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Preferential interactions between small solutes and the protein backbone: a computational analysis.

ABSTRACT: To improve our understanding of the effects of small solutes on protein stability, we conducted atomistic simulations to quantitatively characterize the interactions between two broadly used small solutes, urea and glycine betaine (GB), and a triglycine peptide, which is a good model for a protein backbone. Multiple solute concentrations were analyzed, and each solute-peptide-water ternary system was studied with approximately 200-300 ns of molecular dynamics simulations with the CHARMM force field. The comparison between calculated preferential interaction coefficients (Gamma(23)) and experimentally measured values suggests that semiquantitative agreement with experiments can be obtained if care is exercised to balance interactions among the solute, protein, and water. On the other hand, qualitatively incorrect (i.e., wrong sign in Gamma(23)) results can be obtained if a solute model is constructed by directly taking parameters for chemically similar groups from an existing force field. Such sensitivity suggests that small solute thermodynamic data can be valuable in the development of accurate force field models of biomolecules. Further decomposition of Gamma(23) into group contributions leads to additional insights regarding the effects of small solutes on protein stability. For example, use of the CHARMM force field predicts that urea preferentially interacts with not only amide groups in the peptide backbone but also aliphatic groups, suggesting a role for these interactions in urea-induced protein denaturation; quantitatively, however, it is likely that the CHARMM force field overestimates the interaction between urea and aliphatic groups. The results with GB support a simple thermodynamic model that assumes additivity of preferential interaction between GB and various biomolecular surfaces.

SUBMITTER: Ma L

PROVIDER: S-EPMC3639130 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature

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Preferential interactions between small solutes and the protein backbone: a computational analysis.

Ma Liang L Pegram Laurel L Record M T MT Cui Qiang Q

Biochemistry 20100301 9

To improve our understanding of the effects of small solutes on protein stability, we conducted atomistic simulations to quantitatively characterize the interactions between two broadly used small solutes, urea and glycine betaine (GB), and a triglycine peptide, which is a good model for a protein backbone. Multiple solute concentrations were analyzed, and each solute-peptide-water ternary system was studied with approximately 200-300 ns of molecular dynamics simulations with the CHARMM force fi ...[more]

PMID: 20121154

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Project description:Serotype O157:H7, an enterohemorrhagic Escherichia coli (EHEC), is known to cause gastrointestinal and systemic illnesses ranging from diarrhea and hemorrhagic colitis to potentially fatal hemolytic uremic syndrome. Specific genetic factors like ompA, nsrR, and LEE genes are known to play roles in EHEC pathogenesis. However, these factors are not specific to EHEC and their presence in several non-pathogenic strains indicates that additional factors are involved in pathogenicity. We propose a comprehensive effort to screen for such potential genetic elements, through investigation of biomolecular interactions between E. coli and their host. In this work, an in silico investigation of the protein-protein interactions (PPIs) between human cells and four EHEC strains (viz., EDL933, Sakai, EC4115, and TW14359) was performed in order to understand the virulence and host-colonization strategies of these strains. Potential host-pathogen interactions (HPIs) between human cells and the "non-pathogenic" E. coli strain MG1655 were also probed to evaluate whether and how the variations in the genomes could translate into altered virulence and host-colonization capabilities of the studied bacterial strains. Results indicate that a small subset of HPIs are unique to the studied pathogens and can be implicated in virulence. This subset of interactions involved E. coli proteins like YhdW, ChuT, EivG, and HlyA. These proteins have previously been reported to be involved in bacterial virulence. In addition, clear differences in lineage and clade-specific HPI profiles could be identified. Furthermore, available gene expression profiles of the HPI-proteins were utilized to estimate the proportion of proteins which may be involved in interactions. We hypothesized that a cumulative score of the ratios of bound:unbound proteins (involved in HPIs) would indicate the extent of colonization. Thus, we designed the Host Colonization Index (HCI) measure to determine the host colonization potential of the E. coli strains. Pathogenic strains of E. coli were observed to have higher HCIs as compared to a non-pathogenic laboratory strain. However, no significant differences among the HCIs of the two pathogenic groups were observed. Overall, our findings are expected to provide additional insights into EHEC pathogenesis and are likely to aid in designing alternate preventive and therapeutic strategies.

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Preferential interactions between small solutes and the protein backbone: a computational analysis.

Publications

Preferential interactions between small solutes and the protein backbone: a computational analysis.

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