Predictive models of protease specificity based on quantitative protease-activity profiling data

Publication date: Available online 19 July 2019Source: Biochimica et Biophysica Acta (BBA) - Proteins and ProteomicsAuthor(s): Gennady G. Fedonin, Alexey Eroshkin, Piotr Cieplak, Evgenii V. Matveev, Gennady V. Ponomarev, Mikhail S. Gelfand, Boris I. Ratnikov, Marat D. KazanovAbstractBioinformatics-based prediction of protease substrates can help to elucidate regulatory proteolytic pathways that control a broad range of biological processes such as apoptosis and blood coagulation. The majority of published predictive models are position weight matrices (PWM) reflecting specificity of proteases toward target sequence. These models are typically derived from experimental data on positions of hydrolyzed peptide bonds and show a reasonable predictive power. New emerging techniques that not only register the cleavage position but also measure catalytic efficiency of proteolysis are expected to improve the quality of predictions or at least substantially reduce the number of tested substrates required for confident predictions. The main goal of this study was to develop new prediction models based on such data and to estimate the performance of the constructed models. We used data on catalytic efficiency of proteolysis measured for eight major human matrix metalloproteinases to construct predictive models of protease specificity using a variety of regression analysis techniques. The obtained results suggest that efficiency-based (quantitative) models show a comparable performance wi...

Source: Biochimica et Biophysica Acta (BBA) Proteins and Proteomics - July 19, 2019 Category: Biochemistry Source Type: research