On the Relationship Between Catalytic Residues and their Protein Contact Number

Abstract

Due to advances in structural biology, an increasing number of protein structures of unknown function have been deposited in Protein Data Bank (PDB). These proteins are usually characterized by novel structures and sequences. Conventional comparative methodology (such as sequence alignment, structure comparison, or template search) is unable to determine their function. Thus, it is important to identify protein's function directly from its structure, but this is not an easy task. One of the strategies used is to analyze whether there are distinctive structure-derived features associated with functional residues. If so, one may be able to identify the functional residues directly from a single structure. Recently, we have shown that protein weighted contact number is related to atomic thermal fluctuations and can be used to derive motional correlations in proteins. In this report, we analyze the weighted contact-number profiles of both catalytic residues and non-catalytic residues for a dataset of 760 structures. We found that catalytic residues have distinct distributions of weighted contact numbers from those of non-catalytic residues. Using this feature, we are able to effectively differentiate catalytic residues from other residues with a single optimized threshold value. Our method is simple to implement and compares favourably with other more sophisticated methods. In addition, we discuss the physics behind the relationship between catalytic residues and their contact numbers as well as other features (such as residue centrality or B-factors) associated with catalytic residues.

On the Relationship Between Residue Solvent Exposure and Thermal Fluctuations in Proteins

“…These two models are shown to be able to reproduce B-factor from protein structure. The WCN model was further applied to the prediction of NMR order parameters and the identification of enzyme active sites (Huang et al, 2011). The basic idea of the PFP model is assume that thermal fluctuation of a residue is related to the squared distance between the residue and the center-of-mass of the protein: …”

On the Structural Characteristics of the Protein Active Sites and Their Relation to Thermal Fluctuations

“…The WCN profile, which correlates well with the B-factors but depends only on structure per se, is a much better discriminator for the catalytic residues. Hwang and co-workers showed a straightforward application of the WCN profile to predicting the catalytic residues (Huang, Yu et al 2011). We will illustrate this with an example: S-adenosylmethionine decarboxylase (AdoMetDC) (Ekstrom, Mathews et al 1999), a critical regulatory enzyme of the polyamine synthetic pathway, has 5 catalytic residues.…”

“…The basic idea of the approach is simple: to obtain a threshold value for the WCN profile such that the residues whose Zvalues are below the threshold are predicted to be catalytic residues. The threshold Z-value is determined by minimizing both the false positives and the false negatives of the predicted catalytic residues (Huang, Yu et al 2011). The threshold for the WCN profile is -0.9.…”

“…The threshold for the WCN profile is -0.9. Figure 9 compares the receiver operating characteristics (ROC) curves of 4 structural profiles for their prediction of the active site residues for a data set comprising 760 X-ray nonhomologous enzyme structures (Huang, Yu et al 2011). These profiles are the WCN profile, the PFP profile, the CN profile and the B-factor profile.…”

“…One needs to develop ingenious approaches that do not rely on evolutionary information. Recently, several groups Ben-Shimon & Eisenstein 2005;Huang, Yu et al 2011) developed novel approaches to predict the active sites of enzymes from a single structure without using any homologous structures or known catalytic templates. The basic idea of their approaches is simple: they first identify certain structural or dynamical features that are unique to the active sites; they then further refine this relationship such that it can be used to accurately predict the enzyme catalytic sites.…”