A Unified, Probabilistic Framework for Structure- and Ligand-Based Virtual Screening
S.L. Swann, S.P. Brown, S.W. Muchmore, H. Patel, P. Merta, J. Locklear and P.J. Hajduk, "A Unified, Probabilistic Framework for Structure- and Ligand-Based Virtual Screening", J. Med. Chem., 2011, 54 (5), pp 1223-1232
We present a probabilistic framework for interpreting structure-based virtual screening that returns a quantitative likelihood of observing bioactivity and can be quantitatively combined with ligand-based screening methods to yield a cumulative prediction that consistently outperforms any single screening metric. The approach has been developed and validated on more than 30 different protein targets. Transforming structure-based in silico screening results into robust probabilities of activity enables the general fusion of multiple structure- and ligand-based approaches and returns a quantitative expectation of success that can be used to prioritize (or deprioritize) further discovery activities. This unified probabilistic framework offers a paradigm shift in how docking and scoring results are interpreted, which can enhance early lead-finding efforts by maximizing the value of in silico computational tools.
