Flavonoids from Pterogyne nitens as Zika virus NS2B-NS3 protease inhibitors

Although the widespread epidemic of Zika virus (ZIKV) and its neurological complications are well-known there are still no approved drugs available to treat this arboviral disease or vaccine to prevent the infection. Flavonoids from Pterogyne nitens have already demonstrated anti-flavivirus activity, although their target is unknown. In this study, we virtually screened an in-house database of 150 natural and semi-synthetic compounds against ZIKV NS2B-NS3 protease (NS2B-NS3p) using docking-based virtual screening, as part of the OpenZika project. As a result, we prioritized three flavonoids from P. nitens, quercetin, rutin and pedalitin, for experimental evaluation. We also used machine learning models, built with Assay Central® software, for predicting the activity and toxicity of these flavonoids. Biophysical and enzymatic assays generally agreed with the in silico predictions, confirming that the flavonoids inhibited ZIKV protease. The most promising hit, pedalitin, inhibited ZIKV NS2B-NS3p with an IC50 of 5 μM. In cell-based assays, pedalitin displayed significant activity at 250 and 500 µM, with slight toxicity in Vero cells. The results presented here demonstrate the potential of pedalitin as a candidate for hit-to-lead (H2L) optimization studies towards the discovery of antiviral drug candidates to treat ZIKV infections.

Pharmacoinformatics-based identification of transmembrane protease serine-2 inhibitors from Morus Alba as SARS-CoV-2 cell entry inhibitors

Transmembrane protease serine-2 (TMPRSS2) is a cell-surface protein expressed by epithelial cells of specific tissues including those in the aerodigestive tract. It helps the entry of novel coronavirus (n-CoV) or Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in the host cell. Successful inhibition of the TMPRSS2 can be one of the crucial strategies to stop the SARS-CoV-2 infection. In the present study, a set of bioactive molecules from Morus alba Linn. were screened against the TMPRSS2 through two widely used molecular docking engines such as Autodock vina and Glide. Molecules having a higher binding affinity toward the TMPRSS2 compared to Camostat and Ambroxol were considered for in-silico pharmacokinetic analyses. Based on acceptable pharmacokinetic parameters and drug-likeness, finally, five molecules were found to be important for the TMPRSS2 inhibition. A number of bonding interactions in terms of hydrogen bond and hydrophobic interactions were observed between the proposed molecules and ligand-interacting amino acids of the TMPRSS2. The dynamic behavior and stability of best-docked complex between TRMPRSS2 and proposed molecules were assessed through molecular dynamics (MD) simulation. Several parameters from MD simulation have suggested the stability between the protein and ligands. Binding free energy of each molecule calculated through MM-GBSA approach from the MD simulation trajectory suggested strong affection toward the TMPRSS2. Hence, proposed molecules might be crucial chemical components for the TMPRSS2 inhibition.

Structure-based inhibitor screening of natural products against NSP15 of SARS-CoV-2 revealed thymopentin and oleuropein as potent inhibitors

Coronaviruses are enveloped, non-segmented positive-sense RNA viruses with the largest genome among RNA viruses. Their genome contains a large replicase ORF which encodes nonstructural proteins (NSPs), structural, and accessory genes. NSP15 is a nidoviral RNA uridylate-specific endoribonuclease (NendoU) with C-terminal catalytic domain. The endoribonuclease activity of NSP15 interferes with the innate immune response of the host. Here, we screened Selleckchem Natural product database of the compounds against NSP15, and we found that thymopentin and oleuropein displayed highest binding energies. The binding of these molecules was further validated by molecular dynamic simulations that revealed them as very stable complexes. These drugs might serve as effective counter molecules in the reduction of virulence of this virus; may be more effective if treated in combination with replicase inhibitors. Future validation of both these inhibitors is worth the consideration for patients being treated for COVID-19.

Virtual screening and molecular dynamics simulation study of plant-derived compounds to identify potential inhibitors of main protease from SARS-CoV-2

The new coronavirus (SARS-CoV-2) halts the world economy and caused unbearable medical emergency due to high transmission rate and also no effective vaccine and drugs has been developed which brought the world pandemic situations. The main protease (Mpro) of SARS-CoV-2 may act as an effective target for drug development due to the conservation level. Herein, we have employed a rigorous literature review pipeline to enlist 3063 compounds from more than 200 plants from the Asian region. Therefore, the virtual screening procedure helps us to shortlist the total compounds into 19 based on their better binding energy. Moreover, the Prime MM-GBSA procedure screened the compound dataset further where curcumin, gartanin and robinetin had a score of (-59.439, -52.421 and - 47.544) kcal/mol, respectively. The top three ligands based on binding energy and MM-GBSA scores have most of the binding in the catalytic groove Cys145, His41, Met165, required for the target protein inhibition. The molecular dynamics simulation study confirms the docked complex rigidity and stability by exploring root mean square deviations, root mean square fluctuations, solvent accessible surface area, radius of gyration and hydrogen bond analysis from simulation trajectories. The post-molecular dynamics analysis also confirms the interactions of the curcumin, gartanin and robinetin in the similar binding pockets. Our computational drug designing approach may contribute to the development of drugs against SARS-CoV-2.

Identification of potential natural inhibitors of the receptor-binding domain of the SARS-CoV-2 spike protein using a computational docking approach

Background: The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the only zoonotic-origin CoV to reach the pandemic stage, to which neither an effective vaccine nor a specific therapy is available. The spike glycoprotein harbors the receptor-binding domain (RBD) that mediates the virus's entry to host cells. This study aimed to identify novel inhibitors that target the spike protein's RBD domain through computational screening of chemical and natural compounds. Method: The spike protein was modeled from the recently reported electron microscopy protein structure (PDB ID: 6VSB) and the previously described SARS-CoV protein structure (PDB ID: 6ACD and 6ACJ). Virtual lab bench CLC Drug Discovery was used to computationally screen for potential inhibitory effects of currently prescribed drugs (n = 22), natural antiviral drugs (n = 100), and natural compounds (n = 35032). Quantitative Structure-Activity Relationship (QSAR) studies were also performed to determine the leading binders known for their antiviral activity. Results: Among the drugs currently used to treat SARS-CoV2, hydroxychloroquine and favipiravir were identified as the best binders with an average of four H-bonds, with a binding affinity of - 36.66 kcal/mol and a minimum interaction energy of - 6.63 kcal/mol. In an evaluation of antiviral compounds, fosamprenavir and abacavir showed effective binding of five H-bonds, with an average binding affinity of - 18.75 kcal.mol- 1 and minimum interaction energy of - 3.57 kcal/mol. Furthermore, screening of 100 natural antiviral compounds predicted potential binding modes of glycyrrhizin, nepritin, punicalagin, epigallocatechin gallate, and theaflavin (average binding affinity of - 49.88 kcal/mol and minimum interaction energy of - 4.35 kcal/mol). Additionally, the study reports a list of 25 natural compounds that showed effective binding with an improved average binding affinity of - 51.46 kcal/mol. Conclusions: Using computational screening, we identified potential SARS-CoV-2 S glycoprotein inhibitors that bind to the RBD region. Using structure-based design and combination-based drug therapy, the identified molecules could be used to generate anti-SARS-CoV-2 drug candidates.

Identification of immucillin analogue natural compounds to inhibit Helicobacter pylori MTAN through high throughput virtual screening and molecular dynamics simulation

Abstract

One in every two humans is having Helicobacter pylori (H. pylori) in stomach causing gastric ulcer. Emergence of several drugs in eliminating H. pylori has paved way for emergence of multidrug resistance in them. This resistance is thriving and thereby necessitating the need of a potent drug. Identifying a potential target for medication is crucial. Bacterial 5'-methylthioadenosine/S-enosyl homocysteine nucleosidase (MTAN) is a multifunctional enzyme that controls seven essential metabolic pathways. It functions as a catalyst in the hydrolysis of the N-ribosidic bond of adenosine-based metabolites: S-adenosylhomocysteine (SAH), 5'-methylthioadenosine (MTA), 5'-deoxyadenosine (5'-DOA), and 6-amino-6-deoxyfutalosine. H. pylori unlike other bacteria and humans utilises an alternative pathway for menaquinone synthesis. It utilises Futosiline pathway for menaquinone synthesis which are obligatory component in electron transport pathway. Therefore, the enzymes functioning in this pathway represent them-self as a point of attack for new medications. We targeted MTAN protein of H. pylori to find out a potent natural hit to inhibit its growth. A comparative analysis was made with potent H. pylori MTAN (HpMTAN) known inhibitor, 5'-butylthio-DADMe-Immucillin-A (BuT-DADMe-ImmA) and ZINC natural subset database. Optimized ligands from the ZINC natural database were virtually screened using ligand based pharmacophore hypothesis to obtain the most efficient and potent inhibitors for HpMTAN. The screened leads were evaluated for their therapeutic likeness. Furthermore, the ligands that passed the test were subjected for MM-GBSA with MTAN to reveal the essential features that contributes selectivity. The results showed that Van der Waals contributions play a central role in determining the selectivity of MTAN. Molecular dynamics (MD) studies were carried out for 100 ns to assess the stability of ligands in the active site. MD analysis showed that binding of ZINC00490333 with MTAN is stable compared to reference inhibitor molecule BuT-DADMe-ImmA. Among the natural inhibitors screened after various docking procedures ZINC00490333 has highest binding score for HpMTAN (- 13.987). The ZINC inhibitor was successful in reproducing the BuT-DADMe-ImmA interactions with HpMTAN. Hence we suggest that ZINC00490333 compound may represent as a good lead in designing novel potent inhibitors of HpMTAN. This in silico approach indicates the potential of this molecule for advancing a further step in gastric ulcer treatment.

Graphic abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-021-00081-2.

Screening of SIRT6 inhibitors and activators: A novel activator has an impact on breast cancer cells

Sirtuin 6 (SIRT6), a member of sirtuin family (SIRT1-7), regulates a variety of cellular processes involved in aging, metabolism, and cancer. Dysregulation of SIRT6 is widely observed in different breast cancer subtypes; however, the role and function of SIRT6 in cancer development remain largely unexplored. The aim of this study was to identify novel compounds targeting SIRT6 which may provide a new approach in development of anti-cancer therapy for breast cancer. Virtual screening was utilized to discover potential compounds targeting SIRT6 for in vitro screening. In addition, novel 1,4-dihydropyridine derivatives were synthetized and further subjected for the screening. The impact of the compounds on the deacetylation activity of SIRT6 was determined with HPLC method. The anti-cancer activities were screened for a panel of breast cancer cells. A set of 1,4-dihydropyridine derivatives was identified as SIRT6 inhibitors. A SIRT6 activating compound, (2,4-dihydroxy-phenyl)-2-oxoethyl 2-(3-methyl-4-oxo-2-phenyl-4H-chromen-8-yl)acetate (later called as 4H-chromen), was discovered and it provided 30-40-fold maximal activation. 4H-chromen was proposed to bind similarly to quercetin and place to previously reported SIRT6 activator sites. 4H-chromen was investigated in various breast cancer cells, and it decreased cell proliferation in all cells as well as arrested cell cycle in triple negative cells. Overall, this study describes a highly potent SIRT6 activator and new inhibitors that represent a novel tool to study the mechanism of SIRT6 function.

Identification of new 3-phenyl-1H-indole-2-carbohydrazide derivatives and their structure-activity relationships as potent tubulin inhibitors and anticancer agents: A combined in silico, in vitro and synthetic study

Virtual screening of commercially available molecular entities by using CDRUG, structure-based virtual screening, and similarity identified eight new derivatives of 3-phenyl-1H-indole-2-carbohydrazide with anti-proliferative activities. The molecules were tested experimentally for inhibition of tubulin polymerisation, which revealed furan-3-ylmethylene-3-phenyl-1H-indole-2-carbohydrazide (27a) as the most potent candidate. Molecule 27a was able to induce G2/M phase arrest in A549 cell line, similar to other tubulin inhibitors. Synthetic modifications of 27a were focussed on small substitutions on the furan ring, halogenation at R₁ position and alteration of furyl connectivity. Derivatives 27b, 27d and 27i exhibited the strongest tubulin inhibition activities and were comparable to 27a. Bromine substitution at R₁ position showed most prominent anticancer activities; derivatives 27b-27d displayed the strongest activities against HuCCA-1 cell line and were more potent than doxorubicin and the parent molecule 27a with IC₅₀ values <0.5 μM. Notably, 27b with a 5-methoxy substitution on furan displayed the strongest activity against HepG2 cell line (IC₅₀ = 0.34 µM), while 27d displayed stronger activity against A549 cell line (IC₅₀ = 0.43 µM) compared to doxorubicin and 27a. Fluorine substitutions at the R₁ position tended to show more modest anti-tubulin and anticancer activities, and change of 2-furyl to 3-furyl was tolerable. The new derivatives, thiophenyl 26, displayed the strongest activity against A549 cell line (IC₅₀ = 0.19 µM), while 1-phenylethylidene 21b and 21c exhibited more modest anticancer activities with unclear mechanisms of action; 26 and 21c demonstrated G2/M phase arrest, but showed weak tubulin inhibitory properties. Molecular docking suggests the series inhibit tubulin at the colchicine site, in agreement with the experimental findings. The calculated molecular descriptors indicated that the molecules obey Lipinski's rule which suggests the molecules are drug-like structures.

Metadynamics-based enhanced sampling protocol for virtual screening: case study for 3CLpro protein for SARS-CoV-2

In recent times, computational methods played an important role in the down selection of chemical compounds, which could be a potential drug candidate with a high affinity to target proteins. However, the screening methodologies, including docking, often fails to identify the most effective compound, which could be a ligand for the target protein. To solve that, here we have integrated meta-dynamics, an enhanced sampling molecular simulation method, with all-atom molecular dynamics to determine a specific compound that could target the main protease of novel severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). This combined computational approach uses the enhanced sampling to explore the free energy surface associated with the protein's binding site (including the ligand) in an explicit solvent. We have implemented this method to find new chemical entities that exhibit high specificity of binding to the 3-chymotrypsin-like cysteine protease (3CLpro) present in the SARS-CoV-2 and segregated to the most strongly bound ligands based on free energy and scoring functions (defined and implemented) from a set of 17 ligands which were prescreened for synthesizability and druggability. Additionally, we have compared these 17 ligands' affinities against controls, N3 and 13b α-ketoamide inhibitors, for which experimental crystal structures are available. Based on our results and analysis from the combined molecular simulation approach, we could identify the best compound which could be further taken as a potential candidate for experimental validation.Communicated by Ramaswamy H. Sarma.

Structure-based identification of dual ligands at the A2AR and PDE10A with anti-proliferative effects in lung cancer cell-lines

Enhanced/prolonged cAMP signalling has been suggested as a suppressor of cancer proliferation. Interestingly, two key modulators that elevate cAMP, the A2A receptor (A2AR) and phosphodiesterase 10A (PDE10A), are differentially co-expressed in various types of non-small lung cancer (NSCLC) cell-lines. Thus, finding dual-target compounds, which are simultaneously agonists at the A2AR whilst also inhibiting PDE10A, could be a novel anti-proliferative approach. Using ligand- and structure-based modelling combined with MD simulations (which identified Val84 displacement as a novel conformational descriptor of A2AR activation), a series of known PDE10A inhibitors were shown to dock to the orthosteric site of the A2AR. Subsequent in-vitro analysis confirmed that these compounds bind to the A2AR and exhibit dual-activity at both the A2AR and PDE10A. Furthermore, many of the compounds exhibited promising anti-proliferative effects upon NSCLC cell-lines, which directly correlated with the expression of both PDE10A and the A2AR. Thus, we propose a structure-based methodology, which has been validated in in-vitro binding and functional assays, and demonstrated a promising therapeutic value.

A computational drug repurposing approach in identifying the cephalosporin antibiotic and anti-hepatitis C drug derivatives for COVID-19 treatment

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused over 1.4 million deaths worldwide. Repurposing existing drugs offers the fastest opportunity to identify new indications for existing drugs as a stable solution against coronavirus disease 2019 (COVID-19). The SARS-CoV-2 main protease (Mpro) is a critical target for designing potent antiviral agents against COVID-19. In this study, we identify potential inhibitors against COVID-19, using an amalgam of virtual screening, molecular dynamics (MD) simulations, and binding-free energy approaches from the Korea Chemical Bank drug repurposing (KCB-DR) database. The database screening of KCB-DR resulted in 149 binders. The dynamics of protein-drug complex formation for the seven top scoring drugs were investigated through MD simulations. Six drugs showed stable binding with active site of SARS-CoV-2 Mpro indicated by steady RMSD of protein backbone atoms and potential energy profiles. Furthermore, binding free energy calculations suggested the community-acquired bacterial pneumonia drug ceftaroline fosamil and the hepatitis C virus (HCV) protease inhibitor telaprevir are potent inhibitors against Mpro. Molecular dynamics and interaction analysis revealed that ceftaroline fosamil and telaprevir form hydrogen bonds with important active site residues such as Thr24, Thr25, His41, Thr45, Gly143, Ser144, Cys145, and Glu166 that is supported by crystallographic information of known inhibitors. Telaprevir has potential side effects, but its derivatives have good pharmacokinetic properties and are suggested to bind Mpro. We suggest the telaprevir derivatives and ceftaroline fosamil bind tightly with SARS-CoV-2 Mpro and should be validated through preclinical testing.

Design, synthesis and biological evaluation of pyrazolo[3,4-d]pyridazinone derivatives as covalent FGFR inhibitors

Fibroblast growth factor receptors (FGFRs) have emerged as promising targets for anticancer therapy. In this study, we synthesized and evaluated the biological activity of 66 pyrazolo[3,4-d]pyridazinone derivatives. Kinase inhibition, cell proliferation, and whole blood stability assays were used to evaluate their activity on FGFR, allowing us to explore structure−activity relationships and thus to gain understanding of the structural requirements to modulate covalent inhibitors’ selectivity and reactivity. Among them, compound 10h exhibited potent enzymatic activity against FGFR and remarkably inhibited proliferation of various cancer cells associated with FGFR dysregulation, and suppressed FGFR signaling pathway in cancer cells by the immunoblot analysis. Moreover, 10h displayed highly potent antitumor efficacy (TGI = 91.6%, at a dose of 50 mg/kg) in the FGFR1-amplified NCI-H1581 xenograft model.

Structural analogues of existing anti-viral drugs inhibit SARS-CoV-2 RNA dependent RNA polymerase: A computational hierarchical investigation

The Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) became a pandemic, resulting in an exponentially increased mortality globally and scientists all over the world are struggling to find suitable solutions to combat it. Multiple repurposed drugs have already been in several clinical trials or recently completed. However, none of them shows any promising effect in combating COVID-19. Therefore, developing an effective drug is an unmet global need. RdRp (RNA dependent RNA polymerase) plays a pivotal role in viral replication. Therefore, it is considered as a prime target of drugs that may treat COVID-19. In this study, we have screened a library of compounds, containing approved RdRp inhibitor drugs that were or in use to treat other viruses (favipiravir, sofosbuvir, ribavirin, lopinavir, tenofovir, ritonavir, galidesivir and remdesivir) and their structural analogues, in order to identify potential inhibitors of SARS-CoV-2 RdRp. Extensive screening, molecular docking and molecular dynamics show that five structural analogues have notable inhibitory effects against RdRp of SARS-CoV-2. Importantly, comparative protein-antagonists interaction revealed that these compounds fit well in the pocket of RdRp. ADMET analysis of these compounds suggests their potency as drug candidates. Our identified compounds may serve as potential therapeutics for COVID-19.

Identification of Plasmodium falciparum heat shock 90 inhibitors via molecular docking

A virtual screen was performed to identify anti-malarial compounds targeting Plasmodium falciparum heat shock 90 protein by applying a series of drug-like and commercial availability filters to compounds in the ZINC database, resulting in a virtual library of more than 13 million candidates. The goal of the virtual screen was to identify novel compounds which could serve as a starting point for the development of antimalarials with a mode of action different from anything currently used in the clinic. The screen targeted the ATP binding pocket of the highly conserved Plasmodium heat shock 90 protein, as this protein is critical to the survival of the parasite and has several significant structural differences from the human homolog. The top twelve compounds from the virtual screen were tested in vitro, with all twelve showing no antiproliferative activity against the human fibroblast cell line and three compounds exhibiting single digit or better micromolar antiproliferative activity against the chloroquine-sensitive P. falciparum 3D7 strain.

Identification of novel EED-EZH2 PPI inhibitors using an in silico fragment mapping method

Enhancer of zeste homolog 2 (EZH2) is a histone lysine methyltransferase that is overexpressed in many cancers. Numerous EZH2 inhibitors have been developed as anticancer agents, but recent studies have also focused on protein-protein interaction (PPI) between embryonic ectoderm development (EED) and EZH2 as a novel drug discovery target. Because EED indirectly enhances EZH2 enzymatic activity, EED-EZH2 PPI inhibitors suppress the methyltransferase activity and inhibit cancer growth. By contrast to the numerous promising EZH2 inhibitors, there are a paucity of EED-EZH2 PPI inhibitors reported in the literature. Here, we aimed to discover novel EED-EZH2 PPI inhibitors by first identifying possible binders of EED using an in-house knowledge-based in silico fragment mapping method. Next, 3D pharmacophore models were constructed from the arrangement pattern of the potential binders mapped onto the EED surface. In all, 16 compounds were selected by 3D pharmacophore-based virtual screening followed by docking-based virtual screening. In vitro evaluation revealed that five of these compounds exhibited inhibitory activities. This study has provided structural insights into the discovery and the molecular design of novel EED-EZH2 PPI inhibitors using an in silico fragment mapping method.

Discovery of novel inhibitors against main protease (Mpro) of SARS-CoV-2 via virtual screening and biochemical evaluation

SARS-CoV-2 is the pathogen that caused the global COVID-19 outbreak in 2020. Promising progress has been made in developing vaccines and antiviral drugs. Antivirals medicines are necessary complements of vaccines for post-infection treatment. The main protease (Mpro) is an extremely important protease in the reproduction process of coronaviruses which cleaves pp1ab over more than 11 cleavage sites. In this work, two active main protease inhibitors were found via docking-based virtual screening and bioassay. The IC₅₀ of compound VS10 was 0.20 μM, and the IC₅₀ of compound VS12 was 1.89 μM. The finding in this work can be helpful to understand the interactions of main protease and inhibitors. The active candidates could be potential lead compounds for future drug design.

An integrated virtual screening of compounds from Carica papaya leaves against multiple protein targets of SARS-Coronavirus-2

The pandemic of SARS-Coronavirus-2 (Coronavirus-19) has been progressing by the increasing trend of the cases as well as deaths with neither vaccine nor drug is rationally used to stop the viral spread over. This study aims to perform an integrated virtual screening of compounds that had been identified from Carica papaya leaves, which are proposed to be a herbal treatment for SARS-Coronavirus-2. The screening was initiated by evaluating the 40 compounds from Carica papaya leaves for their drug-like likeness property. The selected compounds were then secondly screened using carcinogenic and toxicity filters. Further selected compounds were thirdly screened for their pharmacokinetic profile and the screening was lastly performed by docking the third selected compounds against multiple protein targets of SARS-Coronavirus-2 employing 3-chymotrypsin-like protease (3CLpro), papain-like protease (PLpro), RNA-dependent-RNA-polymerase (RdRp), endonuclease (EndoU), S1 and S2 region of spike protein. The results show that 20 of 40 compounds, which meet the requirements of drug-like likeness, carcinogenicity-toxicity filter, and pharmacokinetic profiles, can interact with the multiple protein targets of SARS-Coronavirus-2 with the order from high to low affinity as follows: S1 > 3CLpro > EndoU > RdRp > PLpro > S2. In conclusion, Carica papaya leaves are worth to be proposed for further in vitro study against SARS-Coronavirus-2 at both molecular and cellular levels.

Docking-based virtual screening studies aiming at the covalent inhibition of SARS-CoV-2 MPro by targeting the cysteine 145

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the COVID-19 which has infected millions of people worldwide. The main protease of SARS-CoV-2 (M^Pro) has been recognized as a key target for the development of antiviral compounds. Taking advantage of the X-ray crystal complex with reversible covalent inhibitors interacting with the catalytic cysteine 145 (Cys145), we explored flexible docking studies to select alternative compounds able to target this residue as covalent inhibitors. First, docking studies of three known electrophilic compounds led to results consistent with co-crystallized data validating the method for SARS-CoV-2 M^Pro covalent inhibition. Then, libraries of soft electrophiles (overall 41 757 compounds) were submitted to docking-based virtual screening resulting in the identification of 17 molecules having their electrophilic group close to the Cys145 residue. We also investigated flexible docking studies of a focused approved covalent drugs library including 32 compounds with various electrophilic functional groups. Among them, the calculations resulted in the identification of four compounds, namely dimethylfumarate, fosfomycin, ibrutinib and saxagliptin, able first, to bind to the active site of the protein and second, to form a covalent bond with the catalytic cysteine.

Incorporating structural similarity into a scoring function to enhance the prediction of binding affinities

In this study, we developed a novel algorithm to improve the screening performance of an arbitrary docking scoring function by recalibrating the docking score of a query compound based on its structure similarity with a set of training compounds, while the extra computational cost is neglectable. Two popular docking methods, Glide and AutoDock Vina were adopted as the original scoring functions to be processed with our new algorithm and similar improvement performance was achieved. Predicted binding affinities were compared against experimental data from ChEMBL and DUD-E databases. 11 representative drug receptors from diverse drug target categories were applied to evaluate the hybrid scoring function. The effects of four different fingerprints (FP2, FP3, FP4, and MACCS) and the four different compound similarity effect (CSE) functions were explored. Encouragingly, the screening performance was significantly improved for all 11 drug targets especially when CSE = S⁴ (S is the Tanimoto structural similarity) and FP2 fingerprint were applied. The average predictive index (PI) values increased from 0.34 to 0.66 and 0.39 to 0.71 for the Glide and AutoDock vina scoring functions, respectively. To evaluate the performance of the calibration algorithm in drug lead identification, we also imposed an upper limit on the structural similarity to mimic the real scenario of screening diverse libraries for which query ligands are general-purpose screening compounds and they are not necessarily structurally similar to reference ligands. Encouragingly, we found our hybrid scoring function still outperformed the original docking scoring function. The hybrid scoring function was further evaluated using external datasets for two systems and we found the PI values increased from 0.24 to 0.46 and 0.14 to 0.42 for A2AR and CFX systems, respectively. In a conclusion, our calibration algorithm can significantly improve the virtual screening performance in both drug lead optimization and identification phases with neglectable computational cost.

Novel α-amylase and α-glucosidase inhibitors from selected Nigerian antidiabetic plants: an in silico approach

This study aimed to identify novel α-amylase and α-glucosidase inhibitors from Nigerian antidiabetic plants through in silico approach. Virtual screening of the 93 phytoconstituents was performed, and their inhibitory potentials were ranked based on their docking scores. Five hit molecules were selected for each enzyme target with their hydrogen bonding, hydrophobic, electrostatic, and pi interactions analyzed with discovery studio visualizer. The drug-likeness and ADMET studies of the hit molecules were performed to ascertain their druggability properties. Further, three top-ranked hit molecules were subjected to molecular dynamics simulations. The virtual screening, drug-likeness property, and ADMET studies, and molecular dynamics simulations carried out reveal Newbouldiaquinone A, Foetidin, Chamuvaritin, Cajaflavanone, and Azadirolic acid as potential inhibitors of α-amylase while Chamuvaritin, Newbouldiaquinone A, Flowerone, Scoparic acid A and Nimonol were potential inhibitors of α-glucosidase enzyme.Communicated by Ramaswamy H. Sarma.

Discovery of a novel potent cytochrome P450 CYP4Z1 inhibitor

Human cytochrome P450 enzyme CYP4Z1 represents a promising target for the treatment of a multitude of malignancies including breast cancer. The most active known non-covalent inhibitor (1-benzylimidazole) only shows low micromolar affinity to CYP4Z1. We report a new, highly active inhibitor for CYP4Z1 showing confirmed binding in an enzymatic assay and an IC₅₀ value of 63 ± 19 nM in stably transfected MCF-7 cells overexpressing CYP4Z1. The new inhibitor was identified by a systematically developed virtual screening protocol. Binding was rationalized using a carefully elaborated 3D pharmacophore hypothesis and thoroughly characterized using extensive molecular dynamics simulations and dynamic 3D pharmacophore (dynophore) analyses. This novel inhibitor represents a valuable pharmacological tool to accelerate characterization of the still understudied CYP4Z1 and might pave the way for a new treatment strategy in CYP4Z1-associated malignancies. The presented in silico model for predicting CYP4Z1 interaction provides novel mechanistic insights and revealed that the drug ozagrel interacts with CYP4Z1.

Targeting C-terminal Helical bundle of NCOVID19 Envelope (E) protein

One of the most crucial characteristic traits of Envelope (E) proteins in the severe acute respiratory syndrome SARS-CoV-1 and NCOVID19 viruses is their membrane-associated oligomerization led ion channel activity, virion assembly, and replication. NMR spectroscopic structural studies of envelope proteins from both the SARS CoV-1/2 reveal that this protein assembles into a homopentamer. Proof of concept studies via truncation mutants on either transmembrane (VFLLV), glycosylation motif (CACCN), hydrophobic helical bundle (PVYVY) as well as replacing C-terminal "DLLV" segments or point mutants such as S68, E69 residues with cysteine have significantly reduced viral titers of SARS-CoV-1. In this present study, we have first developed SARS-2 E protein homology model based on the pentamer coordinates of SARS-CoV-1 E protein (86.4% structural identity) with good stereochemical quality. Next, we focused on the glycosylation motif and hydrophobic helical bundle regions of E protein shown to be important for viral replication. A four feature (4F) model comprising of an acceptor targeting S60 hydroxyl group, a donor feature anchoring the C40 residue, and two hydrophobic features anchoring the V47 L28, L31, Y55, and P51 residues formed the protein based pharmacophore model targeting the glycosylation motif and helical bundle of E protein. Database screening with this 4F protein pharmacophore, ADMET property filtering on enamine small molecule discovery collection yielded a focused library of ~7000 hits. Further molecular docking and visual inspection of docked pose interactions at the above mention V47 L28, L31, Y55, P51, S60, C40 residues led to the identification of 10 best hits. Our STD NMR binding assay results demonstrate that the ligand 3, 2-(2-amino-2-oxo-ethoxy)-N-benzyl-benzamide, binds to NCOVID19 E protein with a binding affinity (K_D) of 141.7 ± 13.6 μM. Furthermore, the ligand 3 also showed binding to C-terminal peptide (NR25) as evidenced with the STD spectrums of wild type E protein would serve to confirm the involvement of C-terminal helical bundle as envisaged in this study.

ASFP (Artificial Intelligence based Scoring Function Platform): a web server for the development of customized scoring functions

Virtual screening (VS) based on molecular docking has emerged as one of the mainstream technologies of drug discovery due to its low cost and high efficiency. However, the scoring functions (SFs) implemented in most docking programs are not always accurate enough and how to improve their prediction accuracy is still a big challenge. Here, we propose an integrated platform called ASFP, a web server for the development of customized SFs for structure-based VS. There are three main modules in ASFP: (1) the descriptor generation module that can generate up to 3437 descriptors for the modelling of protein–ligand interactions; (2) the AI-based SF construction module that can establish target-specific SFs based on the pre-generated descriptors through three machine learning (ML) techniques; (3) the online prediction module that provides some well-constructed target-specific SFs for VS and an additional generic SF for binding affinity prediction. Our methodology has been validated on several benchmark datasets. The target-specific SFs can achieve an average ROC AUC of 0.973 towards 32 targets and the generic SF can achieve the Pearson correlation coefficient of 0.81 on the PDBbind version 2016 core set. To sum up, the ASFP server is a powerful tool for structure-based VS.

Virtual screening of phytochemical compounds as potential inhibitors against SARS-CoV-2 infection

Background

The present pandemic situation due to coronavirus has led to the search for newer prevention, diagnostic, and treatment methods. The onset of the corona infection in a human results in acute respiratory illness followed by death if not diagnosed and treated with suitable antiretroviral drugs. With the unavailability of the targeted drug treatment, several repurposed drugs are being used for treatment. However, the side-effects of the drugs urges us to move to a search for newer synthetic- or phytochemical-based drugs. The present study investigates the use of various phytochemicals virtually screened from various plant sources in Western Ghats, India, and subsequently molecular docking studies were performed to identify the efficacy of the drug in retroviral infection particularly coronavirus infection.

Results

Out of 57 phytochemicals screened initially based on the structural and physicochemical properties, 39 were effectively used for the docking analysis. Finally, 5 lead compounds with highest hydrophobic interaction and number of H-bonds were screened. Results from the interaction analysis suggest Piperolactam A to be pocketed well with good hydrophobic interaction with the residues in the binding region R1. ADME and toxicity profiling also reveals Piperolactam A with higher LogS values indicating higher permeation and hydrophilicity. Toxicity profiling suggests that the 5 screened compounds to be relatively safe.

Conclusion

The in silico methods used in this study suggests that the compound Piperolactam A to be the most effective inhibitor of S-protein from binding to the GRP78 receptor. By blocking the binding of the S-protein to the CS-GRP78 cell surface receptor, they can inhibit the binding of the virus to the host.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43088-021-00095-x.