A critical part of Matched Molecular Pair Analysis is the includsion of the chemical environment information with the chemical change. Scientists at GSK were the first to publish this finding and quantify the importance. Hence this is second selection for a #BucketListPapers on MMPA.
Lead Optimization Using Matched Molecular Pairs: Inclusion of Contextual Information for Enhanced Prediction of hERG Inhibition, Solubility, and Lipophilicity
J. Chem. Inf. Model. 2010, 50, 1872–1886
More honourable mentions:
In 2006, Abbott Laboratories published Drug-Guru, a medicinal chemistry “expert system” that contained a collection of molecular transformations compiled from the literature and medicinal chemists’ experience. When this was published, we had started work on a similar idea but using MMPA to ‘find’ all of the significant molecular transformations for med chem, thus saving the bother of manual cataloguing, and thus operating in an un-biased way.
A computer software program for drug design using medicinal chemistry rules.
Bioorg. Med. Chem. 2006, 14, 7011-7022.
For the statistical analysis of MMPA and the establishment of ‘med chem rules’ see:
Turbocharging Matched Molecular Pair Analysis: Optimizing the Identification and Analysis of Pairs.
J. Chem. Inf. Model. 2017, 57, 2424−2436
Coming back to the good people at GSK and Sheffield Uni, recently they examined the output drug design algorithms, compared to human output… an excellent read,..
A Turing test for molecular generators
J. Med. Chem. 2020, 63, 20, 11964–11971
#BucketListPapers #DrugDiscovery #MedicinalChemistry #BeTheBestChemistYouCanBe