All Stories

  1. Rational Drug Design of Antineoplastic Agents Using 3D-QSAR, Cheminformatic, and Virtual Screening Approaches
  2. Artificial intelligence in pharmaceutical research and development
  3. Applications of crystal structure prediction – inorganic and network structures: general discussion
  4. Applications of crystal structure prediction – organic molecular structures: general discussion
  5. Crystal structure evaluation: calculating relative stabilities and other criteria: general discussion
  6. Can human experts predict solubility better than computers?
  7. Enzyme function and its evolution
  8. Probing the average distribution of water in organic hydrate crystal structures with radial distribution functions (RDFs)
  9. Are the Sublimation Thermodynamics of Organic Molecules Predictable?
  10. Erratum: Predicting Melting Points of Organic Molecules: Applications to Aqueous Solubility Prediction Using the General Solubility Equation
  11. Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies
  12. A Random Forest Model for Predicting Allosteric and Functional Sites on Proteins
  13. Why do Sequence Signatures Predict Enzyme Mechanism? Homology versus Chemistry
  14. Enzyme mechanism prediction: a template matching problem on InterPro signature subspaces
  15. A note on utilising binary features as ligand descriptors
  16. The Parzen Window method: In terms of two vectors and one matrix
  17. Predicting Melting Points of Organic Molecules: Applications to Aqueous Solubility Prediction Using the General Solubility Equation
  18. Verifying the fully “Laplacianised” posterior Naïve Bayesian approach and more
  19. Greedy and Linear Ensembles of Machine Learning Methods Outperform Single Approaches for QSPR Regression Problems
  20. A review of methods for the calculation of solution free energies and the modelling of systems in solution
  21. Predicting targets of compounds against neurological diseases using cheminformatic methodology
  22. One origin for metallo-β-lactamase activity, or two? An investigation assessing a diverse set of reconstructed ancestral sequences based on a sample of phylogenetic trees
  23. Is Experimental Data Quality the Limiting Factor in Predicting the Aqueous Solubility of Druglike Molecules?
  24. Erratum for “In Silico Target Predictions: Defining a Benchmarking Data Set and Comparison of Performance of the Multiclass Naı̈ve Bayes and Parzen-Rosenblatt Window”
  25. The Natural History of Biocatalytic Mechanisms
  26. From sequence to enzyme mechanism using multi-label machine learning
  27. Uniting Cheminformatics and Chemical Theory To Predict the Intrinsic Aqueous Solubility of Crystalline Druglike Molecules
  28. Machine learning methods in chemoinformatics
  29. PFClust: an optimised implementation of a parameter-free clustering algorithm
  30. Full “Laplacianised” posterior naive Bayesian algorithm
  31. 4273π: Bioinformatics education on low cost ARM hardware
  32. In Silico Target Predictions: Defining a Benchmarking Data Set and Comparison of Performance of the Multiclass Naïve Bayes and Parzen-Rosenblatt Window
  33. PFClust: a novel parameter free clustering algorithm
  34. Predicting the protein targets for athletic performance-enhancing substances
  35. First-Principles Calculation of the Intrinsic Aqueous Solubility of Crystalline Druglike Molecules
  36. Enzyme Informatics
  37. Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification
  38. Is EC class predictable from reaction mechanism?
  39. Predicting the mechanism of phospholipidosis
  40. Comments on “Leave-Cluster-Out Cross-Validation Is Appropriate for Scoring Functions Derived from Diverse Protein Data Sets”: Significance for the Validation of Scoring Functions
  41. Classifying Molecules Using a Sparse Probabilistic Kernel Binary Classifier
  42. Characterizing the complexity of enzymes on the basis of their mechanisms and structures with a bio-computational analysis
  43. Development and Comparison of hERG Blocker Classifiers: Assessment on Different Datasets Yields Markedly Different Results
  44. Informatics, machine learning and computational medicinal chemistry
  45. Predicting Phospholipidosis Using Machine Learning
  46. A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking
  47. Quantitative Comparison of Catalytic Mechanisms and Overall Reactions in Convergently Evolved Enzymes: Implications for Classification of Enzyme Function
  48. Understanding the Functional Roles of Amino Acid Residues in Enzyme Catalysis
  49. Theoretical Study of the Reaction Mechanism of Streptomyces coelicolor Type II Dehydroquinase
  50. Computational toxicology: an overview of the sources of data and of modelling methods
  51. Ligand-Target Prediction Using Winnow and Naive Bayesian Algorithms and the Implications of Overall Performance Statistics
  52. Simultaneous feature selection and parameter optimisation using an artificial ant colony: case study of melting point prediction
  53. Toxicological relationships between proteins obtained from protein target predictions of large toxicity databases
  54. Predicting Intrinsic Aqueous Solubility by a Thermodynamic Cycle
  55. A novel hybrid ultrafast shape descriptor method for use in virtual screening
  56. How To Winnow Actives from Inactives:  Introducing Molecular Orthogonal Sparse Bigrams (MOSBs) and Multiclass Winnow
  57. Why Are Some Properties More Difficult To Predict than Others? A Study of QSPR Models of Solubility, Melting Point, and Log P
  58. The Chemistry of Protein Catalysis
  59. The Geometry of Interactions between Catalytic Residues and their Substrates
  60. Using Reaction Mechanism to Measure Enzyme Similarity
  61. Support vector inductive logic programming outperforms the naive Bayes classifier and inductive logic programming for the classification of bioactive chemical compounds
  62. MACiE (Mechanism, Annotation and Classification in Enzymes): novel tools for searching catalytic mechanisms
  63. Random Forest Models To Predict Aqueous Solubility
  64. Melting Point Prediction Employing k -Nearest Neighbor Algorithms and Genetic Parameter Optimization
  65. Chemoinformatics-Based Classification of Prohibited Substances Employed for Doping in Sport
  66. MACiE: a database of enzyme reaction mechanisms
  67. Knowledge Based Potentials: the Reverse Boltzmann Methodology, Virtual Screening and Molecular Weight Dependence
  68. Predicting protein–ligand binding affinities: a low scoring game?
  69. A structure–odour relationship study using EVA descriptors and hierarchical clustering
  70. Can we predict lattice energy from molecular structure?
  71. Protein Ligand Database (PLD): additional understanding of the nature and specificity of protein-ligand complexes
  72. D-amino acid residues in peptides and proteins
  73. Triazinone tautomers: solid phase energetics
  74. Anisotropic Repulsion Potentials for Cyanuric Chloride (C 3 N 3 Cl 3 ) and Their Application to Modeling the Crystal Structures of Azaaromatic Chlorides
  75. The Relationship between the Sequence Identities of Alpha Helical Proteins in the PDB and the Molecular Similarities of Their Ligands
  76. The Determination of the Crystal Structure of Anhydrous Theophylline by X-ray Powder Diffraction with a Systematic Search Algorithm, Lattice Energy Calculations, and 13 C and 15 N Solid-State NMR:  A Question of Polymorphism in a Given Unit Cell
  77. A Systematic Nonempirical Method of Deriving Model Intermolecular Potentials for Organic Molecules:  Application To Amides
  78. Protein folds and functions
  79. Design, synthesis and structure of a zinc finger with an artificial β-turn
  80. Non‐randomness in side‐chain packing: the distribution of interplanar angles
  81. Multiple Solution Conformations of the Integrin-Binding Cyclic Pentapeptide Cyclo(-Ser-d-Leu-Asp-Val-Pro-). Analysis of the (phi,psi) Space Available to Cyclic Pentapeptides
  82. Modelling the interactions of protein side-chains
  83. Amino/Aromatic Interactions in Proteins: Is the Evidence Stacked Against Hydrogen Bonding?
  84. Towards an understanding of the arginine-aspartate interaction