Hybridized particle swarm algorithm for adaptive structure training of multilayer feed‐forward neural network: QSAR studies of bioactivity of organic compounds

The multilayer feed‐forward ANN is an important modeling technique used in QSAR studying. The training of ANN is usually carried out only to optimize the weights of the neural network and without paying attention to the network topology. Some other strategies used to train ANN are, first, to discover an optimum structure of the network, and then to find weights for an already defined structure. These methods tend to converge to local optima, and may also lead to overfitting. In this article, a hybridized particle swarm optimization (PSO) approach was applied to the neural network structure training (HPSONN). The continuous version of PSO was used for the weight training of ANN, and the modified discrete PSO was applied to find appropriate the network architecture. The network structure and connectivity are trained simultaneously. The two versions of PSO can jointly search the global optimal ANN architecture and weights. A new objective function is formulated to determine the appropriate network architecture and optimum value of the weights. The proposed HPSONN algorithm was used to predict carcinogenic potency of aromatic amines and biological activity of a series of distamycin and distamycin‐like derivatives. The results were compared to those obtained by PSO and GA training in which the network architecture was kept fixed. The comparison demonstrated that the HPSONN is a useful tool for training ANN, which converges quickly towards the optimal position, and can avoid overfitting in some extent. © 2004 Wiley Periodicals, Inc. J Comput Chem 25: 1726–1735, 2004

[1]  D. B. Hibbert Genetic algorithms in chemistry , 1993 .

[2]  R Benigni,et al.  Quantitative structure-activity relationships of mutagenic and carcinogenic aromatic amines. , 2000, Chemical reviews.

[3]  Guo-Li Shen,et al.  Genetic training of network using chaos concept: Application to QSAR studies of vibration modes of tetrahedral halides , 2002, J. Comput. Chem..

[4]  Laura Capolongo,et al.  Novel phenyl nitrogen mustard and half-mustard derivatives of amidino-modified distamycin , 1997 .

[5]  Lemont B. Kier,et al.  The electrotopological state: structure information at the atomic level for molecular graphs , 1991, J. Chem. Inf. Comput. Sci..

[6]  B. Lavine,et al.  Genetic Algorithms in Analytical Chemistry , 1999 .

[7]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[8]  P. Cozzi,et al.  A new class of cytotoxic DNA minor groove binders: alpha-halogenoacrylic derivatives of pyrrolecarbamoyl oligomers. , 2001, Farmaco.

[9]  Maurice Clerc,et al.  The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..

[10]  Lemont B. Kier,et al.  Electrotopological State Indices for Atom Types: A Novel Combination of Electronic, Topological, and Valence State Information , 1995, J. Chem. Inf. Comput. Sci..

[11]  Arup K. Ghose,et al.  Atomic physicochemical parameters for three dimensional structure directed quantitative structure-activity relationships. 4. Additional parameters for hydrophobic and dispersive interactions and their application for an automated superposition of certain naturally occurring nucleoside antibiotics , 1989, J. Chem. Inf. Comput. Sci..

[12]  Larry J. Eshelman,et al.  Preventing Premature Convergence in Genetic Algorithms by Preventing Incest , 1991, ICGA.

[13]  Roberto Gambari,et al.  Synthesis and growth inhibition activity of alpha-bromoacrylic heterocyclic and benzoheterocyclic derivatives of distamycin A modified on the amidino moiety. , 2003, Bioorganic & medicinal chemistry.

[14]  Daniel Svozil,et al.  Introduction to multi-layer feed-forward neural networks , 1997 .

[15]  James L. McClelland,et al.  James L. McClelland, David Rumelhart and the PDP Research Group, Parallel distributed processing: explorations in the microstructure of cognition . Vol. 1. Foundations . Vol. 2. Psychological and biological models . Cambridge MA: M.I.T. Press, 1987. , 1989, Journal of Child Language.

[16]  G. Spalluto,et al.  Novel benzoyl nitrogen mustard derivatives of pyrazole analogues of distamycin A: synthesis and antileukemic activity. , 1999, Bioorganic & medicinal chemistry.

[17]  Laura Capolongo,et al.  Novel phenyl nitrogen mustard and half-mustard derivatives of distamycin A , 1997 .