Looking for the Best QSAR and Docking MethodsGuillermo Restrepo1
|1Laboratorio de Química Teórica, Universidad de Pamplona, Pamplona, Colombia|
|“Results show that the best docking program…” and “this QSAR model is better than…” are customary claims in the specialised scientific literature. The question discussed in this presentation is whether is always possible to talk about a unique “best”. It turns out that seeking for a “best” amongst objects of a set implies ordering them; hence a first object appears, as well as a second, third and so on. This kind of particular ordering leads to what is called as a ranking, quite spread nowadays e.g. in the ranking of universities, journals, etc. Ordering can be mathematically treated through order theory, from which it is found that if several attributes are used to characterise the objects of a set, it may happen that several “bests” and several “worst” result. In this presentation we show how that is possible and how it can help to shed light on the question of the “best” QSAR (Quantitative Structure-Activity Relationship) and docking methods.|
A method to introduce order theory in the kind of situations mentioned before is the Hasse diagram technique (HDT) [1, 2]. The procedure requires the characterisation of the objects to order through objects’ attributes. In general, if two objects x and y are characterised by the attributes q1(x), q2(x), ..., qi(x) and q1(y), q2(y), ..., qi(y), x is ordered (ranked) higher than y if all its attributes are higher than those of y, or if at least one attribute is higher for x while all others are equal. In this case, x and y are said to be comparable. If all attributes of x and y are equal, both objects are equivalent . If x is ranked higher than y and y than z then x is ranked higher than z. If at least one attribute qj fulfils qj(x) < qj(y) while the others are opposite (qi(x) >= qi(y)), x and y are incomparable . These order relationships can be represented as a Hasse diagram (HD). A HD collects all the order relations of the set under study and its interpretation is based upon the lines connecting the objects. In the lecture the simple rules to interpreting it will be explained.
The first example of application of the HDT orders QSAR models developed for estimating mutagenicity of aromatic and heteroaromatic amines . The attributes used to characterise each model are their respective statistics (r2 and s). In the lecture the results of these ordering will be discussed and special attention will be given to equivalent models performing better than the others.
The second example considers the ordering or ten docking programmes based upon their performance against eight proteins regarding their binding mode prediction, virtual screening for lead identification and rank-ordering by affinity for lead optimization. Here also the appearance of equivalent objects and “best” docking programmes is discussed and contrasted with the study where the performance of the mentioned programmes was initially analysed .
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