In Silico Screening of Available Drugs Targeting Non-Small Cell Lung Cancer Targets: A Drug Repurposing Approach

The RAS–RAF–MEK–ERK pathway plays a key role in malevolent cell progression in many tumors. The high structural complexity in the upstream kinases limits the treatment progress. Thus, MEK inhibition is a promising strategy since it is easy to inhibit and is a gatekeeper for the many malignant effects of its downstream effector. Even though MEK inhibitors are under investigation in many cancers, drug resistance continues to be the principal limiting factor to achieving cures in patients with cancer. Hence, we accomplished a high-throughput virtual screening to overcome this bottleneck by the discovery of dual-targeting therapy in cancer treatment. Here, a total of 11,808 DrugBank molecules were assessed through high-throughput virtual screening for their activity against MEK. Further, the Glide docking, MLSF and prime-MM/GBSA methods were implemented to extract the potential lead compounds from the database. Two compounds, DB012661 and DB07642, were outperformed in all the screening analyses. Further, the study results reveal that the lead compounds also have a significant binding capability with the co-target PIM1. Finally, the SIE-based free energy calculation reveals that the binding of compounds was majorly affected by the van der Waals interactions with MEK receptor. Overall, the in silico binding efficacy of these lead compounds against both MEK and PIM1 could be of significant therapeutic interest to overcome drug resistance in the near future.

Virtual Screening and Molecular Dynamics Simulation Study of Influenza Polymerase PB2 Inhibitors

Influenza A virus is the main cause of worldwide epidemics and annual influenza outbreaks in humans. In this study, a virtual screen was performed to identify compounds that interact with the PB2 cap-binding domain (CBD) of influenza A polymerase. A virtual screening workflow based on Glide docking was used to screen an internal database containing 8417 molecules, and then the output compounds were selected based on solubility, absorbance, and structural fingerprints. Of the 16 compounds selected for biological evaluation, six compounds were identified that rescued cells from H1N1 virus-mediated death at non-cytotoxic concentrations, with EC50 values ranging from 2.5–55.43 μM, and that could bind to the PB2 CBD of H1N1, with Kd values ranging from 0.081–1.53 μM. Molecular dynamics (MD) simulations of the docking complexes of our active compounds revealed that each compound had its own binding characteristics that differed from those of VX-787. Our active compounds have novel structures and unique binding modes with PB2 proteins, and are suitable to serve as lead compounds for the development of PB2 inhibitors. An analysis of the MD simulation also helped us to identify the dominant amino acid residues that play a key role in binding the ligand to PB2, suggesting that we should focus on increasing and enhancing the interaction between inhibitors and these major amino acids during lead compound optimization to obtain more active PB2 inhibitors.

Discovery of a Potent Candidate for RET-Specific Non-Small-Cell Lung Cancer—A Combined In Silico and In Vitro Strategy

Rearranged during transfection (RET) is a tyrosine kinase oncogenic receptor, activated in several cancers including non-small-cell lung cancer (NSCLC). Multiple kinase inhibitors vandetanib and cabozantinib are commonly used in the treatment of RET-positive NSCLC. However, specificity, toxicity, and reduced efficacy limit the usage of multiple kinase inhibitors in targeting RET protein. Thus, in the present investigation, we aimed to figure out novel and potent candidates for the inhibition of RET protein using combined in silico and in vitro strategies. In the present study, screening of 11,808 compounds from the DrugBank repository was accomplished by different hypotheses such as pharmacophore, e-pharmacophore, and receptor cavity-based models in the initial stage. The results from the different hypotheses were then integrated to eliminate the false positive prediction. The inhibitory activities of the screened compounds were tested by the glide docking algorithm. Moreover, RF score, Tanimoto coefficient, prime-MM/GBSA, and density functional theory calculations were utilized to re-score the binding free energy of the docked complexes with high precision. This procedure resulted in three lead molecules, namely DB07194, DB03496, and DB11982, against the RET protein. The screened lead molecules together with reference compounds were then subjected to a long molecular dynamics simulation with a 200 ns time duration to validate the inhibitory activity. Further analysis of compounds using MM-PBSA and mutation studies resulted in the identification of potent compound DB07194. In essence, a cell viability assay with RET-specific lung cancer cell line LC-2/ad was also carried out to confirm the in vitro biological activity of the resultant compound, DB07194. Indeed, the results from our study conclude that DB07194 can be effectively translated for this new therapeutic purpose, in contrast to the properties for which it was originally designed and synthesized.

Structure-based docking, pharmacokinetic evaluation, and molecular dynamics-guided evaluation of traditional formulation against SARS-CoV-2 spike protein receptor bind domain and ACE2 receptor complex

There is an urgent need for reliable cure and preventive measures in this hour of the outbreak of SARS-CoV-2. Siddha- and Ayurvedic-based classical formulations have antiviral properties and great potential therapeutic choice in this pandemic situation. In the current study, in silico-based analysis for the binding potential of phytoconstituents from the classical formulations suggested by the Ministry of Ayush (Kabasura Kudineer, Shwas Kuthar Rasa with Kantakari and pippali churna, Talisadi churna) to the interface domain of the SARS-CoV-2 receptor-binding domain and angiotensin-converting enzyme 2 was performed. Maestro software from Schrodinger and tools like Glide Docking, induced fit docking, MM-GBSA, molecular dynamics (MD) simulation, and thermal MM-GBSA was used to analyze the binding of protein PDB ID:6VW1 and the selected 133 ligands in comparison with drug molecules like favipiravir and ribavirin. QikProp-based ADMET evaluation of all the phytoconstituents found them nontoxic and with drug-like properties. Selection of top ten ligands was made based on docking score for further MM-GBSA analysis. After performing IFD of top five molecules iso-chlorogenic acid, taxiphyllin, vasicine, catechin and caffeic acid, MD simulation and thermal MM-GBSA were done. Iso-chlorogenic acid had formed more stable interaction with key residue among all phytoconstituents. Computational-based study has highlighted the potential of the many constituents of traditional medicine to interact with the SARS-CoV-2 RBD and ACE2, which might stop the viral entry into the cell. However, in vivo experiments and clinical trials are necessary for supporting this claim.

Assessing the affinity of oxazolidinedione/hydantoin derivatives for the human 5HT1A/2A receptor through homology modeling and docking studies

A flexible docking of a series of heteroaryl compounds to the binding site of a model of human 5-HT1A/2A receptor was exercised using GLIDE docking methods. The resultant docking scores were used to correlate the in vivo affinity data. The GLIDE docking algorithm when used with a homology model of 5HT1A/2A was based on β2- adrenergic receptor template. The influence of structure and hydrophobic properties of aryl moiety on binding affinities was discussed and a model for ligand binding in the hydrophobic part of the binding site was proposed.

Glide Docking, Autodock, Binding Free Energy and Drug-Likeness Studies for Prediction of Potential Inhibitors of Cyclin-Dependent Kinase 14 Protein in Wnt Signaling Pathway

Cyclin-dependent kinase 14 plays an essential role in multiple cancers. Cyclin-dependent kinase 14 is a serine/threonine kinase and is a member of the cell division cycle 2(cdc2) related protein kinase family, which plays a key role in promoting Wnt signaling pathway of the cell cycle and its overexpression causes various human cancers. The 3D structure of cyclin-dependent kinase 14 was built using the homology-based modeling technique. The generated model is optimized by NAMD-VMD software. The quality of stabilized CDK14 protein was checked using Ramachandran plot and ProSA servers. The potential binding site region was recognized using SiteMap and manual correlation techniques from literature studies. The virtual screening was performed with the TOSLab database of 27253 output molecules against CDK14 protein using Glide docking to assess novel chemical entities. Their binding energies were calculated from PrimeMMGSA and AutoDock. The novel lead molecules have been prioritized based on efficient binding energies (from AutoDock and PrimeMMGBSA), better glide scores, good bioavailability, and acceptable ADME properties. Thus, these are considered as CDK14 protein inhibitors for cancer therapeutics.

Identification of Novel Nrf2 Activator via Protein-ligand Interactions as Remedy for Oxidative Stress in Diabetes Mellitus

Background: Oxidative stress is a significant player in the pathogenesis of diabetes mellitus and the Kelch-like ECH-associated protein1/nuclear factor erythroid 2-related factor 2/antioxidant response element (Keap1/Nrf2/ARE) signaling pathway serves as the essential defense system to mitigate oxidative stress. Nrf2 is responsible for the mitigation of oxidative stress while Keap1 represses Nrf2’s activation upon binding. Identification of Nrf2 activators has started to pick up enthusiasm as they can be used as therapeutic agents against diabetes mellitus. One of the ongoing mechanisms in the activation of Nrf2 is to disrupt Keap1/Nrf2 protein-protein interaction. This study aimed at using computational analysis to screen natural compounds capable of inhibiting Keap1/Nrf2 protein-protein interaction. Methods: A manual curated library of natural compounds was screened against crystal structure of Keap1 using glide docking algorithm. Binding free energy of the docked complexes, and adsorption, digestion, metabolism and excretion (ADME) properties were further employed to identify the hit compounds. The bioactivity of the identified hit against Keap1 was predicted using quantitative structure-activity relationship (QSAR) model. Results: A total of 7 natural compounds (Compound 222, 230, 310, 208, 210, 229 and 205) identified from different medicinal plants were found to be potent against Keap1 based on their binding affinity and binding free energy. The internal validated model kpls_radial_30 with R2 of 0.9109, Q2 of 0.7287 was used to predict the compounds’ bioactivities. Compound 205 was considered as the ideal drug candidate because it showed moderation for ADME properties, had predicted pIC50 of 6.614 and obeyed Lipinski’s rule of five. Conclusion: This study revealed that Compound 205, a compound isolated from Amphipterygium adstringens is worth considering for further experimental analysis.

Natural products as inhibitors of COVID-19 main protease–A virtual screening by molecular docking

Background: The novel coronavirus (2019-nCoV) causes a severe respiratory illness unknown to a human before. Its alarmingly quick transmission to many countries across the world has resulted in a global health emergency. Therefore, an imminent need for drugs to combat this disease has been increased. Worldwide collaborative efforts from scientists are underway to determine a therapy to treat COVID-19 infections and reduce mortality rates. Since herbal medicines and purified natural products have been reported to have antiviral activity against Coronaviruses (CoVs), this in silico evaluation was performed for identifying potential natural compounds with promising inhibitory activities against COVID-19. Methods: In this study, a High Throughput Virtual Screening (HTVS) protocol was used as a fast method for discovering novel drug candidates as potential COVID-19 main protease (Mpro) inhibitors. Over 180,000 natural product-based compounds were obtained from the ZINC database and virtually screened against the COVID-19 Mpro. In this study, the Glide docking program was applied for high throughput virtual screening. Also, Extra precision (XP) has been used following the induced-fit docking (IFD) approach. The ADME properties of all compounds were analyzed and a final selection was made based on the Lipinski rule of five. Also, molecular dynamics (MD) simulations were conducted for a virtual complex of the best scoring compound with COVID-19 protease. Results: Nineteen compounds were introduced as new potential inhibitors. Compound ZINC08765174 (1-[3-(1H-indol-3-yl) propanoyl]-N-(4-phenylbutan-2-yl)piperidine-3-carboxamide showed a strong binding affinity (-11.5 kcal/mol) to the COVID-19 Mpro comparing to peramivir (-9.8 kcal/mol) as a positive control. Conclusions: Based on these findings, nineteen compounds were proposed as possible new COVID-19 inhibitors, of which ZINC08765174 had a high affinity to Mpro. Furthermore, the promising ADME properties of the selected compounds emphasize their potential as attractive candidates for the treatments of COVID-19.

Molecular Docking Investigation of Antiviral Herbal Compounds as Potential Inhibitors of SARS-CoV-2 Spike Receptor

At the beginning of 2020, a new type of Coronavirus (Severe Acute Respiratory Syndrome Coronavirus -2 (SARS-CoV-2)) dismayed the world and led to public health emergencies. This virus has caused a remarkable percentage of morbidity and mortality. Also, the lack of an effective treatment to fight this virus is another concern that should be given attention. Herbal medicines and purified natural products have been reported for their antiviral activity against SARS-CoV-2. In this study, molecular docking of effective compounds in the extracts and essential oils of Zingiber officinale, Glycyrrhiza glabra Sambucus nigra, Panax ginseng Ocimum basilicum, and Origanum vulgare was carried out to investigate their binding to the X-ray structure of the ACE2 binding domain of SARS-CoV-2. The Glide docking program was utilized for molecular docking with standard precision (SP) and extra precision (XP). Finally, 7 compounds- mainly belong to Panax ginseng-showed a higher docking score than some known antiviral compounds. Floralginsenoside B, which is extracted from Panax ginseng, indicated a strong binding affinity (-8.618 kcal/mol) to the crucial residues of the receptor binding domain of SARS-CoV-2 comparing to Doravirine (-7.2 kcal/mol), Hetacillin (-7.1 kcal/mol), Ketoprofen (-7.0 kcal/mol), and Mefloquine (-7.0 kcal/mol) reported in previous articles. Based on the excellent binding affinities of these herbal compounds, we concluded that these phytochemicals could be promising candidates for fighting against the COVID-19 pandemic.

In silico Screening of Natural Compounds as Potential Inhibitors of SARS-CoV-2 Main Protease and Spike RBD: Targets for COVID-19

Historically, plants have been sought after as bio-factories for the production of diverse chemical compounds that offer a multitude of possibilities to cure diseases. To combat the current pandemic coronavirus disease 2019 (COVID-19), plant-based natural compounds are explored for their potential to inhibit the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), the cause of COVID-19. The present study is aimed at the investigation of antiviral action of several groups of phytoconstituents against SARS-CoV-2 using a molecular docking approach to inhibit Main Protease (Mpro) (PDB code: 6LU7) and spike (S) glycoprotein receptor binding domain (RBD) to ACE2 (PDB code: 6M0J) of SARS-CoV-2. For binding affinity evaluation, the docking scores were calculated using the Extra Precision (XP) protocol of the Glide docking module of Maestro. CovDock was also used to investigate covalent docking. The OPLS3e force field was used in simulations. The docking score was calculated by preferring the conformation of the ligand that has the lowest binding free energy (best pose). The results are indicative of better potential of solanine, acetoside, and rutin, as Mpro and spike glycoprotein RBD dual inhibitors. Acetoside and curcumin were found to inhibit Mpro covalently. Curcumin also possessed all the physicochemical and pharmacokinetic parameters in the range. Thus, phytochemicals like solanine, acetoside, rutin, and curcumin hold potential to be developed as treatment options against COVID-19.