估计用放射性核素离子处理后蛋白质的结合

IF 2.9 3区 化学 Q3 CHEMISTRY, PHYSICAL
Ran Friedman
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引用次数: 0

摘要

几种放射性同位素被用于癌症治疗。223Ra以RaCl2盐的形式存在,90Y以微球粒子的形式存在。如果离子放射性核素是游离的,它们就有可能与蛋白质结合,而不是与内源性离子结合,干扰它们的活性,并由它们运输。在本研究中,使用计算方法来估计Y3+, Ra2+和Pb2+ (207Pb是223Ra的衰变产物)对蛋白质的结合亲和力,而不是它们的天然辅因子Ca2+和Mn2+。Y3+被发现与具有取代Ca2+和某种程度上也取代Mn2+的能力的蛋白质紧密结合。Ra2+不与所研究的蛋白结合,但Pb2+可以在Ca2+结合蛋白中取代Ca2+。最近发现的一种配位化合物对223Ra具有高选择性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating protein binding upon treatment with radionuclide ions
Several types of radioactive isotopes are used for cancer treatment. While most are embedded in chelating agents, 223Ra is given as RaCl2 salt and 90Y in microspherical particles. If ionic radionuclides are free, they have the potential to bind to proteins instead of their endogenous ions, interfere with their activity and be transported by them. In this study, a computational approach was used to estimate the binding affinities of Y3+ , Ra2+ and Pb2+ (207Pb is the decay product of 223Ra) to proteins, instead of their native cofactors Ca2+ and Mn2+ . Y3+ was found to bind strongly to proteins with the ability to replace Ca2+ and to some degree also Mn2+ . Ra2+ does not bind to the studied proteins but Pb2+ can replace Ca2+ in Ca2+ binding proteins. A recently identified coordination compound was found to be highly selective for 223Ra.
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来源期刊
Physical Chemistry Chemical Physics
Physical Chemistry Chemical Physics 化学-物理:原子、分子和化学物理
CiteScore
5.50
自引率
9.10%
发文量
2675
审稿时长
2.0 months
期刊介绍: Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.
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