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The Effects Of Nucleotides On Muts-Dna Binding Kinetics Clarify The Role Of Muts Atpase Activity In Mismatch Repair, Manju Hingorani
The Effects Of Nucleotides On Muts-Dna Binding Kinetics Clarify The Role Of Muts Atpase Activity In Mismatch Repair, Manju Hingorani
Manju Hingorani
MutS protein initiates mismatch repair with recognition of a non-Watson-Crick base-pair or base insertion/deletion site in DNA, and its interactions with DNA are modulated by ATPase activity. Here, we present a kinetic analysis of these interactions, including the effects of ATP binding and hydrolysis, reported directly from the mismatch site by 2-aminopurine fluorescence. When free of nucleotides, the Thermus aquaticus MutS dimer binds a mismatch rapidly (k(ON)=3 x 10(6) M(-1) s(-1)) and forms a stable complex with a half-life of 10 s (k(OFF)=0.07 s(-1)). When one or both nucleotide-binding sites on the MutS*mismatch complex are occupied by ATP, the complex …
Contribution Of Msh2 And Msh6 Subunits To The Asymmetric Atpase And Dna Mismatch Binding Activities Of Saccharomyces Cerevisiae Msh2–Msh6 Mismatch Repair Protein, Manju Hingorani
Manju Hingorani
Previous analyses of both Thermus aquaticus MutS homodimer and Saccharomyces cerevisiae Msh2–Msh6 heterodimer have revealed that the subunits in these protein complexes bind and hydrolyze ATP asymmetrically, emulating their asymmetric DNA binding properties. In the MutS homodimer, one subunit (S1) binds ATP with high affinity and hydrolyzes it rapidly, while the other subunit (S2) binds ATP with lower affinity and hydrolyzes it at an apparently slower rate. Interaction of MutS with mismatched DNA results in suppression of ATP hydrolysis at S1—but which of these subunits, S1 or S2, makes specific contact with the mismatch (e.g., base stacking by a conserved …
Model-Based Global Analysis Of Heterogeneous Experimental Data Using Gfit, Manju Hingorani
Model-Based Global Analysis Of Heterogeneous Experimental Data Using Gfit, Manju Hingorani
Manju Hingorani
Regression analysis is indispensible for quantitative understanding of biological systems and for developing accurate computational models. By applying regression analysis, one can validate models and quantify components of the system, including ones that cannot be observed directly. Global (simultaneous) analysis of all experimental data available for the system produces the most informative results. To quantify components of a complex system, the dataset needs to contain experiments of different types performed under a broad range of conditions. However, heterogeneity of such datasets complicates implementation of the global analysis. Computational models continuously evolve to include new knowledge and to account for novel …