iHyd-PseCp: Identify hydroxyproline and hydroxylysine in proteins by incorporating sequence-coupled effects into general PseAAC

Abstract

Protein hydroxylation is a posttranslational modification (PTM), in which a CH group in Pro (P) or Lys (K) residue has been converted into a COH group, or a hydroxyl group (−OH) is converted into an organic compound. Closely associated with cellular signaling activities, this type of PTM is also involved in some major diseases, such as stomach cancer and lung cancer. Therefore, from the angles of both basic research and drug development, we are facing a challenging problem: for an uncharacterized protein sequence containing many residues of P or K, which ones can be hydroxylated, and which ones cannot? With the explosive growth of protein sequences in the post-genomic age, the problem has become even more urgent. To address such a problem, we have developed a predictor called iHyd-PseCp by incorporating the sequence-coupled information into the general pseudo amino acid composition (PseAAC) and introducing the “Random Forest” algorithm to operate the calculation. Rigorous jackknife tests indicated that the new predictor remarkably outperformed the existing state-of-the-art prediction method for the same purpose. For the convenience of most experimental scientists, a user-friendly web-server for iHyd-PseCp has been established at http://www.jci-bioinfo.cn/iHyd-PseCp, by which users can easily obtain their desired results without the need to go through the complicated mathematical equations involved.

Numerical Characterization of Protein Sequences Based on the Generalized Chou’s Pseudo Amino Acid Composition

“…The feature analysis implies that the λ + 1 components beyond the amino acid composition play very important roles in the performance of the experiment. As shown in a series of recent publications (see, e.g., [58,[67][68][69][70][71][72]) in demonstrating new methods or approaches, user-friendly and publicly accessible web-servers will significantly enhance their impacts [73]. We will make efforts in our future work to further improve our method and provide a web-server for the new method presented.…”

iRNA-AI: identifying the adenosine to inosine editing sites in RNA sequences

“…It was successfully used to study signal peptide cleavage sites [32, 33], hydroxyproline and hydroxylysine sites [22, 34], methylation sites [35–37], nitrotyrosine sites [38, 39], carbonylation sites [19], phosphorylation sites [24], sumoylation sites [29], and protein-protein binding sites [40, 41]. According to Chou's scheme, a potential RNA A-I editing site sample can be generally expressed by ${boldnormalR}_{\xi }\left(\mathrm{double-struckA}\right)={\mathrm{normalN}}_{-\xi }{\mathrm{normalN}}_{-\left(\xi -1\right)}\cdots {\mathrm{normalN}}_{-2}{\mathrm{normalN}}_{-1}\mathbb{A}{\mathrm{normalN}}_{+1}{\mathrm{normalN}}_{+2}\cdots {\mathrm{normalN}}_{+\left(\xi -1\right)}{\mathrm{normalN}}_{+\xi }$ where the symbol $\mathrm{double-struckA}$ denotes the single nucleic acid code A (adenine), the subscript ξ is an integer, N – ξ represents the ξ-th upstream nucleotide from the center, the N + ξ the ξ-th downstream nucleotide, and so forth.…”

Predicting Protein–Protein Interaction Sites Using Sequence Descriptors and Site Propensity of Neighboring Amino Acids

“…Since user-friendly and publicly-accessible web-servers represent the future direction [54] for developing practically more useful predictors and will significantly enhance their impacts [55,56], we have provided a web-server for the new method presented in this paper, as done in many recent works [39,43,48,49,57,58,59,60]. The server, named PredPPIS, provides a graphical user interface for users to submit their sequences and receive the predictive results.…”