A statistical framework to evaluate virtual screening

<p>Abstract</p> <p>Background</p> <p>Receiver operating characteristic (ROC) curve is widely used to evaluate virtual screening (VS) studies. However, the method fails to address the "early recognition" problem specific to VS. Although many other metrics, such as RIE, BEDROC, and pROC that emphasize "early recognition" have been proposed, there are no rigorous statistical guidelines for determining the thresholds and performing significance tests. Also no comparisons have been made between these metrics under a statistical framework to better understand their performances.</p> <p>Results</p> <p>We have proposed a statistical framework to evaluate VS studies by which the threshold to determine whether a ranking method is better than random ranking can be derived by bootstrap simulations and 2 ranking methods can be compared by permutation test. We found that different metrics emphasize "early recognition" differently. BEDROC and RIE are 2 statistically equivalent metrics. Our newly proposed metric SLR is superior to pROC. Through extensive simulations, we observed a "seesaw effect" – overemphasizing early recognition reduces the statistical power of a metric to detect true early recognitions.</p> <p>Conclusion</p> <p>The statistical framework developed and tested by us is applicable to any other metric as well, even if their exact distribution is unknown. Under this framework, a threshold can be easily selected according to a pre-specified type I error rate and statistical comparisons between 2 ranking methods becomes possible. The theoretical null distribution of SLR metric is available so that the threshold of SLR can be exactly determined without resorting to bootstrap simulations, which makes it easy to use in practical virtual screening studies.</p

Molecular modeling and synthesis of ZINC02765569 derivatives as protein tyrosine phosphatase 1B inhibitors: lead optimization study

This article describes design, synthesis, and molecular modeling studies of the ZINC02765569 derivatives as potent protein tyrosine phosphatase 1B (PTP1B) inhibitors, which was previously reported as a vHTS hit (ZINC02765569) by our laboratory. Ten compounds were synthesized and characterized by IR, MASS, and NMR followed by in vitro screening for PTP1B inhibition and glucose uptake in skeletal muscle L6 myotubes. The most potent compound 3j shows 66.4 % in vitro PTP1B inhibition and 39.6 % increase in glucose uptake. Glide was used to study the nature of interactions governing binding of designed molecules with active site of the PTP1B enzyme