EasyDock: customizable and scalable docking tool.

Docking of large compound collections becomes an important procedure to discover new chemical entities. Screening of large sets of compounds may also occur in de novo design projects guided by molecular docking. To facilitate these processes, there is a need for automated tools capable of efficiently docking a large number of molecules using multiple computational nodes within a reasonable timeframe. These tools should also allow for easy integration of new docking programs and provide a user-friendly program interface to support the development of further approaches utilizing docking as a foundation. Currently available tools have certain limitations, such as lacking a convenient program interface or lacking support for distributed computations. In response to these limitations, we have developed a module called EasyDock. It can be deployed over a network of computational nodes using the Dask library, without requiring a specific cluster scheduler. Furthermore, we have proposed and implemented a simple model that predicts the runtime of docking experiments and applied it to minimize overall docking time. The current version of EasyDock supports popular docking programs, namely Autodock Vina, gnina, and smina. Additionally, we implemented a supplementary feature to enable docking of boron-containing compounds, which are not inherently supported by Vina and smina, and demonstrated its applicability on a set of 55 PDB protein-ligand complexes.

Evaluation of piperine analogs against prostate cancer targeting AKT1 kinase domain through network pharmacological analysis.

Prostate cancer is the second most fatal malignancy in men after lung cancer, and the fifth leading cause of death. Piperine has been utilized for its therapeutic effects since the time of Ayurveda. According to traditional Chinese medicine, piperine has a wide variety of pharmacological effects, including anti-inflammatory, anti-cancer, and immune-regulating properties. Based on the previous study, Akt1 (protein kinase B) is one of the targets of piperine, it belongs to the group of oncogenes and the mechanism of the Akt1 is an interesting approach for anticancer drug design. From the peer-reviewed literature, five piperine analogs were identified altogether, and a combinatorial collection was formed. However, may not be entirely clear how piperine analogs work to prevent prostate cancer. In the present study, serine-threonine kinase domain Akt1 receptor was employed to analyze the efficacy of piperine analogs against standards using in silico methodologies. Additionally, their drug-likeness was evaluated utilizing online servers like Molinspiration and preADMET. Using AutoDock Vina, the interactions of five piperine analogs and two standards with Akt1 receptor was investigated. Our study reveals that piperine analog-2 (pip2) shows highest binding affinity (- 6.0 kcal/mol) by forming 6 hydrogen bonds with more hydrophobic interactions compared to other four analogs and standards. In conclusion, the piperine analog pip2, which shows strong inhibition affect in Akt1-cancer pathway, may be employed as chemotherapeutic drugs.

Investigating the Anticancer Activity of G-Rh1 Using In Silico and In Vitro Studies (A549 Lung Cancer Cells).

Ginsenoside Rh1 (G-Rh1), a possible bioactive substance isolated from the Korean Panax ginseng Meyer, has a wide range of pharmacological effects. In this study, we have investigated the anticancer efficacy of G-Rh1 via in silico and in vitro methodologies. This study mainly focuses on the two metastatic regulators, Rho-associated protein kinase 1 (ROCK1) and RhoA, along with other standard apoptosis regulators. The ROCK1 protein is a member of the active serine/threonine kinase family that is crucial for many biological processes, including cell division, differentiation, and death, as well as many cellular processes and muscle contraction. The abnormal activation of ROCK1 kinase causes several disorders, whereas numerous studies have also shown that RhoA is expressed highly in various cancers, including colon, lung, ovarian, gastric, and liver malignancies. Hence, inhibiting both ROCK1 and RhoA will be promising in preventing metastasis. Therefore, the molecular level interaction of G-Rh1 with the ROCK1 and RhoA active site residues from the preliminary screening clearly shows its inhibitory potential. Molecular dynamics simulation and principal component analysis give essential insights for comprehending the conformational changes that result from G-Rh1 binding to ROCK1 and RhoA. Further, MTT assay was employed to examine the potential cytotoxicity in vitro against human lung cancer cells (A549) and Raw 264.7 Murine macrophage cells. Thus, G-Rh1 showed significant cytotoxicity against human lung adenocarcinoma (A549) at 100 µg/mL. In addition, we observed an elevated level of reactive oxygen species (ROS) generation, perhaps promoting cancer cell toxicity. Additionally, G-Rh1 suppressed the mRNA expression of RhoA, ROCK1, MMP1, and MMP9 in cancer cell. Accordingly, G-Rh1 upregulated the p53, Bax, Caspase 3, caspase 9 while Bcl2 is downregulated intrinsic pathway. The findings from our study propose that the anticancer activity of G-Rh1 may be related to the induction of apoptosis by the RhoA/ROCK1 signaling pathway. As a result, this study evaluated the functional drug-like compound G-Rh1 from Panax ginseng in preventing and treating lung cancer adenocarcinoma via regulating metastasis and apoptosis.

Molecular Human Targets of Bioactive Alkaloid-Type Compounds from Tabernaemontana cymose Jacq.

Alkaloids are a group of secondary metabolites that have been widely studied for the discovery of new drugs due to their properties on the central nervous system and their anti-inflammatory, antioxidant and anti-cancer activities. Molecular docking was performed for 10 indole alkaloids identified in the ethanol extract of Tabernaemontana cymosa Jacq. with 951 human targets involved in different diseases. The results were analyzed through the KEGG and STRING databases, finding the most relevant physiological associations for alkaloids. The molecule 5-oxocoronaridine proved to be the most active molecule against human proteins (binding energy affinity average = -9.2 kcal/mol) and the analysis of the interactions between the affected proteins pointed to the PI3K/ Akt/mTOR signaling pathway as the main target. The above indicates that indole alkaloids from T. cymosa constitute a promising source for the search and development of new treatments against different types of cancer.

Structure-based virtual screening of bioactive compounds from Indonesian medical plants against severe acute respiratory syndrome coronavirus-2.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a virus that causes the infectious disease coronavirus disease-2019. Currently, there is no effective drug for the prevention and treatment of this virus. This study aimed to identify secondary metabolites that potentially inhibit the key proteins of SARS-CoV-2. This was an in silico molecular docking study of several secondary metabolites of Indonesian herbal plant compounds and other metabolites with antiviral testing history. Virtual screening using AutoDock Vina of 216 Lipinski rule-compliant plant metabolites was performed on 3C-like protease (3CLpro), RNA-dependent RNA polymerase (RdRp), and spike glycoprotein. Ligand preparation was performed using JChem and Schrödinger's software, and virtual protein elucidation was performed using AutoDockTools version 1.5.6. Virtual screening identified several RdRp, spike, and 3CLpro inhibitors. Justicidin D had binding affinities of -8.7, -8.1, and -7.6 kcal mol-1 on RdRp, 3CLpro, and spike, respectively. 10-methoxycamptothecin had binding affinities of -8.5 and -8.2 kcal mol-1 on RdRp and spike, respectively. Inoxanthone had binding affinities of -8.3 and -8.1 kcal mol-1 on RdRp and spike, respectively, while binding affinities of caribine were -9.0 and -7.5 mol-1 on 3CLpro and spike, respectively. Secondary metabolites of compounds from several plants were identified as potential agents for SARS-CoV-2 therapy.

Anti-inflammatory drugs as new inhibitors to xanthine oxidase: In vitro and in silico approach.

The two important targets to treat gout disease are (1) control the hyperuricemia by the inhibition of Xanthine Oxidase (XO) and (2) treatment of acute attacks of gout by the use of anti-inflammatory drugs. It is important to distinguish between therapy to manage hyperuricemia and to reduce acute inflammation. While reducing hyperuricemia is resolved very slowly with available drugs, gout symptoms like pain and inflammation may become persistent. The objective of this study is to find a relevant treatment with a beneficial double effect. (1) As an anti-inflammatory, analgesic, and antipyretic effect and (2) as XO inhibitory effect, which is the main objective of this study. We investigated the effect of five non-steroidal anti-inflammatory drugs (NSAIDs) against human and bovine milk xanthine oxidases (HXO and BXO) using the double enzyme detection method (DED) and molecular docking with the Autodock vina program. in vitro results show that the NSAIDs give an important inhibition to HXO and BXO with an IC50 of 2.04 ± 0.13 µg/ml, 2.75 ± 0.23 µg/ml, 1.45 ± 0.19 µg/ml, 0.31 ± 0.13 µg/ml and 1.27 ± 0.11 µg/ml, for HXO, and 2.96 ± 0.27 µg/ml, 9.46 ± 0.13 µg/ml, 6.21 ± 1.17 µg/ml, 0.83 ± 0.11 µg/ml, and 3.48 ± 0.13 µg/ml, for BXO, for respectively, Naproxen, Ibuprofen, Diclofenac, Indomethacin, and Celecoxib. Testing the inhibitory activity of these drugs on both XOs shows an important inhibition, especially from Indomethacin, which could be a promising lead compound for reducing acute inflammation and at the same time controlling hyperuricemia.

A Comparison between Enrichment Optimization Algorithm (EOA)-Based and Docking-Based Virtual Screening.

Virtual screening (VS) is a well-established method in the initial stages of many drug and material design projects. VS is typically performed using structure-based approaches such as molecular docking, or various ligand-based approaches. Most docking tools were designed to be as global as possible, and consequently only require knowledge on the 3D structure of the biotarget. In contrast, many ligand-based approaches (e.g., 3D-QSAR and pharmacophore) require prior development of project-specific predictive models. Depending on the type of model (e.g., classification or regression), predictive ability is typically evaluated using metrics of performance on either the training set (e.g.,QCV2) or the test set (e.g., specificity, selectivity or QF1/F2/F32). However, none of these metrics were developed with VS in mind, and consequently, their ability to reliably assess the performances of a model in the context of VS is at best limited. With this in mind we have recently reported the development of the enrichment optimization algorithm (EOA). EOA derives QSAR models in the form of multiple linear regression (MLR) equations for VS by optimizing an enrichment-based metric in the space of the descriptors. Here we present an improved version of the algorithm which better handles active compounds and which also takes into account information on inactive (either known inactive or decoy) compounds. We compared the improved EOA in small-scale VS experiments with three common docking tools, namely, Glide-SP, GOLD and AutoDock Vina, employing five molecular targets (acetylcholinesterase, human immunodeficiency virus type 1 protease, MAP kinase p38 alpha, urokinase-type plasminogen activator, and trypsin I). We found that EOA consistently outperformed all docking tools in terms of the area under the ROC curve (AUC) and EF1% metrics that measured the overall and initial success of the VS process, respectively. This was the case when the docking metrics were calculated based on a consensus approach and when they were calculated based on two different sets of single crystal structures. Finally, we propose that EOA could be combined with molecular docking to derive target-specific scoring functions.

InstaDock: A single-click graphical user interface for molecular docking-based virtual high-throughput screening.

Exploring protein-ligand interactions is a subject of immense interest, as it provides deeper insights into molecular recognition, mechanism of interaction and subsequent functions. Predicting an accurate model for a protein-ligand interaction is a challenging task. Molecular docking is a computational method used for predicting the preferred orientation, binding conformations and the binding affinity of a ligand to a macromolecular target, especially protein. It has been applied in 'virtual high-throughput screening' of chemical libraries containing millions of compounds to find potential leads in drug design and discovery. Here, we have developed InstaDock, a free and open access Graphical User Interface (GUI) program that performs molecular docking and high-throughput virtual screening efficiently. InstaDock is a single-click GUI that uses QuickVina-W, a modified version of AutoDock Vina for docking calculations, made especially for the convenience of non-bioinformaticians and for people who are not experts in using computers. InstaDock facilitates onboard analysis of docking and visual results in just a single click. To sum up, InstaDock is the easiest and more interactive interface than ever existing GUIs for molecular docking and high-throughput virtual screening. InstaDock is freely available for academic and industrial research purposes via https://hassanlab.org/instadock.

Computational screening of antagonists against the SARS-CoV-2 (COVID-19) coronavirus by molecular docking.

In the current spread of novel coronavirus (SARS-CoV-2), antiviral drug discovery is of great importance. AutoDock Vina was used to screen potential drugs by molecular docking with the structural protein and non-structural protein sites of new coronavirus. Ribavirin, a common antiviral drug, remdesivir, chloroquine and luteolin were studied. Honeysuckle is generally believed to have antiviral effects in traditional Chinese medicine. In this study, luteolin (the main flavonoid in honeysuckle) was found to bind with a high affinity to the same sites of the main protease of SARS-CoV-2 as the control molecule. Chloroquine has been proved clinically effective and can bind to the main protease; this may be the antiviral mechanism of this drug. The study was restricted to molecular docking without validation by molecular dynamics simulations. Interactions with the main protease may play a key role in fighting against viruses. Luteolin is a potential antiviral molecule worthy of attention.

In Silico, Ex Vivo and In Vivo Studies of Roflumilast as a Potential Antidiarrheal and Antispasmodic agent: Inhibition of the PDE-4 Enzyme and Voltage-gated Ca++ ion Channels.

The aim of the present study was to evaluate the possible gut inhibitory role of the phosphodiesterase (PDE) inhibitor roflumilast. Increasing doses of roflumilast were tested against castor oil-induced diarrhea in mice, whereas the pharmacodynamics of the same effect was determined in isolated rabbit jejunum tissues. For in silico analysis, the identified PDE protein was docked with roflumilast and papaverine using the Autodock vina program from the PyRx virtual screening tool. Roflumilast protected against diarrhea significantly at 0.5 and 1.5 mg/kg doses, with 40% and 80% protection. Ex vivo findings from jejunum tissues show that roflumilast possesses an antispasmodic effect by inhibiting spontaneous contractions in a concentration-dependent manner. Roflumilast reversed carbachol (CCh, 1 µM)-mediated and potassium (K+, 80 mM)-mediated contractile responses with comparable efficacies but different potencies. The observed potency against K+ was significantly higher in comparison to CCh, similar to verapamil. Experiments were extended to further confirm the inhibitory effect on Ca++ channels. Interestingly, roflumilast deflected Ca++ concentration-response curves (CRCs) to the right with suppression of the maximum peak at both tested doses (0.001-0.003 mg/mL), similar to verapamil. The PDE-inhibitory effect was authenticated when pre-incubation of jejunum tissues with roflumilast (0.03-0.1 mg/mL) produced a leftward deflection of isoprenaline-mediated inhibitory CRCs and increased the tissue level of cAMP, similar to papaverine. This idea was further strengthened by molecular docking studies, where roflumilast exhibited a better binding affinity (-9.4 kcal/mol) with the PDE protein than the standard papaverine (-8.3 kcal/mol). In conclusion, inhibition of Ca++ channels and the PDE-4 enzyme explains the pharmacodynamics of the gut inhibitory effect of roflumilast.

In vivo antiulcer activity, phytochemical exploration, and molecular modelling of the polyphenolic-rich fraction of Crepis sancta extract.

Bioactivity-guided investigation of the methanol extract of Crepis sancta aerial parts, collected off Al-Tafilah, South Jordan, was applied, and in this study, the extract was explored for its phytochemical components and in vivo antiulcer activity. In addition, a docking study involving the purified compounds with the newly crystalized gastric proton pump (PDB # 5YLU) was performed. In-depth phytochemical investigation using the state-of-the-art chromatographic and analytical techniques was implemented resulting in the identification of two eudesmane-type sesquiterpenoids, 3-oxo-γ-costic acid (1) and its methyl ester (2) together with seven different methoxylated flavonols (3-9) as the extract's major components. The in vivo antiulcer study at three different doses (50, 100, and 200 mg/kg) against ethanol-induced gastric ulcer in male albino rats, compared to omeprazole (20 mg/kg) as a standard proton pump inhibitor antiulcer drug, revealed that the tested extract, at the middle and the highest doses, featured comparable or even superior activities relative to omeprazole as deduced from histopathological examination, in particular with regard to reducing inflammatory cell infiltration and ceasing mucosal haemorrhage. The tested extract revealed also a dose-dependent reduction in the volume and titrable acidity of the gastric juice together with a dose-dependent increase in the protective gastric mucin content which may explain the noticeable gastroprotective effect. Molecular modelling study of the isolated compounds showed a binding mode similar to the co-crystallized substrate vonoprazan in 5YLU which strengthens the importance of the tested extract as a potential natural remedy for treating gastric ulcer.

Predictive Binding Affinity of Plant-Derived Natural Products Towards the Protein Kinase G Enzyme of Mycobacterium tuberculosis (MtPknG).

Tuberculosis (TB), caused by Mycobacterium tuberculosis, is a growing public health concern worldwide, especially with the emerging challenge of drug resistance to the current drugs. Efforts to discover and develop novel, more effective, and safer anti-TB drugs are urgently needed. Products from natural sources, such as medicinal plants, have played an important role in traditional medicine and continue to provide some inspiring templates for the design of new drugs. Protein kinase G, produced by M. tuberculosis (MtPKnG), is a serine/threonine kinase, that has been reported to prevent phagosome-lysosome fusion and help prolong M. tuberculosis survival within the host's macrophages. Here, we used an in silico, target-based approach (docking) to predict the interactions between MtPknG and 84 chemical constituents from two medicinal plants (Pelargonium reniforme and Pelargonium sidoides) that have a well-documented historical use as natural remedies for TB. Docking scores for ligands towards the target protein were calculated using AutoDock Vina as the predicted binding free energies. Ten flavonoids present in the aerial parts of P. reniforme and/or P. sidoides showed docking scores ranging from -11.1 to -13.2 kcal/mol. Upon calculation of all ligand efficiency indices, we observed that the (-G/MW) ligand efficiency index for flavonoids (4), (5) and (7) was similar to the one obtained for the AX20017 control. When taking all compounds into account, we observed that the best (-G/MW) efficiency index was obtained for coumaric acid, coumaraldehyde, p-hydroxyphenyl acetic acid and p-hydroxybenzyl alcohol. We found that methyl gallate and myricetin had ligand efficiency indices superior and equal to the AX20017 control efficiency, respectively. It remains to be seen if any of the compounds screened in this study exert an effect in M. tuberculosis-infected macrophages.

In silico and in vitro studies of lupeol and iso-orientin as potential antidiabetic agents in a rat model.

Background: In silico characterization can help to explain the interaction between molecules and predict three-dimensional structures. Various studies have confirmed the glucose-lowering effects of plant extracts, ie, lupeol and iso-orientin, which enable them to be used as antidiabetic agents. Purpose: Aims of the present study were to evaluate the hypoglycemic activities of lupeol and iso-orientin in a rat model. The study proposed the effects of alloxan on blood glucose level, body weight, and oxidative stress. Materials and Methods: Thirty (n=30) Wistar albino rats were divided into six groups and were subjected to different combinations of the compounds. Levels of different stress markers, ie, malondialdehyde, superoxide dismutase, catalase, nitric oxide, glutathione, glutathione peroxide, glutathione reductase, and blood glucose levels were estimated with their respective methods. Whereas, for their in silico analysis, identified target proteins, GPR40, glucose-6-phosphatase, UCP2, glycogen phosphorylase, aldose reductase, and glucose transporter-4 were docked with lupeol and iso-orientin. Three-dimensional structures were predicted by ERRAT, Rampage, Verify3D, threading and homology approaches. Results: Blood glucose levels were significantly increased in rats receiving intraperitoneal injection of alloxan (208±6.94 mg/dL) as compared to controls (90±7.38 mg/dL). Infected rats were administered plant extracts; combined treatment of both extracts (lupeol+iso-orientin) significantly reduced the levels of blood glucose (129.06±6.29 mg/dL) and improved the antioxidant status. Fifteen structures of each selected protein were evaluated using various techniques. Consequently, satisfactory quality factors [GPR40 (96.41%), glucose-6-phosphatase (96.56%), UCP2 (72.56%), glycogen phosphorylase (87.24%), aldose reductase (82.46%), and glucose transporter-4 (94.29%)] were selected. Molecular docking revealed interacting residues, effective drug properties and their binding affinities (ie, -8.9 to -12.6 Kcal/mol). Conclusion: Results of the study affirmed the antidiabetic activities of lupeol and iso-orientin. Administration of these extracts (either individually or in combination) significantly reduced blood glucose levels and oxidative stress. Hence, it may be considered beneficial in the treatment of diabetes.

Potential Angiotensin Converting Enzyme Inhibitors from Moringa oleifera.

BACKGROUND: Hypertension is the chronic medical condition and it affected billions of people worldwide. Natural medicines are the main alternatives to treatment for a majority of people suffering from hypertension. Niazicin-A, Niazimin-A, and Niaziminin-B compounds from Moringa oleifera ethanolic leave extract were reported to have potent antihypertensive activity. OBJECTIVE: These compounds were targeted with Angiotensin-converting enzyme [ACE] which is one of the main regulatory enzymes of the renin-angiotensin system. METHODS: Protein-ligand docking of these compounds with [ACE] [both domain N and C] was conceded out through Autodock vina and visualization was done by chimera. Pharmacokinetics study of these compounds was predicted by ADME-Toxicity Prediction. RESULTS: Niazicin-A, Niazimin-A, and Niaziminin-B showed high binding affinity with ACE and partially blocked the active sites of the enzyme. Niazicin-A, Niazimin-A and Niaziminin-B showed the estimated free binding energy of -7.6kcal/mol kcal/mol, -8.8kcal/mol and -8.0kcal/mol respectively with C-domain of ACE and -7.9kcal/mol, -8.5kcal/mol and -7.7kcal/mol respectively with N-domain of ACE. The compounds showed better binding energy with angiotensinconverting enzyme in comparison to Captopril -5.5kcal/mol and -5.6kcal/mol and Enalapril [standard] -8.4kcal/mol and -7.5kcal/mol with C and N domain, respectively. CONCLUSION: Computationally, the selected bioactive molecules have shown better binding energy to known standard drugs which have been already known for inhibition of ACE and can further act as a pharmacophore for in vitro and in vivo studies in the development of alternative medicine.

Practices in Molecular Docking and Structure-Based Virtual Screening.

Drug discovery has evolved significantly over the past two decades. Progress in key areas such as molecular and structural biology has contributed to the elucidation of the three-dimensional structure and function of a wide range of biological molecules of therapeutic interest. In this context, the integration of experimental techniques, such as X-ray crystallography, and computational methods, such as molecular docking, has promoted the emergence of several areas in drug discovery, such as structure-based drug design (SBDD). SBDD strategies have been broadly used to identify, predict and optimize the activity of small molecules toward a molecular target and have contributed to major scientific breakthroughs in pharmaceutical R&D. This chapter outlines molecular docking and structure-based virtual screening (SBVS) protocols used to predict the interaction of small molecules with the phosphatidylinositol-bisphosphate-kinase PI3Kδ, which is a molecular target for hematological diseases. A detailed description of the molecular docking and SBVS procedures and an evaluation of the results are provided.

PLHINT: A knowledge-driven computational approach based on the intermolecular H bond interactions at the protein-ligand interface from docking solutions.

The tendency of docking scoring functions to generate crystal close conformations of ligands bound to protein structures face limitations in not reproducing the exact crystal intermolecular contacts in dock poses. Intermolecular H bond contacts enumerated at the protein-docked ligand interface can be used to train scoring models and improve virtual screening performance. There is a need to incorporate additional knowledge of protein-ligand H bond contacts in extension to crystal contacts from docking solutions within the reproducibility efficiency of the docking program. A computational approach PLHINT (Protein-ligand H bond interaction pattern) is presented here which extracts intermolecular H bond interactions from native-like docked ligand poses, transform into the scoring scheme and apply over the virtual screening results of database molecules. The basic premise of the PLHINT approach is to score the most observed H bond patterns with the high score to achieve high recovery rates. Tested on ten diverse DUD-E benchmark datasets, the approach has demonstrated better overall performance and ligand enrichment competency over virtual screening results generated by three genetic algorithm-based docking programs viz. AutoDock Vina, FlexAID and PLANTS. Furthermore, the approach has successfully recovered the poor and random virtual screening results with better enrichments.

Structure-Based Virtual Screening.

Structure-based virtual screening (SBVS) is a computational approach used in the early-stage drug discovery campaign to search a chemical compound library for novel bioactive molecules against a certain drug target. It utilizes the three-dimensional (3D) structure of the biological target, obtained from X-ray, NMR, or computational modeling, to dock a collection of chemical compounds into the binding site and select a subset of these compounds based on the predicted binding scores for further biological evaluation. In the present work, we illustrate the basic process of conducting a SBVS with examples using freely accessible tools and resources.

Evaluation of a novel virtual screening strategy using receptor decoy binding sites.

Virtual screening is used in biomedical research to predict the binding affinity of a large set of small organic molecules to protein receptor targets. This report shows the development and evaluation of a novel yet straightforward attempt to improve this ranking in receptor-based molecular docking using a receptor-decoy strategy. This strategy includes defining a decoy binding site on the receptor and adjusting the ranking of the true binding-site virtual screen based on the decoy-site screen. The results show that by docking against a receptor-decoy site with Autodock Vina, improved Receiver Operator Characteristic Enrichment (ROCE) was achieved for 5 out of fifteen receptor targets investigated, when up to 15 % of a decoy site rank list was considered. No improved enrichment was seen for 7 targets, while for 3 targets the ROCE was reduced. The extent to which this strategy can effectively improve ligand prediction is dependent on the target receptor investigated.

In silico approach for the discovery of new PPARγ modulators among plant-derived polyphenols.

Peroxisome proliferator-activated receptor gamma (PPARγ) is a well-characterized member of the PPAR family that is predominantly expressed in adipose tissue and plays a significant role in lipid metabolism, adipogenesis, glucose homeostasis, and insulin sensitization. Full agonists of synthetic thiazolidinediones (TZDs) have been therapeutically used in clinical practice to treat type 2 diabetes for many years. Although it can effectively lower blood glucose levels and improve insulin sensitivity, the administration of TZDs has been associated with severe side effects. Based on recent evidence obtained with plant-derived polyphenols, the present in silico study aimed at finding new selective human PPARγ (hPPARγ) modulators that are able to improve glucose homeostasis with reduced side effects compared with TZDs. Docking experiments have been used to select compounds with strong binding affinity (ΔG values ranging from -10.0±0.9 to -11.4±0.9 kcal/mol) by docking against the binding site of several X-ray structures of hPPARγ. These putative modulators present several molecular interactions with the binding site of the protein. Additionally, most of the selected compounds have favorable druggability and good ADMET properties. These results aim to pave the way for further bench-scale analysis for the discovery of new modulators of hPPARγ that do not induce any side effects.