Hicks Celeste, Dhiman Akshima, Barrymore Chauntel, Goswami Tarun
Biomedical, Industrial and Human Factors Engineering, Wright State University, 3640 Col. Glen Hwy, Dayton, OH 45435, USA.
Boonshoft School of Medicine, Wright State University, 3640 Col. Glen Hwy, Dayton, OH 45435, USA.
Bioengineering (Basel). 2022 Oct 25;9(11):612. doi: 10.3390/bioengineering9110612.
This paper reviews the predictive capabilities of blood-based biomarkers to quantify traumatic brain injury (TBI). Biomarkers for concussive conditions also known as mild, to moderate and severe TBI identified along with post-traumatic stress disorder (PTSD) and chronic traumatic encephalopathy (CTE) that occur due to repeated blows to the head during one's lifetime. Since the pathways of these biomarkers into the blood are not fully understood whether there is disruption in the blood-brain barrier (BBB) and the time it takes after injury for the expression of the biomarkers to be able to predict the injury effectively, there is a need to understand the protein biomarker structure and other physical properties. The injury events in terms of brain and mechanics are a result of external force with or without the shrapnel, in the wake of a wave result in local tissue damage. Thus, these mechanisms express specific biomarkers kinetics of which reaches half-life within a few hours after injury to few days. Therefore, there is a need to determine the concentration levels that follow injury. Even though current diagnostics linking biomarkers with TBI severity are not fully developed, there is a need to quantify protein structures and their viability after injury. This research was conducted to fully understand the structures of 12 biomarkers by performing molecular dynamics simulations involving atomic movement and energies of forming hydrogen bonds. Molecular dynamics software, NAMD and VMD were used to determine and compare the approximate thermodynamic stabilities of the biomarkers and their bonding energies. Five biomarkers used clinically were S100B, GFAP, UCHL1, NF-L and tau, the kinetics obtained from literature show that the concentration values abruptly change with time after injury. For a given protein length, associated number of hydrogen bonds and bond energy describe a lower bound region where proteins self-dissolve and do not have long enough half-life to be detected in the fluids. However, above this lower bound, involving higher number of bonds and energy, we hypothesize that biomarkers will be viable to disrupt the BBB and stay longer to be modeled for kinetics for diagnosis and therefore may help in the discoveries of new biomarkers.
本文综述了基于血液的生物标志物对创伤性脑损伤(TBI)进行量化的预测能力。还确定了与脑震荡相关的生物标志物,即轻度、中度和重度TBI,以及创伤后应激障碍(PTSD)和慢性创伤性脑病(CTE),这些疾病是由于一生中头部反复受到撞击而发生的。由于这些生物标志物进入血液的途径尚未完全了解,血脑屏障(BBB)是否存在破坏以及损伤后生物标志物表达能够有效预测损伤所需的时间,因此有必要了解蛋白质生物标志物的结构和其他物理性质。从大脑和力学角度来看,损伤事件是由外力(有或没有弹片)引起的,随后会产生波动,导致局部组织损伤。因此,这些机制会表达特定的生物标志物动力学,其在损伤后数小时至数天内达到半衰期。因此,有必要确定损伤后的浓度水平。尽管目前将生物标志物与TBI严重程度相关联的诊断方法尚未完全开发出来,但仍有必要对损伤后蛋白质结构及其生存能力进行量化。本研究通过进行涉及原子运动和形成氢键能量的分子动力学模拟,以全面了解12种生物标志物的结构。使用分子动力学软件NAMD和VMD来确定和比较生物标志物的近似热力学稳定性及其结合能。临床上使用的五种生物标志物是S100B、GFAP、UCHL1、NF-L和tau,从文献中获得的动力学表明,损伤后浓度值随时间突然变化。对于给定的蛋白质长度,相关的氢键数量和键能描述了一个下限区域,在该区域蛋白质会自我溶解,且半衰期不够长,无法在体液中被检测到。然而,在这个下限之上,涉及更多的键和能量,我们假设生物标志物将能够破坏血脑屏障并停留更长时间,以便为诊断动力学进行建模,因此可能有助于发现新的生物标志物。