Abstract
Voltage-gated K+ channel (VKC) plays important roles in biology procession, especially in nervous system. Different subfamilies of VKCs have different biological functions. Thus, knowing VKCs’ subfamilies has become a meaningful job because it can guide the direction for the disease diagnosis and drug design. However, the traditional wet-experimental methods were costly and time-consuming. It is highly desirable to develop an effective and powerful computational tool for identifying different subfamilies of VKCs. In this study, a predictor, called iVKC-OTC, has been developed by incorporating the optimized tripeptide composition (OTC) generated by feature selection technique into the general form of pseudo-amino acid composition to identify six subfamilies of VKCs. One of the remarkable advantages of introducing the optimized tripeptide composition is being able to avoid the notorious dimension disaster or over fitting problems in statistical predictions. It was observed on a benchmark dataset, by using a jackknife test, that the overall accuracy achieved by iVKC-OTC reaches to 96.77% in identifying the six subfamilies of VKCs, indicating that the new predictor is promising or at least may become a complementary tool to the existing methods in this area. It has not escaped our notice that the optimized tripeptide composition can also be used to investigate other protein classification problems.
Highlights
Ion channels located in the surface of cell membrane can maintain the balance of cell microenvironment by selectively penetrating ions and organic molecules in and out of cells
The raw dataset of voltage-gated K+ channel (VKC) were extracted from the updated Voltage-gated K+ Channel Database (VKCDB) [2] and filtered by VKCPred [5]
If the primary structure of a VKC contains ambiguous residues, such as “B”, “X”, and “Z”, the VKC will be removed; Secondly, if the sequence is fragment of other proteins, it will be excluded because its information is redundant and fragmentary; Thirdly, to objectively evaluate the proposed predictor, the CD-HIT software [7] was used to remove highly similar sequences by setting the cutoff of sequence identity to 60%
Summary
Ion channels located in the surface of cell membrane can maintain the balance of cell microenvironment by selectively penetrating ions and organic molecules in and out of cells. The voltage-gated K+ channel (VKC), which is the largest family of K+ channels, controls the movement of K+ under the stimulation of voltage changes in the cell's membrane potential. During action potentials, they play crucial roles in returning the depolarized cell to a resting state [2]. According to the N- and C-terminal domains, VKCs can be grouped into different subfamilies. Proposed a dipeptide-based method to predict five subfamilies of VKCs. Subsequently, Chen and Lin [5]. According to a comprehensive review [6], to establish a really useful statistical predictor for VKC subfamily prediction, an objective benchmark dataset was constructed. We established a user-friendly web-server for the predictor
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