This paper summarizes the historical development of the discipline that is now called `chemoinformatics'. It shows how this has evolved, principally as a result of technological developments in chemistry and biology during the past decade, from long-established techniques for the modelling and searching of chemical molecules. A total of 30 papers, the earliest dating back to 1957, are briefly summarized to highlight some of the key publications and to show the development of the discipline.
R.V. Williams and M.E. Bowden, Chronology of Chemical Information Science . Available at: www.libsci.sc.edu/bob/chemnet/chchron.htm (accessed 12 November 2007).
2.
D.W. Weisgerber , Chemical Abstracts ServiceChemical Registry System: history, scope and impacts, Journal of the American Society for Information Science48(4) (1997) 349-60.
3.
S.R. Heller (ed.), The Beilstein Online Database - Implementation, Content, and Retrieval (American Chemical Society, Washington, DC, 1990).
4.
R.T. Bottle and J.F.B. Rowland (eds), Information Sources in Chemistry (4th Edition) (Bowker-Saur, London, 1993).
5.
R.E. Maizel , How to Find Chemical Information (3rd Edition) (Wiley, New York, 1998 ).
6.
W.A. Warr and C. Suhr, Chemical Information Management (VCH, Weinheim, 1992).
7.
C.A. Orengo, J.M. Thornton and D.Y. Jones (eds), Bioinformatics (Bios Scientific Publishers, Abingdon, 2002).
8.
A.M. Lesk, An Introduction to Bioinformatics (2nd Edition) (Oxford University Press, Oxford , 2005).
9.
W.V. Metanomski , 50 Years of Chemical Information in the American Chemical Society 1943-1993 (American Chemical Society, Washington, DC, 1993).
10.
W.L. Chen, Chemoinformatics: past, present and future, Journal of Chemical Information and Modeling46(6) (2006) 2230-55.
11.
M.F. Lynch, J.M. Harrison, W.G. Town and J.E. Ash, Computer Handling of Chemical Structure Information ( Macdonald , London, 1971).
12.
W.T. Wipke, S. Heller, R. Feldmann and E. Hyde (eds), Computer Representation and Manipulation of Chemical Information (John Wiley, New York, 1974).
13.
J.E. Ash and E. Hyde (eds), Chemical Information Systems ( Ellis Horwood, Chichester, 1975).
14.
J.E. Ash, P.A. Chubb, S.E. Ward, S.M. Welford and P. Willett (eds), Communication, Storage and Retrieval of Chemical Information (Ellis Horwood, Chichester , 1985).
15.
J.E. Ash, W.A. Warr and P. Willett (eds), Chemical Structure Systems (Ellis Horwood, Chichester, 1991).
16.
W.E. Warr (ed.), Chemical Structures: The International Language of Chemistry (Springer , Berlin, 1988).
17.
P. Willett, A bibliometric analysis of chemoinformatics, Aslib Proceedings (forthcoming).
18.
F.K. Brown , Chemoinformatics: what is it and how does it impact drug discovery? Annual Reports in Medicinal Chemistry33 (1998) 375-84.
19.
W.A. Warr, Balancing the needs of the recruiters and the aims of the educators (1999). Paper presented at the 218th American Chemical Society National Meeting, New Orleans , August 22-26, 1999. Available in part at: www.warr.com/warrzone2000.html (accessed 13 November 2007).
20.
J. Gasteiger , The central role of chemoinformatics, Chemometrics and Intelligent Laboratory Systems82(1/2) ( 2006) 200-209.
21.
H. Kubinyi , QSAR and 3D QSAR in drug design: Part 1, Drug Discovery Today2(11) (1997) 457-67.
22.
H. Kubinyi , QSAR and 3D QSAR in drug design: Part 2, Drug Discovery Today2(12) (1997) 538-46.
23.
H. Kubinyi , From narcosis to hyperspace: the history of QSAR, Quantitative Structure-Activity Relationships21(4) (2002) 348-56.
24.
H. Skolnik , The journal for chemical information and computer scientists: a 25-year perspective, Journal of Chemical Information and Computer Sciences25(3) (1985) 137-40.
25.
H. Schofield , G. Wiggins and P. Willett, Recent developments in chemoinformatics education, Drug Discovery Today6 (18) (2001) 931-4.
26.
D.J. Wild and G.D. Wiggins, Challenges for chemoinformatics education in drug discovery, Drug Discovery Today11(9/10) ( 2006) 436-39.
27.
A.R. Leach and V.J. Gillet, An Introduction to Chemoinformatics (Kluwer, Dordrecht, 2003).
28.
J. Gasteiger and T. Engel (eds), Chemoinformatics: A Textbook ( Wiley-VCH, Weinheim, 2003).
29.
J. Gasteiger (ed.), Handbook of Chemoinformatics (Wiley-VCH, Weinheim, 2003).
30.
M.F. Lynch and P. Willett, Information retrieval research in the Department of Information Studies, University of Sheffield : 1965-1985, Journal of Information Science, 13(4) (1987) 221-34.
31.
N. Bishop , V.J. Gillet, J.D. Holliday and P. Willett, Chemoinformatics research at the University of Sheffield: a history and citation analysis, Journal of Information Science29(4) (2003) 249-67.
32.
L.C. Ray and R.A. Kirsch, Finding chemical records by digital computers , Science126(3278) (1957) 814-19.
33.
G.E. Vleduts , Concerning one system of classification and codification of organic reactions, Information Storage and Retrieval1(2/3) (1963) 117-46.
34.
M.F. Lynch , J.M. Barnard and S.M. Welford, Computer storage and retrieval of generic chemical structures in patents, part 1: introduction and general strategy , Journal of Chemical Information and Computer Sciences21(3) (1981) 148-50.
35.
C.W. Crandell and D.H. Smith, Computer-assisted examination of compounds for common three-dimensional substructures, Journal of Chemical Information and Computer Sciences23(4) (1983) 186-97.
36.
Y.C. Martin , M.G. Bures, E.A. Danaher, J. Delazzer, I. Lico and P.A. Pavlik, A fast new approach to pharmacophore mapping and its application to dopaminergic and benzodiazepine agonists, Journal of Computer-Aided Molecular Design7(1) (1993) 83-102.
37.
G.W. Adamson and J.A. Bush, A method for the automatic classification of chemical structures, Information Storage and Retrieval9(10) ( 1973) 561-8.
38.
R.E. Carhart , D.H. Smith and R. Venkataraghavan, Atom pairs as molecular-features in structure activity studies - definition and applications, Journal of Chemical Information and Computer Sciences25(2) (1985) 64-73.
39.
P. Willett , V. Winterman and D. Bawden, Implementation of nearest-neighbour searching in an online chemical structure search system, Journal of Chemical Information and Computer Sciences26(1) (1986) 36-41.
40.
P. Willett, Similarity and Clustering in Chemical Information Systems ( Research Studies Press, Letchworth, 1987).
41.
P. Willett , Similarity-based virtual screening using 2D fingerprints, Drug Discovery Today11(23/24) ( 2006) 1046-53.
42.
R.D. Cramer , D.E. Patterson and J.D. Bunce, Comparative Molecular-Field Analysis(CoMFA), 1: effect of shape on binding of steroids to carrier proteins , Journal of the American Chemical Society110(18) ( 1988) 5959-67.
43.
S.M. Free and J.W. Wilson, A mathematical contribution to structure-activity studies, Journal of Medicinal Chemistry7(4) (1964) 395-99.
44.
I.D. Kuntz, J.M. Blaney, S.J. Oatley, R. Langridge and T.E. Ferrin, A geometric approach to macromolecule-ligand interactions, Journal of Molecular Biology161(2) (1982) 269-88.
45.
C.A. Lipinski , F. Lombardo, B.W. Dominy and P.J. Feeney, Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings, Advanced Drug Delivery Reviews23(1) (1997) 3-25.
46.
C. Hansch, P.P. Maloney, T. Fujita and R.M. Muir, Correlation of biological activity of phenoxyacetic acids with Hammett substituent constants and partition coefficients, Nature194(4824) (1962) 178-80.
47.
H. Morgan , The generation of a unique machine description for chemical structures - a technique developed at Chemical Abstracts Service , Journal of Chemical Documentation5(2) (1965) 107-13.
48.
E.H. Sussenguth , A graph-theoretic algorithm for matching chemical structures, Journal of Chemical Documentation5(1) (1965) 36-43.
49.
E. Hyde, F.W. Matthews, L.H. Thomson and W.J. Wiswesser, Conversion of Wiswesser notation to a connectivity matrix for organic compounds , Journal of Chemical Documentation7(4) (1967) 200-204.
50.
E.J. Corey and W.T. Wipke, Computer-assisted design of complex organic syntheses, Science166(3902) (1969) 178-92.
51.
J.E. Crowe , M.F. Lynch and W.G. Town, Analysis of structural characteristics of chemical compounds in a large computer-based file, I: non-cyclic fragments , Journal of the Chemical Society (C) ( 1970 ) 990-96.
52.
J.G. Topliss and R.J. Costello, Chance correlations in structure-activity studies using multiple regression analysis, Journal of Medicinal Chemistry15(2) (1972) 1066-8.
53.
R.D. Cramer , G. Redl and C.E. Berkoff, Substructural analysis: a novel approach to the problem of drug design, Journal of Medicinal Chemistry17(5) ( 1974) 533-5.
54.
J. Blair , J. Gasteiger, C. Gillespie, P.D. Gillespie and I. Ugi , Representation of the constitutional and stereochemical features of chemical systems in the computer-assisted design of syntheses , Tetrahedron30(13) (1974) 1845-59.
55.
A. Feldman and L. Hodes, An efficient design for chemical structure searching, I: the screens, Journal of Chemical Information and Computer Sciences15(3) (1975) 147-52.
56.
J.R. Ullmann , An algorithm for subgraph isomorphism, Journal of the ACM23(1) (1976) 31-42.
57.
P. Gund, Three-dimensional pharmacophoric pattern searching, Progress in Molecular and Subcellular Biology5 (1977) 117-43.
58.
M.F. Lynch and P. Willett, The automatic detection of chemical reaction sites, Journal of Chemical Information and Computer Sciences18(3) ( 1978) 154-9.
59.
G.R. Marshall , C.D. Barry, H.E. Bosshard, R.A. Dammkoehler and D.A. Dunn, The conformational parameter in drug design: the active analogue approach in computer-assisted drug design. In: E.C. Olson and R.E. Christoffersen (eds), Computer-Assisted Drug Design Vol. 112 (American Chemical Society, Washington DC , 1979).
60.
S.E. Jakes and P. Willett, Pharmacophoric pattern-matching in files of 3-D chemical structures - selection of interatomic distance screens , Journal of Molecular Graphics4(1) (1986) 12-20.
61.
D.J. Danziger and P.M. Dean, Automated site-directed drug design: a general algorithm for knowledge acquisition about hydrogen-bonding regions at protein surfaces, Proceedings of the Royal Society of London B 236(1283) ( 1989) 101-13.
62.
J. Gasteiger , C. Rudolph and J. Sadowski, Automatic generation of 3D atomic coordinates for organic molecules, Tetrahedron Computer Methodology3 (1990) 537-47.
63.
M.A. Johnson and G.M. Maggiora (eds), Concepts and Applications of Molecular Similarity (John Wiley, New York , 1990).
64.
E.J. Martin , J.M. Blaney, M.A. Siani, D.C. Spellmeyer, A.K. Wong and W.H. Moos, Measuring diversity: experimental design of combinatorial libraries for drug discovery, Journal of Medicinal Chemistry38(9) (1995) 1431-6.
65.
R.D. Brown and Y.C. Martin, Use of structure-activity data to compare structure-based clustering methods and descriptors for use in compound selection , Journal of Chemical Information and Computer Sciences36(3) ( 1996) 572-84.
66.
D.E. Patterson , R.D. Cramer, A.M. Ferguson, R.D. Clark and L.E. Weinberger, Neighbourhood behaviour: a useful concept for validation of `molecular diversity' descriptors , Journal of Medicinal Chemistry39(16) (1996) 3049-59.
67.
W. Graf, H.K. Kaindl, H. Kniess, B. Schmidt and R. Warszawski, Substructure retrieval by means of the BASIC Fragment Search Dictionary based on the Chemical Abstracts Service Chemical Registry III System, Journal of Chemical Information and Computer Sciences19(1) (1979) 51-5.
68.
P.G. Dittmar , N.A. Farmer, W. Fisanick, R.C. Haines and J. Mockus, The CAS ONLINE search system, I: general system design and selection, generation and use of search screens, Journal of Chemical Information and Computer Sciences23(3) (1983) 93-102.
69.
R. Attias, DARC substructure search system: a new approach to chemical information , Journal of Chemical Information and Computer Sciences23(3) (1983) 102-8.
70.
S.R. Heller , G.W.A. Milne and R.J. Feldmann, A computer-based chemical information system, Science195(4275) (1977) 253-9.
71.
A.P. Johnson , Computer aids to synthesis planning, Chemistry in Britain21(1) (1985) 59-67.
72.
W.T. Wipke, Exploring reactions with REACCS. In: Abstracts of the Papers of the American Chemical Society 188th Meeting (August 1984, Philadelphia) 43-CINF, ( ACS , Washington, DC, 1984).
73.
F.H. Allen , S. Bellard, M.D. Brice, B.A. Cartwright, A. Doubleday, H. Higgs, T. Hummelink, B.G. Hummelink-Peters, O. Kennard, W. D.S. Motherwell, J.R. Rogers and D.G. Watson, The Cambridge Crystallographic Data Centre: computer-based search, retrieval, analysis and display of information, Acta Crystallographica B 35 (1979) 2331-9.
74.
F.C. Bernstein , T.F. Koetzle, G.J.B. Williams, E.F. Meyer, M.D. Brice, J.R. Rodgers, O. Kennard, T. Shimanouchi and M. Tasumi, The Protein Data Bank: a computer-based archival file for macromolecular structures, Journal of Molecular Biology112 ( 1977) 535-42.
75.
D.P. Leiter , H.L. Morgan and R.E. Stobaugh, Installation and operation of a registry for chemical compounds, Journal of Chemical Documentation5(4) ( 1965) 238-42.
76.
D.J. Gluck , A chemical structure storage and search system developed at DuPont, Journal of Chemical Documentation5(1) (1965) 43-51.
77.
W. Wipke and T. Dyott, Stereochemically unique naming algorithm , Journal of the American Chemical Society96(15) (1974) 4825-34.
78.
R. Freeland , S. Funk, L. O'Korn and G. Wilson, The Chemical Abstracts Service Chemical Registry System, II: augmented connectivity molecular formula , Journal of Chemical Information and Computer Sciences19(2) (1979) 94-8.
79.
G. Salton and E.H. Sussenguth , Some flexible information retrieval systems using structure matching procedures, AFIPS Conference Proceedings, Spring Joint Computer Conference 25 (1964) 587-97.
80.
A.T. Brint and P. Willett, Pharmacophoric pattern matching in files of 3-D chemical structures: comparison of geometric searching algorithms , Journal of Molecular Graphics5(1) (1987) 49-56.
81.
G.M. Downs , M.F. Lynch, P. Willett, G.A. Manson and G.A. Wilson, Transputer implementations of chemical substructure searching algorithms, Tetrahedron Computer Methodology1(3) ( 1988) 207-17.
82.
L. Hodes , Selection of descriptors according to discrimination and redundancy - application to chemical-structure searching, Journal of Chemical Information and Computer Sciences16(2) (1976) 88-93.
83.
G.W. Adamson , J. Cowell, M.F. Lynch, A.H.W. McLure , W.G. Town and A.M. Yapp, Strategic considerations in the design of screening systems for substructure searches of chemical structure files, Journal of Chemical Documentation13(3) (1973) 153-7.
84.
C.L. Wilkins and M. Randic, A graph theoretical approach to structure-property and structure-activity correlation, Theoretica Chimica Acta58(1) ( 1980) 45-68.
85.
Y.C. Martin , J.L. Kofron and L.M. Traphagen, Do structurally similar molecules have similar biological activities?, Journal of Medicinal Chemistry45(19) ( 2002) 4350-58.
86.
R.P. Sheridan , B.P. Feuston, V.N. Maiorov and S.K. Kearsley, Similarity to molecules in the training set is a good discriminator for prediction accuracy in QSAR, Journal of Chemical Information and Computer Sciences44(6) ( 2004) 1912-28.
87.
J. Bostrom , A. Hogner and S. Schmitt, Do structurally similar ligands bind in a similar fashion?, Journal of Medicinal Chemistry49(23) ( 2006) 6716-25.
88.
H.-J. Böhm and G. Schneider (eds), Virtual Screening for Bioactive Molecules (Wiley-VCH, Weinheim, 2000).
89.
G. Klebe (ed.), Virtual Screening: an Alternative or Complement to High Throughput Screening (Kluwer, Dordrecht, 2000 ).
90.
J. Alvarez and B. Shoichet (eds), Virtual Screening in Drug Discovery (CRC Press, Boca Raton, 2005).
91.
P. Willett , J.M. Barnard and G.M. Downs, Chemical similarity searching, Journal of Chemical Information and Computer Sciences38(6) ( 1998) 983-96.
92.
R.P. Sheridan and S.K. Kearsley, Why do we need so many chemical similarity search methods?Drug Discovery Today7(17) (2002) 903-11.
93.
A. Bender and R.C. Glen, Molecular similarity: a key technique in molecular informatics, Organic and Biomolecular Chemistry2(22) (2004) 3204-18.
94.
J.E. Crowe, P. Leggate, B.N. Rossiter and J.F.B. Rowland, The searching of Wiswesser line notations by means of a character-matching serial search, Journal of Chemical Documentation13(2) (1973) 85-92.
95.
L.H. Thomson , E. Hyde and F.W. Matthews, Organic search and display using a connectivity matrix derived from Wiswesser notation, Journal of Chemical Documentation7(4) (1967) 204-9.
96.
E. Hyde and L.H. Thomson, Structure display, Journal of Chemical Documentation8(3) ( 1968) 138-46.
97.
D. Weininger , SMILES, a chemical language and information system, 1: introduction to methodology and encoding rules, Journal of Chemical Information and Computer Sciences28(1) (1988) 31-6.
98.
J.E. Armitage and M.F. Lynch, Automatic detection of structural similarities among chemical compounds, Journal of the Chemical Society (C) (1967) 521-8.
99.
P.E. Blower and R.C. Dana, Creation of a chemical reaction database from the primary literature. In: P. Willett (ed.), Modern Approaches to Chemical Reaction Searching , (Gower, Aldershot, 1986).
100.
T.E. Moock, J.G. Nourse, D. Grier and W.D. Hounshell, The implementation of atom-atom mapping and related features in the Reaction Access System (REACCS). In: W.A. Warr (ed.), Chemical Structures: The International Language of Chemistry, (Springer, Berlin , 1988).
101.
L. Chen , J.G. Nourse, B.D. Christie, B.A. Leland and D.L. Grier, Over 20 years of reaction access systems from MDL: a novel reaction substructure search algorithm, Journal of Chemical Information and Computer Sciences42(5) ( 2002) 1296-1310.
102.
M.F. Lynch and J.D. Holliday, The Sheffield Generic Structures project: a retrospective review, Journal of Chemical Information and Computer Sciences36(5) (1996) 930-36.
103.
A.H. Berks , Current state of the art of Markush topological search systems, World Patent Information23(1) (2001) 5-13.
104.
G.M. Downs and J.M. Barnard, Techniques for generating descriptive fingerprints in combinatorial libraries, Journal of Chemical Information and Computer Sciences37(1) (1997) 59-61.
105.
O. Güner (ed.), Pharmacophore Perception, Development and Use in Drug Design (International University Line , La Jolla, CA, 2000).
106.
P. Gund, W.T. Wipke and R. Langridge, Computer searching of a molecular structure file for pharmacophoric patterns . In: International Conference on Computers in Chemical Research and Education Vol. 3 (Elsevier, Amsterdam, 1974).
107.
F.H. Allen , The Cambridge Structural Database: a quarter of a million crystal structures and rising, Acta Crystallographica Section B-Structural Science58(31) (2002) 380-88.
108.
R.S. Pearlman , Rapid generation of high quality approximate 3D molecular structures, Chemical Design Automation News2 (1987) 1-7.
109.
C. Hiller and J. Gasteiger, Ein automatisierter Molekülbaukasten. In: J. Gasteiger (ed.), Software-Entwicklung in der Chemie 1 , (Springer, Berlin, 1987).
110.
D.V.S. Green , Automated three-dimensional structure generation . In: Y.C. Martin and P. Willett (eds), Designing Bioactive Molecules: Three-Dimensional Techniques and Applications, (American Chemical Society, Washington DC, 1998).
111.
P. Willett , Searching for pharmacophoric patterns in databases of three-dimensional chemical structures, Journal of Molecular Recognition8(5) (1995) 290-303.
112.
Y.C. Martin and P. Willett (eds), Designing Bioactive Molecules: Three-Dimensional Techniques and Applications (American Chemical Society , Washington, 1998 ).
113.
G. Jones , P. Willett and R.C. Glen, A genetic algorithm for flexible molecular overlay and pharmacophore elucidation, Journal of Computer-Aided Molecular Design9(6) (1995) 532-49.
114.
M. Rarey , B. Kramer, T. Lengauer and G. Klebe, A fast flexible docking method using an incremental construction algorithm, Journal of Molecular Biology261(3) ( 1996) 470-89.
115.
U. Rester , Dock around the clock - current status of small molecule docking and scoring, QSAR & Combinatorial Science25(7) ( 2006) 605-15.
116.
A.R. Leach , B.K. Shoichet and C.E. Peishoff, Prediction of protein-ligand interactions, docking and scoring: successes and gaps, Journal of Medicinal Chemistry49(20) (2006) 5851-5.
117.
Y.C. Martin , Quantitative Drug Design: A Critical Introduction (Marcel Dekker, New York, 1978).
118.
C. Hansch and A. Leo, Exploring QSAR: Fundamentals and Applications in Chemistry and Biology (American Chemical Society, Washington, DC, 1995).
119.
R. Mannhold and H. van de Waterbeemd, Substructure and whole molecule approaches for calculating log P, Journal of Computer-Aided Molecular Design15(4) (2001) 337-54.
120.
J.G. Topliss and R.P. Edwards, Chance factors in studies of quantitative structure-activity relationships, Journal of Medicinal Chemistry22(10) ( 1979) 1238-44.
121.
D.J. Livingstone and D.W. Salt, Judging the significance of multiple linear regression models, Journal of Medicinal Chemistry48(3) (2005) 661-3.
122.
D.W. Salt, S. Ajmani, R. Crichton and D.J. Livingstone , An improved approximation to the estimation of the critical F values in best subset regression, Journal of Chemical Information and Modeling47(1) (2007) 143-9.
123.
D.T. Manallack , D.D. Ellis and D.J. Livingstone, Analysis of linear and nonlinear QSAR data using neural networks, Journal of Medicinal Chemistry37(22) ( 1994) 3758-67.
124.
D.J. Livingstone , The characterisation of chemical structures using molecular properties, Journal of Chemical Information and Computer Sciences40(2) (2000) 195-209.
125.
R. Todeschini and V. Consonni, Handbook of Molecular Descriptors (Wiley-VCH, Weinheim, 2002).
126.
A. Golbraikh and A. Tropsha, Beware of q2!, Journal of Molecular Graphics and Modelling20(4) (2002) 269-76.
127.
D.M. Hawkins , The problem of overfitting, Journal of Chemical Information and Computer Sciences44(1) (2004) 1-12.
128.
S. Wold and W.J. Dunn, Multivariate quantitative structure-activity relationships (QSAR): conditions for their applicability, Journal of Chemical Information and Computer Sciences23(1) (1983) 6-13.
129.
G.W. Adamson and J.A. Bush, A method for relating the structure and properties of chemical compounds, Nature248 (1974) 406-7.
130.
G.W. Adamson and D. Bawden, A method of structure-activity correlation using Wiswesser Line Notation, Journal of Chemical Information and Computer Sciences15(4) (1975) 215-20.
131.
W. Tong , D.R. Lowis, R. Perkins, Y. Chen, W.J. Welsh, D.W. Goddette, T.W. Heritage and D.M. Sheehan, Evaluation of quantitative structure-activity relationship methods for large-scale prediction of chemicals binding to the estrogen receptor, Journal of Chemical Information and Computer Sciences38(4) (1998) 669-77.
132.
A. Ormerod , P. Willett and D. Bawden, Comparison of fragment weighting schemes for substructural analysis, Quantitative Structure-Activity Relationships8(2) (1989) 115-29.
133.
L. Hodes , G.F. Hazard, R.I. Geran and S. Richman, A statistical-heuristic method for automated selection of drugs for screening, Journal of Medicinal Chemistry20(4) ( 1977) 469-75.
134.
J. Hert , P. Willett, D.J. Wilton, P. Acklin, K. Azzaoui, E. Jacoby and A. Schuffenhauer, New methods for ligand-based virtual screening: use of data-fusion and machine-learning techniques to enhance the effectiveness of similarity searching, Journal of Chemical Information and Computer Sciences46(2) (2006) 462-70.
135.
X. Xia , E.G. Maliski, P. Gallant and D. Rogers, Classification of kinase inhibitors using a Bayesian model, Journal of Medicinal Chemistry47(18) (2004) 4463-70.
136.
A.M. Doweyko , The hypothetical active site lattice: an approach to modelling active sites from data on inhibitor molecules, Journal of Medicinal Chemistry31(7) (1988) 1396-1406.
137.
H. Kubinyi, G. Folkers and Y.C. Martin (eds), 3D QSAR in Drug Design (Kluwer/ ESCOM, Leiden, 1998).
138.
R.D. Cramer and B. Wendt, Pushing the boundaries of 3D-QSAR , Journal of Computer-Aided Molecular Design21(1/3) (2007 ) 23-32.
139.
B. Beck , A. Horn, J.E. Carpenter and T. Clark, Enhanced 3D-databases: a fully electrostatic database of AM1-optimized structures, Journal of Chemical Information and Computer Sciences38(6) (1998) 1214-17.
140.
D. Mayer , C.B. Naylor, I. Motoc and G.R. Marshall, A unique geometry of the active site of angiotensin-converting enzyme consistent with structure-activity studies , Journal of Computer-Aided Molecular Design1(1) (1987) 3-16.
141.
R.A. Dammkoehler , S.F. Karasek, E. F.B. Shands and G.R. Marshall, Constrained search of conformational hyperspace, Journal of Computer-Aided Molecular Design3(1) (1989) 3-21.
142.
A.T. Brint and P. Willett, Algorithms for the identification of three-dimensional maximal common substructures, Journal of Chemical Information and Computer Sciences27(4) (1987) 152-8.
143.
C. Bron and J. Kerbosch, Algorithm 457: finding all cliques of an undirected graph, Communications of the ACM16(9) ( 1973) 575-7.
144.
Y.C. Martin , Pharmacophore mapping. In: Y.C. Martin and P. Willett (eds), Designing Bioactive Molecules: Three-Dimensional Techniques and Applications (American Chemical Society , Washington , 1998).
145.
N.A.B. Gray , Computer Assisted Structure Elucidation (John Wiley, New York, 1986).
146.
N.A.B. Gray , Computer-aided structure elucidation. In: J.E. Ash et al. (eds), Chemical Structure Systems, ( Ellis Horwood, Chichester, 1991).
147.
R.K. Lindsay , B.G. Buchanan, E.A. Feigenbaum and J. Lederberg, Applications of Artificial Intelligence for Organic Chemistry: the DENDRAL Project (McGraw-Hill , New York, 1980).
148.
J. Lederberg , Topological mapping of organic molecules, Proceedings of the National Academy of Sciences, USA 53(1) (1965) 134-9.
149.
M.E. Munk , Computer-based structure determination: then and now, Journal of Chemical Information and Computer Sciences38(6) ( 1998) 997-1009.
150.
W. Bremser, HOSE: a novel substructure code, Analytica Chimica Acta103 (1978) 355-65.
151.
B.A. Jezl and D.L. Dalrymple, Computer program for the retrieval and assignment of chemical environments and shifts to facilitate interpretation of carbon-13 nuclear magnetic resonance spectra, Analytical Chemistry47(2) (1975) 203-7.
152.
W.A. Warr, Spectral databases, Chemometrics and Intelligent Laboratory Systems 10(3) ( 1991) 279-92.
153.
M.A. Ott , Cheminformatics and organic chemistry: computer-assisted synthetic analysis. In: J.H. Noordik (ed.), Cheminformatics Developments: History, Reviews and Current Research (IOS Press, Amsterdam, 2004).
154.
E.J. Corey, W.T. Wipke, R.D. Cramer and W.J. Howe, Computer-assisted synthetic analysis: facile man-machine communication of chemical structure by interactive computer graphics, Journal of the American Chemical Society94(2) (1972) 421-31.
155.
W.T. Wipke, G.I. Ouchi and S. Krishnan, Simulation and evaluation of chemical synthesis - SECS: an application of artificial intelligence techniques, Artificial Intelligence11(1/2) (1978) 173-93.
156.
W.T. Wipke and W.J. Howe (eds), Computer Assisted Organic Synthesis (American Chemical Society, Washington, 1977).
157.
F. Loftus, Computer-aided synthesis design; In: J.E. Ash et al. (eds), Chemical Structure Systems ( Ellis Horwood, Chichester, 1991).
158.
I. Ugi and P.D. Gillespie, Matter preserving synthetic pathways and semi-empirical computer assisted planning of syntheses, AngewandteChemie International Edition 10(12) (1971) 915-19.
159.
J. Gasteiger and C. Jochum, EROS: a computer program for generating sequences of reactions, Topics in Current Chemistry74 (1978) 93-126.
160.
W.D. Ihlenfeldt and J. Gasteiger, Computer-assisted planning of organic syntheses: the second generation of programs, Angewandte Chemie International Edition34(23/24) ( 1995) 2613-33.
161.
J. Gasteiger , W.D. Ihlenfeldt, P. Rose and R. Wanke, Computer-assisted prediction and synthesis design, Analytica Chimica Acta235(1) (1990) 65-75.
162.
J.C. Baber and M. Feher, Predicting synthetic accessibility: application in drug discovery and development, Mini Reviews in Medicinal Chemistry4(6) (2004) 681-92.
163.
H.-J. Böhm , The computer program LUDI: a new simple method for the de novo design of enzyme inhibitors, Journal of Computer-Aided Molecular Design6(1) (1992) 61-78.
164.
V.J. Gillet , A.P. Johnson, P. Mata and S. Sike, Automated structure design in 3D, Tetrahedron Computer Methodology3(6C) (1990) 681-96.
165.
R.C. Glen and A.W.R. Payne, A genetic algorithm for the automated generation of molecules with constraints, Journal of Computer-Aided Molecular Design9(2) (1995) 181-202.
166.
G. Schneider and U. Fechner, Computer-based de novo design of drug-like molecules, Nature Reviews Drug Discovery4(8) (2005) 649-63.
167.
P. Willett , V. Winterman and D. Bawden, Implementation of non-hierarchic cluster analysis methods in chemical information systems: selection of compounds for biological testing and clustering of substructure search output, Journal of Chemical Information and Computer Sciences26(3) (1986) 109-18.
168.
P.M. Dean and R.A. Lewis (eds), Molecular Diversity in Drug Design (Kluwer, Amsterdam, 1999 ).
169.
A.K. Ghose and V.N. Viswanadhan (eds), Combinatorial Library Design and Evaluation: Principles, Software Tools and Applications in Drug Discovery (Marcel Dekker, New York, 2001).
170.
A.-D. Gorse , Diversity in medicinal chemistry space, Current Topics in Medicinal Chemistry6(1) (2006) 3-18.
171.
Y.C. Martin , P. Willett, M. Lajiness, M. Johnson, G.M. Maggiora, E. Martin, M.G. Bures, J. Gasteiger, R.D. Cramer, R.S. Pearlman and J.S. Mason, Diverse viewpoints on computational aspects of molecular diversity, Journal of Combinatorial Chemistry3(3) ( 2001) 231-50.
172.
V.J. Gillet , P. Willett and J. Bradshaw, The effectiveness of reactant pools for generating structurally-diverse combinatorial libraries, Journal of Chemical Information and Computer Sciences37(4) (1997) 731-40.
173.
R.D. Brown and Y.C. Martin, The information content of 2D and 3D structural descriptors relevant to ligand-receptor binding, Journal of Chemical Information and Computer Sciences37(1) (1997) 1-9.
174.
V.J. Gillet , W. Khatib, P. Willett, P.J. Fleming and D.V.S. Green, Combinatorial library design using a multiobjective genetic algorithm, Journal of Chemical Information and Computer Sciences42(2) (2002) 375-85.
175.
T.I. Oprea , Property distribution of drug-related chemical databases, Journal of Computer-Aided Molecular Design14(3) (2000) 251-64.
176.
M.M. Hann, A.R. Leach and G. Harper, Molecular complexity and its impact on the probability of finding leads for drug discovery, Journal of Chemical Information and Computer Sciences41(3) (2001) 856-64.
177.
T.I. Oprea, A.M. Davis, S.J. Teague and P.D. Leeson, Is there a difference between leads and drugs? A historical perspective , Journal of Chemical Information and Computer Sciences41(5) (2001) 1308-15.
178.
Ajay, W.P. Walters and M.A. Murcko, Can we learn to distinguish between `drug-like' and `nondrug-like' molecules?, Journal of Medicinal Chemistry41(18) ( 1998) 3314-24.
179.
J. Sadowski and H. Kubinyi, A scoring scheme for discriminating between drugs and nondrugs, Journal of Medicinal Chemistry41(18) ( 1998) 3325-29.
180.
V.J. Gillet , P. Willett and J. Bradshaw, Identification of biological activity profiles using substructural analysis and genetic algorithms, Journal of Chemical Information and Computer Sciences38(2) (1998) 165-79.
181.
E.D. Clarke and J.S. Delaney, Physical and molecular properties of agrochemicals: an analysis of screen inputs, hits, leads, and products , Chimia57(11) (2003) 731-4.
182.
B.B. Goldman and W.P. Walters, Machine learning in computational chemistry , Annual Reports in Computational Chemistry2 (2006) 127-40.
183.
D.E. Clark , Computational prediction of ADMET properties: recent developments and future changes, Annual Reports in Computational Chemistry1 (2005 ) 133-51.
