Screening false positives

The probability that a sequence of interest is present in a library can be calculated as shown in Table 10.1. The optimal digestion of the target (e.g., partial digest with SamSA) to obtain maximum randomness of cloning is achieved when the most abundant insert size equals the vector capacity (Seed et al., 1982). A problem which may frequently occur is the change of representation of clones in the libraries during amplification. Some clones may be lost or become under-represented just because they reproduce slightly less rapidly. Independent libraries may then have to be screened. False positives also occur often, even if utmost care is taken to prevent contamination. 

Shafiq Q, Mutgi A. Urine opiate screening false-positive result with levofloxacin. CMAJ 2010 182(15) 1644-5. 

A major consideration in screening is the detection capability of the screen for both false negatives (lack of detection of an active drug) and propensity to find false positives (detection of a response to the compound not due to therapeutic activity of interest). Ostensibly, false positives might not be considered a serious problem in that secondary testing will detect these and they do not normally interfere with the drug discovery process. 

The use of animal models for depression has two main objectives. One is to provide a behavioural model that can be used to screen potential antidepressant treatments. For this, the behaviour does not have to be an animal analogue of depression all that is needed is for it to be consistently prevented by established antidepressant agents (i.e. no false negatives) but not by drugs which have no antidepressant effect in humans (i.e. no false positives). 

A systematic study was carried out using in parallel 50 standard solutions for each concentration of three natural colorants (curcumin, carminic acid, and caramel as yellow, red, and brown, respectively). No false positive results for synthetics were obtained up to concentrations of 15 and 20 ng/ml for natural red and yellow colorants, respectively, or 110 ng/ml for natural brown colorant. The concentrations have to be high enough to prove that the screening method is able to accurately discriminate natural and synthetic colorants. To make a clear interpretation of the quantitative UV-Vis spectrum, linear regression analysis was used. Quantitative UV-Vis analysis of a dye ° can be calculated according to the following formula ... 

Structurally related compounds may cross-react with the antibody, yielding inaccurate results. In screening for the herbicide alachlor in well water by immunoassay, a number of false positives were reported when compared with gas chromatography (GC) analysis. A metabolite of alachlor was found to be present in the samples and it was subsequently determined that the cross-reactivity by this metabolite accounted for the false-positive results. On the other hand, cross-reactivity by certain structural analogs may not be an issue. For example, in an assay for the herbicide atrazine, cross-reactivity by propazine is 196% because of atrazine and propazine field use... 

Assessment and definition of sensitivity are often described for quantitative analysis but are of equal importance for qualitative devices of the dip-stick type that are very popular for farm- or field-based screening assays. Because of the somewhat subjective nature of visually assessed assays, the assay s sensitivity must be validated using a number of observers to determine at what level a test is deemed positive. The number of false positives and false negatives must be carefully determined in order to balance consumer safety and potential economic loss to animal producers. 

The most X-ray intensive screening method was described by Card et al. [8] on the design of phosphodiesterase (PDE) inhibitors (Figure 1.7). The authors initially biochemically screened a 20,000 member library of small molecular weight (120-350 MW) core scaffold compounds against 5-PDE isoforms at 200 pM. Multiple isoforms of PDE were used in order to eliminate the number of false positives obtained from the screen. There were 316... 

An assay or screen is said to exhibit ROBUSTNESS when it has a high discriminatory power and produces a low number of FALSE NEGATIVE and FALSE POSITIVE results. 

Test a substantial number of compounds. VS methods generally offer enrichment, but most ranked hit lists contain a significant proportion of false positives. Hitlists should be scaled to 1-5% of the compounds in the virtual library screened. In many real world situations, the computational chemist is being asked to choose lists of compounds representing 0.1% or less of the compounds screened (e.g., the best 100 of 100,000 compounds). Typically, VS methods have been validated considering 1%, 5%, or 10% of the total number of compounds in the VS collection. By following up on more compounds, one increases the probability of impact from VS. 

---