ArticleSystems and synthetic biology2010
Structure prediction and validation of an affibody engineered for cell-specific nucleic acid targeting.
Article in Systems and synthetic biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 12 citations in OpenAlex.
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- Differential Evolutionary Selection and Natural Evolvability Observed in ALT Proteins of Human Filarial Parasites.PloS one · 2016Article
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- Intratumoral chemotherapy for lung cancer: re-challenge current targeted therapies.Drug design, development and therapy · 2013Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cell-penetrating peptides comprising cloned epitopes that contribute to membrane transduction, DNA-binding and cell targeting functions are known to facilitate nucleic acid delivery. Using the ITASSER software, we predicted the 3-D structure of a well characterized and efficient transfecting cell-penetrating peptide, namely TAT-Mu and its derivative TAT-Mu-AF protein that harbors a targeting ligand, the HER2-binding affibody. Our model predicts TAT-Mu-AF fusion protein as primarily comprising α-helices. The affibody in TAT-Mu-AF is predicted as a 3-helical domain that is distinct from the TAT-Mu domain. Its positioning in three-dimensional structure is oriented in a manner that possibly favors interactions with receptor and facilitates transport to the target site. The linker region between TAT-Mu and the affibody is also predicted as a helix that is likely to stabilize the overall fold of the TAT-Mu-AF complex. Further, the evaluation of secondary structure of the designed TAT-Mu-AF fusion protein by circular dichroism is in support of our predictions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.