No abstract

PSP94 (prostate secretory protein of 94 amino acids) was regarded as a possible prostate cancer marker, however, it has been controversial. All prior studies were designed to test the free form in serum using antibodies to PSP94. Results presented here demonstrate that PSP94 exists in prostate cancer patients in two forms, free and bound, and that the majority is present as serum bound complexes. This result was demonstrated by using both native and SDS-PAGE analyses of serum proteins from prostate cancer patients. Chromatographic separation of serum total proteins by a molecular sieve column generated two peaks (peak I and II), which were reactive with rabbit antiserum to human PSP94 in Western blot experiments. Peak I was eluted before the IgG fraction at a molecular weight larger than 150 kDa, and peak II appeared after serum albumin ( approximately 67 kDa) was eluted. By using a biotinylated PSP94 as an indicator of the free form of PSP94, we demonstrate that peak I contains serum PSP94-bound complexes and peak II is likely the free form of serum PSP94. Since the molecular weight of serum PSP94-bound complexes is close to IgG during molecular sieve separation, serum PSP94 complexes were further purified through two rounds of protein A column separation, followed by DEAE-ion exchange column chromatography. In vitro dissociation tests of the purified PSP94-bound complexes showed that the binding of serum PSP94-complexes is probably via disulfide bonds and is chemically stable. The results presented here indicate that serum PSP94-bound complexes must be considered in evaluating the clinical utility of PSP94 as a prostate cancer marker.

Prostate secretory protein of 94 amino acids (PSP94) has shown the potential to be a diagnostic biomarker and a therapeutic agent for prostate cancer. Primates have been the main animal models for studying the biology of this molecule. We have cloned and analyzed the cDNA and promoter region of PSP94 from baboon (Papio anubis). Sequence divergence among baboon, monkey, pig, and human, in both the exons and 5'-flanking region indicates rapid evolution of the PSP94 gene. There are conserved steroid hormone response elements (SHRE) in the promoter region of all three primate species. Multiple, alternative transcripts starting near these SHREs and upstream to the TATA box were identified by reverse transcriptase polymerase chain reaction (RT-PCR) and rapid amplification of 5'-cDNA ends (5' RACE) in primate prostatic tissues. This differential transcription initiation may be linked to androgen regulation of PSP94 gene expression. PSP94 transcripts were detected by RT-PCR in a wide variety of mucus-secreting tissues. However, the alternative transcripts were found only in the prostate. The distribution of the PSP94 protein in baboon secretory tissues was also examined by Western blot analysis using a polyclonal antibody against the human homolog. A positive immunoreactive band was detected, but it was weak, due probably to epitope divergence between the two species. In all young, healthy primate animals tested, the level of immunoreactive PSP94 in prostate tissues was lower than expected. In addition, RT-PCR combined with Southern blot analysis on prostate tissues in these animals failed to detect the PSP57 mRNA produced by alternative splicing of PSP94 primary transcript. These observations can be explained by the sexual immaturity and incomplete prostate development in these young primates. This explanation was supported by histological examination of their prostate during PSP94 immunohistochemistry.

PSP94 is a potential biomarker for evaluating patients with prostate carcinoma. We have systematically studied the epitope structure of PSP94 by using a polyclonal antibody against human PSP94. Results of peptide mapping and ELISA tests of dose response to rabbit antiserum against human PSP94 protein showed that only the N-terminal peptides (N30 and M23) are immunoreactive while all the synthetic peptides (C28, C10) located closer to the C-terminus are completely devoid of antigenic activity with the polyclonal antibody. These results were confirmed by analysis of reciprocal competitive binding of PSP94 polyclonal antibody by the N-terminal peptides (N30 and M23) v. either recombinant GST-PSP94 fusion protein, purified recombinant PSP94, or natural PSP94 protein. To further delineate the antigenic activity of the N- and C-termini, we have also expressed N- and C-terminal half of the whole PSP94 (each 47 peptides) using the E. coli GST expression system. The recombinant N47/C47 peptides were released by thrombin cleavage from the GST fusion protein and characterized by Western blotting experiments. Dose response of the recombinant GST-PSP-N47 and -C47 peptides to PSP94 polyclonal antibody showed differential binding activities. Competitive binding of these recombinant N47/C47 proteins against the GST-PSP94 protein demonstrates that the polyclonal antibody has a higher affinity for the N47 peptide than the C47 peptide. Based on the immunological studies of both synthetic peptides and recombinant PSP94- N/C terminal proteins, we propose an epitope structure of human PSP94 with an immuno-dominant N-terminus and an immuno-recessive C-terminus.

Determining the functional conformation of a protein from its amino acid sequence remains a central problem in computational biology. In this paper, we establish the mathematical optimal model of protein folding problem (PFP) on two-dimensional space based on the minimal energy principle. A novel hybrid of elastic net algorithm and local search method (ENLS) is applied successfully to simulations of protein folding on two-dimensional hydrophobic-polar (HP) lattice model. Eight HP benchmark instances with up to 64 amino acids are tested to verify the effectiveness of proposed approach and model. In several cases, the ENLS method finds new lower energy states. The numerical results show that it is drastically superior to other methods in finding the ground state of a protein.

BackgroundPredicting protein structure from amino acid sequence is a prominent problem in computational biology. The long range interactions (or non-local interactions) are known as the main source of complexity for protein folding and dynamics and play the dominant role in the compact architecture. Some simple but exact model, such as HP model, captures the pain point for this difficult problem and has important implications to understand the mapping between protein sequence and structure.ResultsIn this paper, we formulate the biological problem into optimization model to study the hydrophobic-hydrophilic model on 3D square lattice. This is a combinatorial optimization problem and known as NP-hard. Particle swarm optimization is utilized as the heuristic framework to solve the hard problem. To avoid premature in computation, we incorporated the Tabu search strategy. In addition, a pulling strategy was designed to accelerate the convergence of algorithm based on the characteristic of native protein structure. Together a novel hybrid method combining particle swarm optimization, Tabu strategy, and pulling strategy can fold the amino acid sequences on 3D square lattice efficiently. Promising results are reported in several examples by comparing with existing methods. This allows us to use this tool to study the protein stability upon amino acid mutation on 3D lattice. In particular, we evaluate the effect of single amino acid mutation and double amino acids mutation via 3D HP lattice model and some useful insights are derived.ConclusionWe propose a novel hybrid method to combine several heuristic strategies to study HP model on 3D lattice. The results indicate that our hybrid method can predict protein structure more accurately and efficiently. Furthermore, it serves as a useful tools to probe the protein stability on 3D lattice and provides some biological insights.

One of the most prominent problems in computational biology is to predict the natural conformation of a protein from its amino acid sequence. This paper focuses on the three-dimensional hydrophobic-polar (HP) lattice model of this problem. The modified elastic net (EN) algorithm is applied to solve this nonlinear programming hard problem. The lattice partition strategy and two local search methods (LS(1) and LS(2)) are proposed to improve the performance of the modified EN algorithm. The computation and analysis of 12 HP standard benchmark instances are also involved in this paper. The results indicate that the hybrid of modified EN algorithm, lattice partition strategy, and local search methods has a greater tendency to form a globular state than genetic algorithm does. The results of noncompact model are more natural in comparison with that of compact model.

No abstract