Relationship between a point mutation S97C in CK1δ protein and its affect on ATP-binding affinity

Abstract

CK1δ (Casein kinase I isoform delta) is a member of CK1 kinase family protein that mediates neurite outgrowth and the function as brain-specific microtubule-associated protein. ATP binding kinase domain of CK1δ is essential for regulating several key cell cycle signal transduction pathways. Mutation in CK1δ protein is reported to cause cancers and affects normal brain development. S97C mutation in kinase domain of CK1δ protein has been involved to induce breast cancer and ductal carcinoma. We performed molecular docking studies to examine the effect of this mutation on its ATP-binding affinity. Further, we conducted molecular dynamics simulations to understand the structural consequences of S97C mutation over the kinase domain of CK1δ protein. Docking results indicated the loss of ATP-binding affinity of mutant structure, which were further rationalized by molecular dynamics simulations, where a notable loss in 3-D conformation of CK1δ kinase domain was observed in mutant as compared to native. Our results explained the underlying molecular mechanism behind the observed cancer associated phenotype caused by S97C mutation in CK1δ protein.

Optimized 4,5-Diarylimidazoles as Potent/Selective Inhibitors of Protein Kinase CK1δ and Their Structural Relation to p38α MAPK

“…Among them, isoforms δ and ε display the highest consensus, with a 98% sequence identity within their catalytic domain and at least 40% homology within their autoregulatory C-terminal domains [ 2 , 3 , 4 , 5 ]. Pathophysiologically, identification of mutations within the coding region of CK1δ as well as deregulation of CK1δ expression and/or activity levels as important determinants in development and progression of severe human disorders such as Alzheimer’s disease (AD) [ 2 , 6 , 7 , 8 ], amyotrophic lateral sclerosis (ALS) [ 9 ], familial advanced sleep phase syndrome (FASPS) [ 10 ], and cancer [ 2 , 5 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ] has dramatically increased interest in the development of potent and selective small molecule kinase inhibitors for both therapeutic approaches and basic research. However, the existence of paralogous CK1 isoforms that possess similar, different, or even opposite physiological and pathophysiological implications render the design of suitable candidate molecules that target CK1δ in an ideally isoform-dependent manner enormously difficult.…”

In SilicoScreening and Molecular Dynamics Simulation of Disease-Associated nsSNP in TYRP1 Gene and Its Structural Consequences in OCA3

“…Several research articles have stated is effectiveness in identifying the deleterious and disease-associated mutations, thus predicting the pathogenic nsSNPs in correlation to their functional and structural damaging properties [25–28]. Computational studies have previously provided an efficient platform for evaluation and analysis of genetic mutations for their pathological consequences and in determining their underlying molecular mechanism [27–33]. Moreover the conformational changes in the 3D structure of the protein account for the changes in its time dependent physiological affinities and various biochemical pathway alterations [34–37].…”

Using Large-Scale Genomics Data to Identify Driver Mutations in Lung Cancer: Methods and Challenges

“…These short simulations are generally utilized to confirm biochemical data and gain further understanding of the structural consequences of the identified mutation. As these simulations are only short, the information gained can range from as little as the position of the mutations in relation of other regions of the protein [60] and movement of key regions of the structure [61] up to changes in binding affinities of key substrates [59]. All of this information can help to understand the potential impact the mutation is having on the protein in question.…”

“…These typically focus on biochemically significant mutations that have either been published previously [58,59] or are analyzed in vitro/in vivo within the study itself [60,61]. These short simulations are generally utilized to confirm biochemical data and gain further understanding of the structural consequences of the identified mutation.…”