Facultad de Ciencias, Universidad Autónoma de Baja California, Ensenada, Baja California 22860, Mexico.
Facultad of Ingeniería, Arquitectura y Diseño, Universidad Autónoma de Baja California, Ensenada, Baja California 22860, Mexico.
Int J Mol Sci. 2019 May 19;20(10):2476. doi: 10.3390/ijms20102476.
Gap junction (GJ) channels in invertebrates have been used to understand cell-to-cell communication in vertebrates. GJs are a common form of intercellular communication channels which connect the cytoplasm of adjacent cells. Dysregulation and structural alteration of the gap junction-mediated communication have been proven to be associated with a myriad of symptoms and tissue-specific pathologies. Animal models relying on the invertebrate nervous system have exposed a relationship between GJs and the formation of electrical synapses during embryogenesis and adulthood. The modulation of GJs as a therapeutic and clinical tool may eventually provide an alternative for treating tissue formation-related diseases and cell propagation. This review concerns the similarities between innexins and human connexins from nucleotide and protein sequence level perspectives. It also sets forth evidence of computational techniques applied to the study of proteins, sequences, and molecular dynamics. Furthermore, we propose machine learning techniques as a method that could be used to study protein structure, gap junction inhibition, metabolism, and drug development.
缝隙连接(GJ)通道在无脊椎动物中被用于了解脊椎动物中的细胞间通讯。GJ 是连接相邻细胞细胞质的一种常见的细胞间通讯通道形式。缝隙连接介导的通讯的失调和结构改变已被证明与许多症状和组织特异性病理有关。依赖无脊椎动物神经系统的动物模型揭示了 GJ 与胚胎发生和成年期电突触形成之间的关系。作为治疗和临床工具的 GJ 调节最终可能为治疗与组织形成相关的疾病和细胞增殖提供替代方法。本综述涉及从核苷酸和蛋白质序列水平角度来看,连接蛋白和人连接蛋白之间的相似性。它还提出了应用于蛋白质、序列和分子动力学研究的计算技术的证据。此外,我们提出机器学习技术作为一种可用于研究蛋白质结构、间隙连接抑制、代谢和药物开发的方法。