How to find simple and accurate rules for viral protease cleavage specificities

<p>Abstract</p> <p>Background</p> <p>Proteases of human pathogens are becoming increasingly important drug targets, hence it is necessary to understand their substrate specificity and to interpret this knowledge in practically useful ways. New methods are being developed that produce large amounts of cleavage information for individual proteases and some have been applied to extract cleavage rules from data. However, the hitherto proposed methods for extracting rules have been neither easy to understand nor very accurate. To be practically useful, cleavage rules should be accurate, compact, and expressed in an easily understandable way.</p> <p>Results</p> <p>A new method is presented for producing cleavage rules for viral proteases with seemingly complex cleavage profiles. The method is based on orthogonal search-based rule extraction (OSRE) combined with spectral clustering. It is demonstrated on substrate data sets for human immunodeficiency virus type 1 (HIV-1) protease and hepatitis C (HCV) NS3/4A protease, showing excellent prediction performance for both HIV-1 cleavage and HCV NS3/4A cleavage, agreeing with observed HCV genotype differences. New cleavage rules (consensus sequences) are suggested for HIV-1 and HCV NS3/4A cleavages. The practical usability of the method is also demonstrated by using it to predict the location of an internal cleavage site in the HCV NS3 protease and to correct the location of a previously reported internal cleavage site in the HCV NS3 protease. The method is fast to converge and yields accurate rules, on par with previous results for HIV-1 protease and better than previous state-of-the-art for HCV NS3/4A protease. Moreover, the rules are fewer and simpler than previously obtained with rule extraction methods.</p> <p>Conclusion</p> <p>A rule extraction methodology by searching for multivariate low-order predicates yields results that significantly outperform existing rule bases on out-of-sample data, but are more transparent to expert users. The approach yields rules that are easy to use and useful for interpreting experimental data.</p

Heterologous Protein Expression Is Enhanced by Harmonizing the Codon Usage Frequencies of the Target Gene with those of the Expression Host

Synonymous codon replacement can change protein structure and function, indicating that protein structure depends on DNA sequence. During heterologous protein expression, low expression or formation of insoluble aggregates may be attributable to differences in synonymous codon usage between expression and natural hosts. This discordance may be particularly important during translation of the domain boundaries (link/end segments) that separate elements of higher ordered structure. Within such regions, ribosomal progression slows as the ribosome encounters clusters of infrequently used codons that preferentially encode a subset of amino acids. To replicate the modulation of such localized translation rates during heterologous expression, we used known relationships between codon usage frequencies and secondary protein structure to develop an algorithm (“codon harmonization”) for identifying regions of slowly translated mRNA that are putatively associated with link/end segments. It then recommends synonymous replacement codons having usage frequencies in the heterologous expression host that are less than or equal to the usage frequencies of native codons in the native expression host. For protein regions other than these putative link/end segments, it recommends synonymous substitutions with codons having usage frequencies matched as nearly as possible to the native expression system. Previous application of this algorithm facilitated E. coli expression, manufacture and testing of two Plasmodium falciparum vaccine candidates. Here we describe the algorithm in detail and apply it to E. coli expression of three additional P. falciparum proteins. Expression of the “recoded” genes exceeded that of the native genes by 4- to 1,000-fold, representing levels suitable for vaccine manufacture. The proteins were soluble and reacted with a variety of functional conformation-specific mAbs suggesting that they were folded properly and had assumed native conformation. Codon harmonization may further provide a general strategy for improving the expression of soluble functional proteins during heterologous expression in hosts other than E. coli

Development of a Rule Based Prognostic Tool for HER 2 Positive Breast Cancer Patients

International audienceA three stage development process for the production of a hierarchical rule based prognosis tool is described. The application for this tool is specific to breast cancer patients that have a positive expression of the HER 2 gene. The first stage is the development of a Bayesian classification neural network to classify for cancer specific mortality. Secondly, low-order Boolean rules are extracted form this model using an orthogonal search based rule extraction (OSRE) algorithm. Further to these rules additional information is gathered from the Kaplan-Meier survival estimates of the population, stratified by the categorizations of the input variables. Finally, expert knowledge is used to further simplify the rules and to rank them hierarchically in the form of a decision tree. The resulting decision tree groups all observations into specific categories by clinical profile and by event rate. The practical clinical value of this decision support tool will in future be tested by external validation with additional data from other clinical centres