Computational analysis of proteins is an essential shortcut to random experimentation. Multiple sequence alignments (MSAs) reveal evolutionary history of a protein family, govern predictions of 3D structures and functions and guide experimental design. Accuracy of these alignments is critical for the accuracy of conclusions from their analysis. With the finding from the previous round of the grant, we significantly advanced the power of sequence similarity search and improved the accuracy of MSA. Using these techniques, we aided biological discoveries in dozens of collaborations with experimentalists, analyzed medically important protein families and implemented a number of public web-servers. For the next funding period we propose to: 1) Build on our advances to perfect homology search and multiple sequence alignment. Sequence profile search will be improved by more sound statistics and by averaging scores over predicted homologs of found hits. Sequence alignment will be corrected in regions that interact less closely with the rest of the protein and segments that require large adjustments. 2) Maintain, improve and integrate our protein sequence analysis servers. During the first funding period of the grant, in addition to improving our sequence search and alignment web-servers, we developed three new servers for predicting a number of characteristics for a protein sequence, finding literature about a protein and visualizing relationships between proteins as networks, and compiled a searchable database of clinical mutations. We will integrate these servers into a single sequence analysis """"""""stop"""""""", augmented with other information, such as expression patterns, protein interactions, human polymorphism and known diseases. 3) Develop an Atlas of clinical mutations in proteins, freely available for browsing and download without login requirements. Each out of 25,000 known mutations will have a dedicated web-page with mutation's characteristics and predictions about its negative effects.
Accurate protein sequence analysis is an essential step in planning of experiments. Despite recent progress, computational methods are not precise enough to predict properties of biological molecules, explain molecular mechanisms of diseases and design drugs. We will improve the accuracy of sequence analysis methods and apply them to develop an Atlas of clinical mutations - a free, accessible to all on-line interactive database with hypotheses about how each of 25,000 known mutations affects a protein and causes disease.
|Schaeffer, R Dustin; Kinch, Lisa N; Liao, Yuxing et al. (2016) Classification of proteins with shared motifs and internal repeats in the ECOD database. Protein Sci 25:1188-203|
|Song, Jeongmin; Wilhelm, Cara L; Wangdi, Tamding et al. (2016) Absence of TLR11 in Mice Does Not Confer Susceptibility to Salmonella Typhi. Cell 164:827-8|
|Lee, Jyh-Yeuan; Kinch, Lisa N; Borek, Dominika M et al. (2016) Crystal structure of the human sterol transporter ABCG5/ABCG8. Nature 533:561-4|
|Cong, Qian; Shen, Jinhui; Warren, Andrew D et al. (2016) Speciation in Cloudless Sulphurs Gleaned from Complete Genomes. Genome Biol Evol 8:915-31|
|Zhang, Yinxin; Lee, Kwang Min; Kinch, Lisa N et al. (2016) Direct Demonstration That Loop1 of Scap Binds to Loop7: A CRUCIAL EVENT IN CHOLESTEROL HOMEOSTASIS. J Biol Chem 291:12888-96|
|Li, Wenlin; Schaeffer, R Dustin; Otwinowski, Zbyszek et al. (2016) Estimation of Uncertainties in the Global Distance Test (GDT_TS) for CASP Models. PLoS One 11:e0154786|
|Baker, Richard H; Narechania, Apurva; DeSalle, Rob et al. (2016) Spermatogenesis Drives Rapid Gene Creation and Masculinization of the X Chromosome in Stalk-Eyed Flies (Diopsidae). Genome Biol Evol 8:896-914|
|Li, Peng; Rivera-Cancel, Giomar; Kinch, Lisa N et al. (2016) Bile salt receptor complex activates a pathogenic type III secretion system. Elife 5:|
|Cong, Qian; Shen, Jinhui; Borek, Dominika et al. (2016) Complete genomes of Hairstreak butterflies, their speciation, and nucleo-mitochondrial incongruence. Sci Rep 6:24863|
|Kinch, Lisa N; Li, Wenlin; Schaeffer, R Dustin et al. (2016) CASP 11 target classification. Proteins 84 Suppl 1:20-33|
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