کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4496672 1623904 2012 5 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
RFCRYS: Sequence-based protein crystallization propensity prediction by means of random forest
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم کشاورزی و بیولوژیک (عمومی)
پیش نمایش صفحه اول مقاله
RFCRYS: Sequence-based protein crystallization propensity prediction by means of random forest
چکیده انگلیسی

Production of high-quality diffracting crystals is a critical step in determining the 3D structure of a protein by X-ray crystallography. Only 2%–10% of crystallization projects result in high-resolution protein structures. Previously, several computational methods for prediction of protein crystallizability were developed. In this work, we introduce RFCRYS, a Random Forest based method to predict crystallizability of proteins. RFCRYS utilizes mono-, di-, and tri-peptides amino acid compositions, frequencies of amino acids in different physicochemical groups, isoelectric point, molecular weight, and length of protein sequences, from the primary sequences to predict crystallizabillity by using two different databases. RFCRYS was compared with previous methods and the results obtained show that our proposed method using this set of features outperforms existing predictors with higher accuracy, MCC, and Specificity. Especially, our method is characterized by high Specificity of 0.95, which means RFCRYS rarely mispredicts a protein chain to be crystallizable which consequently would be useful for saving time and resources. In conclusion RFCRYS provides accurate crystallizability prediction for a protein chain that can be applied to support crystallization projects getting higher success rate towards obtaining diffraction-quality crystals.


► Highest performance in comparison with the other methods.
► Our results can be used to guide crystallographers to select more feasible alternative targets.
► Our results would save resources to solve more proteins.
► Our results show that RF is well adapted for prediction of crystallization propensity.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Theoretical Biology - Volume 306, 7 August 2012, Pages 115–119
نویسندگان
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