Depth: a web server to compute depth, cavity sizes, detect potential small-molecule ligand-binding cavities and predict the pKa of ionizable residues in proteins

Abstract

Residue depth accurately measures burial and parameterizes local protein environment. Depth is the distance of any atom/residue to the closest bulk water. We consider the non-bulk waters to occupy cavities, whose volumes are determined using a Voronoi procedure. Our estimation of cavity sizes is statistically superior to estimates made by CASTp and VOIDOO, and on par with McVol over a data set of 40 cavities. Our calculated cavity volumes correlated best with the experimentally determined destabilization of 34 mutants from five proteins. Some of the cavities identified are capable of binding small molecule ligands. In this study, we have enhanced our depth-based predictions of binding sites by including evolutionary information. We have demonstrated that on a database (LigASite) of ∼200 proteins, we perform on par with ConCavity and better than MetaPocket 2.0. Our predictions, while less sensitive, are more specific and precise. Finally, we use depth (and other features) to predict pKas of GLU, ASP, LYS and HIS residues. Our results produce an average error of just <1 pH unit over 60 predictions. Our simple empirical method is statistically on par with two and superior to three other methods while inferior to only one. The DEPTH server (http://mspc.bii.a-star.edu.sg/depth/) is an ideal tool for rapid yet accurate structural analyses of protein structures.

Molecular Dynamics Simulations and Structural Network Analysis of c-Abl and c-Src Kinase Core Proteins: Capturing Allosteric Mechanisms and Communication Pathways from Residue Centrality

“…Analytical SASA is estimated computationally using analytical equations and their first and second derivatives and was computed using web server GetArea 95 . Residue depth measures the closest distance of the residue to bulk solvent 96 . In the first step, the protein molecule is solvated and water molecules that clash with atoms of the protein are removed from the box.…”

“…We also evaluated several other residue-based structural parameters, such as local residue flexibility, residue-based relative solvent accessibility (RSA) 95 and residue depth 96 . The RSA and betweenness parameters were generally correlated, showing that highly connected and stable residues would likely to reside in a locally buried structural environment and "poor" centrality was mostly associated with solvent-exposed (high RSA values) residues ( Figure S4 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 43 solvent.…”

Systematic site-directed mutagenesis of the Helicobacter pylori CagL protein of the Cag type IV secretion system identifies novel functional domains

“…We thereby determined the propensity of K170 in the CagL substitution mutant T170K to be locally charged under different conditions, which might be relevant for potential conformational change. The local pKa values for all lysine residues of CagL variant T170K were analyzed based on the CagL protein structure with DEPTH Server64. The results suggest that all other lysine residues except for “artificial” lysine 170 in CagL possess pKa values of around 10 (as expected).…”

Structural Comparison of Prokaryotic and Eukaryotic Folate Transporters by Computational Approach

“…For improved structural and functional analysis, ProFunc tool also reported binding site residues, cleft and nest analysis. Number of binding sites which may participate in ligand binding was figured out by DEPTH, a server dealing with the parameters such as ligand binding cavities and pKa of ionizable residues in proteins [20]. The characterized protein channel, pore shape, pore size, and pore axis were computed using fully automated tool named PoreWalker [20].…”

“…Number of binding sites which may participate in ligand binding was figured out by DEPTH, a server dealing with the parameters such as ligand binding cavities and pKa of ionizable residues in proteins [20]. The characterized protein channel, pore shape, pore size, and pore axis were computed using fully automated tool named PoreWalker [20]. Leucine-rich repeats and motif scanning were carried out by leucine-rich repeats (LRR) Finder [21].…”