In the ubiquitin-proteasome system, E3 ubiquitin ligase (E3s for short) selectively recognize and bind specific regions of their substrate proteins. Sequence motifs whose sites are bound by E3 ubiquitin ligases are called degrons. Because much remains unclear about the relationship between substrate proteins of E3s and their binding sites, there is a need to computationally identify such binding sites from the substrate proteins. For this motif identification problem, in our previous works, we have proposed a series of collapsed Gibbs sampling algorithms, called DegSampler1 and DegSampler2, both of which use position-specific prior information. In this work, we propose a new collapsed Gibbs sampling algorithm, called DegSampler3, by integrating intra-motif pair-wise dependency model into the posterior probability distribution of DegSampler2. In our preliminary experiments, we found that DegSampler3 has the ability of finding more various degron sites than DegSampler2 while keeping the prediction accuracy almost the same as that of the previous method, DegSampler2.