Abstract
Computational methods are increasingly gaining importance as an aid in identifying active sites. Mostly these methods tend to have structural information that supplement sequence conservation based analyses. Development of tools that compute electrostatic potentials has further improved our ability to better characterize the active site residues in proteins. We have described a computational methodology for detecting active sites based on structural and electrostatic conformity - C ata L ytic A ctive S ite P rediction (CLASP). In our pipelined model, physical 3D signature of any particular enzymatic function as defined by its active sites is used to obtain spatially congruent matches. While previous work has revealed that catalytic residues have large pKa deviations from standard values, we show that for a given enzymatic activity, electrostatic potential difference (PD) between analogous residue pairs in an active site taken from different proteins of the same family are similar. False positives in spatially congruent matches are further pruned by PD analysis where cognate pairs with large deviations are rejected. We first present the results of active site prediction by CLASP for two enzymatic activities - β-lactamases and serine proteases, two of the most extensively investigated enzymes. The results of CLASP analysis on motifs extracted from Catalytic Site Atlas (CSA) are also presented in order to demonstrate its ability to accurately classify any protein, putative or otherwise, with known structure. The source code and database is made available at www.sanchak.com/clasp/. Subsequently, we probed alkaline phosphatases (AP), one of the well known promiscuous enzymes, for additional activities. Such a search has led us to predict a hitherto unknown function of shrimp alkaline phosphatase (SAP), where the protein acts as a protease. Finally, we present experimental evidence of the prediction by CLASP by showing that SAP indeed has protease activity in vitro.
Highlights
The PDB database has more than 60,000 protein structures to date [1]
Several methods are available for identifying active site residues in a protein, amongst which methods based on electrostatic potentials are increasingly gaining ground
We present in vitro evidence of the prediction by CataLytic Active Site Prediction (CLASP) that shrimp alkaline phosphatase (SAP) has protease activity
Summary
The PDB database has more than 60,000 protein structures to date [1]. Classification of proteins is the logical outcome of the motivation to add a sense of order in this rapidly growing database [2,3,4,5,6,7]. Finite difference Poisson-Boltzmann (FDPB) electrostatics is used to compute potential differences (PD) and pKa values from charge interactions in proteins [9,10,11]. This continuum model of charges led to the development of tools for studying electrostatic interactions [12,13,14]. Active site residues have pKa values that differ considerably from their intrinsic values [16,17]. The buried nature of residues in active sites often results in their high electrostatic potential which has been used as a differentiator between catalytic and other residues [23,24]
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