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We can enhance binding specificity of a protein by computationally optimizing its sequence for better interactions with one target and worse interaction with alternative target(s).
MOTIVATION: The DNA binding specificity of a transcription factor (TF) is typically represented using a position weight matrix model, which implicitly assumes that individual bases in a TF binding site contribute independently to the binding affinity, an assumption that does not always hold.
If the binding specificity of a TF is already known, pattern matching methods are preferred [9].
Alternatively, the binding specificity of a query sequence can be deduced from a universal PDZ domain family model.
To our knowledge, our study is the first to use such PBMs to investigate the potential influence of the addition of protein cofactors into multiprotein complexes on the DNA binding specificity of a transcription factor.
Cooperative DNA binding, via self-association, often increases the DNA binding specificity of a protein.
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It was surprising that HA1 190, which is critical for receptor-binding specificity of A(H1N1) HAs, was also under positive selection.
We also analyzed the evolutionary trends at HA1 190 and 225 that are critical determinants for receptor-binding specificity of A(H1N1) HA.
For their predominant roles in determining receptor-binding specificity of A(H1N1) HA, and the positive selection on HA1 190 in the subgroup I-v, we further investigated the evolution of HA1 190 and 225 in A(H1N1) strains during 1918∼1009.
Through further analysis of HA1 190, together with HA1 225, the other critical determinant for receptor-binding specificity of A(H1N1), we found that the epidemic HAs and the 1918 pandemic and swine HAs favored one of these two sites for antigenic drift.
We hypothesized that this peptide could confer binding specificity of an antibody to αvβ6.
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