Selected ROCS Publications
Numerous journal articles have been published about ROCS through the years. Included here are some of the more impactful papers. They are arranged in chronological order, beginning with the seminal work on Gaussians by Grant, Gallardo, and Pickup.
Grant, J.A.; Gallardo, M.A.; Pickup, B.T. A Fast Method of Molecular Shape Comparison. A Simple Application of a Gaussian Description of Molecular Shape. J. Comput. Chem. 1996, 17 (14), 1653–1666. DOI: 10.1002/(sici)1096-987x(19961115)17:14<1653::aid-jcc7>3.0.co;2-k
Nicholls, A.; MacCuish, N.E.; MacCuish, J.D. Variable Selection and Model Validation of 2D and 3D Molecular Descriptors. J. Comput.-Aided Mol. Des. 2004, 18 (7), 451–474. DOI: 10.1007/s10822-004-5202-8
Rush, T.S.; Grant, J.A.; Mosyak, L.; Nicholls, A. A Shape-Based 3D Scaffold Hopping Method and Its Application to a Bacterial Protein–Protein Interaction. J. Med. Chem. 2005, 48 (5), 1489–1495. DOI: 10.1021/jm040163o
Haigh, J.A.; Pickup, B.T.; Grant, J.A.; Nicholls, A. Small Molecule Shape-Fingerprints. J. Chem. Inf. Model. 2005, 45 (3), 673-684. DOI: 10.1021/ci049651v
Chen, H.; Lyne, P.D.; Giordanetto, F.; Lovell, T.; Li, J. On Evaluating Molecular-Docking Methods for Pose Prediction and Enrichment Factors. J. Chem. Inf. Model. 2006, 46 (1), 401–415. DOI: 10.1021/ci0503255
Muchmore, S.W.; Souers, A.J.; Akritopoulou-Zanze, I. The Use of Three-Dimensional Shape and Electrostatic Similarity Searching in the Identification of a Melanin-Concentrating Hormone Receptor 1 Antagonist. Chem. Biol. Drug Des. 2006, 67 (2), 174–176. DOI: 10.1111/j.1747-0285.2006.00341.x
Hawkins, P.C.D.; Skillman, A.G.; Nicholls, A. Comparison of Shape-Matching and Docking as Virtual Screening Tools. J. Med. Chem. 2007, 50 (1), 74–82. DOI: 10.1021/jm0603365
McGaughey, G.B.; Sheridan, R.P.; Bayly, C.I.; Culberson, J.C.; Kreatsoulas, C.; Lindsley, S.; Maiorov, V.; Truchon, J.-F.; Cornell, W.D. Comparison of Topological, Shape, and Docking Methods in Virtual Screening. J. Chem. Inf. Model. 2007, 47 (4), 1504–1519. DOI: 10.1021/ci700052x
Boström, J.; Berggren, K., Elebring, T.; Greasley, P.J.; Wilstermann, M. Scaffold Hopping, Synthesis and Structure–Activity Relationships of 5,6-diaryl-pyrazine-2-amide Derivatives: A Novel Series of CB1 Receptor Antagonists. Bioorg. Med. Chem. 2007, 15 (12), 4077–4084. DOI: 10.1016/j.bmc.2007.03.075
Sutherland, J.J.; Nandigam, R.K.; Erickson, J.A.; Vieth, M. Lessons in Molecular Recognition. 2. Assessing and Improving Cross-Docking Accuracy. J. Chem. Inf. Model. 2007, 47 (6), 2293–2302. DOI: 10.1021/ci700253h
Freitas, R.F.; Oprea, T.I.; Montanari, C.A. 2D QSAR and Similarity Studies on Cruzain Inhibitors Aimed at Improving Selectivity over cathepsin L. Bioorg. Med. Chem. 2008, 16 (2), 838–853. DOI: 10.1016/j.bmc.2007.10.048
Sheridan, R.P.; McGaughey, G.B.; Cornell, W.D. Multiple Protein Structures and Multiple Ligands: Effects on the Apparent Goodness of Virtual Screening Results. J. Comput.-Aided Mol. Des. 2008, 22, 257–265. DOI: 10.1007/s10822-008-9168-9
Venhorst, J.; Núñez, S.; Terpstra, J.W.; Kruse, C.G. Assessment of Scaffold Hopping Efficiency by Use of Molecular Interaction Fingerprints. J. Med. Chem. 2008, 51 (11), 3222–3229. DOI: 10.1021/jm8001058
Nandigam, R.K.; Evans, D.A.; Erickson, J.A.; Kim, S.; Sutherland, J.J. Predicting the Accuracy of Ligand Overlay Methods with Random Forest Models. J. Chem. Inf. Model. 2008, 48 (12), 2386–2394. DOI: 10.1021/ci800216f
Sheridan, R.P. Alternative Global Goodness Metrics and Sensitivity Analysis: Heuristics to Check the Robustness of Conclusions from Studies Comparing Virtual Screening Methods. J. Chem. Inf. Model. 2008, 48 (2), 426–433. DOI: 10.1021/ci700380x
Lee, H.S.; Choi, J.; Kufareva, I.; Abagyan, R.; Filikov, A.; Yang, Y.; Yoon, S. Optimization of High Throughput Virtual Screening by Combining Shape-Matching and Docking Methods. J. Chem. Inf. Model. 2008, 48 (3), 489–497. DOI: 10.1021/ci700376c
Pérez-Nueno, V.I.; Ritchie, D.W.; Rabal, O.; Pascual, R.; Borrell, J.I.; Teixidó, J. Comparison of Ligand-Based and Receptor-Based Virtual Screening of HIV Entry Inhibitors for the CXCR4 and CCR5 Receptors Using 3D Ligand Shape Matching and Ligand-Receptor Docking, J. Chem. Inf. Model. 2008, 48 (3), 509–533. DOI: 10.1021/ci700415g
Moffat, K.; Gillet, V.J.; Whittle, M.; Bravi, G.; Leach, A.R. A Comparison of Field-Based Similarity Searching Methods: CatShape, FBSS, and ROCS. J. Chem. Inf. Model. 2008, 48 (4), 719–729. DOI: 10.1021/ci700130j
Muchmore, S.W.; Debe, D.A.; Metz, J.T.; Brown, S.P.; Martin, Y.C.; Hajduk, P.J. Application of Belief Theory to Similarity Data Fusion for Use in Analog Searching and Lead Hopping. J. Chem. Inf. Model. 2008, 48 (5), 941–948. DOI: 10.1021/ci7004498
Naylor, E.; Arredouani, A.; Vasudevan, S.R.; et al. Identification of a Chemical Probe for NAADP by Virtual Screening. Nat. Chem. Biol. 2009, 5, 220–226. DOI: 10.1038/nchembio.150
Oyarzabal, J.; Howe, T.; Alcazar, J.; Andres, J.I.; Alvarez, R.M.; Dautzenberg, F.; Iturrino, L.; Martınez, S.; Van der Linden, I. Novel Approach for Chemotype Hopping Based on Annotated Databases of Chemically Feasible Fragments and a Prospective Case Study: New Melanin Concentrating Hormone Antagonists. J. Med. Chem. 2009, 52 (7), 2076–2089. DOI: 10.1021/jm8016199
Tresadern, G.; Bemporad, D.; Howe, T. A Comparison of Ligand Based Virtual Screening Methods and Application to Corticotropin Releasing Factor 1 Receptor. J. Mol. Graphics Modell. 2009, 27 (8), 860–870. DOI: 10.1016/j.jmgm.2009.01.003
Tuccinardi, T.; Ortors, G.; Santos, M.A.; Marques, S.M.; Nuti, E.; Rossello, A.; Martinelli, A. Multitemplate Alignment Method for the Development of a Reliable 3D-QSAR Model for the Analysis of MMP3 Inhibitors. J. Chem. Inf. Model. 2009, 49 (7), 1715–1724. DOI: 10.1021/ci900118v
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. Molecular Shape and Medicinal Chemistry: A Perspective. J. Med. Chem. 2010, 53 (10), 3862–3886. DOI: 10.1021/jm900818s
Krüger, D.M.; Evers, A. Comparison of Structure- and Ligand-Based Virtual Screening Protocols Considering Hitlist Complementarity and Enrichment Factors. ChemMedChem 2010, 5 (1), 148–158. DOI: 10.1002/cmdc.200900314
Swann, S.L.; Brown, S.P.; Muchmore, S.W.; Patel, H.; Merta, P.; Locklear, J.; Hajduk, P.J. A Unified Probabilistic Framework for Structure- and Ligand-Based Virtual Screening. J. Med. Chem. 2011, 54 (5), 1223–1232. DOI: 10.1021/jm1013677
Wollenhaupt, J.; Metz, A.; Barthel, T.; Lima, G.M.A.; Heine, A.; Mueller, U.; Klebe, G.; Weiss, M.S. F2X-Universal and F2X-Entry: Structurally Diverse Compound Libraries for Crystallographic Fragment Screening. Structure 2020, 28 (6), 694–706.e5. DOI: 10.1016/j.str.2020.04.019
Taylor, A.I.P.; Xu, Y.; Wilkinson, M.; Chakraborty, P.; Brinkworth, A.; Willis, L.F.; Zhuravleva, A.; Ranson, N.A.; Foster, R.; Radford, S.E. Kinetic Steering of Amyloid Formation and Polymorphism by Canagliflozin, a Type-2 Diabetes Drug. J. Am. Chem. Soc. 2025, 147 (14), 11859–11878. DOI: 10.1021/jacs.4c16743
Rossen, L.; Sirockin, F.; Schneider, N.; Grisoni, F. Scaffold Hopping with Generative Reinforcement Learning. J. Chem. Inf. Model. 2025, 65 (13), 6513–6525. DOI: 10.1021/acs.jcim.5c00029