Hoda Anila, Berisha Bajram, Bixheku Xhiliola, Zanchi Fernando Berton
Department Animal Sciences, Agricultural University of Tirana, Albania.
Department of Animal Physiology & Immunology, Life Science Center Weihenstephan, TU Munich (TUM), Germany.
J Biomol Struct Dyn. 2024 Apr 24:1-17. doi: 10.1080/07391102.2024.2335295.
This study delves into the functional and structural implications of non-synonymous single nucleotide polymorphisms (nsSNPs) within the Prolactin Receptor (PRLR) gene. Thirteen deleterious nsSNPs were identified through bioinformatics tools, with SIFT predicting 168 out of 395 nsSNPs as detrimental, exhibiting tolerance index (TI) scores ranging from 0 to 0.05. Polyphen2 assigned likelihood scores >0.99 to all 13 nsSNPs, indicating high probability of harm, while Panther scores classified most nsSNPs as 'probably damaging', with specific mutations like W218R scoring 0.74, suggesting a higher impact. Stability analysis using DDG I-Mutant and DDG Mupro consistently predicted decreased stability for all mutations, with CUPSAT indicating mutations like V125G and W218R significantly decreasing stability. Structural analysis through DynaMut predicted destabilization for all mutations except L196I and L292H. MutPred2 highlighted structural alterations for all nsSNPs except L196I, L293V, R315W, and S353N. Domain analysis revealed key mutations within essential functional domains, with five nsSNPs located within Fibronectin type-III domains. Bayesian analysis through ConSurf identified 9 critical residues, with 11 nsSNPs exhibiting notably high conservation. STRING analysis unveiled a complex interaction network, indicating involvement in vital biological processes like lactation. Molecular dynamics (MD) simulations, spanning 100 nanoseconds, elucidated structural dynamics induced by detrimental missense SNPs. Post-translational modification (PTM) analysis identified specific mutations, such as R351, involved in methylation, while S353 was implicated in phosphorylation and glycosylation. These findings offer comprehensive insights into the molecular and phenotypic effects of deleterious nsSNPs in the PRLR gene, crucial for selective breeding.
本研究深入探讨了催乳素受体（PRLR）基因内非同义单核苷酸多态性（nsSNPs）的功能和结构影响。通过生物信息学工具鉴定出13个有害的nsSNPs，SIFT预测395个nsSNPs中有168个有害，其耐受指数（TI）得分在0到0.05之间。Polyphen2为所有13个nsSNPs赋予的似然得分>0.99，表明有害的可能性很高，而Panther得分将大多数nsSNPs分类为“可能有害”，如W218R等特定突变的得分为0.74，表明影响更大。使用DDG I-Mutant和DDG Mupro进行的稳定性分析一致预测所有突变的稳定性都会降低，CUPSAT表明V125G和W218R等突变会显著降低稳定性。通过DynaMut进行的结构分析预测，除L196I和L292H外，所有突变都会导致不稳定。MutPred2突出显示了除L196I、L293V、R315W和S353N之外的所有nsSNPs的结构改变。结构域分析揭示了关键功能域内的关键突变，有5个nsSNPs位于纤连蛋白III型结构域内。通过ConSurf进行的贝叶斯分析确定了9个关键残基，11个nsSNPs表现出显著的高保守性。STRING分析揭示了一个复杂的相互作用网络，表明其参与了泌乳等重要生物学过程。长达100纳秒的分子动力学（MD）模拟阐明了有害错义SNP诱导的结构动力学。翻译后修饰（PTM）分析确定了参与甲基化的特定突变，如R351，而S353与磷酸化和糖基化有关。这些发现为PRLR基因中有害nsSNPs的分子和表型效应提供了全面的见解，对选择性育种至关重要。
