COMPUTER ANALYSIS OF SEQUENCES FROM MICROORGANISMS

微生物序列的计算机分析

• 批准号: 6111061
• 负责人: JOHN C. WOOTTON
• 金额: --
• 依托单位: NATIONAL LIBRARY OF MEDICINE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/6111061
• 关键词: Archaea; DNA binding protein; Escherichia coli; bacterial DNA; bacterial proteins; biochemical evolution; computer assisted sequence analysis; computer data analysis; computer system design /evaluation; microorganism metabolism; photosynthetic bacteria; protein sequence; protein structure function

Protein sequences deduced from gene sequences of diverse bacteria land archaebacteria, and also, increasingly, from eukaryotic model organisms, are yielding a wealth of new knowledge on protein functions, interactions and evolution. Novel findings, that emerged initially from computational analysis of sequences and sequence databases, have been studied in collaboration with experimental laboratories by concerted methods including directed mutagenesis and spectroscopic/enzymological analyses. Computational strategies are being developed to recognize some of the functional amino acid sequence patterns involved, many of which are subtle and variable. A. Proteins and protein complexes involved in DNA binding, mutagenesis and repair. For patterns of wall-established DNA binding regions, new methods for evaluation of pattern discriminators are being developed and applied to more novel patterns. Low- complexity sequences are frequent in components of multisubunit DNA-binding complexes and require analysis and filtering before database searches. Methods of automated local multiple alignment by iterative sampling are included and evaluated based on test sets of various types of DNA-binding motifs. B. Sequence families in complex bacteria including pathogens. The rapidly growing body of new sequences from pathogenic bacteria, and widely diverse prokaryotes such as multicellular or differentiating bacteria, cyanobacteria and archaebacteria, were investigated by a range of computational analyses. More than 50 percent of the classifiable protein sequences did not have counterparts in E. coli and other well-studied bacteria, and many of these had eukaryotic homologs. Examples of low-complexity segments and multiple repeats are emerging with increasing frequency, especially in proteins involved in surface interactions, for example with the immune system, many of which evolve rapidly. In other cases, novel chemical and metabolic functions have been found. Genome sequences and protein structural studies from matabolically and morphogenetically diverse bacteria and other model organisms continue to provide a rich and cost-effective source of new discoveries on the molecular functions and evolution of proteins including aspects related to human diseases.

从不同的基因序列推断出蛋白质序列