Molecular Structure Disassembly Program (MOSDAP): A chemical information model to automate structure-based physical property estimation

Journal of Chemical Information and Computer Sciences

Volumn 39, Issue 3, 1999, Pages 463-474

  Raymond, John W ^a   Rogers, Tony N ^b  

^a UNIVERSITY OF MICHIGAN   (United States)

^b Michigan Technological University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SOFTWARE; INFORMATION THEORY; MOLECULAR STRUCTURE;

LEXICOGRAPHY; SOFTWARE PACKAGE MOLECULAR STRUCTURE DISASSEMBLY PROGRAM (MOSDAP);

ONLINE SEARCHING;

EID: 0032642258     PISSN: 00952338     EISSN: None     Source Type: Journal    
DOI: 10.1021/ci9803334     Document Type: Article

References (104)

1. Chemical Abstract Services (CAS), Columbus, OH, 1998. 〈http:// www.cas.org/〉.
2. Benson, S. W. Thermochemical Kinetics; Wiley: New York, 1968; Chapter 2.
3. ChemDraw, Cambridge Soft Corporation, Cambridge, MA, 1998. 〈http://products.camsoft.com/chemdraw〉.
4. Howard, P. H.; Boethling, R. S.; Stiteler, W. M.; Meylan, W. M.; Hueber, A. E.; Beauman, J. A.; Larosche, M. E. Predictive Model for Aerobic Biodegradability Developed from a File of Evaluated Biodegradation Data. Environ. Toxicol. Chem. 1992, 11, 593-603.
5. Lyman, W. J.; Reehl, W. F.; Rosenblatt, D. H. Handbook of Chemical Property Estimation Methods; American Chemical Society: Washington, DC, 1990.
6. Reid, C. R.; Prausnitz, J. M.; Poling, B. E. The Properties of Gases & Liquids; McGraw-Hill: New York, 1987.
7. Rogers, T. N.; Mullins, M. E.; Kline, A. Environmental, Safety, and Health Data Estimation Technical Support Documents; Project 912 Sponsor Release, July 1995; Design Institute for Physical Property Data (DIPPR); American Institute for Chemical Engineers (AICHE).
8. Jochum, C.; Hicks, M. G.; Sunkel, J. Physical Property Prediction in Organic Chemistry; Springer-Verlag: Berlin, 1988.
9. Baum, E. J. Chemical Property Estimation: Theory and Application; Lewis Publishers: Boca Raton, FL, 1998.
10. Fredenslund, A.; Jones, R. L.; Prausnitz, J. M. Group-Contribution Estimation of Activity Coefficients in Nonideal Liquid Mixtures. AICHE J. 1975, 21, 1086-1099.
11. Pintar, A. J. Estimation of Autoignition Temperature. Technical Support Document; Project 912, July 1996; Design Institute for Physical Property Data (DIPPR); American Institute for Chemical Engineers (AICHE).
12. Brasie, W. C.; Liou, D. W. Estimating Physical Properties: Chemical Structure Coding. Chem. Eng. Prog. 1965, 61, 102-108.
13. Jochelson, N.; Mohr, C. M.; Reid, R. C. The Automation of Structural Group Contribution Methods in the Estimation of Physical Properties. J. Chem. Doc. 1968, 8, 113-122.
14. Smith, E. G. Wiswesser Line-Formula Chemical Notation Methods; McGraw-Hill: New York, 1968.
15. Sussenguth, E. H. A Graph-Theoretic Algorithm for Matching Chemical Structures. J. Chem. Doc. 1965, 6, 36-43.
16. Barnard, J. M. Substructure Searching Methods: Old & New. J. Chem. Inf. Comput. Sci. 1993, 33, 532-538.
17. Ming, T.; Tauber, S. J. Chemical Structure and Substructure Search by Set Reduction. J. Chem. Doc. 1971, 11, 47-51.
18. Adams, J. T.; So, E. M. Automation of Group-Contribution Techniques for Estimation of Thermophysical Properties. Comput. Comput. Eng. 1985, 9, 269-284.
19. Qu, D.; Su, J.; Muraki, M.; Hayakawa, T. A Decoding System for a Group Contribution Method. J. Chem. Inf. Comput. Sci. 1992, 32, 448-452.
20. Drefahl, A.; Reinhard, M. Similarity-Based and Evaluation of Environmentally Relevant Properties for Organic Compounds in Combination with the Group Contribution Approach. J. Chem. Inf. Sci. 1993, 33, 886-895.
21. Figueras, J. Substructure Search by Set Reduction. J. Chem. Doc. 1972, 12, 237-246.
22. Qu, D.; Fu, B.; Muraki, M.; Hayakawa, T. An Encoding System for a Group Contribution Method. J. Chem. Inf. Comput. Sci. 1992, 32, 443-447.
23. Weinenger, D. SMILES, a Chemical Language and Information System. 1. Introduction to Methodology and Encoding Rules. J. Chem. Inf. Comput. Sci. 1988, 28, 31-36.
24. Weinenger, D.; Weinenger, A.; Weinenger, J. L. SMILES. 2. Algorithm for Generation of Unique SMILES Notation. J. Chem. Inf. Comput. Sci. 1989, 29, 97-101.
25. Smiles Tutorial, Daylight Chemical Services, 1998. 〈http://www. daylight.com/dayhtml/smiles∼intro.htm〉.
26. Willett, P.; Winterman, V. A. Algorithms for the Calculation of Similarity in Chemical Structure Databases. In Concepts and Applications of Molecular Similarity; Johnson, M. A., Maggiore, G. M., Eds.; Wiley: New York, 1990.
27. Brint, A. T.; Willett, P. Algorithms for the Identification of Three-Dimensional Maximal Common Substructures. J. Chem. Inf. Comput. Sci. 1987, 27, 152-158.
28. PC UNIFAC, BrisSoftware, Atlanta, GA.
29. Estimation Program Interface, Syracuse Research Corporation, North Syracuse, NY, 1998. 〈http://esc.syrres.com/~escl/estsoft.htm〉.
30. Cranium, Molecular Knowledge Systems; New Bedford, NH, 1998. 〈http://www.molknow.com/cranium.htm〉.
31. GCDATA, ProSim, Toulouse, France, 1996.
32. GC-Estimate, Novel Advanced Systems Corp; Ann Arbor, MI.
33. PREDICT, Dragon Technology, Inc.; Golden, CO, 1998. 〈http:// www.mwsoftware.com/dragon〉.
34. Linert, W.; Margl, P.; Nusterer, E. The Use of Enhanced Operator-Machine Interfaces in Computer Aided Molecular Design. Comput. Chem. 1991, 15, 1-10.
35. Muller, C.; Scacchi, G.; Come, G. A Compiler for a Linear Chemical Notation. Computers Chem. 1991, 15, 337-342.
36. Leung, K.; Chau, F.; Kwok, P.; Lau, W. ChemISTools: A Computer Software for Chemical Information Systems. Comput. Chem. 1997, 21, 161-166.
37. Ash, J. E.; Hyde, E. Chemical Information System; Ellis Horwood: New York, 1975.
38. Davis, C. H.; Rush, I. E. Information Retrieval and Documentation in Chemistry; Greenwood Press: London, 1974.
39. Ash, S.; Cline, M. A.; Homer, R. W.; Hurst, T.; Smith, G. B. SYBYL Line Notation (SLN): A Versatile Language for Chemical Structure Representation. J. Chem. Inf. Comput. Sci. 1997, 37, 71-79.
40. Tonnelier, C. A.; Fox, J.; Judson, P.; Krause, P.; Pappas, N.; Patel, M. Representation of Chemical Structures in Knowledge-Based Systems: The StAR System. J. Chem. Inf. Comput. Sci. 1997, 37, 117-123.
41. Karabunarliev, S.; Ivanov, J.; Mekenyan, O. Coding of Chemical Structures Based on a Line Notation. Comput. Chem. 1994, 18, 189-193.
42. Franklin, J. L. Prediction of Heat and Free Energies of Organic Compounds. Ind. Eng. Chem. 1949, 41, 1070-1076.
43. Franklin, J. L. Calculation of the Heats of Formation of Gaseous Free Radicals. J. Chem. Phys. 1953, 21, 2029-2033.
44. Joback, K. A Unified Approach to Physical Property Estimation Using Multivariate Statisitical Techniques. MS Thesis, Massachesetts Institute of Technology (MIT), Cambridge, MA, June 1982.
45. Database of SMILES Notations, Syracuse Research Corporation, North Syracuse, NY, 1998. 〈http://esc.syrres.com/~escl/database.htm〉.
46. Feldman, A.; Hodes, L. An Efficient Design for Chemical Structure Searching. I. The Screens. J. Chem. Inf. Comput. Sci. 1975, 15, 147-152.
47. Downs, G. M.; Barnard, J. M. Techniques for Generating Descriptive Fingerprints in Combinatorial Libraries. J. Chem. Inf. Comput. Sci. 1997, 37, 59-61.
48. Akutsu, T.; Bao, F. Approximating Minimum Keys and Optimal Substructure Screens. Computing and Combinatorics. Second Annual International Conference (COCOON), Hong Kong, June 1996.
49. Willett, P. A Screen Set Generation Algorithm. J. Chem. Inf. Comput. Sci. 1979, 19, 159-162.
50. Adamson, G. W.; Clinch, V. A.; Creasey, S. E.; Lynch, M. F. Distributions of Fragment Representations in a Chemical Substructure Search Screening System. J. Chem. Doc. 1974, 14, 72-74.
51. Adamson, G. W.; Bush, J. A.; McLure, A.; Lynch, M. F. An Evaluation of a Substructure Search Screen System Based on Bond-Centered Fragments. J. Chem. Doc. 1974, 14, 44-48.
52. Adamson, G. W.; Lambourne, D. R.; Lynch, M. F. Analysis of Structural Characteristics of Chemical Compounds in a Large Computer-Based File. Part III. Statistical Association of Fragment Incidence, J. Chem. Soc., Perkin Trans. 1 1972, 2428-2433.
53. Welford, S. M.; Lynch, M. F.; Barnard, J. M. Computer Storage and Retrieval of Generic Chemical Structures in Patents.5.Algorithmic Generation of Fragment Descriptors for Generic Structure Screening. J. Chem. Inf. Comput. Sci. 1984, 24, 57-66.
54. Tremblay, J. P.; Sorenson, P. G. Introduction to Data Structures with Applications; McGraw-Hill: New York, 1984.
55. Figueras, J. Ring Perception Using Breadth-First Search. J. Chem. Inf. Comput. Sci. 1996, 36, 986-991.
56. Bauerschmidt, S.; Gasteiger, J. Overcoming the Limitations of a Connection Table Description: A Universal Representation of Chemical Species. J. Chem. Inf. Comput. Sci. 1997, 37, 705-714.
57. Willett, P. A Review of Chemical Structure Retrieval System. J. Chemometrics 1987, 1, 139-155.
58. Gaurilov, D.; Vinogradov, O. Object-Oriented Programming and Object-Oriented Simulation. Proceedings of the SCSC, Ottawa, Canada, 1995.
59. Hansen, H. K. Vapor-Liquid Equilibria by UNIFAC Group Contribution. 5. Revision and Extension. Ind. Eng. Chem. Res. 1991, 10, 2352-2355.
60. Read, R. C. Graph Theory and Computing; Academic Press: New York, 1972; pp 267-283.
61. Downs, G.; Gillet, V.; Holliday, J.; Lynch, M. Theoretical Aspects of Ring Perception and Development of the Extended Set of Smallest Rings Concept. J. Chem. Inf. Comput. Sci. 1989, 29, 187-206.
62. Downs, G.; Gillet, V.; Holliday, J.; Lynch, M. Review of Ring Perception Algorithms for Chemical Graphs. J. Chem. Inf. Comput. Sci. 1989, 29, 172-187.
63. Fan, T.; Panaye, A.; Doucet, J.; Barbu, A. Ring Perception. A New Algorithm for Directly Finding the Smallest Set of Smallest Rings from a Connection Table. J. Chem. Inf. Comput. Sci. 1993, 33, 657-662.
64. Balducci, R.; Pearlman, R. Efficient Exact Solution of the Ring Perception Problem. J. Chem. Inf. Comput. Sci. 1994, 34, 822-831.
65. Stobaugh, R. E. Chemical Substructure Searching. J. Chem. Inf. Comput. Sci. 1985, 25, 71-275.
66. Barnard, J. M. Problems of Substructure Search and Their Solution. In Chemical Structures; Warr, W., Ed.; Springer-Verlag: Berlin, 1988.
67. Willett, P. Processing of Three-Dimensional Chemical Structure Information Using Graph-Theoretic Techniques. Online Information 90; London, 1990; pp 115-127.
68. Brown, R. D.; Jones, G.; Willett, P. Matching Two-Dimensional Chemical Graphs Using Genetic Algorithms. J. Chem. Inf. Comput. Sci. 1994, 34, 63-70.
69. Dengler, A.; Ugi, I. A Central Atom Based Algorithm and Computer Program for Substructure Search. Comput. Chem. 1991, 15, 103-107.
70. Jun, X.; Maosen, Z. HBA: New Algorithm for Structural Match and Applications. Tetrahedron Comput. Methodol. 1989, 2, 75-83.
71. Von Scholley, A. A Relaxation Algorithm for Generic Chemical Structure Searching. J. Chem. Inf. Comput. Sci. 1984, 24, 235-241.
72. Wang, Y. K.; Fan, K. C. Adaptive Optimization for Solving a Class of Subgraph Isomorphism Problems. IEEE 1995, 44-49.
73. Ozawa, K.; Yasud, T.; Fujita, S. Substructure Search with Tree-Structured Data. J. Chem. Inf. Comput. Sci. 1997, 37, 688-695.
74. Xiao, Y.; Qiao, Y.; Zhang, J.; Lin, S.; Zhang, W. A Method for Substructure Search by Atom-Centered Multilayer Code. J. Chem. Inf. Comput. Sci. 1997, 37, 701.
75. Lesk, A. Detection of 3-D Patterns of Atoms in Chemical Structures. Commun. ACM 1979, 22, 219-224.
76. Ullman, J. R. An Algorithm for Subgraph Isomorphism. J. Assoc. Comput. Mach. 1976, 23, 31-42.
77. Brint, A.; Mitchell, E.; Willet, P. Substructure Searching in Files of Three of Dimensional Chemical Structures. In Chemical Structures; Warr, W., Ed.; Springer-Verlag: Berlin, 1988.
78. Artymiuk, P. J.; MacKenzie, A. B.; Grindley, H. M.; Poirette, A. R.; Rice, D. W.; Ujah, E. C.; Willet, P. Representation and Searching of Three-Dimensional Protein Structures Using Graph Theory: Part 5. Chem. Des. Aut. News 1994, 6-17.
79. Sheridan, R. P.; Nilakantan, R.; Rusinko, A.; Bauman, N.; Haraki, K. S.; Venkataraghavan, R. 3DSEARCH: A System for Three-Dimensional Substructure Searching. J. Chem. Inf. Comput. Sci. 1989, 29, 255-260.
80. Wang, T.; Zhou, J. 3DFS: A New 3D Flexible Searching System for Use in Drug Design. J. Chem. Inf. Comput. Sci. 1998, 38, 71-77.
81. Clark, D. E.; Murray, C. W. PRO_LIGAND: An Approach to de Novo Molecular Design. 5. Tools for the Analysis of Generated Structures. J. Chem. Inf. Comput. Sci. 1995, 35, 914-923.
82. Brint, A. T.; Willett, P. Pharmacophoric Pattern Matching in Files of 3D Chemical Structures: Comparison of Geometric Searching Algorithms. J. Mol. Graph. 1987, 5, 49-56.
83. Downs, G. M.; Lynch, M. F.; Willett, P.; Manson, G. A.; Wilson, G. A. Transputer Implementations of Chemical Substructure Searching Algorithms. Tetrahedron Comput. Methodol. 1988, 1, 207-217.
84. Holliday, J. D.; Lynch, M. F. Computer Storage and Retrieval of Generic Chemical Structures in Patents. 16. The Refined Search: An Algorithm for Matching Components of Generic Chemical Structures at the Atom-Bond Level. J. Chem. Inf. Comput. Sci. 1995, 35, 1-7.
85. Mitchell, E. M.; Artymiuk, P. J.; Rice, D. W.; Willett, P. Use of Techniques Derived from Graph Theory to Compare Secondary Structure Motifs in Proteins. J. Mol. Biol. 1989, 212, 151-166.
86. Artymiuk, P. J., Grindley, H. M.; Poirette, A. R.; Rice, D. W.; Ujah, E. C.; Willett, P. Identification of β-Sheet Motifs, of Ψ-Loops, and of Patterns of Amino Acid Residues in Three-Dimensional Protein Structures Using a Subgraph-Isomorphism Algorithm. J. Chem. Inf. Sci. 1994, 34, 54-62.
87. Willett, P.; Wilson, T. Atom-by-Atom Searching Using Massive Parallelism. Implementation of the Ullman Subgraph Isomorphism Algorithm on the Distributed Array Processor. J. Chem. Inf. Sci. 1991, 31, 225-233.
88. Bone, R. G.; Villar, H. O. Exhaustive Enumeration of Molecular Substructures. J. Comput. Chem. 1997, 18, 86-107.
89. Hurst, T. Flexible 3D Searching: The Directed Tweak Technique. J. Chem. Inf. Comput. Sci. 1994, 34, 190-196.
90. Mathematical Challenges from Theoretical/Computational Chemistry; National Research Council; National Academy Press: Washington, DC, 1995.
91. Swamy, M. N. S.; Thulasiraman, K. Graphs, Networks, and Algorithms; Wiley: New York, 1981; pp 536-538.
92. Foulds, L. R. Graph Theory Applications; Springer-Verlag: Berlin, 1992; pp 123-124.
93. Balas, E.; Samuelson, H. A Node Covering Algorithm. Naval Res. Log. Quart. 1977, 24, 213-233.
94. Harche, F.; Thompson, G. The Column Subtraction Algorithm: An Exact Method for Solving Weighted Set Covering, Packing, and Partitioning Problems. Comput. Ops. Res. 1994, 21, 689-705.
95. Beasely, J. An Algorithm for Set Covering Problem. Eur. J. Oper. Res. 1987, 31, 85-93.
96. Beasely, J.; Jornsten, K. Enhancing an Algorithm for Set Covering Problems. Eur. J. Oper. Res. 1992, 58, 293-300.
97. Bertolazzi, P.; Sassano, A. An O(mn) Algorithm for Regular Set-Covering Problems. Theor. Comput. Sci. 1987, 54, 237-247.
98. Baker, E. Efficient Heuristic Algorithms for the Weighted Set Covering Problem. Comput. Oper. Res. 1981, 8, 303-310.
99. Frenz, T. C.; Kreher, D. L. An Algorithm for Enumerating Distinct Cyclic Steiner Systems. J. Combin. Math. Combin. Comput. 1992, 11, 23-32.
100. Kreher, D. L.; Stinson, D. R. Combinatorial Algorithms: Generation, Enumeration and Search. CRC Press: Boca Raton, FL, 1998.
101. Rogers, T.; Kline, A.; Miller, M.; Wieber, D.; Mullins, M. ENVIRON 2001, Environmental, Safety, and Health Data and Estimates for the 21st Century; Project 911, Sponsor Release, March 1999; Design Institute for Physical Property Data (DIPPR); American Institute of Chemical Engineers (AICHE): New York.
102. Data Expert, Epcon International, Houston, TX, 1998. 〈http:// www.epcon.com〉.
103. Mavrovouniou's, M. L.; Pricket, S.; Constantinov, L. Object-Oriented Estimation of Properties from Molecular Structure. European Symposium on Computer Aided Process Engineering-1, S353-S360.
104. SMARTS, Daylight Chemical Services. 1998. 〈http://vww. daylight.com/products/smarts_kit.html〉.