Abstract
Many algorithms that compare protein structures can reveal similarities that suggest related biological functions, even at great evolutionary distances. Proteins with related function often exhibit differences in binding specificity, but few algorithms identify structural variations that effect specificity. To address this problem, we describe the Volumetric Analysis of Surface Properties (VASP), a novel volumetric analysis tool for the comparison of binding sites in aligned protein structures. VASP uses solid volumes to represent protein shape and the shape of surface cavities, clefts and tunnels that are defined with other methods. Our approach, inspired by techniques from constructive solid geometry, enables the isolation of volumetrically conserved and variable regions within three dimensionally superposed volumes. We applied VASP to compute a comparative volumetric analysis of the ligand binding sites formed by members of the steroidogenic acute regulatory protein (StAR)-related lipid transfer (START) domains and the serine proteases. Within both families, VASP isolated individual amino acids that create structural differences between ligand binding cavities that are known to influence differences in binding specificity. Also, VASP isolated cavity subregions that differ between ligand binding cavities which are essential for differences in binding specificity. As such, VASP should prove a valuable tool in the study of protein-ligand binding specificity.
Highlights
The comparative analysis of protein structures is widely used to infer protein function
We present a Volumetric Analysis of Surface Properties (VASP)
VASP differs from existing methods because it compares solid representations of protein structures and cavities based on principles from computer graphics and computer aided design
Summary
The comparative analysis of protein structures is widely used to infer protein function. Geometric alignment of entire structures or of individual domains can reveal that two proteins are related even if this is not evident from sequence. Surface representations of proteins [19,20,21,22,23,24] are, in particular, widely used as they reveal shape recognition features that underlie binding specificity. A large class of phenomena depend on the ability of closely related proteins to bind similar but non-identical ligands. In such cases the function of a protein as normally defined is well-known but its binding preferences may not be
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