S. Caboche, M. Pupin, V. Leclère, A. Fontaine, P. Jacques et al., NORINE: a database of nonribosomal peptides, Nucleic Acids Research, vol.36, issue.Database, pp.326-331, 2008.
DOI : 10.1093/nar/gkm792
URL : https://hal.archives-ouvertes.fr/inria-00281012

S. Sen, J. Young, J. Berrisford, M. Chen, M. Conroy et al., Small molecule annotation for the Protein Data Bank, Database, vol.2014, issue.0, p.116, 2014.
DOI : 10.1093/database/bau116

S. Dutta, D. Dimitropoulos, Z. Feng, I. Persikova, S. Sen et al., Improving the representation of peptide-like inhibitor and antibiotic molecules in the Protein Data Bank, Biopolymers, vol.36, issue.6, pp.659-668, 2014.
DOI : 10.1002/bip.22434

S. Caboche, M. Pupin, V. Leclère, P. Jacques, and G. Kucherov, Structural pattern matching of nonribosomal peptides, BMC Structural Biology, vol.9, issue.1, p.15, 2009.
DOI : 10.1186/1472-6807-9-15
URL : https://hal.archives-ouvertes.fr/hal-00641486

A. Abdo, V. Leclère, P. Jacques, N. Salim, and M. Pupin, Prediction of New Bioactive Molecules using a Bayesian Belief Network, Journal of Chemical Information and Modeling, vol.54, issue.1, pp.30-36, 2014.
DOI : 10.1021/ci4004909
URL : https://hal.archives-ouvertes.fr/hal-01090611

P. Willet, Similarity Searching Using 2D Structural Fingerprints, Methods Mol Biol, vol.672, pp.133-158, 2011.
DOI : 10.1007/978-1-60761-839-3_5

K. Myint and X. Xie, Recent Advances in Fragment-Based QSAR and Multi-Dimensional QSAR Methods, International Journal of Molecular Sciences, vol.11, issue.10, pp.3846-3866, 2010.
DOI : 10.3390/ijms11103846

A. Cherkasov, E. Muratov, D. Fourches, A. Varnek, I. Baskin et al., QSAR Modeling: Where Have You Been? Where Are You Going To?, Journal of Medicinal Chemistry, vol.57, issue.12, pp.4977-5010, 2014.
DOI : 10.1021/jm4004285
URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4074254

O. Donnell, T. Rao, S. Koehler, K. Martin, Y. Eccles et al., A general approach for atom-type assignment and the interconversion of molecular structure files, Journal of Computational Chemistry, vol.108, issue.2, pp.209-214, 1991.
DOI : 10.1002/jcc.540120210

M. Siani, D. Weininger, and J. Blaney, CHUCKLES: A method for representing and searching peptide and peptoid sequences on both monomer and atomic levels, Journal of Chemical Information and Modeling, vol.34, issue.3, pp.588-593, 1994.
DOI : 10.1021/ci00019a017

X. Lewell, D. Judd, S. Watson, and M. Hann, RECAPRetrosynthetic Combinatorial Analysis Procedure:??? A Powerful New Technique for Identifying Privileged Molecular Fragments with Useful Applications in Combinatorial Chemistry, Journal of Chemical Information and Computer Sciences, vol.38, issue.3, pp.511-522, 1998.
DOI : 10.1021/ci970429i

J. Degen, C. Wegscheid-gerlach, A. Zaliani, and M. Rarey, On the Art of Compiling and Using 'Drug-Like' Chemical Fragment Spaces, ChemMedChem, vol.38, issue.10, pp.1503-1507, 2008.
DOI : 10.1002/cmdc.200800178

D. Ghersi and M. Singh, molBLOCKS: decomposing small molecule sets and uncovering enriched fragments, Bioinformatics, vol.30, issue.14, pp.2081-2083, 2014.
DOI : 10.1093/bioinformatics/btu173

H. Chen, X. Zhou, A. Wang, Y. Zheng, Y. Gao et al., Evolutions in fragment-based drug design: the deconstruction???reconstruction approach, Drug Discovery Today, vol.20, issue.1, pp.105-113, 2015.
DOI : 10.1016/j.drudis.2014.09.015

M. Garey and D. Johnson, Computers and intractability: a guide to the theory of NP-completeness, 1979.

J. Ullmann, An Algorithm for Subgraph Isomorphism, Journal of the ACM, vol.23, issue.1, pp.31-42, 1976.
DOI : 10.1145/321921.321925

J. Raymond and P. Willett, Maximum common subgraph isomorphism algorithms for the matching of chemical structures, Journal of Computer-Aided Molecular Design, vol.16, issue.7, pp.521-533, 2002.
DOI : 10.1023/A:1021271615909

G. Mani?, L. Bahiense, and C. De-souza, A branch&cut algorithm for the maximum common edge subgraph problem, Electronic Notes in Discrete Mathematics, vol.35, pp.47-52, 2009.
DOI : 10.1016/j.endm.2009.11.009

T. Kawabata, Build-Up Algorithm for Atomic Correspondence between Chemical Structures, Journal of Chemical Information and Modeling, vol.51, issue.8, pp.1775-1787, 2011.
DOI : 10.1021/ci2001023

S. Hashemifar and J. Xu, HubAlign: an accurate and efficient method for global alignment of protein-protein interaction networks, Bioinformatics, vol.30, issue.17, pp.438-444, 2014.
DOI : 10.1093/bioinformatics/btu450

S. Rahman, M. Bashton, G. Holliday, R. Schrader, and J. Thornton, Small Molecule Subgraph Detector (SMSD) toolkit, Journal of Cheminformatics, vol.1, issue.1, p.12, 2009.
DOI : 10.1186/1758-2946-1-12

H. Ehrlich and M. Rarey, Maximum common subgraph isomorphism algorithms and their applications in molecular science: a review, Wiley Interdisciplinary Reviews: Computational Molecular Science, vol.56, issue.1, pp.68-79, 2011.
DOI : 10.1002/wcms.5

E. Krissinel and K. Henrick, Common subgraph isomorphism detection by backtracking search, Software: Practice and Experience, vol.34, issue.6, pp.591-607, 2004.
DOI : 10.1002/spe.588

D. Eppstein, Subgraph Isomorphism in Planar Graphs and Related Problems, Journal of Graph Algorithms and Applications, vol.3, issue.3, pp.1-27, 1999.
DOI : 10.7155/jgaa.00014

C. Steinbeck, Y. Han, S. Kuhn, O. Horlacher, E. Luttmann et al., The Chemistry Development Kit (CDK):??? An Open-Source Java Library for Chemo- and Bioinformatics, Journal of Chemical Information and Computer Sciences, vol.43, issue.2, pp.493-500, 2003.
DOI : 10.1021/ci025584y

O. Boyle, N. Banck, M. James, C. Morley, C. Vandermeersch et al., Open Babel: An open chemical toolbox, Journal of Cheminformatics, vol.3, issue.1, p.33, 2011.
DOI : 10.1093/nar/gkp324

L. Cordella, P. Foggia, C. Sansone, and M. Vento, A (sub)graph isomorphism algorithm for matching large graphs, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.10, pp.1367-1372, 2004.
DOI : 10.1109/TPAMI.2004.75

H. Shang, Y. Zhang, X. Lin, and J. Yu, Taming verification hardness, Proceedings of the VLDB Endowment, vol.1, issue.1, pp.364-375, 2008.
DOI : 10.14778/1453856.1453899

K. Zhu, Y. Zhang, X. Lin, G. Zhu, and W. Wang, NOVA: A Novel and Efficient Framework for Finding Subgraph Isomorphism Mappings in Large Graphs, Database Systems for Advanced Applications, pp.140-154, 2010.
DOI : 10.1007/978-3-642-12026-8_13

P. Pardalos and J. Xue, The maximum clique problem, Journal of Global Optimization, vol.46, issue.1, pp.301-328, 1994.
DOI : 10.1007/BF01098364

E. Bolton, Y. Wang, P. Thiessen, and S. Bryant, Chapter 12?PubChem: Integrated platform of small molecules and biological activities, pp.217-241, 2008.

J. Westbrook, C. Shao, Z. Feng, M. Zhuravleva, S. Valenkar et al., The chemical component dictionary: complete descriptions of constituent molecules in experimentally determined 3D macromolecules in the Protein Data Bank, Bioinformatics, vol.31, issue.8, pp.1274-1278, 2014.
DOI : 10.1093/bioinformatics/btu789

H. Berman, K. Henrick, and H. Nakamura, Announcing the worldwide Protein Data Bank, Nature Structural Biology, vol.10, issue.12, pp.980-980, 2003.
DOI : 10.1038/nsb1203-980

D. Weininger, SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules, Journal of Chemical Information and Modeling, vol.28, issue.1, pp.31-36, 1988.
DOI : 10.1021/ci00057a005

J. Orlin, Line-digraphs, arborescences, and theorems of tutte and knuth, Journal of Combinatorial Theory, Series B, vol.25, issue.2, pp.187-198, 1978.
DOI : 10.1016/0095-8956(78)90038-2