Background: Structural genomics projects such as the Protein Structure Initiative (PSI) yield many new structures, but often these have no known molecular functions. One approach to recover this information is to use 3D templates -structure-function motifs that consist of a few functionally critical amino acids and may suggest functional similarity when geometrically matched to other structures. Since experimentally determined functional sites are not common enough to define 3D templates on a large scale, this work tests a computational strategy to select relevant residues for 3D templates.

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.

Ricin toxin A chain (RTA) binds to stalk P-proteins to reach the α-sarcin/ricin loop (SRL) where it cleaves a conserved adenine. Arginine residues at the RTA/RTB interface are involved in this interaction. To investigate the individual contribution of each arginine, we generated single, double and triple arginine mutations in RTA. The R235A mutation reduced toxicity and depurination activity more than any other single arginine mutation in yeast. Further reduction in toxicity, depurination activity and ribosome binding was observed when R235A was combined with a mutation in a nearby arginine. RTA interacts with the ribosome via a two-step process, which involves slow and fast interactions. Single arginine mutations eliminated the fast interactions with the ribosome, indicating that they increase the binding rate of RTA. Arginine residues form a positively charged patch to bind to negatively charged residues at the C-termini of P-proteins. When electrostatic interactions conferred by the arginines are lost, hydrophobic interactions are also abolished, suggesting that the hydrophobic interactions alone are insufficient to allow binding. We propose that Arg235 serves as an anchor residue and cooperates with nearby arginines and the hydrophobic interactions to provide the binding specificity and strength in ribosome targeting of RTA.The plant toxin ricin produced by the castor bean plant, Ricinus communis, is one of the most potent and lethal substances known 1 . Due to its wide availability and the ease of production, ricin has been exploited as an agent of bioterrorism and biological warfare 1,2 . Tons of ricin are produced annually worldwide as a by-product of castor oil. Ricin induces apoptosis in transformed cells and has been used for chemotherapy in humans 3,4 . The related Shiga toxins (Stx) produced by E. coli (STEC) can cause severe morbidity and mortality, including hemorrhagic colitis (HC) and hemolytic uremic syndrome (HUS) 5 . These toxins remain a major challenge for food safety and public health. Currently, no FDA-approved vaccine or therapeutics exist to protect against ricin intoxication or Stx-mediated disease. Ricin is a type II ribosome inactivating protein (RIP) consisting of ricin toxin A chain (RTA) and ricin toxin B chain (RTB) connected by a disulfide bond 6 . RTB is a galactose specific lectin that binds to glycolipids or glycoproteins on the cell surface to promote endocytosis of the toxin 7 . RTA is an N-glycosidase that cleaves a conserved adenine (A4324 in rat and A3027 in yeast) from the α-sarcin/ricin loop (SRL) of the large rRNA 8,9 . Ricin holotoxin enters cells through RTB mediated endocytosis. In the ER, the disulfide bond between RTA and RTB is reduced, releasing RTA from RTB 10 . The free RTA enters the cytosol by the endoplasmic reticulum associated degradation (ERAD) pathway to reach the ribosome, to depurinate the SRL and inhibit protein synthesis 11,12 .Though the SRL is highly conserved, the ribosomal context enhances the depurination rate by several orders of magnitude, in...

The complex interactions between proteins and small organic molecules (ligands) are intensively studied because they play key roles in biological processes and drug activities. Here, we present a novel approach to characterise and map the ligand-binding cavities of proteins without direct geometric comparison of structures, based on Principal Component Analysis of cavity properties (related mainly to size, polarity and charge). This approach can provide valuable information on the similarities, and dissimilarities, of binding cavities due to mutations, between-species differences and flexibility upon ligand-binding. The presented results show that information on ligand-binding cavity variations can complement information on protein similarity obtained from sequence comparisons. The predictive aspect of the method is exemplified by successful predictions of serine proteases that were not included in the model construction. The presented strategy to compare ligand-binding cavities of related and unrelated proteins has many potential applications within protein and medicinal chemistry, for example in the characterisation and mapping of “orphan structures”, selection of protein structures for docking studies in structure-based design and identification of proteins for selectivity screens in drug design programs.