Precise Prediction of Calpain Cleavage Sites and Their Aberrance Caused by Mutations in Cancer

Abstract

As a widespread post-translational modification of proteins, calpain-mediated cleavage regulates a broad range of cellular processes, including proliferation, differentiation, cytoskeletal reorganization, and apoptosis. The identification of proteins that undergo calpain cleavage in a site-specific manner is the necessary foundation for understanding the exact molecular mechanisms and regulatory roles of calpain-mediated cleavage. In contrast with time-consuming and labor-intensive experimental methods, computational approaches for detecting calpain cleavage sites have attracted wide attention due to their efficiency and convenience. In this study, we established a novel computational tool named DeepCalpain ( ) for predicting the potential calpain cleavage sites by adopting deep neural network and the particle swarm optimization algorithm. Through critical evaluation and comparison, DeepCalpain exhibited superior performance against other existing tools. Meanwhile, we found that protein interactions could enrich the calpain-substrate regulatory relationship. Since calpain-mediated cleavage was critical for cancer development and progression, we comprehensively analyzed the calpain cleavage associated mutations across 11 cancers with the help of DeepCalpain, which demonstrated that the calpain-mediated cleavage events were affected by mutations and heavily implicated in the regulation of cancer cells. These prediction and analysis results might provide helpful information to reveal the regulatory mechanism of calpain cleavage in biological pathways and different cancer types, which might open new avenues for the diagnosis and treatment of cancers.

An Atlas of Phosphorylation and Proteolytic Processing Events During Excitotoxic Neuronal Death Reveals New Therapeutic Opportunities

“…Based upon the limited data of confirmed calpain cleavage sites in protein substrates and results of peptide library studies to define the substrate specificity determinants near the cleavage sites in synthetic peptides (Cuerrier et al, 2005;Shinkai-Ouchi et al, 2016), a number of algorithms for prediction of calpain substrates and the cleavage sites were designed. The most notable algorithms include calCleaveMKL (duVerle and Mamitsuka, 2019), iProt-Sub (Song et al, 2019) , DeepCalpain (Liu et al, 2019) and GPS-CCD (Liu et al, 2011). Here, we demonstrated for the first time a high degree of conformity of amino acid preferences at the P6-P5' positions in both the potential calpain substrates in neurons and the in vitro peptide substrates of calpains 1 and 2 ( Figures 6B and 6C).…”

pCysMod: Prediction of Multiple Cysteine Modifications Based on Deep Learning Framework

“…Previously, we have developed several protein post-translational modification tools for enzyme-specific lysine acetylation ( Yu et al, 2020 ), calpain-specific cleavage site ( Liu et al, 2019 ), and S -glutathionylation site ( Li et al, 2020 ) prediction based on deep learning framework and particle swarm optimization (PSO) algorithm, which achieved significantly better performance than exiting tools. Traditional machine learning based method requires careful feature selection and scaling, which limited its performance.…”

RMDisease: a database of genetic variants that affect RNA modifications, with implications for epitranscriptome pathogenesis

“…Substantial efforts have been made to relate the genetic variants to their immediate biological consequences, including with regard to transcriptional regulation ( 4 , 5 ), post-transcriptional protein modification ( 6–12 ), RNA–protein interaction ( 13 ), calpain cleavage ( 14 ), ceRNA networks ( 15 ), polyadenylation ( 16 ) and RNA modifications ( 17 , 18 ). Most of these works were based on a widely adopted computational framework, i.e.…”