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Computational genes: a tool for molecular diagnosis and therapy of aberrant mutational phenotype.

Martínez-Pérez IM, Zhang G, Ignatova Z, Zimmermann KH - BMC Bioinformatics (2007)

Bottom Line: The aberrant mutations trigger a cascade reaction: specific molecular markers as input are released and induce a spontaneous self-assembly of a wild type protein or peptide, while the mutational disease phenotype is silenced.We experimentally demostrated in in vitro translation system that a viable protein can be autonomously assembled.Our work demostrates the basic principles of computational genes and particularly, their potential to detect mutations, and as a response thereafter administer an output that suppresses the aberrant disease phenotype and/or restores the lost physiological function.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute of Computer Technology, Hamburg University of Technology, Hamburg 21073, Germany. martinez-perez@tu-harburg.de

ABSTRACT

Background: A finite state machine manipulating information-carrying DNA strands can be used to perform autonomous molecular-scale computations at the cellular level.

Results: We propose a new finite state machine able to detect and correct aberrant molecular phenotype given by mutated genetic transcripts. The aberrant mutations trigger a cascade reaction: specific molecular markers as input are released and induce a spontaneous self-assembly of a wild type protein or peptide, while the mutational disease phenotype is silenced. We experimentally demostrated in in vitro translation system that a viable protein can be autonomously assembled.

Conclusion: Our work demostrates the basic principles of computational genes and particularly, their potential to detect mutations, and as a response thereafter administer an output that suppresses the aberrant disease phenotype and/or restores the lost physiological function.

Show MeSH
Design and assembly of the computational gene exemplified with one eukaryotic gene. A) Diagnosis. The 24 nt long double-stranded diagnostic duplex Am/AB' bears three mismatches positioned at the centre. The single-strand Am represents the mutation signal and the AB' strand the diagnostic signal. The displacement of AB' from Am is thermodynamically favourable due to the full complementary of Am' to Am. Regions highlighted in bold show the positions where mismatches were located before strand displacement. B) Therapy. The eukaryotic hID1 gene is the skeleton of the computational gene. The conserved regions of hID1 serve as constants for designing a functional gene being (for simplicity and demonstration purposes) a part of the hID1 gene product itself. For this reason, the intron sequence of hID1 was modified to construct the required initial and final accepting states, keeping the conserved splicing signals intact. The three elements, e.g., initial state (part A), diagnostic signal (AB'), and final state (part B), revealed a functional 1.6 kb gene encoding a 155 amino acid long (17.3 kDa) protein.
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Figure 2: Design and assembly of the computational gene exemplified with one eukaryotic gene. A) Diagnosis. The 24 nt long double-stranded diagnostic duplex Am/AB' bears three mismatches positioned at the centre. The single-strand Am represents the mutation signal and the AB' strand the diagnostic signal. The displacement of AB' from Am is thermodynamically favourable due to the full complementary of Am' to Am. Regions highlighted in bold show the positions where mismatches were located before strand displacement. B) Therapy. The eukaryotic hID1 gene is the skeleton of the computational gene. The conserved regions of hID1 serve as constants for designing a functional gene being (for simplicity and demonstration purposes) a part of the hID1 gene product itself. For this reason, the intron sequence of hID1 was modified to construct the required initial and final accepting states, keeping the conserved splicing signals intact. The three elements, e.g., initial state (part A), diagnostic signal (AB'), and final state (part B), revealed a functional 1.6 kb gene encoding a 155 amino acid long (17.3 kDa) protein.

Mentions: This rule could allow a protein with a pathogenic mutation to execute its natural physiological function. For instance, a mutation at codon 249 in the p53 protein is characteristic for hepatocellular cancer [15,16] and the CDB3 peptide (nine amino acids) binds to the p53 core domain and stabilises its fold [17]. Although restoring the tumor suppressor activity of the p53 mutants with small stabilising molecules is a promising strategy in cancer therapy, different classes of mutations will require different rescue strategies [18]. The rule (1) can be implemented by a two-state one-symbol automaton consisting of two partially dsDNA molecules and one ssDNA molecule (symbol), which corresponds to the disease-related mutation and provides a molecular switch for the linear self-assembly of the functional gene (Figure 2B, [see Additional file 1]).


Computational genes: a tool for molecular diagnosis and therapy of aberrant mutational phenotype.

Martínez-Pérez IM, Zhang G, Ignatova Z, Zimmermann KH - BMC Bioinformatics (2007)

Design and assembly of the computational gene exemplified with one eukaryotic gene. A) Diagnosis. The 24 nt long double-stranded diagnostic duplex Am/AB' bears three mismatches positioned at the centre. The single-strand Am represents the mutation signal and the AB' strand the diagnostic signal. The displacement of AB' from Am is thermodynamically favourable due to the full complementary of Am' to Am. Regions highlighted in bold show the positions where mismatches were located before strand displacement. B) Therapy. The eukaryotic hID1 gene is the skeleton of the computational gene. The conserved regions of hID1 serve as constants for designing a functional gene being (for simplicity and demonstration purposes) a part of the hID1 gene product itself. For this reason, the intron sequence of hID1 was modified to construct the required initial and final accepting states, keeping the conserved splicing signals intact. The three elements, e.g., initial state (part A), diagnostic signal (AB'), and final state (part B), revealed a functional 1.6 kb gene encoding a 155 amino acid long (17.3 kDa) protein.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
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getmorefigures.php?uid=PMC2175521&req=5

Figure 2: Design and assembly of the computational gene exemplified with one eukaryotic gene. A) Diagnosis. The 24 nt long double-stranded diagnostic duplex Am/AB' bears three mismatches positioned at the centre. The single-strand Am represents the mutation signal and the AB' strand the diagnostic signal. The displacement of AB' from Am is thermodynamically favourable due to the full complementary of Am' to Am. Regions highlighted in bold show the positions where mismatches were located before strand displacement. B) Therapy. The eukaryotic hID1 gene is the skeleton of the computational gene. The conserved regions of hID1 serve as constants for designing a functional gene being (for simplicity and demonstration purposes) a part of the hID1 gene product itself. For this reason, the intron sequence of hID1 was modified to construct the required initial and final accepting states, keeping the conserved splicing signals intact. The three elements, e.g., initial state (part A), diagnostic signal (AB'), and final state (part B), revealed a functional 1.6 kb gene encoding a 155 amino acid long (17.3 kDa) protein.
Mentions: This rule could allow a protein with a pathogenic mutation to execute its natural physiological function. For instance, a mutation at codon 249 in the p53 protein is characteristic for hepatocellular cancer [15,16] and the CDB3 peptide (nine amino acids) binds to the p53 core domain and stabilises its fold [17]. Although restoring the tumor suppressor activity of the p53 mutants with small stabilising molecules is a promising strategy in cancer therapy, different classes of mutations will require different rescue strategies [18]. The rule (1) can be implemented by a two-state one-symbol automaton consisting of two partially dsDNA molecules and one ssDNA molecule (symbol), which corresponds to the disease-related mutation and provides a molecular switch for the linear self-assembly of the functional gene (Figure 2B, [see Additional file 1]).

Bottom Line: The aberrant mutations trigger a cascade reaction: specific molecular markers as input are released and induce a spontaneous self-assembly of a wild type protein or peptide, while the mutational disease phenotype is silenced.We experimentally demostrated in in vitro translation system that a viable protein can be autonomously assembled.Our work demostrates the basic principles of computational genes and particularly, their potential to detect mutations, and as a response thereafter administer an output that suppresses the aberrant disease phenotype and/or restores the lost physiological function.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute of Computer Technology, Hamburg University of Technology, Hamburg 21073, Germany. martinez-perez@tu-harburg.de

ABSTRACT

Background: A finite state machine manipulating information-carrying DNA strands can be used to perform autonomous molecular-scale computations at the cellular level.

Results: We propose a new finite state machine able to detect and correct aberrant molecular phenotype given by mutated genetic transcripts. The aberrant mutations trigger a cascade reaction: specific molecular markers as input are released and induce a spontaneous self-assembly of a wild type protein or peptide, while the mutational disease phenotype is silenced. We experimentally demostrated in in vitro translation system that a viable protein can be autonomously assembled.

Conclusion: Our work demostrates the basic principles of computational genes and particularly, their potential to detect mutations, and as a response thereafter administer an output that suppresses the aberrant disease phenotype and/or restores the lost physiological function.

Show MeSH