Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy | Paper Citation Record

Observation 889957b5-7f84-40b5-9f6f-9afa000715aa · outbound

This paper cites Nature Structural Biology 9(9), 646–652 (2002) https://doi.org/10.1038/nsb0902-646.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Nature Structural Biology 9(9), 646–652 (2002) https://doi.org/10.1038/nsb0902-646

Reference 1

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This paper cites Annual Review of Biophysics41(Volume 41, 2012), 429–452 (2012) https: //doi.org/10.1146/annurev-biophys-042910-155245.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Annual Review of Biophysics41(Volume 41, 2012), 429–452 (2012) https: //doi.org/10.1146/annurev-biophys-042910-155245

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This paper cites Neuron99(6), 1129–1143 (2018) https://doi.org/10.1016/j.neuron.2018.08.011.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Neuron99(6), 1129–1143 (2018) https://doi.org/10.1016/j.neuron.2018.08.011

Reference 3

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This paper cites BMC Biology9(1), 71 (2011) https://doi.org/10.1186/1741-7007-9-71.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy BMC Biology9(1), 71 (2011) https://doi.org/10.1186/1741-7007-9-71

Reference 4

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.469620Z

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This paper cites Journal of Medicinal Chemistry59(9), 4035–4061 (2016) https://doi.org/10.1021/acs.jmedchem.5 b01684 https://doi.org/10.1021/acs.jmedchem.5b01684.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Medicinal Chemistry59(9), 4035–4061 (2016) https://doi.org/10.1021/acs.jmedchem.5 b01684 https://doi.org/10.1021/acs.jmedchem.5b01684

Reference 5

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Observation e05c099a-df41-44ee-ac8c-90c90f9dcc6d · outbound

This paper cites In: Protein Simulations.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy In: Protein Simulations

Reference 6

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This paper cites Jour- nal of Computational Chemistry25(13), 1584–1604 (2004) https://doi.org/10.1002/jcc.20082 https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.20082.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Jour- nal of Computational Chemistry25(13), 1584–1604 (2004) https://doi.org/10.1002/jcc.20082 https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.20082

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

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Observation 2e1424e7-9d23-4473-b8ac-5ddf82673ca6 · outbound

This paper cites In: Kukol, A.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy In: Kukol, A

Reference 8

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.447533Z

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Observation 221f0d11-4dcf-42f6-b1c7-acd4c4c0bc49 · outbound

This paper cites Current Opinion in Structural Biology67, 18–24 (2021) https://doi.org/10.1016/j.sbi.2020.08.006.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Current Opinion in Structural Biology67, 18–24 (2021) https://doi.org/10.1016/j.sbi.2020.08.006

Reference 9

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.669855Z

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Observation a57d31c5-b9a6-4f57-b24a-11cc5fd0cd53 · outbound

This paper cites How Atoms Interact Within Molecules.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy How Atoms Interact Within Molecules

Reference 10

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This paper cites https://arxiv.org/abs/2603.24360.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy https://arxiv.org/abs/2603.24360

Reference 11

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This paper cites Journal of Chemical Theory and Computation21(15), 7550–7560 (2025) https://doi.org/10.1021/acs.jctc.5c00996 https://doi.org/10.1021/acs.jctc.5c00996.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Chemical Theory and Computation21(15), 7550–7560 (2025) https://doi.org/10.1021/acs.jctc.5c00996 https://doi.org/10.1021/acs.jctc.5c00996

Reference 12

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.527483Z

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This paper cites In: Oh, A.H., Agarwal, A., Belgrave, D., Cho, K.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy In: Oh, A.H., Agarwal, A., Belgrave, D., Cho, K

Reference 13

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This paper cites https://arxiv.org/abs/2505.08762.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy https://arxiv.org/abs/2505.08762

Reference 14

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This paper cites https://arxiv.org/abs/2510.099 39 15.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy https://arxiv.org/abs/2510.099 39 15

Reference 15

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This paper cites Scientific Data10(1), 11 (2023) https://doi.org/10.1038/ s41597-022-01882-6.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Scientific Data10(1), 11 (2023) https://doi.org/10.1038/ s41597-022-01882-6

Reference 16

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This paper cites Journal of the American Chemical Society147(21), 17598–17611 (2025) https://doi.org/10.1021/ jacs.4c07099 https://doi.org/10.1021/jacs.4c07099.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of the American Chemical Society147(21), 17598–17611 (2025) https://doi.org/10.1021/ jacs.4c07099 https://doi.org/10.1021/jacs.4c07099

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Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of the American Chemical Society147(37), 33723–33734 (2025) https://doi.or g/10.1021/jacs.5c09558 https://doi.org/10.1021/jacs.5c09558

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This paper cites Science Advances10(14), 4397 (2024) https://doi.org/10.1126/sciadv.adn4397 https://www.science.org/doi/pdf/10.1126/sciadv.adn4397.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Science Advances10(14), 4397 (2024) https://doi.org/10.1126/sciadv.adn4397 https://www.science.org/doi/pdf/10.1126/sciadv.adn4397

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This paper cites Living Journal of Computational Molecular Science4(1), 1583 (2022) https://doi.org/10.33011/livecoms.4.1.1583.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Living Journal of Computational Molecular Science4(1), 1583 (2022) https://doi.org/10.33011/livecoms.4.1.1583

Reference 20

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This paper cites Annual Review of Physical Chemistry75(Volume 75, 2024), 347–370 (2024) https://doi.org/10.1146/annurev-physc hem-083122-125941.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Annual Review of Physical Chemistry75(Volume 75, 2024), 347–370 (2024) https://doi.org/10.1146/annurev-physc hem-083122-125941

Reference 21

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This paper cites Chemical Reviews126(1), 671–713 (2026) https://doi.org/10.1021/ac s.chemrev.5c00700 https://doi.org/10.1021/acs.chemrev.5c00700.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Chemical Reviews126(1), 671–713 (2026) https://doi.org/10.1021/ac s.chemrev.5c00700 https://doi.org/10.1021/acs.chemrev.5c00700

Reference 22

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This paper cites International Journal of Molecular Sciences20(15), 3774 (2019) https://doi.org/10.3390/ijms20153774.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy International Journal of Molecular Sciences20(15), 3774 (2019) https://doi.org/10.3390/ijms20153774

Reference 24

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This paper cites ACS Central Science9(12), 2286–2297 (2023) https://doi.org/10.1021/acscentsci.3c01160 https://doi.org/10.1021/acscentsci.3c01160.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy ACS Central Science9(12), 2286–2297 (2023) https://doi.org/10.1021/acscentsci.3c01160 https://doi.org/10.1021/acscentsci.3c01160

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This paper cites Journal of Chemical The- ory and Computation18(10), 6334–6344 (2022) ht t p s : / / d o i.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Chemical The- ory and Computation18(10), 6334–6344 (2022) ht t p s : / / d o i

Reference 26

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This paper cites Annual Review of Biophysics48(Volume 48, 2019), 275–296 (2019) https://doi.org/10.1146/annurev-biophys-052118-115325.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Annual Review of Biophysics48(Volume 48, 2019), 275–296 (2019) https://doi.org/10.1146/annurev-biophys-052118-115325

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This paper cites The Journal of Chemical Physics155(8), 084101 (2021) https://doi.org/10.1063/5.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy The Journal of Chemical Physics155(8), 084101 (2021) https://doi.org/10.1063/5

Reference 28

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This paper cites Nature Communications14(1), 5739 (2023) https://doi.org/10.1038/s41467-023-41343-1.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Nature Communications14(1), 5739 (2023) https://doi.org/10.1038/s41467-023-41343-1

Reference 29

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.473861Z

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Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy ACS Central Science5(5), 755–767 (2019) https: //doi.org/10.1021/acscentsci.8b00913 https://doi.org/10.1021/acscentsci.8b00913

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Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Annual Review of Physical Chemistry75(Volume 75, 2024), 21–45 (2024) https://doi.org/10.1146/annurev-physche m-062123-010821

Reference 31

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This paper cites The Journal of Chemical Physics164(5) (2026) https://doi.org/10.1063/5.0313624.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy The Journal of Chemical Physics164(5) (2026) https://doi.org/10.1063/5.0313624

Reference 32

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This paper cites Journal of Chemical Theory and Computation (2023) https://doi.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Chemical Theory and Computation (2023) https://doi

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Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy The Journal of Chemical Physics157(24), 244103 (2022) https://doi.org/10.1063/5.0124538

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Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Unresolved cited work

Reference 35

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This paper cites Nature Chemistry (2025) https://doi.org/10.1038/s415 57-025-01874-0.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Nature Chemistry (2025) https://doi.org/10.1038/s415 57-025-01874-0

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Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Nature Communications17(1), 2493 (2026) https://doi.org/10.1 038/s41467-026-70818-0

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Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Chemical Theory and Computation22(1), 219–230 (2026) https: //doi.org/10.1021/acs.jctc.5c01712 https://doi.org/10.1021/acs.jctc.5c01712

Reference 38

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.566302Z

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This paper cites Journal of chemical theory and computation18(10), 6334–6344 (2022).

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of chemical theory and computation18(10), 6334–6344 (2022)

Reference 39

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Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy ACS Central Science9(12), 2286–2297 (2023)

Reference 40

Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

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This paper cites The Journal of Physical Chemistry99(7), 2224–2235 (1995).

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy The Journal of Physical Chemistry99(7), 2224–2235 (1995)

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Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

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Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Chemical Theory and Computation9(4), 2052–2071 (2013) https://doi.org/10.1021/ct301050x https://doi.org/10.1021/ct301050x

Reference 42

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.518960Z

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Observation 0fa493a1-b0b7-4da5-9c9f-36d597252bfe · outbound

This paper cites Jour- nal of Chemical Theory and Computation6(8), 2303–2314 (2010) https://doi.org/10.1021/ct1001818 https://doi.org/10.1021/ct1001818.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Jour- nal of Chemical Theory and Computation6(8), 2303–2314 (2010) https://doi.org/10.1021/ct1001818 https://doi.org/10.1021/ct1001818

Reference 43

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.501264Z

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Observation d66cdf6f-e131-49db-b41f-26d4bb9b93d5 · outbound

This paper cites The Journal of Chemical Physics161(23), 234101 (2024) https://doi.org/10.1063/5.0235 189.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy The Journal of Chemical Physics161(23), 234101 (2024) https://doi.org/10.1063/5.0235 189

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Resolution: verified exact; doi, observed 2026-07-14T08:40:21.494456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bf2ffccd-060f-432a-8a8e-c8b5503bd475 · outbound

This paper cites In: Oh, A.H., Agarwal, A., Belgrave, D., Cho, K.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy In: Oh, A.H., Agarwal, A., Belgrave, D., Cho, K

Reference 45

Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02fc3309-b9dc-4a79-98b2-b193e80e1375 · outbound

This paper cites Journal of Chemical Theory and Computation20(19), 8583–8593 (2024) https://doi.org/10.1021/acs.jctc.4c00794 https://doi.org/10.1021/acs.jctc.4c00794.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Chemical Theory and Computation20(19), 8583–8593 (2024) https://doi.org/10.1021/acs.jctc.4c00794 https://doi.org/10.1021/acs.jctc.4c00794

Reference 46

Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca552c7c-7ab2-4b4a-8e45-08f270d045b9 · outbound

This paper cites an unresolved cited work.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Unresolved cited work

Reference 48

Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 207f1a2b-c09c-4ce8-9ccd-7d810e138467 · outbound

This paper cites The Journal of Physical Chemistry B128(28), 6693–6703 (2024) https: //doi.org/10.1021/acs.jpcb.4c01417 https://doi.org/10.1021/acs.jpcb.4c01417.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy The Journal of Physical Chemistry B128(28), 6693–6703 (2024) https: //doi.org/10.1021/acs.jpcb.4c01417 https://doi.org/10.1021/acs.jpcb.4c01417

Reference 49

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.511991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 398fd6b2-3f38-43b4-bf26-b14a10123a77 · outbound

This paper cites Journal of the American Chemical Society148(5), 4928–4937 (2026) https://doi.org/10.1 021/jacs.5c10940 https://doi.org/10.1021/jacs.5c10940.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of the American Chemical Society148(5), 4928–4937 (2026) https://doi.org/10.1 021/jacs.5c10940 https://doi.org/10.1021/jacs.5c10940

Reference 50

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.582784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9e1538f8-522f-4e94-9745-0062165e1aa8 · outbound

This paper cites Scientific Data10(1), 11 (2023) https://doi.org/10.1038/ s41597-022-01882-6.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Scientific Data10(1), 11 (2023) https://doi.org/10.1038/ s41597-022-01882-6

Reference 51

Resolution: malformed identifier; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c70a11d5-86be-4b49-bf40-d4a622ec7498 · outbound

This paper cites Journal of Chemical Theory and Computation16(7), 4192–4202 (2020) https://doi.org/10.1021/acs.jctc.0c00121 https://doi.org/10.1021/acs.jctc.0c00121.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Chemical Theory and Computation16(7), 4192–4202 (2020) https://doi.org/10.1021/acs.jctc.0c00121 https://doi.org/10.1021/acs.jctc.0c00121

Reference 52

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.503058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5a5dc498-fec7-45c0-824e-2a82e1892e5a · outbound

This paper cites first-principles.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy first-principles

Reference 53

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.462809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 065aabbd-6f4d-426a-bab5-dbed92c2cb4c · outbound

This paper cites Chemical Physics258(2), 121–137 (2000) https://doi.org/10.1016/S0301-0104(00)00179-8.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Chemical Physics258(2), 121–137 (2000) https://doi.org/10.1016/S0301-0104(00)00179-8

Reference 54

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.507343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dcf5bde4-942e-4798-991a-2e043dd47202 · outbound

This paper cites Nucleic Acids Research43(D1), 376–381 (2014) https://doi.or g/10.1093/nar/gku947 https://academic.oup.com/nar/article-pdf/43/D1/D376/7330586/gku947.pdf.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Nucleic Acids Research43(D1), 376–381 (2014) https://doi.or g/10.1093/nar/gku947 https://academic.oup.com/nar/article-pdf/43/D1/D376/7330586/gku947.pdf

Reference 55

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.562075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f0ba049c-2153-4ef2-87e1-8e177858b9b7 · outbound

This paper cites mdCATH: A Large-Scale MD Dataset for Data-Driven Computational Biophysics.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy mdCATH: A Large-Scale MD Dataset for Data-Driven Computational Biophysics

Reference 56

Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdb970ec-c006-459f-bb0b-99e5459c1f83 · outbound

This paper cites Chemical Engineering Journal418, 129307 (2021) https://doi.org/10.1016/j.cej.2021.129307.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Chemical Engineering Journal418, 129307 (2021) https://doi.org/10.1016/j.cej.2021.129307

Reference 57

Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc2129b3-1b58-450e-b479-adf9fe7c5369 · outbound

This paper cites Nature Communications12(1), 6884 (2021) https://doi.org/10.1038/s41467-021-27241-4.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Nature Communications12(1), 6884 (2021) https://doi.org/10.1038/s41467-021-27241-4

Reference 58

Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b8c22db-e047-4f6b-a6e3-50436759e9fe · outbound

This paper cites an unresolved cited work.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Unresolved cited work

Reference 59

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.543396Z

Source-reported events for the cited work

correction dated 2005-04-26. Source: crossref record 10.1063/1.1740022->10.1063/1.1740409:correction, observed 2026-07-11T03:00:28.525025+00:00. This notice travels one citation hop only.

Observation d69ecba5-49b1-4980-9dc6-aeb36de72145 · outbound

This paper cites Journal of Chemical Information and Modeling60(12), 6258–6268 (2020) https://doi.org/10.1021/acs.jcim.0c00904 https://doi.org/10.1021/acs.jcim.0c00904.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Chemical Information and Modeling60(12), 6258–6268 (2020) https://doi.org/10.1021/acs.jcim.0c00904 https://doi.org/10.1021/acs.jcim.0c00904

Reference 61

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.467501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e3cf9c7b-29cb-4fa1-9aae-315a8a7da2e5 · outbound

This paper cites Journal of Chemical Information and Modeling64(20), 7938–7948 (2024) https://doi.org/10.1021/acs.jcim.4c01120 https://doi.org/10.1021/acs.jcim.4c01120.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Chemical Information and Modeling64(20), 7938–7948 (2024) https://doi.org/10.1021/acs.jcim.4c01120 https://doi.org/10.1021/acs.jcim.4c01120

Reference 62

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.437713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 798d3695-90d2-4aa8-9999-05d028dd7221 · outbound

This paper cites The Lancet Neurology15(4), 373–381 (2016) https://doi.org/10.1016/S1474-4422(16)00018-1.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy The Lancet Neurology15(4), 373–381 (2016) https://doi.org/10.1016/S1474-4422(16)00018-1

Reference 63

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.486056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dfc95427-f44f-4f89-b522-e51ee64bc70e · outbound

This paper cites Nature Reviews Drug Discovery7(7), 608–624 (2008) https://doi.org/10.103 8/nrd2590.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Nature Reviews Drug Discovery7(7), 608–624 (2008) https://doi.org/10.103 8/nrd2590

Reference 64

Resolution: malformed identifier; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e8ed673-a2e0-4a67-8e48-c7d154514315 · outbound

This paper cites Journal of Chemical Information and Modeling63(1), 138–146 (2023) https://doi.org/10.1021/acs.jcim.2c01093 https://doi.org/10.1021/acs.jcim.2c01093.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Chemical Information and Modeling63(1), 138–146 (2023) https://doi.org/10.1021/acs.jcim.2c01093 https://doi.org/10.1021/acs.jcim.2c01093

Reference 65

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.494247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 29d6dbcd-dbf4-4f54-b635-1d60370bf699 · outbound

This paper cites Journal of Chemical Information and Modeling58(5), 982–992 (2018) https://doi.org/10.1021/acs.jcim.8b00097 https://doi.org/10.1021/acs.jcim.8b00097.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Chemical Information and Modeling58(5), 982–992 (2018) https://doi.org/10.1021/acs.jcim.8b00097 https://doi.org/10.1021/acs.jcim.8b00097

Reference 66

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.490477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 122645d8-96d5-4f1e-b8db-c9b104a0fa66 · outbound

This paper cites PMID: 31751129.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy PMID: 31751129

Reference 67

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.498761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 53f44ab4-dfc5-492a-9ff4-52846d240eb7 · outbound

This paper cites The Journal of Physical Chemistry B125(14), 3598–3612 (2021) https://doi.org/ 10.1021/acs.jpcb.0c10401 https://doi.org/10.1021/acs.jpcb.0c10401.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy The Journal of Physical Chemistry B125(14), 3598–3612 (2021) https://doi.org/ 10.1021/acs.jpcb.0c10401 https://doi.org/10.1021/acs.jpcb.0c10401

Reference 69

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.533924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 71c465b6-a303-48fe-873d-d5767cc61a62 · outbound

This paper cites The Journal of Physical Chemistry Letters12(32), 7701–7707 (2021) https://doi.org/10.1021/acs.jpclett.1c01987 https://doi.org/10.1021/acs.jpclett.1c01987.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy The Journal of Physical Chemistry Letters12(32), 7701–7707 (2021) https://doi.org/10.1021/acs.jpclett.1c01987 https://doi.org/10.1021/acs.jpclett.1c01987

Reference 70

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.557693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ba40e331-e2c5-41ae-9e0a-7b3040e7b72f · outbound

This paper cites Journal of Computational Chemistry34(25), 2135–2145 (2013) https://doi.org/10.1002/jc c.23354 https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.23354.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Computational Chemistry34(25), 2135–2145 (2013) https://doi.org/10.1002/jc c.23354 https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.23354

Reference 71

Resolution: malformed identifier; doi_truncated, observed 2026-07-14T08:40:21.442841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 72687d9b-d58c-4c22-a1a1-621673c8cbaf · outbound

This paper cites Biophysical Journal99(2), 647–655 (2010) https://doi.org/10.1016/j.bp j.2010.04.062.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Biophysical Journal99(2), 647–655 (2010) https://doi.org/10.1016/j.bp j.2010.04.062

Reference 72

Resolution: malformed identifier; doi_truncated, observed 2026-07-14T08:40:21.451911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5aca364a-b36e-422c-a785-48755106b45d · outbound

This paper cites PLOS ONE7(2), 1–6 (2012) https://doi.org/10.1371/jour nal.pone.0032131.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy PLOS ONE7(2), 1–6 (2012) https://doi.org/10.1371/jour nal.pone.0032131

Reference 73

Resolution: malformed identifier; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 479306dc-e68e-4ab8-8c44-d41fa5db34cd · outbound

This paper cites Journal of the American Chemical Society124(47), 14221–14226 (2002) https://doi.org/10.1021/ja0273288 https://doi.org/10.1021/ja0273288.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of the American Chemical Society124(47), 14221–14226 (2002) https://doi.org/10.1021/ja0273288 https://doi.org/10.1021/ja0273288

Reference 75

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.534795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 06b3a135-9e71-4f06-8baa-d5c9f408394a · outbound

This paper cites Protein Science10(9), 1856–1868 (2001) https://doi.org/10.1110/ps.14301 https://onlinelibrary.wiley.com/doi/pdf/10.1110/ps.14301.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Protein Science10(9), 1856–1868 (2001) https://doi.org/10.1110/ps.14301 https://onlinelibrary.wiley.com/doi/pdf/10.1110/ps.14301

Reference 76

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.538250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ad424233-bbfc-47c5-9a22-41c613f831e7 · outbound

This paper cites Journal of the American Chemical Society117(50), 12562–12566 (1995) https://doi.org/10 .1021/ja00155a020 https://doi.org/10.1021/ja00155a020.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of the American Chemical Society117(50), 12562–12566 (1995) https://doi.org/10 .1021/ja00155a020 https://doi.org/10.1021/ja00155a020

Reference 78

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.651968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 464de351-c2ed-49a2-a84f-01ada5bfb5d3 · outbound

This paper cites Journal of the American Chemical Society133(4), 909–919 (2011) https://doi.org/10.1021/ja107847d https://doi.org/10.1021/ja107847d.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of the American Chemical Society133(4), 909–919 (2011) https://doi.org/10.1021/ja107847d https://doi.org/10.1021/ja107847d

Reference 79

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.447292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0f3b83f2-9901-416f-aeb3-88d7c3cad9a0 · outbound

This paper cites Journal of the American Chemical Society121(12), 2891–2902 (1999) https://doi.org/10.1021/ja983758f https://doi.org/10.1021/ja983758f.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of the American Chemical Society121(12), 2891–2902 (1999) https://doi.org/10.1021/ja983758f https://doi.org/10.1021/ja983758f

Reference 80

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.636525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c2d7889d-5ce1-4fab-a44d-9eabb6e95f8d · outbound

This paper cites Journal of Chemi- cal Theory and Computation21(24), 12709–12724 (2025) https://doi.org/10.1021/acs.jctc.5c01400 https://doi.org/10.1021/acs.jctc.5c01400.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Chemi- cal Theory and Computation21(24), 12709–12724 (2025) https://doi.org/10.1021/acs.jctc.5c01400 https://doi.org/10.1021/acs.jctc.5c01400

Reference 81

Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e2cbfde-c4d0-49a4-823f-f2ff5e05a5e6 · outbound

This paper cites Journal of Chemical Theory and Computation11(7), 3420–3431 (2015) https://doi.org/10.1021/ct501178z https://doi.org/10.1021/ct501178z.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Chemical Theory and Computation11(7), 3420–3431 (2015) https://doi.org/10.1021/ct501178z https://doi.org/10.1021/ct501178z

Reference 82

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.591649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bc4958cd-a6e0-4281-b5a5-197bdde6ef77 · outbound

This paper cites Current Opinion in Structural Biology48, 40–48 (2018) https://doi.org/10.1016/j.sbi.2017.10.008.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Current Opinion in Structural Biology48, 40–48 (2018) https://doi.org/10.1016/j.sbi.2017.10.008

Reference 83

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.478131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e6b59e53-624e-4532-b4e5-7a9a8a4c12ce · outbound

This paper cites Journal of Chemical Theory and Computation11(11), 5513–5524 (2015) https://doi.org/10.1021/acs.jctc.5b00736 https://doi.org/10.1021/acs.jctc.5b00736.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Chemical Theory and Computation11(11), 5513–5524 (2015) https://doi.org/10.1021/acs.jctc.5b00736 https://doi.org/10.1021/acs.jctc.5b00736

Reference 84

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.598980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7a96c6b0-6f35-40d9-a552-7ea9d908748b · outbound

This paper cites The Journal of Chemical Physics153(19), 194101 (2020) https://doi.org/10.1063/5.0026133.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy The Journal of Chemical Physics153(19), 194101 (2020) https://doi.org/10.1063/5.0026133

Reference 85

Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cebbb5f-fe55-435b-bb30-28a4c536e2a3 · outbound

This paper cites The Journal of Chemical Physics 139(9), 090901 (2013) https://doi.org/10.1063/1.4818908.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy The Journal of Chemical Physics 139(9), 090901 (2013) https://doi.org/10.1063/1.4818908

Reference 86

Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb627de4-6b37-4d02-a7ab-8e3b22b92da8 · outbound

This paper cites In: Karabencheva-Christova, T.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy In: Karabencheva-Christova, T

Reference 87

Resolution: malformed identifier; doi_truncated, observed 2026-07-14T08:40:21.481390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d148d678-7c8b-444c-a620-efe3e477efde · outbound

This paper cites Journal of the American Chemical Society121(26), 6275–6279 (1999) https://doi.org/10.1021/ja9909024 https://doi.org/10.1021/ja9909024.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of the American Chemical Society121(26), 6275–6279 (1999) https://doi.org/10.1021/ja9909024 https://doi.org/10.1021/ja9909024

Reference 88

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.618140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6a51b4c3-0390-4bc1-9714-c992bf276716 · outbound

This paper cites Progress in Nuclear Magnetic Resonance Spectroscopy45(3), 275–300 (2004) https: //doi.org/10.1016/j.pnmrs.2004.08.001.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Progress in Nuclear Magnetic Resonance Spectroscopy45(3), 275–300 (2004) https: //doi.org/10.1016/j.pnmrs.2004.08.001

Reference 89

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.442714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4b9f4e99-37c6-4959-b217-820b27aed7b4 · outbound

This paper cites Journal of the American Chemical Society124(15), 4158–4168 (2002) https://doi.org/10.1021/ja012674v https://doi.org/10.1021/ja012674v.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of the American Chemical Society124(15), 4158–4168 (2002) https://doi.org/10.1021/ja012674v https://doi.org/10.1021/ja012674v

Reference 90

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.701266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e3798167-b855-4bca-ad88-8fc4ca509930 · outbound

This paper cites Nature Chem4, 711–717 (2012) https://doi.org/10.1038/ nchem.1396.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Nature Chem4, 711–717 (2012) https://doi.org/10.1038/ nchem.1396

Reference 91

Resolution: malformed identifier; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6e78ad2-e35e-4166-88ae-abafb9db9c17 · outbound

This paper cites Chemical Science10(33), 7734–7745 (2019) https://doi.org/10.1039/c9sc01496a.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Chemical Science10(33), 7734–7745 (2019) https://doi.org/10.1039/c9sc01496a

Reference 92

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.523164Z

Source-reported events for the cited work

correction dated 2019-08-20. Source: crossref record 10.1039/c9sc90176k->10.1039/c9sc01496a:correction, observed 2026-07-11T03:06:52.195658+00:00. This notice travels one citation hop only.

Observation c145159a-d309-47c6-adfd-f35d22cc4a5f · outbound

This paper cites RSC Adv.3, 25252–25257 (2013) https://doi.org/10.1039/C3RA44077J.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy RSC Adv.3, 25252–25257 (2013) https://doi.org/10.1039/C3RA44077J

Reference 93

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.726336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d88e729c-dbb6-42be-9aab-7dd98c88c36d · outbound

This paper cites Journal of the American Chemical Society121(12), 2949–2950 (1999) https://doi.org/10.1021/ja 9902221 https://doi.org/10.1021/ja9902221.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of the American Chemical Society121(12), 2949–2950 (1999) https://doi.org/10.1021/ja 9902221 https://doi.org/10.1021/ja9902221

Reference 94

Resolution: malformed identifier; doi_truncated, observed 2026-07-14T08:40:21.749030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b16987b4-e630-4daf-91ab-f8b451e0be48 · outbound

This paper cites Journal of the American Chemical Society133(24), 9192–9195 (2011) https://doi.org/10.1021/ja202219n https://doi.org/10.1021/ja202219n.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of the American Chemical Society133(24), 9192–9195 (2011) https://doi.org/10.1021/ja202219n https://doi.org/10.1021/ja202219n

Reference 95

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.719148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1c1ae48a-ed4e-47c2-b83f-b33e6eb8f8d3 · outbound

This paper cites Journal of Chemical Information and Modeling60(3), 1453–1460 (2020) https: //doi.org/10.1021/acs.jcim.9b01171 https://doi.org/10.1021/acs.jcim.9b01171.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Chemical Information and Modeling60(3), 1453–1460 (2020) https: //doi.org/10.1021/acs.jcim.9b01171 https://doi.org/10.1021/acs.jcim.9b01171

Reference 96

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.555703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4848c84c-9d57-43d2-8b82-eb53816cbaa7 · outbound

This paper cites https://arxiv.org/abs/2602.19411.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy https://arxiv.org/abs/2602.19411

Reference 97

Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 814d82d6-1b81-4610-902a-62bc6871b6d1 · outbound

This paper cites Computer Physics Communications271, 108171 (2022) https://doi.org/10.1016/j.cpc.2021.108171.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Computer Physics Communications271, 108171 (2022) https://doi.org/10.1016/j.cpc.2021.108171

Reference 98

Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation edf0bca8-1728-4a1d-a68b-bdfdfcef2805 · outbound

This paper cites An Efficient Sparse Kernel Generator for O(3)-Equivariant Deep Networks.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy An Efficient Sparse Kernel Generator for O(3)-Equivariant Deep Networks

Reference 99

Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fb96852-4b31-404c-98cf-a1b0db49aaae · outbound

This paper cites The Journal of Physical Chemistry B128(1), 109–116 (2024) https://doi.org/10.1021/acs.jpcb.3c06662 https://doi.org/10.1021/acs.jpcb.3c06662.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy The Journal of Physical Chemistry B128(1), 109–116 (2024) https://doi.org/10.1021/acs.jpcb.3c06662 https://doi.org/10.1021/acs.jpcb.3c06662

Reference 100

Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7224f6ae-ec46-4e4d-9c0f-2c9ee441aa5c · outbound

This paper cites Biophysical Journal108(5), 1153–1164 (2015) https://doi.org/10.1016/j.bpj.2014.12.047 21.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Biophysical Journal108(5), 1153–1164 (2015) https://doi.org/10.1016/j.bpj.2014.12.047 21

Reference 101

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.715755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2a4e0981-d9ce-47f5-aad8-5fb3eac34cb5 · outbound

This paper cites Journal of Chemical Theory and Computation8(4), 1409–1414 (2012) https://doi.org/10.1021/ct2007814 https://doi.org/10.1021/ct2007814.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Journal of Chemical Theory and Computation8(4), 1409–1414 (2012) https://doi.org/10.1021/ct2007814 https://doi.org/10.1021/ct2007814

Reference 102

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.635233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 767a120c-65db-4df5-8645-4da8092c2b7f · outbound

This paper cites Proteins: Structure, Function, and Bioinformatics85(10), 1944–1956 (2017) https://doi.org/10.1002/prot.25350 https://onlinelibrary.wiley.com/doi/pdf/10.1002/prot.25350.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Proteins: Structure, Function, and Bioinformatics85(10), 1944–1956 (2017) https://doi.org/10.1002/prot.25350 https://onlinelibrary.wiley.com/doi/pdf/10.1002/prot.25350

Reference 103

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.723224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation de692665-4cd1-4f85-a72c-8fe338976966 · outbound

This paper cites Structure-Based Experimental Datasets for Benchmarking Protein Simulation Force Fields.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Structure-Based Experimental Datasets for Benchmarking Protein Simulation Force Fields

Reference 104

Resolution: unresolved; no resolver link, observed 2026-07-14T08:32:21.172051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e5e71b1-8680-4b53-a603-b657d04749a9 · outbound

This paper cites J Chem Theory Comput11(6), 2783–2791 (2015) https://doi.org/10.1021/acs.jctc.5b00056.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy J Chem Theory Comput11(6), 2783–2791 (2015) https://doi.org/10.1021/acs.jctc.5b00056

Reference 105

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.551207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 15b58315-9806-48a0-8e54-cf4dd767c687 · outbound

This paper cites Scientific Reports15(1), 37169 (2025) https: //doi.org/10.1038/s41598-025-24757-3.

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy Scientific Reports15(1), 37169 (2025) https: //doi.org/10.1038/s41598-025-24757-3

Reference 106

Resolution: verified exact; doi, observed 2026-07-14T08:40:21.572754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers