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Abstract: Tracing the characters of very ancient proteins represents one of the biggest challenges in the study of origin of life. Although there are no primitive protein fossils remaining, the characters of very ancient proteins can be traced by molecular fossils embedded in modern proteins. In this paper, first the prior findings in this area are outlined and then a new strategy is proposed to address the intriguing issue. It is interesting to find that various molecular fossils and different protein datasets lead to similar conclusions on the features of very ancient proteins, which can be summarized as follows: (i) the architectures of very ancient proteins belong to the following folds: P-loop containing nucleoside triphosphate hydrolases (c.37), TIM beta/alpha-barrel (c.1), NAD(P)-binding Rossmann-fold domains (c.2), Ferredoxin-like (d.58), Flavodoxin-like (c.23) and Ribonuclease H-like motif (c.55); (ii) the functions of very ancient proteins are related to the metabolisms of purine, pyrimidine, porphyrin, chlorophyll and carbohydrates; (iii) a certain part of very ancient proteins need cofactors (such as ATP, NADH or NADPH) to work normally. [Copyright &y& Elsevier]

Abstract: A rapid method to screen and identify unknown bound proteins to specific nucleic acid probes anchored on ProteinChip array surfaces from crude biological samples has been developed in this paper. It was demonstrated with screening specific binding proteins from LPS-stimulated mouse 70Z/3 pre-B cell nuclear extracts by direct coupling of thioaptamer XBY-S2 to the pre-activated ProteinChip array surfaces. With pre-fractionation of crude nuclear extracts by ion exchange method, specific “on-chip” captured proteins have been obtained that were pure enough to do “on-chip” digestion and the subsequent identification of the “on-chip” bound proteins by microsequencing of the trypsin digested peptide fragments through tandem MS. Five mouse heterogeneous nuclear ribonucleoproteins (hnRNPs) A1, A2/B1, A3, A/B, and D0 were identified. To verify those bound hnRNPs, a novel thioaptamer/antibody sandwich assay provides highly sensitive and selective identification of proteins on ProteinChip arrays. [Copyright &y& Elsevier]

Abstract: Caveolin-1 (Cav-1) is emerging as the central protein controlling caveolae formation, caveolae trafficking, and cellular signalling. In particular, it is known that Cav-1 interacts and modulates the activity of several signalling proteins through the so-called caveolin scaffolding domain. In this paper, we used a bioinformatics approach to assess the validity of some long-standing structural features of Cav-1. We could confirm the existence of a membrane spanning region of Cav-1 and highlight an interesting pattern of palmitoylated cysteine residues explaining the structural features of the Cav-1 C-terminal region. Moreover, the scaffolding domain is predicted to have a different structure than previously reported. [Copyright &y& Elsevier]

Abstract: Functioning as an “address tag” or “zip code” that guides nascent proteins (newly synthesized proteins in the cytosol) to wherever they are needed, signal peptides (also called targeting signals or signal sequences) have become a crucial tool in finding new drugs or reprogramming cells for gene therapy. To effectively and timely use such a tool, however, the first important thing is to develop an automated method for quickly and accurately identifying the signal peptide for a given nascent protein. With the avalanche of new protein sequences generated in the post-genomic era, the challenge has become even more urgent and critical. In this paper, five statistical rulers were derived via performing a mutual information analysis. By combining these statistical rulers, a new prediction algorithm was established and high success prediction rates were observed. The new algorithm may play a complementary role to the existing algorithms in this area. It is anticipated that the mutual information approach introduced here may be very useful for studying many other sequence-coupling problems in molecular biology as well. [Copyright &y& Elsevier]

Abstract: ISG15 was the first ubiquitin-like modifier to be identified. However, the function of ISG15 modification has been an enigma for many years. At present, no data are available about the function of ISGylation for any target. In this paper, we report the identification of Ubc13, which forms a unique ubiquitin-conjugating enzyme (Ubc) complex with ubiquitin enzyme variant Mms2 and generates atypical Lys63-linked ubiquitin conjugates, as one of the targets of ISG15 modification. Furthermore, we identify Lys92 as the only ISG15 modification site in Ubc13, which is the first report about the ISG15 modification site. Using the “covalent affinity” purification assay, we found that unmodified Ubc13 can bind to the ubiquitin–agarose, whereas ISGylated Ubc13 cannot. This result indicates that ISGylation of Ubc13 disrupts its ability to form thioester bond with ubiquitin. [Copyright &y& Elsevier]

Abstract: Prediction of protein classification is both an important and a tempting topic in protein science. This is because of not only that the knowledge thus obtained can provide useful information about the overall structure of a query protein, but also that the practice itself can technically stimulate the development of novel predictors that may be straightforwardly applied to many other relevant areas. In this paper, a novel approach, the so-called “supervised fuzzy clustering approach” is introduced that is featured by utilizing the class label information during the training process. Based on such an approach, a set of “if-then” fuzzy rules for predicting the protein structural classes are extracted from a training dataset. It has been demonstrated through two different working datasets that the overall success prediction rates obtained by the supervised fuzzy clustering approach are all higher than those by the unsupervised fuzzy c-means introduced by the previous investigators [C.T. Zhang, K.C. Chou, G.M. Maggiora. Protein Eng. (1995) 8, 425–435]. It is anticipated that the current predictor may play an important complementary role to other existing predictors in this area to further strengthen the power in predicting the structural classes of proteins and their other characteristic attributes. [Copyright &y& Elsevier]

In this paper, a novel approach has been introduced to predict the disulfide-bonding state of cysteines in proteins by means of a linear discriminator based on their dipeptide composition. The prediction is performed with a newly enlarged dataset with 8114 cysteine-containing segments extracted from 1856 non-homologous proteins of well-resolved three-dimensional structures. The oxidation of cysteines exhibits obvious cooperativity: almost all cysteines in disulfide-bond-containing proteins are in the oxidized form. This cooperativity can be well described by protein’s dipeptide composition, based on which the prediction accuracy of the oxidation form of cysteines scores as high as 89.1% and 85.2%, when measured on cysteine and protein basis using the rigorous jack-knife procedure, respectively. The result demonstrates the applicability of this new relatively simple method and provides superior prediction performance compared with existing methods for the prediction of the oxidation states of cysteines in proteins. [Copyright &y& Elsevier]