Artificial intelligence and the analysis of cryo-EM data provide structural insight into the molecular mechanisms underlying LN-lamininopathies

被引:3
作者
Kulczyk, Arkadiusz W. [1 ,2 ]
机构
[1] Rutgers State Univ, Inst Quantitat Biomed, 174 Frelinghuysen Rd, Piscataway, NJ 08854 USA
[2] Rutgers State Univ, Dept Biochem & Microbiol, 75 Lipman Dr, New Brunswick, NJ 08901 USA
关键词
CONGENITAL MUSCULAR-DYSTROPHY; LAMA2 GENE ANALYSIS; MISSENSE MUTATIONS; N-GLYCOSYLATION; PHENOTYPE; LAMININS; NETWORK; DOMAIN; CHAIN;
D O I
10.1038/s41598-023-45200-5
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Laminins (Lm) are major components of basement membranes (BM), which polymerize to form a planar lattice on cell surface. Genetic alternations of Lm affect their oligomerization patterns and lead to failures in BM assembly manifesting in a group of human disorders collectively defined as Lm N-terminal domain lamininopathies (LN-lamininopathies). We have employed a recently determined cryo-EM structure of the Lm polymer node, the basic repeating unit of the Lm lattice, along with structure prediction and modeling to systematically analyze structures of twenty-three pathogenic Lm polymer nodes implicated in human disease. Our analysis provides the detailed mechanistic explanation how Lm mutations lead to failures in Lm polymerization underlining LN-lamininopathies. We propose the new categorization scheme of LN-lamininopathies based on the insight gained from the structural analysis. Our results can help to facilitate rational drug design aiming in the treatment of Lm deficiencies.
引用
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页数:15
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