| Literature DB >> 26477260 |
Narin S Tangprasertchai1, Xiaojun Zhang1, Yuan Ding1, Kenneth Tham1, Remo Rohs2, Ian S Haworth3, Peter Z Qin4.
Abstract
The technique of site-directed spin labeling (SDSL) provides unique information on biomolecules by monitoring the behavior of a stable radical tag (i.e., spin label) using electron paramagnetic resonance (EPR) spectroscopy. In this chapter, we describe an approach in which SDSL is integrated with computational modeling to map conformations of nucleic acids. This approach builds upon a SDSL tool kit previously developed and validated, which includes three components: (i) a nucleotide-independent nitroxide probe, designated as R5, which can be efficiently attached at defined sites within arbitrary nucleic acid sequences; (ii) inter-R5 distances in the nanometer range, measured via pulsed EPR; and (iii) an efficient program, called NASNOX, that computes inter-R5 distances on given nucleic acid structures. Following a general framework of data mining, our approach uses multiple sets of measured inter-R5 distances to retrieve "correct" all-atom models from a large ensemble of models. The pool of models can be generated independently without relying on the inter-R5 distances, thus allowing a large degree of flexibility in integrating the SDSL-measured distances with a modeling approach best suited for the specific system under investigation. As such, the integrative experimental/computational approach described here represents a hybrid method for determining all-atom models based on experimentally-derived distance measurements.Entities:
Keywords: DEER; DNA; EPR; Hybrid models; Integrative modeling; Protein–DNA binding; RNA; Site-directed spin labeling; Solution-state structure
Mesh:
Substances:
Year: 2015 PMID: 26477260 PMCID: PMC4641853 DOI: 10.1016/bs.mie.2015.07.007
Source DB: PubMed Journal: Methods Enzymol ISSN: 0076-6879 Impact factor: 1.600