• Reference Citation Analysis
  • v
  • v
  • Find an Article
Find an Article PDF (5078629)   Today's Articles (1395)
For: Chmiela S, Vassilev-Galindo V, Unke OT, Kabylda A, Sauceda HE, Tkatchenko A, Müller KR. Accurate global machine learning force fields for molecules with hundreds of atoms. Sci Adv 2023;9:eadf0873. [PMID: 36630510 PMCID: PMC9833674 DOI: 10.1126/sciadv.adf0873] [Citation(s) in RCA: 55] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 11/28/2022] [Indexed: 05/25/2023]
Number Cited by Other Article(s)
1
Manchev YT, Popelier PLA. Impact of Derivative Observations on Gaussian Process Machine Learning Potentials: A Direct Comparison of Three Modeling Approaches. J Chem Theory Comput 2025;21:5490-5500. [PMID: 40408763 DOI: 10.1021/acs.jctc.5c00344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2025]
2
Xia J, Zhang Y, Jiang B. The evolution of machine learning potentials for molecules, reactions and materials. Chem Soc Rev 2025;54:4790-4821. [PMID: 40227021 DOI: 10.1039/d5cs00104h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/15/2025]
3
Lee Y, Chen X, Gericke SM, Li M, Zakharov DN, Head AR, Yang JC, Alexandrova AN. Machine-Learning-Driven Exploration of Surface Reconstructions of Reduced Rutile TiO2. Angew Chem Int Ed Engl 2025:e202501017. [PMID: 40261805 DOI: 10.1002/anie.202501017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2025] [Revised: 03/28/2025] [Accepted: 04/22/2025] [Indexed: 04/24/2025]
4
Huang Q, Li Y, Zhu L, Yu W. Hierarchical Deep Potential with Structure Constraints for Efficient Coarse-Grained Modeling. J Chem Inf Model 2025;65:3203-3214. [PMID: 40119793 DOI: 10.1021/acs.jcim.4c02042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/24/2025]
5
Liu S, Yang Q, Zhang L, Luo S. Highly Precise Prediction of Micro- and Supra-pKa Based on 3D Descriptors Integrating Non-Covalent Interactions. Angew Chem Int Ed Engl 2025;64:e202424069. [PMID: 39904757 DOI: 10.1002/anie.202424069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2024] [Revised: 02/02/2025] [Accepted: 02/04/2025] [Indexed: 02/06/2025]
6
Croitoru A, Kumar A, Lambry JC, Lee J, Sharif S, Yu W, MacKerell AD, Aleksandrov A. Increasing the Accuracy and Robustness of the CHARMM General Force Field with an Expanded Training Set. J Chem Theory Comput 2025;21:3044-3065. [PMID: 40033678 PMCID: PMC11938330 DOI: 10.1021/acs.jctc.5c00046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2025]
7
Lei YK, Yagi K, Sugita Y. Efficient Training of Neural Network Potentials for Chemical and Enzymatic Reactions by Continual Learning. J Chem Theory Comput 2025;21:2695-2711. [PMID: 40065732 PMCID: PMC11912204 DOI: 10.1021/acs.jctc.4c01393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2024] [Revised: 02/04/2025] [Accepted: 02/05/2025] [Indexed: 03/19/2025]
8
Ghukasyan T, Altunyan V, Bughdaryan A, Aghajanyan T, Smbatyan K, Papoian GA, Petrosyan G. Smart distributed data factory volunteer computing platform for active learning-driven molecular data acquisition. Sci Rep 2025;15:7122. [PMID: 40016468 PMCID: PMC11868574 DOI: 10.1038/s41598-025-90981-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2024] [Accepted: 02/17/2025] [Indexed: 03/01/2025]  Open
9
Airas J, Zhang B. Scaling Graph Neural Networks to Large Proteins. J Chem Theory Comput 2025;21:2055-2066. [PMID: 39913331 PMCID: PMC11904306 DOI: 10.1021/acs.jctc.4c01420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/26/2025]
10
Poltavsky I, Puleva M, Charkin-Gorbulin A, Fonseca G, Batatia I, Browning NJ, Chmiela S, Cui M, Frank JT, Heinen S, Huang B, Käser S, Kabylda A, Khan D, Müller C, Price AJA, Riedmiller K, Töpfer K, Ko TW, Meuwly M, Rupp M, Csányi G, Anatole von Lilienfeld O, Margraf JT, Müller KR, Tkatchenko A. Crash testing machine learning force fields for molecules, materials, and interfaces: molecular dynamics in the TEA challenge 2023. Chem Sci 2025;16:3738-3754. [PMID: 39911337 PMCID: PMC11791520 DOI: 10.1039/d4sc06530a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2024] [Accepted: 12/25/2024] [Indexed: 02/07/2025]  Open
11
Poltavsky I, Charkin-Gorbulin A, Puleva M, Fonseca G, Batatia I, Browning NJ, Chmiela S, Cui M, Frank JT, Heinen S, Huang B, Käser S, Kabylda A, Khan D, Müller C, Price AJA, Riedmiller K, Töpfer K, Ko TW, Meuwly M, Rupp M, Csányi G, von Lilienfeld OA, Margraf JT, Müller KR, Tkatchenko A. Crash testing machine learning force fields for molecules, materials, and interfaces: model analysis in the TEA Challenge 2023. Chem Sci 2025;16:3720-3737. [PMID: 39935506 PMCID: PMC11809572 DOI: 10.1039/d4sc06529h] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2024] [Accepted: 12/25/2024] [Indexed: 02/13/2025]  Open
12
Chen J, Gao Q, Huang M, Yu K. Application of modern artificial intelligence techniques in the development of organic molecular force fields. Phys Chem Chem Phys 2025;27:2294-2319. [PMID: 39820957 DOI: 10.1039/d4cp02989e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2025]
13
Esders M, Schnake T, Lederer J, Kabylda A, Montavon G, Tkatchenko A, Müller KR. Analyzing Atomic Interactions in Molecules as Learned by Neural Networks. J Chem Theory Comput 2025;21:714-729. [PMID: 39792788 PMCID: PMC11780731 DOI: 10.1021/acs.jctc.4c01424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2024] [Revised: 12/30/2024] [Accepted: 01/02/2025] [Indexed: 01/12/2025]
14
David R, de la Puente M, Gomez A, Anton O, Stirnemann G, Laage D. ArcaNN: automated enhanced sampling generation of training sets for chemically reactive machine learning interatomic potentials. DIGITAL DISCOVERY 2025;4:54-72. [PMID: 39553851 PMCID: PMC11563209 DOI: 10.1039/d4dd00209a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2024] [Accepted: 10/21/2024] [Indexed: 11/19/2024]
15
Thiemann FL, O'Neill N, Kapil V, Michaelides A, Schran C. Introduction to machine learning potentials for atomistic simulations. JOURNAL OF PHYSICS. CONDENSED MATTER : AN INSTITUTE OF PHYSICS JOURNAL 2024;37:073002. [PMID: 39577092 DOI: 10.1088/1361-648x/ad9657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2024] [Accepted: 11/22/2024] [Indexed: 11/24/2024]
16
Hou YF, Zhang Q, Dral PO. Surprising Dynamics Phenomena in the Diels-Alder Reaction of C60 Uncovered with AI. J Org Chem 2024;89:15041-15047. [PMID: 39358911 DOI: 10.1021/acs.joc.4c01763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2024]
17
Xu W, Xu H, Zhu M, Wen J. Ultrafast dynamics in spatially confined photoisomerization: accelerated simulations through machine learning models. Phys Chem Chem Phys 2024;26:25994-26003. [PMID: 39370956 DOI: 10.1039/d4cp01497a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/08/2024]
18
Zaporozhets I, Musil F, Kapil V, Clementi C. Accurate nuclear quantum statistics on machine-learned classical effective potentials. J Chem Phys 2024;161:134102. [PMID: 39352405 DOI: 10.1063/5.0226764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2024] [Accepted: 09/13/2024] [Indexed: 10/03/2024]  Open
19
Isamura BK, Popelier PLA. Transfer learning of hyperparameters for fast construction of anisotropic GPR models: design and application to the machine-learned force field FFLUX. Phys Chem Chem Phys 2024;26:23677-23691. [PMID: 39224929 PMCID: PMC11369757 DOI: 10.1039/d4cp01862a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Accepted: 08/22/2024] [Indexed: 09/04/2024]
20
Hou YF, Zhang L, Zhang Q, Ge F, Dral PO. Physics-Informed Active Learning for Accelerating Quantum Chemical Simulations. J Chem Theory Comput 2024. [PMID: 39264419 DOI: 10.1021/acs.jctc.4c00821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/13/2024]
21
Tu NTP, Williamson S, Johnson ER, Rowley CN. Modeling Intermolecular Interactions with Exchange-Hole Dipole Moment Dispersion Corrections to Neural Network Potentials. J Phys Chem B 2024;128:8290-8302. [PMID: 39166778 DOI: 10.1021/acs.jpcb.4c02882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/23/2024]
22
Jin Y, Perez-Lemus GR, Zubieta Rico PF, de Pablo JJ. Improving Machine Learned Force Fields for Complex Fluids through Enhanced Sampling: A Liquid Crystal Case Study. J Phys Chem A 2024;128:7257-7268. [PMID: 39150905 DOI: 10.1021/acs.jpca.4c01546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/18/2024]
23
Williams CD, Kalayan J, Burton NA, Bryce RA. Stable and accurate atomistic simulations of flexible molecules using conformationally generalisable machine learned potentials. Chem Sci 2024;15:12780-12795. [PMID: 39148799 PMCID: PMC11323334 DOI: 10.1039/d4sc01109k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Accepted: 07/07/2024] [Indexed: 08/17/2024]  Open
24
Bone RA, Chung MKJ, Ponder JW, Riccardi D, Muzny C, Sundararaman R, Schwarz K. A new method to calculate broadband dielectric spectra of solvents from molecular dynamics simulations demonstrated with polarizable force fields. J Chem Phys 2024;161:064306. [PMID: 39132799 PMCID: PMC11324330 DOI: 10.1063/5.0217883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Accepted: 07/26/2024] [Indexed: 08/13/2024]  Open
25
Litman Y, Kapil V, Feldman YMY, Tisi D, Begušić T, Fidanyan K, Fraux G, Higer J, Kellner M, Li TE, Pós ES, Stocco E, Trenins G, Hirshberg B, Rossi M, Ceriotti M. i-PI 3.0: A flexible and efficient framework for advanced atomistic simulations. J Chem Phys 2024;161:062504. [PMID: 39140447 DOI: 10.1063/5.0215869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Accepted: 07/11/2024] [Indexed: 08/15/2024]  Open
26
Frank JT, Unke OT, Müller KR, Chmiela S. A Euclidean transformer for fast and stable machine learned force fields. Nat Commun 2024;15:6539. [PMID: 39107296 PMCID: PMC11303804 DOI: 10.1038/s41467-024-50620-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 07/10/2024] [Indexed: 08/10/2024]  Open
27
Margraf JT. Neural graph distance embedding for molecular geometry generation. J Comput Chem 2024;45:1784-1790. [PMID: 38655845 DOI: 10.1002/jcc.27349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 03/05/2024] [Accepted: 03/08/2024] [Indexed: 04/26/2024]
28
Biriukov D, Vácha R. Pathways to a Shiny Future: Building the Foundation for Computational Physical Chemistry and Biophysics in 2050. ACS PHYSICAL CHEMISTRY AU 2024;4:302-313. [PMID: 39069976 PMCID: PMC11274290 DOI: 10.1021/acsphyschemau.4c00003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Revised: 03/15/2024] [Accepted: 03/18/2024] [Indexed: 07/30/2024]
29
Slootman E, Poltavsky I, Shinde R, Cocomello J, Moroni S, Tkatchenko A, Filippi C. Accurate Quantum Monte Carlo Forces for Machine-Learned Force Fields: Ethanol as a Benchmark. J Chem Theory Comput 2024;20:6020-6027. [PMID: 39003522 PMCID: PMC11270822 DOI: 10.1021/acs.jctc.4c00498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Revised: 05/31/2024] [Accepted: 06/03/2024] [Indexed: 07/15/2024]
30
Medrano Sandonas L, Van Rompaey D, Fallani A, Hilfiker M, Hahn D, Perez-Benito L, Verhoeven J, Tresadern G, Kurt Wegner J, Ceulemans H, Tkatchenko A. Dataset for quantum-mechanical exploration of conformers and solvent effects in large drug-like molecules. Sci Data 2024;11:742. [PMID: 38972891 PMCID: PMC11228031 DOI: 10.1038/s41597-024-03521-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 06/13/2024] [Indexed: 07/09/2024]  Open
31
Aldossary A, Campos-Gonzalez-Angulo JA, Pablo-García S, Leong SX, Rajaonson EM, Thiede L, Tom G, Wang A, Avagliano D, Aspuru-Guzik A. In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024;36:e2402369. [PMID: 38794859 DOI: 10.1002/adma.202402369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 04/28/2024] [Indexed: 05/26/2024]
32
Fu W, Mo Y, Xiao Y, Liu C, Zhou F, Wang Y, Zhou J, Zhang YJ. Enhancing Molecular Energy Predictions with Physically Constrained Modifications to the Neural Network Potential. J Chem Theory Comput 2024;20:4533-4544. [PMID: 38828925 DOI: 10.1021/acs.jctc.3c01181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
33
Pelaez RP, Simeon G, Galvelis R, Mirarchi A, Eastman P, Doerr S, Thölke P, Markland TE, De Fabritiis G. TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations. J Chem Theory Comput 2024;20:4076-4087. [PMID: 38743033 DOI: 10.1021/acs.jctc.4c00253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
34
Pelaez RP, Simeon G, Galvelis R, Mirarchi A, Eastman P, Doerr S, Thölke P, Markland TE, De Fabritiis G. TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations. ARXIV 2024:arXiv:2402.17660v3. [PMID: 38463504 PMCID: PMC10925388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
35
Wan K, He J, Shi X. Construction of High Accuracy Machine Learning Interatomic Potential for Surface/Interface of Nanomaterials-A Review. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024;36:e2305758. [PMID: 37640376 DOI: 10.1002/adma.202305758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 08/24/2023] [Indexed: 08/31/2023]
36
Chen M, Jiang X, Zhang L, Chen X, Wen Y, Gu Z, Li X, Zheng M. The emergence of machine learning force fields in drug design. Med Res Rev 2024;44:1147-1182. [PMID: 38173298 DOI: 10.1002/med.22008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 11/29/2023] [Accepted: 12/05/2023] [Indexed: 01/05/2024]
37
Zhai Y, Rashmi R, Palos E, Paesani F. Many-body interactions and deep neural network potentials for water. J Chem Phys 2024;160:144501. [PMID: 38587225 DOI: 10.1063/5.0203682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 03/23/2024] [Indexed: 04/09/2024]  Open
38
Unke OT, Stöhr M, Ganscha S, Unterthiner T, Maennel H, Kashubin S, Ahlin D, Gastegger M, Medrano Sandonas L, Berryman JT, Tkatchenko A, Müller KR. Biomolecular dynamics with machine-learned quantum-mechanical force fields trained on diverse chemical fragments. SCIENCE ADVANCES 2024;10:eadn4397. [PMID: 38579003 PMCID: PMC11809612 DOI: 10.1126/sciadv.adn4397] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 02/29/2024] [Indexed: 04/07/2024]
39
Käser S, Meuwly M. Numerical Accuracy Matters: Applications of Machine Learned Potential Energy Surfaces. J Phys Chem Lett 2024:3419-3424. [PMID: 38506827 DOI: 10.1021/acs.jpclett.3c03405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/21/2024]
40
Dral PO. AI in computational chemistry through the lens of a decade-long journey. Chem Commun (Camb) 2024;60:3240-3258. [PMID: 38444290 DOI: 10.1039/d4cc00010b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2024]
41
Horn KP, Vazquez-Salazar LI, Koch CP, Meuwly M. Improving potential energy surfaces using measured Feshbach resonance states. SCIENCE ADVANCES 2024;10:eadi6462. [PMID: 38427733 PMCID: PMC10906917 DOI: 10.1126/sciadv.adi6462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 01/29/2024] [Indexed: 03/03/2024]
42
Brooks CL, MacKerell AD, Post CB, Nilsson L. Biomolecular dynamics in the 21st century. Biochim Biophys Acta Gen Subj 2024;1868:130534. [PMID: 38065235 PMCID: PMC10842176 DOI: 10.1016/j.bbagen.2023.130534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 11/28/2023] [Accepted: 11/29/2023] [Indexed: 01/03/2024]
43
Bonfà P, Onuorah IJ, Lang F, Timrov I, Monacelli L, Wang C, Sun X, Petracic O, Pizzi G, Marzari N, Blundell SJ, De Renzi R. Magnetostriction-Driven Muon Localization in an Antiferromagnetic Oxide. PHYSICAL REVIEW LETTERS 2024;132:046701. [PMID: 38335330 DOI: 10.1103/physrevlett.132.046701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 09/18/2023] [Accepted: 11/20/2023] [Indexed: 02/12/2024]
44
Gelžinytė E, Öeren M, Segall MD, Csányi G. Transferable Machine Learning Interatomic Potential for Bond Dissociation Energy Prediction of Drug-like Molecules. J Chem Theory Comput 2024;20:164-177. [PMID: 38108269 PMCID: PMC10782450 DOI: 10.1021/acs.jctc.3c00710] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 11/30/2023] [Accepted: 11/30/2023] [Indexed: 12/19/2023]
45
Wang Y, Wang T, Li S, He X, Li M, Wang Z, Zheng N, Shao B, Liu TY. Enhancing geometric representations for molecules with equivariant vector-scalar interactive message passing. Nat Commun 2024;15:313. [PMID: 38182565 PMCID: PMC10770089 DOI: 10.1038/s41467-023-43720-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 11/16/2023] [Indexed: 01/07/2024]  Open
46
Fonseca G, Poltavsky I, Tkatchenko A. Force Field Analysis Software and Tools (FFAST): Assessing Machine Learning Force Fields under the Microscope. J Chem Theory Comput 2023;19:8706-8717. [PMID: 38011895 PMCID: PMC10720330 DOI: 10.1021/acs.jctc.3c00985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 11/06/2023] [Accepted: 11/07/2023] [Indexed: 11/29/2023]
47
Kanhaiya K, Nathanson M, In 't Veld PJ, Zhu C, Nikiforov I, Tadmor EB, Choi YK, Im W, Mishra RK, Heinz H. Accurate Force Fields for Atomistic Simulations of Oxides, Hydroxides, and Organic Hybrid Materials up to the Micrometer Scale. J Chem Theory Comput 2023;19:8293-8322. [PMID: 37962992 DOI: 10.1021/acs.jctc.3c00750] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2023]
48
Plé T, Lagardère L, Piquemal JP. Force-field-enhanced neural network interactions: from local equivariant embedding to atom-in-molecule properties and long-range effects. Chem Sci 2023;14:12554-12569. [PMID: 38020379 PMCID: PMC10646944 DOI: 10.1039/d3sc02581k] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 10/03/2023] [Indexed: 12/01/2023]  Open
49
Lederer J, Gastegger M, Schütt KT, Kampffmeyer M, Müller KR, Unke OT. Automatic identification of chemical moieties. Phys Chem Chem Phys 2023;25:26370-26379. [PMID: 37750554 PMCID: PMC10548786 DOI: 10.1039/d3cp03845a] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 08/18/2023] [Indexed: 09/27/2023]
50
Wang T, He X, Li M, Shao B, Liu TY. AIMD-Chig: Exploring the conformational space of a 166-atom protein Chignolin with ab initio molecular dynamics. Sci Data 2023;10:549. [PMID: 37607915 PMCID: PMC10444755 DOI: 10.1038/s41597-023-02465-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 08/11/2023] [Indexed: 08/24/2023]  Open
PrevPage 1 of 2 12Next
© 2004-2025 Baishideng Publishing Group Inc. All rights reserved. 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA