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P N Craig

Publications and source records attributed to P N Craig.

12 recordsLinked to original sources
PubMed1984

NLM-CHEMSORT: an algorithm and computer program for sorting chemical names.

An algorithm is described that has been designed to sort medium-size lists of chemical names, including common, generic, trivial, and systematic names and code numbers, into a logical sequence. It successfully sorted more than 99.5% of 3767 names in its first application. Minor revisions then resulted in more than 99.9% success with the same set of names. The algorithm generates an 80-character primary sort key (alphabetic characters only) and a 16-character secondary level sort key (alphanumeric characters). These sort keys are generated de novo from the name as needed and, thus, do not require increased permanent-storage costs. Sorting on the primary sort key (and secondary sort keys when identical primary keys exist) results in logical sequences of chemical names.

Chemical Phenomena↗
PubMed1979

Quantitative structure-activity relationships in 1-aryl-2-(alkylamino)ethanol antimalarials.

A quantitative structure-activity relationship has been formulated for 646 antimalarials acting against P. berghei in mice. The equation developed has 14 terms, 9 of which are indicator variables. The correlation coefficient for the QSAR is 0.898 and the standard deviation is 0.309. The antimalarials are all arylcarbinols of the type X-ArCHOHCH2NR1R2. Sixty different aryl structures, including a variety of heterocyles, are contained in the study. The most important determinate of activity is found to be the electron-withdrawing ability of the substituents X; the hydrophobic character of X and R plays less important roles. Suggestions for more potent analogues are made and the lack of activity of about 100 additional analogues is also considered.

Animals↗
PubMedDate not supplied

Carcinogenesis: a predictive structure-activity model.

A statistical structure-activity equation has been developed for the estimation of carcinogenic potential for chemicals that have not been subjected to carcinogenesis assays. This discriminant equation is based on substructural fragments and molecular weight obtained for 343 compounds. The data base used for the design of the equation was obtained from the monographs of the International Agency for Research on Cancer. The accuracy of classification for the carcinogens in the model is between 87 and 91%, and for noncarcinogens between 78 and 80% in the presence of between 5.5 and 10.2% of the compounds not being classifiable. The false negative rate ranges between 4 and 5%; the false positive rate is near 11%.

Carcinogens↗