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#11thiccs Sereina Riniker on Machine learning of partial charges from QM calcs and the applic in fixed-charge force fields and cheminf
A classical fixed-charge force field has parameters for bonded atoms and non-bonded. The non-bonded are most important for interactions. Review by me in JCIM 2018, 58, 565. Bonded are from crystallography. Charges come from QM, fitted to liquid properties.
QM-derived partial charges. Extraction from electron density is an undetermined maths problem. Most try to fit to ESP with Kollman-Singh, semi-empirical with bond order corrections, e.g. AM1-BCC. Issues, low quality QM (decrease cost), conformational dependence.
#11thICCS Greg Landrum on How do you build and validate 1500 models and what can you learn from them?
Really..."the Monster Model Factory".. Have >1500 datasets from CHEMBL that I want to build models for. Needs to be automated. Ideally we can learn s.t. about what makes model work vs not work
CRISP-DM - standard process for data mining solutions - see wikipedia
