Cleves, A. E. and Jain, A. N. (2018). Quantitative Surface Field Analysis: Learning Causal Models to Predict Ligand Binding Affinity and Pose. Journal of Computer-Aided Molecular Design, 32, 731-757.

Cleves, A. E. and Jain, A. N. (2017). ForceGen 3D structure and conformer generation: From small lead-like molecules to macrocyclic drugs. Journal of Computer-Aided Molecular Design, 31(5), 419-439.

Cleves, A. E. and Jain, A. N. (2016). Extrapolative prediction using physically-based QSAR. Journal of Computer-Aided Molecular Design, 30(2), 127-152.

Cleves, A. E. and Jain, A. N. (2015). Knowledge-Guided Docking: Accurate Prospective Prediction of Bound Configurations of Novel Ligands using Surflex-Dock. Journal of Computer-Aided Molecular Design, 29(6), 485-509.

Cleves, A. E. and Jain, A. N. (2015). Chemical and Protein Structural Basis for Biological Crosstalk Between PPAR-alpha and COX Enzymes. Journal of Computer-Aided Molecular Design, 29(2),101-112.

Yera, E. R., Cleves, A. E., & Jain, A. N. (2014). Prediction of off-target drug effects through data fusion. In Pacific Symposium on Biocomputing (Vol. 19, pp. 160-171).

Varela, R., Cleves, A. E., Spitzer, R., and Jain, A. N. (2013). A structure-guided approach for protein pocket modeling and affinity prediction. Journal of Computer-Aided Molecular Design, 27(11), 917-934.

Spitzer, R., Cleves, A. E., Varela, R., and Jain, A. N. (2013). Protein function annotation by local binding site surface similarity. Proteins: Structure, Function, and Bioinformatics.

Varela, R., Walters, W. P., Goldman, B. B., and Jain, A. N. (2012). Iterative Refinement of a Binding Pocket Model: Active Computational Steering of Lead Optimization. Journal of Medicinal Chemistry, 55(20), 8926-8942.

Spitzer, R., and Jain, A.N. (2012). Surflex-Dock: Docking Benchmarks and Real-World Application. J Computer-Aided Molecular Design, 26: 687-699.

Jain, A.N., and Cleves, A.C. (2012). Does Your Model Weigh the Same as a Duck? J Computer-Aided Molecular Design, 26, 57-67.

Yera, E.R., Cleves, A.E., and Jain, A.N. (2011) Chemical Structural Novelty: On-Targets and Off-Targets. J Med Chem, 64, 6771-6785.

Spitzer, R., Cleves, A.E., and Jain, A.N. (2011) Surface-Based Protein Binding Pocket Similarity. Proteins, 79: 2746-2763.

Jain, A.N. (2010). QMOD: Physically Meaningful QSAR. J Computer-Aided Molecular Design, 24, 865-878.

Nicholls, A., McGaughey, G.B., Sheridan, R.P., Good, A.C., Warren, G., Mathieu, M., Muchmore, S.W., Brown, S.P., Grant, J.A., Haigh, J.A., Nevins, N., Jain, A.N., Kelley, B. (2010) Molecular Shape and Medicinal Chemistry: A Perspective. J Med Chem, 53: 3862-3886.

Jain, A.N. (2009). Effects of Protein Conformation in Docking: Improved Pose Prediction Through Protein Pocket Adaptation. J Computer-Aided Molecular Design, 23: 355-374

Cleves, A.E. and Jain, A.N. (2008). Effects of Inductive Bias on Computational Evaluations of Ligand-Based Modeling and on Drug Discovery. J Computer-Aided Molecular Design, 22, 147-159

Jain, A.N. (2008). Bias, Reporting, and Sharing: Computational Evaluations of Docking Methods. J Computer-Aided Molecular Design, 22, 201-212.

Pham, T. A. and Jain, A.N. (2008). Customizing Scoring Functions for Docking. J Computer-Aided Molecular Design, 22, 269-286.

Langham, J.J. and Jain, A.N. (2008). Accurate and Interpretable Computational Modeling of Chemical Mutagenicity. J Chem Inf Model, 48, 1833-1839.

Jain, A.N. (2007). Surflex-Dock 2.1: Robust Performance from Ligand Energetic Modeling, Ring Flexibility, and Knowledge-Based Search. J Computer-Aided Molecular Design, 21, 281-306.

Cleves, A. E. and Jain, A.N. (2006). Robust Ligand-Based Modeling of the Biological Targets of Known Drugs. J Med Chem 49, 2921-2938.

Pham, T. A. and Jain, A.N. (2006). Parameter Estimation for Scoring Protein-Ligand Interactions using Negative Training Data. J Med Chem, 49, 5856-5868.

Jain, A.N. (2004). Virtual Screening in Lead Discovery and Optimization. Curr Op Drug Discovery & Dev 7, 396-403.

Jain, A.N. (2004). Ligand-Based Structural Hypotheses for Virtual Screening. J Med Chem 47, 947-961.

Jain, A.N. (2003). Surflex: Fully Automatic Flexible Molecular Docking using a Molecular Similarity-Based Search Engine. J Med Chem 46, 499-511.

Perkins, E., Sun, D., Nguyen, A., Tulac, S., Francesco, M., Tavana, H., Nguyen, H., Tugendreich, S., Barthmaier, P., Couto, J., Yeh, E., Thode, S., Jarnagin, K., Jain, A.N., Morgans, D. & Melese, T. (2001). Novel inhibitors of poly(ADP-ribose) polymerase/PARP1 and PARP2 identified using a cell-based screen in yeast. Cancer Res 61, 4175-83.

Jain, A.N. (2000). Morphological similarity: A 3D molecular similarity method correlated with protein-ligand recognition. J Comput Aided Mol Des 14, 199-213.

Mount, J., Ruppert, J., Welch, W. & Jain, A.N. (1999). IcePick: A flexible surface-based system for molecular diversity. J Med Chem 42, 60-6.

Ghuloum, A.M., Sage, C.R. & Jain, A.N. (1999). Molecular hashkeys: A novel method for molecular characterization and its application for predicting important pharmaceutical properties of molecules. J Med Chem 42, 1739-48.

Ruppert, J., Welch, W. & Jain, A.N. (1997). Automatic identification and representation of protein binding sites for molecular docking. Protein Sci 6, 524-33.

Welch, W., Ruppert, J. & Jain, A.N. (1996). Hammerhead: Fast, fully automated docking of flexible ligands to protein binding sites. Chem Biol 3, 449-62.

Jain, A.N. (1996). Scoring noncovalent protein-ligand interactions: A continuous differentiable function tuned to compute binding affinities. J Comput Aided Mol Des 10, 427-40.

Jain, A.N., Harris, N.L. & Park, J.Y. (1995). Quantitative binding site model generation: compass applied to multiple chemotypes targeting the 5-HT1A receptor. J Med Chem 38, 1295-308.

Jain, A.N., Koile, K. & Chapman, D. (1994). Compass: Predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark. J Med Chem 37, 2315-27.

Jain, A.N., Dietterich, T.G., Lathrop, R.H., Chapman, D., Critchlow, R.E., Jr., Bauer, B.E., Webster, T.A. & Lozano-Perez, T. (1994). A shape-based machine learning tool for drug design. J Comput Aided Mol Des 8, 635-52.



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