Bird Eye View of Protein Subcellular Localization Prediction

Abstract

Proteins are made up of long chain of amino acids that perform a variety of functions in different organisms. The activity of the proteins is determined by the nucleotide sequence of their genes and by its 3D structure. In addition, it is essential for proteins to be destined to their specific locations or compartments to perform their structure and functions. The challenge of computational prediction of subcellular localization of proteins is addressed in various in silico methods. In this review, we reviewed the progress in this field and offered a bird eye view consisting of a comprehensive listing of tools, types of input features explored, machine learning approaches employed, and evaluation matrices applied. We hope the review will be useful for the researchers working in the field of protein localization predictions.

mRNA Trafficking in the Nervous System: A Key Mechanism of the Involvement of Activity-Regulated Cytoskeleton-Associated Protein (Arc) in Synaptic Plasticity

“…2 Neural Plasticity and posttranscriptional modifications are not homogeneously distributed in the cytoplasm, and this fact can be important for cellular functions and energy use. Subcellular localization of a protein may be reached by a mechanism dependent on the signal peptide (localization sequence) within this protein [36]. The other mechanism is ensured by the selective movement (trafficking), anchoring (docking), and localized translation of mRNA, which is crucial in many processes, including patterning of embryonic axes, asymmetric cell division, cell migration, and synaptic plasticity [35].…”

Computational methods for protein localization prediction

“…Another review mainly discusses web-based prediction tools for human protein subcellular localization [29] . General methods and tools for protein localization prediction are introduced in the reviews of [30] , [31] , [32] , [33] , which have a scope similar to ours. However, the most recent review in the literature [30] , [31] , [32] was published in 2014.…”

“…This review focuses on these new methods and tools in addition to previous representative methods. A less detailed review [33] was recently published. Compared to [33] , this review separates the introduction of features, algorithms, and tools in greater detail so readers can better understand their relationships.…”

“…A less detailed review [33] was recently published. Compared to [33] , this review separates the introduction of features, algorithms, and tools in greater detail so readers can better understand their relationships. Additionally, the applicability of the tools is considered, and only actively maintained tools are listed.…”

Improving Protein Subcellular Location Classification by Incorporating Three-Dimensional Structure Information

“…Most of the methods that were developed for the prediction of protein subcellular localizations employed amino acid sequences as the information source because the protein sequence data are abundant and easy to access [ 3 ]. The theoretical basis of the predictions is that one protein is transported into specific subcellular structure(s) according to its signal peptide, which is a short segment buried in the amino acid sequence.…”