Computational Methods for Functional Site Identification Suggest a Substrate Access Channel in Transaldolase

Michael Silberstein[1] (
Melissa R. Landon[1] (
Yaoyu E. Wang[1] (
Andras Perl[2] (
Sandor Vajda[3] (

[1]Graduate Program in Bioinformatics, Boston University, Boston, Massachusetts 02215
[2]Department of Medicine and Microbiology and Immunology, College of Medicine, State University of New York, Syracuse, NY 13210
[3]Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215


The homozygous deletion of Serine 171 results in the catalytic inactivation of the human transaldolase. Since Ser171 is in an outside loop, whereas the catalytic site is inside of the α/β-barrel of the protein at least 15 Å away, the loss of activity is difficult to explain. Two distinct computational methods are used to elucidate the potential origin of inactivation. Computational solvent mapping, which moves small organic molecules as probes around a protein surface and finds favorable binding positions, identifies the region around Ser171 as an important binding site. Three-dimensional cluster analysis, based both on a reference structure and multiple sequence alignment, shows that a patch of functionally important residues extends from Ser171 toward the catalytic site. Based on the findings of these two methods, we propose a novel ligand access path connecting these specific sites to the enzyme's active site. We also suggest that this mechanism may be aided by a significant conformational change involving the separation of two helices, αD and αG, in order to create an easy-access channel between the Ser171-related site and the active site. Further experimental procedures will be necessary to examine the biological feasibility of this proposed ligand shuttling path.

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Japanese Society for Bioinformatics