Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87544, United States.
Department of Computer Science, George Mason University, Fairfax, VA 22030, United States.
Bioinformatics. 2023 Nov 1;39(11). doi: 10.1093/bioinformatics/btad699.
The two strands of the DNA double helix locally and spontaneously separate and recombine in living cells due to the inherent thermal DNA motion. This dynamics results in transient openings in the double helix and is referred to as "DNA breathing" or "DNA bubbles." The propensity to form local transient openings is important in a wide range of biological processes, such as transcription, replication, and transcription factors binding. However, the modeling and computer simulation of these phenomena, have remained a challenge due to the complex interplay of numerous factors, such as, temperature, salt content, DNA sequence, hydrogen bonding, base stacking, and others.
We present pyDNA-EPBD, a parallel software implementation of the Extended Peyrard-Bishop-Dauxois (EPBD) nonlinear DNA model that allows us to describe some features of DNA dynamics in detail. The pyDNA-EPBD generates genomic scale profiles of average base-pair openings, base flipping probability, DNA bubble probability, and calculations of the characteristically dynamic length indicating the number of base pairs statistically significantly affected by a single point mutation using the Markov Chain Monte Carlo algorithm.
pyDNA-EPBD is supported across most operating systems and is freely available at https://github.com/lanl/pyDNA_EPBD. Extensive documentation can be found at https://lanl.github.io/pyDNA_EPBD/.
由于固有热 DNA 运动，DNA 双螺旋的两条链在活细胞中局部且自发地分离和重组。这种动力学导致双螺旋的瞬时开口，被称为“DNA 呼吸”或“DNA 泡”。形成局部瞬时开口的倾向在广泛的生物学过程中很重要，例如转录、复制和转录因子结合。然而，由于许多因素（如温度、盐含量、DNA 序列、氢键、碱基堆积等）的复杂相互作用，这些现象的建模和计算机模拟仍然是一个挑战。
我们提出了 pyDNA-EPBD，这是对扩展 Peyrard-Bishop-Dauxois（EPBD）非线性 DNA 模型的并行软件实现，使我们能够详细描述 DNA 动力学的一些特征。pyDNA-EPBD 使用马尔可夫链蒙特卡罗算法生成平均碱基对开口、碱基翻转概率、DNA 泡概率的基因组规模分布，并计算特征动态长度，该长度表示受单个点突变影响的碱基对数量统计上显著。
pyDNA-EPBD 可在大多数操作系统上使用，可在 https://github.com/lanl/pyDNA_EPBD 上获得。在 https://lanl.github.io/pyDNA_EPBD/ 上可以找到广泛的文档。
