ADME/Tox

The receptor protein PfATP6 has been identified as the common target of artemisinin and curcumin. The work was initiated to assess the antimalarial activity of six curcumin derivatives based on their binding affinities and correlating the in silico docking outcome with in vitro antimalarial screening results. A ligand library of thirty two Knoevenagel condensates of curcumin were designed and docked against PfATP6 protein and six compounds with the best binding scores were synthesized and screened for their antimalarial activity against the sensitive 3D7 strain of Plasmodium falciparum. ADME/Tox, pharmacokinetic and pharmacodynamic profiles of the designed compounds were analyzed and reported. 4-FB was found to have similar binding energy to the standard artemisinin (-6.75 and -6.73 respectively) while 4-MB, 3-HB, 2-HB, B, 4-NB displayed better binding energy than curcumin (-5.95, -5.89, -5.68, -5.35, -5.29 and -5.25 respectively). At a dose of 50 µg/mL all the six compounds showed 100% schizont inhibition while at 5µg/ml, five showed more than 75% inhibition and better results than curcumin. 4-FB showed the best activity with 97.8% schizonticidal activity. The in vitro results superimpose the results obtained from the in silico study thereby encouraging development of promising curcumin leads in the battle against malaria.

In this study, the mass balance, pharmacokinetics (PK) and metabolism of atuliflapon, a novel 5-lipoxygenase-activating protein inhibitor, were investigated in healthy male subjects. A single oral dose of 200 mg [ 14 C]atuliflapon suspension was administered to six healthy male subjects. Mass balance, PK and metabolite profiles of atuliflapon were analyzed using radioactivity monitoring and liquid chromatography with mass spectrometry analysis. The safety of atuliflapon was assessed during the study. Atuliflapon was rapidly absorbed with a median tmax of 1.5 h, followed by a biphasic decline in plasma exposure rendering a terminal half-life of ~20 h. Unchanged atuliflapon was the predominant radioactive component in plasma, accounting for 40.1% of the total drug-related exposure (DRE), while a direct N-glucuronide was the only metabolite exceeding 10% of DRE, accounting for 20.9%. Renal excretion of intact atuliflapon accounted for <1% of the administered dose. In total 85.2% of administered radioactivity was recovered over 312 h with 79.3% and 5.9% in feces and urine, respectively. Parent atuliflapon contributed to approximately 40% of This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

A potential antimalarial prospect should have high efficacy with low toxicity. Synriam TM antimalarial drug has been proven to be safe and effective for the treatment of malaria in human with dearth information on rats. This study investigated its potential toxicity from prolonged administration on lipid profiles and haematological indices in rats. Thirtyfive Wistar rats were randomized into five groups (A-E) of seven rats each. Animals in group A (control) received 0.5 mL distilled water, while groups B, C, D, and E respectively received 4.0, 8.0, 16.0 and 32.0 mg/kg bwt of the drug once daily for 28 days. The concentrations of serum TC, LDL and atherogenic index showed significant (p<0.05) decrease, while serum TRIG, HDL, and VLDL concentrations had no effect (p>0.05). The drug also had no effect (p>0.05) on the levels of the red blood cell count, PCV, Hb, MCV, MCH, and MCHC. Similarly, it had no effect (p>0.05) on the levels of the WBC, lymphocytes and neutrocytes, while the platelet counts had slight (p<0.05) decrease. Hence, Synriam TM is relatively safe at doses of 4.0-32.0 mg/kg bwt in rats when taken once daily with minimal effects on the lipid profiles and haematological indices.

Objective: The reason for the failure of most of the anti-HIV drugs are their poor pharmacokinetics, the poor risk to benefit ratio and the drug resistance. With the objective of developing newer pyrazole scaffolds for effective treatment of HIV, binding mode analysis of designing ligands with the HIV-1RT protein and prediction of key ADME and toxicity parameters of the compounds was in an area of interest.Methods: In this study, molecular docking studies and ADME-T studies were carried out in designing of some novel pyrazole analogs. The protein (PDB ID: 1RT2) was prepared using the Protein Preparation Wizard (Schrodinger Glide 5.0). ADME parameters calculated by QikProp 3.0v and toxicity of designed analogs checked by using two different online software’s namely Lazar and protox.Results: Most of the designed pyrazole analogs have good oral absorption as well as good binding affinity towards HIV-1 reverse transcriptase.Conclusion: Finally total 5 analogs (SGS-2, 3, 12, 13 and 14) f...

Thirty-four imidazole-based compounds synthesized by one-pot catalytic method were evaluated for their antifungal and antibacterial activities against several fungal and bacterial strains. None of the compounds had antibacterial activity. Interestingly, compounds 1, 2, 3, 10 and 15 displayed a strong antifungal activity against all the tested fungal species, while compounds 5, 7, 9, 11, 21 and 27 showed a moderate antifungal activity. To better understand the biological activity of the most active compounds ADME-Tox and molecular docking studies were carried out. Interestingly, compounds 1, 2, 3, 7, 10 and 15 showed excellent bioavailability. In addition, compounds 1, 2 and 3, exhibited good toxicity profiles. Docking studies of the two most active compounds 2 (IC 50 of 95 ± 7.07 μM) and 10 (IC 50 of 235 ± 7.07 μM) suggested that they might act by inhibiting the fungal lanosterol 14α-demethylase. Therefore, these novel antifungal agents merit further characterization for the development of new antifungal therapeutics.

Objective: The reason for the failure of most of the anti-HIV drugs are their poor pharmacokinetics, the poor risk to benefit ratio and the drug resistance. With the objective of developing newer pyrazole scaffolds for effective treatment of HIV, binding mode analysis of designing ligands with the HIV-1RT protein and prediction of key ADME and toxicity parameters of the compounds was in an area of interest. Methods: In this study, molecular docking studies and ADME-T studies were carried out in designing of some novel pyrazole analogs. The protein (PDB ID: 1RT2) was prepared using the Protein Preparation Wizard (Schrodinger Glide 5.0). ADME parameters calculated by QikProp 3.0v and toxicity of designed analogs checked by using two different online software's namely Lazar and protox. Results: Most of the designed pyrazole analogs have good oral absorption as well as good binding affinity towards HIV-1 reverse transcriptase. Conclusion: Finally total 5 analogs (SGS-2, 3, 12, 13 and 14) from the 14 designed leads were found to be best on the basis of molecular docking and ADME-T studies.

The human ether-ago go (hERG) potassium channel (K v 11.1) plays a critical role in mediating cardiac action potential. The blockade of this ion channel can potentially lead fatal disorder and/or long QT syndrome. Many drugs have been withdrawn because of their serious hERG-cardiotoxicity. It is crucial to assess the hERG blockade activity in the early stage of drug discovery. We are particularly interested in the hERG-cardiotoxicity of compounds collected in the DrugBank database considering that many DrugBank compounds have been approved for therapeutic treatments or have high potential to become drugs. Machine learning-based in silico tools offer a rapid and economical platform to virtually screen DrugBank compounds. We design accurate and robust classifiers for blockers/non-blockers and then build re-1

The human ether-ago go (hERG) potassium channel (K v 11.1) plays a critical role in mediating cardiac action potential. The blockade of this ion channel can potentially lead fatal disorder and/or long QT syndrome. Many drugs have been withdrawn because of their serious hERG-cardiotoxicity. It is crucial to assess the hERG blockade activity in the early stage of drug discovery. We are particularly interested in the hERG-cardiotoxicity of compounds collected in the DrugBank database considering that many DrugBank compounds have been approved for therapeutic treatments or have high potential to become drugs. Machine learning-based in silico tools offer a rapid and economical platform to virtually screen DrugBank compounds. We design accurate and robust classifiers for blockers/non-blockers and then build re-1

The receptor protein PfATP6 has been identified as the common target of artemisinin and curcumin. The work was initiated to assess the antimalarial activity of six curcumin derivatives based on their binding affinities and correlating the in silico docking outcome with in vitro antimalarial screening results. A ligand library of thirty two Knoevenagel condensates of curcumin were designed and docked against PfATP6 protein and six compounds with the best binding scores were synthesized and screened for their antimalarial activity against the sensitive 3D7 strain of Plasmodium falciparum. ADME/Tox, pharmacokinetic and pharmacodynamic profiles of the designed compounds were analyzed and reported. 4-FB was found to have similar binding energy to the standard artemisinin (-6.75 and-6.73 respectively) while 4-MB, 3-HB, 2-HB, B, 4-NB displayed better binding energy than curcumin (-5.95,-5.89,-5.68,-5.35,-5.29 and-5.25 respectively). At a dose of 50 µg/mL all the six compounds showed 100% schizont inhibition while at 5µg/ml, five showed more than 75% inhibition and better results than curcumin. 4-FB showed the best activity with 97.8% schizonticidal activity. The in vitro results superimpose the results obtained from the in silico study thereby encouraging development of promising curcumin leads in the battle against malaria.

Anacardic acid (AA) and its derivatives are wellknown for their therapeutic applications ranging from antitumor, antibacterial, antioxidant, anticancer, and so forth. However, their poor pharmacokinetic and safety properties create significant hurdles in the formulation of the final drug molecule. As a part of our endeavor to enhance the potential and exploration of the anticancer activities, a detailed study on the properties of selected AA derivatives was performed in this work. A comprehensive analysis of the drug-like properties of 100 naturally occurring AA derivatives was performed, and the results were compared with certain marketed anticancer drugs. The work focused on the understanding of the interplay among eight physicochemical properties. The relationships between the physicochemical properties, absorption, distribution, metabolism, and excretion attributes, and the in silico toxicity profile for the set of AA derivatives were established. The ligand efficacy of the finally scrutinized 17 AA derivatives on the basis of pharmacokinetic properties and toxicity parameters was further subjected to dock against the potential anticancer target cyclin-dependent kinase 2 (PDB ID: 1W98). In the docked complex, the ligand molecules (AA derivatives) selectively bind with the target residues, and a high binding affinity of the ligand molecules was ensured by the full fitness score using the SwissDock Web server. The BOILED-Egg model shows that out of 17 scrutinized molecules, 3 molecules exhibit gastrointestinal absorption capability and 14 molecules exhibit permeability through the blood−brain barrier penetration. The analysis can also provide some useful insights to chemists to modify the existing natural scaffolds in designing new anacardic anticancer drugs. The increased probability of success may lead to the identification of drug-like candidates with favorable safety profiles after further clinical evaluation.

Background The current study evaluates the analgesic effect of different extracts of Hopea odorata leaves in mice followed by molecular docking and absorption, distribution, metabolism, excretion, and toxicity (ADME/T) analysis of isolated compounds derived from the plant with the COX-1 enzyme. Methods In the present study, the dried leaves of H. odorata were subjected to extraction using methanol, ethanol, and water. In vivo analgesic activity was evaluated by using the acetic acid-induced writhing test and formalin-induced paw licking test, and in silico molecular docking and ADME/T study were performed using Schrödinger Maestro (version 11.1) and online-based tools, respectively, on eight isolated compounds. Results The results showed that the methanolic extract of leaves has highest significant dose-dependent analgesic activity at both 200 and 400 mg/kg followed by ethanolic extract of leaves. Among all the compounds, ampelopsin showed the best docking score of -7.055, ensuring ...

Bedaquiline (TMC-207) is a key anti-tubercular drug to fight against multidrug resistance tuberculosis. Little information is available till date on the impact of any disease state toward its pharmacokinetic behavior. The present research work aimed to investigate the effect of renal impairment and diabetes mellitus on the oral pharmacokinetics of bedaquiline in the rat model. Renal impairment and diabetes mellitus were induced in the Wistar rat model separately using cisplatin and streptozotocin, respectively, and thereafter, an oral pharmacokinetic study of bedaquiline was carried out in the individual disease models as well as in the normal rat model. Pharmacokinetic parameters of bedaquiline were not altered markedly in cisplatin-induced renal-impaired rats compared to normal rats except an area under the curve (AUC) for plasma concentration of bedaquiline in the experimental time frame (AUC 0−t) reduced to 3477 ± 228 from 4984 ± 1174 ng h/mL, respectively. Maximum plasma concentrations of bedaquiline (259 ± 77 ng/mL), AUC 0−t (3112 ± 1046 ng h/mL), and AUC 0−∞ (3673 ± 1493 ng h/mL) were significantly reduced along with an increase in the clearance of bedaquiline (3.1 ± 1.1 L/h/kg) in the case of streptozotocin-induced diabetic rats compared to respective pharmacokinetic parameters of bedaquiline (482 ± 170 ng/mL, 4984 ± 1174 ng h/mL, and 6137 ± 1542 ng h/mL) in the normal rats. Preclinical findings suggest that dose adjustment of bedaquiline is required in the diabetes mellitus condition to prevent the therapeutic failure of bedaquiline treatment, but clinical exploration is needed to establish the fact. It is the first report for the consequence of renal impairment and diabetes mellitus on the pharmacokinetics of bedaquiline in the preclinical model.

Bedaquiline (TMC-207) is a key anti-tubercular drug to fight against multidrug resistance tuberculosis. Little information is available till date on the impact of any disease state toward its pharmacokinetic behavior. The present research work aimed to investigate the effect of renal impairment and diabetes mellitus on the oral pharmacokinetics of bedaquiline in the rat model. Renal impairment and diabetes mellitus were induced in the Wistar rat model separately using cisplatin and streptozotocin, respectively, and thereafter, an oral pharmacokinetic study of bedaquiline was carried out in the individual disease models as well as in the normal rat model. Pharmacokinetic parameters of bedaquiline were not altered markedly in cisplatin-induced renal-impaired rats compared to normal rats except an area under the curve (AUC) for plasma concentration of bedaquiline in the experimental time frame (AUC 0−t) reduced to 3477 ± 228 from 4984 ± 1174 ng h/mL, respectively. Maximum plasma concentrations of bedaquiline (259 ± 77 ng/mL), AUC 0−t (3112 ± 1046 ng h/mL), and AUC 0−∞ (3673 ± 1493 ng h/mL) were significantly reduced along with an increase in the clearance of bedaquiline (3.1 ± 1.1 L/h/kg) in the case of streptozotocin-induced diabetic rats compared to respective pharmacokinetic parameters of bedaquiline (482 ± 170 ng/mL, 4984 ± 1174 ng h/mL, and 6137 ± 1542 ng h/mL) in the normal rats. Preclinical findings suggest that dose adjustment of bedaquiline is required in the diabetes mellitus condition to prevent the therapeutic failure of bedaquiline treatment, but clinical exploration is needed to establish the fact. It is the first report for the consequence of renal impairment and diabetes mellitus on the pharmacokinetics of bedaquiline in the preclinical model.

Epilepsy is a chronic neurological disorder affecting nearly 65-70 million people worldwide. Despite the observed advances in the development of new antiepileptic drugs (AEDs), still about 30-40% of patients cannot achieve a satisfactory seizure control. In our current research, we aimed at using the combined results of radioligand binding experiments, PAMPA-BBB assay and animal experimentations in order to design a group of compounds that exhibit broad spectrum of anticonvulsant activity. The synthesized 4-alkyl-5-substituted-1,2,4triazole-3-thione derivatives were primarily screened in the maximal electroshock-induced seizure (MES) test in mice. Next, the most promising compounds (17, 22) were investigated in 6 Hz (32 mA) psychomotor seizure model. Protective effect of compound 22 was almost similar to that of levetiracetam. Moreover, these compounds did not induce genotoxic and hemolytic changes in human cells as well as they were characterized by low cellular toxicity. Taking into account the structural requirements for good anticonvulsant activity of 4-alkyl-5aryl-1,2,4-triazole-3-thiones, it is visible that small electron-withdrawing substituents attached to phenyl ring have beneficial effects both on affinity towards VGSCs and protective activity in the animal models of epilepsy.

Epilepsy is a chronic neurological disorder affecting nearly 65-70 million people worldwide. Despite the observed advances in the development of new antiepileptic drugs (AEDs), still about 30-40% of patients cannot achieve a satisfactory seizure control. In our current research, we aimed at using the combined results of radioligand binding experiments, PAMPA-BBB assay and animal experimentations in order to design a group of compounds that exhibit broad spectrum of anticonvulsant activity. The synthesized 4-alkyl-5-substituted-1,2,4triazole-3-thione derivatives were primarily screened in the maximal electroshock-induced seizure (MES) test in mice. Next, the most promising compounds (17, 22) were investigated in 6 Hz (32 mA) psychomotor seizure model. Protective effect of compound 22 was almost similar to that of levetiracetam. Moreover, these compounds did not induce genotoxic and hemolytic changes in human cells as well as they were characterized by low cellular toxicity. Taking into account the structural requirements for good anticonvulsant activity of 4-alkyl-5aryl-1,2,4-triazole-3-thiones, it is visible that small electron-withdrawing substituents attached to phenyl ring have beneficial effects both on affinity towards VGSCs and protective activity in the animal models of epilepsy.

Anacardic acid (AA) and its derivatives are wellknown for their therapeutic applications ranging from antitumor, antibacterial, antioxidant, anticancer, and so forth. However, their poor pharmacokinetic and safety properties create significant hurdles in the formulation of the final drug molecule. As a part of our endeavor to enhance the potential and exploration of the anticancer activities, a detailed study on the properties of selected AA derivatives was performed in this work. A comprehensive analysis of the drug-like properties of 100 naturally occurring AA derivatives was performed, and the results were compared with certain marketed anticancer drugs. The work focused on the understanding of the interplay among eight physicochemical properties. The relationships between the physicochemical properties, absorption, distribution, metabolism, and excretion attributes, and the in silico toxicity profile for the set of AA derivatives were established. The ligand efficacy of the finally scrutinized 17 AA derivatives on the basis of pharmacokinetic properties and toxicity parameters was further subjected to dock against the potential anticancer target cyclin-dependent kinase 2 (PDB ID: 1W98). In the docked complex, the ligand molecules (AA derivatives) selectively bind with the target residues, and a high binding affinity of the ligand molecules was ensured by the full fitness score using the SwissDock Web server. The BOILED-Egg model shows that out of 17 scrutinized molecules, 3 molecules exhibit gastrointestinal absorption capability and 14 molecules exhibit permeability through the blood−brain barrier penetration. The analysis can also provide some useful insights to chemists to modify the existing natural scaffolds in designing new anacardic anticancer drugs. The increased probability of success may lead to the identification of drug-like candidates with favorable safety profiles after further clinical evaluation.

The development and approval of new drug is a tedious, expensive and highly time-consuming task. The demand of new drugs is increasing, and the development of natural drugs and traditional drugs are re-emerging as a new strategic task. The in-silico techniques have boosted the development of potential drug candidates. One important category of drugs is nootropes. It improves the cognitive function, memory, motivation and creativity in healthy individuals. The demand of the nootropic drugs has skyrocketed in past few decades. Modafiendz is a novel drug that is often used by the consumers as it is having similarity in structure and property with modafinil (Nootropic drug). But no major studies have been carried out on this molecule, so remains an investigatory molecule. There are several in-silico techniques that can be used to predict the likeness, metabolic activity and pharmacological property of a molecule. In the current study, realizing the importance of modafiendz, various prop...

In the past few years several developments in medications have been made for the better treatment of certain diseases like Breast Cancer, Alzheimer’s disease, Tuberculosis, Obesity and Malaria. Phytochemicals possessing various medicinal properties have opened up the door to discover or design novel drug against these diseases. Syringic acid is such a natural compound found in many plants with a vast range of therapeutic potentials against several diseases. The present study aims to reveal Syringic acid as a potent inhibitor against Breast Cancer, Alzheimer’s disease, Tuberculosis, Obesity and Malaria comparing to the standard drugs of each disease. Molecular docking of syringic acid with critical proteins associated with the diseases was done using Schrödinger Maestro (v11.1). QikProp module of Schrödinger Maestro was used for ADME prediction and the toxicity of the ligand was evaluated by ProTox online databases. Syringic acid was found to exhibit acceptable ADME properties with n...

Developing a new agent in the anti-inflammatory and analgesic field, plants secondary metabolites can be a good source for the Non-Steroidal Anti-inflammatory Drugs (NSAID) drug development. For this purpose we subjected the active compounds of Mimosa pudica Linn. to reveal its potentiality by molecular docking analysis to find out its potent compound against COX which was done by GOLD docking analysis. Docking studies by GOLD showed that vitexin of Mimosa pudica had the highest fitness score against the COX-1 which is 60.43 and 63.49 for COX-2 enzyme. Vitexin of Mimosa pudica detected with significant fitness score and hydrogen bonding against COX-1 and COX-2 which may be a potent analgesic compound.

Drug discovery is shifting focus from industry to outside partners and, in the process, creating new bottlenecks. Technologies like high throughput screening (HTS) have moved to a larger number of academic and institutional laboratories in the USA, with little coordination or consideration of the outputs and creating a translational gap. Although there have been collaborative public-private partnerships in Europe to share pharmaceutical data, the USA has lagged behind. Sharing precompetitive computational models may be the next frontier to provide confidence in the quality of leads produced and attract investment. We now suggest four disruptive strategies for removing drug discovery bottlenecks and discuss some novel ideas for the future to rectify the current unsustainable situation. 10 Dix, D.J. et al. (2007) The ToxCast program for prioritizing toxicity testing of environmental chemicals. Toxicol Sci 95 (1), 5-12 11 Judson, R. et al. (2009) The toxicity data landscape for environmental chemicals.

In the last decade, many statistical-based approaches have been developed to improve poor pharmacokinetics (PK) and to reduce toxicity of lead compounds, which are one of the main causes of high failure rate in drug development. Predictive QSAR models are not always very efficient due to the low number of available biological data and the differences in the experimental protocols. Fortunately, the number of available databases continues to grow every year. However, it remains a challenge to determine the source and the quality of the original data. The main goal is to identify the relevant databases required to generate the most robust predictive models. In this study, an interactive network of databases was proposed to easily find online data sources related to ADME-Tox parameters data. In this map, relevant information regarding scope of application, data availability and data redundancy can be obtained for each data source. To illustrate the usage of data mining from the network, a dataset on plasma protein binding is selected based on various sources such as DrugBank, PubChem and ChEMBL databases. A total of 2,606 unique molecules with experimental values of PPB were extracted and can constitute a consistent dataset for QSAR modeling.

In this paper, we discuss how we safely exchanged proprietary data between third parties in the early years of predictive ADME/Tox model development. At that time, industry scientists wanted to evaluate predictive models, but were not willing to share their structures with software vendors. At the same time, model developers were willing to run the scientists' structures through their models, but they were not willing to reveal which descriptors were important for a particular predictive model. We developed a process where scientists could perform calculations on a broad number of commercially available public descriptors and forward results as a property file, instead of their structures. Meanwhile, the model developer could extract descriptors used in the predictive model, run the model, and pass results back to the scientist. On the following pages, we discuss the pros

β-ketoacyl [acyl carrier protein] synthase A is a key enzyme in the mycobacterial cell wall. The inhibitors for this enzyme can block bacterial cell wall synthesis by blocking Fatty Acid Synthase-II enzyme and thereby stopping mycolic acid synthesis, hence kills the bacteria. Seven ligands were found out after checking their toxicity properties and were docked against the drug target. The result showed highest score for ligand 7 and lowest for ligand 1 i.e., -14.71 and -2.88 respectively. Again ligand L4 and L5 showed moderate score of -14.33 and -13.89 respectively. QSAR model was prepared for eight thiolactomycin compounds and the plot was generated. That was employed to predict the activity of the selected ligands. The prediction showed that ligand L4 and L5 have lower IC50 value of 2.81 µM and 1.62 µM. So these can be potent drugs for the treatment of tuberculosis. The statistical analysis revealed highly significant correlation amongst the data.

Objectives: Flavonoids constitute a large class of polyphenols found in plants. Among flavonoids, Flavonols are the most abundant and widely distributed in nature. Flavonols are present in considerable amounts in fruits and vegetables. They show a wide range of biological activities. In the present study, we wanted to access the cardioprotective activity of some selected flavonols using in silico tools. Method: Binding affinity of flavonols against known cardioprotective drug target Malonyl Coenzyme A was calculated by performing the docking experiment using FlexX. Results: The analysis showed that flavonols have high potential to inhibit the target. The docking studies also showed greater affinity of all selected flavonols towards the active site of Malonyl Coenzyme A with a docking score of -29.2358 Kcal/mol for Morin, -29.0486 Kcal/mol for Kaempferol, -28.3885 Kcal/mol for Fisetin, -27.5950 Kcal/mol for Quercetin, -27.5303 Kcal/mol for Isorhamnetin, -25.7692 Kcal/mol for Myriceti...

The advent of Multi Drug Resistant (MDR) strain of Mycobacterium tuberculosis (TB) necessitated search for new drug targets for the bacterium. It is reported that 3.3% of all new tuberculosis cases had multidrug resistance (MDR-TB) in 2009 and each year, about 0.44 million MDR-TB cases are estimated to emerge and 0.15 million people with MDR-TB die. Keeping such an alarming situation under consideration we wanted to design suitable anti tubercular molecules for new target using computational tools. In the work Methionine aminopeptidase (MetAP) of Mycobacterium tuberculosis was considered as target and three non-toxic phenolic=ketonic compounds were considered as ligands. Docking was done with Flex X and AutoDock 4.2 separately. Ten proven inhibitors of MetAP were collected from literature with their IC50 and were correlated using EasyQSAR to generate QSAR model. Activity of ligands in question was predicted from QSAR. Pharmacophore for each docking was generated using Ligandscout 3....

Natural products continue to be major sources of bioactive compounds and drug candidates not only because of their unique chemical structures but also because of their overall favorable metabolism and pharmacokinetic properties. The number of publicly accessible natural product databases has increased significantly in the past few years. However, the systematic ADME/Tox profile has been reported on a limited basis. For instance, BIOFACQUIM was recently published as a public database of natural products from Mexico, a country with a rich source of biomolecules. However, its ADME/Tox profile has not been reported. Herein, we discuss the results of an in-depth in silico ADME/Tox profile of natural products in BIOFACQUIM and other large public collections of natural products. It was concluded that the absorption and distribution profiles of compounds in BIOFACQUIM are similar to those of approved drugs, while the metabolism profile is comparable to that in the other natural product databases. The excretion profile of compounds in BIOFACQUIM is different from that of the approved drugs, but their predicted toxicity profile is comparable. This work further contributes to the deeper characterization of natural product collections as major sources of bioactive compounds with therapeutic potential.

Alpinia calcarata (Family-Zingiberaceae) is a medicinal plant grows in different parts of Bangladesh. It is commonly used in traditional medicinal system to treat cough, respiratory ailments, bronchitis, asthma, arthritis and diabetes. The aim of our study was to carry out molecular docking to investigate potential binding affinities of phytoconstituents from Alpinia calcarata namely 1,8-Cineole, Alpha Fenchyl Acetate, Calcaratarin-D, Herniarin, Methyl Cinnamate, Quercetin, Shyobunone and Syringic Acid towards COX-1 and COX-2 for analgesic activity. Server based in silico pass prediction of the compounds was performed. Selected phytochemicals were also analyzed for ADME/T properties using QikProp Module. Among a wide range of docking score quercetin and calcaratarin-D showed the best score against both cyclooxygenase enzymes which are-8.047 and-8.28 respectively. So quercetin and calcaratarin-D are the best compounds toward COX-1 and COX-2 as they posses highest docking scores. Pass prediction for analgesic activity of the selected constituents showed greater P a than P i for analgesic activity. Also the results from ADME/T properties ensured the compounds safe for human.

Developing a new agent in the analgesic field, plants secondary metabolites can be a good source for the Non-Steroidal Anti-inflammatory Drugs (NSAID) drug development. For this purpose we subjected the active compounds Clausena lansium of to reveal its potentiality by molecular docking analysis to find out its potent compound against COX-1 and COX-2 which was done by Maestro v 10.1 (Schrodinger) docking analysis. Docking studies by Maestro v 10.1 (Schrodinger) showed that Murrayanine and Clausenaline E of Clausena lansium had the lowest docking score respectively against the COX-1 and COX2 which are-6.471 and-8.325. Murrayanine and Clausenaline E from Clausena lansium detected with significant docking score which may be a potent analgesic compound because the less docking score, the compound will be more potent.

EPA’s National Center for Computational Toxicology is developing automated workflows for curating large databases and providing accurate linkages of data to chemical structures, exposure and hazard information.  The data are being made available via the EPA’s CompTox Chemistry Dashboard (https://comptox.epa.gov/dashboard), a publicly accessible website providing access to data for almost 760,000 chemical substances, the majority of these represented as chemical structures. The web application delivers a wide array of computed and measured physicochemical properties, in vitro high-throughput screening data and in vivo toxicity data as well as integrated chemical linkages to a growing list of literature, toxicology, and analytical chemistry websites. In addition, several specific search types are in development to directly support the mass spectroscopy non-targeted screening community, who are generating important data for detecting and assessing environmental exposures to chemicals contained within DSSTox.  The application provides access to segregated lists of chemicals that are of specific interests to relevant stakeholders including, for example, scientists interested in algal toxins and hydraulic fracturing chemicals.  This presentation will provide an overview of the challenges associated with the curation of data from EPA’s December 2016 Hydraulic Fracturing Drinking Water Assessment Report that represented chemicals reported to be used in hydraulic fracturing fluids and those found in produced water. The data have been integrated into the dashboard with a number of resulting benefits: a searchable database of chemical properties, with hazard and exposure predictions, and open literature. The application of the dashboard to support mass spectrometry non-targeted analysis studies will also be reviewed. This abstract does not reflect U.S. EPA policy.

The U.S. Environmental Protection Agency (EPA) Computational Toxicology Program integrates advances in biology, chemistry, and computer science to help prioritize chemicals for further research based on potential human health risks. This work involves computational and data driven approaches that integrate chemistry, exposure and biological data. These efforts have produced rich data collections of chemical and bioassay data and resulted in the development of numerous software tools for delivering the data to the community. Much has been learned from the development of a disparate suite of software applications and recent work has focused on the integration of the various data sources into a new software architecture. This is intended to reduce the learning curve for multiple applications, uses curated data sources to improve data integration and recall and ultimately delivers better data in a more consumable form for both the user visiting a website and to computers visiting web services. The resulting application has been used to deliver the CompTox chemistry dashboard. This application provides access to ~720,000 chemicals and associated experimental and predicted properties, high-throughput screening data from the ToxCast project and product and functional use data for thousands of chemicals. Flexible searching supports simple chemical identifier look-up based on chemical name and CAS registry number (CASRN) and structure identification is feasible using mass and formula based searching to support mass spectrometrists performing non-targeted analysis. Batch-based searching provides the user with the ability to look up large collections of chemical data using inputs based on name, CASRN, InChIkeys and other identifiers and to export associated information in a series of standard file formats. The CompTox Chemistry Dashboard architecture and development approach has delivered a foundation architecture on which to build new applications for use within the Agency and for use by the research community. This poster will review the software architecture, data streams and the present capabilities of the CompTox Chemistry Dashboard.    This abstract does not reflect U.S. EPA policy.

Over the past decade we have seen a growth in the provision of chemistry data and cheminformatics tools as either free websites or software as a service (SaaS) commercial offerings. These have transformed how we find molecule-related data and use such tools in our research. There have also been efforts to improve collaboration between researchers either openly or through secure transactions using commercial tools. A major challenge in the future will be how such databases and software approaches handle larger data as it accumulates from high throughput screening and enable the user to draw insights, enable predictions and move projects forward. We now discuss how information from some datasets can be made more accessible and how privacy of data should not overwhelm the desire to share it at an appropriate time.

This study aims to predict whether the isolated compounds from Flemingia macrophylla have thrombolytic effects, which were done by using two in silico tools PASS prediction and Molecular docking. Nine phytoconstituents namely beta-sitosterol, cajanin, flemichin E, flemiflavanone A, fleminone, genistein, genistin, kushenol E, neoraufurane, prunetin and stigmasterol were analyzed by the PASS prediction for their thrombolytic activity and found wide range of activity. Flemichin E was the best compound for thrombolytic effect
from all the compounds, though it had much bigger Pa value (0.466) than Pi value (0.004). As a result, flemichin E had 116.5 ratio (Pa : Pi) value. A wide range of docking score found during molecular docking by CPI server. Beta-sitosterol, cajanin, flemichin E, flemiflavanone A, genistein, genistin, kushenol E, neoraufurane and prunetin showed the docking score -7.9, -
8.4, -8.8, -8.6, -8.0, -8.6, -8.7, -8.3 and -7.9, respectively. Data from the both in silico models showed similar values for the same compound, because flemichin E showed high value and
beta-sitosterol, prunetin showed low value in both in silico models. All the data supported that flemichin E is the best compound for thrombosis management, as it possessed higher
value both in PASS prediction and Molecular docking. After flemichin E, genistin showed well docking score (-8.6) and good prediction for thrombolytic effect in PASS prediction.
Further in vitro and in vivo investigation need to identify whether flemichin E, genistin and other compounds have thrombolytic effect or not.

The current rise in the use of open lab notebook techniques means that there are an increasing number of scientists who make chemical information freely and openly available to the entire community as a series of micropublications that are released shortly after the conclusion of each experiment. We propose that this trend be accompanied by a thorough examination of data sharing priorities. We argue that the most significant immediate benefactor of open data is in fact chemical algorithms, which are capable of absorbing vast quantities of data, and using it to present concise insights to working chemists, on a scale that could not be achieved by traditional publication methods. Making this goal practically achievable will require a paradigm shift in the way individual scientists translate their data into digital form, since most contemporary methods of data entry are designed for presentation to humans rather than consumption by machine learning algorithms. We discuss some of the co...

Over the past decade we have seen a growth in the provision of chemistry data and cheminformatics tools as either free websites or software as a service (SaaS) commercial offerings. These have transformed how we find molecule-related data and use such tools in our research. There have also been efforts to improve collaboration between researchers either openly or through secure transactions using commercial tools. A major challenge in the future will be how such databases and software approaches handle larger data as it accumulates from high throughput screening and enable the user to draw insights, enable predictions and move projects forward. We now discuss how information from some datasets can be made more accessible and how privacy of data should not overwhelm the desire to share it at an appropriate time.

The current system of dissemination of scientific data and knowledge is far less efficient than it needs to be to facilitate improved collaborative science, especially considering current publication vehicles and infrastructure. There is a growing movement promoting more Open Science with the belief that a more transparent scientific process can perform far more effectively. The logical extension of this concept is full transparency -exposing a researcher's complete record of progress to the public in near real time. Not only will such a process enable ongoing data sharing it also provides an opportunity to develop collaborative communities of scientists and, at the conclusion of data acquisition, can enable communal extraction of conclusions when necessary. We have named this approach Open Notebook Science and have demonstrated its implementation and feasibility with the UsefulChem project, started in the summer of 2005, with the aim of synthesizing novel anti-malarial compounds. Our system currently uses free hosted services using general blog and wiki functions to facilitate replication across any scientific domains. These services are not chemically intelligent and are limited to text and graphic based data sharing only. For Open Notebook Chemistry the ability to intelligently manipulate, manage and search chemical structures and associated data is necessary and we have demonstrated proof of concept capabilities by integrating with the ChemSpider service, a free access online database managing chemical structures and focused on developing a structure centric community for chemists. This work will require the development of a chemically intelligent software platform to extend the capabilities of both the blog and the wiki environment for managing Open Notebook Science. The exposure of raw experimental procedures and data in a semantically rich format will enable the participation of both human and autonomous agents in the process of scientific discovery. This phenomenon of spontaneous group intelligence, referred to as "Crowdsourcing", has proven valuable in several contexts. Already, productive collaborations have been forged within the UsefulChem project with groups from Indiana University, Nanyang Technological University, the National Cancer Institute and UC San Francisco.

Since 2004 public cheminformatic databases and their collective functionality for exploring relationships between compounds, protein sequences, literature and assay data have advanced dramatically. In parallel, commercial sources that extract and curate such relationships from journals and patents have also been expanding. This work updates a previous comparative study of databases chosen because of their bioactive content, availability of downloads and facility to select informative subsets.

The increase in drug research output from patents, journal articles and public data collections has made it essential for pharmaceutical companies to integrate the extracted ' SAR estate'. The AstraZeneca response has been the development of an enterprise application, Chemistry Connect, containing 45 million unique chemical structures from 18 internal and external sources. It merges compound-to-assay-to-result-to-target relationships so that users can explore their connectivity by searching with drug names, synonyms, chemical structures, patent numbers and target protein identifiers, at a scale not previously available.

The last two years have seen a dramatic expansion in public cheminformatics, as exemplified by the approximate five-fold growth of PubChem from over 50 contributing data sources. Consequently, medicinal chemists who were hitherto limited to commercial databases now also have access to public sources that they can download and/or query directly over the Web. The range of public sources, particularly where they link out to structured bioinformatic and biological data, already offer utilities that have no commercial equivalent. This work reviews compound content comparisons between selected public and commercial databases that capture bioactive content. We focused particularly on those that specify relationships between compounds and their protein targets. Our stringent filtering produced lower unique compound numbers than those reported for individual databases and thereby facilitated standardised comparisons of content. The resultant matrix shows the pairwise comparison of each database and selected subsets. Overall, this showed an unexpected degree of non-overlap, thereby emphasising the complementarity gained from combining public and commercial sources. This conclusion is supported by a Venn-type analysis of GVKBIO, WOMBAT (both commercial) and PubChem (public). These databases show not only overlap but also unique bioactive content in each case because of their different strategies for source selection and data collection.

... A Case Study Sándor Szalma Collaboration in Cancer Research Community: Cancer Biomedical Informatics Grid (caBIG) George A. Komatsoulis ... 24. Open Source Drug Discovery Model Anshu Bhardwaj, Vinod Scaria, Zakir Thomas, Santhosh Adayikkoth, Open Source Drug ...

With the continual pressure to ensure follow-up molecules to billion dollar blockbuster drugs, there is a hurdle in profitability and growth for pharmaceutical companies in the next decades. With each success and failure we increasingly appreciate that a key to the success of synthesized molecules through the research and development process is the possession of drug-like properties. These properties include an adequate bioactivity as well as adequate solubility, an ability to cross critical membranes (intestinal and sometimes blood-brain barrier), reasonable metabolic stability and of course safety in humans. Dependent on the therapeutic area being investigated it might also be desirable to avoid certain enzymes or transporters to circumvent potential drug-drug interactions. It may also be important to limit the induction of these same proteins that can result in further toxicities. We have clearly moved the assessment of in vitro absorption, distribution, metabolism, excretion and toxicity (ADME/TOX) parameters much earlier in the discovery organization than a decade ago with the inclusion of higher throughput systems. We are also now faced with huge amounts of ADME/TOX data for each molecule that need interpretation and also provide a valuable resource for generating predictive computational models for future drug discovery. The present review aims to show what tools exist today for visualizing and modeling ADME/TOX data, what tools need to be developed, and how both the present and future tools are valuable for virtual filtering using ADME/TOX and bioactivity properties in parallel as a viable addition to present practices.

Over the past decade we have seen a growth in the provision of chemistry data and cheminformatics tools as either free websites or software as a service (SaaS) commercial offerings. These have transformed how we find molecule-related data and use such tools in our research. There have also been efforts to improve collaboration between researchers either openly or through secure transactions using commercial tools. A major challenge in the future will be how such databases and software approaches handle larger data as it accumulates from high throughput screening and enable the user to draw insights, enable predictions and move projects forward. We now discuss how information from some datasets can be made more accessible and how privacy of data should not overwhelm the desire to share it at an appropriate time.