Campo de força (química): diferenças entre revisões

Todos [[potenciais interatômicos]] baseiam-se em inúmeras aproximações e derivam de diferentes tipos de dados experimentais. Por isso, eles são chamados de ''empíricos''. Algumas funções de energia existentes não levam em conta a [[polarização dielétrica| polarização]] eletrônica do meio ambiente, um efeito que pode reduzir significativamente interações eletrostáticas de cargas atômicas parciais. Este problema foi resolvido através do desenvolvimento de "campos de força polarizáveis" <ref name="Ponder">Ponder JW and Case DA. (2003). Interatomic potentials and their relative parameters for protein simulations. ''Adv. Prot. Chem.'' '''66''' 27-85.</ref><ref name="warshel">Warshel A, Sharma PK, Kato M and Parson WW (2006). "Modeling Electrostatic Effects in Proteins." ''Biochim. Biophys. Acta'' '''1764''' 1647-1676.</ref> ou usando uma [[constante dielétrica]] macroscópica. No entanto, a aplicação de um único valor de [[constante dielétrica]] é questionável em ambientes altamente heterogêneos de proteínas ou membranas biológicas, e a natureza do dielétrico depende do modelo utilizado.<ref name="Shultz">Schutz CN. and Warshel A. (2001). "What are the dielectric "constants" of proteins and how to validate electrostatic models?". ''Proteins'' '''44''' 400-417.</ref>

 

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Another round of criticism came from practical applications, such as protein structure refinement. It was noted that [[CASP]] participants did not try to refine their models to avoid "''a central embarrassment of molecular mechanics, namely that energy minimization or molecular dynamics generally leads to a model that is less like the experimental structure''".<ref name="Koehl">Koehl P. and Levitt M. (1999). "A brighter future for protein structure prediction". ''Nature Struct. Biol.'' '''6''' 108-111.</ref> Actually, the force fields have been successfully applied for protein structure refinement in different [[X-ray crystallography]] and [[NMR spectroscopy]] applications, especially using program XPLOR.<ref name="Brunger">Brunger AT and Adams PD. (2002). "Molecular dynamics applied to X-ray structure refinement". ''Acc. Chem. Res.'' '''35''' 404-412.</ref> However, such refinement is driven primarily by a set of experimental constraints, whereas the interatomic potentials serve merely to remove interatomic hindrances. The results of calculations are practically the same with rigid sphere potentials implemented in program DYANA <ref name="Guntert">Guntert P. (1998). "Structure calculation of biological macromolecules from NMR data". ''Quart. Rev. Biophys.'' '''31''' 145-237.</ref> (calculations from NMR data), or with programs for crystallographic refinement that do not use any energy functions. The deficiencies of the interatomic potentials remain a major bottleneck in [[homology modeling]] of proteins.<ref name="Tramontano">Tramontano A. and Morea V. (2003). "Assessment of homology-based predictions in CASP5". ''Proteins.'' '''53''' 352-368.</ref> Such situation gave rise to development of alternative empirical scoring functions specifically for [[ligand docking]],<ref name="Gohlke">Gohlke H. and Klebe G. (2002). "Approaches to the description and prediction of the binding affinity of small-molecule ligands to macromolecular receptors". ''Angew. Chem. Internat. Ed.'' '''41''' 2644-2676.</ref> [[protein folding]],<ref name="Edgcomb">Edgcomb S.P. and Murphy K.P. (2000). "Structural energetics of protein folding and binding". ''Current Op. Biotechnol.'' '''11''' 62-66.</ref><ref name="Lazaridis">Lazaridis T. and Karplus M. (2000). "Effective energy functions for protein structure prediction". ''Curr. Op. Struct. Biol.'' '''10''' 139-145.</ref><ref name="awml">Levitt M. and Warshel A. (1975). "Computer Simulations of Protein Folding". ''Nature'' '''253''' 694-698.</ref> homology model refinement,<ref name="krieger">Krieger E., Joo K., Lee J., Lee J., Raman S., Thompson J., Tyka M., Baker D. and Karplus K. (2009). "Improving physical realism, stereochemistry, and side-chain accuracy in homology modeling: Four approaches that performed well in CASP8". ''Proteins'' '''77 Suppl 9''' 114-122.</ref> computational [[protein design]],<ref name="Gordon">Gordon DB, Marshall SA, and Mayo SL (1999). "Energy functions for protein design". ''Curr. Op. Struct. Biol.'' '''9''' 509-513.</ref><ref name="Mendes">Mendes J., Guerois R, and Serrano L (2002). "Energy estimation in protein design". ''Curr. Op. Struct. Biol.'' '''12''' 441-446.</ref><ref name="Rohl">Rohl CA, Strauss CEM, Misura KMS, and Baker D. (2004). "Protein structure prediction using Rosetta". ''Meth. Enz.'' '''383''' 66-93.</ref> and modeling of proteins in membranes.<ref name="Lomize1">Lomize AL, Pogozheva ID, Lomize MA, Mosberg HI (2006). "Positioning of proteins in membranes: A computational approach". ''Protein Sci.'' '''15''' 1318-1333.</ref>