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Exact(3)
Third, we repeat this procedure for all p interactome proteins and assign the prediction scores to pairs between the query compound and all interactome proteins.
The 4D FAPOA entails an optimal assignment step to compute a final similarity value based on the atom-pair tree similarity matrix S. If the approach computes the similarity value between the query compound and a data set compound, the i-th row of S represents the atom-pair tree with the i-th atom of the query compound as root node.
For example, progressive optimization can be applied to similarity searches that involve time-consuming computation of the similarity values between the query compound and compounds in the databases.
Similar(57)
Among the search methods available, 2D fingerprint based conventional similarity search (CSS) is a well-established virtual screening tool [1, 2], in which the similarities between database compounds and the query compound are measured and ranked, and hits are selected from the top of the ranked list.
In our study, a non-iterative search is defined as only one fingerprint or one profile of the query compound participating in the similarity measurement between the query and database compound.
The outputs are the list of predicted human proteins for the query compound and associated information.
Second, from the interactome compounds known to interact with the k-th protein (k = 1, 2,…, p), we select an interactome compound with the highest similarity to the query constituent compound and use the corresponding similarity score as a prediction score to assess the possibility that the query compound interacts with the k-th protein.
In all cases the query compound is retrieved first.
Additionally, atoms and bonds of the query compound are colored by summarizing the effect of single fragments (which are present in the query compound).
After generation of the topological atom fingerprints for the query compound, the fingerprint of each atom in query compound was matched against the two fingerprint databases.
Our service renders this fragment as deactivating, as the query compound would be predicted as active with increased probability if this fragment would not match the query compound.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com