Advances in the Simulations of Enzyme Reactivity in the Dawn of the Artificial Intelligence Age

Wiley Interdisciplinary Reviews Computational Molecular Science, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 1, 2025

ABSTRACT The study of natural enzyme catalytic processes at a molecular level can provide essential information for rational design new enzymes, to be applied in more efficient and environmentally friendly industrial processes. use computational tools, combined with experimental techniques, is providing outstanding milestones the last decades. However, apart from complexity associated nature these large flexible biomolecular machines, full catalyzed process involves different physical chemical steps. Consequently, point view, deep understanding every single step requires selection proper technique get reliable, robust useful results. In this article, we summarize techniques their process, including conformational diversity, allostery those steps, as well enzymes. Because impact artificial intelligence all aspects science during years, special attention has been methods based on foundations some selected recent applications.

Язык: Английский

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Methods for Theoretical Treatment of Local Fields in Proteins and Enzymes

Chemical Reviews, Год журнала: 2025, Номер unknown

Опубликована: Фев. 24, 2025

Electric fields generated by protein scaffolds are crucial in enzymatic catalysis. This review surveys theoretical approaches for detecting, analyzing, and comparing electric fields, electrostatic potentials, their effects on the charge density within enzyme active sites. Pioneering methods like empirical valence bond approach rely evaluating ionic covalent resonance forms influenced field. Strategies employing polarizable force also facilitate field detection. The vibrational Stark effect connects computational simulations to experimental spectroscopy, enabling direct comparisons. We highlight how dynamics induce fluctuations local influencing activity. Recent techniques assess throughout site volume rather than only at specific bonds, machine learning helps relate these global reactivity. Quantum theory of atoms molecules captures entire electron landscape, providing a chemically intuitive perspective field-driven Overall, methodologies show protein-generated highly dynamic heterogeneous, understanding both aspects is critical elucidating mechanisms. holistic view empowers rational engineering tuning promising new avenues drug design, biocatalysis, industrial applications. Future directions include incorporating as explicit design targets enhance catalytic performance biochemical functionalities.

Язык: Английский

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PyCPET─Computing Heterogeneous 3D Protein Electric Fields and Their Dynamics

Journal of Chemical Theory and Computation, Год журнала: 2025, Номер unknown

Опубликована: Апрель 8, 2025

Electrostatic preorganization is an exciting mode to understand the catalytic function of enzymes, yet limited tools exist computationally analyze it. In particular, no methods interpret geometry, dynamics, and fundamental components 3D electric fields, E⃗(r), in protein active sites. To address this, we present PyCPET (Python Computation Electric Field Topologies), a comprehensive, open-source toolbox E⃗(r) enzymes. We designed it around computational efficiency user friendliness with both CPU- GPU-accelerated codes. Our aim provide set functions for rich, descriptive analysis enzyme systems including benchmarking, distribution streamlines computation point principal component analysis, visualization. Finally, demonstrate its versatility by exploring nature electrostatic dynamics three cases: Cytochrome C, Co-substituted Liver Alcohol Dehydrogenase, HIV Protease. These test systems, along previous work, establish as essential toolkit in-depth visualization fields unlocking new avenues understanding contributions catalysis.

Язык: Английский

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Electron transfer engineering of artificially designed cell factory for complete biosynthesis of steroids

Nature Communications, Год журнала: 2025, Номер 16(1)

Опубликована: Апрель 21, 2025

Biosynthesis of steroids by artificially designed cell factories often involves numerous nicotinamide adenine dinucleotide phosphate (NADPH)-dependent enzymes that mediate electron transfer reactions. However, the unclear mechanisms from regeneration to final delivery NADPH-dependent active centers limit systematically engineering improve production. Here, we elucidate for engineer Saccharomyces cerevisiae, including step-by-step residues 7-Dehydrocholesterol reductase (DHCR7) and P450 sterol side chain cleaving enzyme (P450scc), components directing carbon flux, NADPH pathways, high-level production cholesterol (1.78 g/L) pregnenolone (0.83 g/L). The (ETE) process makes chains shorter more stable which significantly accelerates deprotonation proton coupled process. This study underscores significance ETE strategies in biosynthesis expands synthetic biology approaches.

Язык: Английский

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Machine-Learning Prediction of Protein Function from the Portrait of Its Intramolecular Electric Field

Journal of the American Chemical Society, Год журнала: 2024, Номер unknown

Опубликована: Окт. 7, 2024

We introduce a machine learning framework designed to predict enzyme functionality directly from the heterogeneous electric fields inherent protein active sites. apply this method curated data set of heme-iron oxidoreductases, spanning three classes: monooxygenases, peroxidases, and catalases. Conventional analysis, focused on simplistic, point along Fe–O bond, is shown be inadequate for accurate activity prediction. Our model demonstrates that enzyme's 3-D field, alone, can accurately its function, without relying additional protein-specific information. Through feature selection, we uncover key field components not only validate previous studies but also underscore crucial role multiple beyond traditionally emphasized bond in heme enzymes. Furthermore, by integrating dynamics, principal component clustering, QM/MM calculations, reveal while dynamic complexities structures obscure predictions, still retains accuracy. This research significantly advances our understanding how scaffolds possess signature tailored their functions at site. Moreover, it presents novel electrostatics-based tool harness these predicting function.

Язык: Английский

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Enhancing the specific activity of 3α-hydroxysteroid dehydrogenase through cross-regional combinatorial mutagenesis

International Journal of Biological Macromolecules, Год журнала: 2024, Номер 283, С. 137014 - 137014

Опубликована: Ноя. 1, 2024

Язык: Английский

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Machine-learning prediction of protein function from the portrait of its intramolecular electric field

Опубликована: Июнь 20, 2024

We introduce a machine learning framework designed to predict enzyme functionality directly from the heterogeneous electric fields inherent protein active sites. apply this method curated dataset of Heme-Iron Oxidoreductases, spanning three classes: monooxygenases, peroxidases, and catalases. Conventional analysis, focused on simplistic, point along Fe-O bond, are shown be inadequate for accurate activity prediction. Our model demonstrates that enzyme's heterogenous 3-D field, alone, can accurately its function, without relying additional protein-specific information. Through feature selection, we uncover key field components not only validate previous studies but also underscore crucial role multiple beyond traditionally emphasized bond in heme enzymes. Further, by integrating dynamics, principal component clustering, QM/MM calculations, reveal while dynamic complexities structures complicate predictions, accounting increased variability substantially enhance performance. This research significantly advances our understanding how scaffolds possess signature tailored their functions at site. Moreover, it presents novel electrostatics-based tool harness these predicting function.

Язык: Английский

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Excited-state symmetry breaking is an ultrasensitive tool for probing microscopic electric fields

Chemical Science, Год журнала: 2024, Номер 15(38), С. 15565 - 15576

Опубликована: Янв. 1, 2024

Microscopic electric fields are increasingly found to play a pivotal role in catalysis of enzymatic and chemical reactions. Currently, the vibrational Stark effect is main experimental method used measure them. Here, we demonstrate how excited-state symmetry breaking can serve as much more sensitive tool assess these fields. Using transient infrared spectroscopy on quadrupolar probe equipped with nitrile groups both its superior sensitivity that it does not suffer from notorious hydrogen-bond induced upshift C[triple bond, length m-dash]N stretch frequency. In combination conventional ground-state absorption, be disentangle even weak specific hydrogen bond interactions general field effects. We showcase this capability example C-H bonds polar aprotic solvents. Additionally, reveal for first time driven by solvent but entropy pendant side chains chromophore. Our findings only enhance our understanding symmetry-breaking charge-transfer phenomena pave way toward using them sensing modality.

Язык: Английский

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