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AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading
Open accessAbstract
AutoDock Vina, a new program for molecular docking and virtual screening, is presented. AutoDock Vina achieves an approximately two orders of magnitude speed‐up compared with the molecular docking software previously developed in our lab (AutoDock 4), while also significantly improving the accuracy of the binding mode predictions, judging by our tests on the training set used in AutoDock 4 development. Further speed‐up is achieved from parallelism, by using multithreading on multicore machines. AutoDock Vina automatically calculates the grid maps and clusters the results in a way transparent to the user. © 2009 Wiley Periodicals, Inc. J Comput Chem 2010
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“each of four different vitamins (riboflavin, biotin, thiamine, and folate) were docked into the binding pocket of MMSYN1_0877.”
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Kennedy, J., & Eberhart, R. (2002) · Proceedings of ICNN'95 - International Conference on Neural Networks · doi:10.1109/icnn.1995.488968 · Cited by 58,192
Adaptation in Natural and Artificial Systems
Holland, J. H. (1992) · The MIT Press eBooks · doi:10.7551/mitpress/1090.001.0001 · Cited by 47,340
Optimization by Simulated Annealing
Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983) · Science · doi:10.1126/science.220.4598.671 · Cited by 45,134
AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility
Morris, G. M., Huey, R., Lindstrom, W., Sanner, M. F., Belew, R. K., Goodsell, D. S., & Olson, A. J. (2009) · Journal of Computational Chemistry · doi:10.1002/jcc.21256 · Cited by 26,294
Self-citationA new optimizer using particle swarm theory
Eberhart, R., & Kennedy, J. (2002) · MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science · doi:10.1109/mhs.1995.494215 · Cited by 16,067
Braun, W. J., & Murdoch, D. J. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108993456.011 · Cited by 14,099
Nocedal, J., & Wright, S. J. (1999) · Springer eBooks · doi:10.1007/b98874 · Cited by 9,563
Abagyan, R. A., Totrov, M. M., & Kuznetsov, D. (1994) · Journal of Computational Chemistry · doi:10.1002/jcc.540150503 · Cited by 1,718
The statistical-thermodynamic basis for computation of binding affinities: a critical review
Gilson, M. K., Given, J. A., Bush, B. L., & McCammon, J. A. (1997) · Biophysical Journal · doi:10.1016/s0006-3495(97)78756-3 · Cited by 1,222
Wang, R., Lai, L., & Wang, S. (2002) · Journal of Computer-Aided Molecular Design · doi:10.1023/a:1016357811882 · Cited by 1,185
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- Vanopdenbosch N., 1985, J Mol Graph, 3, 110
- Austern M. H., 1999, Generic Programming and the STL
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Sorted by citations
Items 901–1,000 of 1,093
Structural and Functional Roles of Glycosylation in Fungal Laccase from Lentinus sp.
Maestre‐Reyna, M., Liu, W.-C., Jeng, W. Y., Lee, C., Hsu, C.-A., Wen, T.-N., Wang, A. H. ‐., & Shyur, L. (2015) · PLoS ONE · doi:10.1371/journal.pone.0120601 · Cited by 104
Shi, S., Cai, Y., Cai, X., Zheng, X., Cao, D., Ye, F., & Xiang, Z. (2014) · PLoS ONE · doi:10.1371/journal.pone.0089123 · Cited by 99
Specificity of Processing α-Glucosidase I Is Guided by the Substrate Conformation
Barker, M., & Rose, D. R. (2013) · Journal of Biological Chemistry · doi:10.1074/jbc.m113.460436 · Cited by 102
Li, Y., & Yang, J. (2017) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.7b00049 · Cited by 100
Lichman, B. R., Zhao, J., Hailes, H. C., & Ward, J. M. (2017) · Nature Communications · doi:10.1038/ncomms14883 · Cited by 98
Lukinavičius, G., Mitronova, G. Y., Schnorrenberg, S., Butkevich, A. N., Barthel, H., Belov, V. N., & Hell, S. W. (2018) · Chemical Science · doi:10.1039/c7sc05334g · Cited by 98
Rajkumari, J., Borkotoky, S., Murali, A., Suchiang, K., Mohanty, S. K., & Busi, S. (2018) · Microbial Pathogenesis · doi:10.1016/j.micpath.2018.03.012 · Cited by 98
A review of mathematical representations of biomolecular data
Nguyen, D. D., Cang, Z., & Wei, G. (2020) · Physical Chemistry Chemical Physics · doi:10.1039/c9cp06554g · Cited by 101
Deswal, S., Naveen, N., Tittal, R. K., Vikas, D. G., Lal, K., & Kumar, A. (2020) · Journal of Molecular Structure · doi:10.1016/j.molstruc.2020.127982 · Cited by 98
Khan, A., Khan, M., Saleem, S., Babar, Z., Ali, A., Khan, A. A., Sardar, Z., Hamayun, F., Ali, S. S., & Wei, D. (2020) · Interdisciplinary Sciences Computational Life Sciences · doi:10.1007/s12539-020-00381-9 · Cited by 98
Bing, P., Zhou, W., & Tan, S. (2022) · Frontiers in Pharmacology · doi:10.3389/fphar.2022.865065 · Cited by 98
Gökçe, H., Şen, F., Sert, Y., Abdel-Wahab, B. F., Kariuki, B. M., & El-Hiti, G. A.-R. (2022) · Molecules · doi:10.3390/molecules27072193 · Cited by 99
Microbial engineering strategies to utilize waste feedstock for sustainable bioproduction
Aggarwal, N., Pham, H. L., Ranjan, B., Saini, M. K., Liang, Y., Hossain, G. S., Ling, H., Foo, J. L., & Chang, M. W. (2023) · Nature Reviews Bioengineering · doi:10.1038/s44222-023-00129-2 · Cited by 99
Malcor, J.-D. M., Payrot, N., David, M., Faucon, A., Abouzid, K., Jacquot, G., Floquet, N., Debarbieux, F. C., Rougon, G., Martínez, J., et al. (2012) · Journal of Medicinal Chemistry · doi:10.1021/jm2014919 · Cited by 105
DeKeyser, J. G., Laurenzana, E. M., Peterson, E. C., Chen, T., & Omiecinski, C. J. (2011) · Toxicological Sciences · doi:10.1093/toxsci/kfq394 · Cited by 98
Liu, X., Qu, X., Wu, C., Zhai, Z., Tian, B., Li, H., Ouyang, Z., Xu, X., Wang, W., Fan, Q., et al. (2014) · Biomaterials · doi:10.1016/j.biomaterials.2014.04.006 · Cited by 97
Issaoui, N., Ghalla, H., Bardak, F., Karabacak, M., Dlala, N. A., Flakus, H. T., & Oujia, B. (2016) · Journal of Molecular Structure · doi:10.1016/j.molstruc.2016.11.019 · Cited by 97
Ha, N., Jung, I., La, I.-J., Jung, H., & Yoon, M. (2017) · Scientific Reports · doi:10.1038/srep40305 · Cited by 97
Li, X., Guo, T., Lachmanski, L., Manoli, F., Menéndez-Miranda, M., Manet, I. G. J., Guo, Z., Wu, L., Zhang, J., & Gref, R. (2017) · International Journal of Pharmaceutics · doi:10.1016/j.ijpharm.2017.05.056 · Cited by 97
MDockPeP: An ab‐initio protein–peptide docking server
Xu, X., Yan, C., & Zou, X. (2018) · Journal of Computational Chemistry · doi:10.1002/jcc.25555 · Cited by 97
Thomas, R., Mary, Y. S., Resmi, K. S., Narayana, B., Sarojini, B. K., Vijayakumar, G., & Alsenoy, C. V. (2019) · Journal of Molecular Structure · doi:10.1016/j.molstruc.2019.01.003 · Cited by 97
Morrone, J. A., Weber, J. K., Huynh, T., Luo, H., & Cornell, W. D. (2020) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.9b00927 · Cited by 97
Alminderej, F. M., Bakari, S., Almundarij, T. I., Snoussi, M., Aouadi, K., & Kadri, A. (2020) · Plants · doi:10.3390/plants9111534 · Cited by 98
Arshia, A. H., Shadravan, S., Solhjoo, A., Sakhteman, A., & Sami, A. (2021) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2021.104967 · Cited by 97
Kansız, S., Azam, M., Basılı, T., Meral, S., Aktaş, F. A., Yeşilbağ, S., Kim, M., Ağar, A. A., & Dege, N. (2022) · Journal of Molecular Structure · doi:10.1016/j.molstruc.2022.133477 · Cited by 96
Spassov, D. S. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25137124 · Cited by 116
Secret of the major birch pollen allergen Bet v 1: identification of the physiological ligand
von Loetzen, C. S., Hoffmann, T., Hartl, M. J., Schweimer, K., Schwab, W. G., ROSCH, P. J., & Hartl‐Spiegelhauer, O. (2013) · Biochemical Journal · doi:10.1042/bj20130413 · Cited by 97
Histone Deacetylase Inhibitors Equipped with Estrogen Receptor Modulation Activity
Gryder, B. E., Rood, M. K., Johnson, K. A., Patil, V., Raftery, E. D., Yao, L.-P. D., Rice, M., Azizi, B., Doyle, D. F., & Oyelere, A. K. (2013) · Journal of Medicinal Chemistry · doi:10.1021/jm400467w · Cited by 97
Pharmacotherapy Evolution in Alzheimer’s Disease: Current Framework and Relevant Directions
Miculas, D. C., Negru, P. A., Bungau, S. G., Behl, T., Hassan, S. S. U., & Tit, D. M. (2022) · Cells · doi:10.3390/cells12010131 · Cited by 96
A PIK3C3–Ankyrin-B–Dynactin pathway promotes axonal growth and multiorganelle transport
Lorenzo, D. N., Badea, A., Davis, J. Q., Hostettler, J., He, J., Zhong, G., Zhuang, X., & Bennett, V. (2014) · The Journal of Cell Biology · doi:10.1083/jcb.201407063 · Cited by 98
Foulkes, D. M., Byrne, D. P., Bailey, F. P., Ferries, S., Eyers, P. A., Keeshan, K., Shrestha, S., Yeung, W., Kannan, N., Wells, C., et al. (2018) · Science Signaling · doi:10.1126/scisignal.aat7951 · Cited by 95
Banegas‐Luna, A. J., Cerón‐Carrasco, J. P., & Pérez‐Sánchez, H. (2018) · Future Medicinal Chemistry · doi:10.4155/fmc-2018-0076 · Cited by 101
Ortiz, C. L. D., Completo, G. C. J., Nacario, R. C., & Nellas, R. B. (2019) · Scientific Reports · doi:10.1038/s41598-019-52764-8 · Cited by 101
Yu, B., Zhou, S., Cao, L., Hao, Z., Yang, D., Guo, X., Zhang, N., Bakulev, V. A., & Fan, Z. (2020) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.0c00062 · Cited by 98
İçsel, C., Yılmaz, V. T., Aydınlık, Ş., & Aygün, M. (2020) · European Journal of Medicinal Chemistry · doi:10.1016/j.ejmech.2020.112535 · Cited by 98
An artificial metalloenzyme for catalytic cancer-specific DNA cleavage and operando imaging
Gao, L., Zhang, Y., Zhao, L., Niu, W., Tang, Y., Gao, F., Cai, P., Yuan, Q., Wang, X., Jiang, H., et al. (2020) · Science Advances · doi:10.1126/sciadv.abb1421 · Cited by 96
Idris, M. O., Yekeen, A. A., Alakanse, O. S., & Durojaye, O. A. (2020) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2020.1792346 · Cited by 97
Sehailia, M., & Chemat, S. (2020) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2020.1796809 · Cited by 99
Asymmetric photoenzymatic incorporation of fluorinated motifs into olefins
Li, M., Yuan, Y., Harrison, W., Zhang, Z., & Zhao, H. (2024) · Science · doi:10.1126/science.adk8464 · Cited by 96
Chen, C., Bai, L., Cao, F., Wang, S., He, H., Song, M., Chen, H., Liu, Y., Guo, J., Si, Q., et al. (2019) · Oncogene · doi:10.1038/s41388-019-0735-4 · Cited by 97
Ropp, P. J., Spiegel, J. O., Walker, J. L., Green, H., Morales, G. A., Milliken, K. A., Ringe, J. J., & Durrant, J. D. (2019) · Journal of Cheminformatics · doi:10.1186/s13321-019-0358-3 · Cited by 100
Gupta, P., Mohammad, T., Κhan, P., Alajmi, M. F., Hussain, A., Rehman, M. T., & Hassan, M. I. (2019) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2019.109245 · Cited by 94
Wang, G., Liu, W., Gong, Z., Huang, Y., Li, Y., & Peng, Z. (2019) · Journal of Enzyme Inhibition and Medicinal Chemistry · doi:10.1080/14756366.2019.1690479 · Cited by 95
Suppressing STAT5 signaling affects osteosarcoma growth and stemness
Subramaniam, D., Angulo, P., Ponnurangam, S., Dandawate, P. R., Ramamoorthy, P., Pugazhendhi, S., Iwakuma, T., Weir, S. J., Chastain, K. M., & Anant, S. (2020) · Cell Death and Disease · doi:10.1038/s41419-020-2335-1 · Cited by 95
Elmezayen, A. D., & Yelekçi, K. (2020) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2020.1798812 · Cited by 95
Hossain, M. S., Roy, A. S., & Islam, M. S. (2020) · Scientific Reports · doi:10.1038/s41598-020-71457-1 · Cited by 96
Elangovan, N., Thomas, R., & Sowrirajan, S. (2021) · Journal of Molecular Structure · doi:10.1016/j.molstruc.2021.131762 · Cited by 96
Naturally-Occurring Tyrosinase Inhibitors Classified by Enzyme Kinetics and Copper Chelation
Kim, H.-D., Choi, H., Abekura, F., Park, J., Yang, W., Yang, S., & Kim, C. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24098226 · Cited by 95
Singh, N., Pydi, S. P., Upadhyaya, J. D., & Chelikani, P. (2011) · Journal of Biological Chemistry · doi:10.1074/jbc.m111.246983 · Cited by 94
Chang, Y., Tung, Y., Lee, K.-H., Chen, T.-F., Hsiao, Y., Chang, H.-C., Hsieh, T.-T., Su, C.-H., Wang, S.-S., Yu, J.-Y., et al. (2020) · Preprints.org · doi:10.20944/preprints202002.0242.v2 · Cited by 95
Anjomshoa, M., Hadadzadeh, H., Torkzadeh‐Mahani, M., Fatemi, S. J., Adeli‐Sardou, M., Rudbari, H. A., & Nardo, V. M. (2015) · European Journal of Medicinal Chemistry · doi:10.1016/j.ejmech.2015.04.020 · Cited by 94
NRGsuite: a PyMOL plugin to perform docking simulations in real time using FlexAID
Gaudreault, F., Morency, L.-P., & Najmanovich, R. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv458 · Cited by 94
TSPOmutations in rats and a human polymorphism impair the rate of steroid synthesis
Owen, D. R., Fan, J., Campioli, E., Venugopal, S., Midzak, A. S., Daly, E., Harlay, A., Issop, L., Libri, V., Kalogiannopoulou, D., et al. (2017) · Biochemical Journal · doi:10.1042/bcj20170648 · Cited by 103
Yan, H., Casalini, T., Hulsart‐Billström, G., Wang, S., Oommen, O. P., Salvalaglio, M., Larsson, S., Hilborn, J. G., & Varghese, O. P. (2018) · Biomaterials · doi:10.1016/j.biomaterials.2018.01.041 · Cited by 94
Francoz, E., Ranocha, P., Ru, A. L., Martinez, Y., Fourquaux, I., Jauneau, A., Dunand, C., & Burlat, V. (2018) · Developmental Cell · doi:10.1016/j.devcel.2018.11.016 · Cited by 94
Li, Q., Shi, C., Wang, M., Zhou, M., Liang, M., Zhang, T., Yuan, E., Wang, Z., Yao, M., & Ren, J. (2019) · Journal of Functional Foods · doi:10.1016/j.jff.2018.11.024 · Cited by 95
Li, H., Peng, J., Sidorov, P., Leung, Y., Leung, K., Wong, M., Lü, G., & Ballester, P. J. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz183 · Cited by 96
Liu, H., Da, L., & Liu, Y. (2019) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2019.05.066 · Cited by 94
Zhang, B., Huang, J., Liu, K., Zhou, Z., Jiang, L., Shen, Y., & Zhao, D. (2019) · Industrial & Engineering Chemistry Research · doi:10.1021/acs.iecr.9b04214 · Cited by 94
Hayashi, T., Ligibel, M., Sager, E., Voß, M., Hunziker, J., Schroer, K., Šnajdrová, R., & Buller, R. (2019) · Angewandte Chemie International Edition · doi:10.1002/anie.201907245 · Cited by 94
Protein engineering design from directed evolution to de novo synthesis
Xiong, W., Liu, B., Shen, Y., Jing, K., & Savage, T. (2021) · Biochemical Engineering Journal · doi:10.1016/j.bej.2021.108096 · Cited by 94
Rolta, R., Salaria, D., Sharma, P., Sharma, B., Kumar, V., Rathi, B., Verma, M., Sourirajan, A., Baumler, D. J., & Dev, K. (2021) · Current Pharmacology Reports · doi:10.1007/s40495-021-00259-4 · Cited by 96
Seo, S., Choi, J., Park, S., & Ahn, J. (2021) · BMC Bioinformatics · doi:10.1186/s12859-021-04466-0 · Cited by 101
Yang, C., Wang, T., Zhao, Y., Meng, X., Ding, W., Wang, Q., Liu, C., & Deng, H. (2022) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2022.06.010 · Cited by 94
Large-scale chemoproteomics expedites ligand discovery and predicts ligand behavior in cells
Offensperger, F., Tin, G., Duran‐Frigola, M., Hahn, E., Dobner, S., Ende, C. W. A., Strohbach, J. W., Rukavina, A., Brennsteiner, V., Ogilvie, K., et al. (2024) · Science · doi:10.1126/science.adk5864 · Cited by 102
Graph Neural Networks in Modern AI-Aided Drug Discovery
Zhang, O., Lin, H., Zhang, X., Wang, X., Wu, Z., Ye, Q., Zhao, W., Wang, J., Ying, K., Kang, Y., et al. (2025) · Chemical Reviews · doi:10.1021/acs.chemrev.5c00461 · Cited by 110
Capsaicin Interaction with TRPV1 Channels in a Lipid Bilayer: Molecular Dynamics Simulation
Hanson, S. M., Newstead, S. L., Swartz, K. J., & Sansom, M. S. P. (2015) · Biophysical Journal · doi:10.1016/j.bpj.2015.02.013 · Cited by 92
Cougnoux, A., Delmas, J., Gibold, L., Faïs, T., Romagnoli, C., Robin, F., Ramos, G. C., Oswald, É., Darfeuille–Michaud, A., Prati, F., et al. (2015) · Gut · doi:10.1136/gutjnl-2014-307241 · Cited by 105
Desideri, N., Bolasco, A., Fioravanti, R., Monaco, L. P., Orallo, F., Yáñez, M., Ortuso, F., & Alcaro, S. (2011) · Journal of Medicinal Chemistry · doi:10.1021/jm1013709 · Cited by 93
Evolutionary mix-and-match with MFS transporters
Madej, M. G., Dang, S., Yan, N., & Kaback, H. R. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1303538110 · Cited by 93
Impens, F., Rolhion, N., Radoshevich, L., Bécavin, C., Duval, M., Mellin, J. R., del Portillo, F. G., Pucciarelli, M. G., Williams, A. H., & Cossart, P. (2017) · Nature Microbiology · doi:10.1038/nmicrobiol.2017.5 · Cited by 98
AlloFinder: a strategy for allosteric modulator discovery and allosterome analyses
Huang, M., Song, K., Liu, X., Lu, S., Shen, Q., Wang, R., Gao, J., Hong, Y., Li, Q., Ni, D., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky374 · Cited by 92
Bitencourt‐Ferreira, G., & de Azevedo, W. F. (2018) · Biophysical Chemistry · doi:10.1016/j.bpc.2018.05.010 · Cited by 93
He, P., Chen, G., Li, S., Wang, J., Ma, Y., Pan, Y., & He, M. (2018) · Pest Management Science · doi:10.1002/ps.5277 · Cited by 93
Negatu, D. A., Yamada, Y., Xi, Y., Go, M., Zimmerman, M. D., Ganapathy, U. S., Dartois, V. A., Gengenbacher, M., & Dick, T. (2019) · mBio · doi:10.1128/mbio.02781-18 · Cited by 97
Rhein sensitizes human pancreatic cancer cells to EGFR inhibitors by inhibiting STAT3 pathway
Yang, L., Lin, S., Kang, Y., Xiang, Y., Xu, L., Li, J., Dai, X., Liang, G., Huang, X., & Zhao, C. (2019) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-018-1015-9 · Cited by 96
The application of the MM/GBSA method in the binding pose prediction of FGFR inhibitors
Chen, Y., Zheng, Y., Fong, P., Mao, S., & Wang, Q. (2020) · Physical Chemistry Chemical Physics · doi:10.1039/d0cp00831a · Cited by 94
Roth‐Walter, F., Afify, S. M., Pacios, L. F., Blokhuis, B. R. J., Redegeld, F. A., Regner, A., Petje, L., Fiocchi, A. G., Untersmayr, E., Dvořák, Z., et al. (2020) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2020.05.023 · Cited by 96
Sharma, P., Joshi, T., Joshi, T., Chandra, S., & Tamta, S. (2020) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2020.1801507 · Cited by 93
A multi-pronged approach targeting SARS-CoV-2 proteins using ultra-large virtual screening
Gorgulla, C., Das, K. M., Leigh, K. E., Cespugli, M., Fischer, P. D., Wang, Z., Tesseyre, G., Pandita, S., Shnapir, A., Calderaio, A., et al. (2021) · iScience · doi:10.1016/j.isci.2020.102021 · Cited by 96
Pratiwi, R., Nantasenamat, C., Ruankham, W., Suwanjang, W., Prachayasittikul, V., Prachayasittikul, S., & Phopin, K. (2021) · Frontiers in Nutrition · doi:10.3389/fnut.2021.648995 · Cited by 96
A pharmacophore-guided deep learning approach for bioactive molecular generation
Zhu, H., Zhou, R., Cao, D., Tang, J. P., & Li, M. (2023) · Nature Communications · doi:10.1038/s41467-023-41454-9 · Cited by 105
RNA-Activatable Near-Infrared Photosensitizer for Cancer Therapy
Jiang, Y., Huang, S., Ma, H., Weng, J., Du, X., Lin, Z., Kim, J., You, W., Zhang, H., Wang, D., et al. (2024) · Journal of the American Chemical Society · doi:10.1021/jacs.4c09470 · Cited by 93
Chen, H., Yang, Z., Ding, C., Chu, L., Zhang, Y., Terry, K., Liu, H., Shen, Q., & Zhou, J. (2013) · European Journal of Medicinal Chemistry · doi:10.1016/j.ejmech.2013.01.023 · Cited by 94
Mishra, P., Kumar, A., Mamidi, P., Kumar, S., Basantray, I., Saswat, T., Das, I., Nayak, T. K., Chattopadhyay, S., Subudhi, B. B., et al. (2016) · Scientific Reports · doi:10.1038/srep20122 · Cited by 91
Synthesis, biological evaluation and DFT calculation of novel pyrazole and pyrimidine derivatives
Farag, A. M., & Fahim, A. M. (2018) · Journal of Molecular Structure · doi:10.1016/j.molstruc.2018.11.008 · Cited by 93
DeepCPI: A Deep Learning-Based Framework for Large-Scale in Silico Drug Screening
Wan, F., Zhu, Y., Hu, H., Dai, A., Cai, X., Chen, L., Gong, H., Xia, T., Yang, D., Wang, M.-W., et al. (2019) · Genomics, Proteomics & Bioinformatics · doi:10.1016/j.gpb.2019.04.003 · Cited by 92
He, S., Ni, D., Ma, B., Lee, J.-H., Zhang, T., Ghozalli, I., Pirooz, S. D., Zhao, Z., Bharatham, N., Li, B., et al. (2013) · Nature Cell Biology · doi:10.1038/ncb2848 · Cited by 95
Crystal Structure of the 2-Oxoglutarate- and Fe(II)-Dependent Lysyl Hydroxylase JMJD6
Mantri, M., Krojer, T. J., Bagg, E. A. L., Webby, C. J., Butler, D. S., Kochan, G. T., Kavanagh, K. L., Oppermann, U. C. T., McDonough, M. A., & Schofield, C. J. (2010) · Journal of Molecular Biology · doi:10.1016/j.jmb.2010.05.054 · Cited by 94
Zheng, J., Son, D. J., Gu, S. M., Woo, J. R., Ham, Y. W., Lee, H. P., Kim, W., Jung, J., & Hong, J. T. (2016) · Scientific Reports · doi:10.1038/srep26357 · Cited by 94
RetractedOpen source molecular modeling
Pirhadi, S., Sunseri, J., & Koes, D. R. (2016) · Journal of Molecular Graphics and Modelling · doi:10.1016/j.jmgm.2016.07.008 · Cited by 95
Yadav, S., Pandey, S. K., Singh, V. K., Goel, Y., Kumar, A., & Singh, S. M. (2017) · PLoS ONE · doi:10.1371/journal.pone.0176403 · Cited by 92
Structure and application of antifreeze proteins from Antarctic bacteria
Muñoz-Torres, P., Márquez, S. L., González-Nilo, F. D., Márquez‐Miranda, V., & Blamey, J. M. (2017) · Microbial Cell Factories · doi:10.1186/s12934-017-0737-2 · Cited by 92
Ahmed, A., Shamsi, A., Khan, M. S., Husain, F. M., & Bano, B. (2018) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2018.02.137 · Cited by 92
Li, B., Rui, J., Ding, X., & Yang, X. (2018) · Journal of Ethnopharmacology · doi:10.1016/j.jep.2018.12.033 · Cited by 92
New insights into GluT1 mechanics during glucose transfer
Galochkina, T. V., Chong, M. N. F., Challali, L., Abbar, S., & Etchebest, C. (2019) · Scientific Reports · doi:10.1038/s41598-018-37367-z · Cited by 102
Dexlin, X. D. D., Tarika, J. D. D., Kumar, S. M., Mariappan, A., & Beaula, T. J. (2021) · Journal of Molecular Structure · doi:10.1016/j.molstruc.2021.131165 · Cited by 95
G4LDB 2.2: a database for discovering and studying G-quadruplex and i-Motif ligands
Wang, Y., Yang, Q., Lin, X., Chen, D., Wang, Z., Chen, B., Han, H., Chen, H.-D., Cai, K., Li, Q., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab952 · Cited by 93
POLθ processes ssDNA gaps and promotes replication fork progression in BRCA1-deficient cells
Schrempf, A., Bernardo, S., Arasa-Verge, E. A., Ramírez-Otero, M. A., Wilson, J., Kirchhofer, D., Timelthaler, G., Ambros, A. M., Kaya, A., Wieder, M., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111716 · Cited by 92
GraphscoreDTA: optimized graph neural network for protein–ligand binding affinity prediction
Wang, K., Zhou, R., Tang, J. P., & Li, M. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad340 · Cited by 94
Metadata
- Authors
- Trott, O., & Olson, A. J.
- Affiliations
- Scripps Research Institute (US)
- Corresponding author
- Olson, Arthur J.
- ORCID
- Olson, Arthur J.
- Venue
- Journal of Computational Chemistry
- Publisher
- Wiley
- Published
- 2009-06-04
- Volume
- 31
- Issue
- 2
- Pages
- 455-461
- ISSN
- 0192-8651 (ISSN-L)
- 1096-987X
- PMC
- PMC3041641
- OpenAlex
- W2134967712
- Cited by
- 38,412
- References
- 24
- Citations by year
- 2026: 4951 · 2025: 5289 · 2024: 4793 · 2023: 4241 · 2022: 4250 · 2021: 3687 · 2020: 2903 · 2019: 1858 · 2018: 1560 · 2017: 1225 · 2016: 1035 · 2015: 832 · 2014: 613 · 2013: 508 · 2012: 346
- FWCI
- 212.46
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Computational Chemistry (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Institute of General Medical Sciences (R01GM069832)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Advanced Chemical Physics Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Keywords
- AutoDock Vina, molecular docking, virtual screening, scoring functions, binding mode prediction, multithreading, multi-core parallelization, grid map
- MeSH terms
- Algorithms, Automation, Binding Sites, Hydrogen Bonding, Ligands, Sensitivity and Specificity, Software, Solvents, Thermodynamics, Time Factors, Computational Biology, Molecular Dynamics Simulation, Hydrophobic and Hydrophilic Interactions
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 ›
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