Perspectives on Ligand/Protein Binding Kinetics Simulations: Force Fields, Machine Learning, Sampling, and User-Friendliness

Journal of Chemical Theory and Computation, Journal Year: 2023, Volume and Issue: 19(18), P. 6047 - 6061

Published: Sept. 1, 2023

Computational techniques applied to drug discovery have gained considerable popularity for their ability filter potentially active drugs from inactive ones, reducing the time scale and costs of preclinical investigations. The main focus these studies has historically been search compounds endowed with high affinity a specific molecular target ensure formation stable long-lasting complexes. Recent evidence also correlated in vivo efficacy its binding kinetics, thus opening new fascinating scenarios ligand/protein kinetic simulations discovery. present article examines state art field, providing brief summary most popular advanced kinetics evaluating current limitations potential solutions reach more accurate models. Particular emphasis is put on need paradigm change methodologies toward ligand protein parametrization, force field problem, characterization transition states, sampling issue, algorithms' performance, user-friendliness, data openness.

Language: Английский

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Enhanced sampling strategies for molecular simulation of DNA

Wiley Interdisciplinary Reviews Computational Molecular Science, Journal Year: 2024, Volume and Issue: 14(2)

Published: March 1, 2024

Abstract Molecular dynamics (MD) simulations can provide detailed insights into complex molecular systems, such as DNA, at high resolution in space and time. Using current computer architectures, time scales of tens microseconds are feasible with contemporary all‐atom force fields. However, these timescales insufficient to accurately characterize large conformational transitions DNA compare calculations experimental data. This review discusses the advantages drawbacks two simulation approaches overcome timescale challenge. The first approach is based on adding biasing potentials system drive transitions. Umbrella sampling, steered MD, metadynamics examples methods. A key challenge methods necessity selecting one or a few efficient coordinates, commonly referred collective variables (CVs), along which apply potential. path‐metadynamics methodology addresses this issue by finding optimal route(s) between states multi‐dimensional CV space. second strategy path focuses MD assumption that even though rare, they generally fast. Stopping soon reach stable state significantly increase efficiency. We introduce two‐dimensional Müller–Brown applications featured for different processes: Watson–Crick–Franklin Hoogsteen transition adenine–thymine base pairs binding DNA‐binding protein domain DNA. article categorized under: Statistical Mechanics Dynamics Monte‐Carlo Methods Free Energy Software Simulation

Language: Английский

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The use of collective variables and enhanced sampling in the simulations of existing and emerging microporous materials

Nanoscale, Journal Year: 2024, Volume and Issue: 16(19), P. 9186 - 9196

Published: Jan. 1, 2024

This review summarizes how enhanced sampling methods are used to investigate the complex properties of microporous materials.

Language: Английский

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Recent Advances in Computer-Aided Structure-Based Drug Design on Ion Channels

International Journal of Molecular Sciences, Journal Year: 2023, Volume and Issue: 24(11), P. 9226 - 9226

Published: May 25, 2023

Ion channels play important roles in fundamental biological processes, such as electric signaling cells, muscle contraction, hormone secretion, and regulation of the immune response. Targeting ion with drugs represents a treatment option for neurological cardiovascular diseases, muscular degradation disorders, pathologies related to disturbed pain sensation. While there are more than 300 different human organism, have been developed only some them currently available lack selectivity. Computational approaches an indispensable tool drug discovery can speed up, especially, early development stages lead identification optimization. The number molecular structures has considerably increased over last ten years, providing new opportunities structure-based development. This review summarizes knowledge about channel classification, structure, mechanisms, pathology main focus on recent developments field computer-aided, design channels. We highlight studies that link structural data modeling chemoinformatic characterization molecules targeting These hold great potential advance research future.

Language: Английский

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Unravelling the interactions between small molecules and liposomal bilayers via molecular dynamics and thermodynamic modelling

International Journal of Pharmaceutics, Journal Year: 2024, Volume and Issue: 660, P. 124367 - 124367

Published: June 18, 2024

Lipid-based drug delivery systems hold immense promise in addressing critical medical needs, from cancer and neurodegenerative diseases to infectious diseases. By encapsulating active pharmaceutical ingredients - ranging small molecule drugs proteins nucleic acids these nanocarriers enhance treatment efficacy safety. However, their commercial success faces hurdles, such as the lack of a systematic design approach issues related scalability reproducibility. This work aims provide insights into drug-phospholipid interaction by combining molecular dynamic simulations thermodynamic modelling techniques. In particular, we have made connection between structural properties system physicochemical performance drug-loaded liposomal nanoformulations. We considered two prototypical drugs, felodipine (FEL) naproxen (NPX), one model hydrogenated soy phosphatidylcholine (HSPC) bilayer membrane. Molecular revealed which regions within phospholipid bilayers are most least favoured molecules. NPX tends reside at water-phospholipid interface is characterized lower free energy barrier for membrane permeation. Meanwhile, FEL prefers sit hydrophobic tails phospholipids higher Flory-Huggins modelling, angle X-ray scattering, light TEM, release studies nanoformulations confirmed this difference. The naproxen-phospholipid has permeation, miscibility with bilayer, larger nanoparticle size, faster aqueous medium than felodipine. suggest that combination dynamics thermodynamics may offer new tool designing developing lipid-based unmet applications.

Language: 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, Journal Year: 2024, Volume and Issue: 25(17), P. 9725 - 9725

Published: Sept. 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.

Language: Английский

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All-around local structure classification with supervised learning: The example of crystal phases and dislocations in complex oxides

Computer Physics Communications, Journal Year: 2025, Volume and Issue: 309, P. 109480 - 109480

Published: Jan. 8, 2025

Language: 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, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 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.

Language: Английский

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Foundations of molecular dynamics simulations: how and what

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

Published: Feb. 28, 2025

Abstract In this review, we discuss computational methods to study condensed matter systems and processes occurring in phase. We begin by laying down the theoretical framework of statistical mechanics starting from fundamental laws governing nuclei electrons. Among others, present connection between thermodynamics using a pure language, which makes it easier extend microscopic interpretation thermodynamic potentials other relevant quantities, such as Landau free energy (also known potential mean force). Computational for estimating quantities equilibrium non-equilibrium systems, well reactive events, are discussed. An extended Appendix is added, where artificial intelligence recently introduced. These can enhance power atomistic simulations, allowing achieve at same time accuracy efficiency calculation interest.

Language: Английский

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Unsupervised Learning of Progress Coordinates during Weighted Ensemble Simulations: Application to NTL9 Protein Folding

Journal of Chemical Theory and Computation, Journal Year: 2025, Volume and Issue: unknown

Published: March 19, 2025

A major challenge for many rare-event sampling strategies is the identification of progress coordinates that capture slowest relevant motions. Machine-learning methods can identify in an unsupervised manner have therefore been great interest to simulation community. Here, we developed a general method identifying "on-the-fly" during weighted ensemble (WE) via deep learning (DL) outliers among sampled conformations. Our identifies latent space model system's conformations periodically trained using convolutional variational autoencoder. As proof principle, applied our DL-enhanced WE simulate NTL9 protein folding process. To enable rapid tests, simulations propagated discrete-state synthetic molecular dynamics trajectories generative, fine-grained Markov state model. Results revealed on-the-fly DL enhanced efficiency by >3-fold estimating rate constant. efforts are significant step forward slow rare event sampling.

Language: Английский

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