Graph-Based Methods for Rational Drug Design
Author:
Droschinsky AndreORCID, Humbeck LinaORCID, Koch OliverORCID, Kriege Nils M.ORCID, Mutzel PetraORCID, Schäfer TillORCID
Abstract
AbstractRational drug design deals with computational methods to accelerate the development of new drugs. Among other tasks, it is necessary to analyze huge databases of small molecules. Since a direct relationship between the structure of these molecules and their effect (e.g., toxicity) can be assumed in many cases, a wide set of methods is based on the modeling of the molecules as graphs with attributes.Here, we discuss our results concerning structural molecular similarity searches and molecular clustering and put them into the wider context of graph similarity search. In particular, we discuss algorithms for computing graph similarity w.r.t. maximum common subgraphs and their extension to domain specific requirements.
Publisher
Springer Nature Switzerland
Reference58 articles.
1. Ackerman, M., Ben-David, S.: Clusterability: a theoretical study. In: Dyk, D.A.V., Welling, M. (eds.) Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics. JMLR Proceedings, AISTATS 2009, vol. 5, pp. 1–8. JMLR.org, Clearwater Beach, Florida (2009). https://www.jmlr.org/proceedings/papers/v5/ackerman09a.html 2. Aggarwal, C.C., Procopiuc, C.M., Wolf, J.L., Yu, P.S., Park, J.S.: Fast algorithms for projected clustering. In: Delis, A., Faloutsos, C., Ghandeharizadeh, S. (eds.) COMAD, ACM SIGMOD 1999, pp. 61–72. ACM Press, Philadelphia (1999). https://doi.org/10.1145/304182.304188 3. Aggarwal, C.C., Ta, N., Wang, J., Feng, J., Zaki, M.J.: Xproj: a framework for projected structural clustering of xml documents. In: Berkhin, P., Caruana, R., Wu, X. (eds.) Proceedings of the 13th International Conference on Knowledge Discovery and Data Mining, pp. 46–55. ACM Press, San Jose (2007). https://doi.org/10.1145/1281192.1281201 4. Bento, A.P., et al.: The ChEMBL bioactivity database: an update. Nucleic Acids Res. 42(D1), D1083–D1090 (2013). https://doi.org/10.1093/nar/gkt1031 5. Beyer, K.S., Goldstein, J., Ramakrishnan, R., Shaft, U.: When is “nearest neighbor" meaningful? In: Proceedings of the 7th International Conference on Database Theory, ICDT 1999, pp. 217–235. Springer-Verlag, London (1999). https://doi.org/10.1007/3-540-49257-7_15, https://dl.acm.org/citation.cfm?id=645503.656271
|
|