Dataset Information

Parallel analysis of tetramerization domain mutants of the human p53 protein using PCR colonies.

ABSTRACT: A highly-parallel yeast functional assay, capable of screening approximately 100-1,000 mutants in parallel and designed to screen the activity of transcription activator proteins, was utilized to functionally characterize tetramerization domain mutants of the human p53 transcription factor and tumor suppressor protein. A library containing each of the 19 possible single amino acid substitutions (57 mutants) at three positions in the tetramerization domain of the human p53 protein, was functionally screened in Saccharomyces cerevisiae. Amino acids Leu330 and Ile332, whose side chains form a portion of a hydrophobic pocket that stabilizes the active p53 tetramer, were found to tolerate most hydrophobic amino acid substitutions while hydrophilic substitutions resulted in the inactivation of the protein. Amino acid Gln331 tolerated essentially all mutations. Importantly, highly parallel mutagenesis and cloning techniques were utilized which, in conjunction with recently reported highly parallel DNA sequencing methods, would be capable of increasing throughput an additional 2-3 orders of magnitude.

SUBMITTER: Merritt J

PROVIDER: S-EPMC2269032 | biostudies-other | 2007

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:INTRODUCTION: The accurate packing of protein side chains is important for many computational biology problems, such as ab initio protein structure prediction, homology modelling, and protein design and ligand docking applications. Many of existing solutions are modelled as a computational optimisation problem. As well as the design of search algorithms, most solutions suffer from an inaccurate energy function for judging whether a prediction is good or bad. Even if the search has found the lowest energy, there is no certainty of obtaining the protein structures with correct side chains. METHODS: We present a side-chain modelling method, pacoPacker, which uses a parallel ant colony optimisation strategy based on sharing a single pheromone matrix. This parallel approach combines different sources of energy functions and generates protein side-chain conformations with the lowest energies jointly determined by the various energy functions. We further optimised the selected rotamers to construct subrotamer by rotamer minimisation, which reasonably improved the discreteness of the rotamer library. RESULTS: We focused on improving the accuracy of side-chain conformation prediction. For a testing set of 442 proteins, 87.19% of X1 and 77.11% of X12 angles were predicted correctly within 40° of the X-ray positions. We compared the accuracy of pacoPacker with state-of-the-art methods, such as CIS-RR and SCWRL4. We analysed the results from different perspectives, in terms of protein chain and individual residues. In this comprehensive benchmark testing, 51.5% of proteins within a length of 400 amino acids predicted by pacoPacker were superior to the results of CIS-RR and SCWRL4 simultaneously. Finally, we also showed the advantage of using the subrotamers strategy. All results confirmed that our parallel approach is competitive to state-of-the-art solutions for packing side chains. CONCLUSIONS: This parallel approach combines various sources of searching intelligence and energy functions to pack protein side chains. It provides a frame-work for combining different inaccuracy/usefulness objective functions by designing parallel heuristic search algorithms.

Dataset Information

Parallel analysis of tetramerization domain mutants of the human p53 protein using PCR colonies.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets