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 ΔG_binding 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.

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 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 (M^pro) inhibitor. In this study, a database containing 2017 flavone analogs was prepared and screened against SARS-CoV-2 M^pro using the molecular docking technique. According to the results, 371 flavone analogs exhibited good potency towards M^pro 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 M^pro. Compared to rutin, PubChem-129-716-607 and PubChem-885-071-27 showed better binding affinities against SARS-CoV-2 M^pro over 150 ns MD course with ΔG_binding 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 M^pro active site over 150 ns MD simulations. The oral bioavailabilities of probable SARS-CoV-2 M^pro 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.

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 (M^pro) 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 (ΔG_binding) > -48.0 kcal/mol. Interestingly, among the identified NLPs, four bis([1,3]dioxolo)pyran-5-carboxamide derivatives showed ΔG_binding > -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-M^pro 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.