THEMATICS is Effective for Active Site Prediction in Comparative Model Structures

Shehadi, I.A., Ilyin, V., Murga, L.F., Ondrechen, M.J. and Uzun, A.

THEMATICS (Theoretical Microscopic Titration Curves) is a simple, reliable computational predictor of the active sites of enzymes from structure. Our method, based on well-established Finite Difference Poisson-Boltzmann techniques, identifies the ionisable residues with anomalous predicted titration behaviour. A cluster of two or more such perturbed residues is a very reliable predictor of the active site. The power of the method is that it only requires the three-dimensional structure as input. The protein does not have to bear any resemblance in sequence or structure to any previously characterized protein. The disadvantage of the method is that it does require the structure. We now present evidence that THEMATICS can also locate the active site in structures built by comparative modelling from similar structures. Results are given for three sets of orthologous proteins (Triosephosphate isomerase, 6-Hydroxymethyl-7,8- dihydropterin pyrophosphokinase, and Aspartate aminotransferase) and for one set of human homologues of Aldose reductase with different functions. In all of the cases studied, THEMATICS correctly locates the active site in the model structures. This suggests that the method can be applicable to proteins for which an experimentally determined structure is unavailable.

Cite as: Shehadi, I.A., Ilyin, V., Murga, L.F., Ondrechen, M.J. and Uzun, A. (2004). THEMATICS is Effective for Active Site Prediction in Comparative Model Structures. In Proc. Second Asia-Pacific Bioinformatics Conference (APBC2004), Dunedin, New Zealand. CRPIT, 29. Chen, Y.-P. P., Ed. ACS. 209-215.

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