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2020 – today
- 2024
[j16]Ajay N. Jain
, Alexander C. Brueckner, Christine Jorge, Ann E. Cleves, Purnima Khandelwal, Janet Caceres Cortes, Luciano Mueller:
Correction: Complex peptide macrocycle optimization: combining NMR restraints with conformational analysis to guide structure-based and ligand-based design. J. Comput. Aided Mol. Des. 38(1): 12 (2024)- [j15]Ann E. Cleves, Ajay N. Jain, David A. Demeter, Zachary A. Buchan, Jeremy Wilmot, Erin N. Hancock:
From UK-2A to florylpicoxamid: Active learning to identify a mimic of a macrocyclic natural product. J. Comput. Aided Mol. Des. 38(1): 19 (2024) - [j14]Ann E. Cleves, Himani Tandon, Ajay N. Jain:
Structure-based pose prediction: Non-cognate docking extended to macrocyclic ligands. J. Comput. Aided Mol. Des. 38(1): 33 (2024) - 2023
- [j13]Ajay N. Jain, Alexander C. Brueckner, Christine Jorge, Ann E. Cleves, Purnima Khandelwal, Janet Caceres Cortes, Luciano Mueller:
Complex peptide macrocycle optimization: combining NMR restraints with conformational analysis to guide structure-based and ligand-based design. J. Comput. Aided Mol. Des. 37(11): 519-535 (2023) - 2021
- [j12]Ann E. Cleves, Stephen R. Johnson, Ajay N. Jain:
Synergy and Complementarity between Focused Machine Learning and Physics-Based Simulation in Affinity Prediction. J. Chem. Inf. Model. 61(12): 5948-5966 (2021) - 2020
- [j11]Ann E. Cleves, Ajay N. Jain:
Structure- and Ligand-Based Virtual Screening on DUD-E+: Performance Dependence on Approximations to the Binding Pocket. J. Chem. Inf. Model. 60(9): 4296-4310 (2020)
2010 – 2019
- 2019
- [j10]Ajay N. Jain, Ann E. Cleves, Qi Gao, Xiao Wang, Yizhou Liu, Edward C. Sherer, Mikhail Y. Reibarkh:
Complex macrocycle exploration: parallel, heuristic, and constraint-based conformer generation using ForceGen. J. Comput. Aided Mol. Des. 33(6): 531-558 (2019) - [j9]Ann E. Cleves, Stephen R. Johnson, Ajay N. Jain:
Electrostatic-field and surface-shape similarity for virtual screening and pose prediction. J. Comput. Aided Mol. Des. 33(10): 865-886 (2019) - 2018
- [j8]Ann E. Cleves, Ajay N. Jain:
Quantitative surface field analysis: learning causal models to predict ligand binding affinity and pose. J. Comput. Aided Mol. Des. 32(7): 731-757 (2018) - 2017
- [j7]Ann E. Cleves, Ajay N. Jain:
ForceGen 3D structure and conformer generation: from small lead-like molecules to macrocyclic drugs. J. Comput. Aided Mol. Des. 31(5): 419-439 (2017) - 2016
- [j6]Ann E. Cleves, Ajay N. Jain:
Extrapolative prediction using physically-based QSAR. J. Comput. Aided Mol. Des. 30(2): 127-152 (2016) - 2015
- [j5]Ann E. Cleves, Ajay N. Jain:
Chemical and protein structural basis for biological crosstalk between PPARα and COX enzymes. J. Comput. Aided Mol. Des. 29(2): 101-112 (2015) - [j4]Ann E. Cleves, Ajay N. Jain:
Knowledge-guided docking: accurate prospective prediction of bound configurations of novel ligands using Surflex-Dock. J. Comput. Aided Mol. Des. 29(6): 485-509 (2015) - 2014
- [c1]Emmanuel R. Yera, Ann E. Cleves, Ajay N. Jain:
Prediction of Off-Target Drug Effects Through Data Fusion. Pacific Symposium on Biocomputing 2014: 160-171 - 2013
- [j3]Rocco Varela, Ann E. Cleves, Russell Spitzer, Ajay N. Jain:
A structure-guided approach for protein pocket modeling and affinity prediction. J. Comput. Aided Mol. Des. 27(11): 917-934 (2013) - 2012
- [j2]Ajay N. Jain, Ann E. Cleves:
Does your model weigh the same as a Duck? J. Comput. Aided Mol. Des. 26(1): 57-67 (2012)
2000 – 2009
- 2008
- [j1]Ann E. Cleves, Ajay N. Jain:
Effects of inductive bias on computational evaluations of ligand-based modeling and on drug discovery. J. Comput. Aided Mol. Des. 22(3-4): 147-159 (2008)
Coauthor Index
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