Computational mechanistic investigation of the kinetic resolution of α-methyl-phenylacetaldehyde by norcoclaurine synthase DOI Creative Commons
Shiqing Zhang,

Chenghua Zhang,

Aijing Guo

et al.

Communications Chemistry, Journal Year: 2024, Volume and Issue: 7(1)

Published: March 27, 2024

Abstract Norcoclaurine synthase from Thalictrum flavum ( Tf NCS) demonstrated high stereospecificity and yield in catalyzing the Pictet-Spengler reaction of dopamine with chiral aldehydes, achieving kinetic resolution aldehydes. However, mechanism factors contributing to stereoselectivity remain unclear. Herein, by using quantum chemical calculations, mechanisms NCS-catalyzed reactions both enantiomers α-methyl-phenylacetaldehyde are studied. The calculations reveal a mirroring natural substrates, for which deprotonation C5−H cyclized intermediate is rate-limiting. calculated overall barriers 20.1 kcal mol -1 21.6 R )- S )-α-methyl-phenylacetaldehyde, respectively. M97 L72 residues proposed be key stereospecificity. obtained detailed information helpful designing new variants NCS extended substrate scope, also advancing our understanding potential applications.

Language: Английский

Navigating the landscape of enzyme design: from molecular simulations to machine learning DOI Creative Commons
Jiahui Zhou, Meilan Huang

Chemical Society Reviews, Journal Year: 2024, Volume and Issue: 53(16), P. 8202 - 8239

Published: Jan. 1, 2024

Global environmental issues and sustainable development call for new technologies fine chemical synthesis waste valorization. Biocatalysis has attracted great attention as the alternative to traditional organic synthesis. However, it is challenging navigate vast sequence space identify those proteins with admirable biocatalytic functions. The recent of deep-learning based structure prediction methods such AlphaFold2 reinforced by different computational simulations or multiscale calculations largely expanded 3D databases enabled structure-based design. While approaches shed light on site-specific enzyme engineering, they are not suitable large-scale screening potential biocatalysts. Effective utilization big data using machine learning techniques opens up a era accelerated predictions. Here, we review applications machine-learning guided We also provide our view challenges perspectives effectively employing design integrating molecular learning, importance database construction algorithm in attaining predictive ML models explore fitness landscape

Language: Английский

Citations

21
Learning from Protein Engineering by Deconvolution of Multi‐Mutational Variants DOI Creative Commons
Frank Hollmann,

Joaquin Sanchis,

Manfred T. Reetz

et al.

Angewandte Chemie International Edition, Journal Year: 2024, Volume and Issue: 63(36)

Published: June 17, 2024

Abstract This review analyzes a development in biochemistry, enzymology and biotechnology that originally came as surprise. Following the establishment of directed evolution stereoselective enzymes organic chemistry, concept partial or complete deconvolution selective multi‐mutational variants was introduced. Early experiments led to finding mutations can interact cooperatively antagonistically with one another, not just additively. During past decade, this phenomenon shown be general. In some studies, molecular dynamics (MD) quantum mechanics/molecular mechanics (QM/MM) computations were performed order shed light on origin non‐additivity at all stages an evolutionary upward climb. Data used construct unique multi‐dimensional rugged fitness pathway landscapes, which provide mechanistic insights different from traditional landscapes. Along related line, biochemists have long tested result introducing two point enzyme for reasons, followed by comparison respective double mutant so‐called cycles, showed only additive effects, but more recently also uncovered cooperative antagonistic non‐additive effects. We conclude suggestions future work, call unified overall picture epistasis.

Language: Английский

Citations

18
Quantum mechanical-based strategies in drug discovery: Finding the pace to new challenges in drug design DOI Creative Commons
Tiziana Ginex, Javier Vázquez,

Carolina Estarellas

et al.

Current Opinion in Structural Biology, Journal Year: 2024, Volume and Issue: 87, P. 102870 - 102870

Published: June 24, 2024

The expansion of the chemical space to tangible libraries containing billions synthesizable molecules opens exciting opportunities for drug discovery, but also challenges power computer-aided design prioritize best candidates. This directly hits quantum mechanics (QM) methods, which provide chemically accurate properties, subject small-sized systems. Preserving accuracy while optimizing computational cost is at heart many efforts develop high-quality, efficient QM-based strategies, reflected in refined algorithms and approaches. QM-tailored physics-based force fields coupling QM with machine learning, conjunction computing performance supercomputing resources, will enhance ability use these methods discovery. challenge formidable, we undoubtedly see impressive advances that define a new era.

Language: Английский

Citations

11
Eliminating Imaginary Vibrational Frequencies in Quantum-Chemical Cluster Models of Enzymatic Active Sites DOI
Paige E. Bowling, Saswata Dasgupta, John M. Herbert

et al.

Journal of Chemical Information and Modeling, Journal Year: 2024, Volume and Issue: 64(9), P. 3912 - 3922

Published: April 22, 2024

In constructing finite models of enzyme active sites for quantum-chemical calculations, atoms at the periphery model must be constrained to prevent unphysical rearrangements during geometry relaxation. A simple fixed-atom or "coordinate-lock" approach is commonly employed but leads undesirable artifacts in form small imaginary frequencies. These preclude evaluation finite-temperature free-energy corrections, limiting thermochemical calculations enthalpies only. Full-dimensional vibrational frequency are possible by replacing constraints with harmonic confining potentials. Here, we compare that an alternative strategy which contributions Hessian simply omitted. While latter does eliminate frequencies, it tends underestimate both zero-point energy and entropy while introducing artificial rigidity. Harmonic potentials frequencies provide a flexible means construct active-site can used unconstrained relaxations, affording better convergence reaction energies barrier heights respect size, as compared constraints.

Language: Английский

Citations

8
Quantum Mechanical Cluster Models for Calculations on Enzymatic Reaction Mechanisms: Set‐Up and Accuracy DOI Creative Commons
Sam P. de Visser, Henrik P. H. Wong, Yi Zhang

et al.

Chemistry - A European Journal, Journal Year: 2024, Volume and Issue: 30(60)

Published: Aug. 7, 2024

Enzymes turnover substrates into products with amazing efficiency and selectivity as such have great potential for use in biotechnology pharmaceutical applications. However, details of their catalytic cycles the origins surrounding regio- chemoselectivity enzymatic reaction processes remain unknown, which makes engineering enzymes challenging. Computational modelling can assist experimental work field establish factors that influence rates product distributions. A popular approach is quantum mechanical cluster models take first- second coordination sphere enzyme active site consideration. These QM are widely applied but often results obtained dependent on model choice selection. Herein, we show give highly accurate reproduce distributions free energies activation within several kcal mol

Language: Английский

Citations

7
Mechanistic Investigation on C–C Bond Cleavage of Anthraquinone Catalyzed by an Atypical Nonheme Iron-Dependent Dioxygenase BTG13 DOI
Zhiwei Deng, Hao Su, Xiaodong Hou

et al.

ACS Catalysis, Journal Year: 2024, Volume and Issue: 14(2), P. 797 - 811

Published: Jan. 3, 2024

An atypical nonheme iron-dependent dioxygenase BTG13 with a rare iron coordination of four histidine residues and carboxylated-lysine (Kcx) was recently reported to catalyze the C4a–C10 bond cleavage anthraquinone. However, reaction mechanism remains elusive. Herein, detailed is studied using molecular dynamics simulations density functional theory calculations. The comprehensive mechanistic study shows that most favorable pathway for C–C anthraquinone involves two unusual steps: (1) hydrogen atom abstraction (HAA) from an sp3-hybridized carbon substrate by FeIII–O2•– (2) oxygen rebound radical via homolytic O–O cleavage, which activates FeIII–OOH form FeIV═O species. Furthermore, our results reveal Kcx could increase electron-donating ability ferrous iron, thereby boosting activation dioxygen species facilitating following HAA processes. This advances current knowledge reactions catalyzed oxygenases.

Language: Английский

Citations

6
Mutexa: A Computational Ecosystem for Intelligent Protein Engineering DOI Creative Commons
Zhongyue Yang, Qianzhen Shao, Yaoyukun Jiang

et al.

Journal of Chemical Theory and Computation, Journal Year: 2023, Volume and Issue: 19(21), P. 7459 - 7477

Published: Oct. 13, 2023

Protein engineering holds immense promise in shaping the future of biomedicine and biotechnology. This Review focuses on our ongoing development Mutexa, a computational ecosystem designed to enable "intelligent protein engineering". In this vision, researchers will seamlessly acquire sequences variants with desired functions as biocatalysts, therapeutic peptides, diagnostic proteins through finely-tuned machine, akin Amazon Alexa's role versatile virtual assistant. The technical foundation Mutexa has been established database that combines relates enzyme structures their respective (e.g., IntEnzyDB), workflow software packages high-throughput modeling EnzyHTP LassoHTP), scoring map sequence-structure-function relationship EnzyKR DeepLasso). We showcase applications these tools benchmarking convergence conditions functional descriptors across mutants, investigating electrostatics cavity distributions SAM-dependent methyltransferases, understanding nonelectrostatic dynamic effects catalysis. Finally, we conclude by addressing steps fundamental challenges endeavor develop new assist identification beneficial mutants engineering.

Language: Английский

Citations

11
Structural and Computational Insights into the Noncanonical Aromatization in Fungal Polyketide Biosynthesis DOI
Hang Wang, Chao Peng, Xiaoxuan Chen

et al.

ACS Catalysis, Journal Year: 2024, Volume and Issue: 14(14), P. 10796 - 10805

Published: July 3, 2024

Language: Английский

Citations

4
Computational Study on the Reaction Mechanism of 5‐Enolpyruvylshikimate‐3‐phosphate Synthase from Nicotiana Tabacum DOI Creative Commons
Qingfang Han,

Beibei Lin,

Ziwei Liu

et al.

ChemistryOpen, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 7, 2025

Abstract 5‐Enolpyruvylshikimate‐3‐phosphate synthase (EPSPS) catalyzes the conversion of 5‐enolpyruvate (PEP) and shikimic acid phosphate (S3P) to 5‐enolpyruvylshikimic acid‐3‐phosphate (EPSP), releasing inorganic phosphate. This reaction is sixth step shikimate pathway, which a metabolic pathway used by microorganisms plants for biosynthesis aromatic amino acids folates but not in mammals. In present study, detailed mechanism EPSPS from Nicotiana tabacum ( Nt EPSPS) revealed quantum chemical calculations with cluster approach. The proposed involve formation carbocation intermediate, tetrahedral C−O bond cleavage re‐formation C=C bond. All four steps are concerted processes involving proton transfer events. suggest step‐wise intermediate hydroxyl group S3P Asp331 nucleophilic attack on carbocation, consistent proposal literature. energy profile entire presented, showing that phosphate, rate‐limiting step. interaction between Glu359 residue significant stabilizing

Language: Английский

Citations

0
Evolutionary Specialization of a Promiscuous Designer Enzyme DOI Creative Commons
Reuben B. Leveson‐Gower, Laura Tiessler‐Sala, H.J. Rozeboom

et al.

ACS Catalysis, Journal Year: 2025, Volume and Issue: 15(3), P. 1544 - 1552

Published: Jan. 13, 2025

The evolution of a promiscuous enzyme for its various activities often results in catalytically specialized variants. This is an important natural mechanism to ensure the proper functioning metabolic networks. It also acts as both curse and blessing engineers, where enzymes that have undergone directed may exhibit exquisite selectivity at expense diminished overall catalytic repertoire. We previously performed two independent campaigns on designer leverages unique properties noncanonical amino acid (ncAA) para-aminophenylalanine (pAF) residue, resulting evolved variants which are specialized. Here, we combine mutagenesis, crystallography, computation reveal molecular basis specialization phenomenon. In one variant, unexpected change quaternary structure biases substrate dynamics promote enantioselective catalysis, while other demonstrates synergistic cooperation between side chains pAF residue form semisynthetic machinery.

Language: Английский

Citations

0