Summary
One of the goals of computational chemists is to automate the de novo design of bioactive molecules. Despite significant advances in computational approaches to ligand design and binding energy evaluation, novel procedures for ligand design are required. Evolutionary computation provides a new approach to this design endeavor. We propose an evolutionary tool for de novo peptide design, based on the evaluation of energies for peptide binding to a user-defined protein surface patch. Special emphasis has been placed on the evaluation of the proposed peptides, leading to two different evaluation heuristics. The software developed was successfully tested on the design of ligands for the proteins prolyl oligopeptidase, p53, and DNA gyrase.
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References
Böhm H.J. (1998). Journal of Computer-Aided Molecular Design 12: 309–323
Kubinyi H. (1999). Journal Receptor and Signal Transduction Research 19: 15–39
Ajay A.,Walters W.P., Murko M.A. (1998). Journal of Medical Chemistry 41: 3314–3324
Zou X., Sun Y., Kuntz I.D. (1999). Journal of American Chemistry Society 121: 8033-1-8043
Apostolakis J., Caflish A. (1999). Combinatorial Chemistry and High Throughput Screening 2: 91–104
Codina A., Gairí M., Tarragó T., Vigueras A.R., Feliz M., Ludevid D., Giralt E. (2002). Jornal of Biomolecular NMR 22: 295–296
Chiva C., Barthe P., Codina A., Gairí M., Molina F., Granier C., Pugniere M., Inui T., Nishi H., Nishiuchi Y., Kimura T., Sakakibara S., Albericio F., Giralt E. (2003). Journal of American Chemistry Society 125: 1508–1517
Thormann M., Pons M. (2001). Journal of Computational Chemistry 22: 1971–1982
Loffet A. (2002). Journal of Peptide Science 8: 1–7
Malmsten M., Surfactants and Polymers in Drug Delivery, Marcel Dekker, 2002
Henry, C.M. and Washinton, E., Chem. Eng. News., 79 (2001) 69–74.
Pinilla C., Appel J.R., Borras E., Houghten R.A. (2003). Nature Medicine 9: 118–122
Jones S., Thornton J.M. (1997). Journal of Molecular Biology 272: 121–132
Holland J.H., Adaptation in Natural and Artificial Systems, University of Michigan Press, 1975
Krasnogor N. (2002). Studies on the Theory and Design Space of Memetic Algorithms. PhD dissertation at University of the West England, Bristol
Baluja S., Caruana, R., Proceedings of the International Conference on Machine Learning, Morgan Kaufmann (1995) 112–128
Pelikan, M., Goldberg, D.E. and Cantú-Paz, E., Proceedings of the Genetic and Evolutionary Computation Conference GECCO-99, Morgan Kaufmann (1999)
Morris G., Goodsell D., Halliday R., Huey R., Belew R., Olson A. (1998). Journal of Computational Chemistry 19: 1639–1662
Moon J.B., Howe J.W. (1991). Proteins: Structure, Function and Genetics 11: 314–328
Gillet V.J., Newell W., Mata P., Myatt G., Sike S., Zsoldos Z., Johnson A.P. (1994). Journal of Chemical Information and Computer Sciences 34: 207–217
Douglet D., Thoreau E., Grassy G. (2000). Journal of computer-aided molecular design 14: 449–466
Budin N., Majeux N., Tenette C., Caflisch A. (2001). Journal of Computational Chemistry 22: 1956–1970
Frenkel D., Clark D.E., Li J., Murray C.W., Robson B., Waszkowycz B., Westhead D.R. (1995). Journal of Computer-Aided Molecular Design 9: 213–225
Böhm H.J. (1996). Program biophysical molecular biology 3: 197–210
Wang R., Gao Y., Lai L. (2000). Journal of molecular modeling 6: 498–516
Mandell A., Selz K., Shlesinger M., Algorithmic design of peptides for binding and/or modulation of the funcions of receptors and/or other proteins, Patent No. 767460, 2002
Teixido M., Belda I., Roselló X., Gonzalez S., Fabre M., Llorà X., Bacardit J., Garrell J.M., Vilaró S., Albericio F., Giralt E. (2002). QSAR and Combinatorial Sciences 22: 745–753
Weber L., Wallbaum S., Broger C., Gubernator K. (1995). Angewantde Chemical International Edition English 34: 2280–2282
Singh J., Ator M.A., Jaeger E.P., Allen M.P., Whipple D.A., Soloweij J.E., Chowdhary S., Treasurywala A.M. (1996). Journal of American Chemical Society 118: 1669–1676
Schneider G., Schrodl W., Wallukat G., Muller J., Nissen E., Ronspeck W., Wrede P., Kunze R. (1998). Proceedings of Natural Academy of Sciences 95: 12179–12184
Pegg S., Haresco J., Kuntz I. (2001). Journal of Computer-Aided Molecular Design 15: 911–933
Haack T., González M.J., Sánchez Y., Giralt E. (1997). Letters in Peptide Science 4: 377–386
Fogel G.B., Corne D.W., Evolutionary Computation in Bioinformatics Elsevier Science, 2002
Patel S., Stott I., Bhakoo M., Elliott P., Patenting Evolved Bactericidal Peptides, in Creative Evolutionary Systems, eds. Bentley, P. and Corne, D.W., Morgan Kaufmann Publishers, 2001
Kamphausen S., Höltgen N., Wirsching F., Morys-Wortmann C., Riester D., Goetz R., Thürk M., Schwienhorst A. (2002). Journal of Computer-Aided Molecular Design 16: 551–567
Michaud S.R., Zydallis J.B., Lamont G.B., Pachter R., Technical Proceedings of the 2001 International Conference on Computational Nanoscience and Nanotechnology (2001) 29–32
Goh, G.K.-M. and Foster, J.A., Proceedings of the Genetic and Evolutionary Computation Conference GECCO-2000, Morgan Kaufmann (2000) 27–33
Yamashita F., Wanchana S., Hashida M. (2002). Journal of Pharmaceutical Sciences 91: 2230–2238
Shoichet B.K., McGovern S.L., Wei B., Irwin JJ. (2002). Current Opinion in Chemical Biology 6: 439–446
Scheider G., Lee M., Stahl M., Schneider P. (2000). Journal of Computer-Aided Molecular Design 14: 487–494
Koza J.R., Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press (1992)
Baker J.E., Proceedings of the First International Conference on Genetic Algorithms, Erlbaum (1985) 101–111
Baker, J.E., Proceedings of the Second International Conference on Genetic Algorithms, Erlbaum (1987) 14–21
Michalewicz, Z., Genetic Algorithms + Data Structures = Evolution Programs, Springer, 1992
Back T., Evolutionary Algorithms in Theory and Practice, Oxford University Press, 1997
Schwefel, H.P., Numerische Optimierung von Computer-Modellen mittels der Evolutionsstrategie, Birkhaeuser, 1977
Howard, R. and Matheson, J., Readings on the Principles and Applications of Decision Analysis, volume III, eds. Howard, R. and Matheson, J., Strategic Decisions Group (1981) 721–762
Pearl, J., Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, Morgan Kaufmann, 1988
Heckerman, D., Geiger, D. and Chickering, D.M, Technical report of Microsoft Research, MSR-TR-94-09, 1995
Pelikan, M., Goldberg, D.E and Cantú-Paz, E., Technical report of IlliGAL, No. 98013, 1998
Vajda S., Camacho C.J. (2004) Trends in Biotechnology 22: 110–116
Macke T.J., Case D.A. (). NAB User’s Manual, Departament of Molecular Biology, The Scripps Research Institute, La Jolla, California, 1999
Chou P.Y., Fasman, G.D. (1978). Advanced in Enzymology 47: 45–148
Berman H.M, Westbrook J., Feng Z., Gilliland G., Bhat T.N, Weissig H., Shindyalov I.N., Bourne P.E. (2000). Nucleic Acids Research 28: 235–242
Yoshimoto T., Fischl M., Orlowski R., Walter R. (1978). Journal of Biological Chemistry 10: 3708–3716
Fülöp V., Bocskei Z., Polgár L. (1998). Cell 94: 161–170
Goossens F., De Meester I., Vanhoof G., Scharpé S. (1996). European Journal Clinical Chemistry and Clinical Biochemistry 34: 17–22
Mentlein R. (1988). FEBS Letters 234: 251–256
Maes M., Goossens F., Scharpé S., Calabrese J., Desnyder R., Meltzer H.Y. (1995). Psychiatry Research 58: 217–225
Maes M., Lin A.H., Bonaccorso S., Goossens F., Gastel A.V., Pioli R., Delmerie L., Scharpé S. (1999). Journal of Affective Disorders 53: 27–34
Vogelstein B., Lane D., Levine A.J. (2000). Nature 408: 307–310
Chene P. (2001). Oncogene 20: 2611–2617
Clore M., Ernst J., Clubb R., Omichinski J.G., Kennedy W.M.P., Sakaguchi K., Appella E., Gronenborn A.M. (1995). Nature Structural Biology 2: 321–333
Salvatella X., Martinell M., Gairí M., Mateu M.G., Feliz M., Hamilton A.D., de Mendoza J., Giralt E. (2004). Angewantde Chemie International Edition 43: 196–198
Martinell M., Disseny síntesi i estudi de lligands peptídics capaços de reconèixer la superfície de la p53, PhD dissertation at Universitat de Barcelona, 2004
Gellert M. (1981). Annual Review of Biochemistry 50: 879–910
Vizan J.L., Hernandez-Chico C., del Castillo I., Moreno F. (1991). EMBO Journal 10: 467–476
Yorgey P., Davagnino J., Kolter R. (1993). Molecular Microbiology 9: 897–905
Luz J.G., Huang M., Garcia K.C., Rudolph M.G., Apostolopoulos V., Teyton L., Wilson I.A. (2002). The Journal of Experimental Medicine 195: 1175–1186
Falk K., Rotzschke O., Stevanovic S., Jung G., Rammensee H.G. (2001). Nature 351: 290–296
Pelikan M., Goldberg D.E., Cantú-Paz E., Technical report of IlliGAL, No. 2000001, 2000
Acknowledgments
The authors thank I. Traus for his creative input on the computational aspects of this work, and Prof. X. Vilasis for his mathematical support in the implementation of Bayesian network learning algorithms. The authors would also like to thank the Parc Científic de Barcelona for providing the␣computational resources used for this research.
This work was partially supported by grants from Fundación BBVA, Fundació Marató TV3 and the Ministerio de Ciencia y Tecnología FEDER (BIO2002-2301 and EET2001-4813), the Air Force Office of Scientific Research, Air Force Materiel Command, USAF (F49620-03-1-0129), and by the Technology Research, Education, and Commercialization Center (TRECC), at the University of Illinois at Urbana–Champaign, administered by the National Center for Supercomputing Applications (NCSA) and funded by the Office of Naval Research (N00014-01-1-0175). The US Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation thereon.
The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Air Force Office of Scientific Research, the Technology Research, Education, and Commercialization Center, the Office of Naval Research, or the U.S. Government.
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Belda, I., Madurga, S., Llorà, X. et al. ENPDA: an evolutionary structure-based de novo peptide design algorithm. J Comput Aided Mol Des 19, 585–601 (2005). https://doi.org/10.1007/s10822-005-9015-1
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DOI: https://doi.org/10.1007/s10822-005-9015-1