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Catalysts
Special Issues
High-Throughput Computational Design of Catalysts
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High-Throughput Computational Design of Catalysts

A special issue of Catalysts (ISSN 2073-4344). This special issue belongs to the section "Computational Catalysis".

Deadline for manuscript submissions: closed (15 June 2023) | Viewed by 4725

Special Issue Editors

Prof. Dr. Kaili Nie

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Guest Editor
Beijing Key Laboratory of Bioprocess, National Energy R&D Center for Biorefinery, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
Interests: enzymatic catalysis; molecular dynamitic simulation; enzyme rational design; enzyme direct evolution
Dr. Yu Ji

E-Mail Website
Guest Editor
Lehrstuhl für Biotechnologie, RWTH Aachen University, Worringerweg 3, 52074 Aachen, Germany
Interests: enzyme engineering; peptide engineering; ultrahigh-throughput screening systems; micro/nanoplastic detection, quantification and degradation
Dr. Chun Shen

E-Mail Website
Guest Editor
Beijing Key Laboratory of Bioprocess, College of Life Science and Technology, Beijing University of Chemical Technology, No. 15 of North Three-Ring East Road, Chaoyang District, Beijing 100029, China
Interests: heterogeneous catalysis; reaction mechanism; active site of catalyst; bio-refinery

Special Issue Information

Dear Colleagues,

Nowadays, most chemicals and fuels are produced from petroleum or biomass based on various catalysts, which lead to an increasing demand for new catalyst development. However, traditional procedure of catalysts development based on experimental method is inefficient, which could not meet the huge demand of modern industrialization. The development of quantum mechanics and algorithm computational technologies makes it possible to design the catalyst in silico. Meanwhile, the rapid development of more efficient and accurate of the computational methods facilitate the application of computational chemistry in the new catalyst development. The related works indicated that the interplay between experiment and computational chemistry showed its potential for catalyst screening, and with the help of computational predication, the cost of catalysts development would be reduced, while the process of investigation would also be accelerated.

This special issue focus on recent advances in high-throughput computational design of catalysts and emphasize the versatile opportunities and the great potential of computational chemistry in the design of homogeneous and heterogeneous catalysts, and biocatalysts, as well as the prediction of reaction pathways. The methodological and theoretical approaches and developments of computational design and high-throughput screening method for various kinds of catalysts are also welcome.

Prof. Dr. Kaili Nie
Dr. Yu Ji
Dr. Chun Shen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Catalysts is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • catalyst
  • heterogeneous, homogeneous or biocatalysis
  • high-throughput computational design
  • molecular dynametic simulation
  • quantum mechanics
  • catalyst design
  • catalyst discovery
  • catalyst optimization

Published Papers (3 papers)

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Research

11 pages, 1780 KiB  
Article
Rational Design of Cyclodextrin Glycosyltransferase with Improved Hesperidin Glycosylation Activity
by Hanchi Chen, Jiajun Wang, Yi Liu, Yongfan Chen, Chunfeng Wang, Linjiang Zhu, Yuele Lu and Xiaolong Chen
Catalysts 2023, 13(5), 885; https://doi.org/10.3390/catal13050885 - 14 May 2023
Cited by 1 | Viewed by 1232
Abstract
Cyclodextrin glycosyltransferase (CGTase) can catalyze the glycosylation of hesperidin, resulting in α-glycosyl hesperidin with significantly improved water solubility. In this study, a rational design of CGTase to improve its hesperidin glycosylation activity was investigated. The strategy we employed involved docking hesperidin in its [...] Read more.
Cyclodextrin glycosyltransferase (CGTase) can catalyze the glycosylation of hesperidin, resulting in α-glycosyl hesperidin with significantly improved water solubility. In this study, a rational design of CGTase to improve its hesperidin glycosylation activity was investigated. The strategy we employed involved docking hesperidin in its near-attack conformation and virtually mutating the surrounding residues, followed by calculating the changes in binding energy using Rosetta flex-ddG. The mutations with a stabilization effect were then subjected to an activity assay. Starting from CGTase-Y217F, we obtained three double-point mutants, Y217F/M351F, Y217F/M351L, and Y217F/D393H, with improved hesperidin glycosylation activities after screening twenty variants. The best variant, Y217F/D393H, exhibited a catalytic activity of 1305 U/g, and its kcat/KmA is 2.36 times higher compared to CGTase-Y217F and 15.14 times higher compared to the wild-type CGTase. Molecular dynamic simulations indicated that hesperidin was repulsed by CGTase-Y217F when bound in a near-attack conformation. However, by introducing a second-point mutation with a stabilization effect, the repulsion effect is weakened, resulting in a reduction in the distances between the bond-forming atoms and, thus, favoring the reaction. Full article
(This article belongs to the Special Issue High-Throughput Computational Design of Catalysts)
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10 pages, 4728 KiB  
Article
Enhancing the Thermal Stability of Glutathione Bifunctional Synthase by B-Factor Strategy and Un/Folding Free Energy Calculation
by Wenlong Zhu, Heming Sun, Qixuan Jiang, Ruonan Zheng, Qingyun Wang, Qinfei Zhang, Luo Liu and Hui Cao
Catalysts 2022, 12(12), 1649; https://doi.org/10.3390/catal12121649 - 15 Dec 2022
Cited by 1 | Viewed by 1092
Abstract
Glutathione is of great significance in pharmaceutical and health fields, and one-step synthesis of reduced glutathione by glutathione bifunctional synthase has become a focus of research. The stability of glutathione bifunctional synthase is generally poor and urgently needs to be modified. The B-factor [...] Read more.
Glutathione is of great significance in pharmaceutical and health fields, and one-step synthesis of reduced glutathione by glutathione bifunctional synthase has become a focus of research. The stability of glutathione bifunctional synthase is generally poor and urgently needs to be modified. The B-factor strategy and un/folding free energy calculation were both applied to enhance the thermal stability of glutathione bifunctional synthase from Streptococcus agalactiae (GshFSA). Based on the concept of B-factor strategy, we calculated the B-factor by molecular dynamics simulation to find flexible residues, performed point saturation mutations and high-throughput screening. At the same time, we also calculated the un/folding free energy of GshFSA and performed the point mutations. The optimal mutant from the B-factor strategy was R270S, which had a 2.62-fold increase in half-life period compared to the wild type, and the Q406M was the optimal mutant from the un/folding free energy calculation, with a 3.02-fold increase in half-life period. Both of them have provided a mechanistic explanation. Full article
(This article belongs to the Special Issue High-Throughput Computational Design of Catalysts)
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13 pages, 4383 KiB  
Article
Biocatalytic Cascade of Sebacic Acid Production with In Situ Co-Factor Regeneration Enabled by Engineering of an Alcohol Dehydrogenase
by Jie Lu, Dong Lu, Qiuyang Wu, Shuming Jin, Junfeng Liu, Meng Qin, Li Deng, Fang Wang and Kaili Nie
Catalysts 2022, 12(11), 1318; https://doi.org/10.3390/catal12111318 - 27 Oct 2022
Cited by 1 | Viewed by 1822
Abstract
Sebacic acid (1,10-decanedioic acid) is an important chemical intermediate. Traditional chemical oxidation methods for sebacic acid production do not conform with “green” manufacturing. With the rapid development of enzymatic technologies, a biocatalytic cascade method based on the Baeyer–Villiger monooxygenase was developed. The most [...] Read more.
Sebacic acid (1,10-decanedioic acid) is an important chemical intermediate. Traditional chemical oxidation methods for sebacic acid production do not conform with “green” manufacturing. With the rapid development of enzymatic technologies, a biocatalytic cascade method based on the Baeyer–Villiger monooxygenase was developed. The most attractive point of the method is the oleic acid that can be utilized as raw material, which is abundant in nature. However, this bio-catalysis process needs co-factor electron carriers, and the high cost of the co-factor limits its progress. In this piece of work, a co-factor in situ regeneration system between ADH from Micrococcus luteus WIUJH20 (MlADH) and BVMO is proposed. Since the co-factors of both enzymes are different, switching the co-factor preference of native MlADH from NAD+ to NADP+ is necessary. Switching research was carried out based on in silico simulation, and the sites of Tyr36, Asp 37, Ala38, and Val39 were selected for mutation investigation. The experimental results demonstrated that mutants of MlADH_D37G and MlADH_D37G/A38T/V39K would utilize NADP+ efficiently, and the mutant of MlADH_D37G/A38T/V39K demonstrated the highest sebacic acid yield with the combination of BVMO. The results indicated that the in situ co-factor generation system is successfully developed, which would improve the efficiency of the biocatalytic cascade for sebacic acid production and is helpful for simplifying product isolation, thus, reducing the cost of the enzymatic transformations process. Full article
(This article belongs to the Special Issue High-Throughput Computational Design of Catalysts)
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