揭示致病性错义突变对相应蛋白质的分子效应对于开发治疗解决方案至关重要。这对于单基因疾病尤其重要,因为,对于大多数人来说,没有可用的治疗方法,虽然通常,治疗应在早期发展阶段提供。这需要低成本的快速靶向药物开发。这里,我们报告了一个更新的单基因疾病数据库(MOGEDO),其中包括768个蛋白质和相应的2559个致病性和1763个良性突变,以及相应蛋白质的功能分类。使用数据库和各种预测折叠自由能变化(ΔΔG)的计算工具,我们证明,平均而言,70%的致病病例导致蛋白质稳定性下降。如此大的分数表明人们应该着眼于对稳定突变蛋白结构的小分子进行计算机筛选。我们强调,ΔΔG的知识是必不可少的,因为人们想要开发补偿ΔΔG的稳定剂,但不要让蛋白质过度稳定,因为过度稳定的蛋白质可能是功能失调的。我们证明,通过使用ΔΔG和预测的突变位点的溶剂暴露,人们可以开发出一种预测方法来区分致病性突变和良性突变,其成功率甚至优于一些主要的致病性预测因子。此外,与其他突变相比,疏水-疏水突变在折叠自由能变化与致病性之间具有更强的相关性。此外,涉及Cys的突变,Gly,Arg,Trp,和Tyr氨基酸被任何其他氨基酸取代更有可能是致病性的。为了便于进一步检测致病突变,上述768种蛋白质中的野生型氨基酸突变为其他19个残基(14,847,817个突变),用SAAFEC-SEQ计算ΔΔG,和5,506,051个突变被预测为致病性。
Revealing the molecular effect that pathogenic missense mutations have on the corresponding protein is crucial for developing therapeutic solutions. This is especially important for monogenic diseases since, for most of them, there is no treatment available, while typically, the treatment should be provided in the early development stages. This requires fast targeted drug development at a low cost. Here, we report an updated database of monogenic disorders (MOGEDO), which includes 768 proteins and the corresponding 2559 pathogenic and 1763 benign mutations, along with the functional classification of the corresponding proteins. Using the database and various computational tools that predict folding free energy change (ΔΔG), we demonstrate that, on average, 70% of pathogenic cases result in decreased protein stability. Such a large fraction indicates that one should aim at in silico screening for small molecules stabilizing the structure of the mutant protein. We emphasize that knowledge of ΔΔG is essential because one wants to develop stabilizers that compensate for ΔΔG, but do not make protein over-stable, since over-stable protein may be dysfunctional. We demonstrate that, by using ΔΔG and predicted solvent exposure of the mutation site, one can develop a predictive method that distinguishes pathogenic from benign mutations with a success rate even better than some of the leading pathogenicity predictors. Furthermore, hydrophobic-hydrophobic mutations have stronger correlations between folding free energy change and pathogenicity compared with others. Also, mutations involving Cys, Gly, Arg, Trp, and Tyr amino acids being replaced by any other amino acid are more likely to be pathogenic. To facilitate further detection of pathogenic mutations, the wild type of amino acids in the 768 proteins mentioned above was mutated to other 19 residues (14,847,817 mutations), the ΔΔG was calculated with SAAFEC-SEQ, and 5,506,051 mutations were predicted to be pathogenic.