Bioinformatic analysis of protein families for identification of variable amino acid residues responsible for functional diversity

Suplatov, Dmitry A.; Shalaeva, Daria N.; Kirilin, Evgeny; Arzhanik, Vladimir K.; Švedas, Vytas K.

doi:10.1080/07391102.2012.750249

Cited by 28 publications

(27 citation statements)

References 46 publications

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“…Functional subfamilies can be defined according to experimentally obtained functional annotation. However, because the amount of experimental data is limited, similarity-based clustering strategies have been proposed to automatically predict functional subfamilies in large datasets [67]. SSPs were shown to be responsible for functional discrimination among homologous proteins; they are preferentially associated with catalytic and regulatory sites in enzymes [69].…”

Section: Systematic Rational Designmentioning

confidence: 99%

“…3A). The latest bioinformatic procedures to detect SSPs implement entropy-based measures of subfamily-dependent distribution of amino acids, take into account sequence and structural information, physicochemical properties of amino acid side chains and perform ranking to automatically select the most statistically significant hotspots for further evaluation [67,68]. Functional subfamilies can be defined according to experimentally obtained functional annotation.…”

Section: Systematic Rational Designmentioning

confidence: 99%

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Robust enzyme design: Bioinformatic tools for improved protein stability

Suplatov

Voevodin

Švedas

2014

Biotechnology Journal

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The ability of proteins and enzymes to maintain a functionally active conformation under adverse environmental conditions is an important feature of biocatalysts, vaccines, and biopharmaceutical proteins. From an evolutionary perspective, robust stability of proteins improves their biological fitness and allows for further optimization. Viewed from an industrial perspective, enzyme stability is crucial for the practical application of enzymes under the required reaction conditions. In this review, we analyze bioinformatic-driven strategies that are used to predict structural changes that can be applied to wild type proteins in order to produce more stable variants. The most commonly employed techniques can be classified into stochastic approaches, empirical or systematic rational design strategies, and design of chimeric proteins. We conclude that bioinformatic analysis can be efficiently used to study large protein superfamilies systematically as well as to predict particular structural changes which increase enzyme stability. Evolution has created a diversity of protein properties that are encoded in genomic sequences and structural data. Bioinformatics has the power to uncover this evolutionary code and provide a reproducible selection of hotspots - key residues to be mutated in order to produce more stable and functionally diverse proteins and enzymes. Further development of systematic bioinformatic procedures is needed to organize and analyze sequences and structures of proteins within large superfamilies and to link them to function, as well as to provide knowledge-based predictions for experimental evaluation.

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Section: Systematic Rational Designmentioning

confidence: 99%

Section: Systematic Rational Designmentioning

confidence: 99%

Robust enzyme design: Bioinformatic tools for improved protein stability

Suplatov

Voevodin

Švedas

2014

Biotechnology Journal

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“…"QuickZebra + 3D" -sequence and structural analysis The "QuickZebra + 3D" mode in addition to the sequence input requires a PDB structure file that should correspond to one of the MSA sequences. Incorporation of the 3D information can significantly improve Zebra predictions (Suplatov et al, 2013). Moreover, the PDB file will be used to produce PyMol session files (.pse) with structural representations of the SSPs for each subfamily classification.…”

Section: "Quickzebra" -Sequence Analysis Onlymentioning

confidence: 99%

“…Zebra implements the recently developed bioinformatic algorithm (Suplatov et al, 2013). A multiple sequence alignment (MSA) and, optionally, structural information about the protein superfamily are used as an input.…”

Section: Identification Of Subfamily-specific Positionsmentioning

confidence: 99%

“…Principles, mathematics, and advantages of the algorithm have been presented elsewhere (Suplatov, Shalaeva, Kirilin, Arzhanik, & Švedas, 2013). Here, we describe the corresponding web server Zebra as an automated and efficient remote tool for systematic analysis of SSPs in large protein superfamilies to promote the wide circulation of the method.…”

Section: Introductionmentioning

confidence: 99%

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Zebra: a web server for bioinformatic analysis of diverse protein families

Suplatov

Kirilin

Takhaveev

et al. 2013

Journal of Biomolecular Structure and Dynamics

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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 .

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Bioinformatic analysis of the fold type I PLP‐dependent enzymes reveals determinants of reaction specificity in l‐threonine aldolase from Aeromonas jandaei

2018

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Understanding the role of specific amino acid residues in the molecular mechanism of a protein's function is one of the most challenging problems in modern biology. A systematic bioinformatic analysis of protein families and superfamilies can help in the study of structure–function relationships and in the design of improved variants of enzymes/proteins, but represents a methodological challenge. The pyridoxal‐5′‐phosphate ( PLP )‐dependent enzymes are catalytically diverse and include the aspartate aminotransferase superfamily which implements a common structural framework known as type fold I. In this work, the recently developed bioinformatic online methods Mustguseal and Zebra were used to collect and study a large representative set of the aspartate aminotransferase superfamily with high structural, but low sequence similarity to l ‐threonine aldolase from Aeromonas jandaei ( LTA aj), in order to identify conserved positions that provide general properties in the superfamily, and to reveal family‐specific positions (FSPs) responsible for functional diversity. The roles of the identified residues in the catalytic mechanism and reaction specificity of LTA aj were then studied by experimental site‐directed mutagenesis and molecular modelling. It was shown that FSPs determine reaction specificity by coordinating the PLP cofactor in the enzyme's active centre, thus influencing its activation and the tautomeric equilibrium of the intermediates, which can be used as hotspots to modulate the protein's functional properties. Mutagenesis at the selected FSPs in LTA aj led to a reduction in a native catalytic activity and increased the rate of promiscuous reactions. The results provide insight into the structural basis of catalytic promiscuity of the PLP ‐dependent enzymes and demonstrate the potential of bioinformatic analysis in studying structure–function relationship in protein superfamilies.

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Bioinformatic analysis of protein families for identification of variable amino acid residues responsible for functional diversity

Cited by 28 publications

References 46 publications

Robust enzyme design: Bioinformatic tools for improved protein stability

Robust enzyme design: Bioinformatic tools for improved protein stability

Zebra: a web server for bioinformatic analysis of diverse protein families

Bioinformatic analysis of the fold type I PLP‐dependent enzymes reveals determinants of reaction specificity in l‐threonine aldolase from Aeromonas jandaei

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