Protein stability provides advantageous development of novel properties and can be crucial in affording tolerance to mutations that introduce functionally preferential phenotypes. Consequently, understanding the determining factors for protein stability is important for the study of structure-function relationship and design of novel protein functions. Thermal stability has been extensively studied in connection with practical application of biocatalysts. However, little work has been done to explore the mechanism of pH-dependent inactivation. In this study, bioinformatic analysis of the Ntn-hydrolase superfamily was performed to identify functionally important subfamily-specific positions in protein structures. Furthermore, the involvement of these positions in pH-induced inactivation was studied. The conformational mobility of penicillin acylase in Escherichia coli was analyzed through molecular modeling in neutral and alkaline conditions. Two functionally important subfamily-specific residues, Gluβ482 and Aspβ484, were found. Ionization of these residues at alkaline pH promoted the collapse of a buried network of stabilizing interactions that consequently disrupted the functional protein conformation. The subfamily-specific position Aspβ484 was selected as a hotspot for mutation to engineer enzyme variant tolerant to alkaline medium. The corresponding Dβ484N mutant was produced and showed 9-fold increase in stability at alkaline conditions. Bioinformatic analysis of subfamily-specific positions can be further explored to study mechanisms of protein inactivation and to design more stable variants for the engineering of homologous Ntn-hydrolases with improved catalytic properties.
Proteins within a single family usually share a common function but differ in more specific features and can be divided into subfamilies with different properties. Availability of genomic, structural, and functional information implemented into numerous databases provides new opportunities for bioinformatic analysis of homologous proteins. In this work, new method of bioinformatic analysis has been developed to identify subfamily-specific positions (SSPs)--conserved only within protein subfamilies, but different between subfamilies--that seem to play important role in functional diversity. A novel scoring function is suggested to consider structural information as well as physicochemical and residue conservation in protein subfamilies. Random shuffling is performed to rank results by significance, and Bernoulli statistics is applied to calculate p-values. Algorithm does not require predefined subfamily classification and can propose it automatically by graph-based clustering. This method can be used as a tool to explore SSPs with different structural localization in order to understand their implication to structure-function relationship and protein function. Web interface to the program is available at http://biokinet.belozersky.msu.ru/zebra.
During evolution of proteins from a common ancestor, one functional property can be preserved while others can vary leading to functional diversity. A systematic study of the corresponding adaptive mutations provides a key to one of the most challenging problems of modern structural biology - understanding the impact of amino acid substitutions on protein function. The subfamily-specific positions (SSPs) are conserved within functional subfamilies but are different between them and, therefore, seem to be responsible for functional diversity in protein superfamilies. Consequently, a corresponding method to perform the bioinformatic analysis of sequence and structural data has to be implemented in the common laboratory practice to study the structure-function relationship in proteins and develop novel protein engineering strategies. This paper describes Zebra web server - a powerful remote platform that implements a novel bioinformatic analysis algorithm to study diverse protein families. It is the first application that provides specificity determinants at different levels of functional classification, therefore addressing complex functional diversity of large superfamilies. Statistical analysis is implemented to automatically select a set of highly significant SSPs to be used as hotspots for directed evolution or rational design experiments and analyzed studying the structure-function relationship. Zebra results are provided in two ways - (1) as a single all-in-one parsable text file and (2) as PyMol sessions with structural representation of SSPs. Zebra web server is available at http://biokinet.belozersky.msu.ru/zebra .
The new web-server pocketZebra implements the power of bioinformatics and geometry-based structural approaches to identify and rank subfamily-specific binding sites in proteins by functional significance, and select particular positions in the structure that determine selective accommodation of ligands. A new scoring function has been developed to annotate binding sites by the presence of the subfamily-specific positions in diverse protein families. pocketZebra web-server has multiple input modes to meet the needs of users with different experience in bioinformatics. The server provides on-site visualization of the results as well as off-line version of the output in annotated text format and as PyMol sessions ready for structural analysis. pocketZebra can be used to study structure–function relationship and regulation in large protein superfamilies, classify functionally important binding sites and annotate proteins with unknown function. The server can be used to engineer ligand-binding sites and allosteric regulation of enzymes, or implemented in a drug discovery process to search for potential molecular targets and novel selective inhibitors/effectors. The server, documentation and examples are freely available at http://biokinet.belozersky.msu.ru/pocketzebra and there are no login requirements.
Soft tissue sarcomas (STS) are heterogeneous cancers with more than 100 histological subtypes, different in molecular alterations, which make its personalized therapy very complex. Gold standard of chemotherapy for advanced STS includes combinations of Doxorubicin and Ifosfamide or Gemcitabine and Docetaxel. Chemotherapy is efficient for less than 50% of patients and it is followed by a fast development of drug resistance. Our study was directed to the search of genetic alterations in cancer cells associated with chemoresistance of undifferentiated pleomorphic and synovial sarcomas to the abovementioned genotoxic drugs. We analyzed chemoresistance of cancer cells in vitro using primary STS cultures and performed genetic analysis for the components of apoptotic signaling. In 27% of tumors, we revealed alterations in TP53, ATM, PIK3CB, PIK3R1, NTRK1, and CSF2RB. Cells from STS specimens with found genetic alterations were resistant to Dox, excluding the only one case when TP53 mutation resulted in the substitution Leu344Arg associated with partial oligomerization loss and did not cause total loss of TP53 function. Significant association between alterations in the components of apoptosis signaling and chemoresistance to Dox was found. Our data are important to elaborate further the therapeutic strategy for STS patients with alterations in apoptotic signaling.
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