Journal of Computational Chemistry最新文献

{"title":"Quantifying the Cooperativity of Backbone Hydrogen Bonding","authors":"You Xu,&nbsp;Jing Huang","doi":"10.1002/jcc.70133","DOIUrl":"https://doi.org/10.1002/jcc.70133","url":null,"abstract":"<div>\u0000 \u0000 <p>The hydrogen bonds (H-bonds) between backbone amide and carbonyl groups are fundamental to the stability, structure, and dynamics of proteins. A key feature of such hydrogen bonding interactions is that multiple H-bonds can enhance each other when aligned, as such in the <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>α</mi>\u0000 </mrow>\u0000 <annotation>$$ alpha $$</annotation>\u0000 </semantics></math>-helix or <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>β</mi>\u0000 </mrow>\u0000 <annotation>$$ beta $$</annotation>\u0000 </semantics></math>-sheet secondary structures. To better understand this cooperative effect, we propose a new physical quantity to evaluate the cooperativity of intermolecular interactions. Using H-bond aligned N-methylacetamide molecules as the model system, we assess the cooperativity of protein backbone hydrogen bonds using quantum chemistry (QM) calculations at the MP2/aug-cc-pVTZ level, revealing cooperative energies ranging from 2 to 4.3 kcal/mol. A set of protein force fields was benchmarked against QM results. While the additive force field failed to reproduce cooperativity, polarizable force fields, including the Drude and AMOEBA protein force fields, have been found to reproduce the trend of QM results, albeit with smaller magnitude. This work demonstrates the theoretical utility of the proposed formula for quantifying cooperativity and its relevance in force field parameterization. Incorporating cooperative energy into polarizable models presents a pathway to achieving more accurate simulations of biomolecular systems.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 14","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144085102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-Covalent Molecular Interaction Rules to Define Internal Dimer Coordinates for Quantum Mechanical Potential Energy Scans","authors":"Suliman Sharif,&nbsp;Anmol Kumar,&nbsp;Alexander D. MacKerell Jr.","doi":"10.1002/jcc.70136","DOIUrl":"10.1002/jcc.70136","url":null,"abstract":"<p>Non-covalent interactions (NCI) dominate the properties of condensed phase systems. Towards a detailed understanding of NCI, quantum mechanical (QM) methods allow for accurate estimates of interaction energies and geometries, allowing for the contributions of different types of NCI to condensed phase properties to be understood. In addition, such information can be used for the optimization of empirical force fields, including the specific contribution of electrostatic versus van der Waals interactions. However, to date, the relative orientation of monomers defining molecular interactions of dimers is often based on full geometry optimizations of all degrees of freedom or extracted from known experimental structures of biological molecules. In such cases, the spatial relationship of the monomers often leads to multiple atoms in each monomer making significant contributions to the interactions occurring in the dimer, confounding understanding of the contributions of specific atoms or functional groups. To overcome this, a workflow is presented that allows for systematic control of the interaction orientation between monomers to be performed through the use of molecular interaction rules (MIR) in an extendable tool that can be applied to a broad range of chemical space. Using the “MIR workflow” allows a user to perform automation of the determination of well-defined monomer interaction orientations in dimers using Z-matrices, allowing for potential energy scans (PES) to be performed on combinatorial pairs of the monomers. In addition, compiled monomer and dimer geometries and PES data are stored in an extendable database. Illustration of the utility of the workflow is performed based on a collection of 89 monomers encompassing a variety of functional group classes from which 10,616 interaction dimers can be automatically generated. PES between all dimers were calculated at the QM HF/6-31G*, MP2/6-31G*, and ωb97x-d3/6-31G* model chemistries. In addition, analysis of the benzene dimer in three interaction orientations, a hydrogen bond interaction between azetidinone and <i>N</i>-methylacetamide, and the interaction of pyridine with acetone in the Burgi–Dunitz orientation are presented including results with the aug-cc-pVDZ basis set. Results show the impact of different QM model chemistries on minimum interaction energies and distances over a large ensemble of intermolecular interactions with emphasis on the contributions of dispersion.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 14","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70136","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144066549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing Many-Body Charge Transfer Effects With the Fragment Molecular Orbital Method","authors":"Dmitri G. Fedorov","doi":"10.1002/jcc.70128","DOIUrl":"https://doi.org/10.1002/jcc.70128","url":null,"abstract":"<p>A many-body expansion of charge transfer (CT) energies is developed for the fragment molecular orbital method. It is applied to decouple CT and mix terms in interaction energy decomposition analyses. Many-body charge transfer is graphically illustrated in the form of frontier orbital diagrams. The contribution of CT to molecular interactions is elucidated in the application of the method to water clusters, solvated ions, and polypeptide motifs.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 13","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70128","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143950295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Practical Machine Learning Strategies. 2. Accurate Prediction of ωB97X-V/6-311+G(2df,2p), ωB97M-V/6-311+G(2df,2p) and ωB97M(2)/6-311+G(2df,2p) Energies From Neural Networks Trained From ωB97X-D/6-31G* Equilibrium Geometries and Energies","authors":"Philip Klunzinger,&nbsp;Thomas Hehre,&nbsp;Bernard Deppmeier,&nbsp;William Ohlinger,&nbsp;Warren Hehre","doi":"10.1002/jcc.70129","DOIUrl":"https://doi.org/10.1002/jcc.70129","url":null,"abstract":"<div>\u0000 \u0000 <p>Starting from ωB97X-D/6-31G* geometries and energies, neural network models have been trained to reproduce energies from three density functionals: ωB97X-V, ωB97M-V, and ωB97M(2), using the 6-311+G(2df,2p) basis set. Training sets on the order of 300 k organic molecules were utilized [≈295,000 molecules for the ωB97X-V functional (up to molecular weight 400 amu); and ≈289,000 molecules for both the ωB97M-V and ωB97M(2) functionals (up to molecular weight 380 amu)]. All training and validation molecules comprise uncharged, closed shell singlets including H, C, N, O, F, S, Cl, and Br (only). The resulting models have been assessed using molecules outside the training sets. Total energies obtained from the neural network models rarely differ from the corresponding density functional values by more than 2–5 kJ/mol (RMS), while differences in conformer energies are typically less than 1 kJ/mol.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 13","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143944704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Probe-Related Correlations on Local Electrostatic Potentials Around DNA","authors":"Chuanying Chen,&nbsp;Binhan Yu,&nbsp;Xi Wang,&nbsp;Junji Iwahara,&nbsp;B. Montgomery Pettitt","doi":"10.1002/jcc.70125","DOIUrl":"https://doi.org/10.1002/jcc.70125","url":null,"abstract":"<div>\u0000 \u0000 <p>In this work, we perform a test of effectiveness and accuracy of using different approximations to interpret NMR paramagnetic relaxation enhancements experiment to measure local electrostatic potentials for DNA at ionic strengths from 0.138 to 0.938 M in KCl salt solution with PROXYL spin probes. Continuum Poisson-Boltzmann (PB) theory, multiscale Brownian dynamics, and all-atom molecular dynamics simulations are carried out to predict and interpret local potentials. Local potentials around DNA demonstrate strong salt dependence. Experimental results are in good agreement at 0.138 M ionic strength with continuum theory and simulation. Compared to experiment, the PB and multiscale simulation methods overestimate local potentials in magnitude at medium to high salt concentration. We find that the overestimate is mainly caused by ignoring the probe-probe and probe-ions correlations in the proximity of DNA. The probe-related correlations can be up to 0.4 kcal/mol in certain regions. Comparisons of the experiment and the calculations emphasize not only the importance of orientations of probes but also the probe-related correlations in determination of near-surface-zone potentials.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 13","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143944699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modulation of the Product Upon the Reaction of CO2 With Dimethylamine Cluster: A Topological Analysis of the Reaction Mechanism","authors":"Mohammad Esmaïl Alikhani,&nbsp;Bernard Silvi","doi":"10.1002/jcc.70135","DOIUrl":"https://doi.org/10.1002/jcc.70135","url":null,"abstract":"<p>The capture, activation, and reaction of carbon dioxide with dimethylamine (DMA) clusters have been investigated theoretically in the gas phase. The electronic structure of various compounds has been obtained using the density functional theory approach. The partitioning of the reaction path into different domains of structural stability has been done within the framework of the electron localization function (ELF) analysis. It has been found that DMA cluster size is a key parameter in modulating CO₂ conversion, both energetically and structurally. It has been shown that as the size of DMA clusters increases, hidden domains transform into real domains and the energy barrier for the rate-limiting step significantly decreases, so that a slow and unlikely reaction becomes an instantaneous and viable reaction. Carbamic acid hydrogen bonded with a DMA dimer is the unique product of the reaction of CO₂ with a DMA trimer.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 13","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70135","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143950052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GPU Accelerated Hybrid Particle-Field Molecular Dynamics: Multi-Node/Multi-GPU Implementation and Large-Scale Benchmarks of the OCCAM Code","authors":"Rosario Esposito,&nbsp;Giuseppe Mensitieri,&nbsp;You-Liang Zhou,&nbsp;Zhong-Yuan Lu,&nbsp;Ying Zhao,&nbsp;Toshihiro Kawakatsu,&nbsp;Giuseppe Milano","doi":"10.1002/jcc.70126","DOIUrl":"https://doi.org/10.1002/jcc.70126","url":null,"abstract":"<p>A parallelization strategy for hybrid particle-field molecular dynamics (hPF-MD) simulations on multi-node multi-GPU architectures is proposed. Two design principles have been followed to achieve a massively parallel version of the OCCAM code for distributed GPU computing: performing all the computations only on GPUs, minimizing data exchange between CPU and GPUs, and among GPUs. The hPF-MD scheme is particularly suitable to develop a GPU-resident and low data exchange code. Comparison of performances obtained using the previous multi-CPU code with the proposed multi-node multi-GPU version are reported. Several non-trivial issues to enable applications for systems of considerable sizes, including large input files handling and memory occupation, have been addressed. Large-scale benchmarks of hPF-MD simulations for system sizes up to 10 billion particles are presented. Performances obtained using a moderate quantity of computational resources highlight the feasibility of hPF-MD simulations in systematic studies of large-scale multibillion particle systems. This opens the possibility to perform systematic/routine studies and to reveal new molecular insights for problems on scales previously inaccessible to molecular simulations.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 13","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70126","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143944703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PDBrestore: A Free Web Interface for Processing and Fixing Protein Chains From Raw PDB Files","authors":"Piero Procacci","doi":"10.1002/jcc.70124","DOIUrl":"https://doi.org/10.1002/jcc.70124","url":null,"abstract":"<p>We present PDBrestore, a free web interface for repairing protein PDB chains extracted from either a local PDB file or a PDB file downloaded from the Protein Data Bank. PDBrestore performs several key tasks: It adds hydrogen atoms, completes missing atoms in side chains, fills gaps in the sequence, derives the <span>itp</span> parameter file for a ligand according to the GAFF2 force field for GROMACS applications, and generates a reasonably pre-equilibrated solvated simulation box. The interface is designed to streamline the cumbersome preparatory work required to set up an initial protein-ligand coordinates PDB file for use in drug design projects, such as free energy perturbation or thermodynamic integration calculations of ligand binding affinities. Additionally, PDBrestore is available as a command-line application within the open-source ORAC distribution, which can be freely downloaded from the website: www1.chim.unifi.it/orac.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 13","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70124","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143944705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the Functional Importance of Conformer-Dependent Atomic Partial Charge Assignment","authors":"Meghan Osato,&nbsp;Hannah M. Baumann,&nbsp;Jennifer Huang,&nbsp;Irfan Alibay,&nbsp;David L. Mobley","doi":"10.1002/jcc.70112","DOIUrl":"https://doi.org/10.1002/jcc.70112","url":null,"abstract":"<p>Physics-based methods such as protein-ligand binding free energy calculations have been increasingly adopted in early-stage drug discovery to prioritize promising compounds for synthesis. However, the accuracy of these methods is highly dependent on the details of the calculation and choices made while preparing the ligands and protein ahead of running calculations. During ligand preparation, researchers typically assign partial atomic charges to each ligand atom using a specific ligand conformation for charge assignment, often the input conformer. While it is a well-known problem that partial charge assignment is dependent on conformation, little investigation has explored the downstream effects of varied partial charge assignment on free energy estimates. Preliminary benchmarks from the Open Free Energy Project show that generating partial charges from different input conformers leads to variation of up to <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>±</mo>\u0000 <mn>5</mn>\u0000 <mo>.</mo>\u0000 <mn>3</mn>\u0000 </mrow>\u0000 <annotation>$$ pm 5.3 $$</annotation>\u0000 </semantics></math> kcal/mol in calculated relative binding free energies due to variation in partial charges alone. In this study, we more systematically explore this issue, investigating it in smaller systems using absolute hydration free energy calculations to reduce the degrees of freedom and sources of statistical error as compared to larger protein-ligand systems. We investigate how differences in partial charge generation (such as those caused by input conformer choice, partial charge engine, and hardware) may lead to differences in calculated absolute hydration free energy (AHFE) values. We demonstrate that supplying different input conformers to a partial charge engine can result in atomic partial charge discrepancies of up to 0.681 e, resulting in differences in calculated AHFE of <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>6</mn>\u0000 <mo>.</mo>\u0000 <mn>9</mn>\u0000 <mo>±</mo>\u0000 <mn>0</mn>\u0000 <mo>.</mo>\u0000 <mn>1</mn>\u0000 </mrow>\u0000 <annotation>$$ 6.9pm 0.1 $$</annotation>\u0000 </semantics></math> kcal/mol. We find that even relatively small variations in partial charge assignment can result in notable differences in calculated AHFE. Thus, care should be taken when assigning partial charges to ensure reproducibility and accuracy of any resulting free energy calculations. We expect that these effects will be magnified in pharmaceutically relevant binding free energy calculations with additional degrees of freedom, more highly directional interactions than in water, and potentially more statistical error.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 13","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70112","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143950150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Graph Neural Network for 3-Dimensional Structures Including Dihedral Angles for Molecular Property Prediction","authors":"Sri Abhirath Reddy Sangala,&nbsp;Shampa Raghunathan","doi":"10.1002/jcc.70121","DOIUrl":"https://doi.org/10.1002/jcc.70121","url":null,"abstract":"<div>\u0000 \u0000 <p>The prediction of molecular properties using graph neural network (GNN)- based approaches has attracted great attention in recent years. Topological molecular graphs are commonly used for representing molecules in machine learning (ML). However, the challenge is to utilize the complete geometry information, such as, bonds, angles, and dihedral angles while processing a molecular graph. In this work, we present predictive GNN accounting three-dimensional molecular structures including the dihedral angles (GNN3Dihed) in a systematic manner. Additionally, we demonstrate that the usage of autoencoders to generate latent space embeddings for usually sparse atomic and bond vectors reduces the number of parameters in the message passing stage while not reducing performance. We compare the performance of GNN3Dihed with state-of-the-art baselines on several tasks (regression and classification), for example, solubility prediction, toxicity prediction, binding affinity, and quantum mechanical property prediction, and showed that the present architecture often outperforms other models—demonstrating the importance of 3D structural information for ML in chemistry.</p>\u0000 </div>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 13","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143944701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}