Naturally Occurring Plant-Based Anticancerous Candidates as Potential ERK2 Inhibitors: In-Silico Database Mining and Molecular Dynamics Simulations.

The evolutionarily conserved extracellular signal-regulated kinase 2 (ERK2) is involved in regulating cellular signaling in both normal and pathological conditions. ERK2 expression is critical for human development, while hyperactivation is a major factor in tumor progression. Up to now, there have been no approved inhibitors that target ERK2, and as such, here we report on screening of a naturally occurring plant-based anticancerous compound-activity-target (NPACT) database for prospective ERK2 inhibitors. More than 1,500 phytochemicals were screened using in-silico molecular docking and molecular dynamics (MD) approaches. NPACT compounds with a docking score lower than a co-crystallized LHZ inhibitor (calc.-10.5 kcal/mol) were subjected to MD simulations. Binding energies (ΔGbinding) of inhibitor-ERK2 complexes over the MD course were estimated using an MM-GBSA approach. Based on MM-GBSA//100 ns MD simulations, the steroid zhankuic acid C (NPACT01034) demonstrated greater binding affinity against ERK2 protein than LHZ, with ΔGbinding values of -50.0 and -47.7 kcal/mol, respectively. Structural and energetical analyses throughout the MD course demonstrated stabilization of zhankuic acid C complexed with ERK2 protein. The anticipated ADMET properties of zhankuic acid C indicated minimal toxicity. Moreover, in-silico evaluation of fourteen ERK2 inhibitors in clinical trials demonstrated the higher binding affinity of zhankuic acid C towards ERK2 protein.

Pyronaridine as a Bromodomain-Containing Protein 4-N-Terminal Bromodomain (BRD4-BD1) Inhibitor: In Silico Database Mining, Molecular Docking, and Molecular Dynamics Simulation.

BRD4 (bromodomain-containing protein 4) is an epigenetic reader that realizes histone proteins and promotes the transcription of genes linked to cancer progression and non-cancer diseases such as acute heart failure and severe inflammation. The highly conserved N-terminal bromodomain (BD1) recognizes acylated lysine residues to organize the expression of genes. As such, BD1 is essential for disrupting BRD4 interactions and is a promising target for cancer treatment. To identify new BD1 inhibitors, a SuperDRUG2 database that contains more than 4600 pharmaceutical compounds was screened using in silico techniques. The efficiency of the AutoDock Vina1.1.2 software to anticipate inhibitor-BRD4-BD1 binding poses was first evaluated based on the co-crystallized R6S ligand in complex with BRD4-BD1. From database screening, the most promising BRD4-BD1 inhibitors were subsequently submitted to molecular dynamics (MD) simulations integrated with an MM-GBSA approach. MM-GBSA computations indicated promising BD1 binding with a benzonaphthyridine derivative, pyronaridine (SD003509), with an energy prediction (ΔGbinding) of -42.7 kcal/mol in comparison with -41.5 kcal/mol for a positive control inhibitor (R6S). Pharmacokinetic properties predicted oral bioavailability for both ligands, while post-dynamic analyses of the BRD4-BD1 binding pocket demonstrated greater stability for pyronaridine. These results confirm that in silico studies can provide insight into novel protein-ligand regulators, specifically that pyronaridine is a potential cancer drug candidate.

SuperNatural inhibitors to reverse multidrug resistance emerged by ABCB1 transporter: Database mining, lipid-mediated molecular dynamics, and pharmacokinetics study.

An effective approach to reverse multidrug resistance (MDR) is P-glycoprotein (P-gp, ABCB1) transport inhibition. To identify such molecular regulators, the SuperNatural II database, which comprises > 326,000 compounds, was virtually screened for ABCB1 transporter inhibitors. The Lipinski rule was utilized to initially screen the SuperNatural II database, identifying 128,126 compounds. Those natural compounds were docked against the ABCB1 transporter, and those with docking scores less than zosuquidar (ZQU) inhibitor were subjected to molecular dynamics (MD) simulations. Based on MM-GBA binding energy (ΔGbinding) estimations, UMHSN00009999 and UMHSN00097206 demonstrated ΔGbinding values of -68.3 and -64.1 kcal/mol, respectively, compared to ZQU with a ΔGbinding value of -49.8 kcal/mol. For an investigation of stability, structural and energetic analyses for UMHSN00009999- and UMHSN00097206-ABCB1 complexes were performed and proved the high steadiness of these complexes throughout 100 ns MD simulations. Pharmacokinetic properties of the identified compounds were also predicted. To mimic the physiological conditions, MD simulations in POPC membrane surroundings were applied to the UMHSN00009999- and UMHSN00097206-ABCB1 complexes. These results demonstrated that UMHSN00009999 and UMHSN00097206 are promising ABCB1 inhibitors for reversing MDR in cancer and warrant additional in-vitro/in-vivo studies.

In-Silico Mining of the Toxins Database (T3DB) towards Hunting Prospective Candidates as ABCB1 Inhibitors: Integrated Molecular Docking and Lipid Bilayer-Enhanced Molecular Dynamics Study.

Multidrug resistance (MDR) is one of the most problematic issues in chemotherapeutic carcinoma therapy. The ABCB1 transporter, a drug efflux pump overexpressed in cancer cells, has been thoroughly investigated for its association with MDR. Thus, discovering ABCB1 inhibitors can reverse the MDR in cancer cells. In the current work, a molecular docking technique was utilized for hunting the most prospective ABCB1 inhibitors from the Toxin and Toxin-Target Database (T3DB). Based on the docking computations, the most promising T3DB compounds complexed with the ABCB1 transporter were subjected to molecular dynamics (MD) simulations over 100 ns. Utilizing the MM-GBSA approach, the corresponding binding affinities were computed. Compared to ZQU (calc. -49.8 kcal/mol), Emamectin B1a (T3D1043), Emamectin B1b (T3D1044), Vincristine (T3D4016), Vinblastine (T3D4017), and Vindesine (T3D2479) complexed with ABCB1 transporter demonstrated outstanding binding affinities with ΔGbinding values of -93.0, -92.6, -93.8, -92.2, and -90.8 kcal/mol, respectively. The structural and energetic investigations confirmed the constancy of the identified T3DB compounds complexed with the ABCB1 transporter during the 100 ns MD course. To mimic the physiological conditions, MD simulations were conducted for those identified inhibitors complexed with ABCB1 transporter in the presence of a POPC membrane. These findings revealed that Emamectin B1a, Emamectin B1b, Vincristine, Vinblastine, and Vindesine are promising ABCB1 inhibitors that can reverse the MDR. Therefore, subjecting those compounds to further in-vitro and in-vivo investigations is worthwhile.

Potential drug candidates as P-glycoprotein inhibitors to reverse multidrug resistance in cancer: an in silico drug discovery study.

The failure of chemotherapy in the treatment of carcinoma is mainly due to the development of multidrug resistance (MDR), which is largely caused by the overexpression of P-glycoprotein (P-gp/ABCB1/MDR1). Until recently, the 3D structure of the P-gp transporter has not been experimentally resolved, which restricted the discovery of prospective P-gp inhibitors utilizing in silico techniques. In this study, the binding energies of 512 drug candidates in clinical or investigational stages were assessed as potential P-gp inhibitors employing in silico methods. On the basis of the available experimental data, the performance of the AutoDock4.2.6 software to predict the drug-P-gp binding mode was initially validated. Molecular docking and molecular dynamics (MD) simulations combined with molecular mechanics-generalized Born surface area (MM-GBSA) binding energy computations were subsequently conducted to screen the investigated drug candidates. Based on the current results, five promising drug candidates, namely valspodar, dactinomycin, elbasvir, temsirolimus, and sirolimus, showed promising binding energies against P-gp transporter with ΔGbinding values of -126.7, -112.1, -111.9, -102.9, and -101.4 kcal/mol, respectively. The post-MD analyses revealed the energetical and structural stabilities of the identified drug candidates in complex with the P-gp transporter. Furthermore, in order to mimic the physiological conditions, the potent drugs complexed with the P-gp were subjected to 100 ns MD simulations in an explicit membrane-water environment. The pharmacokinetic properties of the identified drugs were predicted and demonstrated good ADMET characteristics. Overall, these results indicated that valspodar, dactinomycin, elbasvir, temsirolimus, and sirolimus hold promise as prospective P-gp inhibitors and warrant further invitro/invivo investigations.

In silico drug discovery of SIRT2 inhibitors from natural source as anticancer agents.

Sirtuin 2 (SIRT2) is a member of the sirtuin protein family, which includes lysine deacylases that are NAD+-dependent and organize several biological processes. Different forms of cancer have been associated with dysregulation of SIRT2 activity. Hence, identifying potent inhibitors for SIRT2 has piqued considerable attention in the drug discovery community. In the current study, the Natural Products Atlas (NPAtlas) database was mined to hunt potential SIRT2 inhibitors utilizing in silico techniques. Initially, the performance of the employed docking protocol to anticipate ligand-SIRT2 binding mode was assessed according to the accessible experimental data. Based on the predicted docking scores, the most promising NPAtlas molecules were selected and submitted to molecular dynamics (MD) simulations, followed by binding energy computations. Based on the MM-GBSA binding energy estimations over a 200 ns MD course, three NPAtlas compounds, namely NPA009578, NPA006805, and NPA001884, were identified with better ΔGbinding towards SIRT2 protein than the native ligand (SirReal2) with values of - 59.9, - 57.4, - 53.5, and - 49.7 kcal/mol, respectively. On the basis of structural and energetic assessments, the identified NPAtlas compounds were confirmed to be steady over a 200 ns MD course. The drug-likeness and pharmacokinetic characteristics of the identified NPAtlas molecules were anticipated, and robust bioavailability was predicted. Conclusively, the current results propose potent inhibitors for SIRT2 deserving more in vitro/in vivo investigation.

Chetomin, a SARS-CoV-2 3C-like Protease (3CLpro) Inhibitor: In Silico Screening, Enzyme Docking, Molecular Dynamics and Pharmacokinetics Analysis.

The emergence of the Coronavirus Disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has led to over 6 million deaths. The 3C-like protease (3CLpro) enzyme of the SARS-CoV-2 virus is an attractive druggable target for exploring therapeutic drug candidates to combat COVID-19 due to its key function in viral replication. Marine natural products (MNPs) have attracted considerable attention as alternative sources of antiviral drug candidates. In looking for potential 3CLpro inhibitors, the MNP database (>14,000 molecules) was virtually screened against 3CLpro with the assistance of molecular docking computations. The performance of AutoDock and OEDocking software in anticipating the ligand-3CLpro binding mode was first validated according to the available experimental data. Based on the docking scores, the most potent MNPs were further subjected to molecular dynamics (MD) simulations, and the binding affinities of those molecules were computed using the MM-GBSA approach. According to MM-GBSA//200 ns MD simulations, chetomin (UMHMNP1403367) exhibited a higher binding affinity against 3CLpro than XF7, with ΔGbinding values of −55.5 and −43.7 kcal/mol, respectively. The steadiness and tightness of chetomin with 3CLpro were evaluated, revealing the high stabilization of chetomin (UMHMNP1403367) inside the binding pocket of 3CLpro throughout 200 ns MD simulations. The physicochemical and pharmacokinetic features of chetomin were also predicted, and the oral bioavailability of chetomin was demonstrated. Furthermore, the potentiality of chetomin analogues −namely, chetomin A-D− as 3CLpro inhibitors was investigated. These results warrant further in vivo and in vitro assays of chetomin (UMHMNP1403367) as a promising anti-COVID-19 drug candidate.

In silico drug repurposing and lipid bilayer molecular dynamics puzzled out potential breast cancer resistance protein (BCRP/ABCG2) inhibitors.

Multidrug resistance (MDR) is a fundamental reason for the fiasco of carcinoma chemotherapy. A wide variety of anticarcinoma drugs are expelled from neoplasm cells through the ATP-binding cassette (ABC) transporter superfamily, rendering the neoplasm cells resistant to treatment. The ATP-binding cassette transporter G2 (ABCG2, gene symbol BCRP) is an ABC efflux transporter that plays a key function in MDR to antineoplastic therapies. For these reasons, the identification of medicaments as BCRP inhibitors could assist in discovering better curative approaches for breast cancer therapy. Because of the deficiency of prospective BCRP inhibitors, the SuperDRUG2 database was virtually screened for inhibitor activity towards the BCRP transporter using molecular docking computations. The most potent drug candidates were then characterized utilizing molecular dynamics (MD) simulations. Furthermore, molecular mechanics-generalized Born surface area (MM-GBSA) binding affinities of the most potent drug candidates were estimated. Based on the MM-GBSA binding affinities throughout 150 ns MD simulations, three drugs-namely zotarolimus (SD002595), temsirolimus (SD003393), and glecaprevir (SD006009)-revealed greater binding affinities towards BCRP transporter compared to the co-crystallized BWQ ligand with ΔGbinding values of -86.6 ± 5.6, -79.5 ± 8.0, -75.8 ± 4.6 and -59.5 ± 4.1 kcal/mol, respectively. The steadiness of these promising drugs bound with BCRP transporter was examined utilizing their structural and energetical analyses throughout a 150 ns MD simulation. To imitate the physiological environment, 150 ns MD simulations for the identified drugs bound with BCRP transporter were conducted in the 1-palmitoyl-2-oleoyl-phosphatidylcholine lipid bilayer. These findings identify zotarolimus, temsirolimus and glecaprevir as auspicious anti-MDR drug leads that warrant further experimental assays.Communicated by Ramaswamy H. Sarma.

Exploring Natural Product Activity and Species Source Candidates for Hunting ABCB1 Transporter Inhibitors: An In Silico Drug Discovery Study.

The P-glycoprotein (P-gp/ABCB1) is responsible for a xenobiotic efflux pump that shackles intracellular drug accumulation. Additionally, it is included in the dud of considerable antiviral and anticancer chemotherapies because of the multidrug resistance (MDR) phenomenon. In the search for prospective anticancer drugs that inhibit the ABCB1 transporter, the Natural Product Activity and Species Source (NPASS) database, containing >35,000 molecules, was explored for identifying ABCB1 inhibitors. The performance of AutoDock4.2.6 software to anticipate ABCB1 docking score and pose was first assessed according to available experimental data. The docking scores of the NPASS molecules were predicted against the ABCB1 transporter. Molecular dynamics (MD) simulations were conducted for molecules with docking scores lower than taxol, a reference inhibitor, pursued by molecular mechanics-generalized Born surface area (MM-GBSA) binding energy estimations. On the basis of MM-GBSA calculations, five compounds revealed promising binding affinities as ABCB1 inhibitors with ΔGbinding < −105.0 kcal/mol. The binding affinity and stability of the identified inhibitors were compared to the chemotherapeutic agent. Structural and energetical analyses unveiled great steadiness of the investigated inhibitors within the ABCB1 active site throughout 100 ns MD simulations. Conclusively, these findings point out that NPC104372, NPC475164, NPC2313, NPC197736, and NPC477344 hold guarantees as potential ABCB1 drug candidates and warrant further in vitro/in vivo tests.

Exploring Toxins for Hunting SARS-CoV-2 Main Protease Inhibitors: Molecular Docking, Molecular Dynamics, Pharmacokinetic Properties, and Reactome Study.

The main protease (Mpro) is a potential druggable target in SARS-CoV-2 replication. Herein, an in silico study was conducted to mine for Mpro inhibitors from toxin sources. A toxin and toxin-target database (T3DB) was virtually screened for inhibitor activity towards the Mpro enzyme utilizing molecular docking calculations. Promising toxins were subsequently characterized using a combination of molecular dynamics (MD) simulations and molecular mechanics-generalized Born surface area (MM-GBSA) binding energy estimations. According to the MM-GBSA binding energies over 200 ns MD simulations, three toxins-namely philanthotoxin (T3D2489), azaspiracid (T3D2672), and taziprinone (T3D2378)-demonstrated higher binding affinities against SARS-CoV-2 Mpro than the co-crystalized inhibitor XF7 with MM-GBSA binding energies of -58.9, -55.9, -50.1, and -43.7 kcal/mol, respectively. The molecular network analyses showed that philanthotoxin provides a ligand lead using the STRING database, which includes the biochemical top 20 signaling genes CTSB, CTSL, and CTSK. Ultimately, pathway enrichment analysis (PEA) and Reactome mining results revealed that philanthotoxin could prevent severe lung injury in COVID-19 patients through the remodeling of interleukins (IL-4 and IL-13) and the matrix metalloproteinases (MMPs). These findings have identified that philanthotoxin-a venom of the Egyptian solitary wasp-holds promise as a potential Mpro inhibitor and warrants further in vitro/in vivo validation.

Naturally occurring plant-based anticancerous candidates as prospective ABCG2 inhibitors: an in silico drug discovery study.

ATP-binding cassette transporter G2 (ABCG2) is an efflux transporter related to the clinical multidrug resistance (MDR) phenomenon. Identifying ABCG2 inhibitors could help discover extraordinary curative strategies for carcinoma remediation. Hitherto, there is no medication drug inhibiting ABCG2 transporter, notwithstanding that a considerable number of drugs have been submitted to clinical-trial and investigational phases. In the search for unprecedented chemical compounds that could inhibit the ABCG2 transporter, an in silico screening was conducted on the Naturally Occurring Plant-based Anticancer Compound-Activity-Target (NPACT) database containing 1574 compounds. Inhibitor-ABCG2 binding affinities were estimated based on molecular docking and molecular minimization (MM) calculations and compared to a co-crystallized inhibitor (BWQ) acting as a reference inhibitor. Molecular dynamics (MD) simulations pursued by molecular mechanics-generalized Born surface area (MM-GBSA) binding energy estimations were further executed for compounds with MM-GBSA//MM binding energies lower than BWQ (calc. - 60.5 kcal/mol). NPACT00968 and NPACT01545 demonstrated auspicious inhibitory activities according to binding affinities (ΔGbinding) over the 100 ns MD simulations that were nearly one and a half folds compared to BWQ (- 100.4, - 94.7, and - 62.9 kcal/mol, respectively). Throughout the 100 ns MD simulations, structural and energetical analyses unveiled outstanding stability of the ABCG2 transporter when bound with NPACT00968 and NPACT01545. In silico calculations hold a promise for those two inhibitors as drug candidates of ABCG2 transporter and emphasize that further in vitro and in vivo experiments are guaranteed.

In Silico Targeting Human Multidrug Transporter ABCG2 in Breast Cancer: Database Screening, Molecular Docking, and Molecular Dynamics Study.

ABCG2 is a substantial member of the ABC transporter superfamily that plays a significant role in multidrug resistance in cancer. Until recently, the 3D structure of ABCG2 has not been resolved, which resulted in the limitation of developing potential ABCG2 inhibitors using structure-based drug discovery. Herein, eMolecules, ChEMBL, and ChEBI databases, containing >25 million compounds, were virtually screened against the ABCG2 transporter in homodimer form. Performance of AutoDock4.2.6 software to predict inhibitor-ABCG2 binding mode and affinity were validated on the basis of available experimental data. The explored databases were filtered based on docking scores. The most potent hits with binding affinities higher than that of experimental bound ligand (MZ29) were then selected and subjected to molecular mechanics minimization, followed by binding energy calculation using molecular mechanics-generalized Born surface area (MM-GBSA) approach. Furthermore, molecular dynamics simulations for 50 ns, followed by MM-GBSA binding energy calculations, were performed for the promising compounds, unveiling eight potential inhibitors with binding affinities <-55.8 kcal/mol. Structural and energetic analyses demonstrated the stability of the eight identified inhibitors over the 50 ns MD simulation. This research sheds light on the potentiality of the identified ABCG2 inhibitors as a therapeutic approach to overcome multidrug resistance cancer therapy.

Non-ß-Lactam Allosteric Inhibitors Target Methicillin-Resistant Staphylococcus aureus: An In Silico Drug Discovery Study.

Penicillin-binding proteins (PBPs) catalyze the final stages for peptidoglycan cell-wall bio-synthesis. Mutations in the PBP2a subunit can attenuate ß-lactam antibiotic activity, resulting in unimpeded cell-wall formation and methicillin-resistant Staphylococcus aureus (MRSA). A double mutation in PBP2a (i.e., N146K and E150K) is resistant to ß-lactam inhibitors; however, (E)-3-(2-(4-cyanostyryl)-4-oxoquinazolin-3(4H)-yl) benzoic acid (QNZ), a heterocyclic antibiotic devoid of a ß-lactam ring, interacts non-covalently with PBP2a allosteric site and inhibits PBP enzymatic activity. In the search for novel inhibitors that target this PBP2a allosteric site in acidic medium, an in silico screening was performed. Chemical databases including eMolecules, ChEMBL, and ChEBI were virtually screened for candidate inhibitors with a physicochemical similarity to QNZ. PBP2a binding affinities from the screening were calculated based on molecular docking with co-crystallized ligand QNZ serving as a reference. Molecular minimization calculations were performed for inhibitors with docking scores lower than QNZ (calc. -8.3 kcal/mol) followed by combined MD simulations and MM-GBSA binding energy calculations. Compounds eMol26313223 and eMol26314565 exhibited promising inhibitor activities based on binding affinities (ΔGbinding) that were twice that of QNZ (-38.5, -34.5, and -15.4 kcal/mol, respectively). Structural and energetic analyses over a 50 ns MD simulation revealed high stability for the inhibitors when complexed with the double mutated PBP2a. The pharmacokinetic properties of the two inhibitors were predicted using an in silico ADMET analysis. Calculated binding affinities hold promise for eMol26313223 and eMol26314565 as allosteric inhibitors of PBP2a in acidic medium and establish that further in vitro and in vivo inhibition experimentation is warranted.

Blue Biotechnology: Computational Screening of Sarcophyton Cembranoid Diterpenes for SARS-CoV-2 Main Protease Inhibition.

The coronavirus pandemic has affected more than 150 million people, while over 3.25 million people have died from the coronavirus disease 2019 (COVID-19). As there are no established therapies for COVID-19 treatment, drugs that inhibit viral replication are a promising target; specifically, the main protease (Mpro) that process CoV-encoded polyproteins serves as an Achilles heel for assembly of replication-transcription machinery as well as down-stream viral replication. In the search for potential antiviral drugs that target Mpro, a series of cembranoid diterpenes from the biologically active soft-coral genus Sarcophyton have been examined as SARS-CoV-2 Mpro inhibitors. Over 360 metabolites from the genus were screened using molecular docking calculations. Promising diterpenes were further characterized by molecular dynamics (MD) simulations based on molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations. According to in silico calculations, five cembranoid diterpenes manifested adequate binding affinities as Mpro inhibitors with ΔGbinding < -33.0 kcal/mol. Binding energy and structural analyses of the most potent Sarcophyton inhibitor, bislatumlide A (340), was compared to darunavir, an HIV protease inhibitor that has been recently subjected to clinical-trial as an anti-COVID-19 drug. In silico analysis indicates that 340 has a higher binding affinity against Mpro than darunavir with ΔGbinding values of -43.8 and -34.8 kcal/mol, respectively throughout 100 ns MD simulations. Drug-likeness calculations revealed robust bioavailability and protein-protein interactions were identified for 340; biochemical signaling genes included ACE, MAPK14 and ESR1 as identified based on a STRING database. Pathway enrichment analysis combined with reactome mining revealed that 340 has the capability to re-modulate the p38 MAPK pathway hijacked by SARS-CoV-2 and antagonize injurious effects. These findings justify further in vivo and in vitro testing of 340 as an antiviral agent against SARS-CoV-2.

Prospective Drug Candidates as Human Multidrug Transporter ABCG2 Inhibitors: an In Silico Drug Discovery Study.

Breast cancer resistance protein (ABCG2) is a human ATP-binding cassette (ABC) that plays a paramount role in multidrug resistance (MDR) in cancer therapy. The discovery of ABCG2 inhibitors could assist in designing unprecedented therapeutic strategies for cancer treatment. There is as yet no approved drug targeting ABCG2, although a large number of drug candidates have been clinically investigated. In this work, binding affinities of 181 drug candidates in clinical-trial or investigational stages as ABCG2 inhibitors were inspected using in silico techniques. Based on available experimental data, the performance of AutoDock4.2.6 software was first validated to predict the inhibitor-ABCG2 binding mode and affinity. Combined molecular docking calculations and molecular dynamics (MD) simulations, followed by molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations, were then performed to filter out the studied drug candidates. From the estimated docking scores and MM-GBSA binding energies, six auspicious drug candidates-namely, pibrentasvir, venetoclax, ledipasvir, avatrombopag, cobicistat, and revefenacin-exhibited auspicious binding energies with value < -70.0 kcal/mol. Interestingly, pibrentasvir, venetoclax, and ledipasvir were observed to show even higher binding affinities with the ABCG2 transporter with binding energies of < -80.0 kcal/mol over long MD simulations of 100 ns. The stabilities of these three promising candidates in complex with ABCG2 transporter were demonstrated by their energetics and structural analyses throughout the 100 ns MD simulations. The current study throws new light on pibrentasvir, venetoclax, and ledipasvir as curative options for multidrug resistant cancers by inhibiting ABCG2 transporter.

In Silico Mining of Terpenes from Red-Sea Invertebrates for SARS-CoV-2 Main Protease (Mpro) Inhibitors.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent for the COVID-19 pandemic, which generated more than 1.82 million deaths in 2020 alone, in addition to 83.8 million infections. Currently, there is no antiviral medication to treat COVID-19. In the search for drug leads, marine-derived metabolites are reported here as prospective SARS-CoV-2 inhibitors. Two hundred and twenty-seven terpene natural products isolated from the biodiverse Red-Sea ecosystem were screened for inhibitor activity against the SARS-CoV-2 main protease (Mpro) using molecular docking and molecular dynamics (MD) simulations combined with molecular mechanics/generalized Born surface area binding energy calculations. On the basis of in silico analyses, six terpenes demonstrated high potency as Mpro inhibitors with ΔGbinding ≤ -40.0 kcal/mol. The stability and binding affinity of the most potent metabolite, erylosides B, were compared to the human immunodeficiency virus protease inhibitor, lopinavir. Erylosides B showed greater binding affinity towards SARS-CoV-2 Mpro than lopinavir over 100 ns with ΔGbinding values of -51.9 vs. -33.6 kcal/mol, respectively. Protein-protein interactions indicate that erylosides B biochemical signaling shares gene components that mediate severe acute respiratory syndrome diseases, including the cytokine- and immune-signaling components BCL2L1, IL2, and PRKC. Pathway enrichment analysis and Boolean network modeling were performed towards a deep dissection and mining of the erylosides B target-function interactions. The current study identifies erylosides B as a promising anti-COVID-19 drug lead that warrants further in vitro and in vivo testing.

Rutin and flavone analogs as prospective SARS-CoV-2 main protease inhibitors: In silico drug discovery study.

Coronavirus disease 2019 (COVID-19) is a new pandemic characterized by quick spreading and illness of the respiratory system. To date, there is no specific therapy for Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). Flavonoids, especially rutin, have attracted considerable interest as a prospective SARS-CoV-2 main protease (Mpro) inhibitor. In this study, a database containing 2017 flavone analogs was prepared and screened against SARS-CoV-2 Mpro using the molecular docking technique. According to the results, 371 flavone analogs exhibited good potency towards Mpro with docking scores less than -9.0 kcal/mol. Molecular dynamics (MD) simulations, followed by molecular mechanics-generalized Born surface area (MM/GBSA) binding energy calculations, were performed for the top potent analogs in complex with Mpro. Compared to rutin, PubChem-129-716-607 and PubChem-885-071-27 showed better binding affinities against SARS-CoV-2 Mpro over 150 ns MD course with ΔGbinding values of -69.0 and -68.1 kcal/mol, respectively. Structural and energetic analyses demonstrated high stability of the identified analogs inside the SARS-CoV-2 Mpro active site over 150 ns MD simulations. The oral bioavailabilities of probable SARS-CoV-2 Mpro inhibitors were underpinned using drug-likeness parameters. A comparison of the binding affinities demonstrated that the MM/GBSA binding energies of the identified flavone analogs were approximately three and two times less than those of lopinavir and baicalein, respectively. In conclusion, PubChem-129-716-607 and PubChem-885-071-27 are promising anti-COVID-19 drug candidates that warrant further clinical investigations.

In Silico Evaluation of Prospective Anti-COVID-19 Drug Candidates as Potential SARS-CoV-2 Main Protease Inhibitors.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a recently emanating human infectious coronavirus that causes COVID-19 disease. On 11th March 2020, it has been announced as a pandemic by the World Health Organization (WHO). Recently, several repositioned drugs have been subjected to clinical investigations as anti-COVID-19 drugs. Here, in silico drug discovery tools were utilized to evaluate the binding affinities and features of eighteen anti-COVID-19 drug candidates against SARS-CoV-2 main protease (Mpro). Molecular docking calculations using Autodock Vina showed considerable binding affinities of the investigated drugs with docking scores ranging from - 5.3 to - 8.3 kcal/mol, with higher binding affinities for HIV drugs compared to the other antiviral drugs. Molecular dynamics (MD) simulations were performed for the predicted drug-Mpro complexes for 50 ns, followed by binding energy calculations utilizing molecular mechanics-generalized Born surface area (MM-GBSA) approach. MM-GBSA calculations demonstrated promising binding affinities of TMC-310911 and ritonavir towards SARS-CoV-2 Mpro, with binding energy values of - 52.8 and - 49.4 kcal/mol, respectively. Surpass potentialities of TMC-310911 and ritonavir are returned to their capabilities of forming multiple hydrogen bonds with the proximal amino acids inside Mpro's binding site. Structural and energetic analyses involving root-mean-square deviation, binding energy per-frame, center-of-mass distance, and hydrogen bond length demonstrated the stability of TMC-310911 and ritonavir inside the Mpro's active site over the 50 ns MD simulation. This study sheds light on HIV protease drugs as prospective SARS-CoV-2 Mpro inhibitors.

Natural-like products as potential SARS-CoV-2 Mpro inhibitors: in-silico drug discovery.

In December 2019, a COVID-19 epidemic was discovered in Wuhan, China, and since has disseminated around the world impacting human health for millions. Herein, in-silico drug discovery approaches have been utilized to identify potential natural products (NPs) as Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro) inhibitors. The MolPort database that contains over 100,000 NPs was screened and filtered using molecular docking techniques. Based on calculated docking scores, the top 5,000 NPs/natural-like products (NLPs) were selected and subjected to molecular dynamics (MD) simulations followed by molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations. Combined 50 ns MD simulations and MM-GBSA calculations revealed nine potent NLPs with binding affinities (ΔGbinding) > -48.0 kcal/mol. Interestingly, among the identified NLPs, four bis([1,3]dioxolo)pyran-5-carboxamide derivatives showed ΔGbinding > -56.0 kcal/mol, forming essential short hydrogen bonds with HIS163 and GLY143 amino acids via dioxolane oxygen atoms. Structural and energetic analyses over 50 ns MD simulation demonstrated NLP-Mpro complex stability. Drug-likeness predictions revealed the prospects of the identified NLPs as potential drug candidates. The findings are expected to provide a novel contribution to the field of COVID-19 drug discovery.Communicated by Ramaswamy H. Sarma.

Repurposing of FDA-approved antivirals, antibiotics, anthelmintics, antioxidants, and cell protectives against SARS-CoV-2 papain-like protease.

SARS-CoV-2 or Coronavirus disease 19 (COVID-19) is a rapidly spreading, highly contagious, and sometimes fatal disease for which drug discovery and vaccine development are critical. SARS-CoV-2 papain-like protease (PLpro) was used to virtually screen 1697 clinical FDA-approved drugs. Among the top results expected to bind with SARS-CoV-2 PLpro strongly were three cell protectives and antioxidants (NAD+, quercitrin, and oxiglutatione), three antivirals (ritonavir, moroxydine, and zanamivir), two antimicrobials (doripenem and sulfaguanidine), two anticancer drugs, three benzimidazole anthelmintics, one antacid (famotidine), three anti-hypertensive ACE receptor blockers (candesartan, losartan, and valsartan) and other miscellaneous systemically or topically acting drugs. The binding patterns of these drugs were superior to the previously identified SARS CoV PLpro inhibitor, 6-mercaptopurine (6-MP), suggesting a potential for repurposing these drugs to treat COVID-19. The objective of drug repurposing is the rapid relocation of safe and approved drugs by bypassing the lengthy pharmacokinetic, toxicity, and preclinical phases. The ten drugs with the highest estimated docking scores with favorable pharmacokinetics were subjected to molecular dynamics (MD) simulations followed by molecular mechanics/generalized Born surface area (MM/GBSA) binding energy calculations. Phenformin, quercetin, and ritonavir all demonstrated prospective binding affinities for COVID-19 PLpro over 50 ns MD simulations, with binding energy values of -56.6, -40.9, and -37.6 kcal/mol, respectively. Energetic and structural analyses showed phenformin was more stable than quercetin and ritonavir. The list of the drugs provided herein constitutes a primer for clinical application in COVID-19 patients and guidance for further antiviral studies.Communicated by Ramaswamy H. Sarma.