Effects of inductive bias on computational evaluations of ligand-based modeling and on drug discovery. - Ann E. Cleves; Ajay N. Jain (J. Comput. Aided Mol. Des., 2008)

Does your model weigh the same as a Duck? - Ajay N. Jain; Ann E. Cleves (J. Comput. Aided Mol. Des., 2012)

A structure-guided approach for protein pocket modeling and affinity prediction. - Rocco Varela; Ann E. Cleves; Russell Spitzer; Ajay N. Jain (J. Comput. Aided Mol. Des., 2013)

Prediction of Off-Target Drug Effects Through Data Fusion. - Emmanuel R. Yera; Ann E. Cleves; Ajay N. Jain (Pacific Symposium on Biocomputing, 2014)

Chemical and protein structural basis for biological crosstalk between PPARα and COX enzymes. - Ann E. Cleves; Ajay N. Jain (J. Comput. Aided Mol. Des., 2015)

Knowledge-guided docking: accurate prospective prediction of bound configurations of novel ligands using Surflex-Dock. - Ann E. Cleves; Ajay N. Jain (J. Comput. Aided Mol. Des., 2015)

Extrapolative prediction using physically-based QSAR. - Ann E. Cleves; Ajay N. Jain (J. Comput. Aided Mol. Des., 2016)

ForceGen 3D structure and conformer generation: from small lead-like molecules to macrocyclic drugs. - Ann E. Cleves; Ajay N. Jain (J. Comput. Aided Mol. Des., 2017)

Quantitative surface field analysis: learning causal models to predict ligand binding affinity and pose. - Ann E. Cleves; Ajay N. Jain (J. Comput. Aided Mol. Des., 2018)

Electrostatic-field and surface-shape similarity for virtual screening and pose prediction. - Ann E. Cleves; Stephen R. Johnson; Ajay N. Jain (J. Comput. Aided Mol. Des., 2019)

Complex macrocycle exploration: parallel, heuristic, and constraint-based conformer generation using ForceGen. - Ajay N. Jain; Ann E. Cleves; Qi Gao; Xiao Wang; Yizhou Liu; Edward C. Sherer; Mikhail Y. Reibarkh (J. Comput. Aided Mol. Des., 2019)

Structure- and Ligand-Based Virtual Screening on DUD-E+: Performance Dependence on Approximations to the Binding Pocket. - Ann E. Cleves; Ajay N. Jain (J. Chem. Inf. Model., 2020)

Synergy and Complementarity between Focused Machine Learning and Physics-Based Simulation in Affinity Prediction. - Ann E. Cleves; Stephen R. Johnson; Ajay N. Jain (J. Chem. Inf. Model., 2021)

Complex peptide macrocycle optimization: combining NMR restraints with conformational analysis to guide structure-based and ligand-based design. - Ajay N. Jain; Alexander C. Brueckner; Christine Jorge; Ann E. Cleves; Purnima Khandelwal; Janet Caceres Cortes; Luciano Mueller (J. Comput. Aided Mol. Des., 2023)

Deep-Learning Based Docking Methods: Fair Comparisons to Conventional Docking Workflows. - Ajay N. Jain; Ann E. Cleves; W. Patrick Walters (CoRR, 2024)

From UK-2A to florylpicoxamid: Active learning to identify a mimic of a macrocyclic natural product. - Ann E. Cleves; Ajay N. Jain; David A. Demeter; Zachary A. Buchan; Jeremy Wilmot; Erin N. Hancock (J. Comput. Aided Mol. Des., 2024)

Structure-based pose prediction: Non-cognate docking extended to macrocyclic ligands. - Ann E. Cleves; Himani Tandon; Ajay N. Jain (J. Comput. Aided Mol. Des., 2024)

Correction: Complex peptide macrocycle optimization: combining NMR restraints with conformational analysis to guide structure-based and ligand-based design. - Ajay N. Jain; Alexander C. Brueckner; Christine Jorge; Ann E. Cleves; Purnima Khandelwal; Janet Caceres Cortes; Luciano Mueller (J. Comput. Aided Mol. Des., 2024)