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Lukasz Jaroszewski

Publications and source records attributed to Lukasz Jaroszewski.

At least 55 records · Page 3Linked to original sources
PubMed2004

Integrated web service for improving alignment quality based on segments comparison.

BACKGROUND: Defining blocks forming the global protein structure on the basis of local structural regularity is a very fruitful idea, extensively used in description, and prediction of structure from only sequence information. Over many years the secondary structure elements were used as available building blocks with great success. Specially prepared sets of possible structural motifs can be used to describe similarity between very distant, non-homologous proteins. The reason for utilizing the structural information in the description of proteins is straightforward. Structural comparison is able to detect approximately twice as many distant relationships as sequence comparison at the same error rate. RESULTS: Here we provide a new fragment library for Local Structure Segment (LSS) prediction called FRAGlib which is integrated with a previously described segment alignment algorithm SEA. A joined FRAGlib/SEA server provides easy access to both algorithms, allowing a one stop alignment service using a novel approach to protein sequence alignment based on a network matching approach. The FRAGlib used as secondary structure prediction achieves only 73% accuracy in Q3 measure, but when combined with the SEA alignment, it achieves a significant improvement in pairwise sequence alignment quality, as compared to previous SEA implementation and other public alignment algorithms. The FRAGlib algorithm takes approximately 2 min. to search over FRAGlib database for a typical query protein with 500 residues. The SEA service align two typical proteins within circa approximately 5 min. All supplementary materials (detailed results of all the benchmarks, the list of test proteins and the whole fragments library) are available for download on-line at http://ffas.ljcrf.edu/darman/results/. CONCLUSIONS: The joined FRAGlib/SEA server will be a valuable tool both for molecular biologists working on protein sequence analysis and for bioinformaticians developing computational methods of structure prediction and alignment of proteins.

Computational Biology↗
PubMed2004

The importance of alignment accuracy for molecular replacement.

Many crystallographic protein structures are being determined using molecular replacement (MR), a model-based phasing method that has become increasingly important with the steady growth of the PDB. While there are several highly automated software packages for MR, the methods for preparing optimal search models for MR are relatively unexplored. Recent advances in sequence-comparison methods allow the detection of more distantly related homologs and more accurate alignment of their sequences. It was investigated whether simple homology models (without modeling of unaligned regions) based on alignments from these improved methods are able to increase the potential of MR. 27 crystal structures were determined using a highly parallelized MR pipeline that facilitates all steps including homology detection, model preparation, MR searches, automated refinement and rebuilding. Several types of search models prepared with standard sequence-sequence alignment (BLAST) and more accurate profile-sequence and profile-profile methods (PSI-BLAST, FFAS) were compared in MR trials. The analysis shows that models based on more accurate alignments have a higher success rate in cases where the unknown structure and the search model share less than 35% sequence identity. It is concluded that by using different types of simple models based on accurate alignments, the success rate of MR can be significantly increased.

Bacterial Proteins↗
PubMed2004

The interplay of fold recognition and experimental structure determination in structural genomics.

Achieving the goals of structural genomics initiatives depends on the outcomes of two groups of factors: the number and distribution of experimentally determined protein structures, and our ability to assign novel proteins to known structures (fold recognition) and use them to build models (modeling). The quality of the tools used for fold recognition defines the scope of experimental effort - the more distant the templates that can be recognized, the smaller the number of proteins that have to be solved. Recent improvements in fold recognition may have suggested that the goals of structural genomics initiatives are getting closer. However, problems that surfaced during the first few years of active work have put many of the early estimates in doubt and new ones are still slow in coming.

Animals↗
PubMed2003

Domain analysis of the tubulin cofactor system: a model for tubulin folding and dimerization.

BACKGROUND: The correct folding and dimerization of tubulins, before their addition to the microtubular structure, needs a group of conserved proteins called cofactors A to E. The biochemical analysis of cofactors gave an insight to their general functions, however not much is known about the domain structure and detailed, molecular function of these proteins. RESULTS: Combining modelling and fold prediction tools, we present 3D models of all cofactors, including several previously unannotated domains of cofactors B-E. Apart from the new HEAT and Armadillo domains in cofactor D and an unusual spectrin-like domain in cofactor C, we have identified a new subfamily of ubiquitin-like domains in cofactors B and E. Together, these observations provide a reliable, molecular level model of cofactor complex. CONCLUSION: Distant homology searches allowed the identification of unknown regions of cofactors as self-reliant domains and allow us to present a detailed hypothesis of how a cofactor complex performs its function.

Amino Acid Sequence↗
PubMed2003

A segment alignment approach to protein comparison.

MOTIVATION: Local structure segments (LSSs) are small structural units shared by unrelated proteins. They are extensively used in protein structure comparison, and predicted LSSs (PLSSs) are used very successfully in ab initio folding simulations. However, predicted or real LSSs are rarely exploited by protein sequence comparison programs that are based on position-by-position alignments. RESULTS: We developed a SEgment Alignment algorithm (SEA) to compare proteins described as a collection of predicted local structure segments (PLSSs), which is equivalent to an unweighted graph (network). Any specific structure, real or predicted corresponds to a specific path in this network. SEA then uses a network matching approach to find two most similar paths in networks representing two proteins. SEA explores the uncertainty and diversity of predicted local structure information to search for a globally optimal solution. It simultaneously solves two related problems: the alignment of two proteins and the local structure prediction for each of them. On a benchmark of protein pairs with low sequence similarity, we show that application of the SEA algorithm improves alignment quality as compared to FFAS profile-profile alignment, and in some cases SEA alignments can match the structural alignments, a feat previously impossible for any sequence based alignment methods.

Algorithms↗