000202482 001__ 202482
000202482 005__ 20181203023634.0
000202482 0247_ $$2doi$$a10.2533/chimia.2014.642
000202482 022__ $$a0009-4293
000202482 02470 $$2ISI$$a000342477000011
000202482 037__ $$aARTICLE
000202482 245__ $$aLessons from Nature: Computational Design of Biomimetic Compounds and Processes
000202482 260__ $$aBern$$bSchweizerische Chemische Gesellschaft$$c2014
000202482 269__ $$a2014
000202482 300__ $$a6
000202482 336__ $$aJournal Articles
000202482 520__ $$aThrough millions of years of evolution, Nature has accomplished the development of highly efficient and sustainable processes and the idea to understand and copy natural strategies is therefore very appealing. However, in spite of intense experimental and computational research, it has turned out to be a difficult task to design efficient biomimetic systems. Here we discuss a novel strategy for the computational design of biomimetic compounds and processes that consists of i) target selection; ii) atomistic and electronic characterization of the wild type system and the biomimetic compounds; iii) identification of key descriptors through feature selection iv) choice of biomimetic template and v) efficient search of chemical and sequence space for optimization of the biomimetic system. As a proof-of-principles study, this general approach is illustrated for the computational design of a 'green' catalyst mimicking the action of the zinc metalloenzyme Human Carbonic Anhydrase (HCA). HCA is a natural model for CO2 fixation since the enzyme is able to convert CO2 into bicarbonate. Very recently, a weakly active HCA mimic based on a trihelical peptide bundle was synthetized. We have used quantum mechanical/molecular mechanical (QM/MM) Car-Parrinello simulations to study the mechanisms of action of HCA and its peptidic mimic and employed the obtained information to guide the design of improved biomimetic analogues. Applying a genetic algorithm based optimization procedure, we were able to re-engineer and optimize the biomimetic system towards its natural counter part. In a second example, we discuss a similar strategy for the design of biomimetic sensitizers for use in dye-sensitized solar cells.
000202482 6531_ $$aBiomimetic compounds
000202482 6531_ $$aComputational enzyme design
000202482 6531_ $$aDensity Functional Theory
000202482 6531_ $$aDye-sensitized solar cells
000202482 6531_ $$aGreen chemistry
000202482 6531_ $$aMixed quantum mechanical-molecular mechanical (QM/MM) simulations
000202482 6531_ $$aNatural catalysts
000202482 700__ $$0247080$$aBozkurt, Esra$$g227618
000202482 700__ $$0245413$$aAshari, Negar$$g195114
000202482 700__ $$0246263$$aBrowning, Nicholas$$g240680
000202482 700__ $$0242794$$aBrunk, Elizabeth$$g188106
000202482 700__ $$0242797$$aCampomanes, Pablo$$g182406
000202482 700__ $$aPerez, Marta A. S.
000202482 700__ $$0241350$$aRothlisberger, Ursula$$g150117
000202482 773__ $$j68$$k9$$q642-647$$tChimia
000202482 909C0 $$0252093$$pLCBC$$xU2
000202482 909CO $$ooai:infoscience.tind.io:202482$$pSB$$particle
000202482 917Z8 $$x232236
000202482 937__ $$aEPFL-ARTICLE-202482
000202482 973__ $$aEPFL$$rREVIEWED$$sPUBLISHED
000202482 980__ $$aARTICLE