Cystathionine beta-Synthase (CBS) single amino acid mutations

Please go to the prediction submission form to submit you predictions for the CBS dataset (to submit, you need to be logged into your account).

Background: CBS is a vitamin-dependent enzyme involved in cysteine biosynthesis via the transsulfuration pathway. The human CBS requires two cofactors for function, vitamin B6 (in the active form of pyridoxal 5’-phosphate [PLP], supplemented in the soluble form of pyridoxine) and heme.

Dataset: 57 single amino acid mutations were introduced within the human CBS coding region. These mutations are synthetic, and are thus not necessarily clinically observed. The effect of each mutation was measured with yeast complementation assay, where growth is dependent upon the level of mutant function. Rates are expressed as a percentage relative to wild type grown with the same amount of exogenous pyridoxine supplementation, plus and minus the standard deviation. Two concentrations of pyridoxine, high and low, are provided.

The reference sequences within NCBI Entrez database are:
mRNA reference sequence NM_000071
protein reference sequence NP_000062

Example dataset: Predictors are provided an example dataset (please see below), where the relative growth rates of 6 single amino acid human CBS substitutions are given. In this example dataset, a qualitative assessment of the change in functionality is given in addition to the growth rate.

Nucleotide Mutation(s) Substituted Residue Growth Rate 400 ng/ml Pyridoxine Change in functionality Growth Rate 2 ng/ml Pyridoxine Change in functionality
418, G>A D140N 103 +/- 25 none 79 +/- 8 impaired
620, C>G A207G 0 severely impaired
674, A>G N225S 70 +/- 12 impaired 37 +/- 13 impaired
791, T>C I264T 109 +/- 14 none 106 +/- 17 none
967, T>G W323G 0 severely impaired
1070, C>G A357G 104 +/- 19 none 95 +/- 20 none

Prediction dataset: 51 single amino acid mutations within the human CBS coding region. The dataset is available for download here: CBS-prediction-dataset. The file was revised 3 Nov 2010 to exclude the example dataset of 6 mutations.

Prediction challenge: Predictors are asked to submit predictions on the effect of the mutations in the function of CBS both in high co-factor (pyridoxine) concentration (400ng/ml) and in low co-factor concentration (2ng/ml). The submitted prediction should be a numeric value with a standard deviation. In addition, we ask predictors to submit the raw output data of the prediction algorithm. The predictions will be assessed against the numeric values actually measured for each mutation in the yeast assay.

Prediction submission format: The prediction submission is a simple text file. The organizers provide a file template, which should be used for submission. In the submitted file, each line should include the following columns:

1) The substituted residue as listed in the prediction dataset file, use the order as provided in the template form
2) Prediction of relative growth rate in high pyridoxine concentration (400ng/ml)
3) Standard deviation of the prediction in column 2
4) Prediction of relative growth rate in low pyridoxine concentration (2 ng/ml)
5) Standard deviation of the prediction in column 4
6) Raw output data from your prediction algorithm

Columns 1, 2, 4 and 6 are required, columns 3 and 5 are optional. In the template file, columns 2-6 are marked with an “*”. Submit your predictions by replacing the “*” with your prediction value. If predictions cannot be submitted for a specific line (mutation), leave the sign “*” in these columns. The validity of the submitted prediction file will be checked with a script, so please make sure you follow these submission guidelines strictly.

In addition, your submission should include a detailed description of the method used to make the predictions. This information will be submitted as a separate file.

Please go to the prediction submission form to submit you predictions for the CBS dataset (to submit, you need to be logged into your account).

Please download a Pdf document (CBS_description_and_data.pdf) for a more through background information, the example dataset and prediction datasets. The file was revised 3 Nov 2010 to exclude the example dataset from prediction dataset list and to add edits to the table presenting the example dataset.

Jasper RineDago Dimster-Denk
Dataset provided by Jasper Rine and Dago Dimster-Denk, University of California Berkeley