Computational Ways to Enhance Protein Inhibitor Design
Computational Ways to Enhance Protein Inhibitor Design
Two new computational approaches are described to aid in the design of new peptide-based drugs by evaluating ensembles of protein structures from their dynamics and through the assessing of structures using empirical contact potential. These approaches build on the concept that conformational variability can aid in the binding process and, for disordered proteins, can even facilitate the binding of more diverse ligands. This latter consideration indicates that such a design process should be less restrictive so that multiple inhibitors might be effective. The example chosen here focuses on proteins/peptides that bind to hemagglutinin (HA) to block the large-scale conformational change for activation. Variability in the conformations is considered from sets of experimental structures, or as an alternative, from their simple computed dynamics; the set of designe peptides/small proteins from the David Baker lab designed to bind to hemagglutinin, is the large set considered and is assessed with the new empirical contact potentials.
- The Ohio State University United States
- Iowa State University United States
- THE OHIO STATE UNIVERSITY United States
- Sabancı University Turkey
- SABANCI UNIVERSITY
protein potentials, Protein ensemble, Computational design, Protein potentials, QH301-705.5, protein ensemble, computational design, Biochemistry, Genetics and Molecular Biology (miscellaneous), Biochemistry, peptide design, Peptide design, Molecular Biosciences, Protein design, Biology (General), protein design, Molecular Biology
protein potentials, Protein ensemble, Computational design, Protein potentials, QH301-705.5, protein ensemble, computational design, Biochemistry, Genetics and Molecular Biology (miscellaneous), Biochemistry, peptide design, Peptide design, Molecular Biosciences, Protein design, Biology (General), protein design, Molecular Biology
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