Inverse-QSPR for de novo design: a review.

Researchers

Journal

Modalities

Models

Abstract

The use of computer tools to solve chemistry-related problems – chemoinformatics – has given rise to a large number of publications. Among all chemoinformatics techniques, the use of statistically based approaches for property predictions has been the subject of numerous research reflecting new developments and many cases of applications. Models relating a property to molecular features are gathered under the acronym QSPR, for Quantitative Structure Property Relationships. Apart from the obvious use of such models to predict property values for new compounds, their use to virtually synthesize new molecules – de novo design – is currently a high-interest subject. Inverse-QSPR (i-QSPR) methods have hence been developed to accelerate the discovery of new materials that meet a set of specifications. In the proposed manuscript, we review existing i-QSPR methodologies published in the open literature in a way to highlight developments, applications, improvements and limitations of each.
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