The DOI matches its Crossref record.
PROPKA3: Consistent Treatment of Internal and Surface Residues in Empirical p KaPredictions
Abstract
In this study, we have revised the rules and parameters for one of the most commonly used empirical pKa predictors, PROPKA, based on better physical description of the desolvation and dielectric response for the protein. We have introduced a new and consistent approach to interpolate the description between the previously distinct classifications into internal and surface residues, which otherwise is found to give rise to an erratic and discontinuous behavior. Since the goal of this study is to lay out the framework and validate the concept, it focuses on Asp and Glu residues where the protein pKa values and structures are assumed to be more reliable. The new and improved implementation is evaluated and discussed; it is found to agree better with experiment than the previous implementation (in parentheses): rmsd = 0.79 (0.91) for Asp and Glu, 0.75 (0.97) for Tyr, 0.65 (0.72) for Lys, and 1.00 (1.37) for His residues. The most significant advance, however, is in reducing the number of outliers and removing unreasonable sensitivity to small structural changes that arise from classifying residues as either internal or surface.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 35
- Raquet X., 1997, Biophys. J., 73, 2416, 10.1016/S0006-3495(97)78270-5 · DOI
- Nielsen J. E., 2003, Protein Sci., 12, 1894, 10.1110/ps.03114903 · DOI
- Lamotte-Brasseur J., 1999, Protein Sci., 8, 404, 10.1110/ps.8.2.404 · DOI
- Lamotte-Brasseur J., 2000, Proteins, 40, 23, 10.1002/(SICI)1097-0134(20000701)40:1<23::AID-PROT40>3.0.CO;2-7 · DOI
- Warshel A., 1981, Biochemistry, 20, 3167, 10.1021/bi00514a028 · DOI
- Warshel A., 1981, Acc. Chem. Res., 14, 284, 10.1021/ar00069a004 · DOI
- Gunner M. R., 2006, Biochim. Biophys. Acta, Bioenerg., 1757, 942, 10.1016/j.bbabio.2006.06.005 · DOI
- Gunner M. R., 2000, Biochim. Biophys. Acta, Bioenerg., 1458, 63, 10.1016/S0005-2728(00)00060-8 · DOI
- Beroza P., 1998, Energ. Biol. Macromol., Part B, 295, 170, 10.1016/S0076-6879(98)95040-6 · DOI
- Warshel A., 1998, Curr. Opin. Struct. Biol., 8, 211, 10.1016/S0959-440X(98)80041-9 · DOI · Paper page
- Ullmann G. M., 1999, Eur. Biophys. J. Biophys., 28, 533, 10.1007/s002490050236 · DOI
- Nielsen J. E., 2003, Protein Sci., 12, 313, 10.1110/ps.0229903 · DOI
- Mongan J., 2005, Curr. Opin. Struct. Biol., 15, 157, 10.1016/j.sbi.2005.02.002 · DOI
- Lee A. C., 2009, J. Chem. Inf. Model., 49, 2013, 10.1021/ci900209w · DOI
- Davies M. N., 2006, BMC Biochem., 7, 10.1186/1471-2091-7-18 · DOI
- Stanton C. L., 2008, J. Chem. Theory. Comput., 4, 951, 10.1021/ct8000014 · DOI
- Li H., 2005, Proteins, 61, 704, 10.1002/prot.20660 · DOI · Paper page
- Bas D. C., 2008, Proteins, 73, 765, 10.1002/prot.22102 · DOI
- Tanford C., 1957, J. Am. Chem. Soc., 79, 5333, 10.1021/ja01577a001 · DOI
- Warshel A., 1984, Proc. Natl. Acad. Sci., India, Sect. B, 81, 4785, 10.1073/pnas.81.15.4785 · DOI
- Tanford C., 1972, Biochemistry, 11, 2192-&, 10.1021/bi00761a029 · DOI
- Mallik B., 2002, J. Comput. Chem., 23, 1090, 10.1002/jcc.10104 · DOI
- Schutz C. N., 2001, Proteins, 44, 400, 10.1002/prot.1106 · DOI
- Sham Y. Y., 1997, J. Phys. Chem. B, 101, 4458, 10.1021/jp963412w · DOI
- Mehler E. L., 1999, Biophys. J., 77, 3, 10.1016/S0006-3495(99)76868-2 · DOI
- Jensen J. H., 2005, J. Phys. Chem. A, 109, 6634, 10.1021/jp051922x · DOI
- Olsson M. H. M., 2003, J. Am. Chem. Soc., 125, 5025, 10.1021/ja0212157 · DOI
- Powers N., 2006, J. Biomol. NMR, 35, 39, 10.1007/s10858-006-9003-3 · DOI
- Forsyth W. R., 2002, Proteins, 48, 388, 10.1002/prot.10174 · DOI
- Song Y. F., 2009, J. Comput. Chem., 30, 2231, 10.1002/jcc.21222 · DOI
- Hassan S. A., 2000, J. Phys. Chem. B, 104, 6490, 10.1021/jp9938967 · DOI
- Wisz M. S., 2003, Proteins, 51, 360, 10.1002/prot.10332 · DOI
- Simonson T., 2004, J. Am. Chem. Soc., 126, 4167, 10.1021/ja039788m · DOI · Paper page
- Pokala N., 2004, Protein Sci., 13, 925, 10.1110/ps.03486104 · DOI
- Georgescu R. E., 2002, Biophys. J., 83, 1731, 10.1016/S0006-3495(02)73940-4 · DOI
Cited by
Structure of hepcidin-bound ferroportin reveals iron homeostatic mechanisms
Billesbølle, C. B., Azumaya, C. M., Kretsch, R. C., Powers, A. S., Gonen, S., Schneider, S., Arvedson, T., Dror, R. O., Cheng, Y., & Manglik, A. (2020) · Nature · doi:10.1038/s41586-020-2668-z · Cited by 344
SARS-CoV-2 escape in vitro from a highly neutralizing COVID-19 convalescent plasma
Andreano, E., Piccini, G., Licastro, D., Casalino, L., Johnson, N. V., Paciello, I., Monego, S. D., Pantano, E., Manganaro, N., Manenti, A., et al. (2020) · doi:10.1101/2020.12.28.424451
Eckhard, U., Huesgen, P. F., Schilling, O., Bellac, C. L., Butler, G. S., Cox, J. H., Dufour, A., Goebeler, V., Kappelhoff, R., Keller, U. A. D., et al. (2016) · Matrix Biology · doi:10.1016/j.matbio.2015.09.003 · Cited by 212
Efficient Determination of Protein–Protein Standard Binding Free Energies from First Principles
Gumbart, J. C., Roux, B., & Chipot, C. (2013) · Journal of Chemical Theory and Computation · doi:10.1021/ct400273t · Cited by 211
Perspective on the Current State-of-the-Art of Quantum Computing for Drug Discovery Applications
Blunt, N. S., Camps, J., Crawford, O., Izsák, R., Leontica, S., Mirani, A., Moylett, A. E., Scivier, S. A., Sünderhauf, C., Schopf, P., et al. (2022) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.2c00574 · Cited by 192
Crystal structures of a GABAA-receptor chimera reveal new endogenous neurosteroid-binding sites.
Laverty, D., Thomas, P., Field, M., Andersen, O. J., Gold, M. G., Biggin, P. C., Gielen, M., & Smart, T. G. (2017) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.3477 · Cited by 179
Direct protein-lipid interactions shape the conformational landscape of secondary transporters
Martens, C., Shekhar, M., Borysik, A. J., Lau, A. M., Reading, E., Tajkhorshid, E., Booth, P. J., & Politis, A. (2018) · Nature Communications · doi:10.1038/s41467-018-06704-1 · Cited by 134
Martinize2 and Vermouth provide a unified framework for molecular topology generation
Kroon, P. C., Grünewald, F., Barnoud, J., van Tilburg, M., Brasnett, C., Souza, P. C., Wassenaar, T. A., & Marrink, S. J. (2025) · eLife · doi:10.7554/elife.90627 · Cited by 124
Lai, P.-K., Gallegos, A., Mody, N., Sathish, H. A., & Trout, B. L. (2022) · mAbs · doi:10.1080/19420862.2022.2026208 · Cited by 103
Bat genomes illuminate adaptations to viral tolerance and disease resistance
Morales, A. E., Dong, Y., Brown, T., Baid, K., Kontopoulos, D. G., Gonzalez, V., Huang, Z., Ahmed, A.-W., Bhuinya, A., Hilgers, L., et al. (2025) · Nature · doi:10.1038/s41586-024-08471-0 · Cited by 78
Mutations along a TET2 active site scaffold stall oxidation at 5-hydroxymethylcytosine
Liu, M. Y., Torabifard, H., Crawford, D. J., DeNizio, J. E., Cao, X.-J., Garcia, B. A., Cisneros, G. A., & Kohli, R. M. (2017) · Nature Chemical Biology · doi:10.1038/nchembio.2250 · Cited by 78
Computational enzyme design by catalytic motif scaffolding
Braun, M., Tripp, A., Chakatok, M., Kaltenbrunner, S., Fischer, C., Stoll, D., Bijelic, A., Elaily, W., Totaro, M. G., Moser, M., et al. (2026) · Nature · doi:10.1038/s41586-025-09747-9 · Cited by 73
Computational Alanine Scanning Mutagenesis: MM-PBSA vs TI
Martins, S. A., Perez, M. A. S., Moreira, I. S., Sousa, S. F., Ramos, M. J., & Fernandes, P. A. (2013) · Journal of Chemical Theory and Computation · doi:10.1021/ct4000372 · Cited by 72
Improving the Accuracy of Protein Thermostability Predictions for Single Point Mutations
Duan, J., Lupyan, D., & Wang, L. (2020) · Biophysical Journal · doi:10.1016/j.bpj.2020.05.020 · Cited by 63
Development of covalent inhibitors: Principle, design, and application in cancer
Zheng, L., Li, Y., Wu, D., Xiao, H., Zheng, S., Wang, G., & Sun, Q. (2023) · MedComm – Oncology · doi:10.1002/mog2.56 · Cited by 71
Kosugi, T., & Hayashi, S. (2012) · Journal of the American Chemical Society · doi:10.1021/ja212117m · Cited by 58
Zhang, L., Zhang, D., Wang, X., Yuan, C., Li, Y., Jia, X., Gao, X., Yen, H.-L., Cheung, P. P.-H., & Huang, X. (2021) · Physical Chemistry Chemical Physics · doi:10.1039/d0cp05948j · Cited by 52
Lai, P.-K., Fernando, A., Cloutier, T. K., Kingsbury, J. S., Gokarn, Y., Halloran, K. T., Calero-Rubio, C., & Trout, B. L. (2021) · Journal of Pharmaceutical Sciences · doi:10.1016/j.xphs.2020.12.014 · Cited by 45
EnzyHTP: A High-Throughput Computational Platform for Enzyme Modeling
Shao, Q., Jiang, Y., & Yang, Z. J. (2022) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.1c01424 · Cited by 43
Three-step docking by WIPI2, ATG16L1, and ATG3 delivers LC3 to the phagophore
Rao, S., Skulsuppaisarn, M., Strong, L. M., Ren, X., Lazarou, M., Hurley, J. H., & Hummer, G. (2024) · Science Advances · doi:10.1126/sciadv.adj8027 · Cited by 40
Butler, V. J., Gao, F., Corrales, C. I., Cortopassi, W. A., Caballero, B., Vohra, M., Ashrafi, K., Cuervo, A. M., Jacobson, M. P., Coppola, G., et al. (2019) · PLOS Genetics · doi:10.1371/journal.pgen.1008295 · Cited by 39
Roth, O., Yechezkel, S., Serero, O., Eliyahu, A., Vints, I., Tzeela, P., Carignano, A., Janacek, D. P., Peters, V., Kessel, A., et al. (2024) · Nature Biotechnology · doi:10.1038/s41587-023-02065-3 · Cited by 39
Biological and Computational Evaluation of Resveratrol Inhibitors against Alzheimer's Disease
Koukoulitsa, C., Villalonga-Barber, C., Csonka, R., Alexi, X., Leonis, G., Dellis, D., Hamelink, E., Belda, O., Steele, B. R., Micha-Screttas, M., et al. (2016) · Journal of Enzyme Inhibition and Medicinal Chemistry · doi:10.3109/14756366.2014.1003928 · Cited by 37
Protein p K a Prediction by Tree-Based Machine Learning
Chen, A. Y., Lee, J., Damjanovic, A., & Brooks, B. R. (2022) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.1c01257 · Cited by 37
Tandem metalloenzymes gate plant cell entry by pathogenic fungi
Bissaro, B., Kodama, S., Nishiuchi, T., Díaz-Rovira, A. M., Hage, H., Ribeaucourt, D., Haon, M., Grisel, S., Simaan, A. J., Beisson, F., et al. (2022) · Science Advances · doi:10.1126/sciadv.ade9982 · Cited by 37
Structural pathway for PI3-kinase regulation by VPS15 in autophagy
Cook, A. S. I., Chen, M., Nguyen, T. N., Cabezudo, A. C., Khuu, G., Rao, S., Garcia, S. N., Yang, M., Iavarone, A. T., Ren, X., et al. (2025) · Science · doi:10.1126/science.adl3787 · Cited by 34
Scarabelli, G., Oloo, E. O., Maier, J. K. X., & Rodriguez-Granillo, A. (2022) · Journal of Molecular Biology · doi:10.1016/j.jmb.2021.167375 · Cited by 33
Bashour, H., Smorodina, E., Pariset, M., Zhong, J., Akbar, R., Chernigovskaya, M., Lê Quý, K., Snapkow, I., Rawat, P., Krawczyk, K., et al. (2024) · Communications Biology · doi:10.1038/s42003-024-06561-3 · Cited by 32
Long, T., Li, D., Vale, G., Jiang, Y., Schmiege, P., Yang, Z. J., McDonald, J. G., & Li, X. (2024) · Cell · doi:10.1016/j.cell.2024.08.004 · Cited by 31
Basis for Accurate Protein p K a Prediction with Machine Learning
Cai, Z., Liu, T., Lin, Q., He, J., Lei, X., Luo, F., & Huang, Y. (2023) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.3c00254 · Cited by 31
Peck Justice, S. A., Barron, M. P., Qi, G. D., Wijeratne, H. R. S., Victorino, J. F., Simpson, E. R., Vilseck, J. Z., Wijeratne, A. B., & Mosley, A. L. (2020) · Journal of Biological Chemistry · doi:10.1074/jbc.ra120.014576 · Cited by 28
Peck Justice, S. A., Qi, G., Wijeratne, H. R. S., Victorino, J. F., Simpson, E. R., Wijeratne, A. B., & Mosley, A. L. (2019) · doi:10.1101/2019.12.30.891267 · Cited by 28
Coskun, D., Chen, W., Clark, A. J., Lu, C., Harder, E. D., Wang, L., Friesner, R. A., & Miller, E. B. (2022) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.2c00954 · Cited by 28
PcoB is a defense outer membrane protein that facilitates cellular uptake of copper
Li, P., Nayeri, N., Górecki, K., Becares, E. R., Wang, K., Mahato, D. R., Andersson, M., Abeyrathna, S. S., Lindkvist‐Petersson, K., Meloni, G., et al. (2022) · Protein Science · doi:10.1002/pro.4364 · Cited by 25
Molecular principles of redox-coupled sodium pumping of the ancient Rnf machinery
Kumar, A., Roth, J., Kim, H., Saura, P., Bohn, S., Reif-Trauttmansdorff, T., Schubert, A., Kaila, V. R. I., Schuller, J. M., & Müller, V. (2025) · Nature Communications · doi:10.1038/s41467-025-57375-8 · Cited by 24
Sampson, J. M., Cannon, D. A., Duan, J., Epstein, J. C. K., Sergeeva, A. P., Katsamba, P. S., Mannepalli, S. M., Bahna, F. A., Adihou, H., Guéret, S. M., et al. (2024) · Journal of Molecular Biology · doi:10.1016/j.jmb.2024.168640 · Cited by 24
Characterizing glucokinase variant mechanisms using a multiplexed abundance assay
Gersing, S., Schulze, T. K., Cagiada, M., Stein, A., Roth, F. P., Lindorff-Larsen, K., & Hartmann-Petersen, R. (2024) · Genome Biology · doi:10.1186/s13059-024-03238-2 · Cited by 23
Unraveling the nature of the catalytic power of fluoroacetate dehalogenase
Miranda‐Rojas, S., Fernández, I., Kästner, J., Toro‐Labbé, A., & Mendizábal, F. (2018) · ChemCatChem · doi:10.1002/cctc.201701517 · Cited by 23
Structural insights into the mechanism of phosphate recognition and transport by XPR1
Zhang, W., Chen, Y., Guan, Z., Wang, Y., Tang, M., Du, Z., Zhang, J., Cheng, M., Zuo, J., Liu, Y., et al. (2025) · Nature Communications · doi:10.1038/s41467-024-55471-9 · Cited by 20
Xie, B., Le Rouzic, V. P., Goldberg, A., Tsai, M.-H. M., Chen, L., Zhang, T., Sinha, A., Pan, Y.-X., Baumann, M. H., & Shi, L. (2023) · Neuropharmacology · doi:10.1016/j.neuropharm.2023.109442 · Cited by 18
Milk Protein Adsorption on Metallic Iron Surfaces
(2023) · doi:10.3390/nano13121857 · Cited by 17
Integrated Covalent Drug Design Workflow Using Site Identification by Ligand Competitive Saturation
Yu, W., Weber, D. J., & MacKerell, A. D. (2023) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.3c00232 · Cited by 16
Nordquist, E. B., Zhao, M., Kumar, A., & MacKerell, A. D. (2024) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.4c01189 · Cited by 15
Wozniak, S., Janson, G., & Feig, M. (2025) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.4c01682 · Cited by 14
Structural mechanisms for VMAT2 inhibition by tetrabenazine
Dalton, M. P., Cheng, M. H., Bahar, I., & Coleman, J. A. (2024) · eLife · doi:10.7554/elife.91973.4 · Cited by 14
Xu, S., & Onoda, A. (2025) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.4c01288 · Cited by 13
Photocobilins integrate B12 and bilin photochemistry for enzyme control
Zhang, S., Jeffreys, L. N., Poddar, H., Yu, Y., Liu, C., Patel, K., Johannissen, L. O., Zhu, L., Cliff, M. J., Yan, C., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-46995-1 · Cited by 13
Functional and structural analysis of a cyclization domain in a cyclic β-1,2-glucan synthase
Tanaka, N., Saito, R., Kobayashi, K., Nakai, H., Kamo, S., Kuramochi, K., Taguchi, H., Nakajima, M., & Masaike, T. (2024) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-024-13013-9 · Cited by 13
Samsudin, F., Gan, S. K.-E., & Bond, P. J. (2021) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2020.12.022 · Cited by 16
Spiegel, M. (2025) · Chemistry – A European Journal · doi:10.1002/chem.202403755 · Cited by 12
Targeting Tuberculosis: Novel Scaffolds for Inhibiting Cytochrome bd Oxidase
Seitz, C., Ahn, S.-H., Wei, H., Kyte, M., Cook, G. M., Krause, K. L., & McCammon, J. A. (2024) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.4c00344 · Cited by 11
ATP-Bound State of the Uncoupling Protein 1 (UCP1) from Molecular Simulations
Jacobsen, L., Lydersen, L., & Khandelia, H. (2023) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.3c03473 · Cited by 10
Multiscale modelling of biomolecular corona formation on metallic surfaces
Amini, P. M., Rouse, I., Subbotina, J., & Lobaskin, V. (2024) · Beilstein Journal of Nanotechnology · doi:10.3762/bjnano.15.21 · Cited by 10
Lisboa, J., Pereira, C., Pinto, R. D., Rodrigues, I. S., Pereira, L. M. G., Pinheiro, B., Oliveira, P., Pereira, P. J. B., Azevedo, J. E., Durand, D., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-43054-z · Cited by 9
Allosteric Regulation in the Ligand Binding Domain of Retinoic Acid Receptorγ
Chebaro, Y., Sirigu, S., Amal, I., Lutzing, R., Stote, R. H., Rochette-Egly, C., Rochel, N., & Dejaegere, A. (2017) · PLOS ONE · doi:10.1371/journal.pone.0171043 · Cited by 8
Berksoz, M., & Atilgan, C. (2024) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26688 · Cited by 8
Andjelkovic, M., Zinovjev, K., Ruiz-Pernía, J. J., & Tuñón, I. (2025) · ACS Catalysis · doi:10.1021/acscatal.4c07791 · Cited by 7
Deganutti, G., Pipito, L., Rujan, R. M., Weizmann, T., Griffin, P., Ciancetta, A., Moro, S., & Reynolds, C. A. (2025) · eLife · doi:10.7554/elife.96513 · Cited by 7
Engineering of soluble bacteriorhodopsin
Nikolaev, A., Orlov, Y., Tsybrov, F., Kuznetsova, E., Shishkin, P., Kuzmin, A., Mikhailov, A., Nikolaeva, Y. S., Anuchina, A., Chizhov, I., et al. (2025) · Chemical Science · doi:10.1039/d5sc02453f · Cited by 6
drMD: Molecular Dynamics for Experimentalists
Shrimpton-Phoenix, E., Notari, E., Kluonis, T., & Wood, C. W. (2025) · Journal of Molecular Biology · doi:10.1016/j.jmb.2024.168918 · Cited by 6
Tentonin 3 is a pore-forming subunit of a slow inactivation mechanosensitive channel
Pak, S., Ryu, H., Lim, S., Nguyen, T.-L., Yang, S., Kang, S., Yu, Y. G., Woo, J., Kim, C., Fenollar-Ferrer, C., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114334 · Cited by 6
Structural mechanisms for VMAT2 inhibition by tetrabenazine
Dalton, M. P., Cheng, M. H., Bahar, I., & Coleman, J. A. (2023) · doi:10.1101/2023.09.05.556211 · Cited by 6
Wang, B., Wang, C., Chen, J., Liu, D., Sun, C., Zhang, J., Zhang, K., & Li, H. (2026) · Nature Machine Intelligence · doi:10.1038/s42256-026-01198-9 · Cited by 5
Insights into the Catalytic Activity of a Metagenome-Derived Urethanase
Świderek, K., Arafet, K., de Sousa Batista, V., Grajales-Hernández, D., López-Gallego, F., & Moliner, V. (2025) · Journal of the American Chemical Society · doi:10.1021/jacs.5c13147 · Cited by 4
Coral anthozoan-specific opsins employ a novel chloride counterion for spectral tuning
Sakai, Y., Sen, S., Sugihara, T., Kakeyama, Y., Iwasaki, M., Schertler, G. F., Deupi, X., Koyanagi, M., & Terakita, A. (2025) · eLife · doi:10.7554/elife.105451 · Cited by 2
Molecular basis of prostaglandin E2 reuptake by organic anion transporter PGT
Zhu, Z., Li, Y., Xia, H., Yang, C., Zhou, Z., Chao, Y., Ba, Q., Li, D., & Qu, Q. (2025) · Nature Communications · doi:10.1038/s41467-025-67025-8 · Cited by 2
Coarse-Graining the Recognition of a Glycolipid by the C-Type Lectin Mincle Receptor
Noriega, M., Corey, R. A., Haanappel, E., Demange, P., Czaplicki, G., Atkinson, R. A., & Chavent, M. (2024) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.4c03242 · Cited by 2
De novo design of anti-variant COVID-19 vaccine
Goswami, A., Kumar, M., Ullah, S., & Gore, M. M. (2023) · Biology Methods and Protocols · doi:10.1093/biomethods/bpad021 · Cited by 2
Stuart, W. S., Jenkins, C. H., Ireland, P. M., Isupov, M. N., Norville, I. H., & Harmer, N. J. (2025) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2025.108517 · Cited by 1
Barron, M. P., Wijeratne, H. R. S., Runnebohm, A. M., Caric, K. M., Mosley, A. L., & Vilseck, J. Z. (2025) · doi:10.1101/2025.06.30.662390 · Cited by 1
Melet, L., Canan, J., Villalobos, P., Vidal-Veuthey, B., González-Toro, F., Orellana, I., Rivas-Pardo, J. A., Cárdenas, J. P., Moraga, C., Castro-Fernández, V., et al. (2025) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2025.11.009 · Cited by 1
Dluhosch, D., Kersten, L. S., Minges, A., Schott-Verdugo, S., Gohlke, H., & Groth, G. (2025) · doi:10.1101/2025.01.21.634023
Mechanistic origin of C - over O -glycosylation in glycosyltransferase GgCGT: a QM/MM study
Terada, D., Inagaki, T., & Hatanaka, M. (2026) · Bulletin of the Chemical Society of Japan · doi:10.1093/bulcsj/uoag026
Metadata
- Authors
- Olsson, M. H. M., Søndergaard, C. R., Rostkowski, M., & Jensen, J. H.
- Venue
- Journal of Chemical Theory and Computation
- Publisher
- American Chemical Society (ACS)
- Published
- 2011-01-06
- Volume
- 7
- Issue
- 2
- Pages
- 525-537
- ISSN
- 1549-9618 (ISSN-L)
- 1549-9626
- OpenAlex
- W2330799739
- Cited by
- 4,435
- References
- 0
- FWCI
- 35.27
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.