Investigating vesicular selection

  • Authors:

  • Yun-Geun Lee;Bob McKay;Kang-Il Kim;Dong-Kyun Kim;Nguyen Xuan Hoai

  • Affiliations:

  • School of Computer Science and Engineering, Seoul National University, Seoul 151744, Republic of Korea;School of Computer Science and Engineering, Seoul National University, Seoul 151744, Republic of Korea;School of Computer Science and Engineering, Seoul National University, Seoul 151744, Republic of Korea;School of Computer Science and Engineering, Seoul National University, Seoul 151744, Republic of Korea;Faculty of IT, Hanoi University, Hanoi, Viet Nam

  • Venue:
  • Applied Soft Computing
  • Year:
  • 2011

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Abstract

Abstract: Directed protein evolution has led to major advances in organic chemistry, enabling the development of highly optimised proteins. The SELEX method has also been highly effective in evolving ribose nucleic acid (RNA) or deoxy-ribose nucleic acid (DNA) molecules; variants have been proposed which allow SELEX to be used in protein evolution. All of these methods can be viewed as evolutionary algorithms implemented in chemistry. A number of methods rely on selection of natural cells, or of artificial bubbles. These methods result in a new form of selection mechanism, which we call vesicular selection (VS). It is not, prima facie, clear whether VS is an effective selection mechanism, or how its performance is affected by changes in vesicle size. It is difficult to investigate this in vitro, so we use in silico methods derived from evolutionary computation. The primary aim is to test whether this selection method hinders biochemical evolutionary search (in which case, it might be worth investing research effort in discovering alternative selection methods). An in silico implementation of this selection method, embedded in an otherwise-typical evolutionary computation system, shows reasonable ability to solve tough optimisation problems, together with an acceptable ability to concentrate the solutions found. We compare it with tournament selection (TS), a standard evolutionary computation method, which can be finely tuned for high selection pressure, but only coarsely tuned for low selection pressure. By contrast, the new selection mechanism VS is highly tunable at low selection pressures. It is thus particularly suited to problem domains where extensive exploration capabilities are required. Since there is very good reason to believe that protein search spaces require highly exploratory search, the selection mechanism is well matched to its application in combinatorial chemistry.