Large-scale prediction of function shift in protein families with a focus on enzymatic function

Protein function shift can be predicted from sequence comparisons, either using positive selection signals or evolutionary rate estimation. None of the methods have been validated on large datasets, however. Here we investigate existing and novel methods for protein function shift prediction, and benchmark the accuracy against a large dataset of proteins with known enzymatic functions. Function change was predicted between subfamilies by identifying two kinds of sites in a multiple sequence alignment: Conservation-Shifting Sites (CSS), which are conserved in two subfamilies using two different amino acid types, and Rate-Shifting Sites (RSS), which have different evolutionary rates in two subfamilies. CSS were predicted by a new entropy-based method, and RSS using the Rate-Shift program. In principle, the more CSS and RSS between two subfamilies, the more likely a function shift between them. A test dataset was built by extracting subfamilies from Pfam with different EC numbers that belong to the same domain family. Subfamilies were generated automatically using a phylogenetic tree-based program, BETE. The dataset comprised 997 subfamily pairs with four or more members per subfamily. We observed a significant increase in CSS and RSS for subfamily comparisons with different EC numbers compared to cases with same EC numbers. The discrimination was better using RSS than CSS, and was more pronounced for larger families. Combining RSS and CSS by discriminant analysis improved classification accuracy to 71%. The method was applied to the Pfam database and the results are available at http://FunShift.cgb.ki.se. A closer examination of some superfamily comparisons showed that single EC numbers sometimes embody distinct functional classes. Hence, the measured accuracy of function shift is underestimated.     

Force calculations in automated docking: enzyme-substrate interactions in Fusarium oxysporum Cel7B

AutoDock is a small-molecule docking program that uses an energy function to score docked ligands. Here AutoDock's grid-based method for energy evaluation was exploited to evaluate the force exerted by Fusarium oxysporum Cel7B on the atoms of docked cellooligosaccharides and a thiooligosaccharide substrate analog. Coupled with the interaction energies evaluated for each docked ligand, these forces give insight into the dynamics of the ligand in the active site, and help to elucidate the relative importance of specific enzyme-substrate interactions in stabilizing the substrate transition-state conformation. The processive force on the docked substrate in the F. oxysporum Cel7B active site is less than half of that on the docked substrate in the Hypocrea jecorina Cel7A active site. Hydrogen bonding interactions of the enzyme with the C2 hydroxyl group of the glucosyl residue in subsite -2 and with the C3 hydroxyl group of the glucosyl residue in subsite +1 are the most significant in stabilizing the distorted14B transition-state conformation of the glucosyl residue in subsite -1. The force calculations also help to elucidate the mechanism that prevents the active site from fouling.     

Candidate nsSNPs that can affect the functions and interactions of cell cycle proteins

Nonsynonymous single nucleotide polymorphisms (nsSNPs) alter the encoded amino acid sequence, and are thus likely to affect the function of the proteins, and represent potential disease-modifiers. There is an enormous number of nsSNPs in the human population, and the major challenge lies in distinguishing the functionally significant and potentially disease-related ones from the rest. In this study, we analyzed the genetic variations that can alter the functions and the interactions of a group of cell cycle proteins (n = 60) and the proteins interacting with them (n = 26) using computational tools. As a result, we extracted 249 nsSNPs from 77 cell cycle proteins and their interaction partners from public SNP databases. Only 31 (12.4%) of the nsSNPs were validated. The majority (64.5%) of the validated SNPs were rare (minor allele frequencies < 5%). Evolutionary conservation analysis using the SIFT tool suggested that 16.1% of the validated nsSNPs may disrupt the protein function. In addition, 58% of the validated nsSNPs were located in functional protein domains/motifs, which together with the evolutionary conservation analysis enabled us to infer possible biological consequences of the nsSNPs in our set. Our study strongly suggests the presence of naturally occurring genetic variations in the cell cycle proteins that may affect their interactions and functions with possible roles in complex human diseases, such as cancer.     

Sequence patterns associated with disordered regions in proteins

The relationship between amino acid sequence and intrinsic disorder in proteins is investigated. Two databases, one of disordered proteins and the other of globular proteins, are analyzed and compared in order to extract simple sequence patterns of a few amino acids or amino acid properties that characterize disordered segments. It is found that a number of reliable, nonrandom associations exists. In particular, two types of patterns appear to be recurrent: a proline-rich pattern and a (positively or negatively) charged pattern. These results indicate that local sequence information can determine disordered regions in proteins. The derived patterns provide some insights into the physical reasons for disordered structures. They should also be helpful in improving currently available prediction methods.     

Structures of vertebrate hyaluronidases and their unique enzymatic mechanism of hydrolysis

Human hyaluronidases (Hyals) are a group of five endo-beta-acetyl-hexosaminidase enzymes, Hyal-1, -2, -3, -4, and PH-20, which degrade hyaluronan using a hydrolytic mechanism of action. Catalysis by these Hyals has been shown to follow a double-displacement scheme. This involves a single Glu residue within the enzyme, the only catalytic residue, as the proton donor (acid). Also involved is a carbonyl group of the hyaluronan (HA) N-acetyl-D-glucosamine as a unique type of nucleophile. Thus the substrate participates in the mechanism of action of its own catalysis. An oxocarbonium ion transition state is postulated, but there is no formation of a covalent enzyme-glycan intermediate, as found in most such reactions. The major domain is catalytic and has a distorted (beta/alpha)8 triose phosphate isomerase (TIM) barrel fold. The C-terminal domain is separated by a peptide linker. Each Hyal has a different C-terminal sequence and structure, the function of which is unknown. These unique C-termini may participate in the additional function(s) associated with these multifunctional enzymes.     

Anchor profiles of HLA-specific peptides: analysis by a novel affinity scoring method and experimental validation

The study of intermolecular interactions is a fundamental research subject in biology. Here we report on the development of a quantitative structure-based affinity scoring method for peptide-protein complexes, named PepScope. The method operates on the basis of a highly specific force field function (CHARMM) that is applied to all-atom structural representations of peptide-receptor complexes. Peptide side-chain contributions to total affinity are scored after detailed rotameric sampling followed by controlled energy refinement. A de novo approach to estimate dehydration energies was developed, based on the simulation of individual amino acids in a solvent box filled with explicit water molecules. Transferability of the method was demonstrated by its application to the hydrophobic HLA-A2 and -A24 receptors, the polar HLA-A1, and the sterically ruled HLA-B7 receptor. A combined theoretical and experimental study on 39 anchor substitutions in FxSKQYMTx/HLA-A2 and -A24 complexes indicated a prediction accuracy of about two thirds of a log-unit in Kd. Analysis of free energy contributions identified a great role of desolvation and conformational strain effects in establishing a given specificity profile. Interestingly, the method rightly predicted that most anchor profiles are less specific than so far assumed. This suggests that many potential T-cell epitopes could be missed with current prediction methods. The results presented in this work may therefore significantly affect T-cell epitope discovery programs applied in the field of peptide vaccine development.     

A pharmacophore-based evolutionary approach for screening selective estrogen receptor modulators

We developed a pharmacophore-based evolutionary approach for virtual screening. This tool, termed the Generic Evolutionary Method for molecular DOCKing (GEMDOCK), combines an evolutionary approach with a new pharmacophore-based scoring function. The former integrates discrete and continuous global search strategies with local search strategies to expedite convergence. The latter, integrating an empirical-based energy function and pharmacological preferences (binding-site pharmacological interactions and ligand preferences), simultaneously serves as the scoring function for both molecular docking and postdocking analyses to improve screening accuracy. We apply pharmacological interaction preferences to select the ligands that form pharmacological interactions with target proteins, and use the ligand preferences to eliminate the ligands that violate the electrostatic or hydrophilic constraints. We assessed the accuracy of our approach using human estrogen receptor (ER) and a ligand database from the comparative studies of Bissantz et al. (J Med Chem 2000;43:4759-4767). Using GEMDOCK, the average goodness-of-hit (GH) score was 0.83 and the average false-positive rate was 0.13% for ER antagonists, and the average GH score was 0.48 and the average false-positive rate was 0.75% for ER agonists. The performance of GEMDOCK was superior to competing methods such as GOLD and DOCK. We found that our pharmacophore-based scoring function indeed was able to reduce the number of false positives; moreover, the resulting pharmacological interactions at the binding site, as well as ligand preferences, were important to the screening accuracy of our experiments. These results suggest that GEMDOCK constitutes a robust tool for virtual database screening.     

Structural characterization of proteins using residue environments

A primary challenge for structural genomics is the automated functional characterization of protein structures. We have developed a sequence-independent method called S-BLEST (Structure-Based Local Environment Search Tool) for the annotation of previously uncharacterized protein structures. S-BLEST encodes the local environment of an amino acid as a vector of structural property values. It has been applied to all amino acids in a nonredundant database of protein structures to generate a searchable structural resource. Given a query amino acid from an experimentally determined or modeled structure, S-BLEST quickly identifies similar amino acid environments using a K-nearest neighbor search. In addition, the method gives an estimation of the statistical significance of each result. We validated S-BLEST on X-ray crystal structures from the ASTRAL 40 nonredundant dataset. We then applied it to 86 crystallographically determined proteins in the protein data bank (PDB) with unknown function and with no significant sequence neighbors in the PDB. S-BLEST was able to associate 20 proteins with at least one local structural neighbor and identify the amino acid environments that are most similar between those neighbors.     

Pharmacokinetics of theanine enantiomers in rats

Theanine, first discovered in tea, is a chiral nonproteinic amino acid that has been reported to have cardiovascular, neurological, and oncological effects. It is being considered as a therapeutic/medicinal agent and additive in consumer products. The present study evaluated the pharmacokinetics of D-theanine, L-theanine, and D,L-theanine in plasma and urine using LC-ESI/MS in rats after oral (p.o.) and intraperitoneal (i.p.) administration. Oral administration data indicated that gut absorption of d-theanine was far less than that of L-theanine. However, after i.p. administration, plasma theanine concentrations of L- and D-theanine were similar. This indicated that D- and L-theanine may exhibit a competitive effect with respect to intestinal absorption. Regardless of the route of administration, p.o. or i.p., the presence of the other enantiomer always decreased theanine plasma concentrations, indicating D,L-theanine competition with respect to urinary reabsorption. Data on urinary concentrations of D-theanine suggested that the D-isomer may be eliminated with minimal metabolism. L-Theanine appeared to be preferentially reabsorbed and metabolized by the kidney while D-theanine was preferentially excreted. Clearly, the bioequivalencies of D,L-theanine and its enantiomers were found to be quite different from one another. Consequently, the efficacy of commercial theanine products containing D-theanine, L-theanine, or D,L-theanine may be quite different.     

Surprising Effects of Synaptic Excitation

Typically, excitatory synaptic coupling is thought of as an influence that accelerates and propagates firing in neuronal networks. This paper reviews recent results explaining how, contrary to these expectations, the presence of excitatory synaptic coupling can drastically slow oscillations in a network and how localized, sustained activity can arise in a network with purely excitatory coupling, without sustained inputs. These two effects stem from interactions of excitatory coupling with two different forms of intrinsic neuronal dynamics, and both serve to highlight the fact that the influence of synaptic coupling in a network depends strongly on the intrinsic properties of cells in the network.This work was partially supported by the National Science Foundation, under award DMS-0414023