While finding all the chemical structures that match a given set of physico-chemical analytical data seems to be an intractable computational problem, it is possible to use stochastic techniques to generate a sample of three-dimensional molecular models that is statistically representative of the entire population of potential models.
Performing a structure elucidation using a stochastic approach is similar to studying the conformational space of a molecule using stochastic methods such as Monte Carlo or Genetic Algorithm methods. However, in the case of structure elucidation the search space is no longer composed of the ensemble of all possible conformations, but is composed of the finite number of possible structural isomers that can be constructed from a set of analytical data.
We have demonstrated that by using a stochastic approach, it is possible to generate a sample of three-dimensional molecular models that statistically represents the entire population of all the possible models that can be built from a set of analytical data.
We have also designed a stochastic algorithm based on the simulated annealing method that searches chemical structures with desired properties. Theoretically, the algorithm was shown to be efficient (i.e., polynomial-time). Practically, the algorithm performs remarkably well even in very large search space sizes (up to 1032).
The above sampling techniques are being applied to investigate molecular structures studied in polymer science, biochemistry, geochemistry, fuel, petroleum, and materials sciences. The proposed stochastic techniques appear to be essential tools for anyone who wants to use molecular modeling techniques for structurally unresolved molecular compounds.

Papers

Faulon. J. L..Stochastic Generator of Chemical Structure. 2. Using Simulated Annealing To Search the Space of Constitutional Isomers.J. Chem. Inf. Comput. Sci.1996, 36, 731-740. Abstract (.html). Full paper (.ps.gz).

Faulon, J. L. Unraveling complex molecules. CHEMTECH1995, 25, 16-23.

Faulon. J. L..Stochastic Generator of Chemical Structure. 1. Application to the Structure Elucidation of Large Molecules.J. Chem. Inf. Comput. Sci.1994, 34, 1204-1218. Abstract (.html). Full paper (.ps.gz).

Papers (applications)

Kowaleski I., Vandenbroucke M., Faulon J. L., Taylor J., Behar F., Huc A. (1996). Asphaltene Molecular Modeling of Boscan Crude Oil, Revue de l'I.F.P 51, 161-170.

Kowaleski I., Vandenbroucke M., Taylor J., Faulon J. L., Huc A. (1996). Preliminary Results on Molecular Modeling of Asphaltene using Structure Elucidation Programs in Conjonction with Molecular Simulation Programs, Energy&Fuel 10, 97-107.

Boduszynski, M. M., Faulon J. L. (1996) Molecular Structure Elucidation of Cycloalkyl-coronenes found in Hydrocracked Oils, Proceedings of the Dhahran 1996 Lab. R&D Center Technical Exchange Meeting.

Boduszynski, M. M., Rechsteiner, C. E., Grudoski D. A., Iwamoto J. D., Faulon J. L. (1996) The Effect of Molecular Structure on Molecular Weight - Boiling Point Relationship for Petroleum Fractions, Proceedings of the Dhahran 1996 Lab. R&D Center Technical Exchange Meeting.

Pohl P. I., Faulon J. L., Carlson G. A., Smith D. M. (1996). A Computer Study of the Pore Structure of Imogolite, Lamgmuir, 18, 4463-4468

Faulon J. L., Loy D. A., Carlson G. A., and Shea K. J. (1995). Computer-aided Structure Elucidation for Arylsilsesquioxane Gels, Computational Materials Science 3, 334-346.

Pohl P. I., Faulon J. L., Smith D. M. (1995). Molecular Dynamics Computer Simulations of Silica Aerogels, J. Non Cryst. Solids 186, 349-355.

Faulon J. L., Carlson, G.A., and Hatcher P. G. (1994). A Three-Dimensional Model for Lignocellulose from Gymnospermous Wood, Org. Geochem. 211, 1169-1179.

Faulon, J.L., and Hatcher, P. G. (1994). Is There Any Order in the Structure of Lignin ?, Energy & Fuels 8, 402-407.

Faulon J. L. , Mathews J. P., Carlson G. A., and Hatcher P. G. (1994). Correlation Between Microporosity and Fractal Dimension of Bituminous Coal Based on Computer-Generated Models, Energy & Fuels 8, 408-414.

Faulon J. L. , Carlson G. A., and Hatcher P. G. (1993). Statistical Model for Bituminous Coal: A Three-Dimensional Evaluation of Structural and Physical Properties Based on Computer-Generated Structures, Energy & Fuels 7, 1062-1072.

Faulon J. L., Hatcher P. G. , Carlson, G.A., and Wenzel K. A.(1993). A computer-aided Molecular Model for High Volatile Bituminous Coal, Fuel Processing Technology 34, 277-293.

Hatcher, P. G., Faulon J. L., Clifford D. A., Mathews J. P. (1993) A Three-dimensional Structural Model for Humic Acids from Oxidized Soil. Proccedings of the 6th IHSS Int. Meeting, Elsevier, Amsterdam, 436-446.

Faulon J.L., Vandenbroucke M., Drappier J.M., Behar F., and Romero M. (1990). 3D Chemical Model for Geological Macromolecules, Org. Geochem. 16, 981-993.

While finding all the chemical structures that match a given set of physico-chemical analytical data seems to be an intractable computational problem, it is possible to use stochastic techniques to generate a sample of three-dimensional molecular models that is statistically representative of the entire population of potential models.

Performing a structure elucidation using a stochastic approach is similar to studying the conformational space of a molecule using stochastic methods such as Monte Carlo or Genetic Algorithm methods. However, in the case of structure elucidation the search space is no longer composed of the ensemble of all possible conformations, but is composed of the finite number of possible structural isomers that can be constructed from a set of analytical data.

We have demonstrated that by using a stochastic approach, it is possible to generate a sample of three-dimensional molecular models that statistically represents the entire population of all the possible models that can be built from a set of analytical data.

We have also designed a stochastic algorithm based on the simulated annealing method that searches chemical structures with desired properties. Theoretically, the algorithm was shown to be efficient (i.e., polynomial-time). Practically, the algorithm performs remarkably well even in very large search space sizes (up to 1032).

The above sampling techniques are being applied to investigate molecular structures studied in polymer science, biochemistry, geochemistry, fuel, petroleum, and materials sciences. The proposed stochastic techniques appear to be essential tools for anyone who wants to use molecular modeling techniques for structurally unresolved molecular compounds.

Papers.Stochastic Generator of Chemical Structure. 2. Using Simulated Annealing To Search the Space of Constitutional Isomers.J. Chem. Inf. Comput. Sci.1996, 36,731-740.Abstract (.html). Full paper (.ps.gz).Unraveling complex molecules.CHEMTECH1995,25, 16-23..Stochastic Generator of Chemical Structure. 1. Application to the Structure Elucidation of Large Molecules.J. Chem. Inf. Comput. Sci.1994, 34,1204-1218.Abstract (.html). Full paper (.ps.gz).Papers (applications)JLF 1997