Identification of essential oil phytocompounds as natural inhibitors of Odorant-binding protein to prevent malaria through in silico approach

Malaria predominantly affects millions annually in the African and Asian tropical and subtropical countries. With no effective vaccine, malaria prevention is exclusively dependent on preventing human-vector interaction. Anopheles gambiae, the main vector of the malaria parasite Plasmodium falciparum contains Odorant Binding proteins (OBPs) which are considered an attractive drug target for anti-malarial therapy. To identify a potential anti-malarial compound, we performed a structure-based screening of 876 phytocompounds derived from essential oils against the OBP4 by molecular docking. The compounds having better docking scores were assessed for drug-likeness, toxicity, and molecular interaction analysis. As per the results, strong affinities and high stability were demonstrated by two phytocompounds viz. Alpha-cyperone (-8.1 kcal mol-1) and Humulene oxide (-8.1 kcal mol-1) with OBP4. The hydrophobic interactions involve Phe123, Ala106, Thr57, Ala52, Thr69, and Ile64 within the binding cavities, which may block the OBP4 receptor resulting in disorientation. After that, the potential compounds were subjected to molecular dynamics (MD) simulation to evaluate their structural stability and dynamics at the active site of OBP4. The MM-PBSA result revealed that Alpha-cyperone and Humulene oxide had binding free energy of -92.44 kJ mol-1 and -113.25 kJ mol-1, respectively. Simulation outcomes demonstrate that these phytocompounds displayed considerable significant structural and pharmacological properties. The LD50 value of Alpha-cyperone and Humulene oxide also suggested that both are safe and suitable for use in natural repellent development. We suggest that the use of these compounds can minimize the treatment period and the various side effects associated with the currently available anti-malarial drugs.Communicated by Ramaswamy H. Sarma.

In silico screening of natural compounds to inhibit interaction of human ACE2 receptor and spike protein of SARS-CoV-2 for the prevention of COVID-19

A computational investigation was carried out to find out potential phytochemicals that could inhibit the binding of human angiotensin-converting enzyme-2 (ACE2) receptors to spike protein of SARS-CoV-2 which is an essential step to gain entry inside human cells and onset of viral infection known as Coronavirus disease (COVID-19). A library of phytochemicals was screened by virtual screening against ACE2 receptors resulting in twenty phytochemicals out of 686 which had binding energy (-11.8 to -6.9 kcal/mol). Drug-likeness gave five hits, but ADMET analysis yielded 4 nontoxic hit phytochemicals. Molecular dynamics simulation of four-hit compounds resulted in acceptable stability and good dynamics behavior. These phytochemicals are Hinokinin, Gmelanone, Isocolumbin, and Tinocordioside, from Vitis vinifera, Gmelina arborea, and Tinospora cordifolia. The above-mentioned phytochemicals may be promising ACE2 inhibitors and can prevent infection of SARS-CoV-2 by inhibiting the entry of the virus into host cells.Communicated by Ramaswamy H. Sarma.

Identification of SARS-CoV-2 RNA dependent RNA polymerase inhibitors using pharmacophore modelling, molecular docking and molecular dynamics simulation approaches

The RNA-dependent RNA polymerase (RdRp) is one of the crucial enzymes in severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) catalysing the replication of RNA, therefore acts as a potential target for antiviral drug design. The fixation of a ligand in the active site of RdRp may alter the SARS-CoV-2 life cycle. Present work aimed at identifying novel inhibitors of the SARS-CoV-2 RdRp enzyme by performing pharmacophore-based virtual screening, molecular docking and molecular dynamics simulation (MDS). Initially, the pharmacophore model of SARS-CoV-2 RdRp was constructed and the resulting model was used to screen compounds from ChEMBL, ZINC and PubChem databases. During the investigation, 180 compounds were screened using the above model and subjected to molecular docking with RdRp. Two compounds viz. ChEMBL1276156 and PubChem135548348 showed a strong binding affinity with RdRp than its standard inhibitor, Remdesivir. Toxicity prediction of these two compounds reveals their non-toxic nature. These compounds were further subjected to MDS for 100 ns to check their stability after binding with RdRp. The MDS of RdRp-ChEMBL1276156 and RdRp-PubChem135548348 complexes show enhanced stability in comparison to the RdRp-Remdesivir complex. The average interaction energy calculated after 100 ns of MDS was -146.56 and -172.68 KJ mol^-1 for RdRp-CHEMBL1276156 complex and RdRp-PubChem135548348 complex, respectively, while -59.90 KJ mol^-1 for RdRp-Remdesivir complex. The current investigation reveals that these two compounds are potent inhibitors of SARS-CoV-2 RdRp and they could be tested in the experimental condition to evaluate their efficacy against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Screening of potential bio-molecules from Moringa olifera against SARS-CoV-2 main protease using computational approaches

COVID-19 caused by SARS-CoV-2 is responsible for the deaths of millions of people worldwide. It is having devastating effects on the people of all countries. In this regard, the phytochemicals of medicinal plants could be explored to prevent this disease. M. oleifera is a miracle plant with antibacterial, antiviral, and antioxidant properties because of its high content of flavonoids, glucosides and glucosinolates. Therefore, we constructed a library of 294 phytochemicals of M. oleifera and filtered it through the FAF-Drugs4. Further, molecular docking studies of filtered phytochemicals were performed with Mpro enzyme to investigate the binding interactions. Drug likeness properties, ADMET prediction were analyzed to determine the therapeutic aspect of these compounds. Based on the binding energy score of the top 4 compounds, the results indicate that Vicenin-2 has the highest binding affinity (-8.6 kcal mol^-1) as compared to the reference molecule (-8.4 kcal mol^-1). ADMET result reveals that all top four compounds have minimal toxic effects and good absorption. Further, 500 ns molecular dynamics simulation of the top four compounds showed that Kaempferol-3-O-rutinoside and Vitexin have good stability with Mpro. These two compounds were then subjected for MMPBSA (last 50 ns) calculation to analyze the protein-ligand stability and dynamic behavior. Kaempferol-3-O-rutinoside and Vitexin showed very good binding free energy i.e. -40.136 kJ mol^-1 and -26.784 kJ mol^-1, respectively. Promising outcomes from MD simulations evidence the worth of these compounds for future drug development to combat coronavirus disease.Communicated by Ramaswamy H. Sarma.

Critical challenges of integrating OPEX strategies with I4.0 technologies in manufacturing SMEs: a few pieces of evidence from developing economies

Purpose

The study proposes to determine the impending challenges to lean integration with Industry 4.0 (I4.0) in manufacturing that aims at achieving desired operational performance. Integrating lean and Industry 4.0 as the two industrial approaches is synergetic in providing operational benefits such as increasing flexibility, improving productivity, reducing cost, reducing delivery time, improving quality and value stream mapping (VSM). There is an urgent need to understand the integrated potential of OPEX strategies like lean manufacturing and also to determine the challenges for manufacturing SMEs and further suggest a strategic roadmap for the future.

Design/methodology/approach

The current work has used a combined approach on interpretative structural modeling (ISM) and fuzzy Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) approach to structure the multiple level analysis for the implementation challenges to integrate OPEX strategies with Industry 4.0.

Findings

The research has found that the indulgence of various implementation issues like lack of standardization, lack of vision and lack of trained support, all are the major challenges that inhibit the integration of OPEX strategies with I4.0 technologies in manufacturing.

Research limitations/implications

The research has investigated the internal factors acting as a roadblock to lean and Industry 4.0 adoption. Further studies may consider external factors to lean and Industry 4.0 implementation. Also, further research may consider other operational excellence approaches and extend further to relevant sectors.

Practical implications

This study provides the analysis of barriers that is useful for the managers to take strategic actions for implementing OPEX strategies with I4.0 in smart manufacturing.

Originality/value

The research determines the adoption challenges towards the integrated framework. This is the first study to explore challenges in integrating OPEX strategies with I4.0 technologies in manufacturing SMEs.

Molecular basis for the repurposing of histamine H2-receptor antagonist to treat COVID-19

With the world threatened by a second surge in the number of Coronavirus cases, there is an urgent need for the development of effective treatment for the novel coronavirus (COVID-19). Recently, global attention has turned to preliminary reports on the promising anti-COVID-19 effect of histamine H2-receptor antagonists (H2RAs), most especially Famotidine. Therefore, this study was designed to exploit a possible molecular basis for the efficacy of H2RAs against coronavirus. Molecular docking was performed between four H2RAs, Cimetidine, Famotidine, Nizatidine, Ranitidine, and three non-structural proteins viz. NSP3, NSP7/8 complex, and NSP9. Thereafter, a 100 ns molecular dynamics simulation was carried out with the most outstanding ligands to determine the stability. Thereafter, Famotidine and Cimetidine were subjected to gene target prediction analysis using HitPickV2 and eXpression2Kinases server to determine the possible network of genes associated with their anti-COVID activities. Results obtained from molecular docking showed the superiority of Famotidine and Cimetidine compared to other H2RAs with a higher binding affinity to all selected targets. Molecular dynamic simulation and MMPBSA results revealed that Famotidine as well as Cimetidine bind to non-structural proteins more efficiently with high stability over 100 ns. Results obtained suggest that Famotidine and Cimetidine could be a viable option to treat COVID-19 with a mechanism of action that involves the inhibition of viral replication through the inhibition of non-structural proteins. Therefore, Famotidineand Cimetidine qualify for further study as a potential treatment for COVID-19.

Evaluation of the inhibitory potential of Valproic acid against histone deacetylase of Leishmania donovani and computational studies of Valproic acid derivatives

Valproic acid (VA) is a proven inhibitor of human histone deacetylases (HDACs). The homogenous HDAC has been associated with all major human parasitic pathogens and hence, it has been considered an attractive drug target for anti-leishmanial therapy. To assist in drug design endeavors for HDACs, an in-vitro study has been presented to investigate the VA inhibition on Leishmania donovani HDAC (LdHDAC). The regression analysis of VA by 24 hrs viability assay confirmed its activity against LdHDAC. Moreover, the toxicity of VA is also well documented. Thus, the in-silico experiments were also conducted to screen the non-toxic VA derivatives as anti-leishmanial drug candidates having potential as inhibitors of LdHDAC. For in-silico study, the 3D structure of target LdHDAC was developed by homology modeling. Based on their in-silico activity, we shortlisted 13 VA derivatives having maximum affinity for LdHDAC and identified four potential derivatives that can specifically bind to this protein. After that, these ligands were subjected to molecular dynamics simulation. These derivatives may be effective against L. donovani promastigotes since they followed Lipinski's RO5 and were non-toxic. Thus, screened derivatives can be considered as lead ligands for targeting LdHDAC and may be used as possible drug candidates to treat leishmaniasis and overcome the limitation of anti-leishmanial drugs. This is the first report of antileishmanial potential of VA and its derivatives targeting LdHDAC. Hence, the current investigation presents a search for novel target specific drugs to aid the anti-leishmanial drug development. Communicated by Ramaswamy H. Sarma.

Identification of natural inhibitors against Mpro of SARS-CoV-2 by molecular docking, molecular dynamics simulation, and MM/PBSA methods

The recent outbreak of SARS-CoV-2 disease, also known as COVID-19, has emerged as a pandemic. The unavailability of specific therapeutic drugs and vaccines urgently demands sincere efforts for drug discovery against COVID-19. The main protease (Mpro) of SARS-CoV-2 is a critical drug target as it plays an essential role in virus replication. Therefore for the identification of potential inhibitors of SARS-CoV-2 Mpro, we applied a structure-based virtual screening approach followed by molecular dynamics (MD) study. A library of 686 phytochemicals was subjected to virtual screening which resulted in 28 phytochemicals based on binding energy. These phytochemicals were further subjected to drug-likeness and toxicity analysis, which resulted in seven drug-like hits. Out of seven, five phytochemicals viz., Mpro-Dehydrtectol (-10.3 kcal/mol), Epsilon-viniferin (-8.6 kcal/mol), Peimisine (-8.6 kcal/mol), Gmelanone (-8.4 kcal/mol), and Isocolumbin (-8.4 kcal/mol) were non-toxic. Consequently, these phytochemicals are subjected to MD, post MD analysis, and MM/PBSA calculations. The results of 100 ns MD simulation, RMSF, SASA, Rg, and MM/PBSA show that Epsilon-viniferin (-29.240 kJ/mol), Mpro-Peimisine (-43.031 kJ/mol) and Gmelanone (-13.093 kJ/mol) form a stable complex with Mpro and could be used as potential inhibitors of SARS-CoV-2 Mpro. However, further investigation of these inhibitors against Mpro receptor of COVID-19 is needed to validate their candidacy for clinical trials. Communicated by Ramaswamy H. Sarma.

Identification of Berbamine, Oxyacanthine and Rutin from Berberis asiatica as anti-SARS-CoV-2 compounds: An in silico study

Owing to the shortage of specific medicines, the global pandemic of COVID-19 caused by SARS-CoV-2 has been the greatest challenge for the science community. Researchers from all over the world developed some drugs which failed to completely suppress the contiguous disease. SARS-CoV-2 main protease (Mpro), an important component in viral pathogenesis, is considered as a prospective drug target to stop SARS-CoV-2 infection. Since identification of phytochemicals with anti-Mpro activity has been carried out to develop the potential drugs against SARS-CoV-2. Therefore, the present study was conducted to screen phytochemicals of Berberis asiatica for anti-SARS-CoV-2 activity. Through text mining, thirty phytochemicals were reported from B. asiatica, of which, three phytochemicals (Berbamine, Oxyacanthine, and Rutin) show high affinity with the SARS-CoV-2 Mpro and exhibited favorable intermolecular interactions with the catalytic residues (His41 and Cys145) and other essential residues. The molecular dynamics simulation showed that Mpro-phytochemical complexes are more stable, less fluctuating, more compact, and moderately extended than the Mpro-X77 (Reference) complex. The number of H-bonds and MMPBSA results also demonstrates that Berbamine, Oxyacanthine, and Rutin are potent Mpro inhibitors having free energy of −20.79, −33.35, and −31.12 kcal mol⁻¹ respectively. The toxicity risk prediction supports all phytochemicals for drug-like and non-toxic nature. From the result, we propose that binding of these phytochemicals could hamper the function of Mpro. This work suggests that selected phytochemicals could be used as novel anti-COVID-19 drug candidates, and might act as novel compounds for in vitro and in vivo study.

Computational investigation of drug bank compounds against 3C-like protease (3CLpro) of SARS-CoV-2 using deep learning and molecular dynamics simulation

Blocking the main replicating enzyme, 3 Chymotrypsin-like protease (3CL^pro) is the most promising drug development strategy against the SARS-CoV-2 virus, responsible for the current COVID-19 pandemic. In the present work, 9101 drugs obtained from the drug bank database were screened against SARS-CoV-2 3CL^pro prosing deep learning, molecular docking, and molecular dynamics simulation techniques. In the initial stage, 500 drug-screened by deep learning regression model and subjected to molecular docking that resulted in 10 screened compounds with strong binding affinity. Further, five compounds were checked for their binding potential by analyzing molecular dynamics simulation for 100 ns at 300 K. In the final stage, two compounds {4-[(2s,4e)-2-(1,3-Benzothiazol-2-Yl)-2-(1h-1,2,3-Benzotriazol-1-Yl)-5-Phenylpent-4-Enyl]Phenyl}(Difluoro)Methylphosphonic Acid and 1-(3-(2,4-dimethylthiazol-5-yl)-4-oxo-2,4-dihydroindeno[1,2-c]pyrazol-5-yl)-3-(4-methylpiperazin-1-yl)urea were screened as potential hits by analyzing several parameters like RMSD, Rg, RMSF, MMPBSA, and SASA. Thus, our study suggests two potential drugs that can be tested in the experimental conditions to evaluate the efficacy against SARS-CoV-2. Further, such drugs could be modified to develop more potent drugs against COVID-19.

QSAR modeling and pharmacoinformatics of SARS coronavirus 3C-like protease inhibitors

The search for effective treatment against novel coronavirus (COVID-19) remains a global challenge due to controversies on available vaccines. In this study, data of SARS coronavirus 3C-like protease (3CLpro) inhibitors; a key drug target in the coronavirus genome was retrieved from CHEMBL database. Quantitative Structure-Activity Relationship (QSAR) studies, Molecular docking, Absorption-Distribution-Metabolism-Excretion-Toxicity (ADMET) and molecular dynamics simulation (MDS) were carried out using these 3CLpro inhibitors. QSAR model constructed using the data had correlation coefficient R² value of 0.907; cross-validated correlation coefficient Q² value of 0.866 and test set predicted correlation coefficient R²_pred value of 0.517. Variance inflation factor (VIF) values for descriptors contained in the model ranged from 1.352 to 1.68, hence, these descriptors were orthogonal to one another. Therefore, the model was statistically significant and can be used to screen and design new molecules for their inhibitory activity against 3CLpro. Molecular docking showed that seven of the compounds (inhibitors) used in the study had a remarkable binding affinity (-9.2 to -10.3 kcal/mol) for 3CLpro. ADMET study revealed that five (CHEMBL Accession IDs 19438, 196635, 377150, 208763, and 210097) of the seven compounds with good binding ability obeyed Lipinski's rule of five. Hence, they were compounds with drug-like properties. MDS analysis revealed that 3CLpro-compound 21, 3CLpro-compound 22, 3CLpro-compound 40 complexes are very stable as compared to the reference 3CLpro-X77 complex. Therefore, this study identified three potent inhibitors of 3CLpro viz. CHEMBL194398, CHEMBL196635, and CHEMBL210097 that can be further explored for the treatment of COVID-19.

Deep-learning based repurposing of FDA-approved drugs against Candida albicans dihydrofolate reductase and molecular dynamics study

Candida albicans causes the fatal fungal bloodstream infection in humans called Candidiasis. Most of the Candida species are resistant to the antifungals used to treat them. Drug-resistant C. albicans poses very serious public health issues. To overcome this, the development of effective drugs with novel mechanism(s) of action is requisite. Drug repurposing is considered a viable alternative approach to overcome the above issue. In the present study, we have attempted to identify drugs that could target the essential enzyme, dihydrofolate reductase of C. albicans (CaDHFR) to find out potent and selective antifungal antifolates. FDA-approved-drug-library from the Selleck database containing 1930 drugs was screened against CaDHFR using deep-learning, molecular docking, X-score and similarity search methods. The screened compounds showing better binding with CaDHFR were subjected to molecular dynamics simulation (MDS). The results of post-MDS analysis like RMSD, RMSF, RG, SASA, the number of hydrogen bonds and PCA suggest that Paritaprevir, Lumacaftor and Rifampin can make good interaction with CaDHFR. Furthermore, analysis of binding free energy corroborated the stability of interactions as they had binding energy of -114.91 kJ mol^-1, -79.22 kJ mol^-1 and -78.52 kJ mol^-1 for Paritaprevir, Lumacaftor and Rifampin respectively as compared to the reference (-63.10 kJ mol^-1). From the results, we conclude that these drugs have great potential to inhibit CaDHFR and would add to the drug discovery against candidiasis, and hence these drugs for repurposing should be explored further.

Interdomain linkers tailor the stability of immunoglobulin repeats in polyproteins

Linkers in polyproteins are considered as mere spacers between two adjacent domains. However, a series of studies using single-molecule force spectroscopy have recently reported distinct thermodynamic stability of I27 in polyproteins with varying linkers and indicated the vital role of linkers in domain stability. A flexible glycine rich linker (-(GGG)_n, n ≥ 3) featured unfolding at lower forces than the regularly used arg-ser (RS) based linker. Interdomain interactions among I27 domains in Gly-rich linkers were suggested to lead to reduced domain stability. However, the negative impact of inter domain interactions on domain stability is thermodynamically counter-intuitive and demanded thorough investigations. Here, using an array of ensemble equilibrium experiments and in-silico measurements with I27 singlet and doublets with two aforementioned linkers, we delineate that the inter-domain interactions in fact raise the stability of the polyprotein with RS linker. More surprisingly, a highly flexible Gly-rich linker has no interference on the stability of polyprotein. Overall, we conclude that flexible linkers are preferred in a polyprotein for maintaining domain's independence.

Identification of potent Antigen 85C inhibitors of Mycobacterium tuberculosis via in-house lichen library and binding free energy studies Part-II

Tuberculosis remains the cause of mortality throughout the world. Currently, the available anti-tubercular drugs are not effective because of the existence of Multi-Drug resistant tuberculosis (MDR-TB) and Extensively-Drug resistant tuberculosis (XDR-TB). It has, therefore, become necessary to develop novel drugs that inhibit the activity of drug-resistant Mycobacterium tuberculosis. Due to the existence of MDR and XDR-TB, Mtb Ag85C has risen out as a propitious molecular drug target as it has importance in the synthesis of main components of the Mtb cell envelope which are essential for the virulence and survival of Mtb. In a previous paper, we studied a potential drug target by virtual high throughput screening of compounds and in continuation of the study on Mtb Ag85C, we further studied the role of lichen compounds in the inhibition of Ag85C. In the current research work, virtual screening of a lichen compounds library was performed against Ag85C. Further, ADMET analysis was employed to filter out the screened lichen compounds. Bioactivity score and toxicity prediction finalized four lichen compounds i.e. Portentol, Aspicilin, Parietinic acid and Polyporic acid as potential inhibitors of Ag85C. The stability and dynamic behavior of four compounds were analyzed by using Molecular dynamics simulation which indicated that they may be potential inhibitors of Ag85C. Therefore, based on the above results, Portentol, Aspicilin, Parietinic acid and Polyporic acid may be potential drug candidates against Mtb. We suggest that the use of these compounds can minimize the treatment time-period and the various side effects associated with the currently available anti-tubercular drugs.

Repurposing of FDA approved drugs against Salmonella enteric serovar Typhi by targeting dihydrofolate reductase: an in silico study

Drug-resistant Salmonella enteric serovar Typhi (S. Typhi) poses a vital public health issue. To overcome drug resistance issues, the development of effective drugs with novel mechanism(s) of action is required. In this regard, drug repurposing is a viable alternative approach to find novel drugs to overcome drug resistance. Therefore, a FDA-approved-drug-library containing 1930 drugs was analyzed against the dihydrofolate reductase (DHFR) of S. Typhi using deep learning regression algorithms. Initially, a total of 500 compounds were screened, followed by rescreening by molecular docking. Further, from screened compounds by molecular docking, the top eight compounds were subjected to molecular dynamics (MD) simulation. Analysis of MD simulation resulted in four potential compounds, namely; Duvelisib, Amenamevir, Lifitegrast and Nilotinib against the DHFR enzyme. During the MD simulation, these four drugs achieved good stability during the 100 ns trajectory period at 300 K. Further to know the insights of the complex's stability, we calculated RMSF, RG, SASA and interaction energy for the last 60 ns trajectory period because all complexes showed the stability after 40 ns trajectory period. MM-PBSA analysis of the last 10 ns of MD trajectories showed the stability of the complexes. From our results, we conclude that these drugs can also be useful for treating typhoid fever and can inhibit S. Typhi by interfering with the function of the DHFR enzyme. Communicated by Ramaswamy H. Sarma.

Using Chou's 5-steps rule to study pharmacophore-based virtual screening of SARS-CoV-2 Mpro inhibitors

Abstract

Recently emerged SARS-CoV-2 is the cause of the ongoing outbreak of COVID-19. It is responsible for the deaths of millions of people and has caused global economic and social disruption. The numbers of COVID-19 cases are increasing exponentially across the world. Control of this pandemic disease is challenging because there is no effective drug or vaccine available against this virus and this situation demands an urgent need for the development of anti-SARS-CoV-2 potential medicines. In this regard, the main protease (Mpro) has emerged as an essential drug target as it plays a vital role in virus replication and transcription. In this research, we have identified two novel potent inhibitors of the Mpro (PubChem3408741 and PubChem4167619) from PubChem database by pharmacophore-based high-throughput virtual screening. The molecular docking, toxicity, and pharmacophore analysis indicate that these compounds may act as potential anti-viral candidates. The molecular dynamic simulation along with the binding free energy calculation by MMPBSA showed that these compounds bind to Mpro enzyme with high stability over 50 ns. Our results showed that two compounds: PubChem3408741 and PubChem4167619 had the binding free energy of − 94.02 kJ mol⁻¹ and − 122.75 kJ mol⁻¹, respectively, as compared to reference X77 (− 76.48 kJ mol⁻¹). Based on our work’s findings, we propose that these compounds can be considered as lead molecules for targeting Mpro enzyme and they can be potential SARS-CoV-2 inhibitors. These inhibitors could be tested in vitro and explored for effective drug development against COVID-19.

Graphic abstract

Electronic supplementary material

The online version of this article (10.1007/s11030-020-10148-5) contains supplementary material, which is available to authorized users.

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

Predictive modeling by deep learning, virtual screening and molecular dynamics study of natural compounds against SARS-CoV-2 main protease

The whole world is facing a great challenging time due to Coronavirus disease (COVID-19) caused by SARS-CoV-2. Globally, more than 14.6 M people have been diagnosed and more than 595 K deaths are reported. Currently, no effective vaccine or drugs are available to combat COVID-19. Therefore, the whole world is looking for new drug candidates that can treat the COVID-19. In this study, we conducted a virtual screening of natural compounds using a deep-learning method. A deep-learning algorithm was used for the predictive modeling of a CHEMBL3927 dataset of inhibitors of Main protease (Mpro). Several predictive models were developed and evaluated based on R², MAE MSE, RMSE, and Loss. The best model with R²=0.83, MAE = 1.06, MSE = 1.5, RMSE = 1.2, and loss = 1.5 was deployed on the Selleck database containing 1611 natural compounds for virtual screening. The model predicted 500 hits showing the value score between 6.9 and 3.8. The screened compounds were further enriched by molecular docking resulting in 39 compounds based on comparison with the reference (X77). Out of them, only four compounds were found to be drug-like and three were non-toxic. The complexes of compounds and Mpro were finally subjected to Molecular dynamic (MD) simulation for 100 ns. The MMPBSA result showed that two compounds Palmatine and Sauchinone formed very stable complex with Mpro and had free energy of −71.47 kJ mol⁻¹ and −71.68 kJ mol⁻¹ respectively as compared to X77 (−69.58 kJ mol⁻¹). From this study, we can suggest that the identified natural compounds may be considered for therapeutic development against the SARS-CoV-2.

Communicated by Ramaswamy H. Sarma

Molecular dynamics simulation for screening phytochemicals as α-amylase inhibitors from medicinal plants

Diabetes mellitus (DM) is a complicated metabolic disorder with several enzymes, including α-amylase and α-glycosidase. The α-amylase is responsible for postprandial glucose levels; therefore, inhibiting its activity is helpful in diabetes management. Hence, to find natural inhibitors of α-amylase, we have prepared a 257 phytochemical library from selected medicinal plants with antidiabetic activity and conducted a virtual screening and molecular dynamics study. Seventy-nine phytochemicals were screened out of 257 phytochemicals based on binding energy, ranged from -10.1 kcal mol^-1 to -7.6 kcal mol^-1. The binding energies of screened compounds were lower or equal to the reference molecule (-7.6 kcal mol^-1). The binding affinity of six screened phytochemicals was re-scored by X-SCORE. These phytochemicals were subjected to ADMET and Drug-likeness analysis. After screening docking and drug-likeness analysis, six phytochemicals viz., Shahidine, Epicatechin, Quercetin, Isocolumbin, Ellagic acid, Luteolin and a reference molecule (Acarbose) were subjected to Molecular dynamics (MD) simulation to analyze the stability of the docked protein-ligand complex. The values of root mean square deviation, RMSF, RG, SASA, H-Bond, the interaction energy of all protein-ligand complexes were calculated after 30 ns of MD simulation. The results of screened complexes revealed good stability as compared to reference Acarbose. Pharmacophore features of the screened phytochemicals and α-amylase inhibitors showed many common pharmacophore features. Based on finding the screened phytochemicals, e.g. Shahidine, Epicatechin, Quercetin, Isocolumbin, Ellagic acid, and Luteolin, may be used as a potential inhibitors against α-amylase. These phytochemicals could be optimized and synthesized to develop potential drugs to manage and treat diabetes, targeting α-amylase.Communicated by Ramaswamy H. Sarma.

In silico identification of natural fungicide from Melia azedarach against isocitrate lyase of Fusarium graminearum

Isocitrate Lyase (ICL) is a crucial enzyme involved in the Glyoxylate pathway, essential for the virulence of several fungal pathogens including Fusarium graminearum. ICL is a novel target for the discovery of antifungal compounds and F. graminearum ICL inhibitors can be used to control the growth of this fungus. Although, several inhibitors of ICL have been identified, however, most of these inhibitors are not environment-friendly. Hence there is still a need to discover natural inhibitors of ICL that can be more effective. To identify a potential antifungal compound, we performed a structure-based screening of phytochemicals of Melia azedarach against the FgICL structure by molecular docking and 104 ligands were found to have a better docking score as compared to the reference molecule. These compounds were assessed for drug-likeness and ADMET prediction. After molecular docking, drug-likeness and toxicity analysis, six potential compounds (Melianoninol (-6.6 kcal/mol), Nimbinene (-7.7 kcal/mol), Vilasinin (-8.1 kcal/mol), Fraxinellone (-6.7 kcal/mol), Gedunin (-7.8 kcal/mol), and Meldenin (-7.8 kcal/mol)) were subjected for rescoring by X-Score. The structural stability and dynamics of screened compounds at the active site of FgICL were examined using MD simulation and MM-PBSA analysis. The result of MM-PBSA revealed that four phytochemicals viz. Melianoninol, Nimbinene, Vilasinin, and Fraxinellone had binding free energy of -17.25 kcal/mol, -59.35 kcal/mol, -64.79 kcal/mol, and -29.86 kcal/mol, respectively. Molecular dynamics simulation and MM-PBSA demonstrated that these four phytochemicals displayed considerable significant structural and pharmacological properties and could be probable antifungal drug candidates against F. graminearum. These phyotchemicals of M. azedarach may be suitable candidates for further experimental analysis. [Formula: see text]Communicated by Ramaswamy H. Sarma.

In silico screening of natural compounds against COVID-19 by targeting Mpro and ACE2 using molecular docking

OBJECTIVE

Currently, Coronavirus COVID-19 is spreading worldwide very rapidly and its control is very difficult because there is no effective vaccine or drugs available in markets. This virus can infect both animals and people and cause illnesses of the respiratory tract. WHO has declared Coronavirus as pandemic and the whole world is fighting against Coronavirus. Globally, more than 199,478 people have been diagnosed with COVID-19. As of March 18, 2020, more than 167 countries have been affected and more than 8000 deaths have been reported. The main country being affected is China followed by Italy, Iran, Spain, France, and the USA.

MATERIALS AND METHODS

Since there are no effective drugs available against Coronavirus, we conducted virtual screening of phytochemicals to find novel compounds against this virus. Hence, we created a phytochemical library of 318 phytochemicals from 11 plants which have been reported as antiviral, antibacterial and antifungal activity. The phytochemical library was subjected to virtual screening against molecular targets; Main protease (Mpro) and Angiotensin-Converting Enzyme 2 (ACE2).

RESULTS

Top 10 compounds were selected from each target which had better and significantly low binding energy as compared to the reference molecule.

CONCLUSIONS

Based on the binding energy score, we suggest that these compounds can be tested against Coronavirus and used to develop effective antiviral drugs.

In silico screening of potential antidiabetic phytochemicals from Phyllanthus emblica against therapeutic targets of type 2 diabetes

ETHNOPHARMACOLOGICAL RELEVANCE

Phyllanthus emblica Linn. (Syn. Emblica officinalis Gaertn.), has been used to cure many ailments of human beings. Literature survey demonstrates that it has many pharmacological activities i.e. antidiabetic, antioxidant, anti-microbial, antifungal, antiallergic, antiviral, and anticancer properties.

AIM OF THE STUDY

The present study aimed to identify the novel plant-derived antidiabetic compounds from P. emblica to understand the molecular basis of antidiabetic activities.

MATERIAL AND METHODS

Text mining analysis of P. emblica and its disease association was carried out using server DLAD4U. Due to the highest score of P. emblica with diabetes, the virtual screening of a phytochemical library of P. emblica against three targets of diabetes was carried out. After that FAF-Drug4, admetSAR and DruLiTo servers were used for drug-likeness prediction. Additionally, pharmacophore modeling was also carried out to understand the antidiabetic activity of screened compounds.

RESULTS

The docking scores, drug-likeness and pharmacophore studies found that Ellagic acid, Estradiol, Sesamine, Kaempferol, Zeatin, Quercetin, and Leucodelphinidin are potential antidiabetic compounds.

CONCLUSIONS

Our study shows that phytochemicals of P. emblica are very potential antidiabetic candidates. Using the modern techniques these molecules could be used to develop an effective antidiabetic drugs from a natural resource.

Molecular docking and molecular dynamics simulation approach to screen natural compounds for inhibition of Xanthomonas oryzae pv. Oryzae by targeting peptide deformylase

Xanthomonas oryzae pv. Oryzae (Xoo) causes bacterial leaf blight (BLB) of rice which results in a huge loss in production. Many chemicals are used to control BLB disease. However, these chemicals are toxic to the environments, animals and human beings. Thus, there is a demand to discover potential and safe natural pesticides to manage BLB disease successfully. Therefore, we screened a library of phytochemicals of different plants having antibacterial activity by targeting Peptide Deformylase (PDF) of Xoo using in silico techniques. A library of 318 phytochemicals was prepared and subjected to rigid and flexible molecular docking against PDF followed by molecular dynamics simulation and free energy analysis of protein-ligand complexes. The results of virtual screening showed that 14 compounds from different plants have good binding energy as compare to reference molecule (3 R)-2,3-dihydro[1,3] thiazolo [3,2 a]benzimidazol-3-ol) (-7.7 kcal mol^-1). Out of 14 hit compounds, eight compounds that were selected based on binding energy were analyzed by Molecular dynamic (MD) simulation. Analysis of MD simulation revealed that eight compounds namely; Bisdemethoxycurcumin, Rosmarinic acid, Piperanine, Dihydropiperlonguminine, Piperdardine, Dihydrocurcumin and Lonhumosides B achieved good stability during the 80 ns MD simulation at 300 K in term of the RMSD. Further, we calculated RMSF, RG, SASA, and interaction energy after 40 ns due to showing the stability of complexes. From our results, we conclude that these natural compounds could inhibit Xoo by targeting PDF receptor and can be used as potential bactericidal candidates against BLB disease of rice against Xoo and other bacteria. Communicated by Ramaswamy H. Sarma.

In silico screening of anti-inflammatory compounds from Lichen by targeting cyclooxygenase-2

Non-steroidal anti-inflammatory drugs (NSAID) targeting cyclooxygenase-2 are clinically effective. However, they lack anti-thrombotic activity resulting in incidences of adverse effects like myocardial infarction, gastrointestinal and abdominal discomfort which necessitate for discovering new drug candidates with improved therapeutic effects and tolerability. Various recent researches have suggested that many lichens offer a vast reservoir for anti-inflammatory drug candidates which are natural as well as safe for human consumption. Drug discovery is a very complex and time-consuming process; however, in silico techniques can make this process simple and economic. Hence to find out natural anti-inflammatory compounds, we have carried out the virtual screening of 412 lichen compounds by molecular docking with human Cox-2 enzyme and validated the docking score by X-Score followed by ADMET and Drug-likeness analysis. The resulting 6 top-scored compounds were subjected to Molecular dynamics simulation (MDS) to analyze the stability of docked protein-ligand complex, to assess the fluctuation and conformational changes during protein-ligand interaction. The values of RMSD, Rg, and interaction energy after 30 ns of MDS revealed the good stability of these Lichen compounds in the active site pocket of Cox-2 in compare to reference, JMS. Additionally, we have done the pharmacophore analysis which found many common pharmacophore features between Lichen compounds and well known anti-inflammatory compounds. Our result shows that these lichen compounds are potential anti-inflammatory candidates and could be further modified and evaluated to develop more effective anti-inflammatory drugs with fewer side effects for the treatment of inflammatory diseases.Communicated by Ramaswamy H. Sarma.

The duration of intrapartum maternal hyperglycaemia predicts neonatal hypoglycaemia in women with pre-existing diabetes

AIM

There is a high incidence of neonatal hypoglycaemia in neonates born to mothers with pre-existing diabetes. This often necessitates admission to the neonatal intensive care. Guidelines suggest maintaining intrapartum blood glucose levels (BGLs) of 4-7 mmol/l in women with diabetes to reduce the risk of neonatal hypoglycaemia. This study assessed whether intrapartum BGLs in women with pre-gestational Type 1 and 2 diabetes were predictive of neonatal hypoglycaemia.

METHODS

A retrospective analysis of 261 births delivered at a tertiary hospital in Australia from 2009 to 2014.

RESULTS

There were 122 cases of neonatal hypoglycaemia (glucose ≤ 2.6 mmol/l) in 261 births (47%). The mothers in the neonatal hypoglycaemia group spent less time with BGL in the range 4-7 mmol/l [55 ± 37% vs. 65 ± 35%, P = 0.02; odds ratio (OR) 0.992, P = 0.03] and more time with BGL in the 7-10 mmol/l range (31 ± 34% vs. 18 ± 27%, P = 0.003; OR 1.013, P = 0.003) compared with those without neonatal hypoglycaemia. Although statistically significant, receiver operating characteristic (ROC) curve analysis showed that time spent with maternal BGLs in the range 4-7 mmol/l [area under the curve (AUC) = 0.58] or 7-10 mmol (AUC = 0.60) was not strong enough to be a useful clinical predictor of neonatal hypoglycaemia. HbA_1c in the second trimester of pregnancy (P = 0.02, OR 1.42) and percentage time spent in BGL range of 7-10 mmol/l (P = 0.001, OR 1.02) were both associated with a risk of neonatal hypoglycaemia in a logistic regression model. HbA_1c in the third trimester (P = 0.07, OR 1.28) approached, but did not reach, significance.

CONCLUSIONS

These data support a BGL range of 4-7 mmol/l as an intrapartum target. Glycaemic control in the second trimester is associated with neonatal hypoglycaemia. Improvement in ante- and intrapartum glycaemic control may reduce neonatal hypoglycaemia in women with pre-existing diabetes.

A difficult case of recurrent hypoglycaemia: role of insulin assays in establishing the diagnosis

BACKGROUND

Insulin assays are designed to detect endogenous insulin, however, insulin assays produced by different manufacturers may detect exogenous recombinant insulin, with varying degrees of cross-reactivity between different assays. We report a fascinating and difficult case of recurrent hypoglycaemia, where the final diagnosis was established with the help of insulin assays using different platforms.

CASE REPORT

A 24-year-old female presented with recurrent hypoglycaemic episodes on a background of Type 1 diabetes mellitus and a completely resected synovial sarcoma of the right hip several years previously. She reported significant physical, sexual and emotional abuse leading to reduced appetite and weight loss. Despite withdrawing insulin therapy, she experienced profound hypoglycaemic episodes with detectable C-peptide and inappropriately elevated insulin levels, suggesting endogenous hyperinsulinaemic hypoglycaemia; however, localization studies were negative and finally she was found to have exogenous hyperinsulinaemia after discordant insulin levels were detected using two different insulin assays. The C-peptide level was elevated as a result of stimulation by parenteral dextrose and was suppressed after dextrose was ceased. Her Type 1 diabetes mellitus was fabricated and she had factitious hypoglycaemia.

CONCLUSIONS

Factitious hypoglycemia is difficult to diagnose and treat. A low blood glucose level, suppressed C-peptide level and an inappropriately elevated insulin level is the classic finding. We were able to make a diagnosis in the present case after discordant insulin levels were detected on the two different insulin assays, signifying cross-reactivities of the recombinant insulin with the assays. A multidisciplinary team approach with psychiatric input is needed to treat such cases.

SETD2 loss-of-function promotes renal cancer branched evolution through replication stress and impaired DNA repair

Defining mechanisms that generate intratumour heterogeneity and branched evolution may inspire novel therapeutic approaches to limit tumour diversity and adaptation. SETD2 (Su(var), Enhancer of zeste, Trithorax-domain containing 2) trimethylates histone-3 lysine-36 (H3K36me3) at sites of active transcription and is mutated in diverse tumour types, including clear cell renal carcinomas (ccRCCs). Distinct SETD2 mutations have been identified in spatially separated regions in ccRCC, indicative of intratumour heterogeneity. In this study, we have addressed the consequences of SETD2 loss-of-function through an integrated bioinformatics and functional genomics approach. We find that bi-allelic SETD2 aberrations are not associated with microsatellite instability in ccRCC. SETD2 depletion in ccRCC cells revealed aberrant and reduced nucleosome compaction and chromatin association of the key replication proteins minichromosome maintenance complex component (MCM7) and DNA polymerase δ hindering replication fork progression, and failure to load lens epithelium-derived growth factor and the Rad51 homologous recombination repair factor at DNA breaks. Consistent with these data, we observe chromosomal breakpoint locations are biased away from H3K36me3 sites in SETD2 wild-type ccRCCs relative to tumours with bi-allelic SETD2 aberrations and that H3K36me3-negative ccRCCs display elevated DNA damage in vivo. These data suggest a role for SETD2 in maintaining genome integrity through nucleosome stabilization, suppression of replication stress and the coordination of DNA repair.

Diabetes myonecrosis - A rare complication

We report a patient with very rare complication of poorly controlled diabetes. Diabetes myonecrosis is a self-limiting condition with unclear pathogenesis and it most commonly affects the quadriceps muscle. Physicians should consider this diagnosis in diabetic patients presenting with sudden onset, non-traumatic muscular pain.

An association analysis between psychophysical characteristics and genome-wide gene expression changes in human adaptation to the extreme climate at the Antarctic Dome Argus

Genome-wide gene expression measurements have enabled comprehensive studies that integrate the changes of gene expression and phenotypic information to uncover their novel associations. Here we reported the association analysis between psychophysical phenotypes and genome-wide gene expression changes in human adaptation to one of the most extreme climates on Earth, the Antarctic Dome Argus. Dome A is the highest ice feature in Antarctica, and may be the coldest, driest and windiest location on earth. It is considered unapproachable due to its hostile environment. In 2007, a Chinese team of 17 male explorers made the expedition to Dome A for scientific investigation. Overall, 133 psychophysical phenotypes were recorded, and genome-wide gene expression profiles from the blood samples of the explorers were measured before their departure and upon their arrival at Dome A. We found that mood disturbances, including tension (anxiety), depression, anger and fatigue, had a strong, positive, linear relationship with the level of a male sex hormone, testosterone, using the Pearson correlation coefficient (PCC) analysis. We also demonstrated that significantly lowest-level Gene Ontology groups in changes of gene expression in blood cells with erythrocyte removal were consistent with the adaptation of the psychophysical characteristics. Interestingly, we discovered a list of genes that were strongly related to significant phenotypes using phenotype and gene expression PCC analysis. Importantly, among the 70 genes that were identified, most were significantly related to mood disturbances, where 42 genes have been reported in the literature mining, suggesting that the other 28 genes were likely novel genes involved in the mood disturbance mechanism. Taken together, our association analysis provides a reliable method to uncover novel genes and mechanisms related to phenotypes, although further studies are needed.

The long-acting β2 -adrenoceptor agonist, indacaterol, enhances glucocorticoid receptor-mediated transcription in human airway epithelial cells in a gene- and agonist-dependent manner

BACKGROUND AND PURPOSE

Inhaled glucocorticoid (ICS)/long-acting β2 -adrenoceptor agonist (LABA) combination therapy is a recommended treatment option for patients with moderate/severe asthma in whom adequate control cannot be achieved by an ICS alone. Previously, we discovered that LABAs can augment dexamethasone-inducible gene expression and proposed that this effect may explain how these two drugs interact to deliver superior clinical benefit. Herein, we extended that observation by analysing, pharmacodynamically, the effect of the LABA, indacaterol, on glucocorticoid receptor (GR)-mediated gene transcription induced by seven ligands with intrinsic activity values that span the spectrum of full agonism to antagonism.

EXPERIMENTAL APPROACH

BEAS-2B human airway epithelial cells stably transfected with a 2× glucocorticoid response element luciferase reporter were used to model gene transcription together with an analysis of several glucocorticoid-inducible genes.

KEY RESULTS

Indacaterol augmented glucocorticoid-induced reporter activation in a manner that was positively related to the intrinsic activity of the GR agonist. This effect was demonstrated by an increase in response maxima without a change in GR agonist affinity or efficacy. Indacaterol also enhanced glucocorticoid-inducible gene expression. However, the magnitude of this effect was dependent on both the GR agonist and the gene of interest.

CONCLUSIONS AND IMPLICATIONS

These data suggest that indacaterol activates a molecular rheostat, which increases the transcriptional competency of GR in an agonist- and gene-dependent manner without apparently changing the relationship between fractional GR occupancy and response. These findings provide a platform to rationally design ICS/LABA combination therapy that is based on the generation of agonist-dependent gene expression profiles in target and off-target tissues.

An analysis of glucocorticoid receptor-mediated gene expression in BEAS-2B human airway epithelial cells identifies distinct, ligand-directed, transcription profiles with implications for asthma therapeutics

BACKGROUND AND PURPOSE

International asthma guidelines recommend that inhaled glucocorticoids be used as a monotherapy in all patients with mild to moderate disease because of their ability to suppress airways inflammation. Current evidence suggests that the therapeutic benefit of glucocorticoids is due to the transactivation and transrepression of anti-inflammatory and pro-inflammatory genes respectively. However, the extent to which clinically relevant glucocorticoids are equivalent in their ability to modulate gene expression is unclear.

EXPERIMENTAL APPROACH

A pharmacodynamics investigation of glucocorticoid receptor (GR)-mediated gene transactivation in BEAS-2B human airway epithelial cells was performed using a glucocorticoid response element luciferase reporter coupled with an analysis of glucocorticoid-inducible genes encoding proteins with anti-inflammatory and adverse-effect potential.

KEY RESULTS

Using transactivation as a functionally relevant output, a given glucocorticoid displayed a unique, gene expression 'fingerprint' where intrinsic efficacy and GR density were essential determinants. We showed that depending on the gene selected for analysis, a given glucocorticoid can behave as an antagonist, partial agonist, full agonist or even 'super agonist'. In the likely event that different, tissue-dependent gene expression profiles are reproduced in vivo, then the anti-inflammatory and adverse-effect potential of many glucocorticoids currently available as asthma therapeutics may not be equivalent.

CONCLUSIONS AND IMPLICATIONS

The generation of gene expression 'fingerprints' in target and off-target human tissues could assist the rational design of GR agonists with improved therapeutic ratios. This approach could identify compounds that are useful in the management of severe asthma and other inflammatory disorders where systemic exposure is desirable.

Sequenza: allele-specific copy number and mutation profiles from tumor sequencing data

BACKGROUND

Exome or whole-genome deep sequencing of tumor DNA along with paired normal DNA can potentially provide a detailed picture of the somatic mutations that characterize the tumor. However, analysis of such sequence data can be complicated by the presence of normal cells in the tumor specimen, by intratumor heterogeneity, and by the sheer size of the raw data. In particular, determination of copy number variations from exome sequencing data alone has proven difficult; thus, single nucleotide polymorphism (SNP) arrays have often been used for this task. Recently, algorithms to estimate absolute, but not allele-specific, copy number profiles from tumor sequencing data have been described.

MATERIALS AND METHODS

We developed Sequenza, a software package that uses paired tumor-normal DNA sequencing data to estimate tumor cellularity and ploidy, and to calculate allele-specific copy number profiles and mutation profiles. We applied Sequenza, as well as two previously published algorithms, to exome sequence data from 30 tumors from The Cancer Genome Atlas. We assessed the performance of these algorithms by comparing their results with those generated using matched SNP arrays and processed by the allele-specific copy number analysis of tumors (ASCAT) algorithm.

RESULTS

Comparison between Sequenza/exome and SNP/ASCAT revealed strong correlation in cellularity (Pearson's r = 0.90) and ploidy estimates (r = 0.42, or r = 0.94 after manual inspecting alternative solutions). This performance was noticeably superior to previously published algorithms. In addition, in artificial data simulating normal-tumor admixtures, Sequenza detected the correct ploidy in samples with tumor content as low as 30%.

CONCLUSIONS

The agreement between Sequenza and SNP array-based copy number profiles suggests that exome sequencing alone is sufficient not only for identifying small scale mutations but also for estimating cellularity and inferring DNA copy number aberrations.

Formulation, process development and evaluation of artemether and lumefantrine soft gelatin capsule

Artemether and Lumefantrine capsules are indicated for the treatment of P. falciparum malaria cases resistant to both chloroquine and sulphadoxine, pyrimethamine combination. Both artemether and lumefantrine act as blood schizontocides. Artemether is a sesquiterpene lactone derived from artemisinin. Artemisinin is a compound derived from the sweet wormwood plant and has been used for centuries in traditional Chinese medicine to treat fever. Lumefantrine is a synthetic aryl-amino alcohol antimalarial (quinine, mefloquine and halofantrine are members of the same group). Artemether is absorbed fairly rapidly with peak plasma concentrations reached about 2 hours after dosing. Absorption of lumefantrine, a highly lipophilic compound, starts after a lag period of up to 2 hours, with peak plasma concentration about 6-8 hours after dosing. In order to overcome this problem, we have observed that when the drug is given in the soft gelatin dosage form, the bioavailability of the drug is increased. Thus, increasing the absorption of the drug and peak plasma concentration is reached earlier then the conventional dosage form.

Formulation and evaluation of transparent ibuprofen soft gelatin capsule

The compound ibuprofen, 2-(4-isobutylphenyl) propionic acid, has been known e.g. from Martindale, the Extra Pharmacopoeia, 28^th edition, 1982, p.256, as a drug which had anti-inflammatory and analgesic properties. It is used for the treatment of rheumatoid arthritis or other inflammatory diseases of joints, soft tissue rheumatism and gout. Ibuprofen, because of its analgesic properties, has been widely used as anodyne, e.g. against pain or discomfort associated with headache, toothache or menstruation.

A medication suitable to combat acute pain is demanded to display its effects fast which action, in turn, is only achieved by a quick release and good bio-availability of the active-ingredient. It is for the commercial forms in particular that the conditions of preparation must be strictly observed, as minor alterations in production procedures such as mixing, pressure of compression and type of machine will affect the physical properties of the particles of he active ingredient and will deteriorate its bio-availability. It is an object of this presentation to provide a medicament that can be readily taken that contains an active amount of ibuprofen in a carrier, that is simple to prepare and that will quickly display a high activity.

Genome-wide association identifies SKIV2L and MYRIP as protective factors for age-related macular degeneration

Age-related macular degeneration (AMD) is the leading cause of blindness in the elderly in the developed world. We conducted a genome-wide association study in a series of families enriched for AMD and completed a meta-analysis of this new data with results from reanalysis of an existing study of a late-stage case-control cohort. We tested the top findings for replication in 1896 cases and 1866 controls and identified two novel genetic protective factors for AMD. In addition to the complement factor H (CFH) (P=2.3 × 10⁻⁶⁴) and age-related maculopathy susceptibility 2 (ARMS2) (P=1.2 × 10⁻⁶⁰) loci, we observed a protective effect at rs429608, an intronic SNP in SKIV2L (P=5.3 × 10⁻¹⁵), a gene near the complement component 2 (C2)/complement factor B (BF) locus, that indicates the protective effect may be mediated by variants other than the C2/BF variants previously studied. Haplotype analysis at this locus identified three protective haplotypes defined by the rs429608 protective allele. We also identified a new potentially protective effect at rs2679798 in MYRIP (P=2.9 × 10⁻⁴), a gene involved in retinal pigment epithelium melanosome trafficking. Interestingly, MYRIP was initially identified in the family-based scan and was confirmed in the case-control set. From these efforts, we report the identification of two novel protective factors for AMD and confirm the previously known associations at CFH, ARMS2 and C3.

Complement factor H polymorphisms, renal phenotypes and age-related macular degeneration: the Blue Mountains Eye Study

Complement factor H (CFH) is a key regulator of the alternative pathway of complement and its mutations have been associated with membranoproliferative glomerulonephritis type II, atypical hemolytic uremic syndrome and age-related macular degeneration (AMD), suggesting that alternative pathway dysregulation is a common pathogenetic feature of these ocular and renal conditions. In this study we tested the hypothesis that common CFH variants have a global role in renal function in the Australian population-based Blue Mountains Eye Study (BMES). We replicated the association of I62V with estimated glomerular filtration rate (GFR; P=0.017) and creatinine clearance (CRCL; P=0.015). The minor allele of I62V (G) was deleterious: adding one copy of the G allele decreased GFR/CRCL by approximately 0.98 ml min(-1) per 1.73 m(2) (95% confidence interval (CI): 0.97, 0.99). We also replicated the association of Y402H with AMD and provided an unbiased estimate of population attributable risk (PAR). The minor allele of Y402H (C) was deleterious: the odds ratio estimate of CC genotype compared to TT was 1.87 (95% CI: 1.44, 2.45). The PAR of the C allele was estimated as 0.22 (95% CI: 0.15, 0.28). In summary, in the BMES population we confirmed the association between I62V and renal function, as measured by the estimated GFR, plus the association of Y402H with both early- and late-stage AMD.

Renal transplantation in Indo-Asian patients in the UK

Membership of some ethnic groups has an effect on renal transplant outcome but little is known about the impact of Indo-Asian ethnicity, despite this group's high incidence of renal disease. We compared outcomes in Indo-Asians and Caucasians at the Hammersmith Hospital (Indo-Asians, N = 46; Caucasians, N = 90), in the Long-Term Efficacy and Safety Surveillance (LOTESS) database of cyclosporin-treated renal transplant recipients (Indo-Asians, N = 254; Caucasians, N = 4262) and the National Transplant Database held by UK Transplant (Indo-Asians, N = 459; Caucasians, N = 4831). The baseline demographic and co-morbid characteristics of the two ethnic groups were comparable, save for more diabetes in the Indo-Asian community. Following transplantation, the incidence of delayed graft function and steroid-resistant acute rejection were also comparable, as were graft and patient survival (out to 5 years) and graft function. In addition, post-transplant blood pressure, levels of cholesterol and triglycerides and exposure to corticosteroids and cyclosporin were comparable. However, when patients who were not diabetic before transplantation were studied separately, there was an increased incidence of diabetes in the Indo-Asian community (Hammersmith data: Indo-Asians 10.9% vs. Caucasians 3.3%, p = 0.02; LOTESS data Indo-Asians 5.5% vs. Caucasians 1.6%, p < 0.0001). Subsequent management of this group should pursue immunosuppressive regimens less likely to impair post-transplant glucose tolerance.

Sodium butyrate inhibits platelet-derived growth factor-induced proliferation of vascular smooth muscle cells

Sodium butyrate (SB), a naturally occurring short-chain fatty acid, was investigated for its therapeutic value as an antiproliferative agent for vascular smooth muscle cells (SMCs). At 5-mmol/L concentration, SB had no significant effect on rat SMC proliferation. However, at the same concentration, SB inhibited platelet-derived growth factor (PDGF)-AA-, -AB-, and -BB-induced proliferation of SMCs. Exposure of SMCs to PDGF-BB resulted in activation of receptor intrinsic tyrosine kinase activity and autophosphorylation of beta-PDGF-receptor (beta-PDGFR). The activated beta-PDGFR physically associated and phosphorylated signaling molecules such as ras-GTPase activating protein (GAP) and phospholipase C gamma (PLC gamma). SB, in the absence of PDGF-BB, caused neither beta-PDGFR tyrosine phosphorylation nor phosphorylation and association of GAP and PLC gamma with beta-PDGFR. PDGF-BB-enhanced activation of receptor intrinsic tyrosine kinase activity and autophosphorylation of tyrosine residues of beta-PDGFR were unaffected by SB irrespective of whether SMCs were preincubated with SB before exposure to PDGF-BB plus SB or incubated concomitantly with PDGF-BB plus SB. Likewise, phosphorylation and association of GAP and PLC gamma with PDGF-BB-activated beta-PDGFR were unaffected. In addition, SB did not block PDGF-BB-stimulated, PLC gamma-mediated production of inositol triphosphate. Similarly, PDGF-BB-induced beta-PDGFR degradation was unaffected when SMCs were exposed to PDGF-BB plus SB, and SB by itself had no influence on beta-PDGFR degradation. Unlike beta-PDGFR kinase activity, mitogen-activated protein kinase (MAP-kinase) activity was stimulated by SB by about 2.7-fold. Exposure of SMCs to PDGF-BB caused an approximately 11.4-fold increase in MAP-kinase activity and this increase in activity was not significantly affected when cells were coincubated with PDGF-BB and SB (10.3-fold). However, pretreatment of SMCs with SB for 30 minutes and subsequent incubation in PDGF-BB plus SB abolished most of the PDGF-BB-induced MAP-kinase activity (4.6-fold). Transcription of growth response genes such as c-fos, c-jun, and c-myc were induced by PDGF-BB, and their induction was suppressed, particularly c-myc, by incubating SMCs with PDGF-BB plus SB. Similarly, preincubation of cells with SB for 30 minutes and subsequent incubation in PDGF-BB plus SB diminished PDGF-BB-induced transcription of c-fos, c-jun, and c-myc. However, SB by itself had no significant effect on c-fos, c-jun, and c-myc transcription.(ABSTRACT TRUNCATED AT 400 WORDS)

Phytochemical investigation of roots of Pterocarpus marsupium. Isolation and structural studies of two new flavanone glycosides

From the roots of Pterocarpus marsupium 7-Hydroxy-6, 8-dimethyl flavanone-7-O-alpha-L-arabinopyranoside and 7,8,4'-trihydroxy-3', 5'-dimethoxy flavanone-4'-O-beta-D-glucopyranoside have been isolated and their structure elucidated.