Web-based 3D-visualization of the DrugBank chemical space

BACKGROUND Similarly to the periodic table for elements, chemical space offers an organizing principle for representing the diversity of organic molecules, usually in the form of multi-dimensional property spaces that are subjected to dimensionality reduction methods to obtain 3D-spaces or 2D-maps suitable for visual inspection. Unfortunately, tools to look at chemical space on the internet are currently very limited. RESULTS Herein we present webDrugCS, a web application freely available at www.gdb.unibe.ch to visualize DrugBank (www.drugbank.ca, containing over 6000 investigational and approved drugs) in five different property spaces. WebDrugCS displays 3D-clouds of color-coded grid points representing molecules, whose structural formula is displayed on mouse over with an option to link to the corresponding molecule page at the DrugBank website. The 3D-clouds are obtained by principal component analysis of high dimensional property spaces describing constitution and topology (42D molecular quantum numbers MQN), structural features (34D SMILES fingerprint SMIfp), molecular shape (20D atom pair fingerprint APfp), pharmacophores (55D atom category extended atom pair fingerprint Xfp) and substructures (1024D binary substructure fingerprint Sfp). User defined molecules can be uploaded as SMILES lists and displayed together with DrugBank. In contrast to 2D-maps where many compounds fold onto each other, these 3D-spaces have a comparable resolution to their parent high-dimensional chemical space. CONCLUSION To the best of our knowledge webDrugCS is the first publicly available web tool for interactive visualization and exploration of the DrugBank chemical space in 3D. WebDrugCS works on computers, tablets and phones, and facilitates the visual exploration of DrugBank to rapidly learn about the structural diversity of small molecule drugs.Graphical abstractwebDrugCS visualization of DrugBank projected in 3D MQN space color-coded by ring count, with pointer showing the drug 5-fluorouracil

The Polypharmacology Browser PPB2: Target Prediction Combining Nearest Neighbors with Machine Learning

Here we report PPB2 as a target prediction tool assigning targets to a query molecule based on ChEMBL data. PPB2 computes ligand similarities using molecular fingerprints encoding composition (MQN), molecular shape and pharmacophores (Xfp), and substructures (ECfp4), and features an unprecedented combination of nearest neighbor (NN) searches and Naïve Bayes (NB) machine learning, together with simple NN searches, NB and Deep Neural Network (DNN) machine learning models as further options. Although NN(ECfp4) gives the best results in terms of recall in a 10-fold cross-validation study, combining NN searches with NB machine learning provides superior precision statistics, as well as better results in a case study predicting off-targets of a recently reported TRPV6 calcium channel inhibitor, illustrating the value of this combined approach. PPB2 is available to assess possible off-targets of small molecule drug-like compounds by public access at ppb2.gdb.tools

Virtual Exploration of the Ring Systems Chemical Universe

Here, we explore the chemical space of all virtually possible organic molecules focusing on ring systems, which represent the cyclic cores of organic molecules obtained by removing all acyclic bonds and converting all remaining atoms to carbon. This approach circumvents the combinatorial explosion encountered when enumerating the molecules themselves. We report the chemical universe database GDB4c containing 916 130 ring systems up to four saturated or aromatic rings and maximum ring size of 14 atoms and GDB4c3D containing the corresponding 6 555 929 stereoisomers. Almost all (98.6%) of these ring systems are unknown and represent chiral 3D-shaped macrocycles containing small rings and quaternary centers reminiscent of polycyclic natural products. We envision that GDB4c can serve to select new ring systems from which to design analogs of such natural products. The database is available for download at www.gdb.unibe.ch together with interactive visualization and search tools as a resource for molecular design

Colonnes en béton armé renforcées de PRFV sous un chargement sismique simulé

Abstract : Steel and fiber-reinforced-polymer (FRP) materials have different mechanical and physical characteristics. High corrosion resistance, high strength to weight ratio, non-conductivity, favorable fatigue enable the FRP to be considered as alternative reinforcement for structures in harsh environment. Meanwhile, FRP bars have low modulus of elasticity and linear-elastic stress-strain curve. These features raise concerns about the applicability of using such materials as reinforcement for structures prone to earthquakes. The main demand for the structural members in structures subjected to seismic loads is dissipating energy without strength loss which is known as ductility. In the rigid frames, columns are expected to be the primary elements of energy dissipation in structures subjected to seismic loads. The present study addresses the feasibility of reinforced-concrete columns totally reinforced with glass-fiber-reinforced-polymer (GFRP) bars achieving reasonable strength and the drift requirements specified in various codes. Eleven full-scale reinforced concrete columns—two reinforced with steel bars (as reference specimens) and nine totally reinforced with GFRP bars—were constructed and tested to failure. The columns were tested under quasi-static reversed cyclic lateral loading and simultaneously subjected to compression axial load. The columns are 400 mm square cross-section with a shear span 1650 mm. The specimen simulates a column with 3.7 m in height in a typical building with the point of contra-flexure located at the column mid-height. The tested parameters were the longitudinal reinforcement ratio (0.63, 0.95 and 2.14), the spacing of the transverse stirrups (80, 100, 150), tie configuration (C1, C2, C3 and C4), and axial load level (20%, 30% and 40%). The test results clearly show that properly designed and detailed GFRP-reinforced concrete columns could reach high deformation levels with no strength degradation. An acceptable level of energy dissipation compared with steel-reinforced concrete columns is provided by GFRP reinforced concrete columns. The dissipated energy of GFRP reinforced concrete columns was 75% and 70% of the counter steel columns at 2.5% and 4% drift ratio respectively. High drift capacity achieved by the columns up to 10% with no significant loss in strength. The high drift capacity and acceptable dissipated energy enable the GFRP columns to be part of the moment resisting frames in regions prone to seismic activities. The experimental ultimate drift ratios were compared with the estimated drift ratios using the confinement Equation in CSA S806-12. It was found from the comparison that the confinement Equation underestimates values of the drift ratios thus the experimental drift ratios were used to modify transverse FRP reinforcement area in CSA S806-12. The hysteretic behavior encouraged to propose a design procedure for the columns to be part of the moderate ductile and ductile moment resisting frames. The development of design guidelines, however, depends on determining the elastic and inelastic deformations and on assessing the force modification factor and equivalent plastic-hinge length for GFRP-reinforced concrete columns. The experimental results of the GFRP-reinforced columns were used to justify the design guideline, proving the accuracy of the proposed design equations.L’acier et les matériaux à base de polymères renforcés de fibres (PRF) ont des caractéristiques physiques et mécaniques différentes. La résistance à la haute corrosion, le rapport résistance vs poids, la non-conductivité et la bonne résistance à la fatigue font des barres d’armature en PRF, un renforcement alternatif aux barres d’armature en acier, pour des structures dans des environnements agressifs. Cependant, les barres d’armature en PRF ont un bas module d’élasticité et une courbe contrainte-déformation sous forme linéaire. Ces caractéristiques soulèvent des problèmes d'applicabilité quant à l’utilisation de tels matériaux comme renforcement pour des structures situées en forte zone sismique. La principale exigence pour les éléments structuraux des structures soumises à des charges sismiques est la dissipation d'énergie sans perte de résistance connue sous le nom de ductilité. Dans les structures rigides de type cadre, on s'attend à ce que les colonnes soient les premiers éléments à dissiper l'énergie dans les structures soumises à ces charges. La présente étude traite de la faisabilité des colonnes en béton armé entièrement renforcées de barres d’armature en polymères renforcés de fibres de verre (PRFV), obtenant une résistance et un déplacement latéral raisonnable par rapport aux exigences spécifiées dans divers codes. Onze colonnes à grande échelle ont été fabriquées: deux colonnes renforcées de barres d'acier (comme spécimens de référence) et neuf colonnes renforcées entièrement de barres en PRFV. Les colonnes ont été testées jusqu’à la rupture sous une charge quasi-statique latérale cyclique inversée et soumises simultanément à une charge axiale de compression. Les colonnes ont une section carrée de 400 mm avec une portée de cisaillement de 1650 mm pour simuler une colonne de 3,7 m de hauteur dans un bâtiment typique avec le point d’inflexion situé à la mi-hauteur. Les paramètres testés sont : le taux d’armature longitudinal (0,63%, 0,95% et 2,14 %), l'espacement des étriers (80mm, 100mm, 150 mm), les différentes configurations (C1, C2, C3 et C4) et le niveau de charge axiale (20%, 30 % et 40%). Les résultats des essais montrent clairement que les colonnes en béton renforcées de PRFV et bien conçues peuvent atteindre des niveaux de déformation élevés sans réduction de résistance. Un niveau acceptable de dissipation d'énergie, par rapport aux colonnes en béton armé avec de l’armature en acier, est atteint par les colonnes en béton armé de PRFV. L'énergie dissipée des colonnes en béton armé de PRFV était respectivement de 75% et 70% des colonnes en acier à un rapport déplacement latéral de 2,5% et 4%. Un déplacement supérieur a été atteint par les colonnes en PRFV jusqu'à 10% sans perte significative de résistance. La capacité d’un déplacement supérieur et l’énergie dissipée acceptable permettent aux colonnes en PRFV de participer au moment résistant dans des régions sujettes à des activités sismiques. Les rapports des déplacements expérimentaux ultimes ont été comparés avec les rapports estimés en utilisant l’Équation de confinement du code CSA S806-12. À partir de la comparaison, il a été trouvé que l’Équation de confinement sous-estime les valeurs des rapports de déplacement, donc les rapports de déplacement expérimentaux étaient utilisés pour modifier la zone de renforcement transversal du code CSA S806-12. Le comportement hystérétique encourage à proposer une procédure de conception pour que les colonnes fassent partie des cadres rigides à ductilité modérée et résistant au moment. Cependant, l'élaboration de guides de conception dépend de la détermination des déformations élastiques et inélastiques et de l'évaluation du facteur de modification de la force sismique et de la longueur de la rotule plastique pour les colonnes en béton armé renforcées de PRFV. Les résultats expérimentaux des colonnes renforcées de PRFV étudiées ont été utilisés pour justifier la ligne directrice de conception, ce qui prouve l’efficacité des équations de conception proposées

Discovery of novel drug-like antitubercular hits targeting the MEP pathway enzyme DXPS by strategic application of ligand-based virtual screening.

In the present manuscript, we describe how we successfully used ligand-based virtual screening (LBVS) to identify two small-molecule, drug-like hit classes with excellent ADMET profiles against the difficult to address microbial enzyme 1-deoxy-d-xylulose-5-phosphate synthase (DXPS). In the fight against antimicrobial resistance (AMR), it has become increasingly important to address novel targets such as DXPS, the first enzyme of the 2-C-methyl-d-erythritol-4-phosphate (MEP) pathway, which affords the universal isoprenoid precursors. This pathway is absent in humans but essential for pathogens such as Mycobacterium tuberculosis, making it a rich source of drug targets for the development of novel anti-infectives. Standard computer-aided drug-design tools, frequently applied in other areas of drug development, often fail for targets with large, hydrophilic binding sites such as DXPS. Therefore, we introduce the concept of pseudo-inhibitors, combining the benefits of pseudo-ligands (defining a pharmacophore) and pseudo-receptors (defining anchor points in the binding site), for providing the basis to perform a LBVS against M. tuberculosis DXPS. Starting from a diverse set of reference ligands showing weak inhibition of the orthologue from Deinococcus radiodurans DXPS, we identified three structurally unrelated classes with promising in vitro (against M. tuberculosis DXPS) and whole-cell activity including extensively drug-resistant strains of M. tuberculosis. The hits were validated to be specific inhibitors of DXPS and to have a unique mechanism of inhibition. Furthermore, two of the hits have a balanced profile in terms of metabolic and plasma stability and display a low frequency of resistance development, making them ideal starting points for hit-to-lead optimization of antibiotics with an unprecedented mode of action

Discovery of novel drug-like antitubercular hits targeting the MEP pathway enzyme DXPS by strategic application of ligand-based virtual screening

In the present manuscript, we describe how we successfully used ligand-based virtual screening (LBVS) to identify two small-molecule, drug-like hit classes with excellent ADMET profiles against the difficult to address microbial enzyme 1-deoxy-D-xylulose-5-phosphate synthase (DXPS). In the fight against antimicrobial resistance (AMR), it has become increasingly important to address novel targets such as DXPS, the first enzyme of the 2-C-methyl-D-erythritol-4-phosphate (MEP) pathway, which affords the universal isoprenoid precursors. This pathway is absent in humans but essential for pathogens such as Mycobacterium tuberculosis, making it a rich source of drug targets for the development of novel anti-infectives. Standard computer-aided drug-design tools, frequently applied in other areas of drug development, often fail for targets with large, hydrophilic binding sites such as DXPS. Therefore, we introduce the concept of pseudo-inhibitors, combining the benefits of pseudo-ligands (defining a pharmacophore) and pseudo-receptors (defining anchor points in the binding site), for providing the basis to perform a LBVS against M. tuberculosis DXPS. Starting from a diverse set of reference ligands showing weak inhibition of the orthologue from Deinococcus radiodurans DXPS, we identified three structurally unrelated classes with promising in vitro (against M. tuberculosis DXPS) and whole-cell activity including extensively drug-resistant strains of M. tuberculosis. The hits were validated to be specific inhibitors of DXPS and to have a unique mechanism of inhibition. Furthermore, two of the hits have a balanced profile in terms of metabolic and plasma stability and display a low frequency of resistance development, making them ideal starting points for hit-to-lead optimization of antibiotics with an unprecedented mode of action

Exploring Chemical Space for Drug Discovery Using the Chemical Universe Database

[Image: see text] Herein we review our recent efforts in searching for bioactive ligands by enumeration and virtual screening of the unknown chemical space of small molecules. Enumeration from first principles shows that almost all small molecules (>99.9%) have never been synthesized and are still available to be prepared and tested. We discuss open access sources of molecules, the classification and representation of chemical space using molecular quantum numbers (MQN), its exhaustive enumeration in form of the chemical universe generated databases (GDB), and examples of using these databases for prospective drug discovery. MQN-searchable GDB, PubChem, and DrugBank are freely accessible at www.gdb.unibe.ch

The Polypharmacology Browser PPB2: Target Prediction Combining Nearest Neighbors with Machine Learning

Here we report PPB2 as a target prediction tool assigning targets to a query molecule based on ChEMBL data. PPB2 computes ligand similarities using molecular fingerprints encoding composition (MQN), molecular shape and pharmacophores (Xfp), and substructures (ECfp4), and features an unprecedented combination of nearest neighbor (NN) searches and Naïve Bayes (NB) machine learning, together with simple NN searches, NB and Deep Neural Network (DNN) machine learning models as further options. Although NN(ECfp4) gives the best results in terms of recall in a 10-fold cross-validation study, combining NN searches with NB machine learning provides superior precision statistics, as well as better results in a case study predicting off-targets of a recently reported TRPV6 calcium channel inhibitor, illustrating the value of this combined approach. PPB2 is available to assess possible off-targets of small molecule drug-like compounds by public access at ppb2.gdb.tools.</div

The polypharmacology browser: a web-based multi-fingerprint target prediction tool using ChEMBL bioactivity data

BACKGROUND: Several web-based tools have been reported recently which predict the possible targets of a small molecule by similarity to compounds of known bioactivity using molecular fingerprints (fps), however predictions in each case rely on similarities computed from only one or two fps. Considering that structural similarity and therefore the predicted targets strongly depend on the method used for comparison, it would be highly desirable to predict targets using a broader set of fps simultaneously. RESULTS: Herein, we present the polypharmacology browser (PPB), a web-based platform which predicts possible targets for small molecules by searching for nearest neighbors using ten different fps describing composition, substructures, molecular shape and pharmacophores. PPB searches through 4613 groups of at least 10 same target annotated bioactive molecules from ChEMBL and returns a list of predicted targets ranked by consensus voting scheme and p value. A validation study across 670 drugs with up to 20 targets showed that combining the predictions from all 10 fps gives the best results, with on average 50% of the known targets of a drug being correctly predicted with a hit rate of 25%. Furthermore, when profiling a new inhibitor of the calcium channel TRPV6 against 24 targets taken from a safety screen panel, we observed inhibition in 5 out of 5 targets predicted by PPB and in 7 out of 18 targets not predicted by PPB. The rate of correct (5/12) and incorrect (0/12) predictions for this compound by PPB was comparable to that of other web-based prediction tools. CONCLUSION: PPB offers a versatile platform for target prediction based on multi-fingerprint comparisons, and is freely accessible at www.gdb.unibe.ch as a valuable support for drug discovery. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13321-017-0199-x) contains supplementary material, which is available to authorized users