Multiple virtual screening approaches for finding new hepatitis C virus RNA-dependent RNA polymerase inhibitors: structure-based screens and molecular dynamics for the pursue of new poly pharmacological inhibitors

Virtual screening approach for the discovery of selective 5α-reductase type II inhibitors for benign prostatic hyperplasia treatment

Background: 5α-Reductase type II (5αR2) inhibition is a promising strategy for benign prostatic hyperplasia treatment. A computational approach including virtual screening, ligand-based 3D pharmacophore modeling, 2D quantitative structure-activity relationship and molecular docking simulations were adopted to develop novel inhibitors. Results: Hits were first filtered via the validated pharmacophore and 2D quantitative structure-activity relationship models. Docking on the recently determined cocrystallized structure of 5αR2 showed three promising hits. Visual inspection results were compared with finasteride ligand and dihydrotestosterone as reference, to explain the role of binding to Glu57 and Tyr91 for 5αR2 selective inhibition. Conclusion: Alignment between Hit 2 and finasteride in the binding pocket showed similar binding modes. The biological activity prediction showed antitumor and androgen targeting activity of the new hits.

An Exploration of the Inhibitory Mechanism of Rationally Screened Benzofuran-1,3,4-Oxadiazoles and-1,2,4-Triazoles as Inhibitors of NS5B RdRp Hepatitis C Virus through Pharmacoinformatic Approaches

Benzofuran, 1,3,4-oxadiazole, and 1,2,4-triazole are privileged heterocyclic moieties that display the most promising and wide spectrum of biological activities against a wide variety of diseases. In the current study, benzofuran-1,3,4-oxadiazole BF1-BF7 and benzofuran-1,2,4-triazole compounds BF8-BF15 were tested against HCV NS5B RNA-dependent RNA polymerase (RdRp) utilizing structure-based screening via a computer-aided drug design (CADD) approach. A molecular docking approach was applied to evaluate the binding potential of benzofuran-appended 1,3,4-oxadiazole and 1,2,4-triazole BF1-BF15 molecules. Benzofuran-1,3,4-oxadiazole scaffolds BF1-BF7 showed lesser binding affinities (-12.63 to -14.04 Kcal/mol) than benzofuran-1,2,4-triazole scaffolds BF8-BF15 (-14.11 to -16.09 Kcal/mol) against the HCV NS5B enzyme. Molecular docking studies revealed the excellent binding affinity scores exhibited by benzofuran-1,2,4-triazole structural motifs BF-9 (-16.09 Kcal/mol), BF-12 (-15.75 Kcal/mol), and BF-13 (-15.82 Kcal/mol), respectively, which were comparatively better than benzofuran-based HCV NS5B inhibitors' standard reference drug Nesbuvir (-15.42 Kcal/mol). A molecular dynamics simulation assay was also conducted to obtain valuable insights about the enzyme-compounds interaction profile and structural stability, which indicated the strong intermolecular energies of the BF-9+NS5B complex and the BF-12+NS5B complex as per the MM-PBSA method, while the BF-12+NS5B complex was the most stable system as per the MM-GBSA calculation. The drug-likeness and ADMET studies of all the benzofuran-1,2,4-triazole derivatives BF8-BF15 revealed that these compounds possessed good medicinal chemistry profiles in agreement with all the evaluated parameters for being drugs. The molecular docking affinity scores, MM-PBSA/MM-GBSA and MD-simulation stability analysis, drug-likeness profiling, and ADMET study assessment indicated that N-4-fluorophenyl-S-linked benzofuran-1,2,4-triazole BF-12 could be a future promising anti-HCV NS5B RdRp inhibitor therapeutic drug candidate that has a structural agreement with the Nesbuvir standard reference drug.

In-silico screening of naturally derived phytochemicals against SARS-CoV Main protease

Coronavirus disease 2019 (COVID-19) is a rapidly growing pandemic that requires urgent therapeutic intervention. Finding potential anti COVID-19 drugs aside from approved vaccines is progressively going on. The chemically diverse natural products represent valuable sources for drug leads. In this study, we aimed to find out safe and effective COVID-19 protease inhibitors from a library of natural products which share the main nucleus/skeleton of FDA-approved drugs that were employed in COVID-19 treatment guidelines or repurposed by previous studies. Our library was subjected to virtual screening against SARS-CoV Main protease (Mpro) using Molecular Operating Environment (MOE) software. Twenty-two out of those natural candidates showed higher binding scores compared to their analogues. We repurpose these natural products including alkaloids, glucosinolates, and phenolics as potential platforms for the development of anti-SARS-CoV-2 therapeutics. This study paves the way towards discovering a lead used in the treatment of COVID-19 from natural sources and introduces phytomedicines with dual therapeutic effects against COVID-19 besides their original pharmacological effects. We recommend further in vitro evaluation of their anti-COVID-19 activity and future clinical studies.

In silico screening of potent inhibitors against COVID-19 key targets from a library of FDA-approved drugs

Coronavirus disease (COVID-19) is an emerging pandemic that threatens the world since the early days of 2020. Development of vaccines or new drugs against COVID-19 comprises several stages of investigation including efficacy, safety, and approval studies. A shortcut to this delicate pathway is computational-based analysis of FDA-approved drugs against assigned molecular targets of the coronavirus. In this study, we virtually screened a library of FDA-approved drugs prescribed for different therapeutic purposes against versatile COVID-19 specific proteins which are crucial for the virus life cycle. Three antibiotics in our screening polymyxin B, bafilomycin A, and rifampicin show motivating binding stability with more than one target of the virus. Another category of tested drugs is oral antiseptics of mouth rinsing solutions that unexpectedly exhibited significant affinity to the target proteins employed by the virus for attachment and cell internalization. Other OTC drugs widely used and tested in our study are heartburn drugs and they show no significant binding. We tested also some other drugs falling under the scope of investigation regarding interference with a degree of severity of COVID-19 like angiotensin II blockers used as antihypertensive, and our study suggests a therapeutic rather than predisposing effect of these drugs against COVID-19.

In silico screening of potent bioactive compounds from honeybee products against COVID-19 target enzymes

After the early advent of the Coronavirus Disease 2019 (COVID-19) pandemic, myriads of FDA-approved drugs have been massively repurposed for COVID-19 treatment based on molecular docking against selected protein targets that play fundamental roles in the replication cycle of the novel coronavirus. Honeybee products are well known of their nutritional values and medicinal effects. Bee products contain bioactive compounds in the form of a collection of phenolic acids, flavonoids, and terpenes of natural origin that display wide spectrum antiviral effects. We revealed by molecular docking the profound binding affinity of 14 selected phenolics and terpenes present in honey and propolis (bees glue) against the main protease (Mpro) and RNA-dependent RNA polymerase (RdRp) enzymes of the novel SARS-CoV-2 virus (the causative agent of COVID-19) using AutoDock Vina software. Of these compounds, p-coumaric acid, ellagic acid, kaempferol, and quercetin have the strongest interaction with the SARS-CoV-2 target enzymes, and it may be considered an effective COVID-19 inhibitor.

Computational selection of flavonoid compounds as inhibitors against SARS-CoV-2 main protease, RNA-dependent RNA polymerase and spike proteins: A molecular docking study

An outbreak of Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 has been recognized as a global health concern. Since, no specific antiviral drug is proven effective for treatment against COVID-19, identification of new therapeutics is an urgent need. In this study, flavonoid compounds were analyzed for its inhibitory potential against important protein targets of SARS-CoV-2 using computational approaches. Virtual docking was performed for screening of flavonoid compounds retrieved from PubChem against the main protease of SARS-CoV-2 using COVID-19 docking server. The cut off of dock score was set to >-9 kcal/mol and screened compounds were individually docked against main protease, RNA-dependent RNA polymerase, and spike proteins using AutoDock 4.1 software. Finally, lead flavonoid compounds were subjected to ADMET analysis. A total of 458 flavonoid compounds were virtually screened against main protease target and 36 compounds were selected based on the interaction energy value >-9 kcal/mol. Furthermore, these compounds were individually docked against protein targets and top 10 lead compounds were identified. Among the lead compounds, agathisflavone showed highest binding energy value of -8.4 kcal/mol against main protease, Albireodelphin showed highest dock score of -9.8 kcal/mol and -11.2 kcal/mol against RdRp, and spike proteins, respectively. Based on the high dock score and ADMET properties, top 5 lead molecules such as Albireodelphin, Apigenin 7-(6″-malonylglucoside), Cyanidin-3-(p-coumaroyl)-rutinoside-5-glucoside, Delphinidin 3-O-beta-D-glucoside 5-O-(6-coumaroyl-beta-D-glucoside) and (-)-Maackiain-3-O-glucosyl-6″-O-malonate were identified as potent inhibitors against main protease, RdRp, and spike protein targets of SARS-CoV-2. These all compounds are having non-carcinogenic and non-mutagenic properties. This study finding suggests that the screened compounds include Albireodelphin, Apigenin 7-(6″-malonylglucoside), Cyanidin-3-(p-coumaroyl)-rutinoside-5-glucoside, Delphinidin 3-O-beta-D-glucoside 5-O-(6-coumaroyl-beta-D-glucoside) and (-)-Maackiain-3-O-glucosyl-6″-O-malonate could be the potent inhibitors of SARS-CoV-2 targets.

Comparing cefotaxime and ceftriaxone in combating meningitis through nose-to-brain delivery using bio/chemoinformatics tools

Bio/chemoinformatics tools can be deployed to compare antimicrobial agents aiming to select an efficient nose-to-brain formulation targeting the meningitis disease by utilizing the differences in the main structural, topological and electronic descriptors of the drugs. Cefotaxime and ceftriaxone were compared at the formulation level (by comparing the loading in gelatin and tripalmitin matrices as bases for the formation of nanoparticulate systems), at the biopharmaceutical level (through the interaction with mucin and the P-gp efflux pumps) and at the therapeutic level (through studying the interaction with S. pneumoniae bacterial receptors). GROMACS v4.6.5 software package was used to carry-out all-atom molecular dynamics simulations. Higher affinity of ceftriaxone was observed compared to cefotaxime on the investigated biopharmaceutical and therapeutic macromolecules. Both drugs showed successful docking on mucin, P-gp efflux pump and S. pneumoniae PBP1a and 2b; but ceftriaxone showed higher affinity to the P-gp efflux pump proteins and higher docking on mucin. Ceftriaxone showed less out-of-matrix diffusion and higher entrapment on the gelatin and the tripalmitin matrices. Accordingly, Ceftriaxone gelatin nanospheres or tripalmitin solid lipid nanoparticles may pose a more feasible and efficient nose-to-brain formulation targeting the meningitis disease compared to the cefotaxime counterparts.

A dynamic simulation study of FDA drug from zinc database against COVID-19 main protease receptor

The sudden outbreak of COVID-19 has been responsible for several deaths across the globe. Due to its high contagious nature, it spreads from one human to another very quickly. Now it becomes a global public health threat with no approved treatments. In silico techniques can accelerate the drug development process. Our research aimed to identify the novel drugs for inhibition of Main protease (Mpro) enzyme of COVID-19 by performing in silico approach. In this context, a library consisting of 3180 FDA-approved drugs from ‘the ZINC database’ was used to identify novel drug candidates against ‘the Mpro’ of SARS-CoV-2. Initially, the top 10 drugs out of 3180 drugs were selected by molecular docking according to their binding score. Among 10 selected drugs; seven drugs that showed binding with Mpro enzyme residue Glu166 were subjected to100 ns Molecular dynamics (MD) simulation. Out of seven compounds, four namely, ZINC03831201, ZINC08101052, ZINC01482077, and ZINC03830817 were found significant based on MD simulation results. Furthermore, RMSD, RMSF, RG, SASA, PCA, MMPBSA (for last 40 ns) were calculated for the 100 ns trajectory period. Currently, the world needs potent drugs in a short period and this work suggests that these four drugs could be used as novel drugs against COVID-19 and it also provides new lead compounds for further in vitro, in vivo, and ongoing clinical studies against SARS-CoV-2.

Communicated by Ramaswamy H. Sarma

HCVpred: A web server for predicting the bioactivity of hepatitis C virus NS5B inhibitors

Hepatitis C virus (HCV) is one of the major causes of liver disease affecting an estimated 170 million people culminating in 300,000 deaths from cirrhosis or liver cancer. NS5B is one of three potential therapeutic targets against HCV (i.e., the other two being NS3/4A and NS5A) that is central to viral replication. In this study, we developed a classification structure-activity relationship (CSAR) model for identifying substructures giving rise to anti-HCV activities among a set of 578 non-redundant compounds. NS5B inhibitors were described by a set of 12 fingerprint descriptors and predictive models were constructed from 100 independent data splits using the random forest algorithm. The modelability (MODI index) of the data set was determined to be robust with a value of 0.88 exceeding established threshold of 0.65. The predictive performance was deduced by the accuracy, sensitivity, specificity, and Matthews correlation coefficient, which was found to be statistically robust (i.e., the former three parameters afforded values in excess of 0.8 while the latter statistical parameter provided a value >0.7). An in-depth analysis of the top 20 important descriptors revealed that aromatic ring and alkyl side chains are important for NS5B inhibition. Finally, the predictive model is deployed as a publicly accessible HCVpred web server (available at http://codes.bio/hcvpred/) that would allow users to predict the biological activity as being active or inactive against HCV NS5B. Thus, the knowledge and web server presented herein can be used in the design of more potent and specific drugs against the HCV NS5B.

Virtual screening and repurposing of FDA approved drugs against COVID-19 main protease

Aims

In December 2019, the Coronavirus disease-2019 (COVID-19) virus has emerged in Wuhan, China. In this research, the first resolved COVID-19 crystal structure (main protease) was targeted in a virtual screening study by of FDA approved drugs dataset. In addition, a knowledge gap in relations of COVID-19 with the previously known fatal Coronaviruses (CoVs) epidemics, SARS and MERS CoVs, was covered by investigation of sequence statistics and phylogenetics.

Materials and methods

Molecular modeling, virtual screening, docking, sequence comparison statistics and phylogenetics of the COVID-19 main protease were investigated.

Key findings

COVID-19 Mpro formed a phylogenetic group with SARS CoV that was distant from MERS CoV. The identity% was 96.061 and 51.61 for COVID-19/SARS and COVID-19/MERS CoV sequence comparisons, respectively. The top 20 drugs in the virtual screening studies comprised a broad-spectrum antiviral (ribavirin), anti-hepatitis B virus (telbivudine), two vitamins (vitamin B12 and nicotinamide) and other miscellaneous systemically acting drugs. Of special interest, ribavirin had been used in treating cases of SARS CoV.

Significance

The present study provided a comprehensive targeting of the first resolved COVID+19 structure of Mpro and found a suitable save drugs for repurposing against the viral Mpro. Ribavirin, telbivudine, vitamin B12 and nicotinamide can be combined and used for COVID treatment. This initiative relocates already marketed and approved safe drugs for potential use in COVID-treatment.

Enhanced Allicin Cytotoxicity on HEPG-2 Cells Using Glycyrrhetinic Acid Surface-Decorated Gelatin Nanoparticles

The cytotoxic potential of allicin was evaluated on different cancer cell lines, particularly, hepatic (HepG-2), breast (MCF-7), lung (A-549), and prostatic (PC-3), where allicin scored an IC₅₀ score of 19.26 μM on HepG-2. In order to increase the cell uptake, optimized allicin-loaded gelatin nanoparticles (GNPs) were prepared where the optimum formulation was surface-conjugated to glycyrrhetinic acid. GNPs were optimized using a D-optimal design. The optimum formulation had a particle size of 370.7 ± 6.78 nm and polydispersity index of 0.0363 ± 0.009 and 39.13 ± 2.38% of drug entrapment. The conjugation of the ligand, glycyrrhetinic acid with allicin-loaded GNPs, was confirmed utilizing ¹H NMR. Drug release profiles in the presence/absence of collagenase were obtained. Finally, a cytotoxicity study on HepG-2 was performed for the unconjugated and conjugated allicin-loaded GNPs scoring IC₅₀ of 10.95 and 5.046 μM, revealing two- and fourfold enhancements in allicin cytotoxicity, respectively. To our knowledge, the ligand-carrier pair, glycyrrhetinic acid-gelatin, was not explored before, and the developed system poses a successful liver cancer therapy.

Review on chemogenomic approaches towards hepatitis C viral targets

Hepatitis C virus (HCV) is the most prevalent viral pathogen that infects more than 185 million people worldwide. HCV infection leads to chronic liver diseases such as liver cirrhosis and hepatocellular carcinoma. Direct-acting antivirals (DAAs) are the recent combination therapy for HCV infection with reduced side effects than prior therapies. Sustained virological response (SVR) acts as a gold standard marker to monitor the success of antiviral treatment. Older treatment therapies attain 50-55% of SVR compared with DAAs which attain around 90-95%. The current review emphasizes the recent chemogenomic updates that have been unfolded through structure-based drug design of HCV drug target proteins (NS3/4A, NS5A, and NS5B) and ligand-based drug design of DAAs in achieving a stable HCV viral treatment strategies.

Identifying the novel inhibitors of lysine-specific demethylase 1 (LSD1) combining pharmacophore-based and structure-based virtual screening

Lysine-specific demethylase 1 (LSD1) has been reported to connect with a range of solid tumors. Thus, the exploration of LSD1 inhibitors has emerged as an effective strategy for cancer treatment. In this study, we constructed a pharmacophore model based on a series of flavin adenine dinucleotide (FAD)-competing inhibitors bearing triazole - dithiocarbamate scaffold combining docking, structure-activity relationship (SAR) study, and molecular dynamic (MD) simulation. Meanwhile, another pharmacophore model was also constructed manually, relying on several speculated substrate-competing inhibitors and reported putative vital interactions with LSD1. On the basis of the two pharmacophore models, multi-step virtual screenings (VSs) were performed against substrate-binding pocket and FAD-binding pocket, respectively, combining pharmacophore-based and structure-based strategy to exploit novel LSD1 inhibitors. After bioassay evaluation, four compounds among 21 hits with diverse and novel scaffolds exhibited inhibition activity at the range of 3.63-101.43 μM. Furthermore, substructure-based enrichment was performed, and four compounds with a more potent activity were identified. After that, the time-dependent assay proved that the most potent compound with IC₅₀ 2.21 μM inhibits LSD1 activity in a manner of time-independent. In addition, the compound exhibited a cellular inhibitory effect against LSD1 in MGC-803 cells and may inhibit cell migration and invasion by reversing EMT in cultured gastric cancer cells. Considering the binding mode and SAR of the series of compounds, we could roughly deem that these compounds containing 3-methylxanthine scaffold act through occupying substrate-binding pocket competitively. This study presented a new starting point to develop novel LSD1 inhibitors.

Quantum molecular modeling of hepatitis C virus inhibition through non-structural protein 5B polymerase receptor binding of C5-arylidene rhodanines

We have carried out high-level quantum chemical computations followed by molecular docking studies on a set of 17C₅-arylidene rhodanine isomers to provide insights into the binding modes with different reported binding pockets of the nonstructural protein 5B (NS5B) polymerase that contribute to the hepatitis C virus (HCV) inhibition. We optimized the multi-target profile of the selected rhodanine analogs to investigate potential non-nucleotide inhibitors (NNIs) by quantum chemical optimization of the 18 isomers followed by docking with quantum chemically optimized structures of each isomer with NS5B polymerase at multiple binding pockets. The binding affinities of the PP-I, PP-II and TP-II pockets of NS5B polymerase were analyzed for all the 17 isomers of 2-[(5Z)-5-(2,4-dichlorobenzylidene)-4-oxo-2-thioxo-1,3-thiazolidin-3-yl]-3-phenylpropanoic acid. On the basis of binding propensity at the different pockets and inhibitor constants, we ranked these isomers as potential candidates for the HCV inhibition. We have identified four isomers as promising NNIs of NS5B polymerase with comparable binding and inhibition to the standard (1,3) dichloro substituted isomer that exhibits in vitro activity and several other isomers as candidates in a "multi-targeted drug" approach.

Broad-spectrum non-nucleoside inhibitors for caliciviruses

Viruses of the Caliciviridae cause significant and sometimes lethal diseases, however despite substantial research efforts, specific antivirals are lacking. Broad-spectrum antivirals could combat multiple viral pathogens, offering a rapid solution when no therapies exist. The RNA-dependent RNA polymerase (RdRp) is an attractive antiviral target as it is essential for viral replication and lacks mammalian homologs. To focus the search for pan-Caliciviridae antivirals, the RdRp was probed with non-nucleoside inhibitors (NNIs) developed against hepatitis C virus (HCV) to reveal both allosteric ligands for structure-activity relationship enhancement, and highly-conserved RdRp pockets for antiviral targeting. The ability of HCV NNIs to inhibit calicivirus RdRp activities was assessed using in vitro enzyme and murine norovirus cell culture assays. Results revealed that three NNIs which bound the HCV RdRp Thumb I (TI) site also inhibited transcriptional activities of six RdRps spanning the Norovirus, Sapovirus and Lagovirus genera of the Caliciviridae. These NNIs included JTK-109 (RdRp inhibition range: IC₅₀ 4.3-16.6 μM), TMC-647055 (IC₅₀ range: 18.8-45.4 μM) and Beclabuvir (IC₅₀ range: 23.8->100 μM). In silico studies and site-directed mutagenesis indicated the JTK-109 binding site was within the calicivirus RdRp thumb domain, in a pocket termed Site-B, which is highly-conserved within all calicivirus RdRps. Additionally, RdRp inhibition assays revealed that JTK-109 was antagonistic with the previously reported RdRp inhibitor pyridoxal-5'-phosphate-6-(2'-naphthylazo-6'-nitro-4',8'-disulfonate) tetrasodium salt (PPNDS), that also binds to Site-B. Moreover, like JTK-109, PPNDS was also a potent inhibitor of polymerases from six viruses spanning the three Caliciviridae genera tested (IC₅₀ range: 0.1-2.3 μM). Together, this study demonstrates the potential for de novo development of broad-spectrum antivirals that target the highly-conserved RdRp thumb pocket, Site-B. We also revealed three broad-spectrum HCV NNIs that could be used as antiviral scaffolds for further development against caliciviruses and other viruses.

Computational Approaches for the Discovery of Novel Hepatitis C Virus NS3/4A and NS5B Inhibitors

Nonstructural 5B (NS5B) polymerase and Nonstructural 3/4A (NS3/4A) protease have proven to be promising targets for the development of anti-HCV (Hepatitis C Virus) agents. The NS5B polymerase is of paramount importance in HCV viral replication; therefore, employing NS5B inhibitors was considered an effective way for the treatment of HCV. Identifying inhibitors against NS3/4A serine protease represents another attractive approach applied in anti-HCV drug discovery, which is evidenced by its crucial role of in the biogenesis of the viral replication activity. In this chapter, many different computational approaches including Quantitative Structure-Activity Relationship (QSAR) and virtual screening in anti-HCV drug discovery were considered and discussed in detail. Virtual Screening (VS) techniques, including ligand-based and structure-based, and QSAR have been utilized for the discovery of NS5B inhibitors. Moreover, using various in silico protocols and workflows, a number of studies have been conducted with an aim of identifying potential NS3/4A blockage agents.

Selecting optimum protein nano-carriers for natural polyphenols using chemoinformatics tools

BACKGROUND

The normal fate of any natural product with a therapeutic potential is to be formulated into an effective medicine. However, the conventional methods of selecting the suitable formulations or carriers based on the formulator experiences, trials and errors as well as materials availability do not usually yield the optimal results.

HYPOTHESIS

We hypothesize the possibility of the virtual optimum selection of a protein carrier for two polyphenolic compounds widely investigated for their chemopreventive effects; resveratrol and curcumin using a combination of some chemoinformatics tools.

METHODS

Two protein-based nanoparticles namely; albumin and gelatin nanoparticles were compared as carriers for the two selected phytochemicals; resveratrol and curcumin. Resveratrol-albumin, resveratrol-gelatin and curcumin-albumin results were gathered from the literature. While, a new combination (formulation), comprising curcumin as the cargo and gelatin nanoparticles as the carrier, was prepared and evaluated as a potential medicine for breast cancer. Combined chemoinformatics tools, namely; molecular dynamics and molecular docking were used to determine the optimum carrier for each of the two chemopreventive agents.

RESULTS

A new curcumin-gelatin nanoparticulate formulation was prepared and proven cytotoxic after an application period of 48h on MCF-7 breast cancer cell-lines scoring an IC₅₀ value of 64.8µg/ml. The utilized chemoinformatics tools comprising the molecular dynamics simulations of the protein nano-particulate drug-carriers followed by the molecular docking of phytochemical drugs on these carriers could capture the optimum protein carrier for each of the tested phytochemical and hence propose a successful formulation.

CONCLUSION

This study presents one in a series that proves the novel addressed concept of the utilization of computational tools rather than wet-lab experimentation in providing better selection of drug-carrier pairs aiming for better formulations and the subsequent successful therapeutic effects.

A study of the allosteric inhibition of HCV RNA-dependent RNA polymerase and implementing virtual screening for the selection of promising dual-site inhibitors with low resistance potential

Structure-based pharmacophores were generated and validated using the bioactive conformations of different co-crystallized enzyme-inhibitor complexes for allosteric palm-1 and thumb-2 inhibitors of NS5B. Two pharmacophore models were obtained, one for palm-1 inhibitors with sensitivity = 0.929 and specificity = 0.983, and the other for thumb-2 inhibitors with sensitivity = 1 and specificity = 0.979. In addition, a quantitative structure activity relationship (QSAR) models were developed based on using the values of different scoring functions as descriptors predicting the activity on both allosteric binding sites (palm-1 and thumb-2). QSAR studies revealed good predictive and statistically significant two descriptor models (r²= .837, r²_adjusted = .792 and r²_prediction = .688 for palm-1 model and r²= .927, r²_adjusted = .908 and r²_prediction = .779 for thumb-2 model). External validation for the QSAR models assured their prediction power with r²_ext= .72 and .89 for palm-1 and thumb-2, respectively. Different docking protocols were examined for their validity to predict the correct binding poses of inhibitors inside their respective binding sites. Virtual screening was carried out on ZINC database using the generated pharmacophores, the selected valid docking algorithms and QSAR models to find compounds that could theoretically bind to both sites simultaneously.

Identification of Novel Inhibitors of Mycobacterium tuberculosis PknG Using Pharmacophore Based Virtual Screening, Docking, Molecular Dynamics Simulation, and Their Biological Evaluation

PknG is a Ser/thr protein kinase that plays a crucial role in regulatory processes within the mycobacterial cell and signaling cascade of the infected host cell. The essentiality of PknG in mycobacterial virulence by blocking phagosome-lysosome fusion as well as its role in intrinsic antibiotic resistance makes it an attractive drug target. However, only very few compounds have been reported as Mycobacterium tuberculosis PknG (MtPknG) inhibitors so far. Therefore, in an effort to find potential inhibitors against MtPknG, we report here a sequential pharmacophore-based virtual screening workflow, 3-fold docking with different search algorithms, and molecular dynamic simulations for better insight into the predicted binding mode of identified hits. After detailed analysis of the results, six ligands were selected for in vitro analysis. Three of these molecules showed significant inhibitory activity against MtPknG. In addition, inhibitory studies of mycobacterial growth in infected THP-1 macrophages demonstrated considerable growth inhibition of M. bovis BCG induced through compound NRB04248 without any cytotoxic effect against host macrophages. Our results suggest that the compound NRB04248 can be explored for further design and optimization of MtPknG inhibitors.

Docking studies of Pakistani HCV NS3 helicase: a possible antiviral drug target

The nonstructural protein 3 (NS3) of hepatitis C virus (HCV) helicase is believed to be essential for viral replication and has become an attractive target for the development of antiviral drugs. The study of helicase is useful for elucidating its involvement in positive sense single-stranded RNA virus replication and to serve as templates for the design of novel antiviral drugs. In recent years, several models have been proposed on the conformational change leading to protein movement and RNA unwinding. Some compounds have been recently reported to inhibit the helicase and these include small molecules, RNA aptamers and antibodies. The current study is designed to help gain insights for the consideration of potential inhibitors for Pakistani HCV NS3 helicase protein. We have cloned, expressed and purified HCV NS3 helicase from Pakistani HCV serum samples and determined its 3D structure and employed it further in computational docking analysis to identify inhibitors against HCV genotype 3a (GT3a),including six antiviral key molecules such as quercetin, beta-carotene, resveratrol, catechins, lycopene and lutein. The conformation obtained after docking showed good hydrogen bond (HBond) interactions with best docking energy for quercetin and catechins followed by resveratrol and lutein. These anti-helicase key molecules will offer an alternative attraction to target the viral helicase, due to the current limitation with the interferon resistance treatment and presences of high rate of resistance in anti-protease inhibitor classes.

Identification of novel small molecules as inhibitors of hepatitis C virus by structure-based virtual screening

Hepatitis C virus (HCV) NS3/NS4A serine protease is essential for viral replication, which is regarded as a promising drug target for developing direct-acting anti-HCV agents. In this study, sixteen novel compounds with cell-based HCV replicon activity ranging from 3.0 to 28.2 μM (IC₅₀) were successfully identified by means of structure-based virtual screening. Compound 5 and compound 11, with an IC₅₀ of 3.0 μM and 5.1 μM, respectively, are the two most potent molecules with low cytotoxicity.

InCoB2012 Conference: from biological data to knowledge to technological breakthroughs

Ten years ago when Asia-Pacific Bioinformatics Network held the first International Conference on Bioinformatics (InCoB) in Bangkok its theme was North-South Networking. At that time InCoB aimed to provide biologists and bioinformatics researchers in the Asia-Pacific region a forum to meet, interact with, and disseminate knowledge about the burgeoning field of bioinformatics. Meanwhile InCoB has evolved into a major regional bioinformatics conference that attracts not only talented and established scientists from the region but increasingly also from East Asia, North America and Europe. Since 2006 InCoB yielded 114 articles in BMC Bioinformatics supplement issues that have been cited nearly 1,000 times to date. In part, these developments reflect the success of bioinformatics education and continuous efforts to integrate and utilize bioinformatics in biotechnology and biosciences in the Asia-Pacific region. A cross-section of research leading from biological data to knowledge and to technological applications, the InCoB2012 theme, is introduced in this editorial. Other highlights included sessions organized by the Pan-Asian Pacific Genome Initiative and a Machine Learning in Immunology competition. InCoB2013 is scheduled for September 18-21, 2013 at Suzhou, China.