Multiple protein-DNA interfaces unravelled by evolutionary information, physico-chemical and geometrical properties

Abstract

Interactions between proteins and nucleic acids are at the heart of many essential biological processes. Despite increasing structural information about how these interactions may take place, our understanding of the usage made of protein surfaces by nucleic acids is still very limited. This is in part due to the inherent complexity associated to protein surface deformability and evolution. In this work, we present a method that contributes to decipher such complexity by predicting protein-DNA interfaces and characterizing their properties. It relies on three biologically and physically meaningful descriptors, namely evolutionary conservation, physico-chemical properties and surface geometry. We carefully assessed its performance on several hundreds of protein structures and compared it to several machinelearning state-of-the-art methods. Our approach achieves a higher sensitivity compared to the other methods, with a similar precision. Importantly, we show that it is able to unravel 'hidden' binding sites by applying it to unbound protein structures and to proteins binding to DNA via multiple sites and in different conformations. It is also applicable to the detection of RNA-binding sites, without significant loss of performance. This confirms that DNA and RNA-binding sites share similar properties. Our method is implemented as a fully automated tool, JET 2 DNA , freely accessible at: http://www.lcqb.upmc.fr/JET2DNA. We also provide a new dataset of 187 protein-DNA complex structures, along with a subset of 82 associated unbound structures. The set represents the largest body of high-resolution crystallographic structures of protein-DNA complexes, use biological protein assemblies as DNA-binding units, and covers all major types of protein-DNA interactions.

From complete cross-docking to partners identification and binding sites predictions

“…In the past years, a lot of effort has been dedicated to describe the way in which proteins interact and, in particular, to characterise their interfaces. Depending on the type and function of the interaction, these may be evolutionary conserved, display peculiar physico-chemical properties or adopt an archetypal geometry [10][11][12][13][14][15][16][17][18][19][20]. For example, DNA-binding sites are systematically enriched in positively charged residues [10] and antigens are recognized by highly protruding loops [12].…”

“…Depending on the type and function of the interaction, these may be evolutionary conserved, display peculiar physico-chemical properties or adopt an archetypal geometry [10][11][12][13][14][15][16][17][18][19][20]. For example, DNA-binding sites are systematically enriched in positively charged residues [10] and antigens are recognized by highly protruding loops [12]. Such properties can be efficiently exploited toward an accurate detection of protein interfaces [10][11][12][21][22][23][24][25][26][27].…”

“…For example, DNA-binding sites are systematically enriched in positively charged residues [10] and antigens are recognized by highly protruding loops [12]. Such properties can be efficiently exploited toward an accurate detection of protein interfaces [10][11][12][21][22][23][24][25][26][27]. However, the large scale assessment of predicted interfaces is problematic as our knowledge of protein surface usage by multiple partners is still very limited [23].…”

Directed co-evolution of interacting protein–peptide pairs by compartmentalized two-hybrid replication (C2HR)

“…We have described facile detection of protein–peptide interactions through coupling to enzymatic activity of a thermostable nucleic acid polymerase. Whilst we have exemplified using the Stoffel fragment of Taq polymerase, evolutionary conservation of protein–nucleic acid interaction mechanisms ( 29 , 30 ) suggests that other families and classes of polymerase (e.g., DNA/RNA dependent RNA polymerase) could potentially be configured to work in C2HR. As shown, E. coli cells co-expressing a protein–peptide pair can be added directly into a PCR tube and interaction validated by assessing amplicon yield after thermal cycling.…”

HOPMA: Boosting Protein Functional Dynamics with Colored Contact Maps

“…89−91 ■ MATERIALS AND METHODS Data Sets. We considered four reference protein benchmark sets, namely the iMod benchmark, 92 the HR-PDNA187 benchmark, 93 the Protein−protein Docking Benchmark v5 (PPDBv5), 94 and the data set reported in Sfriso et al 90 (Table 1). We used the iMod benchmark as the validation set and the other benchmarks as testing sets.…”