ISSN:
1573-4951
Keywords:
Automated prediction
;
QSAR
;
Molecular shape
;
Ligand binding
;
Molecular recognition
Source:
Springer Online Journal Archives 1860-2000
Topics:
Chemistry and Pharmacology
Notes:
Summary Building predictive models for iterative drug design in the absence of a known target protein structure is an important challenge. We present a novel technique, Compass, that removes a major obstacle to accurate prediction by automatically selecting conformations and alignments of molecules without the benefit of a characterized active site. The technique combines explicit representation of molecular shape with neural network learning methods to produce highly predictive models, even across chemically distinct classes of molecules. We apply the method to predicting human perception of musk odor and show how the resulting models can provide graphical guidance for chemical modifications.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF00124012
Permalink