Sensitivity Analysis of a Two-Dimensional Square Lattice Model of Protein Folding

Bleil, R.; Wong, Chung F.; Rabitz, Herschel

doi:10.1021/j100010a057

Cited by 9 publications

(6 citation statements)

References 14 publications

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“…Sensitivity analysis has been developed in the engineering field to characterize uncertainties in input variables and model parameters. At present the methodology is also successfully used for a wide variety of complex physicochemical phenomena ranging from scattering problems to protein folding . Previously other groups have investigated the sensitivity analysis of liquid water.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity Analysis of Thermodynamic Properties of Liquid Water: A General Approach to Improve Empirical Potentials

2005

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A sensitivity analysis of bulk water thermodynamics is presented in an effort to understand the relation between qualitative features of molecular potentials and properties that they predict. The analysis is incorporated in molecular dynamics simulations and investigates the sensitivity of the Helmholtz free energy, internal energy, entropy, heat capacity, pressure, thermal pressure coefficient, and static dielectric constant to components of the potential rather than the parameters of a given functional form. The sensitivities of the properties are calculated with respect to the van der Waals repulsive and the attractive parts, plus short- and long-range Coulomb parts of three four site empirical water potentials: TIP4P, Dang-Chang and TTM2R. The polarization sensitivity is calculated for the polarizable Dang-Chang and TTM2R potentials. This new type of analysis allows direct comparisons of the sensitivities for different potentials that use different functional forms. The analysis indicates that all investigated properties are most sensitive to the van der Waals repulsive, the short-range Coulomb and the polarization components of the potentials. When polarization is included in the potentials, the magnitude of the sensitivity of the Helmholtz free energy, internal energy, and entropy with respect to this part of the potential is comparable in magnitude to the other electrostatic components. In addition similarities in trends of observed sensitivities for nonpolarizable and polarizable potentials lead to the conclusion that the complexity of the model is not of critical importance for the calculation of these thermodynamic properties for bulk water. The van der Waals attractive and the long-range Coulomb sensitivities are relatively small for the entropy, heat capacity, thermal pressure coefficient and the static dielectric constant, while small changes in any of the potential contributions will significantly affect the pressure. The analysis suggests a procedure for modification of the potentials to improve predictions of thermodynamic properties and we demonstrate this general approach for modifying potentials for one of the potentials.

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Section: Introductionmentioning

confidence: 99%

Sensitivity Analysis of Thermodynamic Properties of Liquid Water: A General Approach to Improve Empirical Potentials

2005

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“…Excluding all the (i,i11) and (i,i12) interactions in the model was one example. Another approach being examined is to use sensitivity analysis [10][11][12][13][14][15]47 as a tool to help choose the most significant interactions to be included in the model. Sensitivity analysis is an approach that systematically analyzes the relationship between a set of properties of a (bio)molecular system and the parameters of a computational model used to model the behavior of the system.…”

Section: Resultsmentioning

confidence: 99%

“…For instance, we have systematically removed all the (i,i11) and (i,i12) interactions to examine the performance of the model. We have also begun to use sensitivity analysis [10][11][12][13][14][15]47 to help select key interactions to be included in the model, because sensitivity analysis can provide an efficient tool for identifying the interaction parameters that are most significant in determining the helicity of polypeptides. Nevertheless, the current HCTT has been successful in identifying helical segments in proteins and requires very little computational time (the calculations of the helicity of all the residues in the 51 proteins analyzed in Table V took approximately 15 minutes on a Silicon Graphics Power Challenge R10000).…”

Section: Discussionmentioning

confidence: 99%

Predicting helical segments in proteins by a helix-coil transition theory with parameters derived from a structural database of proteins

Misra

Wong

1997

Proteins

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A novel helix-coil transition theory has been developed. This new theory contains more types of interactions than similar theories developed earlier. The parameters of the models were obtained from a database of 351 nonhomologous proteins. No manual adjustment of the parameters was performed. The interaction parameters obtained in this manner were found to be physically meaningful, consistent with current understanding of helix stabilizing/destabilizing interactions. Novel insights into helix stabilizing/destabilizing interactions have also emerged from this analysis. The theory developed here worked well in sorting out helical residues from amino acid sequences. If the theory was forced to make prediction on every residue of a given amino acid sequence, its performance was the best among ten other secondary structural prediction algorithms in distinguishing helical residues from nonhelical ones. The theory worked even better if one only required it to make prediction on residues that were "predictable" (identifiable by the theory); > 90% predictive reliability could be achieved. The helical residues or segments identified by the helix-coil transition theory can be used as secondary structural contraints to speed up the prediction of the three-dimensional structure of a protein by reducing the dimension of a computational protein folding problem. Possible further improvements of this helix-coil transition theory are also discussed.

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“…The application of sensitivity analysis in the studies of complicated chemical and biological networks has a long history. [1][2][3][4] In chemical kinetics, the associated techniques have been applied to combustion, 5 atmospheric chemistry, 6 the determination of parameters of potential energy surfaces, 7 biomolecular simulations, 8,9 etc. The tool of sensitivity analysis speeds up the processes in identifying the key parameters that control the behavior and performance of the entire systems.…”

Section: Introductionmentioning

confidence: 99%

Time-Dependent Sensitivity Analysis of Biological Networks: Coupled MAPK and PI3K Signal Transduction Pathways

Yuan

2006

J. Phys. Chem. A

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Sensitivity analysis has been widely used in the studies of complicated chemical reaction and biological networks, for example, in combustion studies and metabolic control analysis of pathways. In the latter cases, the responses of system properties at steady states with respect to changes of parameters, such as initial concentrations and rate constants, are often expressed as sensitivities. Besides steady-state sensitivities, time-dependent sensitivities should be useful; however, the explicit use of them in analyzing complicated biological systems has so far been limited. Using the coupled mitogen activated protein kinase (MAPK)-phophatidylinoisitol 3'-kinase (PI3K) system of the Ras pathways, known to be involved in about 30% of human cancers, as an example, we show that time-dependent sensitivities are useful for the studies of complex biological systems. They provide, for example, the following information: (a) multiple time scales existing in a complex system involving cross-talks and feedback loops; (b) the signs and strengths of responses to perturbations (as system complication increases, the signs of global responses are not always easily determined; for example, response may change sign more than once as time evolves); (c) beyond concentration dynamics, sensitivities revealing further details about the intricate dynamics and the effects of the cross-talks; (d) ranking of vulnerability of nodes of a biological network using integrated sensitivity-a first step toward the identification of drug targets; (e) reduced sensitivity serving as a measure of the stability or robustness of pathways. Our results indicate that the role of the PI3K branch in the coupled pathways is to enhance the robustness of the MAPK pathway. More importantly, they demonstrate that time-dependent sensitivity analysis can be a valuable tool in system biology.

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Sensitivity Analysis of a Two-Dimensional Square Lattice Model of Protein Folding

Cited by 9 publications

References 14 publications

Sensitivity Analysis of Thermodynamic Properties of Liquid Water: A General Approach to Improve Empirical Potentials

Sensitivity Analysis of Thermodynamic Properties of Liquid Water: A General Approach to Improve Empirical Potentials

Predicting helical segments in proteins by a helix-coil transition theory with parameters derived from a structural database of proteins

Time-Dependent Sensitivity Analysis of Biological Networks: Coupled MAPK and PI3K Signal Transduction Pathways

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