Maximal-substructure algorithm

The supercomputer could also offer a solution to this problem. An algorithm has been devised which can generate the largest substructures which two compounds have in common (22). It thus can intercompare all of the 15 best-matching compounds to find substructures predicted by STIRS which are not in the 589. This maximal-substructure algorithm is not used routinely, however, because of the extensive computer time required again, the supercomputer could make this feasible. 

Automatic identification of larger substructures with simpler algorithms can be visualized. Substructures from the 589 list identified by STIRS could be used to restrict, and thus speed, the maximal substructure search. Those compounds of the 15 best-matches containing the substructure with the highest reliability... 

A substructure search algorithm is usually the first step in the implementation of other important topological procedures for the analysis of chemical structures such as identification of equivalent atoms, determination of maximal common substructure, ring detection, calculation of topological indices, etc. 

Brint, A.T. and Willett, P. (1987a). Algorithms for the Identification of Three-Dimensional Maximal Common Substructures. J.Chem.Inf.Comput.ScL, 27,152-158. 

Xu, J. (1996) GMA a generic match algorithm for structural homomorphism, isomorphism, and maximal common substructure match and its applications./. Ghem. Inf. Gomput. Sci, 36, 25-34. 

Because of limitations of space, the structure isomorphism problem will not be further discussed. This chapter will focus on the discussion of the major algorithms and methodologies for solving substructure and maximal common substructure problems and their applications. 

Early Work in the Development of Maximal Common Substructure Search Algorithms... 

Chen L, Robien W. MCSS a new algorithm for perception of maximal common substructures and its application to NMR spectral studies. 1. The algorithm. J Chem Inf Comput Sci 1992 32 501-506. 

Tonnelier C, Jauffret P, Hanser T, Kaufmann G. Machine learning of generic reactions 3. An efficient algorithm for maximal common substructure determination. Tetrahedron Comput Methodol 1990 3 351-358. 

Brint AT, Willett P. Algorithms for the identification of three-dimensional maximal common substructures. J Chem Inf Comput Sci 1987 27 152-158. 

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