Tendwa Maureen Bilinga, Chebon-Bore Lorna, Lobb Kevin, Musyoka Thommas Mutemi, Tastan Bishop Özlem
Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Makhanda 6140, South Africa.
Department of Chemistry, Rhodes University, Makhanda 6140, South Africa.
Molecules. 2021 May 14;26(10):2929. doi: 10.3390/molecules26102929.
The dimeric dihydropyrimidine dehydrogenase (DPD), metalloenzyme, an adjunct anti-cancer drug target, contains highly specialized 4 × FeS clusters per chain. These clusters facilitate the catalysis of the rate-limiting step in the pyrimidine degradation pathway through a harmonized electron transfer cascade that triggers a redox catabolic reaction. In the process, the bulk of the administered 5-fluorouracil (5-FU) cancer drug is inactivated, while a small proportion is activated to nucleic acid antimetabolites. The occurrence of missense mutations in DPD protein within the general population, including those of African descent, has adverse toxicity effects due to altered 5-FU metabolism. Thus, deciphering mutation effects on protein structure and function is vital, especially for precision medicine purposes. We previously proposed combining molecular dynamics (MD) and dynamic residue network (DRN) analysis to decipher the molecular mechanisms of missense mutations in other proteins. However, the presence of FeS clusters in DPD poses a challenge for such in silico studies. The existing AMBER force field parameters cannot accurately describe the Fe center coordination exhibited by this enzyme. Therefore, this study aimed to derive AMBER force field parameters for DPD enzyme Fe centers, using the original Seminario method and the collation features Visual Force Field Derivation Toolkit as a supportive approach. All-atom MD simulations were performed to validate the results. Both approaches generated similar force field parameters, which accurately described the human DPD protein FeS cluster architecture. This information is crucial and opens new avenues for in silico cancer pharmacogenomics and drug discovery related research on 5-FU drug efficacy and toxicity issues.
二聚体二氢嘧啶脱氢酶（DPD）是一种金属酶，也是辅助抗癌药物靶点，每条链含有高度特殊的4×FeS簇。这些簇通过协调的电子传递级联促进嘧啶降解途径中限速步骤的催化，该级联引发氧化还原分解代谢反应。在此过程中，大部分施用的5-氟尿嘧啶（5-FU）抗癌药物被灭活，而一小部分被激活为核酸抗代谢物。在包括非洲裔在内的普通人群中，DPD蛋白发生错义突变会因5-FU代谢改变而产生不良毒性作用。因此，解读突变对蛋白质结构和功能的影响至关重要，特别是对于精准医学而言。我们之前提出结合分子动力学（MD）和动态残基网络（DRN）分析来解读其他蛋白质中错义突变的分子机制。然而，DPD中FeS簇的存在给此类计算机模拟研究带来了挑战。现有的AMBER力场参数无法准确描述该酶所呈现的Fe中心配位情况。因此，本研究旨在使用原始的塞米纳里奥方法，并以视觉力场推导工具包的整理功能作为辅助方法，推导DPD酶Fe中心的AMBER力场参数。进行全原子MD模拟以验证结果。两种方法都产生了相似的力场参数，准确描述了人DPD蛋白的FeS簇结构。这些信息至关重要，并为计算机癌症药物基因组学以及与5-FU药物疗效和毒性问题相关的药物发现研究开辟了新途径。
