Functional analysis of the distal region of the third intracellular loop of PROKR2.

Mutations in the G-protein-coupled receptor PROKR2 have been identified in patients with idiopathic hypogonadotropic hypogonadism (IHH) and Kallmann syndrome (KS) manifesting with delayed puberty and infertility. Recently, the homozygous mutation V274D was identified in a man displaying KS with an apparent reversal of hypogonadism. The affected amino acid, valine 274, is located at the junction region of the third intracellular loop (IL3) and the sixth transmembrane domain (TM6). In this study, we first studied the effect of V274D and related mutations (V274A, V274T, and V274R) on the signaling activity and cell surface expression of PROKR2. Our data indicate that a charged amino acid substitution at residue 274 of PROKR2 results in low cell surface expression and loss-of-function. Furthermore, we studied the effects of two clusters of basic amino acids located at the proximal region of Val274 on the cell surface expression and function of PROKR2. The deletion of RRK (270-272) resulted in undetectable cell surface expression, whereas RKR (264-266)-deleted PROKR2 was expressed normally on the cell surface but showed loss-of-function due to a deficiency in G-protein coupling. Our data indicate that the distal region of the IL3 of PROKR2 may differentially influence receptor trafficking and G-protein coupling.

Expression and characterization of a variant of TACI (CRD2-shortTACIFc) in Pichia pastoris.

TACI is a member of the tumor necrosis factor receptor superfamily and serves as a key regulator of B cell function. The extracellular domain of a typical TNFR contains multiple copies of CRD, which bind in the monomermonomer interfaces of a trimeric ligand. TACI binds to two ligands, APRIL and BAFF, with high affinity and contains two CRD in its extracellular regions, while BCMA and BR3, contain a single or partial CRD for binding the two ligands. However, TACI can be classified as a single CRD receptor because the amino-terminal CRD1 doesn't contribute to ligand binding. To obtain a new variant of TACI possessing higher affinities for binding, we fused a repeat sequence of CRD2 to the N-terminus of the short form of TACI. The new APRIL antagonist peptide, CRD2-shortTACI-Fc, was designed based on the modeling 3-D complex structure of TACI and APRIL. As expected, the purified recombinant CRD2-shortTACI-Fc fusion protein could bind to APRIL in vitro and demonstrated dose-dependent inhibition of APRIL-induced proliferative activity in Raji cells. We found that CRD2-shortTACI-Fc, has a higher affinity for binding to ligands than short-TACI-Fc, which contains a single CRD2.

Protein sumoylation sites prediction based on two-stage feature selection.

Protein sumoylation is one of the most important post-translational modifications. Accurate prediction of sumoylation sites is very useful for the analysis of proteome. Though the putative motif Psi K XE can be used, optimization of prediction models still remains a challenge. In this study, we developed a prediction system based on feature selection strategy. A total of 1,272 peptides with 14 residues from SUMOsp (Xue et al. [8] Nucleic Acids Res 34:W254-W257, 2006) were investigated in this study, including 212 substrates and 1,060 non-substrates. Among the substrates, only 162 substrates comply to the motif Psi K XE. First, 1,272 substrates were divided into training set and test set. All the substrates were encoded into feature vectors by hundreds of amino acid properties collected by Amino Acid Index Database (AAIndex, http://www.genome.jp/aaindex ). Then, mRMR (minimum redundancy-maximum relevance) method was applied to extract the most informative features. Finally, Nearest Neighbor Algorithm (NNA) was used to produce the prediction models. Tested by Leave-one-out (LOO) cross-validation, the optimal prediction model reaches the accuracy of 84.4% for the training set and 76.4% for the test set. Especially, 180 substrates were correctly predicted, which was 18 more than using the motif Psi K XE. The final selected features indicate that amino acid residues with two-residue downstream and one-residue upstream of the sumoylation sites play the most important role in determining the occurrence of sumoylation. Based on the feature selection strategy, our prediction system can not only be used for high throughput prediction of sumoylation sites but also as a tool to investigate the mechanism of sumoylation.

[A method for delineation of domains in proteins based on refolding free energy--application to continuous and discontinuous domains].

Domain is a protein architecture in a subunit. It might be defined as a basic unit for structure, function, folding, evolution and design. Different combinations of domains lead to the formation of various tertiary structures with various functions for proteins. The delineation of domains for a protein is important both conceptually and practically, which remains up to date a challenging and unsolved problem. Based on the above definition, a method was previously proposed based on refolding free energy to define continuous domains in proteins. By constructing a residue-residue contact matrix, using correspondence analysis, and then selecting optimal partition function of a protein according to refolding free energy and some empirical scoring functions, a new computer program, PDOM, was developed, which was applicable to both continuous and discontinuous domains. When compared with the manual partition results reported by crystallographers, PDOM has achieved an accuracy of 76% on a test data set including 55 protein structures frequently used. The differences in 13 proteins between PDOM, literature as well as SCOP have been discussed extensively.

Delineation of Continuous Domains in Proteins by Differences of Free Energy.

Domain is a protein architecture under proteins' tertiary structure,which can be identified in most of proteins. Different combinations of domains lead to the formation of diverse tertiary structures with diverse function for proteins. The delineation of domains for a protein is important not only conceptually but also practically. Unfortunately, up to now there is not an ideal means to achieve that. This paper proposes a method for domain delineation based on the maximum refolding free energy. The criteria are more or less objective. By using this method, 50 proteins are analyzed. The boundaries for most proteins agree with the data reported in literature. There are a few examples that seem more reasonable, although they are not identical with those in literature.