PRO_LIGAND: An approach to de novo molecular design. 1. Application to the design of organic molecules. - David E. Clark; David Frenkel; Stephen A. Levy; Jin Li 004; Christopher W. Murray; Barry Robson; Bohdan Waszkowycz; David R. Westhead (J. Comput. Aided Mol. Des., 1995)

PRO_LIGAND: An approach to de novo molecular design. 4. Application to the design of peptides. - David Frenkel; David E. Clark; Jin Li 004; Christopher W. Murray; Barry Robson; Bohdan Waszkowycz; David R. Westhead (J. Comput. Aided Mol. Des., 1995)

PRO_LIGAND: An approach to de novo molecular design. 6. Flexible fitting in the design of peptides. - Christopher W. Murray; David E. Clark; Deirdre G. Byrne (J. Comput. Aided Mol. Des., 1995)

PRO_LIGAND: An approach to de novo molecular design. 3. A genetic algorithm for structure refinement. - David R. Westhead; David E. Clark; David Frenkel; Jin Li 004; Christopher W. Murray; Barry Robson; Bohdan Waszkowycz (J. Comput. Aided Mol. Des., 1995)

PRO_LIGAND: An Approach to de Novo Molecular Design, 5. Tools for the Analysis of Generated Structures. - David E. Clark; Christopher W. Murray (J. Chem. Inf. Comput. Sci., 1995)

Active-site-directed 3D database searching: Pharmacophore extraction and validation of hits. - David E. Clark; David R. Westhead; Richard A. Sykes; Christopher W. Murray (J. Comput. Aided Mol. Des., 1996)

MOLMAKER: De Novo Generation of 3D Databases for Use in Drug Design. - David E. Clark; Michael A. Firth; Christopher W. Murray (J. Chem. Inf. Comput. Sci., 1996)

Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes. - Matthew D. Eldridge; Christopher W. Murray; Timothy R. Auton; Gaia Valeria Paolini; Roger P. Mee (J. Comput. Aided Mol. Des., 1997)

PRO_SELECT: Combining structure-based drug design and combinatorial chemistry for rapid lead discovery. 1. Technology. - Christopher W. Murray; David E. Clark; Timothy R. Auton; Michael A. Firth; Jin Li 004; Richard A. Sykes; Bohdan Waszkowycz; David R. Westhead; Stephen C. Young (J. Comput. Aided Mol. Des., 1997)

A comparison of heuristic search algorithms for molecular docking. - David R. Westhead; David E. Clark; Christopher W. Murray (J. Comput. Aided Mol. Des., 1997)

Empirical scoring functions. II. The testing of an empirical scoring function for the prediction of ligand-receptor binding affinities and the use of Bayesian regression to improve the quality of the model. - Christopher W. Murray; Timothy R. Auton; Matthew D. Eldridge (J. Comput. Aided Mol. Des., 1998)

The sensitivity of the results of molecular docking to induced fit effects: Application to thrombin, thermolysin and neuraminidase. - Christopher W. Murray; Carol A. Baxter; David A. Frenkel (J. Comput. Aided Mol. Des., 1999)

New Approach to Molecular Docking and Its Application to Virtual Screening of Chemical Databases. - Carol A. Baxter; Christopher W. Murray; Bohdan Waszkowycz; Jin Li 004; Richard A. Sykes; Richard G. A. Bone; Tim D. J. Perkins; William Wylie (J. Chem. Inf. Comput. Sci., 2000)

Sensitivity of molecular docking to induced fit effects in influenza virus neuraminidase. - Louise Birch; Christopher W. Murray; Michael J. Hartshorn; Ian J. Tickle; Marcel L. Verdonk (J. Comput. Aided Mol. Des., 2002)

The consequences of translational and rotational entropy lost by small molecules on binding to proteins. - Christopher W. Murray; Marcel L. Verdonk (J. Comput. Aided Mol. Des., 2002)

Virtual Screening Using Protein-Ligand Docking: Avoiding Artificial Enrichment. - Marcel L. Verdonk; Valerio Berdini; Michael J. Hartshorn; Wijnand T. M. Mooij; Christopher W. Murray; Richard D. Taylor; Paul Watson 002 (J. Chem. Inf. Model., 2004)

Protein-Ligand Docking against Non-Native Protein Conformers. - Marcel L. Verdonk; Paul N. Mortenson; Richard J. Hall; Michael J. Hartshorn; Christopher W. Murray (J. Chem. Inf. Model., 2008)

Assessing the lipophilicity of fragments and early hits. - Paul N. Mortenson; Christopher W. Murray (J. Comput. Aided Mol. Des., 2011)

Meaningful machine learning models and machine-learned pharmacophores from fragment screening campaigns. - Carl Poelking; Gianni Chessari; Christopher W. Murray; Richard J. Hall; Lucy J. Colwell; Marcel L. Verdonk (CoRR, 2022)