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− | The atom typing algorithm is based on a flexible [[PATTY]] expert system. | + | The atom typing algorithm is based on a flexible [[PATTY]] expert system ([[Article:bs93]]). This assignment requires previously assigned [[Aromaticity]] and [[Hybridisation]] informations. Some basic atom typing rules were e.g. published by ([[Article:ksfams96]]) |
| ==Data ([[PATTY]] expert system)== | | ==Data ([[PATTY]] expert system)== |
− | * [http://cvs.sourceforge.net/viewcvs.py/openbabel/openbabel/data/atomtyp.txt?view=markup atomtyp.txt] | + | * [http://openbabel.svn.sourceforge.net/viewvc/openbabel/openbabel/trunk/data/atomtyp.txt?view=markup atomtyp.txt] |
− | ==References==
| + | * [http://openbabel.svn.sourceforge.net/viewvc/openbabel/openbabel/trunk/data/types.txt?view=markup types.txt] |
− | @Article{bs93,
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− | author = {B. L. Bush and R. P. Sheridan},
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− | title = {{PATTY}: {A} {P}rogrammable {A}tom {T}yper and {L}anguage for {A}utomatic
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− | {C}lassification of {A}toms in {M}olecular {D}atabases.},
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− | journal = {J. Chem. Inf. Comput. Sci.},
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− | year = {1993},
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− | volume = {33},
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− | pages = {756-762},
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− | }
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− | | + | |
− | @Article{ksfams96,
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− | author = {S. K. Kearsley and S. Sallamack and E. M. Fluder and J. D. Andose
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− | and R. T. Mosley and R. P. Sheridan},
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− | title = {{C}hemical {S}imilarity {U}sing {P}hysiochemical {P}roperty {D}escriptors},
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− | journal = {J. Chem. Inf. Comput. Sci.},
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− | year = {1996},
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− | volume = {36},
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− | pages = {118--127},
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− | abstract = {Similarity searches using topological descriptors have proved extremely
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− | useful in aiding large-scale screening. We describe alternative
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− | forms of the atom pair (Carhart et al. J. Chem. Inf. Comput. Sci.
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− | 1985, 25,64-73.) and topological torsion (Nilakantan et al. J. Chem.
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− | Inf. Comput. Sci. 1987, 27,82-85.) descriptors that use physiochemical
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− | atom types. These types are based on binding property class, atomic
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− | log P contribution, and partial atomic charges. The new descriptors
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− | are meant to be more fuzzy than the original descriptors. We propose
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− | objective criteria for determining how effective one descriptor
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− | is versus another in selecting active compounds from large databases.
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− | Using these criteria, we run similarity searches over the Derwent
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− | Standard Drug File with ten typical druglike probes. The new descriptors
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− | are not as good as the original descriptors in selecting actives
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− | if one considers the average over all probes, but the new descriptors
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− | do better for several individual probes. Generally we find that
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− | whether one descriptor does better than another varies from probe
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− | to probe in a way almost impossible to predict a priori. Most importantly,
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− | we find that different descriptors typically select very different
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− | sets of actives. Thus it is advantageous to run similarity probes
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− | with several types of descriptors.},
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− | doi = {[http://dx.doi.org/10.1021/ci950274j 10.1021/ci950274j]}
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− | }
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