Abstract
The biochemical half maximal inhibitory concentration (IC50) is the most commonly used metric for on-target activity in lead optimization. It is used to guide lead optimization, build large-scale chemogenomics analysis, off-target activity and toxicity models based on public data. However, the use of public biochemical IC50 data is problematic, because they are assay specific and comparable only under certain conditions. For large scale analysis it is not feasible to check each data entry manually and it is very tempting to mix all available IC50 values from public database even if assay information is not reported. As previously reported for Ki database analysis, we first analyzed the types of errors, the redundancy and the variability that can be found in ChEMBL IC50 database. For assessing the variability of IC50 data independently measured in two different labs at least ten IC50 data for identical protein-ligand systems against the same target were searched in ChEMBL. As a not sufficient number of cases of this type are available, the variability of IC50 data was assessed by comparing all pairs of independent IC50 measurements on identical protein-ligand systems. The standard deviation of IC50 data is only 25% larger than the standard deviation of Ki data, suggesting that mixing IC50 data from different assays, even not knowing assay conditions details, only adds a moderate amount of noise to the overall data. The standard deviation of public ChEMBL IC50 data, as expected, resulted greater than the standard deviation of in-house intra-laboratory/inter-day IC50 data. Augmenting mixed public IC50 data by public Ki data does not deteriorate the quality of the mixed IC50 data, if the Ki is corrected by an offset. For a broad dataset such as ChEMBL database a Ki- IC50 conversion factor of 2 was found to be the most reasonable.
Highlights
IntroductionPublic collections of IC50 data (the half maximal inhibitory concentrations of ligands on their protein targets) represent a wealth of knowledge on bioactivity with growing importance
Public collections of IC50 data represent a wealth of knowledge on bioactivity with growing importance
In order to assess the comparability of IC50 values, we first extracted all series of compounds that have been measured against the same protein target in two independent assays from whole ChEMBL
Summary
Public collections of IC50 data (the half maximal inhibitory concentrations of ligands on their protein targets) represent a wealth of knowledge on bioactivity with growing importance. [2] Proper usage of IC50 data facilitates the development of useful methods for drug discovery. Examples of such applications are the global mapping of pharmacological space by Paolini and coworkers, [3] the Similarity Ensemble Approach (SEA), [4] the Bayesian models for adverse drug reactions by Bender and coworkers, [5] the models used for polypharmacological optimization by Hopkins et al, [6] and the kinome-wide activity modeling studies by Schuerer and Muskal. [7] These methods can be used to predict off-target effects based on heterogeneous public activity data and chemical similarity analysis. For the simplest typical case of competitive monosubstrate enzyme inhibition, Ki can be calculated from the IC50 according to the Cheng-Prusoff equation: Ki
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