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Identification of sequences common to more than one therapeutic target to treat complex diseases: simulating the high variance in sequence interactivity evolved to modulate robust phenotypes.

Varela MA - BMC Genomics (2015)

Bottom Line: Genome-wide association studies show that most human traits and diseases are caused by a combination of environmental and genetic causes, with each one of these having a relatively small effect.The increase in the variance of sequence interactivity detected in the human and mouse genomes when compared with less complex organisms could have expedited the evolution of regulators able to interact to multiple gene products and modulate robust phenotypes.The identification of sequences common to more than one therapeutic target carried out in this study could facilitate the design of new multispecific methods able to modify simultaneously key pathways to treat complex diseases.

View Article: PubMed Central - PubMed

Affiliation: Department of Physiology, Anatomy and Genetics, University of Oxford, South Parks Road, Oxford, OX1 3QX, UK. miguel.varela@wikisequences.org.

ABSTRACT

Background: Genome-wide association studies show that most human traits and diseases are caused by a combination of environmental and genetic causes, with each one of these having a relatively small effect. In contrast, most therapies based on macromolecules like antibodies, antisense oligonucleotides or peptides focus on a single gene product. On the other hand, complex organisms seem to have a plethora of functional molecules able to bind specifically to multiple genes or genes products based on their sequences but the mechanisms that lead organisms to recruit these multispecific regulators remain unclear.

Results: The mutational biases inferred from the genomic sequences of six organisms show an increase in the variance of sequence interactivity in complex organisms. The high variance in the interactivity of sequences presents an ideal evolutionary substrate to recruit sequence-specific regulators able to target multiple gene products. For example, here it is shown how the 3'UTR can fluctuate between sequences likely to be complementary to other sites in the genome in the search for advantageous interactions. A library of nucleotide- and peptide-based tools was built using a script to search for candidates (e.g. peptides, antigens to raise antibodies or antisense oligonucleotides) to target sequences shared by key pathways in human disorders, such as cancer and immune diseases. This resource will be accessible to the community at www.wikisequences.org .

Conclusions: This study describes and encourages the adoption of the same multitarget strategy (e.g., miRNAs, Hsp90) that has evolved in organisms to modify complex traits to treat diseases with robust pathological phenotypes. The increase in the variance of sequence interactivity detected in the human and mouse genomes when compared with less complex organisms could have expedited the evolution of regulators able to interact to multiple gene products and modulate robust phenotypes. The identification of sequences common to more than one therapeutic target carried out in this study could facilitate the design of new multispecific methods able to modify simultaneously key pathways to treat complex diseases.

No MeSH data available.


Related in: MedlinePlus

Prediction of peptide structures. Further characterization of the peptides included in Table 2, red: helical, green: extended, blue: coil. Peptide structure was predicted using PEP-FOLD, which is based on hidden Markov models. The structure of these peptides is of importance to define their usefulness depending on their application (eg to raise antibodies, as decoys etc.)
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Fig4: Prediction of peptide structures. Further characterization of the peptides included in Table 2, red: helical, green: extended, blue: coil. Peptide structure was predicted using PEP-FOLD, which is based on hidden Markov models. The structure of these peptides is of importance to define their usefulness depending on their application (eg to raise antibodies, as decoys etc.)

Mentions: In regards to peptide sequences, targets present in multiple proteins and involved in particular human diseases could be employed as decoys [39, 40], to raise antibodies [41], delivered directly in the form of stapled peptides [42–44] or incorporated as loops into naturally occurring cyclic peptides [45, 46] (Table 2). The structure predicted for these peptides can be observed in Fig. 4. Finally, sequences present in multiple homing peptides could specifically recognize more than one type of tumor [47, 48] (Additional file 3: Table S3). The accession numbers of all the peptide and nucleotide sequences that were searched for targets shared by key pathways can be found in the (Additional files 4: Table S4) and (Additional file 5: Table S5). Further details on how the search was performed are in (Additional file 6: Figure S1).Fig. 4


Identification of sequences common to more than one therapeutic target to treat complex diseases: simulating the high variance in sequence interactivity evolved to modulate robust phenotypes.

Varela MA - BMC Genomics (2015)

Prediction of peptide structures. Further characterization of the peptides included in Table 2, red: helical, green: extended, blue: coil. Peptide structure was predicted using PEP-FOLD, which is based on hidden Markov models. The structure of these peptides is of importance to define their usefulness depending on their application (eg to raise antibodies, as decoys etc.)
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4506634&req=5

Fig4: Prediction of peptide structures. Further characterization of the peptides included in Table 2, red: helical, green: extended, blue: coil. Peptide structure was predicted using PEP-FOLD, which is based on hidden Markov models. The structure of these peptides is of importance to define their usefulness depending on their application (eg to raise antibodies, as decoys etc.)
Mentions: In regards to peptide sequences, targets present in multiple proteins and involved in particular human diseases could be employed as decoys [39, 40], to raise antibodies [41], delivered directly in the form of stapled peptides [42–44] or incorporated as loops into naturally occurring cyclic peptides [45, 46] (Table 2). The structure predicted for these peptides can be observed in Fig. 4. Finally, sequences present in multiple homing peptides could specifically recognize more than one type of tumor [47, 48] (Additional file 3: Table S3). The accession numbers of all the peptide and nucleotide sequences that were searched for targets shared by key pathways can be found in the (Additional files 4: Table S4) and (Additional file 5: Table S5). Further details on how the search was performed are in (Additional file 6: Figure S1).Fig. 4

Bottom Line: Genome-wide association studies show that most human traits and diseases are caused by a combination of environmental and genetic causes, with each one of these having a relatively small effect.The increase in the variance of sequence interactivity detected in the human and mouse genomes when compared with less complex organisms could have expedited the evolution of regulators able to interact to multiple gene products and modulate robust phenotypes.The identification of sequences common to more than one therapeutic target carried out in this study could facilitate the design of new multispecific methods able to modify simultaneously key pathways to treat complex diseases.

View Article: PubMed Central - PubMed

Affiliation: Department of Physiology, Anatomy and Genetics, University of Oxford, South Parks Road, Oxford, OX1 3QX, UK. miguel.varela@wikisequences.org.

ABSTRACT

Background: Genome-wide association studies show that most human traits and diseases are caused by a combination of environmental and genetic causes, with each one of these having a relatively small effect. In contrast, most therapies based on macromolecules like antibodies, antisense oligonucleotides or peptides focus on a single gene product. On the other hand, complex organisms seem to have a plethora of functional molecules able to bind specifically to multiple genes or genes products based on their sequences but the mechanisms that lead organisms to recruit these multispecific regulators remain unclear.

Results: The mutational biases inferred from the genomic sequences of six organisms show an increase in the variance of sequence interactivity in complex organisms. The high variance in the interactivity of sequences presents an ideal evolutionary substrate to recruit sequence-specific regulators able to target multiple gene products. For example, here it is shown how the 3'UTR can fluctuate between sequences likely to be complementary to other sites in the genome in the search for advantageous interactions. A library of nucleotide- and peptide-based tools was built using a script to search for candidates (e.g. peptides, antigens to raise antibodies or antisense oligonucleotides) to target sequences shared by key pathways in human disorders, such as cancer and immune diseases. This resource will be accessible to the community at www.wikisequences.org .

Conclusions: This study describes and encourages the adoption of the same multitarget strategy (e.g., miRNAs, Hsp90) that has evolved in organisms to modify complex traits to treat diseases with robust pathological phenotypes. The increase in the variance of sequence interactivity detected in the human and mouse genomes when compared with less complex organisms could have expedited the evolution of regulators able to interact to multiple gene products and modulate robust phenotypes. The identification of sequences common to more than one therapeutic target carried out in this study could facilitate the design of new multispecific methods able to modify simultaneously key pathways to treat complex diseases.

No MeSH data available.


Related in: MedlinePlus