Journal of Chemical Theory and Computation最新文献

Pothos: A Python Package for Polymer Chain Orientation and Microstructure Evolution Monitoring.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-12-23 DOI: 10.1021/acs.jctc.4c01216

Thomas J Barrett, Marilyn L Minus

引用次数: 0

Development of Molecular Dynamics Parameters and Theoretical Analysis of Excitonic and Optical Properties in the Light-Harvesting Complex II.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-12-20 DOI: 10.1021/acs.jctc.4c01214

Zhe Zhu, Masahiro Higashi, Shinji Saito

{"title":"Development of Molecular Dynamics Parameters and Theoretical Analysis of Excitonic and Optical Properties in the Light-Harvesting Complex II.","authors":"Zhe Zhu, Masahiro Higashi, Shinji Saito","doi":"10.1021/acs.jctc.4c01214","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01214","url":null,"abstract":"The light-harvesting complex II (LHCII) in green plants exhibits highly efficient excitation energy transfer (EET). A comprehensive understanding of the EET mechanism in LHCII requires quantum chemical, molecular dynamics (MD), and statistical mechanics calculations that can adequately describe pigment molecules in heterogeneous environments. Herein, we develop MD simulation parameters that accurately reproduce the quantum mechanical/molecular mechanical energies of both the ground and excited states of all chlorophyll (Chl) molecules in membrane embedded LHCII. The present simulations reveal that Chl a molecules reside in more inhomogeneous environments than Chl b molecules. We also find a narrow gap between the exciton energy levels of Chl a and Chl b. In addition, we investigate the nature of the exciton states of Chl molecules, such as delocalization, and analyze the optical spectra of LHCII, which align with experimental results. Thus, the MD simulation parameters developed in this study successfully reproduce the excitonic and optical properties of the Chl molecules in LHCII, validating their effectiveness.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142869272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

BioStructNet: Structure-Based Network with Transfer Learning for Predicting Biocatalyst Functions.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-12-20 DOI: 10.1021/acs.jctc.4c01391

Xiangwen Wang, Jiahui Zhou, Jane Mueller, Derek Quinn, Alexandra Carvalho, Thomas S Moody, Meilan Huang

{"title":"BioStructNet: Structure-Based Network with Transfer Learning for Predicting Biocatalyst Functions.","authors":"Xiangwen Wang, Jiahui Zhou, Jane Mueller, Derek Quinn, Alexandra Carvalho, Thomas S Moody, Meilan Huang","doi":"10.1021/acs.jctc.4c01391","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01391","url":null,"abstract":"Enzyme-substrate interactions are essential to both biological processes and industrial applications. Advanced machine learning techniques have significantly accelerated biocatalysis research, revolutionizing the prediction of biocatalytic activities and facilitating the discovery of novel biocatalysts. However, the limited availability of data for specific enzyme functions, such as conversion efficiency and stereoselectivity, presents challenges for prediction accuracy. In this study, we developed BioStructNet, a structure-based deep learning network that integrates both protein and ligand structural data to capture the complexity of enzyme-substrate interactions. Benchmarking studies with different algorithms showed the enhanced predictive accuracy of BioStructNet. To further optimize the prediction accuracy for the small data set, we implemented transfer learning in the framework, training a source model on a large data set and fine-tuning it on a small, function-specific data set, using the CalB data set as a case study. The model performance was validated by comparing the attention heat maps generated by the BioStructNet interaction module with the enzyme-substrate interactions revealed from molecular dynamics simulations of enzyme-substrate complexes. BioStructNet would accelerate the discovery of functional enzymes for industrial use, particularly in cases where the training data sets for machine learning are small.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient Polarizable QM/MM Using the Direct Reaction Field Hamiltonian with Electrostatic Potential Fitted Multipole Operators.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-12-20 DOI: 10.1021/acs.jctc.4c01219

Thomas P Fay, Nicolas Ferré, Miquel Huix-Rotllant

{"title":"Efficient Polarizable QM/MM Using the Direct Reaction Field Hamiltonian with Electrostatic Potential Fitted Multipole Operators.","authors":"Thomas P Fay, Nicolas Ferré, Miquel Huix-Rotllant","doi":"10.1021/acs.jctc.4c01219","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01219","url":null,"abstract":"Electronic polarization and dispersion are decisive actors in determining interaction energies between molecules. These interactions have a particularly profound effect on excitation energies of molecules in complex environments, especially when the excitation involves a significant degree of charge reorganization. The direct reaction field (DRF) approach, which has seen a recent revival of interest, provides a powerful framework for describing these interactions in quantum mechanics/molecular mechanics (QM/MM) models of systems, where a small subsystem of interest is described using quantum chemical methods and the remainder is treated with a simple MM force field. In this paper we show how the DRF approach can be combined with the electrostatic potential fitted (ESPF) multipole operator description of the QM region charge density, which significantly improves the efficiency of the method, particularly for large MM systems, and for typical calculations effectively eliminates the dependence on MM system size. We also show how the DRF approach can be combined with fluctuating charge descriptions of the polarizable environment, as well as previously used atom-centered dipole-polarizability based models. We further show that the ESPF-DRF method provides an accurate description of molecular interactions in both ground and excited electronic states of the QM system and apply it to predict the gas to aqueous solution solvatochromic shifts in the UV/visible absorption spectrum of acrolein.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A General and Transferable Local Hybrid Functional for Electronic Structure Theory and Many-Fermion Approaches.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-12-20 DOI: 10.1021/acs.jctc.4c01309

Christof Holzer, Yannick J Franzke

{"title":"A General and Transferable Local Hybrid Functional for Electronic Structure Theory and Many-Fermion Approaches.","authors":"Christof Holzer, Yannick J Franzke","doi":"10.1021/acs.jctc.4c01309","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01309","url":null,"abstract":"Density functional theory has become the workhorse of quantum physics, chemistry, and materials science. Within these fields, a broad range of applications needs to be covered. These applications range from solids to molecular systems, from organic to inorganic chemistry, or even from electrons to other Fermions, such as protons or muons. This is emphasized by the plethora of density functional approximations that have been developed for various cases. In this work, two new local hybrid exchange-correlation density functionals are constructed from first-principles, promoting generality and transferability. We show that constraint satisfaction can be achieved even for admixtures with full exact exchange, without sacrificing accuracy. The performance of the new functionals CHYF-PBE and CHYF-B95 is assessed for thermochemical properties, excitation energies, Mössbauer isomer shifts, NMR spin-spin coupling constants, NMR shieldings and shifts, magnetizabilities, and EPR hyperfine coupling constants. Here, the new density functional shows excellent performance throughout all tests and is numerically robust only requiring small grids for converged results. Additionally, both functionals can easily be generalized to arbitrary Fermions as shown for electron-proton correlation energies. Therefore, we outline that density functionals generated in this way are general purpose tools for quantum mechanical studies.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Flow Matching for Optimal Reaction Coordinates of Biomolecular Systems.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-12-19 DOI: 10.1021/acs.jctc.4c01139

Mingyuan Zhang, Zhicheng Zhang, Hao Wu, Yong Wang

{"title":"Flow Matching for Optimal Reaction Coordinates of Biomolecular Systems.","authors":"Mingyuan Zhang, Zhicheng Zhang, Hao Wu, Yong Wang","doi":"10.1021/acs.jctc.4c01139","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01139","url":null,"abstract":"We present flow matching for reaction coordinates (FMRC), a novel deep learning algorithm designed to identify optimal reaction coordinates (RC) in biomolecular reversible dynamics. FMRC is based on the mathematical principles of lumpability and decomposability, which we reformulate into a conditional probability framework for efficient data-driven optimization using deep generative models. While FMRC does not explicitly learn the well-established transfer operator or its eigenfunctions, it can effectively encode the dynamics of leading eigenfunctions of the system transfer operator into its low-dimensional RC space. We further quantitatively compare its performance with several state-of-the-art algorithms by evaluating the quality of Markov state models (MSM) constructed in their respective RC spaces, demonstrating the superiority of FMRC in three increasingly complex biomolecular systems. In addition, we successfully demonstrated the efficacy of FMRC for bias deposition in the enhanced sampling of a simple model system. Finally, we discuss its potential applications in downstream applications such as enhanced sampling methods and MSM construction.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142851621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Absolute and Relative Binding Free Energy Calculations of Nucleotides to Multiple Protein Classes.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-12-19 DOI: 10.1021/acs.jctc.4c01440

Apoorva Purohit, Xiaolin Cheng

{"title":"Absolute and Relative Binding Free Energy Calculations of Nucleotides to Multiple Protein Classes.","authors":"Apoorva Purohit, Xiaolin Cheng","doi":"10.1021/acs.jctc.4c01440","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01440","url":null,"abstract":"Polyphosphate nucleotides, such as ATP, ADP, GTP, and GDP, play a crucial role in modulating protein functions through binding and/or catalytically activating proteins (enzymes). However, accurately calculating the binding free energies for these charged and flexible ligands poses challenges due to slow conformational relaxation and the limitations of force fields. In this study, we examine the accuracy and reliability of alchemical free energy simulations with fixed-charge force fields for the binding of four nucleotides to nine proteins of various classes, including kinases, ATPases, and GTPases. Our results indicate that the alchemical simulations effectively reproduce experimental binding free energies for all proteins that do not undergo significant conformational changes between their triphosphate nucleotide-bound and diphosphate nucleotide-bound states, with 87.5% (7 out of 8) of the absolute binding free energy results for 4 proteins within ±2 kcal/mol of experimental values and 88.9% (8 out of 9) of the relative binding free energy results for 9 proteins within ±3 kcal/mol of experimental values. However, our calculations show significant inaccuracies when divalent ions are included, suggesting that nonpolarizable force fields may not accurately capture interactions involving these ions. Additionally, the presence of highly charged and flexible ligands necessitates extensive conformational sampling to account for the long relaxation times associated with long-range electrostatic interactions. The simulation strategy presented here, along with its demonstrated accuracy across multiple protein classes, will be valuable for predicting the binding of nucleotides or their analogs to protein targets.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142851615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Equipartitioning of Molecular Degrees of Freedom in MD Simulations of Gaseous Systems via an Advanced Thermostatization Strategy.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-12-19 DOI: 10.1021/acs.jctc.4c01580

Jakob Gamper, Josef M Gallmetzer, Risnita Vicky Listyarini, Alexander K H Weiss, Thomas S Hofer

{"title":"Equipartitioning of Molecular Degrees of Freedom in MD Simulations of Gaseous Systems via an Advanced Thermostatization Strategy.","authors":"Jakob Gamper, Josef M Gallmetzer, Risnita Vicky Listyarini, Alexander K H Weiss, Thomas S Hofer","doi":"10.1021/acs.jctc.4c01580","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01580","url":null,"abstract":"This work introduces a dedicated thermostatization strategy for molecular dynamics simulations of gaseous systems. The proposed thermostat is based on the stochastic canonical velocity rescaling approach by Bussi and co-workers and is capable of ensuring an equal distribution of the kinetic energy among the translational, rotational, and vibrational degrees of freedom. The outlined framework ensures the correct treatment of the kinetic energy in gaseous systems, which is typically not the case in standard approaches due to the limited number of collisions between particles associated with a large free mean path. Additionally, an efficient strategy to effectively correct for intramolecular contributions to the virial in quantum mechanical simulations is presented. The equipartitioning thermostat was successfully tested by the determination of pV diagrams for carbon dioxide and methane at the density functional tight binding level of theory. The results unequivocally demonstrate that the equipartitioning thermostat can effectively achieve an equal distribution of the kinetic energy among the different degrees of freedom, thereby ensuring correct pressure in gaseous systems. Furthermore, RDF calculations show the capability of the proposed method to accurately depict the structure of gaseous systems, as well as enable an adequate treatment of gas molecules under confinement, as exemplified by an MD simulation of (CO2)50@MOF-5.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142851619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Calculation of Adsorbate Free Energy Using the Damping Function Method.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-12-19 DOI: 10.1021/acs.jctc.4c01079

Yanhua Lei, Lei Liu, Erjun Zhang

{"title":"Calculation of Adsorbate Free Energy Using the Damping Function Method.","authors":"Yanhua Lei, Lei Liu, Erjun Zhang","doi":"10.1021/acs.jctc.4c01079","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01079","url":null,"abstract":"Adsorbate free energies are important parameters in surface chemistry and catalysis. Because of its simplicity, the harmonic oscillator (HO) model remains the most widely used method for calculating adsorbate free energy in many fields, including microkinetic modeling. However, it is well-known that the HO method is ineffective for weak adsorption. In this study, we propose a translational model with a diffusion barrier to calculate the state functions of near free translation. Furthermore, an effective mass is introduced in this model. To address hindered translation uniformly, a diffusion barrier-based damping function (DF) is proposed that effectively links the harmonic vibration and translation limits. Adsorbates are divided into three categories according to their adsorption strength and diffusion barrier height. Adsorbed hydrogen atoms have a strong binding energy and relatively high vibrational frequency but a low diffusion barrier. The HT and our proposed DF methods predict that the adsorbed hydrogen atoms behave as translation above room temperature, while the previous DF method predicts that they behave as vibration at any temperature. At last, the dehydrogenation reaction of propane on the Pt(111) surface was taken as an example to illustrate the influence of different methods on the thermodynamic functions.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142851616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AlphaMut: A Deep Reinforcement Learning Model to Suggest Helix-Disrupting Mutations.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2024-12-19 DOI: 10.1021/acs.jctc.4c01387

Prathith Bhargav, Arnab Mukherjee

引用次数: 0