Zooming across the Alchemical Space DOI

Mengchen Zhou,

Xueguang Shao, Wensheng Cai

et al.

The Journal of Physical Chemistry Letters, Journal Year: 2025, Volume and Issue: unknown, P. 4419 - 4427

Published: April 24, 2025

Alchemical transformations, whereby chemical species are modified seamlessly, represent a powerful tool in molecular simulations and free-energy calculations, with broad range of applications. A general-extent, or alchemical parameter, λ ∈ [0,1], describes the gradual transition between initial final states transformation, its discretization critically affects reliability efficiency calculations. For transformations involving large moieties, perturbation (FEP) thermodynamic integration (TI) require numerous intermediates, λ-states, to ensure appropriate overlap configurational ensembles suitable convergence simulation, each state demanding extensive sampling, which burdens computational feasibility. To address this limitation, we combine λ-dynamics─treating as dynamic variable─with enhanced-sampling approach well-tempered metadynamics-extended adaptive biasing force (WTM-eABF), forming basis WTM-λABF. By handling continuously varying collective variable (CV) applying bin-discretized bias, WTM-λABF efficiently explores λ-space, even when latter is stratified intermediates. Calculations free-energies hydration, protein-ligand binding, amino-acid mutations proteins reveal that consistently converges faster than standard FEP λ-ABF, advantages becoming more pronounced number intermediates rises. We find can handle many 1,000 allowing significant potential-energy changes, be tackled utmost accuracy. Additionally, rapid exploration continuous λ-space accelerates sampling orthogonal space. confident has potential serve foundational method for routine applications relevant chemistry biophysics, ranging from drug discovery protein engineering design.

Language: Английский

A thermodynamic cycle to predict the competitive inhibition outcomes of an evolving enzyme DOI Creative Commons
Ebru Çetin, Haleh Abdizadeh, Ali Rana Atılgan

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 7, 2025

Abstract Understanding competitive inhibition at the molecular level is essential for unraveling dynamics of enzyme-inhibitor interactions and predicting evolutionary outcomes resistance mutations. In this study, we present a framework linking to alchemical free energy perturbation (FEP) calculations, focusing on E. coli dihydrofolate reductase (DHFR) its by trimethoprim (TMP). Using thermodynamic cycles, relate experimentally measured binding constants ( K i m ) differences associated with wild-type mutant forms DHFR mean error 0.9 kcal/mol, providing insights into underpinnings TMP resistance. Our findings highlight importance local conformational in inhibition. Mutations affect substrate inhibitor affinities differently, influencing fitness landscape under selective pressure from TMP. FEP simulations reveal that mutations stabilize inhibitor-bound or substrate-bound states through specific structural and/or dynamical effects. The interplay these effects showcases significant epistasis certain cases. ability separately assess provides valuable insights, allowing more precise interpretation mutation epistatic interactions. Furthermore, identify key challenges simulations, including convergence issues arising charge-changing long-range allosteric By integrating computational experimental data, provide an effective approach functional impact their contributions landscapes. These pave way constructing robust mutational scanning protocols designing therapeutic strategies against resistant bacterial strains.

Language: Английский

Citations

0
Divide-and-Conquer ABFE: Improving Free Energy Calculations by Enhancing Water Sampling DOI
Runduo Liu,

Yufen Yao,

Wanyi Huang

et al.

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

Published: March 24, 2025

Free energy perturbation (FEP) is a promising method for accurately predicting molecular interactions, widely applied in fields such as drug design, materials science, and catalysis. However, FEP calculations, particularly those aqueous environments, often suffer from convergence issues due to insufficient sampling of water molecules. These challenges are critical solvation-related free small molecule-protein binding, interface adsorption on surfaces. To address these limitations, we present the divide-and-conquer absolute binding (DC-ABFE) method. By partitioning ligand or molecule into atomic groups sequentially decoupling their van der Waals DC-ABFE improves re-entry sampling, enhances phase-space overlap, significantly calculations. Our benchmark demonstrates that achieves more reproducible reliable predictions compared traditional methods. applicable range calculations involving solvation effects. Additionally, this establishes stronger foundation precise screening, offering robust tool affinities discovery.

Language: Английский

Citations

0
A Thermodynamic Cycle to Predict the Competitive Inhibition Outcomes of an Evolving Enzyme DOI Creative Commons
Ebru Çetin, Haleh Abdizadeh, Ali Rana Atılgan

et al.

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

Published: April 23, 2025

Understanding competitive inhibition at the molecular level is essential for unraveling dynamics of enzyme-inhibitor interactions and predicting evolutionary outcomes resistance mutations. In this study, we present a framework linking to alchemical free energy perturbation (FEP) calculations, focusing on Escherichia coli dihydrofolate reductase (DHFR) its by trimethoprim (TMP). Using thermodynamic cycles, relate experimentally measured binding constants (Ki Km) differences associated with wild-type mutant forms DHFR mean error 0.9 kcal/mol, providing insight into underpinnings TMP resistance. Our findings highlight importance local conformational in inhibition. Mutations affect substrate inhibitor affinities differently, influencing fitness landscape under selective pressure from TMP. FEP simulations reveal that mutations stabilize inhibitor-bound or substrate-bound states through specific structural and/or dynamical effects. The interplay these effects showcases significant molecular-level epistasis certain cases. ability separately assess provides valuable insights, allowing more precise interpretation mutation epistatic interactions. Furthermore, identify key challenges simulations, including convergence issues arising charge-changing long-range allosteric By integrating computational experimental data, provide an effective approach functional impact their contributions landscapes. These insights pave way constructing robust mutational scanning protocols designing therapeutic strategies against resistant bacterial strains.

Language: Английский

Citations

0
Zooming across the Alchemical Space DOI

Mengchen Zhou,

Xueguang Shao, Wensheng Cai

et al.

The Journal of Physical Chemistry Letters, Journal Year: 2025, Volume and Issue: unknown, P. 4419 - 4427

Published: April 24, 2025

Alchemical transformations, whereby chemical species are modified seamlessly, represent a powerful tool in molecular simulations and free-energy calculations, with broad range of applications. A general-extent, or alchemical parameter, λ ∈ [0,1], describes the gradual transition between initial final states transformation, its discretization critically affects reliability efficiency calculations. For transformations involving large moieties, perturbation (FEP) thermodynamic integration (TI) require numerous intermediates, λ-states, to ensure appropriate overlap configurational ensembles suitable convergence simulation, each state demanding extensive sampling, which burdens computational feasibility. To address this limitation, we combine λ-dynamics─treating as dynamic variable─with enhanced-sampling approach well-tempered metadynamics-extended adaptive biasing force (WTM-eABF), forming basis WTM-λABF. By handling continuously varying collective variable (CV) applying bin-discretized bias, WTM-λABF efficiently explores λ-space, even when latter is stratified intermediates. Calculations free-energies hydration, protein-ligand binding, amino-acid mutations proteins reveal that consistently converges faster than standard FEP λ-ABF, advantages becoming more pronounced number intermediates rises. We find can handle many 1,000 allowing significant potential-energy changes, be tackled utmost accuracy. Additionally, rapid exploration continuous λ-space accelerates sampling orthogonal space. confident has potential serve foundational method for routine applications relevant chemistry biophysics, ranging from drug discovery protein engineering design.

Language: Английский

Citations

0