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A MULTISCALE APPROACH TO SAMPLING NASCENT PEPTIDE CHAINS IN THE RIBOSOMAL EXIT TUNNEL

机译:在核糖体出口隧道中采样新生肽链的多尺度方法

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We present a new multiscale method that combines all-atom molecular dynamics with coarse-grained sampling, towards the aim of bridging two levels of physiology: the atomic scale of protein side chains and small molecules, and the huge scale of macromolecular complexes like the ribosome. Our approach uses all-atom simulations of peptide (or other ligand) fragments to calculate local 3D spatial potentials of mean force (PMF). The individual fragment PMFs are then used as a potential for a coarse-grained chain representation of the entire molecule. Conformational space and sequence space are sampled efficiently using generalized ensemble Monte Carlo. Here, we apply this method to the study of nascent polypeptides inside the cavity of the ribosome exit tunnel. We show how the method can be used to explore the accessible conformational and sequence space of nascent polypeptide chains near the ribosome peptidyl transfer center (PTC), with the eventual aim of understanding the basis of specificity for co-translational regulation. The method has many potential applications to predicting binding specificity and design, and is sufficiently general to allow even greater separation of scales in future work.
机译:我们提出了一种新的多尺度方法,将全原子分子动力学与粗粒化的采样相结合,旨在弥合两种水平的生理学:蛋白质侧链和小分子的原子标度,以及核糖体等大分子复合物的巨大大规模。我们的方法使用肽(或其他配体)片段的全原子仿真来计算平均力(PMF)的局部3D空间电位。然后将各个片段PMF用于整个分子的粗粒链表示的潜力。使用广义集合蒙特卡罗有效地采样构象空间和序列空间。在这里,我们将该方法应用于核糖体出口隧道腔内的新生多肽的研究。我们展示了如何用于探索核糖体肽基转移中心(PTC)附近的新生多肽链的可访问构象和序列空间,最终目的是理解共转规律的特异性的基础。该方法具有许多潜在的应用,以预测绑定特异性和设计,并且足够一般,以便在将来的工作中甚至更加分离尺度。

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