Last modified by emacasali on 2023/01/11 16:05
From version 5.1
edited by emacasali
on 2023/01/11 10:53
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To version 7.1
edited by emacasali
on 2023/01/11 11:07
Change comment: Uploaded new attachment "image-20230111110707-1.png", version {1}

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4 4  (((
5 5  = MEDIUM - Machine lEarning Drug dIscovery throUgh dynaMics =
6 6  
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9 9  
10 -ML-based DF classification tool
9 +Giorgio Colombo Group (UNIPV)
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12 12  )))
13 13  
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18 -= What can I find here? =
17 += Why this tool is useful? =
19 19  
20 -* Notice how the table of contents on the right
21 -* is automatically updated
22 -* to hold this page's headers
19 +The prediction of the best ligand for a specific protein could be a huge challenge using the classical approaches like molecular docking and stabilisation energy calculations.
23 23  
21 +Here we report on a fast and solid workflow which starts from our DF-matrix method to analyse how the protein globally behaves in the presence of a ligand. Machine Learning (ML) trains a Convolutional Neural Network (CNN) model directly on the pixel images of DF: train is preformed using a known ligand and the different behaviour of the protein is evaluated in the presence and in absence of it.
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23 +With the so trained model further predictions can be performed using different ligands.
24 +
24 24  = Who has access? =
25 25  
26 26  Describe the audience of this collab.
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