Exploring Dimensionality, Systematic Mutations and Number of Contacts in Simple HP ab-initio Protein Folding Using a Blackboard-based Agent Platform
A computational platform is presented in this
contribution. It has been designed as a virtual laboratory to be used
for exploring optimization algorithms in biological problems. This
platform is built on a blackboard-based agent architecture. As a test
case, the version of the platform presented here is devoted to the
study of protein folding, initially with a bead-like description of the
chain and with the widely used model of hydrophobic and polar
residues (HP model). Some details of the platform design are
presented along with its capabilities and also are revised some
explorations of the protein folding problems with different types of
discrete space. It is also shown the capability of the platform to
incorporate specific tools for the structural analysis of the runs in
order to understand and improve the optimization process.
Accordingly, the results obtained demonstrate that the ensemble of
computational tools into a single platform is worthwhile by itself,
since experiments developed on it can be designed to fulfill different
levels of information in a self-consistent fashion. By now, it is being
explored how an experiment design can be useful to create a
computational agent to be included within the platform. These
inclusions of designed agents –or software pieces– are useful for the
better accomplishment of the tasks to be developed by the platform.
Clearly, while the number of agents increases the new version of the
virtual laboratory thus enhances in robustness and functionality.
[1] Robson, B., PROTEIN FOLDING. Trends in Biochemical Sciences, 1976.
1(3): p. 49-50.
[2] Levinthal C, Are there pathways for protein folding? Journal De Chimie
Physique Et De Physico-Chimie Biologique, 1968. 65(1): p. 44-&.
[3] Gonzalez, P.P., et al., An adaptable multi-agent based virtual laboratory
to explore complex problems in structural biology. Starting case study:
simplistic protein folding. Journal of Computational Biology, 2009: p.
Submitted.
[4] Sohl, J.L., S.S. Jaswal, and D.A. Agard, Unfolded conformations of alphalytic
protease are more stable than its native state. Nature, 1998.
395(6704): p. 817-819.
[5] Sadqi, M., D. Fushman, and V. Munoz, Atom-by-atom analysis of global
downhill protein folding. Nature, 2006. 442(7100): p. 317-321.
[6] Creighton, T.E., EXPERIMENTAL STUDIES OF PROTEIN FOLDING
AND UNFOLDING. Progress in Biophysics & Molecular Biology, 1978.
33(3): p. 231-297.
[7] Snow, C.D., et al., Absolute comparison of simulated and experimental
protein-folding dynamics. Nature, 2002. 420(6911): p. 102-106.
[8] Oh, K., K.S. Jeong, and J.S. Moore, Folding-driven synthesis of oligomers.
Nature, 2001. 414(6866): p. 889-893.
[9] Shakhnovich, E., V. Abkevich, and O. Ptitsyn, Conserved residues and the
mechanism of protein folding. Nature, 1996. 379(6560): p. 96-98.
[10] Betz, S.F., et al., Crystallization of a designed peptide from a molten
globule ensemble. Folding & Design, 1996. 1(1): p. 57-64.
[11] Koide, S., et al., Design of single-layer beta-sheets without a
hydrophobic core. Nature, 2000. 403(6768): p. 456-460.
[12] Minor, D.L. and P.S. Kim, Context-dependent secondary structure
formation of a designed protein sequence. Nature, 1996. 380(6576): p.
730-734.
[13] Robertson, D.E., et al., DESIGN AND SYNTHESIS OF MULTI-HEME
PROTEINS. Nature, 1994. 368(6470): p. 425-431.
[14] Miller, W.T. and D.P. Raleigh, Protein folding: From basic science to
biotechnology. Genetic Analysis-Biomolecular Engineering, 1996. 12(5-
6): p. 169-172.
[15] Gething, M.J. and J. Sambrook, PROTEIN FOLDING IN THE CELL.
Nature, 1992. 355(6355): p. 33-45.
[16] Carulla, N., et al., Molecular recycling within amyloid fibrils. Nature,
2005. 436(7050): p. 554-558.
[17] Levy, E.D., et al., Assembly reflects evolution of protein complexes.
Nature, 2008. 453(7199): p. 1262-U66.
[18] Egger, G., et al., Epigenetics in human disease and prospects for
epigenetic therapy. Nature, 2004. 429(6990): p. 457-463.
[19] Liu, X., et al., The structural basis of protein acetylation by the
p300/CBP transcriptional coactivator. Nature, 2008. 451(7180): p. 846-
850.
[20] Conway, G. and G. Toenniessen, Feeding the world in the twenty-first
century. Nature, 1999. 402(6761): p. C55-C58.
[21] Kato, M., et al., Plant biotechnology - Caffeine synthase gene from tea
leaves. Nature, 2000. 406(6799): p. 956-957.
[22] Schwartz, T.W. and W.L. Hubbell, Structural biology - A moving story of
receptors. Nature, 2008. 455(7212): p. 473-474.
[23] Ferguson, N., et al., Structural biology - Analysis of 'downhill' protein
folding. Nature, 2007. 445(7129): p. E14-E15.
[24] Zhou, Z. and Y.W. Bai, Structural biology - Analysis of protein-folding
cooperativity. Nature, 2007. 445(7129): p. E16-E17.
[25] Economou, A., Structural biology - Clamour for a kiss. Nature, 2008.
455(7215): p. 879-880.
[26] Stefani, M., Protein Folding and Misfolding on Surfaces. International
Journal of Molecular Sciences, 2008. 9(12): p. 2515-2542.
[27] Cha, J.N., et al., Biomimetic synthesis of ordered silica structures
mediated by block copolypeptides. Nature, 2000. 403(6767): p. 289-292.
[28] Kloxin, A.M. and K.S. Anseth, Materials science - Protein gels on the
move. Nature, 2008. 454(7205): p. 705-706.
[29] Meldrum, F.C., et al., SYNTHESIS OF INORGANIC NANOPHASE
MATERIALS IN SUPRAMOLECULAR PROTEIN CAGES. Nature, 1991.
349(6311): p. 684-687.
[30] Howard, J., Molecular motors: structural adaptations to cellular
functions. Nature, 1997. 389(6651): p. 561-567.
[31] Schliwa, M. and G. Woehlke, Molecular motors. Nature, 2003.
422(6933): p. 759-765.
[32] Brockwell, D.J., D.A. Smith, and S.E. Radford, Protein folding
mechanisms: new methods and emerging ideas. Current Opinion in
Structural Biology, 2000. 10(1): p. 16-25.
[33] Radford, S.E., Protein folding: progress made and promises ahead.
Trends in Biochemical Sciences, 2000. 25(12): p. 611-618.
[34] Chiti, F., et al., Rationalization of the effects of mutations on peptide and
protein aggregation rates. Nature, 2003. 424(6950): p. 805-808.
[35] Serrano, L., et al., EFFECT OF ALANINE VERSUS GLYCINE IN
ALPHA-HELICES ON PROTEIN STABILITY. Nature, 1992. 356(6368):
p. 453-455.
[36] Negrete, J. and P.P. Gonzalez, A Net of Multi-Agent Expert Systems with
Emergent Control. Expert Systems With Applications, 1998. 14(1-2).
[37] Wooldridge, M., The Gaia methodology for agent-oriented analysis and
design. Autonomous Agents and Multi-Agent Systems, 2000. 3(3): p.
285-312.
[38] Liu, H., M.X. Tang, and J.H. Frazer, Supporting evolution in a multiagent
cooperative design environment. Advances in Engineering
Software, 2002. 33(6): p. 319-328.
[39] Wooldridge, M.J., Software engineering with agents: Pitfalls and
pratfalls. IEEE Internet Computing, 1999. 3(3): p. 20-+.
[40] Gallimore, R.J., et al., Cooperating agents for 3-D scientific data
interpretation. Ieee Transactions on Systems Man and Cybernetics Part
C-Applications and Reviews, 1999. 29(1): p. 110-126.
[41] Gonzalez, P.P., et al., Cellulat: an agent-based intracellular signalling
model. Biosystems, 2003. 68(2-3): p. 171-185.
[42] Ominici, A., A. Ricci, and M. Viroli, Coordination artifacts:
Environment-based coordination for intelligent agents. AAMAS'04,
2006.
[43] Ominici, A., et al., Coordination artifacts: Environment-based
coordination for intelligen agents. Proceedings of 3rd International Joint
Conference on Autonomous Agents and Multi-Agent Systems, 2004: p.
286-293.
[44] Gonzalez, P.P. and J. Negrete, REDSIEX: A Cooperative Network of
Expert Systems with Blackboard Architectures. Expert Systems, 1997.
14(4): p. 180-189.
[45] Lagunez-Otero, J., et al., Cellulat, in Artificial Life VIII: Proceedings of
the Eight International Conference on Artificial Life, R.K. Standish, M.A.
Bedau, and H.A. Abbass, Editors. 2002: Sydney, Australia. p. 97-100.
[46] Dill, K.A., THEORY FOR THE FOLDING AND STABILITY OF
GLOBULAR-PROTEINS. Biochemistry, 1985. 24(6): p. 1501-1509.
[47] Dill, K.A., Polymer principles and protein folding. Protein Science,
1999. 8(6): p. 1166-1180.
[48] Dill, K.A., et al., PRINCIPLES OF PROTEIN-FOLDING - A
PERSPECTIVE FROM SIMPLE EXACT MODELS. Protein Science,
1995. 4(4): p. 561-602.
[49] Goldberg, D.E., Genetic Algorithms in Search, Optimization, and
Machine Learning. 1989: Addison-Wesley Professional.
[50] Lima, C., Parameter Setting in Evolutionary Algorithms. 2007, Berlin:
Springer.
[51] Mitchell, M., An Introduction to Genetic Algorithms (Complex Adaptive
Systems). 1998: The MIT Press.
[52] Panchenko, A.R., Z. Luthey-Schulten, and P.G. Wolynes, Foldons,
protein structural modules, and exons. Proceedings of the National
Academy of Sciences of the United States of America, 1996. 93(5): p.
2008-2013.
[53] Ferreiro, D.U., et al., The energy landscapes of repeat-containing
proteins: Topology, cooperativity, and the folding funnels of onedimensional
architectures. Plos Computational Biology, 2008. 4(5).
[54] Englander, S.W., L. Mayne, and M.M.G. Krishna, Protein folding and
misfolding: mechanism and principles. Quarterly Reviews of Biophysics,
2007. 40(4): p. 287-326.
[55] Bedard, S., et al., Protein folding: Independent unrelated pathways or
predetermined pathway with optional errors. Proceedings of the National
Academy of Sciences of the United States of America, 2008. 105(20): p.
7182-7187.
[56] Lindberg, M.O. and M. Oliveberg, Malleability of protein folding
pathways: a simple reason for complex behaviour. Current Opinion in
Structural Biology, 2007. 17(1): p. 21-29.
[57] Olofsson, M., et al., Folding of S6 structures with divergent amino acid
composition: Pathway flexibility within partly overlapping foldons.
Journal of Molecular Biology, 2007. 365(1): p. 237-248.
[1] Robson, B., PROTEIN FOLDING. Trends in Biochemical Sciences, 1976.
1(3): p. 49-50.
[2] Levinthal C, Are there pathways for protein folding? Journal De Chimie
Physique Et De Physico-Chimie Biologique, 1968. 65(1): p. 44-&.
[3] Gonzalez, P.P., et al., An adaptable multi-agent based virtual laboratory
to explore complex problems in structural biology. Starting case study:
simplistic protein folding. Journal of Computational Biology, 2009: p.
Submitted.
[4] Sohl, J.L., S.S. Jaswal, and D.A. Agard, Unfolded conformations of alphalytic
protease are more stable than its native state. Nature, 1998.
395(6704): p. 817-819.
[5] Sadqi, M., D. Fushman, and V. Munoz, Atom-by-atom analysis of global
downhill protein folding. Nature, 2006. 442(7100): p. 317-321.
[6] Creighton, T.E., EXPERIMENTAL STUDIES OF PROTEIN FOLDING
AND UNFOLDING. Progress in Biophysics & Molecular Biology, 1978.
33(3): p. 231-297.
[7] Snow, C.D., et al., Absolute comparison of simulated and experimental
protein-folding dynamics. Nature, 2002. 420(6911): p. 102-106.
[8] Oh, K., K.S. Jeong, and J.S. Moore, Folding-driven synthesis of oligomers.
Nature, 2001. 414(6866): p. 889-893.
[9] Shakhnovich, E., V. Abkevich, and O. Ptitsyn, Conserved residues and the
mechanism of protein folding. Nature, 1996. 379(6560): p. 96-98.
[10] Betz, S.F., et al., Crystallization of a designed peptide from a molten
globule ensemble. Folding & Design, 1996. 1(1): p. 57-64.
[11] Koide, S., et al., Design of single-layer beta-sheets without a
hydrophobic core. Nature, 2000. 403(6768): p. 456-460.
[12] Minor, D.L. and P.S. Kim, Context-dependent secondary structure
formation of a designed protein sequence. Nature, 1996. 380(6576): p.
730-734.
[13] Robertson, D.E., et al., DESIGN AND SYNTHESIS OF MULTI-HEME
PROTEINS. Nature, 1994. 368(6470): p. 425-431.
[14] Miller, W.T. and D.P. Raleigh, Protein folding: From basic science to
biotechnology. Genetic Analysis-Biomolecular Engineering, 1996. 12(5-
6): p. 169-172.
[15] Gething, M.J. and J. Sambrook, PROTEIN FOLDING IN THE CELL.
Nature, 1992. 355(6355): p. 33-45.
[16] Carulla, N., et al., Molecular recycling within amyloid fibrils. Nature,
2005. 436(7050): p. 554-558.
[17] Levy, E.D., et al., Assembly reflects evolution of protein complexes.
Nature, 2008. 453(7199): p. 1262-U66.
[18] Egger, G., et al., Epigenetics in human disease and prospects for
epigenetic therapy. Nature, 2004. 429(6990): p. 457-463.
[19] Liu, X., et al., The structural basis of protein acetylation by the
p300/CBP transcriptional coactivator. Nature, 2008. 451(7180): p. 846-
850.
[20] Conway, G. and G. Toenniessen, Feeding the world in the twenty-first
century. Nature, 1999. 402(6761): p. C55-C58.
[21] Kato, M., et al., Plant biotechnology - Caffeine synthase gene from tea
leaves. Nature, 2000. 406(6799): p. 956-957.
[22] Schwartz, T.W. and W.L. Hubbell, Structural biology - A moving story of
receptors. Nature, 2008. 455(7212): p. 473-474.
[23] Ferguson, N., et al., Structural biology - Analysis of 'downhill' protein
folding. Nature, 2007. 445(7129): p. E14-E15.
[24] Zhou, Z. and Y.W. Bai, Structural biology - Analysis of protein-folding
cooperativity. Nature, 2007. 445(7129): p. E16-E17.
[25] Economou, A., Structural biology - Clamour for a kiss. Nature, 2008.
455(7215): p. 879-880.
[26] Stefani, M., Protein Folding and Misfolding on Surfaces. International
Journal of Molecular Sciences, 2008. 9(12): p. 2515-2542.
[27] Cha, J.N., et al., Biomimetic synthesis of ordered silica structures
mediated by block copolypeptides. Nature, 2000. 403(6767): p. 289-292.
[28] Kloxin, A.M. and K.S. Anseth, Materials science - Protein gels on the
move. Nature, 2008. 454(7205): p. 705-706.
[29] Meldrum, F.C., et al., SYNTHESIS OF INORGANIC NANOPHASE
MATERIALS IN SUPRAMOLECULAR PROTEIN CAGES. Nature, 1991.
349(6311): p. 684-687.
[30] Howard, J., Molecular motors: structural adaptations to cellular
functions. Nature, 1997. 389(6651): p. 561-567.
[31] Schliwa, M. and G. Woehlke, Molecular motors. Nature, 2003.
422(6933): p. 759-765.
[32] Brockwell, D.J., D.A. Smith, and S.E. Radford, Protein folding
mechanisms: new methods and emerging ideas. Current Opinion in
Structural Biology, 2000. 10(1): p. 16-25.
[33] Radford, S.E., Protein folding: progress made and promises ahead.
Trends in Biochemical Sciences, 2000. 25(12): p. 611-618.
[34] Chiti, F., et al., Rationalization of the effects of mutations on peptide and
protein aggregation rates. Nature, 2003. 424(6950): p. 805-808.
[35] Serrano, L., et al., EFFECT OF ALANINE VERSUS GLYCINE IN
ALPHA-HELICES ON PROTEIN STABILITY. Nature, 1992. 356(6368):
p. 453-455.
[36] Negrete, J. and P.P. Gonzalez, A Net of Multi-Agent Expert Systems with
Emergent Control. Expert Systems With Applications, 1998. 14(1-2).
[37] Wooldridge, M., The Gaia methodology for agent-oriented analysis and
design. Autonomous Agents and Multi-Agent Systems, 2000. 3(3): p.
285-312.
[38] Liu, H., M.X. Tang, and J.H. Frazer, Supporting evolution in a multiagent
cooperative design environment. Advances in Engineering
Software, 2002. 33(6): p. 319-328.
[39] Wooldridge, M.J., Software engineering with agents: Pitfalls and
pratfalls. IEEE Internet Computing, 1999. 3(3): p. 20-+.
[40] Gallimore, R.J., et al., Cooperating agents for 3-D scientific data
interpretation. Ieee Transactions on Systems Man and Cybernetics Part
C-Applications and Reviews, 1999. 29(1): p. 110-126.
[41] Gonzalez, P.P., et al., Cellulat: an agent-based intracellular signalling
model. Biosystems, 2003. 68(2-3): p. 171-185.
[42] Ominici, A., A. Ricci, and M. Viroli, Coordination artifacts:
Environment-based coordination for intelligent agents. AAMAS'04,
2006.
[43] Ominici, A., et al., Coordination artifacts: Environment-based
coordination for intelligen agents. Proceedings of 3rd International Joint
Conference on Autonomous Agents and Multi-Agent Systems, 2004: p.
286-293.
[44] Gonzalez, P.P. and J. Negrete, REDSIEX: A Cooperative Network of
Expert Systems with Blackboard Architectures. Expert Systems, 1997.
14(4): p. 180-189.
[45] Lagunez-Otero, J., et al., Cellulat, in Artificial Life VIII: Proceedings of
the Eight International Conference on Artificial Life, R.K. Standish, M.A.
Bedau, and H.A. Abbass, Editors. 2002: Sydney, Australia. p. 97-100.
[46] Dill, K.A., THEORY FOR THE FOLDING AND STABILITY OF
GLOBULAR-PROTEINS. Biochemistry, 1985. 24(6): p. 1501-1509.
[47] Dill, K.A., Polymer principles and protein folding. Protein Science,
1999. 8(6): p. 1166-1180.
[48] Dill, K.A., et al., PRINCIPLES OF PROTEIN-FOLDING - A
PERSPECTIVE FROM SIMPLE EXACT MODELS. Protein Science,
1995. 4(4): p. 561-602.
[49] Goldberg, D.E., Genetic Algorithms in Search, Optimization, and
Machine Learning. 1989: Addison-Wesley Professional.
[50] Lima, C., Parameter Setting in Evolutionary Algorithms. 2007, Berlin:
Springer.
[51] Mitchell, M., An Introduction to Genetic Algorithms (Complex Adaptive
Systems). 1998: The MIT Press.
[52] Panchenko, A.R., Z. Luthey-Schulten, and P.G. Wolynes, Foldons,
protein structural modules, and exons. Proceedings of the National
Academy of Sciences of the United States of America, 1996. 93(5): p.
2008-2013.
[53] Ferreiro, D.U., et al., The energy landscapes of repeat-containing
proteins: Topology, cooperativity, and the folding funnels of onedimensional
architectures. Plos Computational Biology, 2008. 4(5).
[54] Englander, S.W., L. Mayne, and M.M.G. Krishna, Protein folding and
misfolding: mechanism and principles. Quarterly Reviews of Biophysics,
2007. 40(4): p. 287-326.
[55] Bedard, S., et al., Protein folding: Independent unrelated pathways or
predetermined pathway with optional errors. Proceedings of the National
Academy of Sciences of the United States of America, 2008. 105(20): p.
7182-7187.
[56] Lindberg, M.O. and M. Oliveberg, Malleability of protein folding
pathways: a simple reason for complex behaviour. Current Opinion in
Structural Biology, 2007. 17(1): p. 21-29.
[57] Olofsson, M., et al., Folding of S6 structures with divergent amino acid
composition: Pathway flexibility within partly overlapping foldons.
Journal of Molecular Biology, 2007. 365(1): p. 237-248.
@article{"International Journal of Engineering, Mathematical and Physical Sciences:59040", author = "Hiram I. Beltrán and Arturo Rojo-Domínguez and Máximo Eduardo Sánchez Gutiérrez and Pedro Pablo
González Pérez", title = "Exploring Dimensionality, Systematic Mutations and Number of Contacts in Simple HP ab-initio Protein Folding Using a Blackboard-based Agent Platform", abstract = "A computational platform is presented in this
contribution. It has been designed as a virtual laboratory to be used
for exploring optimization algorithms in biological problems. This
platform is built on a blackboard-based agent architecture. As a test
case, the version of the platform presented here is devoted to the
study of protein folding, initially with a bead-like description of the
chain and with the widely used model of hydrophobic and polar
residues (HP model). Some details of the platform design are
presented along with its capabilities and also are revised some
explorations of the protein folding problems with different types of
discrete space. It is also shown the capability of the platform to
incorporate specific tools for the structural analysis of the runs in
order to understand and improve the optimization process.
Accordingly, the results obtained demonstrate that the ensemble of
computational tools into a single platform is worthwhile by itself,
since experiments developed on it can be designed to fulfill different
levels of information in a self-consistent fashion. By now, it is being
explored how an experiment design can be useful to create a
computational agent to be included within the platform. These
inclusions of designed agents –or software pieces– are useful for the
better accomplishment of the tasks to be developed by the platform.
Clearly, while the number of agents increases the new version of the
virtual laboratory thus enhances in robustness and functionality.", keywords = "genetic algorithms, multi-agent systems,bioinformatics, optimization, protein folding, structural biology.", volume = "3", number = "4", pages = "269-10", }
