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Graphic Abstract 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. Supplementary information The online version of this article (10.1007/s10930-020-09945-6) contains supplementary material, which is available to authorized users.

Herein, the DrugBank database which contains 10,036 approved and investigational drugs was explored deeply for potential drugs that target SARS-CoV-2 main protease (Mpro). Filtration process of the database was conducted using three levels of accuracy for molecular docking calculations. The top 35 drugs with docking scores > −11.0 kcal/mol were then subjected to 10 ns molecular dynamics (MD) simulations followed by molecular mechanics–generalized Born surface area (MM-GBSA) binding energy calculations. The results showed that DB02388 and Cobicistat (DB09065) exhibited potential binding affinities towards Mpro over 100 ns MD simulations, with binding energy values of −49.67 and −46.60 kcal/mol, respectively. Binding energy and structural analyses demonstrated the higher stability of DB02388 over Cobicistat. The potency of DB02388 and Cobicistat is attributed to their abilities to form several hydrogen bonds with the essential amino acids inside the active site of Mpro. Compared to DB02388 and Cobicistat, Darunavir showed a much lower binding affinity of −34.83 kcal/mol. The present study highlights the potentiality of DB02388 and Cobicistat as anti-COVID-19 drugs for clinical trials. Communicated by Ramaswamy H. Sarma., Graphical Abstract

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

Two sesquiterpenes, 8α-anisate-dauc-4-ene-3,9-dione (webiol anisate) (1) and 10α-acetoxy-6α-benzoate-jaeschkeanadiol (2) as well as, ten known analogues (3–10), and two sesquiterpene coumarins (11–12) were isolated from an organic root extract of Ferula vesceritensis (Fam. Apiaceae). Chemical structures were elucidated based on IR, 1D- and 2D-NMR and HRMS, spectroscopic analyses. With molecular overlap observed between two protease inhibitors that are being examined as anti-COVID-19 drugs, and sesquiterpenes isolated here, metabolite molecular docking calculations were made using the main protease (Mpro), which is required for viral multiplication as well as RNA-dependent RNA polymerase (RdRp). In silico binding-inhibition analysis predicted that select F. vesceritensis sesquiterpenes can bind to these enzymes required for viral replication. Structures of the isolated constituents were also consistent with the chemo-systematic grouping of F. vesceritensis secondary metabolites with other Ferula species.

Penicillin-binding proteins (PBPs) catalyze the final stages for peptidoglycan cell-wall bio-synthesis. Mutations in the PBP2a subunit can attenuate β-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 β-lactam inhibitors, however, (E)-3-(2-(4-cyanostyryl)-4-oxoquinazolin-3(4H)-yl) benzoic acid (QNZ), a heterocyclic antibiotic devoid of a β-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.

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 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

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

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., Graphical abstract Image 1

The current study was set to discover selective Plasmodium falciparum phosphatidylinositol-4-OH kinase type III beta (pfPI4KB) inhibitors as potential antimalarial agents using combined structure-based and ligand-based drug discovery approach. A comparative model of pfPI4KB was first constructed and validated using molecular docking techniques. Performance of Autodock4.2 and Vina4 software in predicting the inhibitor-PI4KB binding mode and energy was assessed based on two Test Sets: Test Set I contained five ligands with resolved crystal structures with PI4KB, while Test Set II considered eleven compounds with known IC50 value towards PI4KB. The outperformance of Autodock as compared to Vina was reported, giving a correlation coefficient (R2) value of 0.87 and 0.90 for Test Set I and Test Set II, respectively. Pharmacophore-based screening was then conducted to identify drug-like molecules from ZINC database with physicochemical similarity to two potent pfPI4KB inhibitors –namely cpa and cpb. For each query inhibitor, the best 1000 hits in terms of TanimotoCombo scores were selected and subjected to molecular docking and molecular dynamics (MD) calculations. Binding energy was then estimated using molecular mechanics–generalized Born surface area (MM-GBSA) approach over 50 ns MD simulations of the inhibitor-pfPI4KB complexes. According to the calculated MM-GBSA binding energies, ZINC78988474 and ZINC20564116 were identified as potent pfPI4KB inhibitors with binding energies better than those of cpa and cpb, with ΔGbinding ≥ −34.56 kcal/mol. The inhibitor-pfPI4KB interaction and stability were examined over 50 ns MD simulation; as well the selectivity of the identified inhibitors towards pfPI4KB over PI4KB was reported.