From face to interface recognition: A differential geometric approach to distinguish DNA from RNA binding surfaces

Research output: Contribution to journalReview articlepeer-review

Abstract

Protein nucleic acid interactions play a critical role in all steps of the gene expression pathway. Nucleic acid (NA) binding proteins interact with their partners, DNA or RNA, via distinct regions on their surface that are characterized by an ensemble of chemical, physical and geometrical properties. In this study, we introduce a novel methodology based on differential geometry, commonly used in face recognition, to characterize and predict NA binding surfaces on proteins. Applying the method on experimentally solved three-dimensional structures of proteins we successfully classify double-stranded DNA (dsDNA) from single-stranded RNA (ssRNA) binding proteins, with 83 accuracy. We show that the method is insensitive to conformational changes that occur upon binding and can be applicable for de novo protein-function prediction. Remarkably, when concentrating on the zinc finger motif, we distinguish successfully between RNA and DNA binding interfaces possessing the same binding motif even within the same protein, as demonstrated for the RNA polymerase transcription-factor, TFIIIA. In conclusion, we present a novel methodology to characterize protein surfaces, which can accurately tell apart dsDNA from an ssRNA binding interfaces. The strength of our method in recognizing fine-tuned differences on NA binding interfaces make it applicable for many other molecular recognition problems, with potential implications for drug design.

Original languageEnglish
Pages (from-to)7390-7399
Number of pages10
JournalNucleic acids research
Volume39
Issue number17
DOIs
StatePublished - Sep 2011

All Science Journal Classification (ASJC) codes

  • Genetics

Fingerprint

Dive into the research topics of 'From face to interface recognition: A differential geometric approach to distinguish DNA from RNA binding surfaces'. Together they form a unique fingerprint.

Cite this