Service interruption on Monday 11 July from 12:30 to 13:00: all the sites of the CCSD (HAL, EpiSciences, SciencesConf, AureHAL) will be inaccessible (network hardware connection).
Skip to Main content Skip to Navigation
Journal articles

Pareto optimization in computational protein design with multiple objectives.

Abstract : The optimization for function in computational design requires the treatment of, often competing, multiple objectives. Current algorithms reduce the problem to a single objective optimization problem, with the consequent loss of relevant solutions. We present a procedure, based on a variant of a Pareto algorithm, to optimize various competing objectives in protein design that allows reducing in several orders of magnitude the search of the solution space. Our methodology maintains the diversity of solutions and provides an iterative way to incorporate automatic design methods in the design of functional proteins. We have applied our systematic procedure to design enzymes optimized for both catalysis and stability. However, this methodology can be applied to any computational chemistry application requiring multi-objective combinatorial optimization techniques.
Document type :
Journal articles
Complete list of metadata
Contributor : Denis Roura Connect in order to contact the contributor
Submitted on : Friday, January 4, 2013 - 1:30:57 PM
Last modification on : Monday, May 10, 2021 - 5:32:02 PM

Links full text




Maria Suarez, Pablo Tortosa, J. Carrera, A. Jaramillo. Pareto optimization in computational protein design with multiple objectives.. Journal of Computational Chemistry, Wiley, 2008, 29 (16), pp.2704-11. ⟨10.1002/jcc.20981⟩. ⟨hal-00767089⟩



Record views