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Polypeptide and Protein Modeling for Drug Design

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Encyclopedia of Computational Neuroscience

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Synonyms

Computational modeling; Computational structural biology; Structure-aided drug design

Definition

Modeling of polypeptides and proteins, often referred to as biomolecular or molecular modeling, encompasses the use of theoretical models and computational methods to model the structure and dynamics of molecules of biological interest such as peptides, proteins and small organic molecules (ligands).

The aims of protein and peptide modeling for drug design include: (i) modeling the three-dimensional structure of proteins of current or potential drug targets; (ii) identifying and characterizing the structural dynamics associated with the function of a particular protein or peptide; and (iii) predicting the structure and molecular interactions of protein-ligand complexes. This knowledge underpins structure-based and rational drug design. It can aid in the design and optimization of drug molecules by shedding light on their mode of action, specificity and selectivity.

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References

  • Alder BJ, Wainwright TE (1959) Studies in molecular dynamics. I. General method. J Chem Phys 31:459–466

    Article  CAS  Google Scholar 

  • Baron R, Nichols SE, McCammon JA (2012) On the use of molecular dynamics receptor conformations for virtual screening. In: Baron R (ed) Computational drug discovery and design. Springer, New York

    Chapter  Google Scholar 

  • Cross AJ, Yocca FD (2012) Essential CNS drug development – pre-clinical development. In: Kalali A, Preskorn S, Kwentus J, Stahl SM (eds) Essential CNS drug development. Cambridge University Press, Cambridge

    Google Scholar 

  • De Lucca GV, Erickson-Viitanen S, Lam PYS (1997) Cyclic HIV protease inhibitors capable of displacing the active site structural water molecule. Drug Discov Today 2:6–18

    Article  Google Scholar 

  • Druker BJ, Lydon NB (2000) Lessons learned from the development of an Abl tyrosine kinase inhibitor for chronic myelogenous leukemia. J Clin Investig 105:3–7

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Goodfellow JM (2008) Computer modelling in molecular biology. Weinheim, New York

    Google Scholar 

  • Greer J, Erickson JW, Baldwin JJ, Varneyl MD (1994) Application of the three-dimensional structures of protein target molecules in structure-based drug design. Med Chem 37:1035–1054

    Article  CAS  Google Scholar 

  • Gumbart JC, Roux B, Chipot C (2012) Standard binding free energies from computer simulations: what is the best strategy? J Chem Theory Comput 9(1):794–802. doi:10.1021/ct3008099

    PubMed Central  Google Scholar 

  • Hefti FF (2004) Drug discovery for nervous system diseases. Wiley, Hoboken

    Google Scholar 

  • Jensen F (2007) Introduction to computational chemistry. Wiley, New York

    Google Scholar 

  • Kozma D, Simon I, Tusnády G (2013) PDBTM: Protein Data Bank of transmembrane proteins after 8 years. Nucleic Acids Res 41:D524–D529

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Lorenz C, Doltsinis NL (2012) Molecular dynamics simulation: from “ab initio” to “coarse grained”. In: Leszczynski J (ed) Handbook of computational chemistry. Springer, New York

    Google Scholar 

  • Náray-Szabó G, Perczel A, Láng A (2012) Protein modeling. In: Leszczynski J (ed) Handbook of computational chemistry. Springer, New York

    Google Scholar 

  • Nowak W (2012) Applications of computational methods to simulations of proteins dynamics. In: Leszczynski J (ed) Handbook of computational chemistry. Springer, New York

    Google Scholar 

  • Rahman A (1964) Correlations in the motion of atoms in liquid argon. Phys Rev 136:405–411

    Article  CAS  Google Scholar 

  • Rangwala H (2010) A survey of remote homology detection and fold recognition methods. In: Rangwala H, Karypis G (eds) Introduction to protein structure prediction methods and algorithms. Wiley, Hoboken

    Chapter  Google Scholar 

  • Rost B (1999) Twilight zone of protein sequence alignments. Prot Eng Des Sel 12:85–94

    Article  CAS  Google Scholar 

  • RSCB Protein Data Bank (2013) Research collaboratory for structural bioinformatics. http://www.rcsb.org/pdb/home/home.do. Accessed 12 Oct 2013

  • Schushan M, Ben-Tal N (2010) Modeling and validation of transmembrane protein structures. In: Rangwala H, Karypis G (eds) Introduction to protein structure prediction methods and algorithms. Wiley, Hoboken

    Google Scholar 

  • Shirts MR (2012) Best practices in free energy calculations for drug design. In: Baron R (ed) Computational drug discovery and design. Springer, New York

    Google Scholar 

  • Squire LR, Berg D, Bloom FE, du Lac S, Ghosh A, Spitzer NC (2008) Fundamental neuroscience. Elsevier, Burlington

    Google Scholar 

  • The Nobel Prize in chemistry 2013 – press release (2013) Nobel media AB. http://www.nobelprize.org/nobel_prizes/chemistry/laureates/2013/press.html

  • von Hoerner S (1960) Die numerische Integration des n-Körper-Problemes für Sternhaufen, I. Z Astrophys 50:184–214

    Google Scholar 

  • von Hoerner S (1963) Die numerische Integration des n-Körper-Problems für Sternhaufen, II. Z Astrophys 57:47–82

    Google Scholar 

  • Xu Y, Xu D, Liang J, Wooley JC (2007) Computational methods for protein structure prediction and modeling. Springer, New York

    Book  Google Scholar 

  • Zvelebil M, Baum JO (2008) Understanding bioinformatics. Garland Science, New York

    Google Scholar 

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Author information

Authors and Affiliations

  1. School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, Qld, 4072, Australia

    Dr. Megan L. O’Mara & Dr. Evelyne Deplazes

  2. School of Mathematics and Physics, University of Queensland, Brisbane, Qld, 4072, Australia

    Dr. Megan L. O’Mara

  3. Institute for Molecular Bioscience, University of Queensland, Brisbane, Qld, 4072, Australia

    Dr. Evelyne Deplazes

Authors
  1. Dr. Megan L. O’Mara
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  2. Dr. Evelyne Deplazes
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Corresponding author

Correspondence to Megan L. O’Mara .

Editor information

Editors and Affiliations

  1. Atlanta, Georgia, USA

    Dieter Jaeger

  2. Department of Biomedical Engineering, Florida International University, Miami, Florida, USA

    Ranu Jung

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O’Mara, M.L., Deplazes, E. (2013). Polypeptide and Protein Modeling for Drug Design. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_732-1

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  • DOI: https://doi.org/10.1007/978-1-4614-7320-6_732-1

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  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4614-7320-6

  • eBook Packages: Springer Reference Biomedicine and Life SciencesReference Module Biomedical and Life Sciences

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