TY - JOUR AU - Savjani, K. T. AU - Gajjar, A. K. AU - Savjani, J. K. PY - 2012 DA - 2012// TI - Drug solubility: importance and enhancement techniques JO - ISRN Pharm VL - 2012 ID - Savjani2012 ER - TY - JOUR AU - Lipinski, C. A. AU - Lombardo, F. AU - Dominy, B. W. AU - Feeney, P. J. PY - 2001 DA - 2001// TI - Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings JO - Adv Drug Deliv Rev VL - 46 UR - https://doi.org/10.1016/S0169-409X(00)00129-0 DO - 10.1016/S0169-409X(00)00129-0 ID - Lipinski2001 ER - TY - JOUR AU - Simon, D. I. AU - Brosius, F. C. AU - Rothstein, D. M. PY - 1990 DA - 1990// TI - Sulfadiazine crystalluria revisited: the treatment of Toxoplasma encephalitis in patients with acquired immunodeficiency syndrome JO - Arch Intern Med VL - 150 UR - https://doi.org/10.1001/archinte.1990.00390220113023 DO - 10.1001/archinte.1990.00390220113023 ID - Simon1990 ER - TY - JOUR AU - Kennedy, T. PY - 1997 DA - 1997// TI - Managing the drug discovery/development interface JO - Drug Discov Today VL - 2 UR - https://doi.org/10.1016/S1359-6446(97)01099-4 DO - 10.1016/S1359-6446(97)01099-4 ID - Kennedy1997 ER - TY - JOUR AU - Lipinski, C. PY - 2002 DA - 2002// TI - Poor aqueous solubility—an industry wide problem in drug discovery JO - Am Pharm Rev VL - 5 ID - Lipinski2002 ER - TY - JOUR AU - Box, K. AU - Comer, J. E. AU - Gravestock, T. AU - Stuart, M. PY - 2009 DA - 2009// TI - New ideas about the solubility of drugs JO - Chem Biodivers VL - 6 UR - https://doi.org/10.1002/cbdv.200900164 DO - 10.1002/cbdv.200900164 ID - Box2009 ER - TY - JOUR AU - Llinas, A. AU - Glen, R. C. AU - Goodman, J. M. PY - 2008 DA - 2008// TI - Solubility challenge: can you predict solubilities of 32 molecules using a database of 100 reliable measurements? JO - J Chem Inf Model VL - 48 UR - https://doi.org/10.1021/ci800058v DO - 10.1021/ci800058v ID - Llinas2008 ER - TY - JOUR AU - Hopfinger, A. J. AU - Esposito, E. X. AU - Llinas, A. AU - Glen, R. C. AU - Goodman, J. M. PY - 2008 DA - 2008// TI - Findings of the challenge to predict aqueous solubility JO - J Chem Inf Model VL - 49 UR - https://doi.org/10.1021/ci800436c DO - 10.1021/ci800436c ID - Hopfinger2008 ER - TY - JOUR AU - Palmer, D. S. AU - Mitchell, J. B. O. PY - 2014 DA - 2014// TI - Is experimental data quality the limiting factor in predicting the aqueous solubility of druglike molecules? JO - Mol Pharm VL - 11 UR - https://doi.org/10.1021/mp500103r DO - 10.1021/mp500103r ID - Palmer2014 ER - TY - JOUR AU - Jorgensen, W. L. AU - Duffy, E. M. PY - 2002 DA - 2002// TI - Prediction of drug solubility from structure JO - Adv Drug Deliv Rev VL - 54 UR - https://doi.org/10.1016/S0169-409X(02)00008-X DO - 10.1016/S0169-409X(02)00008-X ID - Jorgensen2002 ER - TY - JOUR AU - Palmer, D. S. AU - O’Boyle, N. M. AU - Glen, R. C. AU - Mitchell, J. B. O. PY - 2007 DA - 2007// TI - Random forest models to predict aqueous solubility JO - J Chem Inf Model VL - 47 UR - https://doi.org/10.1021/ci060164k DO - 10.1021/ci060164k ID - Palmer2007 ER - TY - JOUR AU - Hughes, L. D. AU - Palmer, D. S. AU - Nigsch, F. AU - Mitchell, J. B. O. PY - 2008 DA - 2008// TI - Why are some properties more difficult to predict than others? A study of QSPR models of solubility, melting point, and log P JO - J Chem Inf Model VL - 48 UR - https://doi.org/10.1021/ci700307p DO - 10.1021/ci700307p ID - Hughes2008 ER - TY - JOUR AU - McDonagh, J. L. AU - Nath, N. AU - Ferrari, L. AU - Mourik, T. AU - Mitchell, J. B. O. PY - 2014 DA - 2014// TI - Uniting cheminformatics and chemical theory to predict the intrinsic aqueous solubility of crystalline druglike molecules JO - J Chem Inf Model VL - 54 UR - https://doi.org/10.1021/ci4005805 DO - 10.1021/ci4005805 ID - McDonagh2014 ER - TY - STD TI - Mitchell JBO, McDonagh JL, Boobier S. DLS-100 solubility dataset. University of St Andrews Research Portal. https://doi.org/10.17630/3a3a5abc-8458-4924-8e6c-b804347605e8 ID - ref14 ER - TY - STD TI - Mitchell JBO, McDonagh JL, Boobier S. DLS-100 solubility dataset, Figshare. https://doi.org/10.6084/m9.figshare.5545639 ID - ref15 ER - TY - JOUR AU - Gattuso, J. -. P. AU - Mach, K. J. AU - Morgan, G. PY - 2013 DA - 2013// TI - Ocean acidification and its impacts: an expert survey JO - Clim Change VL - 117 UR - https://doi.org/10.1007/s10584-012-0591-5 DO - 10.1007/s10584-012-0591-5 ID - Gattuso2013 ER - TY - BOOK AU - Müller, V. C. AU - Bostrom, N. PY - 2016 DA - 2016// TI - Fundamental issues of artificial intelligence PB - Springer CY - Berlin ID - Müller2016 ER - TY - BOOK AU - Surowiecki, J. PY - 2004 DA - 2004// TI - The wisdom of crowds: why the many are smarter than the few and how collective wisdom shapes business, economies, societies, and nations PB - Doubleday CY - New York ID - Surowiecki2004 ER - TY - JOUR AU - Iyer, R. AU - Graham, J. PY - 2012 DA - 2012// TI - Leveraging the wisdom of crowds in a data-rich utopia JO - Psychol Inq VL - 23 UR - https://doi.org/10.1080/1047840X.2012.705244 DO - 10.1080/1047840X.2012.705244 ID - Iyer2012 ER - TY - JOUR AU - Galton, F. PY - 1907 DA - 1907// TI - Vox populi JO - Nature VL - 75 UR - https://doi.org/10.1038/075450a0 DO - 10.1038/075450a0 ID - Galton1907 ER - TY - JOUR AU - Mitchell, J. B. O. PY - 2014 DA - 2014// TI - Machine learning methods in chemoinformatics JO - WIREs Comput Mol Sci VL - 4 UR - https://doi.org/10.1002/wcms.1183 DO - 10.1002/wcms.1183 ID - Mitchell2014 ER - TY - JOUR AU - Bhat, A. U. AU - Merchant, S. S. AU - Bhagwat, S. S. PY - 2008 DA - 2008// TI - Prediction of melting points of organic compounds using extreme learning machines JO - Ind Eng Chem Res VL - 47 UR - https://doi.org/10.1021/ie0704647 DO - 10.1021/ie0704647 ID - Bhat2008 ER - TY - JOUR AU - Charifson, P. S. AU - Corkery, J. J. AU - Murcko, M. A. AU - Walters, W. P. PY - 1999 DA - 1999// TI - Consensus scoring: a method for obtaining improved hit rates from docking databases of three-dimensional structures into proteins JO - J Med Chem VL - 42 UR - https://doi.org/10.1021/jm990352k DO - 10.1021/jm990352k ID - Charifson1999 ER - TY - JOUR AU - Franco, P. AU - Porta, N. AU - Holliday, J. D. AU - Willett, P. PY - 2014 DA - 2014// TI - The use of 2D fingerprint methods to support the assessment of structural similarity in orphan drug legislation JO - J Cheminform VL - 6 UR - https://doi.org/10.1186/1758-2946-6-5 DO - 10.1186/1758-2946-6-5 ID - Franco2014 ER - TY - BOOK AU - Michalski, R. S. AU - Carbonell, J. G. AU - Mitchell, T. M. PY - 2013 DA - 2013// TI - Machine learning: an artificial intelligence approach PB - Springer CY - Berlin ID - Michalski2013 ER - TY - STD TI - Bishop CM (2006) Pattern recognition and machine learning. Springer, New York ID - ref26 ER - TY - JOUR AU - Tsai, C. -. F. AU - Hsu, Y. -. F. AU - Lin, C. -. Y. AU - Lin, W. -. Y. PY - 2009 DA - 2009// TI - Intrusion detection by machine learning: a review JO - Expert Syst Appl VL - 36 UR - https://doi.org/10.1016/j.eswa.2009.05.029 DO - 10.1016/j.eswa.2009.05.029 ID - Tsai2009 ER - TY - JOUR AU - Bose, I. AU - Mahapatra, R. K. PY - 2001 DA - 2001// TI - Business data mining—a machine learning perspective JO - Inf Manag VL - 39 UR - https://doi.org/10.1016/S0378-7206(01)00091-X DO - 10.1016/S0378-7206(01)00091-X ID - Bose2001 ER - TY - JOUR AU - Burbidge, R. AU - Trotter, M. AU - Buxton, B. AU - Holden, S. PY - 2001 DA - 2001// TI - Drug design by machine learning: support vector machines for pharmaceutical data analysis JO - Comput Chem VL - 26 UR - https://doi.org/10.1016/S0097-8485(01)00094-8 DO - 10.1016/S0097-8485(01)00094-8 ID - Burbidge2001 ER - TY - JOUR AU - Lavecchia, A. PY - 2015 DA - 2015// TI - Machine-learning approaches in drug discovery: methods and applications JO - Drug Discov Today VL - 20 UR - https://doi.org/10.1016/j.drudis.2014.10.012 DO - 10.1016/j.drudis.2014.10.012 ID - Lavecchia2015 ER - TY - JOUR AU - Judson, R. AU - Elloumi, F. AU - Setzer, R. W. AU - Li, Z. AU - Shah, I. PY - 2008 DA - 2008// TI - A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model JO - BMC Bioinform VL - 9 UR - https://doi.org/10.1186/1471-2105-9-241 DO - 10.1186/1471-2105-9-241 ID - Judson2008 ER - TY - JOUR AU - Cheng, F. AU - Li, W. AU - Zhou, Y. AU - Shen, J. AU - Wu, Z. AU - Liu, G. AU - Lee, P. W. AU - Tang, Y. PY - 2012 DA - 2012// TI - admetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties JO - J Chem Inf Model VL - 52 UR - https://doi.org/10.1021/ci300367a DO - 10.1021/ci300367a ID - Cheng2012 ER - TY - JOUR AU - King, R. D. AU - Muggleton, S. H. AU - Srinivasan, A. AU - Sternberg, M. PY - 1996 DA - 1996// TI - Structure-activity relationships derived by machine learning: the use of atoms and their bond connectivities to predict mutagenicity by inductive logic programming JO - Proc Natl Acad Sci VL - 93 UR - https://doi.org/10.1073/pnas.93.1.438 DO - 10.1073/pnas.93.1.438 ID - King1996 ER - TY - JOUR AU - Reker, D. AU - Schneider, P. AU - Schneider, G. PY - 2016 DA - 2016// TI - Multi-objective active machine learning rapidly improves structure–activity models and reveals new protein–protein interaction inhibitors JO - Chem Sci VL - 7 UR - https://doi.org/10.1039/C5SC04272K DO - 10.1039/C5SC04272K ID - Reker2016 ER - TY - JOUR AU - Lusci, A. AU - Pollastri, G. AU - Baldi, P. PY - 2013 DA - 2013// TI - Deep architectures and deep learning in chemoinformatics: the prediction of aqueous solubility for drug-like molecules JO - J Chem Inf Model VL - 53 UR - https://doi.org/10.1021/ci400187y DO - 10.1021/ci400187y ID - Lusci2013 ER - TY - BOOK AU - Todeschini, R. AU - Consonni, V. PY - 2008 DA - 2008// TI - Handbook of molecular descriptors PB - Wiley CY - London ID - Todeschini2008 ER - TY - JOUR AU - Palmer, D. S. AU - Llinas, A. AU - Morao, I. AU - Day, G. M. AU - Goodman, J. M. AU - Glen, R. C. PY - 2008 DA - 2008// TI - Predicting intrinsic aqueous solubility by a thermodynamic cycle JO - Mol Pharm VL - 5 UR - https://doi.org/10.1021/mp7000878 DO - 10.1021/mp7000878 ID - Palmer2008 ER - TY - JOUR AU - Narasimham, L. Y. S. AU - Barhate, V. D. PY - 2011 DA - 2011// TI - Kinetic and intrinsic solubility determination of some beta-blockers and antidiabetics by potentiometry JO - J Pharm Res VL - 4 ID - Narasimham2011 ER - TY - JOUR AU - Rytting, E. AU - Lentz, K. A. AU - Chen, X. Q. Q. AU - Qian, F. AU - Vakatesh, S. PY - 2005 DA - 2005// TI - Aqueous and cosolvent solubility data for drug-like organic compounds JO - AAPS J VL - 7 UR - https://doi.org/10.1208/aapsj070110 DO - 10.1208/aapsj070110 ID - Rytting2005 ER - TY - JOUR AU - Shareef, A. AU - Angove, M. J. AU - Wells, J. D. AU - Johnson, B. B. PY - 2006 DA - 2006// TI - Aqueous solubilities of estrone, 17β-estradiol, 17α-ethynylestradiol, and bisphenol A JO - J Chem Eng Data VL - 51 UR - https://doi.org/10.1021/je050318c DO - 10.1021/je050318c ID - Shareef2006 ER - TY - JOUR AU - Ran, Y. AU - Yalkowsky, S. H. PY - 2001 DA - 2001// TI - Prediction of drug solubility by the general solubility equation (GSE) JO - J Chem Inf Comput Sci VL - 41 UR - https://doi.org/10.1021/ci000338c DO - 10.1021/ci000338c ID - Ran2001 ER - TY - JOUR AU - Bergstrom, C. A. S. AU - Luthman, K. AU - Artursson, P. PY - 2004 DA - 2004// TI - Accuracy of calculated pH-dependent aqueous drug solubility JO - Eur J Pharm Sci VL - 22 UR - https://doi.org/10.1016/j.ejps.2004.04.006 DO - 10.1016/j.ejps.2004.04.006 ID - Bergstrom2004 ER - TY - JOUR AU - Bergstrom, C. A. S. AU - Wassvik, C. M. AU - Norinder, U. AU - Luthman, K. AU - Artursson, P. PY - 2004 DA - 2004// TI - Global and local computational models for aqueous solubility prediction of drug-like molecules JO - J Chem Inf Comput Sci VL - 44 UR - https://doi.org/10.1021/ci049909h DO - 10.1021/ci049909h ID - Bergstrom2004 ER - TY - JOUR AU - Palmer, D. S. AU - McDonagh, J. L. AU - Mitchell, J. B. O. AU - Mourik, T. AU - Fedorov, M. V. PY - 2012 DA - 2012// TI - First-principles calculation of the intrinsic aqueous solubility of crystalline druglike molecules JO - J Chem Theory Comput VL - 8 UR - https://doi.org/10.1021/ct300345m DO - 10.1021/ct300345m ID - Palmer2012 ER - TY - JOUR AU - McDonagh, J. L. AU - Mourik, T. AU - Mitchell, J. B. O. PY - 2015 DA - 2015// TI - Predicting melting points of organic molecules: applications to aqueous solubility prediction using the general solubility equation JO - Mol Inf VL - 34 UR - https://doi.org/10.1002/minf.201500052 DO - 10.1002/minf.201500052 ID - McDonagh2015 ER - TY - JOUR AU - Weininger, D. PY - 1988 DA - 1988// TI - SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules JO - J Chem Inf Comput Sci VL - 28 UR - https://doi.org/10.1021/ci00057a005 DO - 10.1021/ci00057a005 ID - Weininger1988 ER - TY - JOUR AU - O’Boyle, N. M. PY - 2012 DA - 2012// TI - Towards a universal SMILES representation—a standard method to generate canonical SMILES based on the InChI JO - J Cheminform VL - 4 UR - https://doi.org/10.1186/1758-2946-4-22 DO - 10.1186/1758-2946-4-22 ID - O’Boyle2012 ER - TY - JOUR AU - Steinbeck, C. AU - Han, Y. AU - Kuhn, S. AU - Horlacher, O. AU - Luttmann, E. AU - Willighagen, E. PY - 2003 DA - 2003// TI - The chemistry development kit (CDK): an open-source java library for chemo- and bioinformatics JO - J Chem Inf Comput Sci VL - 43 UR - https://doi.org/10.1021/ci025584y DO - 10.1021/ci025584y ID - Steinbeck2003 ER - TY - JOUR AU - Quinlan, J. R. PY - 1986 DA - 1986// TI - Induction of decision trees JO - Mach Learn VL - 1 ID - Quinlan1986 ER - TY - JOUR AU - Raileanu, L. E. AU - Stoffel, K. PY - 2004 DA - 2004// TI - Theoretical comparison between the Gini index and information gain criteria JO - Ann Math Artif Intell VL - 41 UR - https://doi.org/10.1023/B:AMAI.0000018580.96245.c6 DO - 10.1023/B:AMAI.0000018580.96245.c6 ID - Raileanu2004 ER - TY - JOUR AU - Breiman, L. PY - 2001 DA - 2001// TI - Random forests JO - Mach Learn VL - 45 UR - https://doi.org/10.1023/A:1010933404324 DO - 10.1023/A:1010933404324 ID - Breiman2001 ER - TY - JOUR AU - Svetnik, V. AU - Liaw, A. AU - Tong, C. AU - Culberson, J. C. AU - Sheridan, R. P. AU - Feuston, B. P. PY - 2003 DA - 2003// TI - Random forest: a classification and regression tool for compound classification and QSAR modeling JO - J Chem Inf Comput Sci VL - 43 UR - https://doi.org/10.1021/ci034160g DO - 10.1021/ci034160g ID - Svetnik2003 ER - TY - JOUR AU - Breiman, L. PY - 1996 DA - 1996// TI - Bagging predictors JO - Mach Learn VL - 24 ID - Breiman1996 ER - TY - JOUR AU - Geurts, P. AU - Ernst, D. AU - Wehenkel, L. PY - 2006 DA - 2006// TI - Extremely randomized trees JO - Mach Learn VL - 63 UR - https://doi.org/10.1007/s10994-006-6226-1 DO - 10.1007/s10994-006-6226-1 ID - Geurts2006 ER - TY - BOOK AU - Schapire, R. E. PY - 2003 DA - 2003// TI - Nonlinear estimation and classification PB - Springer CY - Berlin UR - https://doi.org/10.1007/978-0-387-21579-2_9 DO - 10.1007/978-0-387-21579-2_9 ID - Schapire2003 ER - TY - JOUR AU - Guenther, N. AU - Schonlau, M. PY - 2016 DA - 2016// TI - Support vector machines JO - Stata J VL - 16 ID - Guenther2016 ER - TY - STD TI - Schölkopf B, Smola A (2005) Support vector machines. In: Encyclopedia of biostatistics. Wiley. http://dx.doi.org/10.1002/0470011815.b2a14038 ID - ref57 ER - TY - BOOK AU - Garreta, R. AU - Moncecchi, G. PY - 2013 DA - 2013// TI - Learning scikit-learn: machine learning in python PB - Packt Publishing Ltd CY - Birmingham ID - Garreta2013 ER - TY - JOUR AU - Denoeux, T. PY - 1995 DA - 1995// TI - A k-nearest neighbor classification rule based on Dempster–Shafer theory JO - IEEE Trans Syst Man Cybern VL - 25 UR - https://doi.org/10.1109/21.376493 DO - 10.1109/21.376493 ID - Denoeux1995 ER - TY - JOUR AU - Hopfield, J. J. PY - 1988 DA - 1988// TI - Artificial neural networks JO - IEEE Circuits Devices Mag VL - 4 UR - https://doi.org/10.1109/101.8118 DO - 10.1109/101.8118 ID - Hopfield1988 ER - TY - BOOK AU - Pham, D. T. AU - Packianather, M. AU - Afify, A. PY - 2007 DA - 2007// TI - Computational intelligence PB - Springer CY - Berlin UR - https://doi.org/10.1007/0-387-37452-3_3 DO - 10.1007/0-387-37452-3_3 ID - Pham2007 ER - TY - JOUR AU - Connors, B. W. AU - Long, M. A. PY - 2004 DA - 2004// TI - Electrical synapses in the mammalian brain JO - Annu Rev Neurosci VL - 27 UR - https://doi.org/10.1146/annurev.neuro.26.041002.131128 DO - 10.1146/annurev.neuro.26.041002.131128 ID - Connors2004 ER - TY - STD TI - Hinton GE, Srivastava N, Krizhevsky A, Sutskever I, Salakhutdinov RR (2012) ArXiv Preprint http://arxiv.org/abs/1207.0580, pp 1–18 UR - http://arxiv.org/abs/1207.0580 ID - ref63 ER - TY - STD TI - Collobert R, Bengio S (2004) Links between perceptrons, MLPs and SVMs. In: Proceedings of the twenty-first international conference on machine learning. ICML ‘04. New York, NY, USA. ACM. https://doi.org/10.1145/1015330.1015415 ID - ref64 ER - TY - JOUR AU - Wold, S. AU - Sjostrom, M. AU - Eriksson, L. PY - 2001 DA - 2001// TI - PLS-regression: a basic tool of chemometrics JO - Chemom Intell Lab Syst VL - 58 UR - https://doi.org/10.1016/S0169-7439(01)00155-1 DO - 10.1016/S0169-7439(01)00155-1 ID - Wold2001 ER - TY - STD TI - Bottou L (2010) Proceedings of COMPSTAT’2010. Springer, Berlin, pp 177–186 ID - ref66 ER - TY - STD TI - Qualtrics (Version Feb 2017), Provo, Utah, USA, 2017. http://www.qualtrics.com UR - http://www.qualtrics.com ID - ref67 ER - TY - STD TI - ChemDoodle (Version 8.1.0), iChemLabs, 2017. https://www.chemdoodle.com UR - https://www.chemdoodle.com ID - ref68 ER - TY - STD TI - Menke J, Martinez TR (2004) Using permutations instead of student’s t distribution for p-values in paired-difference algorithm comparisons. In: 2004 IEEE international joint conference on neural networks (IEEE Cat. No. 04CH37541). IEEE, pp 1331–1335. https://doi.org/10.1109/ijcnn.2004.1380138 ID - ref69 ER - TY - JOUR AU - Comer, J. AU - Judge, S. AU - Matthews, D. AU - Towers, L. AU - Falcone, B. AU - Goodman, J. PY - 2014 DA - 2014// TI - The intrinsic aqueous solubility of indomethacin JO - ADMET DMPK ID - Comer2014 ER - TY - JOUR AU - Herman, R. A. AU - Veng-Pedersen, P. PY - 1994 DA - 1994// TI - Quantitative structure–pharmacokinetic relationships for systemic drug distribution kinetics not confined to a congeneric series JO - J Pharm Sci VL - 83 UR - https://doi.org/10.1002/jps.2600830332 DO - 10.1002/jps.2600830332 ID - Herman1994 ER - TY - BOOK AU - Yalkowsky, S. H. AU - Dannenfelser, R. M. PY - 1992 DA - 1992// TI - Aquasol database of aqueous solubility PB - College of Pharmacy, University of Arizona CY - Tucson ID - Yalkowsky1992 ER - TY - BOOK AU - Yalkowsky, S. H. AU - He, Y. AU - Jain, P. PY - 2010 DA - 2010// TI - Handbook of aqueous solubility data PB - CRC Press CY - Boca Raton UR - https://doi.org/10.1201/EBK1439802458 DO - 10.1201/EBK1439802458 ID - Yalkowsky2010 ER - TY - STD TI - Albert A, Brown DJ, Cheeseman G (1951) 103. Pteridine studies. Part I. Pteridine, and 2- and 4-amino- and 2- and 4-hydroxy-pteridines. J Chem Soc 474–485. http://doi.org/10.1039/JR9510000474 ID - ref74 ER - TY - STD TI - Albert A, Lister JH, Pedersen C (1956) 886. Pteridine studies. Part X. Pteridines with more than one hydroxy- or amino-group. J Chem Soc 4621–4628. http://doi.org/10.1039/JR9560004621 ID - ref75 ER - TY - JOUR AU - Khatib, F. AU - DiMaio, F. AU - Cooper, S. AU - Kazmierczyk, M. AU - Gilski, M. AU - Krzywda, S. PY - 2011 DA - 2011// TI - Crystal structure of a monomeric retroviral protease solved by protein folding game players JO - Nat Struct Mol Biol VL - 18 UR - https://doi.org/10.1038/nsmb.2119 DO - 10.1038/nsmb.2119 ID - Khatib2011 ER -