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.

The maximum achievable accuracy of in silico models depends on the quality of the experimental data. Consequently, experimental uncertainty defines a natural upper limit to the predictive performance possible. Models that yield errors smaller than the experimental uncertainty are necessarily overtrained. A reliable estimate of the experimental uncertainty is therefore of high importance to all originators and users of in silico models. The data deposited in ChEMBL was analyzed for reproducibility, i.e., the experimental uncertainty of independent measurements. Careful filtering of the data was required because ChEMBL contains unit-transcription errors, undifferentiated stereoisomers, and repeated citations of single measurements (90% of all pairs). The experimental uncertainty is estimated to yield a mean error of 0.44 pK(i) units, a standard deviation of 0.54 pK(i) units, and a median error of 0.34 pK(i) units. The maximum possible squared Pearson correlation coefficient (R(2)) on large data sets is estimated to be 0.81.

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Root system architecture determines many of the vital functions of a tree, e.g. stability of anchorage and resource uptake. The shoot:root ratio is determined through the allocation of resources. Studies on below-ground architectural elements in boreal mixed forests are relatively scarce despite the fact that knowledge on below-ground interactions and allocation changes in relation to stand developmental stage and soil fertility is needed both in ecological and silvicultural research. In this study, sixty tree root systems of three different tree species, Betula pendula, Picea abies and Pinus sylvestris, were excavated in five mixed forest stands in order to quantify differences between the species and sites in terms of rooting behaviour. Root architecture differed greatly between the species, implying different solutions for the functions of root systems. Half of the P. sylvestris had developed a taproot as a response to anchorage needs, while P. abies correspondingly had pronounced secondary growth of proximal roots. Betula pendula had the most extensive root system, illustrating the greater demand of deciduous trees for water. Betula pendula was also the most sensitive to soil fertility: it favoured exploration on the poorest site, as illustrated by the high total root length, whereas on the most fertile site its strategy was to efficiently exploit soil resources through increased branching intensity. The results obtained in this study provide basic knowledge on the architectural characteristics of boreal tree root systems for use by forestry professionals and modellers.