TY - JOUR

T1 - Novel high-risk missense mutations identification in FAT4 gene causing Hennekam syndrome and Van Maldergem syndrome 2 through molecular dynamics simulation

AU - Shinwari, Khyber

AU - Rehman, Hafiz Muzzammel

AU - Xiao, Ningkun

AU - Guojun, Liu

AU - Khan, Muhammad Ajmal

AU - Bolkov, Mikhail A.

AU - Tuzankina, Irina A.

AU - Chereshnev, Valery A.

N1 - The research funding from the Ministry of Science and Higher Education of the Russian Federation (Ural Federal University Program of Development within the Priority-2030 Program) is gratefully acknowledged.

PY - 2023/1/1

Y1 - 2023/1/1

N2 - Hennekam syndrome (HS) is an autosomal recessive disease in the pathogenesis of which lymphangiectasia and lymphedema plays a key role. HS is associated with mutations in CCBE1, FAT4, and ADAMTS3 proteins that somehow affect the activation of the primary lymphangiogenic growth factor VEGF-C. We used several in silico methods to test this theory. According to NCBI, FAT4 gene contains 3,343 non-synonymous SNPs, of which 298 were predicted to be deleterious using SIFT and Polyphen2. These 298 SNPs were further studied using various mutation prediction tools. Our results showed that eleven nsSNPs (D2978G, V986D, Y1912C, R4799C, D1022G, G4786R, D2439E, E2426Q, R4643C, N1309I, and Y2909H) detected by these tools are deleterious. Additionally, three mutations in FAT4 gene (rs12650153, rs1567047, and rs1039808) in patient suspected with HS were discovered through candidate variant filtering of whole-exome sequencing, and in silico study of these mutations revealed that these are highly destabilizing the protein structure and function. Using molecular dynamics simulation (MDS) we focused on the mutations (11 mutations predicted by our insilco study, 3 reported in the patient and 5 already published mutations for HS and VMS), while one mutation (G4786R) was detected in the MPDZ domain. The RMSD and RMSF supports the destability of mutant protein compared to wild type. The mutations found in this cohort of studies have not previously been reported for HS. These mutations may contribute to better understanding of disease predisposition associated with FAT4 Cadherin-like domain activation and further aid to effective approaches for diagnosis and treatment of the disorder.

AB - Hennekam syndrome (HS) is an autosomal recessive disease in the pathogenesis of which lymphangiectasia and lymphedema plays a key role. HS is associated with mutations in CCBE1, FAT4, and ADAMTS3 proteins that somehow affect the activation of the primary lymphangiogenic growth factor VEGF-C. We used several in silico methods to test this theory. According to NCBI, FAT4 gene contains 3,343 non-synonymous SNPs, of which 298 were predicted to be deleterious using SIFT and Polyphen2. These 298 SNPs were further studied using various mutation prediction tools. Our results showed that eleven nsSNPs (D2978G, V986D, Y1912C, R4799C, D1022G, G4786R, D2439E, E2426Q, R4643C, N1309I, and Y2909H) detected by these tools are deleterious. Additionally, three mutations in FAT4 gene (rs12650153, rs1567047, and rs1039808) in patient suspected with HS were discovered through candidate variant filtering of whole-exome sequencing, and in silico study of these mutations revealed that these are highly destabilizing the protein structure and function. Using molecular dynamics simulation (MDS) we focused on the mutations (11 mutations predicted by our insilco study, 3 reported in the patient and 5 already published mutations for HS and VMS), while one mutation (G4786R) was detected in the MPDZ domain. The RMSD and RMSF supports the destability of mutant protein compared to wild type. The mutations found in this cohort of studies have not previously been reported for HS. These mutations may contribute to better understanding of disease predisposition associated with FAT4 Cadherin-like domain activation and further aid to effective approaches for diagnosis and treatment of the disorder.

UR - http://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=85146450575

U2 - 10.1016/j.imu.2023.101160

DO - 10.1016/j.imu.2023.101160

M3 - Article

VL - 37

JO - Informatics in Medicine Unlocked

JF - Informatics in Medicine Unlocked

SN - 2352-9148

M1 - 101160

ER -