Best Practices for QSAR Model Development, Validation, and Exploitation
University of North Carolina at Chapel Hill
Abstract
After nearly five decades "in the making", QSAR modeling has established itself as one of the major computational molecular modeling methodologies. As any mature research discipline, QSAR modeling can be characterized by a collection of well defined protocols and procedures that enable the expert application of the method for exploring and exploiting ever growing collections of biologically active chemical compounds. This review examines most critical QSAR modeling routines that we regard as best practices in the field. We discuss these procedures in the context of integrative predictive QSAR modeling workflow that is focused on achieving models of the highest statistical rigor and external predictive power.…
Citation impact
- FWCI
- 56.63
- Percentile
- 100%
- References
- 60
Authors
1Topics & keywords
- Quantitative structure–activity relationship
- Model validation
- Computer science
- Applicability domain
- Biochemical engineering
- Data mining
- Machine learning
- Data science