All Stories

  1. Reliable Prediction of Caco-2 Permeability by Supervised Recursive Machine Learning Approaches
  2. Integration of In Silico, In Vitro and In Situ Tools for the Preformulation and Characterization of a Novel Cardio-Neuroprotective Compound during the Early Stages of Drug Development
  3. ADME prediction with KNIME: A retrospective contribution to the second “Solubility Challenge”
  4. A Novel Automated Framework for QSAR Modeling of Highly Imbalanced Leishmania High-Throughput Screening Data
  5. ICH Guideline for Biopharmaceutics Classification System-Based Biowaiver (M9): Toward Harmonization in Latin American Countries
  6. Policy of Multisource Drug Products in Latin America: Opportunities and Challenges on the Application of Bioequivalence In Vitro Assays
  7. ADME Prediction with KNIME: Development and Validation of a Publicly Available Workflow for the Prediction of Human Oral Bioavailability
  8. Equilibrium solubility using shake-flask method of JM-20: a synthetic molecule with neuroprotective action
  9. In Silico Assessment of ADME Properties: Advances in Caco-2 Cell Monolayer Permeability Modeling
  10. Integrating theoretical and experimental permeability estimations for provisional biopharmaceutical classification: Application to the WHO essential medicines
  11. Computational modeling of human oral bioavailability: what will be next?
  12. Biowaiver or Bioequivalence: Ambiguity in Sildenafil Citrate BCS Classification
  13. Importance and applications of cell- and tissue-based in vitro models for drug permeability screening in early stages of drug development
  14. Exploring different strategies for imbalanced ADME data problem: case study on Caco-2 permeability modeling
  15. The efficacy of 2-nitrovinylfuran derivatives againstLeishmania in vitro and in vivo
  16. Bacterial FabH: Towards the Discovery of New Broad-Spectrum Antibiotics
  17. Toward the computer-aided discovery of FabH inhibitors. Do predictive QSAR models ensure high quality virtual screening performance?
  18. Provisional Classification andin SilicoStudy of Biopharmaceutical System Based on Caco-2 Cell Permeability and Dose Number
  19. The Use of Rule-Based and QSPR Approaches in ADME Profiling: A Case Study on Caco-2 Permeability
  20. Thermodynamic computational approach to capture molecular recognition in the binding of different inhibitors to the DNA gyrase B subunit from Escherichia coli
  21. FDA-approved Drugs Selected Using Virtual Screening Bind Specifically to G-quadruplex DNA
  22. GA(M)E-QSAR: A Novel, Fully Automatic Genetic-Algorithm-(Meta)-Ensembles Approach for Binary Classification in Ligand-Based Drug Design
  23. Computational and Pharmacoinformatic Approaches to Oral Bioavailability Prediction
  24. Combining molecular docking and QSAR studies for modelling the antigyrase activity of cyclothialidine derivatives
  25. Molecular dynamics and docking simulations as a proof of high flexibility in E. coli FabH and its relevance for accurate inhibitor modeling
  26. In Silico Prediction of Caco-2 Cell Permeability by a Classification QSAR Approach
  27. Exploring the conformational changes of the ATP binding site of gyrase B from Escherichia coli complexed with different established inhibitors by using molecular dynamics simulation
  28. Prediction of telomerase inhibitory activity for acridinic derivatives based on chemical structure
  29. Telomerase Inhibitory Activity of Acridinic Derivatives: A 3D-QSAR Approach
  30. Multi-target QSPR assemble of a Complex Network for the distribution of chemicals to biphasic systems and biological tissues
  31. Quantitative structure carcinogenicity relationship for detecting structural alerts in nitroso-compounds☆Species: Rat; Sex: Male; Route of administration: Water
  32. QSAR modeling of the rodent carcinogenicity of nitrocompounds
  33. Quantitative Structure−Carcinogenicity Relationship for Detecting Structural Alerts in Nitroso Compounds: Species, Rat; Sex, Female; Route of Administration, Gavage
  34. Quantitative structure carcinogenicity relationship for detecting structural alerts in nitroso-compounds
  35. Application of the replacement method as a novel variable selection strategy in QSAR. 1. Carcinogenic potential
  36. A topological substructural approach for the prediction of P-glycoprotein substrates
  37. Quantitative structure activity relationship for the computational prediction of nitrocompounds carcinogenicity
  38. A radial-distribution-function approach for predicting rodent carcinogenicity
  39. The Prediction of Carcinogenicity from Molecular Structure
  40. A topological substructural approach applied to the computational prediction of rodent carcinogenicity
  41. Quantitative structure–activity relationship to predict toxicological properties of benzene derivative compounds
  42. Unified Markov thermodynamics based on stochastic forms to classify drugs considering molecular structure, partition system, and biological species:
  43. Computational method to predict human intestinal absorption
  44. In silico prediction of central nervous system activity of compounds. Identification of potential pharmacophores by the TOPS–MODE approach
  45. TOPS‐MODE Approach for the Prediction of Blood–Brain Barrier Permeation
  46. A novel approach to predict a toxicological property of aromatic compounds in the Tetrahymena pyriformis
  47. 3D-MEDNEs:  An Alternative “In Silico” Technique for Chemical Research in Toxicology. 1. Prediction of Chemically Induced Agranulocytosis
  48. Markovian chemicals "in silico" design (MARCH-INSIDE), a promising approach for computer-aided molecular design I: discovery of anticancer compounds
  49. A topological-substructural molecular design (TOPS-MODE) approach to determining pharmacokinetics and pharmacological properties of 6-fluoroquinolone derivatives
  50. Total and Local Quadratic Indices of the “Molecular Pseudograph’s Atom Adjacency Matrix”. Application to Prediction of Caco-2 Permeability of Drugs
  51. TOPS-MODE Based QSARs Derived from Heterogeneous Series of Compounds. Applications to the Design of New Herbicides