Lecture 2 Thermodynamic prediction and chemical/enzymatic probing of RNA structure Thermodynamic prediction MFOLD algorithm dynamic algorithm energy matrix vs traceback bp scoring via n.n. Turner rules other factors - loop size, tetraloops, etc parameters DNA vs RNA circular vs linear temperature max number of sequences to examine p - how different must they be? energy cut-off bp specifications/exclusions output files scoring matrix connect files graphics files colorization by frequency of occurance When this approach is useful small (<100) RNAs or discrete substructures as a source of reasonable structures for beginning CSA w/ probing where you only have a single sequence works best with thermophilic RNAs unalignable SELEX products examples D.radiodurans P D.radiodurans P P8 E1 RNA weaknesses long sequences pseudoknots large loops, esp. internal loops details high A+U or G+C sequences Chemical & enzymatic probing principle common probes (TABLE) enzymes RNase U2 - unpaired G RNase T1 - unpaired A>G>>C>U S1 nuclease - unpaired N RNase V1 - stacked (paired?) N chemicals DMS (dimethylsulfate) - A(N1), C(N3), G(N7) CMCT - G(N1), U(N3) DEPC (diethylpyrocarbonate) - A(N7) kethoxal - G(N1), G(N2) ENU (ethylnitrosourea) - any accessible P Fe-EDTA (hydroxide radicals) - ribose Pb++ - ribose-P in metal-binding sites examples from paper DMS footprints from Connie Yarian weaknesses MUST use at <1 cleavage per molecule steric hinderance specificities not very defined interpretation difficult strengths physiological conditions best at identifying CHANGES in structure or footprints can be made quantitative, e.g. to derive binding constants can be used with homologous seqs from different organisms to ID important results Combination for prediction of structure from a single or a few sequences example - E1 RNA, pVX virus 5' end