Knowledge-based model of hydrogen-bonding propensity in organic crystals

Peter T. A. Galek, Laszlo Fabian, W. D. Samuel Motherwell, Frank H. Allen, Neil Feeder

Research output: Contribution to journalArticlepeer-review

135 Citations (Scopus)


A new method is presented to predict which donors and acceptors form hydrogen bonds in a crystal structure, based on the statistical analysis of hydrogen bonds in the Cambridge Structural Database (CSD). The method is named the logit hydrogen-bonding propensity (LHP) model. The approach has a potential application in identifying both likely and unusual hydrogen bonding, which can help to rationalize stable and metastable crystalline forms, of relevance to drug development in the pharmaceutical industry. Whilst polymorph prediction techniques are widely used, the LHP model is knowledge-based and is not restricted by the computational issues of polymorph prediction, and as such may form a valuable precursor to polymorph screening. Model construction applies logistic regression, using training data obtained with a new survey method based on the CSD system. The survey categorizes the hydrogen bonds and extracts model parameter values using descriptive structural and chemical properties from three-dimensional organic crystal structures. LHP predictions from a fitted model are made using two-dimensional observables alone. In the initial cases analysed, the model is highly accurate, achieving ~ 90% correct classification of both observed hydrogen bonds and non-interacting donor-acceptor pairs. Extensive statistical validation shows the LHP model to be robust across a range of small-molecule organic crystal structures.
Original languageEnglish
Pages (from-to)768-782
Number of pages15
JournalActa Crystallographica Section B
Issue number5
Publication statusPublished - 2007

Cite this