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 vs. QSARhow could we say there is no

difference ?

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. QSARRoadmap

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 ?

Similarity : philosophers’ view

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”

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

Chemical Grouping by Similarity

H3CCH3

O

NumericalValues

Similarity between points

Similarity between structures

Selected similar compounds

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

J. Med. Chem. 2002,45,4350-4358

Cutoff values % of actives detected % False positives

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

compoundsA 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)

Distances - exampleby 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.

Data set 2

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)

SAR vs. QSARhow could we say there is no

difference ?

Two common things to this point: Both methods use numerical

representation of chemical compounds; Both methods need to decide which

representation to use;

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

“Neibourhood principle” Analysis

Neighbourhood in the descriptor

space

Similar activity values

Descriptor

Act

ivit

y

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)

SAR vs. QSARhow could we say there is a

difference ?

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.

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