CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed

The Journal of Physical Chemistry B, Год журнала: 2024, Номер 128(41), С. 9976 - 10042

Опубликована: Сен. 20, 2024

Since its inception nearly a half century ago, CHARMM has been playing central role in computational biochemistry and biophysics. Commensurate with the developments experimental research advances computer hardware, range of methods applicability have also grown. This review summarizes major that occurred after 2009 when last was published. They include following: new faster simulation engines, accessible user interfaces for convenient workflows, vast array analysis encompass quantum mechanical, atomistic, coarse-grained levels, as well extensive coverage force fields. In addition to providing current snapshot development, this may serve starting point exploring relevant theories tackling contemporary emerging problems biomolecular systems. is freely available academic nonprofit at https://academiccharmm.org/program.

Язык: Английский

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Puerarin—A Promising Flavonoid: Biosynthesis, Extraction Methods, Analytical Techniques, and Biological Effects

International Journal of Molecular Sciences, Год журнала: 2024, Номер 25(10), С. 5222 - 5222

Опубликована: Май 10, 2024

Flavonoids, a variety of plant secondary metabolites, are known for their diverse biological activities. Isoflavones subgroup flavonoids that have gained attention potential health benefits. Puerarin is one the bioactive isoflavones found in Kudzu root and Pueraria genus, which widely used alternative Chinese medicine, has been to be effective treating chronic conditions like cardiovascular diseases, liver gastric respiratory diabetes, Alzheimer’s disease, cancer. extensively researched both scientific clinical studies over past few years. The purpose this review provide an up-to-date exploration puerarin biosynthesis, most common extraction methods, analytical techniques, effects, new perspective medical pharmaceutical research development.

Язык: Английский

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Machine Learning Quantum Mechanical/Molecular Mechanical Potentials: Evaluating Transferability in Dihydrofolate Reductase-Catalyzed Reactions

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

Опубликована: Янв. 15, 2025

Integrating machine learning potentials (MLPs) with quantum mechanical/molecular mechanical (QM/MM) free energy simulations has emerged as a powerful approach for studying enzymatic catalysis. However, its practical application been hindered by the time-consuming process of generating necessary training, validation, and test data MLP models through QM/MM simulations. Furthermore, entire needs to be repeated each specific enzyme system reaction. To overcome this bottleneck, it is required that trained MLPs exhibit transferability across different environments reacting species, thereby eliminating need retraining new variant. In study, we explore potential evaluating pretrained ΔMLP model mutations within MM environment using QM/MM-based ML architecture developed Pan, X. J. Chem. Theory Comput. 2021, 17(9), 5745–5758. The study includes scenarios such single point substitutions, homologous from even transition an aqueous environment, where last two systems have substantially used in training. results show effectively captures predicts effects on electrostatic interactions, producing reliable profiles enzyme-catalyzed reactions without retraining. also identified notable limitations transferability, particularly when transitioning water-rich environments. Overall, demonstrates robustness Pan et al.'s diverse systems, well further research development more sophisticated training methods.

Язык: Английский

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Microbial lipases: advances in production, purification, biochemical characterization, and multifaceted applications in industry and medicine

Microbial Cell Factories, Год журнала: 2025, Номер 24(1)

Опубликована: Фев. 12, 2025

Abstract Lipases are biocatalysts of significant industrial and medical relevance, owing to their ability hydrolyze lipid substrates catalyze esterification reactions under mild conditions. This review provides a comprehensive overview microbial lipases’ production, purification, biochemical properties. It explores optimized fermentation strategies enhance enzyme yield, including using agro-industrial residues as substrates. The challenges associated with purification techniques such ultrafiltration, chromatography, precipitation discussed, alongside methods improve stability specificity. Additionally, the addresses growing importance genetic engineering approaches for improving lipase characteristics, activity, stability, this highlights diverse applications lipases in industries, food, pharmaceuticals, biofuels, cosmetics. enzyme’s role bioremediation, biodegradation, synthesis bioactive compounds is analyzed, emphasizing its potential sustainable eco-friendly technologies. biocatalytic properties make them ideal candidates green chemistry initiatives these industries. In biomedical domain, has shown promise drug delivery systems, anti-obesity treatments, diagnostics. insights into strategic development microbes cell factories production lipases, paving way future research innovations technology.

Язык: Английский

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A structural perspective on enzymes and their catalytic mechanisms

Current Opinion in Structural Biology, Год журнала: 2025, Номер 92, С. 103040 - 103040

Опубликована: Март 31, 2025

In this perspective, we analyse the progress made in our knowledge of enzyme sequences, structures and functions last 2 years. We review how much new data have been garnered annotated, derived from study proteins using structural computational approaches. Recent advances towards capturing 'Catalysis silico' are described, including predictions structures, their interactions mechanisms. highlight flood data, driven by metagenomic sequencing, improved resources, high coverage Protein Data Bank E.C. classes AI-driven structure prediction techniques that facilitate accurate protein structures. note focus on disordered regions context regulation specificity comment emerging bioinformatic approaches capture reaction mechanisms computationally for comparing predicting also consider drivers field next five

Язык: Английский

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CHARMM-GUI QM/MM Interfacer for a Quantum Mechanical and Molecular Mechanical (QM/MM) Simulation Setup: 1. Semiempirical Methods

Journal of Chemical Theory and Computation, Год журнала: 2024, Номер 20(12), С. 5337 - 5351

Опубликована: Июнь 10, 2024

Quantum mechanical (QM) treatments, when combined with molecular (MM) force fields, can effectively handle enzyme-catalyzed reactions without significantly increasing the computational cost. In this context, we present CHARMM-GUI QM/MM Interfacer, a web-based cyberinfrastructure designed to streamline preparation of various simulation inputs ligand modification. The development Interfacer has been achieved through integration existing modules, such as PDB Reader and Manipulator, Solution Builder, Membrane Builder. addition, new functionalities have developed facilitate one-stop systems enable interactive intuitive modifications QM atom selections. offers support for range semiempirical methods, including AM1(+/d), PM3(+/PDDG), MNDO(+/d, +/PDDG), PM6, RM1, SCC-DFTB, tailored both AMBER CHARMM. A nontrivial setup related modification, link-atom insertion, charge distribution is automatized user interfaces. To illustrate robustness conducted simulations three enzyme–substrate systems: dihydrofolate reductase, insulin receptor kinase, oligosaccharyltransferase. created tutorial videos about building these systems, which be found at https://www.charmm-gui.org/demo/qmi. expected valuable accessible tool that simplifies accelerates process hybrid simulations.

Язык: Английский

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Magnesium induced structural reorganization in the active site of adenylate kinase

Science Advances, Год журнала: 2024, Номер 10(32)

Опубликована: Авг. 9, 2024

Phosphoryl transfer is a fundamental reaction in cellular signaling and metabolism that requires Mg

Язык: Английский

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Utilizing Molecular Dynamics Simulations, Machine Learning, Cryo-EM, and NMR Spectroscopy to Predict and Validate Protein Dynamics

International Journal of Molecular Sciences, Год журнала: 2024, Номер 25(17), С. 9725 - 9725

Опубликована: Сен. 8, 2024

Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes. Recent advancements experimental techniques, computational methods, and artificial intelligence have revolutionized our understanding of protein dynamics. Nuclear magnetic resonance spectroscopy provides atomic-resolution insights, while molecular simulations offer detailed trajectories motions. Computational methods applied X-ray crystallography cryo-electron microscopy (cryo-EM) enabled the exploration dynamics, capturing ensembles that were previously unattainable. The integration machine learning, exemplified by AlphaFold2, has accelerated structure prediction analysis. These approaches revealed importance allosteric regulation, enzyme catalysis, intrinsically disordered proteins. shift towards ensemble representations structures application single-molecule techniques further enhanced ability capture dynamic nature Understanding is essential for elucidating mechanisms, designing drugs, developing novel biocatalysts, marking significant paradigm structural biology drug discovery.

Язык: Английский

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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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Discovery, design, and engineering of enzymes based on molecular retrobiosynthesis

mLife, Год журнала: 2025, Номер 4(2), С. 107 - 125

Опубликована: Март 28, 2025

Abstract Biosynthesis—a process utilizing biological systems to synthesize chemical compounds—has emerged as a revolutionary solution 21st‐century challenges due its environmental sustainability, scalability, and high stereoselectivity regioselectivity. Recent advancements in artificial intelligence (AI) are accelerating biosynthesis by enabling intelligent design, construction, optimization of enzymatic reactions systems. We first introduce the molecular retrosynthesis route planning biochemical pathway including single‐step algorithms AI‐based design tools. highlight advantages large language models addressing sparsity data. Furthermore, we review enzyme discovery methods based on sequence structure alignment techniques. Breakthroughs structural prediction expected significantly improve accuracy discovery. also summarize for de novo generation nonnatural or orphan reactions, focusing functional annotation techniques reaction small molecule similarity. Turning engineering, discuss strategies thermostability, solubility, activity, well applications AI these fields. The shift from traditional experiment‐driven data‐driven computationally driven is already underway. Finally, present potential provide perspective future research directions. envision expanded biocatalysis drug development, green chemistry, complex synthesis.

Язык: Английский

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