Chapter Two - Integrating computational and experimental methods for efficient biocatalytic synthesis of polyesters
The research on biocatalyzed polycondensation has delivered an array of polyesters having molecular weights below 20,000 g mol− 1 but characterized by controlled structures and desired functionalities. Their unique catalytic efficiency under mild conditions enables enzymes to catalyze the polyconden...
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ftunivgenova:oai:iris.unige.it:11567/1062483 2024-04-14T08:04:00+00:00 Chapter Two - Integrating computational and experimental methods for efficient biocatalytic synthesis of polyesters Pellis A Gardossi L A. Pellis, L. Gardossi Pellis, A Gardossi, L 2019 ELETTRONICO https://hdl.handle.net/11567/1062483 https://doi.org/10.1016/bs.mie.2019.07.040 eng eng info:eu-repo/semantics/altIdentifier/wos/WOS:000500284200003 ispartofbook:Methods in Enzymology volume:627 firstpage:23 lastpage:55 numberofpages:33 https://hdl.handle.net/11567/1062483 doi:10.1016/bs.mie.2019.07.040 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85070753088 info:eu-repo/semantics/bookPart 2019 ftunivgenova https://doi.org/10.1016/bs.mie.2019.07.040 2024-03-21T02:36:53Z The research on biocatalyzed polycondensation has delivered an array of polyesters having molecular weights below 20,000 g mol− 1 but characterized by controlled structures and desired functionalities. Their unique catalytic efficiency under mild conditions enables enzymes to catalyze the polycondensation of monomers bearing labile lateral moieties that can be easily accessed via post-polymerization modifications. Despite this great potential, nowadays biocatalysts are not employed for polycondensation on industrial scale due to some bottlenecks related to the formulation of biocatalysts and the process configuration, which make the enzymatic technology non-economic. Recycling the enzymatic catalysts is not only a matter of producing an active and robust formulation, but it also requires the optimal integration of such biocatalyst within a specific reactor and process configuration that must enable efficient mass-transfer while preserving the integrity of the enzymatic preparation. In this chapter, we describe examples of integrated experimental-computational approaches for the rational planning and implementation of enzymatic polycondensation using lipase B from Candida antarctica and cutinase 1 from Thermobifida cellulosilytica. They rely on molecular visualization, molecular modeling and chemometrics, which are methods requiring very modest computational power and approachable by operators who do not have specific computational background. The examples also address the sustainability issue, by describing solvent-free processes involving bio-based monomers and biocatalysts immobilized on renewable carriers. Book Part Antarc* Antarctica Università degli Studi di Genova: CINECA IRIS 23 55 |
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Università degli Studi di Genova: CINECA IRIS |
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English |
description |
The research on biocatalyzed polycondensation has delivered an array of polyesters having molecular weights below 20,000 g mol− 1 but characterized by controlled structures and desired functionalities. Their unique catalytic efficiency under mild conditions enables enzymes to catalyze the polycondensation of monomers bearing labile lateral moieties that can be easily accessed via post-polymerization modifications. Despite this great potential, nowadays biocatalysts are not employed for polycondensation on industrial scale due to some bottlenecks related to the formulation of biocatalysts and the process configuration, which make the enzymatic technology non-economic. Recycling the enzymatic catalysts is not only a matter of producing an active and robust formulation, but it also requires the optimal integration of such biocatalyst within a specific reactor and process configuration that must enable efficient mass-transfer while preserving the integrity of the enzymatic preparation. In this chapter, we describe examples of integrated experimental-computational approaches for the rational planning and implementation of enzymatic polycondensation using lipase B from Candida antarctica and cutinase 1 from Thermobifida cellulosilytica. They rely on molecular visualization, molecular modeling and chemometrics, which are methods requiring very modest computational power and approachable by operators who do not have specific computational background. The examples also address the sustainability issue, by describing solvent-free processes involving bio-based monomers and biocatalysts immobilized on renewable carriers. |
author2 |
A. Pellis, L. Gardossi Pellis, A Gardossi, L |
format |
Book Part |
author |
Pellis A Gardossi L |
spellingShingle |
Pellis A Gardossi L Chapter Two - Integrating computational and experimental methods for efficient biocatalytic synthesis of polyesters |
author_facet |
Pellis A Gardossi L |
author_sort |
Pellis A |
title |
Chapter Two - Integrating computational and experimental methods for efficient biocatalytic synthesis of polyesters |
title_short |
Chapter Two - Integrating computational and experimental methods for efficient biocatalytic synthesis of polyesters |
title_full |
Chapter Two - Integrating computational and experimental methods for efficient biocatalytic synthesis of polyesters |
title_fullStr |
Chapter Two - Integrating computational and experimental methods for efficient biocatalytic synthesis of polyesters |
title_full_unstemmed |
Chapter Two - Integrating computational and experimental methods for efficient biocatalytic synthesis of polyesters |
title_sort |
chapter two - integrating computational and experimental methods for efficient biocatalytic synthesis of polyesters |
publishDate |
2019 |
url |
https://hdl.handle.net/11567/1062483 https://doi.org/10.1016/bs.mie.2019.07.040 |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_relation |
info:eu-repo/semantics/altIdentifier/wos/WOS:000500284200003 ispartofbook:Methods in Enzymology volume:627 firstpage:23 lastpage:55 numberofpages:33 https://hdl.handle.net/11567/1062483 doi:10.1016/bs.mie.2019.07.040 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85070753088 |
op_doi |
https://doi.org/10.1016/bs.mie.2019.07.040 |
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