The Structure-Function Linkage Database.

The Structure-Function Linkage Database (SFLD, http://sfld.rbvi.ucsf.edu/) is a manually curated classification resource describing structure-function relationships for functionally diverse enzyme superfamilies. Members of such superfamilies are diverse in their overall reactions yet share a common ancestor and some conserved active site features associated with conserved functional attributes such as a partial reaction. Thus, despite their different functions, members of these superfamilies 'look alike', making them easy to misannotate. To address this complexity and enable rational transfer of functional features to unknowns only for those members for which we have sufficient functional information, we subdivide superfamily members into subgroups using sequence information, and lastly into families, sets of enzymes known to catalyze the same reaction using the same mechanistic strategy. Browsing and searching options in the SFLD provide access to all of these levels. The SFLD offers manually curated as well as automatically classified superfamily sets, both accompanied by search and download options for all hierarchical levels. Additional information includes multiple sequence alignments, tab-separated files of functional and other attributes, and sequence similarity networks. The latter provide a new and intuitively powerful way to visualize functional trends mapped to the context of sequence similarity.

Pythoscape: a framework for generation of large protein similarity networks.

Pythoscape is a framework implemented in Python for processing large protein similarity networks for visualization in other software packages. Protein similarity networks are graphical representations of sequence, structural and other similarities among proteins for which pairwise all-by-all similarity connections have been calculated. Mapping of biological and other information to network nodes or edges enables hypothesis creation about sequence-structure-function relationships across sets of related proteins. Pythoscape provides several options to calculate pairwise similarities for input sequences or structures, applies filters to network edges and defines sets of similar nodes and their associated data as single nodes (termed representative nodes) for compression of network information and output data or formatted files for visualization.

The evolution of function in strictosidine synthase-like proteins.

The exponential growth of sequence data provides abundant information for the discovery of new enzyme reactions. Correctly annotating the functions of highly diverse proteins can be difficult, however, hindering use of this information. Global analysis of large superfamilies of related proteins is a powerful strategy for understanding the evolution of reactions by identifying catalytic commonalities and differences in reaction and substrate specificity, even when only a few members have been biochemically or structurally characterized. A comparison of >2500 sequences sharing the six-bladed ß-propeller fold establishes sequence, structural, and functional links among the three subgroups of the functionally diverse N6P superfamily: the arylesterase-like and senescence marker protein-30/gluconolactonase/luciferin-regenerating enzyme-like (SGL) subgroups, representing enzymes that catalyze lactonase and related hydrolytic reactions, and the so-called strictosidine synthase-like (SSL) subgroup. Metal-coordinating residues were identified as broadly conserved in the active sites of all three subgroups except for a few proteins from the SSL subgroup, which have been experimentally determined to catalyze the quite different strictosidine synthase (SS) reaction, a metal-independent condensation reaction. Despite these differences, comparison of conserved catalytic features of the arylesterase-like and SGL enzymes with the SSs identified similar structural and mechanistic attributes between the hydrolytic reactions catalyzed by the former and the condensation reaction catalyzed by SS. The results also suggest that despite their annotations, the great majority of these >500 SSL sequences do not catalyze the SS reaction; rather, they likely catalyze hydrolytic reactions typical of the other two subgroups instead. This prediction was confirmed experimentally for one of these proteins.

Charge asymmetries in hydration of polar solutes.

We study the solvation of polar molecules in water. The center of water's dipole moment is offset from its steric center. In common water models, the Lennard-Jones center is closer to the negatively charged oxygen than to the positively charged hydrogens. This asymmetry of water's charge sites leads to different hydration free energies of positive versus negative ions of the same size. Here, we explore these hydration effects for some hypothetical neutral solutes, and two real solutes, with molecular dynamics simulations using several different water models. We find that, like ions, polar solutes are solvated differently in water depending on the sign of the partial charges. Solutes having a large negative charge balancing diffuse positive charges are preferentially solvated relative to those having a large positive charge balancing diffuse negative charges. Asymmetries in hydration free energies can be as large as 10 kcal/mol for neutral benzene-sized solutes. These asymmetries are mainly enthalpic, arising primarily from the first solvation shell water structure. Such effects are not readily captured by implicit solvent models, which respond symmetrically with respect to charge.