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EVolver: an optimization engine for evolving protein sequences to stabilize the respective structures.

ABSTRACT: BACKGROUND: Many structural bioinformatics approaches employ sequence profile-based threading techniques. To improve fold recognition rates, homology searching may include artificially evolved amino acid sequences, which were demonstrated to enhance the sensitivity of protein threading in targeting midnight zone templates. FINDINGS: We describe implementation details of eVolver, an optimization algorithm that evolves protein sequences to stabilize the respective structures by a variety of potentials, which are compatible with those commonly used in protein threading. In a case study focusing on LARG PDZ domain, we show that artificially evolved sequences have quite high capabilities to recognize the correct protein structures using standard sequence profile-based fold recognition. CONCLUSIONS: Computationally design protein sequences can be incorporated in existing sequence profile-based threading approaches to increase their sensitivity. They also provide a desired linkage between protein structure and function in in silico experiments that relate to e.g. the completeness of protein structure space, the origin of folds and protein universe. eVolver is freely available as a user-friendly webserver and a well-documented stand-alone software distribution at http://www.brylinski.org/evolver.

SUBMITTER: Brylinski M

PROVIDER: S-EPMC3735418 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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eVolver: an optimization engine for evolving protein sequences to stabilize the respective structures.

Brylinski Michal M

BMC research notes 20130731

<h4>Background</h4>Many structural bioinformatics approaches employ sequence profile-based threading techniques. To improve fold recognition rates, homology searching may include artificially evolved amino acid sequences, which were demonstrated to enhance the sensitivity of protein threading in targeting midnight zone templates.<h4>Findings</h4>We describe implementation details of eVolver, an optimization algorithm that evolves protein sequences to stabilize the respective structures by a vari ...[more]

PMID: 23902875

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Project description:Here we focus on identifying conserved elements that are required for Chaserr function, a lncRNA that we recently characterized as being essential for mouse viability (https://doi.org/10.1038/s41467-019-13075-8). Chaserr is highly conserved in different species, and is located in close proximity (<2kb) to the transcription start site of CHD2. It acts in concert with the CHD2 protein to maintain proper Chd2 expression levels. Using the LncLOOM framework we identified AUGG enriched conserved elements which are located in the last exon of mouse Chaserr. In order to identify proteins that potentially bind to these conserved regions, we used in vitro transcription to generate the following biotinylated RNAs; along with their antisense controls: 1) The WT sequence, containing the first 322 nt of the last exon of Chaserr (bases 764–1086 of the NR_037601 isoform). An antisense control fragment was also prepared, labelled as AWT 2) The mutant conserved (MC) sequence, that contained AUGG→UACC mutations in four conserved motifs that were found using LncLOOM. An antisense control fragment was also prepared, labelled as AMC 3) The muatant all (MA) sequence in which all seven of the AUGG sites in the last exon were mutated to UACC. An antisense control fragment was also prepared, labelled as AMA 4) We also included a No Probe Control, which did not contain an RNA fragment. The fragments were incubated with N2a cell lysates followed by RNA-pulldown and Mass Spec analysis. The experiment was performed in triplicate. A total of 938 proteins were found to associate with the WT sequence: 74 of these were enriched ≥3-fold compared to the antisense sequence.We identified 9 proteins that had ≥2-fold higher recovery when using the WT sequence compared to both mutants. Included in these proteins was DHX36, which showed the highest enrichment compared to the mutated sequences. We validated the association of DHX36 with Chaserr through RNA immunoprecipitation experiments.

Dataset Information

EVolver: an optimization engine for evolving protein sequences to stabilize the respective structures.

Publications

eVolver: an optimization engine for evolving protein sequences to stabilize the respective structures.

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