5D-QSAR: the key for simulating induced fit?
The results indicate that the formal investment of additional computer time is well-returned both in quantitative and in qualitative values: less-biased boundary conditions, healthier (i.e., less inbred) model populations, and more accurate predictions of new compounds.
Ionophores and Their Structures
- M. Dobler
- 23 September 1981
Provides a comprehensive survey of the three-dimensional structure of ionophores. Supplements the stereoscopic picture of the molecule with a list of orthogonal coordinates for constituent atoms.…
VirtualToxLab - a platform for estimating the toxic potential of drugs, chemicals and natural products.
VirtualToxLab - in silico prediction of the toxic (endocrine-disrupting) potential of drugs, chemicals and natural products. Two years and 2,000 compounds of experience: a progress report.
The VirtualToxLab is an in silico tool for predicting the toxic (endocrine-disrupting) potential of drugs, chemicals and natural products. It is based on a fully automated protocol and calculates the…
PrGen: Pseudoreceptor Modeling Using Receptor‐mediated Ligand Alignment and Pharmacophore Equilibration
A ligand equilibration protocol that permits to identify an alternate position, orientation and conformation for each ligand molecule by means of conformational search within a primordial receptor model, constructed about the most potent ligands of a series is developed.
Combining protein modeling and 6D-QSAR. Simulating the binding of structurally diverse ligands to the estrogen receptor.
The results obtained suggest that the underlying philosophy combines flexible docking and 6D-QSAR is suitable for the identification of an endocrine-disrupting potential associated with drugs and chemicals.
OpenVirtualToxLab--a platform for generating and exchanging in silico toxicity data.
Multidimensional QSAR: Moving from three‐ to five‐dimensional concepts
3D-QSAR simulations allow for a specific interaction scheme with the virtual receptor, but they presume the knowledge of the bioactive conformation of the ligand molecules and require a sophisticated guess about manifestation and magnitude of the associated induced fit.
The challenge of predicting drug toxicity in silico.
- A. Vedani, M. Dobler, M. Lill
- Biology, ChemistryBasic & Clinical Pharmacology & Toxicology
- 1 September 2006
Results suggest that the laboratory's approach is suited for the in silico identification of adverse effects triggered by drugs and chemicals and encouraged us to compile an Internet Database for the virtual screening of drugs andchemicals for toxic effects.
Raptor: combining dual-shell representation, induced-fit simulation, and hydrophobicity scoring in receptor modeling: application toward the simulation of structurally diverse ligand sets.
A novel receptor-modeling approach based on multidimensional quantitative structure-activity relationships (QSARs) that makes the approach independent from a partial-charge model and allows one to smoothly model ligand molecules binding to the receptor with different net charges.