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SAR vs QSAR or “is QSAR different from SAR”. Joanna Jaworska Procer & Gamble, Brussels, Belgium and Nina Jeliazkova IPP, Bulgarian Academy of Sciences, Sofia, Bulgaria. SAR is supposed to be not quantitative concept SAR is based on the notion of “similarity” :
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SAR vs QSARor “is QSAR different from SAR” Joanna Jaworska Procer & Gamble, Brussels, Belgium and Nina Jeliazkova IPP, Bulgarian Academy of Sciences, Sofia, Bulgaria
SAR is supposed to be not quantitative concept SAR is based on the notion of “similarity” : “Similar compounds have similar activity” “Dissimilar compounds have dissimilar activity” QSAR aims to derive a quantitative model of the activity SAR vs. QSARhow could we say there is no difference ?
What “similarity” means? A philosophers’ view and implications to the toxicology; Are the basic tenets of SAR true ? What do similarity measures measure ? How does the similarity measure relate to QSAR modeling ? SAR vs. QSARRoadmap
exploiting the similarity concept is a sign of immature science (Quine) “it is ill defined to say “A is similar to B” and it is only meaningful to say “A is similar to B with respect to C” Similarity : philosophers’ view implications for toxicology : A chemical “A” cannot be similar to a chemical “B” in absolute terms but only with respect to some measurable key feature
Numerical Values Chemical Grouping by Similarity Similarity between structures Selected similar compounds Similarity between points ?
Structural similarity • Does not imply always similarity in activity • Martin et al. 2002 J.Med.Chem 45,4350-58 • Does not always imply similarity in descriptors • Kubinyi, H., Chemical Similarity and Biological activity (with permission of the author)
Structurally similar compounds can have very different properties
Example: Y.Martin et al ( 2002) Do structurally similar molecules have similar biological activity ? • Set of 1645 chemicals with IC50s for monoamine oxidase inhibition • Daylight fingertips 1024 bits long ( 0-7 bonds) • Using Tanimoto coeff with a cut off value 0f 0.85 only 30 % of actives were detected Cutoff values % of actives detected % False positives J. Med. Chem. 2002,45,4350-4358
How else to measure chemical similarity ? • Describe chemical compounds with a set of numerical values ( fingerprints, diverse descriptors, field values, etc.) • Set up some measure between values (Euclidean distance, Tanimoto distance, Carbo similarity index, etc.) What do we actually measure ? And how it is related to the activity ?
What do we measure ? The distance between numerical representations of chemical compounds A few warnings: • The numerical representation is not unique • The numerical representation includes only part of all the information about the compound • A distance measure reflects “closeness” only if the data holds specific assumptions (next slide - example)
Data set 2 Data set 1 Distances - example by Euclidean distance we will decide that the red point is closer to the data set 2, while a human will note that it belongs to the data set 1. • Distances give results which are not always expected intuitively • Be aware of the assumptions behind distances (e.g. Euclidean distance gives good results with normally distributed data in orthogonal space)
How do we represent a chemical compound ? Fingerprints, Descriptors (more than 3000 available), electron density, various fields, etc. All representations lose information. We should ensure this information is not important. How?
Finding important information • A problem not unique to (Q)SAR • Lot of methods available • Most popular (e.g. PCA ) not the best Possible solution : look for the most discriminative information (example: descriptors which provide best discrimination between active and inactive compounds)
Two common things to this point: Both methods use numerical representation of chemical compounds; Both methods need to decide which representation to use; SAR vs. QSARhow could we say there is no difference ? One more difference : “SAR is a qualitative not a quantitative relationship” Is this true indeed?
Similarity and Activity • Proximity with respect to descriptors does not necessary mean proximity with respect to the activity (example) • This is only true if a linear relationship holds between descriptors and activity (examples) • The linear relationship is only a special case, given the complexity of biochemical interactions. Its use should be justified in every specific case • Structural similarity should be used with care (examples)
“Neighbourhood principle” • Molecules in the same local region (“neighbourhood”) of a descriptor space tend to have similar values of a desired property • Contradictory evidence exists : both supporting and rejecting
Similar activity values Activity Neighbourhood in the descriptor space Descriptor “Neibourhood principle” Analysis Depends on the relationship between the descriptors and activity !!!
“Neighbourhood principle” Lessons • In order to apply the “neighbourhood principle” the TYPE of the relationship between descriptor and activity should be known; • The “neighbourhood principle” is genuine only if the relationship is LINEAR; • The linear relationship is only a simple special case, given the complexity of biochemical interactions. Its use SHOULD BE JUSTIFIED in every specific case.
SAR vs QSAR • SAR is based on the “similarity” principle; • The principle is assumed, but in the reality it is not always true; • Similarity of structures • Similarity of descriptors • The authenticity depends on the type of the relationship between descriptors (numerical representation of chemicals) and activity; • The type of the relationship should be known (or derived)
Three common things to this point: Both methods use numerical representation of chemical compounds; Both methods need to decide which representation to use; Both methods need to derive the relationship between numerical representation (descriptors, etc.) and activity. SAR vs. QSARhow could we say there is a difference ?
Thank you! When you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind: it may be the beginning of knowledge, but you have scarcely advanced to the stage of science. William Thomson, Lord Kelvin