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Biomedical subjects

Lukasz Jaroszewski

Publications and source records attributed to Lukasz Jaroszewski.

62 records · Page 4Linked to original sources
PubMed2002

Tyrosine phosphorylation of VHR phosphatase by ZAP-70.

The ZAP-70 tyrosine kinase is a key component of the signaling machinery for the T cell antigen receptor (TCR). Whereas recruitment and activation of ZAP-70 are relatively well understood, the proteins phosphorylated by ZAP-70 are incompletely known. We report here that VHR, a Vaccinia virus VH1-related dual-specific protein phosphatase that inactivates the mitogen-activated kinases Erk2 and Jnk, is phosphorylated at Y138 by ZAP-70. Tyr138 phosphorylation was required for VHR to inhibit the Erk2-Elk-1 pathway and, conversely, the VHR(Y138F) mutant augmented TCR-induced Erk2 kinase and activation of the gene encoding interleukin 2. These results suggest that VHR is a target for ZAP-70 and tempers activation of the Erk2 pathway in a ZAP-70-controlled manner.

DNA-Binding Proteins↗
PubMed2002

Structural genomics of the Thermotoga maritima proteome implemented in a high-throughput structure determination pipeline.

Structural genomics is emerging as a principal approach to define protein structure-function relationships. To apply this approach on a genomic scale, novel methods and technologies must be developed to determine large numbers of structures. We describe the design and implementation of a high-throughput structural genomics pipeline and its application to the proteome of the thermophilic bacterium Thermotoga maritima. By using this pipeline, we successfully cloned and attempted expression of 1,376 of the predicted 1,877 genes (73%) and have identified crystallization conditions for 432 proteins, comprising 23% of the T. maritima proteome. Representative structures from TM0423 glycerol dehydrogenase and TM0449 thymidylate synthase-complementing protein are presented as examples of final outputs from the pipeline.

Cloning, Molecular↗
PubMed2002

Tolerating some redundancy significantly speeds up clustering of large protein databases.

MOTIVATION: Sequence clustering replaces groups of similar sequences in a database with single representatives. Clustering large protein databases like the NCBI Non-Redundant database (NR) using even the best currently available clustering algorithms is very time-consuming and only practical at relatively high sequence identity thresholds. Our previous program, CD-HI, clustered NR at 90% identity in approximately 1 h and at 75% identity in approximately 1 day on a 1 GHz Linux PC (Li et al., Bioinformatics, 17, 282, 2001); however even faster clustering speed is needed because the size of protein databases are rapidly growing and many applications desire a lower attainable thresholds. RESULTS: For our previous algorithm (CD-HI), we have employed short-word filters to speed up the clustering. In this paper, we show that tolerating some redundancy makes for more efficient use of these short-word filters and increases the program's speed 100 times. Our new program implements this technique and clusters NR at 70% identity within 2 h, and at 50% identity in approximately 5 days. Although some redundancy is present after clustering, our new program's results only differ from our previous program's by less than 0.4%.

Algorithms↗
PubMed2002

Sequence clustering strategies improve remote homology recognitions while reducing search times.

Sequence databases are rapidly growing, thereby increasing the coverage of protein sequence space, but this coverage is uneven because most sequencing efforts have concentrated on a small number of organisms. The resulting granularity of sequence space creates many problems for profile-based sequence comparison programs. In this paper, we suggest several strategies that address these problems, and at the same time speed up the searches for homologous proteins and improve the ability of profile methods to recognize distant homologies. One of our strategies combines database clustering, which removes highly redundant sequence, and a two-step PSI-BLAST (PDB-BLAST), which separates sequence spaces of profile composition and space of homology searching. The combination of these strategies improves distant homology recognitions by more than 100%, while using only 10% of the CPU time of the standard PSI-BLAST search. Another method, intermediate profile searches, allows for the exploration of additional search directions that are normally dominated by large protein sub-families within very diverse families. All methods are evaluated with a large fold-recognition benchmark.

Amino Acid Motifs↗
PubMed2002

In search for more accurate alignments in the twilight zone.

A major bottleneck in comparative modeling is the alignment quality; this is especially true for proteins whose distant relationships could be reliably recognized only by recent advances in fold recognition. The best algorithms excel in recognizing distant homologs but often produce incorrect alignments for over 50% of protein pairs in large fold-prediction benchmarks. The alignments obtained by sequence-sequence or sequence-structure matching algorithms differ significantly from the structural alignments. To study this problem, we developed a simplified method to explicitly enumerate all possible alignments for a pair of proteins. This allowed us to estimate the number of significantly different alignments for a given scoring method that score better than the structural alignment. Using several examples of distantly related proteins, we show that for standard sequence-sequence alignment methods, the number of significantly different alignments is usually large, often about 10(10) alternatives. This distance decreases when the alignment method is improved, but the number is still too large for the brute force enumeration approach. More effective strategies were needed, so we evaluated and compared two well-known approaches for searching the space of suboptimal alignments. We combined their best features and produced a hybrid method, which yielded alignments that surpassed the original alignments for about 50% of protein pairs with minimal computational effort.

Algorithms↗
PubMed2001

Inhibition of T cell antigen receptor signaling by VHR-related MKPX (VHX), a new dual specificity phosphatase related to VH1 related (VHR).

A cDNA encoding a novel, human, dual-specific protein phosphatase was identified in the Incyte data base. The open reading frame predicted a protein of 184 amino acids related to the Vaccinia virus VH1 and human VH1-related (VHR) phosphatases. Expression VHR-related MKPX (VHX) was highest in thymus, but also detectable in monocytes and lymphocytes. A VHX-specific antiserum detected a protein with an apparent molecular mass of 19 kDa in many cells, including T lymphocytes and monocytes. VHX expression was not induced by T cell activation, but decreased somewhat at later time points. In vitro, VHX dephosphorylated the Erk2 mitogen-activated protein kinase with faster kinetics than did VHR, which is thought to be specific for Erk1 and 2. When expressed in Jurkat T cells, VHX had the capacity to suppress T cell antigen receptor-induced activation of Erk2 and of an NFAT/AP-1 luciferase reporter, but not an NF-kappaB reporter. Thus, VHX is a new member of the VH1/VHR group of small dual-specific phosphatases that act in mitogen-activated protein kinase signaling pathways.

Amino Acid Sequence↗