Journal of Chemical Theory and Computation最新文献_第8页

Multiproperty Deep Learning of the Correlation Energy of Electrons and the Physicochemical Properties of Molecules. 电子相关能与分子物理化学性质的多性质深度学习。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-06-24 Epub Date: 2025-06-10 DOI: 10.1021/acs.jctc.5c00414

Yan Yuan, Yilin Zhao, Linling Lu, Junjie Wang, Jingbo Chen, Shubin Liu, Paul W Ayers, Dongbo Zhao

{"title":"Multiproperty Deep Learning of the Correlation Energy of Electrons and the Physicochemical Properties of Molecules.","authors":"Yan Yuan, Yilin Zhao, Linling Lu, Junjie Wang, Jingbo Chen, Shubin Liu, Paul W Ayers, Dongbo Zhao","doi":"10.1021/acs.jctc.5c00414","DOIUrl":"10.1021/acs.jctc.5c00414","url":null,"abstract":"The density-based descriptors from the information-theoretic approach (ITA) are used as features for multiproperty deep learning (DL), predicting the correlation energy and physicochemical properties of molecules. In addition to response properties (molecular polarizability αiso and NMR shielding constant σiso) where ITA has been shown to work well before, we consider four conceptually distinct but practically related concepts: electron correlation, redox potential, octanol-water partition coefficient (logKow), and the wavelength of maximum absorption (λmax). The DL-predicted results are in good agreement with either the calculated or experimental counterparts, indicative of the model's robustness. We verified the transferability of redox potentials of phenazine derivatives. Generalizability is observed for the λmax data: small chromophores are used for training/validation but the test set has sizable molecules. The trained DL model outperforms the conventional TD-DFT method in terms of accuracy and efficiency. We also showcase that the isotropic quadrupole moment (Θiso) is a good predictor of logKow. This establishes that versatile density-based ITA quantities can be used to make accurate, low-cost predictions of both extensive and intensive properties, suggesting that this ITA-DL protocol has the potential for closed-loop chemistry automation. Implication of this work is straightforward, that a universal framework should be possible based on the ITA-based DL models.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"5997-6006"},"PeriodicalIF":5.7,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256712","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

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-06-24

Ke Liao*,

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IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-06-24

Shirong Wang, and , Xin Xu*,

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IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-06-24

Tanika Duivenvoorden, Quang K. Loi, Stephen Sanderson and Debra J. Searles*,

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IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-06-24

Abhijeet Sadashiv Gangan*, Ekin Dogus Cubuk, Samuel S. Schoenholz, Mathieu Bauchy and N. M. Anoop Krishnan*,

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IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-06-24

Robert M. Raddi, Tim Marshall, Yunhui Ge and Vincent A. Voelz*,

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MSBack: Multiscale Backmapping of Highly Coarse-Grained Proteins Using Constrained Diffusion. 使用受限扩散的高粗粒度蛋白质的多尺度反向映射。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-06-24 Epub Date: 2025-06-01 DOI: 10.1021/acs.jctc.5c00459

Curt Waltmann, Yihang Wang, Chengxi Yang, Siyoung Kim, Gregory A Voth

{"title":"MSBack: Multiscale Backmapping of Highly Coarse-Grained Proteins Using Constrained Diffusion.","authors":"Curt Waltmann, Yihang Wang, Chengxi Yang, Siyoung Kim, Gregory A Voth","doi":"10.1021/acs.jctc.5c00459","DOIUrl":"10.1021/acs.jctc.5c00459","url":null,"abstract":"Coarse-grained (CG) molecular dynamics is a powerful tool for simulating the collective behavior of biomolecules. However, the structural information lost during coarse-graining prevents the CG configurations from being more widely useful (e.g., for ligand binding). Regenerating the lost all-atom coordinates, or backmapping, is an unmet challenge for protein CG at resolutions lower than one coarse-grain site or bead per amino acid residue. This low resolution is computationally necessary to simulate many protein complexes including viruses like SARS-CoV-2 and HIV-1. We propose MSBack, a method to backmap highly CG proteins using a diffusion model for the all-atom coordinates constrained to fit the CG coordinates. This diffusion process works by perturbing a known all-atom structure and does not require retraining. We show that this stochastically generates a distribution of α-carbon traces that match the CG coordinates. By combining this with physics-based methods for smaller-length backmapping, we fully backmap a mature HIV-1 capsid bound with the small molecule inositol hexakisphosphate at 1 Å resolution.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"6184-6193"},"PeriodicalIF":5.7,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12199737/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144197783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-06-24

Curt Waltmann, Yihang Wang, Chengxi Yang, Siyoung Kim and Gregory A. Voth*,

引用次数: 0

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-06-24

Razan E. Daoud, Simone Veglianti, Anna Piras, Abderrahmane Semmeq, Samuele Giannini, Giacomo Prampolini* and Daniele Padula*,

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Using Matrix-Free Tensor-Network Optimizations To Construct a Reduced-Scaling and Robust Second-Order Mo̷ller-Plesset Theory. 用无矩阵张量网络优化构造降标度鲁棒二阶Mo - ller-Plesset理论。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-06-24 Epub Date: 2025-06-04 DOI: 10.1021/acs.jctc.5c00277

Karl Pierce, Miguel Morales

{"title":"Using Matrix-Free Tensor-Network Optimizations To Construct a Reduced-Scaling and Robust Second-Order Mo̷ller-Plesset Theory.","authors":"Karl Pierce, Miguel Morales","doi":"10.1021/acs.jctc.5c00277","DOIUrl":"10.1021/acs.jctc.5c00277","url":null,"abstract":"We investigate the efficient combination of the canonical polyadic decomposition (CPD) and tensor hyper-contraction (THC) approaches. We first present a novel low-cost CPD solver that leverages a precomputed THC factorization of an order-4 tensor to efficiently optimize the order-4 CPD with <math><mi>O</mi><mrow><mo>(</mo><mi>N</mi><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>)</mo></mrow></math> scaling. With the matrix-free THC-based optimization strategy in hand, we can efficiently generate CPD factorizations of the order-4 two-electron integral tensors and develop novel electronic structure methods that take advantage of both the THC and CPD approximations. Next, we investigate the application of a combined CPD and THC approximation of the Laplace transform (LT) second-order Mo̷ller-Plesset (MP2) method. We exploit the ability to switch efficiently between the THC and CPD factorizations of the two-electron integrals to reduce the computational complexity of the LT MP2 method while preserving the accuracy of the approach. Furthermore, we take advantage of the robust fitting approximation to eliminate the leading-order error in the CPD approximated tensor networks. Finally, we show that modest values of THC and CPD rank preserve the accuracy of the LT MP2 method and that this CPD + THC LT MP2 strategy realizes a performance advantage over canonical LT MP2 in both computational wall-times and memory resource requirements.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"5952-5964"},"PeriodicalIF":5.7,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144223737","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