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Subfamily specific conservation profiles for proteins based on n-gram patterns.

ABSTRACT: BACKGROUND:A new algorithm has been developed for generating conservation profiles that reflect the evolutionary history of the subfamily associated with a query sequence. It is based on n-gram patterns (NP{n,m}) which are sets of n residues and m wildcards in windows of size n+m. The generation of conservation profiles is treated as a signal-to-noise problem where the signal is the count of n-gram patterns in target sequences that are similar to the query sequence and the noise is the count over all target sequences. The signal is differentiated from the noise by applying singular value decomposition to sets of target sequences rank ordered by similarity with respect to the query. RESULTS:The new algorithm was used to construct 4,248 profiles from 120 randomly selected Pfam-A families. These were compared to profiles generated from multiple alignments using the consensus approach. The two profiles were similar whenever the subfamily associated with the query sequence was well represented in the multiple alignment. It was possible to construct subfamily specific conservation profiles using the new algorithm for subfamilies with as few as five members. The speed of the new algorithm was comparable to the multiple alignment approach. CONCLUSION:Subfamily specific conservation profiles can be generated by the new algorithm without aprioi knowledge of family relationships or domain architecture. This is useful when the subfamily contains multiple domains with different levels of representation in protein databases. It may also be applicable when the subfamily sample size is too small for the multiple alignment approach.

SUBMITTER: Vries JK

PROVIDER: S-EPMC2267698 | biostudies-literature | 2008 Jan

REPOSITORIES: biostudies-literature

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Subfamily specific conservation profiles for proteins based on n-gram patterns.

Vries John K JK Liu Xiong X

BMC bioinformatics 20080130

<h4>Background</h4>A new algorithm has been developed for generating conservation profiles that reflect the evolutionary history of the subfamily associated with a query sequence. It is based on n-gram patterns (NP{n,m}) which are sets of n residues and m wildcards in windows of size n+m. The generation of conservation profiles is treated as a signal-to-noise problem where the signal is the count of n-gram patterns in target sequences that are similar to the query sequence and the noise is the c ...[more]

PMID: 18234090

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Project description:BACKGROUND:Type III secretion systems (T3SSs) are central to the pathogenesis and specifically deliver their secreted substrates (type III secreted proteins, T3SPs) into host cells. Since T3SPs play a crucial role in pathogen-host interactions, identifying them is crucial to our understanding of the pathogenic mechanisms of T3SSs. This study reports a novel and effective method for identifying the distinctive residues which are conserved different from other SPs for T3SPs prediction. Moreover, the importance of several sequence features was evaluated and further, a promising prediction model was constructed. RESULTS:Based on the conservation profiles constructed by a position-specific scoring matrix (PSSM), 52 distinctive residues were identified. To our knowledge, this is the first attempt to identify the distinct residues of T3SPs. Of the 52 distinct residues, the first 30 amino acid residues are all included, which is consistent with previous studies reporting that the secretion signal generally occurs within the first 30 residue positions. However, the remaining 22 positions span residues 30-100 were also proven by our method to contain important signal information for T3SP secretion because the translocation of many effectors also depends on the chaperone-binding residues that follow the secretion signal. For further feature optimisation and compression, permutation importance analysis was conducted to select 62 optimal sequence features. A prediction model across 16 species was developed using random forest to classify T3SPs and non-T3 SPs, with high receiver operating curve of 0.93 in the 10-fold cross validation and an accuracy of 94.29% for the test set. Moreover, when performing on a common independent dataset, the results demonstrate that our method outperforms all the others published to date. Finally, the novel, experimentally confirmed T3 effectors were used to further demonstrate the model's correct application. The model and all data used in this paper are freely available at http://cic.scu.edu.cn/bioinformatics/T3SPs.zip.

Project description:The monovalent anions formate, nitrite and hydrosulphide are main metabolites of bacterial respiration during anaerobic mixed-acid fermentation. When accumulated in the cytoplasm, these anions become cytotoxic. Membrane proteins that selectively transport these monovalent anions across the membrane have been identified and they belong to the family of Formate/Nitrite Transporters (FNTs). Individual members that selectively transport formate, nitrite and hydrosulphide have been investigated. Experimentally determined structures of FNTs indicate that they share the same hourglass helical fold with aquaporins and aquaglyceroporins and have two constriction regions, namely, cytoplasmic slit and central constriction. Members of FNTs are found in bacteria, archaea, fungi and protists. However, no FNT homolog has been identified in mammals. With FNTs as potential drug targets for many bacterial diseases, it is important to understand the mechanism of selectivity and transport across these transporters.We have systematically searched the sequence databases and identified 2206 FNT sequences from bacteria, archaea and eukaryotes. Although FNT sequences are very diverse, homology modeling followed by structure-based sequence alignment revealed that nearly one third of all the positions within the transmembrane region exhibit high conservation either as a group or at the level of individual residues across all three kingdoms. Phylogenetic analysis of prokaryotic FNT sequences revealed eight different subgroups. Formate, nitrite and hydrosulphide transporters respectively are clustered into two (FocA and FdhC), three (NirC-?, NirC-? and NirC-?) and one (HSC) subfamilies. We have also recognized two FNT subgroups (YfdC-? and YfdC-?) with unassigned function. Analysis of taxonomic distribution indicates that each subfamily prefers specific taxonomic groups. Structure-based sequence alignment of individual subfamily members revealed that certain positions in the two constriction regions and some residues facing the interior show subfamily-specific conservation. We have also identified examples of FNTs with the two constriction regions formed by residues that are less frequently observed. We have developed dbFNT, a database of FNT models and associated details. dbFNT is freely available to scientific community.Taxonomic distribution and sequence conservation of FNTs exhibit subfamily-specific features. The conservation pattern in the central constriction and cytoplasmic slit in the open and closed states are distinct for YfdC and NirC subfamilies. The same is true for some residues facing the interior of the transporters. The specific residues in these positions can exert influence on the type of solutes that are transported by these proteins. With FNTs found in many disease-causing bacteria, the knowledge gained in this study can be used in the development and design of anti-bacterial drugs.

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Subfamily specific conservation profiles for proteins based on n-gram patterns.

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Subfamily specific conservation profiles for proteins based on n-gram patterns.

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