| could DataWarrior "build evolutionary libray" criteria be applied to design minipeptides? [message #2482] |
Sun, 01 November 2026 08:38 |
juliocoll
Messages: 36
Registered: January 2023
Location: Madrid SPAIN
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The build evolutionary library of DataWarrior is a powerful tool to design drug-like compounds and selec those with high affinities among many of their possible alternatives. I really appreciated it!
While sucessfully working with the 2-years-old new deep-learning peptide-design programs such as BoltzGen and many others, and if I did not misundertstood their algorithms, I noticed that still they did not employed any affinity-docking evolutionary algorithm to iteratively select for their best peptide designs. Up to now, BoltGen and others generate only structurally fitting peptides.
I wonder if those type of protein-peptide affinity designs could be incorporated into the criteria of the build evolutionary library. In other words, could an affinity minipeptide criteria (6 to 12-mer) be added to the build evolutionary library of DataWarrior? perhaps by restriciting the libraries amino acids during evolution rather than atoms? perhaps by including protein-peptide interaction/affinity predictions by other programs like Prodigy? perhaps other ideas?
Julio Coll
Profesor de Investigación. Emérito
Dpt.Biotecnología
CSIC-centro Nacional INIA, Madrid, SPAIN
Dr. Biologia Univ.Comp(UCM). Madrid, Spain
PHD. Biology Mass.Inst,Technol (MIT). Massachusetts, USA
orcid: 0000-0001-8496-3493
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