Abstract
The linear notations are more compact than connection tables so they can be useful for storing and transmitting large number of chemical structures. Implicitly they contain the information needed to compute all kinds of molecular structures and, thus, molecular properties derived from these structures. In this DOSM is a new method of obtaining a rough description of 2D molecular structure from its 2D connection graph in the form of character string. Our method is based on the fragmentation of DOSM strings into overlapping substrings of a defined size that we call LINGO-DOSM. The integral set of LINGO-DOSM derived from a given DOSM string, LINGO-DOSM allows rigorous structure specification using very small and simple rule. In this paper, we study the possibility of using the textual descriptor for describing the 2D structure of the molecule. Simulated virtual screening experiments with the MDDR database show clearly the superiority of the LINGO-DOSM descriptor compared to many standard descriptors tested in this paper.
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References
Agrafiotis, D.K., Myslik, J.C., Salemme, F.R.: Advances in diversity profiling and combinatorial series design. Mol. Diversity 4, 1–22 (1999)
Jorgensen, W.L.: The many roles of computation in drug discovery. Science 303 (2004)
Flower, D.R.: On the properties of bit-string-based measures of chemical similarity. J. Chem. Inf. Comput. Sci. 38, 379–386 (1998)
Willett, P., Barnard, J.M., Downs, G.M.: Chemical similarity searching. J. Chem. Inf. Comput. Sci. 38, 983–996 (1998)
Brown, R.D.: Descriptors for Diversity Analysis. Perspect. Drug. Discovery Des. 7/8, 31–49 (1997)
David, V., Michael, T., Miquel, P.: LINGO, an Efficient Holographic Text Based Method To Calculate Biophysical Properties and Intermolecular Similarities. J. Chem. Inf. Model. 45, 386–393 (2005)
UNITY Reference Manual, Tripos Inc., St. Louis, MO (1995)
Winkler, D.A., Burden, F.R.: Holographic QSAR of benzodiazepine. Quant. Struct.-Act. Relat. 17, 224–231 (1998)
Leach, A.R., Gillet, V.J.: An Introduction to Chemoinformatics. Kluwer, Dordrecht (2003)
Wild, D.J., Willett, P.: Similarity Searching in Files of Three-Dimensional Chemical Structures. Alignment of Molecular Electrostatic Potential Fields with a Genetic Algorithm. J. Chem. Inf. Comput. Sci. 36, 159–167 (1996)
Kirchmair, J., Distinto, S., Markt, P., Schuster, D., Spitzer, G.M., Liedl, K.R., Wolber, G.: How To Optimize Shape-Based Virtual Screening: Choosing the Right Query and Including Chemical Information. J. Chem. Inf. Model. 49, 678–692 (2009)
Rush, T.S., Grant, J.A., Mosyak, L., Nicholls, A.: A Shape-Based 3-D Scaffold Hopping Method and Its Application to a Bacterial Protein−Protein Interaction. J. Med. Chem. 48, 1489–1495 (2005)
Warr, W.A.: Representation of chemical structures. Wiley Interdisciplinary Reviews: Computational Molecular Science 1, 557–579 (2011)
Hall, L.H., Kier, L.B.: Issues in representation of molecular structure: The development of molecular connectivity. J. Mol. Graph. 20, 4–18 (2001)
Kogej, T., Engkvist, O., Blomberg, N., Muresan, S.: Multifingerprint Based Similarity Searches for Targeted Class Compound Selection. J. Chem. Inf. Model. 46, 1201–1213 (2006)
Weininger, D.: SMILES, A chemical language and information system. 1. Introduction to methodology and encoding rules. J. Chem. Inf. Comp. Sci. 28, 31–36 (1988)
SciTegicAccelrys Inc.
Yap, C.W.: PaDEL-descriptor: An open source software to calculate molecular descriptors and fingerprints. J. Comput. Chem. 32, 1466–1474 (2011)
Abdo, A., Chen, B., Mueller, C., Salim, N., Willett, P.: Ligand-Based Virtual Screening Using Bayesian Networks. J. Chem. Inf. Model. 50, 1012–1020 (2010)
Altschul, S.F., Madden, T.L., Schäffer, A.A., Zhang, J., Zhang, Z., Miller, W., Lipman, D.J.: Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25, 3389–3402 (1997)
Brown, R.D., Martin, Y.C.: Use of Structure-Activity Data To Compare Structure-Based Clustering Methods and Descriptors for Use in Compound Selection. J. Chem. Inf. Comput. Sci. 36, 572–584 (1996)
Siegel, S., Castellan, N.J.: Nonparametric Statistics for The Behavioral Sciences. McGraw-Hill, New York (1988)
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Hentabli, H., Salim, N., Abdo, A., Saeed, F. (2013). LINGO-DOSM: LINGO for Descriptors of Outline Shape of Molecules. In: Selamat, A., Nguyen, N.T., Haron, H. (eds) Intelligent Information and Database Systems. ACIIDS 2013. Lecture Notes in Computer Science(), vol 7803. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36543-0_33
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DOI: https://doi.org/10.1007/978-3-642-36543-0_33
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