As the screening criteria for their ADMET properties were performed, only two compounds have shown suitable pharmacological properties for human administration which were shortlisted. Furthermore, the stability of binding of these compounds was assessed by performing molecular dynamics (MD) simulations. Based on further analysis through molecular dynamics simulations and reactivity studies, it was concluded that only the Pycnanthuquinone C (17) and the Pycnanthuquinone A (18) extracted from the Pycnanthus angolensis could be considered as candidate inhibitors for targeted protein. Indeed, we expect that these compounds could show excellent in vitro and in vivo activity against SARS-CoV-2.

3D-QSAR, ADME-Tox, and molecular docking of semisynthetic triterpene derivatives as antibacterial and insecticide agents

In the present work, 27 triterpene derivatives have been subjected to 3D-QSAR, ADME-Tox, and molecular docking for their insecticidal activity. The selected derivatives are previously semi-synthesized based on compounds obtained from Euphorbia resinifera and Euphorbia officinarum latex. The in silico studies were used to predict and to evaluate the antibacterial and insecticidal properties of the 3D structure of triterpene derivatives. The 3D-QSAR models are developed using CoMFA and CoMSIA techniques, and they have showed excellent statistical results (R² = 0.99; Q² = 0.672; R²_pred = 0.91 for CoMFA and R² = 0.97; Q² = 0.61; R²_pred = 0.94 for CoMSIA). The results indicate that the built models are able to describe the relationship between the structure of triterpene derivatives and the pLD₅₀ bioactivity. Based on contour maps obtained from CoMFA and CoMSIA models, 38 new molecules are designed and their pLD₅₀ activities are predicted. The drug-like and ADME-Tox properties of the molecule designed are examined and led to the selection of four molecules (55, 56, 59, 64) as promising antibacterial and insecticidal agents. Compounds 55, 56, 59, and 64 are able to inhibit the MurE (PDB code: 1E8C) and EcR (PDB code: 1R20) proteins involved in the process of antibacterial and insecticidal activities. This hypothesis is confirmed by the implementation of a molecular docking test. This test predicted the most important referential interactions that occur between the structure of triterpene derivatives and the targeted receptors. Among the four docked molecules, three molecules (55, 56, and 59) showed greater stability than the reference molecule 16 inside the MurE and EcR receptors pocket. Therefore, the structure of the three new triterpene derivatives can be adopted as reference for the synthesis of antibacterial drugs and also in the development of insecticides.