Year |
Citation |
Score |
2023 |
Masters MR, Mahmoud AH, Wei Y, Lill MA. Deep Learning Model for Efficient Protein-Ligand Docking with Implicit Side-Chain Flexibility. Journal of Chemical Information and Modeling. 63: 1695-1707. PMID 36916514 DOI: 10.1021/acs.jcim.2c01436 |
0.409 |
|
2020 |
Ghanbarpour A, Mahmoud AH, Lill MA. Instantaneous generation of protein hydration properties from static structures. Communications Chemistry. 3: 188. PMID 36703451 DOI: 10.1038/s42004-020-00435-5 |
0.369 |
|
2020 |
Mahmoud AH, Masters MR, Yang Y, Lill MA. Elucidating the multiple roles of hydration for accurate protein-ligand binding prediction via deep learning. Communications Chemistry. 3: 19. PMID 36703428 DOI: 10.1038/s42004-020-0261-x |
0.489 |
|
2020 |
Mahmoud AH, Masters MR, Yang Y, Lill MA. Elucidating the multiple roles of hydration for accurate protein-ligand binding prediction via deep learning Communications Chemistry. 3. DOI: 10.1038/s42004-020-0261-x |
0.33 |
|
2019 |
Bartolowits MD, Gast JM, Hasler AJ, Cirrincione AM, O'Connor RJ, Mahmoud AH, Lill MA, Davisson VJ. Discovery of Inhibitors for Proliferating Cell Nuclear Antigen Using a Computational-Based Linked-Multiple-Fragment Screen. Acs Omega. 4: 15181-15196. PMID 31552364 DOI: 10.1021/acsomega.9b02079 |
0.335 |
|
2019 |
Mahmoud AH, Yang Y, Lill MA. Improving atom type diversity and sampling in co-solvent simulations using λ-dynamics. Journal of Chemical Theory and Computation. PMID 30933496 DOI: 10.1021/Acs.Jctc.8B00940 |
0.388 |
|
2018 |
Yang Y, Mahmoud AH, Lill MA. Modeling of halogen-protein interactions in co-solvent molecular dynamics simulations. Journal of Chemical Information and Modeling. PMID 30525593 DOI: 10.1021/Acs.Jcim.8B00806 |
0.382 |
|
2018 |
Masters MR, Mahmoud AH, Yang Y, Lill MA. Efficient and Accurate Hydration Site Profiling for Enclosed Binding Sites. Journal of Chemical Information and Modeling. PMID 30289252 DOI: 10.1021/Acs.Jcim.8B00544 |
0.372 |
|
2018 |
Yang Y, Abdallah AHA, Lill MA. Calculation of Thermodynamic Properties of Bound Water Molecules. Methods in Molecular Biology (Clifton, N.J.). 1762: 389-402. PMID 29594782 DOI: 10.1007/978-1-4939-7756-7_19 |
0.442 |
|
2017 |
Yang Y, Hu B, Lill MA. WATsite2.0 with PyMOL Plugin: Hydration Site Prediction and Visualization. Methods in Molecular Biology (Clifton, N.J.). 1611: 123-134. PMID 28451976 DOI: 10.1007/978-1-4939-7015-5_10 |
0.441 |
|
2016 |
Yang Y, Lill MA. Dissecting the Influence of Protein Flexibility on the Location and Thermodynamic Profile of Explicit Water Molecules in Protein-Ligand Binding. Journal of Chemical Theory and Computation. PMID 27494046 DOI: 10.1021/Acs.Jctc.6B00411 |
0.446 |
|
2016 |
Kingsley LJ, Esquivel-Rodríguez J, Yang Y, Kihara D, Lill MA. Ranking protein-protein docking results using steered molecular dynamics and potential of mean force calculations. Journal of Computational Chemistry. PMID 27232548 DOI: 10.1002/Jcc.24412 |
0.433 |
|
2015 |
Kingsley LJ, Wilson GL, Essex ME, Lill MA. Combining structure- and ligand-based approaches to improve site of metabolism prediction in CYP2C9 substrates. Pharmaceutical Research. 32: 986-1001. PMID 25208877 DOI: 10.1007/s11095-014-1511-3 |
0.34 |
|
2015 |
Kingsley LJ, Wilson GL, Essex ME, Lill MA. Combining structure- and ligand-based approaches to improve site of metabolism prediction in CYP2C9 substrates Pharmaceutical Research. 32: 986-1001. DOI: 10.1007/s11095-014-1511-3 |
0.306 |
|
2014 |
Yang Y, Hu B, Lill MA. Analysis of factors influencing hydration site prediction based on molecular dynamics simulations. Journal of Chemical Information and Modeling. 54: 2987-95. PMID 25252619 DOI: 10.1021/Ci500426Q |
0.437 |
|
2014 |
Ghomi HT, Thompson JJ, Lill MA. Are distance-dependent statistical potentials considering three interacting bodies superior to two-body statistical potentials for protein structure prediction? Journal of Bioinformatics and Computational Biology. 12: 1450022. PMID 25212727 DOI: 10.1142/S021972001450022X |
0.304 |
|
2014 |
Kingsley LJ, Lill MA. Including ligand-induced protein flexibility into protein tunnel prediction. Journal of Computational Chemistry. 35: 1748-56. PMID 25043499 DOI: 10.1002/jcc.23680 |
0.375 |
|
2014 |
Pedley AM, Lill MA, Davisson VJ. Flexibility of PCNA-protein interface accommodates differential binding partners. Plos One. 9: e102481. PMID 25036435 DOI: 10.1371/Journal.Pone.0102481 |
0.322 |
|
2014 |
Kingsley LJ, Lill MA. Ensemble generation and the influence of protein flexibility on geometric tunnel prediction in cytochrome P450 enzymes. Plos One. 9: e99408. PMID 24956479 DOI: 10.1371/journal.pone.0099408 |
0.399 |
|
2014 |
Hu B, Lill MA. WATsite: hydration site prediction program with PyMOL interface. Journal of Computational Chemistry. 35: 1255-60. PMID 24752524 DOI: 10.1002/jcc.23616 |
0.329 |
|
2014 |
Hu B, Lill MA. PharmDock: a pharmacophore-based docking program. Journal of Cheminformatics. 6: 14. PMID 24739488 DOI: 10.1186/1758-2946-6-14 |
0.332 |
|
2014 |
Kingsley LJ, Lill MA. IterTunnel; a method for predicting and evaluating ligand EgressTunnels in proteins with buried active sites Journal of Cheminformatics. 6. DOI: 10.1186/1758-2946-6-S1-P62 |
0.342 |
|
2013 |
Xu M, Lill MA. Induced fit docking, and the use of QM/MM methods in docking. Drug Discovery Today. Technologies. 10: e411-8. PMID 24050138 DOI: 10.1016/J.Ddtec.2013.02.003 |
0.583 |
|
2013 |
Hu B, Lill MA. Exploring the potential of protein-based pharmacophore models in ligand pose prediction and ranking. Journal of Chemical Information and Modeling. 53: 1179-90. PMID 23621564 DOI: 10.1021/ci400143r |
0.372 |
|
2013 |
Lill M. Virtual screening in drug design. Methods in Molecular Biology (Clifton, N.J.). 993: 1-12. PMID 23568460 DOI: 10.1007/978-1-62703-342-8_1 |
0.341 |
|
2012 |
Kortagere S, Lill M, Kerrigan J. Role of computational methods in pharmaceutical sciences. Methods in Molecular Biology (Clifton, N.J.). 929: 21-48. PMID 23007425 DOI: 10.1007/978-1-62703-050-2_3 |
0.347 |
|
2012 |
Hu B, Lill MA. Protein pharmacophore selection using hydration-site analysis. Journal of Chemical Information and Modeling. 52: 1046-60. PMID 22397751 DOI: 10.1021/ci200620h |
0.356 |
|
2012 |
Xu M, Lill MA. Utilizing experimental data for reducing ensemble size in flexible-protein docking. Journal of Chemical Information and Modeling. 52: 187-98. PMID 22146074 DOI: 10.1021/Ci200428T |
0.532 |
|
2012 |
Danielson ML, Lill MA. Predicting flexible loop regions that interact with ligands: the challenge of accurate scoring. Proteins. 80: 246-60. PMID 22072600 DOI: 10.1002/Prot.23199 |
0.688 |
|
2011 |
Danielson ML, Desai PV, Mohutsky MA, Wrighton SA, Lill MA. Potentially increasing the metabolic stability of drug candidates via computational site of metabolism prediction by CYP2C9: The utility of incorporating protein flexibility via an ensemble of structures. European Journal of Medicinal Chemistry. 46: 3953-63. PMID 21703735 DOI: 10.1016/J.Ejmech.2011.05.067 |
0.689 |
|
2011 |
Lill MA. Efficient incorporation of protein flexibility and dynamics into molecular docking simulations. Biochemistry. 50: 6157-69. PMID 21678954 DOI: 10.1021/bi2004558 |
0.35 |
|
2011 |
Xu M, Lill MA. Significant enhancement of docking sensitivity using implicit ligand sampling. Journal of Chemical Information and Modeling. 51: 693-706. PMID 21375306 DOI: 10.1021/Ci100457T |
0.612 |
|
2011 |
Lill MA, Danielson ML. Computer-aided drug design platform using PyMOL. Journal of Computer-Aided Molecular Design. 25: 13-9. PMID 21053052 DOI: 10.1007/S10822-010-9395-8 |
0.653 |
|
2010 |
Danielson ML, Lill MA. New computational method for prediction of interacting protein loop regions. Proteins. 78: 1748-59. PMID 20186974 DOI: 10.1002/Prot.22690 |
0.68 |
|
2009 |
Ekins S, Kortagere S, Iyer M, Reschly EJ, Lill MA, Redinbo MR, Krasowski MD. Challenges predicting ligand-receptor interactions of promiscuous proteins: the nuclear receptor PXR. Plos Computational Biology. 5: e1000594. PMID 20011107 DOI: 10.1371/Journal.Pcbi.1000594 |
0.358 |
|
2009 |
Spreafico M, Ernst B, Lill MA, Smiesko M, Vedani A. Mixed-model QSAR at the glucocorticoid receptor: predicting the binding mode and affinity of psychotropic drugs. Chemmedchem. 4: 100-9. PMID 19009570 DOI: 10.1002/Cmdc.200800274 |
0.323 |
|
2008 |
Jiang Q, Yin X, Lill MA, Danielson ML, Freiser H, Huang J. Long-chain carboxychromanols, metabolites of vitamin E, are potent inhibitors of cyclooxygenases. Proceedings of the National Academy of Sciences of the United States of America. 105: 20464-9. PMID 19074288 DOI: 10.1073/Pnas.0810962106 |
0.596 |
|
2007 |
Lill MA. Multi-dimensional QSAR in drug discovery. Drug Discovery Today. 12: 1013-7. PMID 18061879 DOI: 10.1016/j.drudis.2007.08.004 |
0.343 |
|
2006 |
Lill MA, Dobler M, Vedani A. Prediction of small-molecule binding to cytochrome P450 3A4: flexible docking combined with multidimensional QSAR. Chemmedchem. 1: 73-81. PMID 16892339 DOI: 10.1002/cmdc.200500024 |
0.37 |
|
2006 |
Lill MA. Computational pharmaceutical chemistry - Novel technologies for lead optimization and the prediction of ADMET properties Chimia. 60: 33-36. DOI: 10.2533/000942906777675128 |
0.406 |
|
2005 |
Lill MA, Winiger F, Vedani A, Ernst B. Impact of induced fit on ligand binding to the androgen receptor: a multidimensional QSAR study to predict endocrine-disrupting effects of environmental chemicals. Journal of Medicinal Chemistry. 48: 5666-74. PMID 16134935 DOI: 10.1021/Jm050403F |
0.335 |
|
2005 |
Vedani A, Dobler M, Lill MA. Combining protein modeling and 6D-QSAR. Simulating the binding of structurally diverse ligands to the estrogen receptor. Journal of Medicinal Chemistry. 48: 3700-3. PMID 15916421 DOI: 10.1021/jm050185q |
0.307 |
|
2003 |
Dobler M, Lill MA, Vedani A. From crystal structures and their analysis to the in silico prediction of toxic phenomena Helvetica Chimica Acta. 86: 1554-1568. DOI: 10.1002/hlca.200390134 |
0.309 |
|
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