Characterizing Protease Specificity: How Many Substrates Do We Need?

Abstract

Calculation of cleavage entropies allows to quantify, map and compare protease substrate specificity by an information entropy based approach. The metric intrinsically depends on the number of experimentally determined substrates (data points). Thus a statistical analysis of its numerical stability is crucial to estimate the systematic error made by estimating specificity based on a limited number of substrates. In this contribution, we show the mathematical basis for estimating the uncertainty in cleavage entropies. Sets of cleavage entropies are calculated using experimental cleavage data and modeled extreme cases. By analyzing the underlying mathematics and applying statistical tools, a linear dependence of the metric in respect to 1/n was found. This allows us to extrapolate the values to an infinite number of samples and to estimate the errors. Analyzing the errors, a minimum number of 30 substrates was found to be necessary to characterize substrate specificity, in terms of amino acid variability, for a protease (S4-S4’) with an uncertainty of 5 percent. Therefore, we encourage experimental researchers in the protease field to record specificity profiles of novel proteases aiming to identify at least 30 peptide substrates of maximum sequence diversity. We expect a full characterization of protease specificity helpful to rationalize biological functions of proteases and to assist rational drug design.

Electrostatic recognition in substrate binding to serine proteases

“…Several methods have been published to describe and localize promiscuity and specificity of the protease binding interface, thus facilitating a comparison of individual proteases. [18][19][20][21] Our cleavage entropy metric 14,22 is based on substrate data deposited in the MEROPS database 23 and quantifies the specificity of peptide recognition in each subpocket. To compare proteases based on their substrate recognition, we developed a metric that considers the positional abundance of individual amino acids.…”

An unexpected switch in peptide binding mode: from simulation to substrate specificity

“…Based on the proteomics data of 3,064 peptides from Yu et al (Yu et al, 2015), which also contains tryptic cleavages, cleavage entropies of 0.962/0.977/0.969/0.966 result for P1′–P4′, in line with the apparent rather low specificity. Roughly 30 diverse substrates would suffice to calculate the specificity for each subsite S4 to S4′ with an uncertainty of 5% (Schauperl et al, 2015). A kinetics study of KLK7 ranked synthetic peptides according to their k cat / K M and corroborated the preference of Tyr and Phe in P1 position, Leu and other hydrophobic residues in P2, whereby P1′ Ser/Arg, P2′ Val/Arg, and P3′ Arg/Ser are most favourable (Oliveira et al, 2015).…”

Structural determinants of specificity and regulation of activity in the allosteric loop network of human KLK8/neuropsin

“…1B ). Comprising 25 cleavages, the MEROPS matrix is just below the theoretical limit of 30 substrates for a reliable specificity determination within a 95% confidence interval, using the information entropy as measure of specificity 46 . By contrast, the PICS measurement comprised 73 substrate cleavages, which increases the reliability substantially, as evidenced by the concordance with the virtually unbiased positional scanning library results (Fig.…”