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Updated: Aug 6, 2026

Analyzing and Building Nucleic Acid Structures with 3DNA
Published on: April 26, 2013
Structural Modeling of Protein-DNA Interactions Underlying Genome Copy Number Variation in Nanoviruses
Aamir Lal1,2, Myeonghwan Kwak1,2, Muhammad Amir Qureshi1,2
1Department of Plant Medicals, Gyeongkuk National University, Andong 36729, Korea.
Abstract:
Multipartite nanoviruses possess multiple segmented genomes that accumulate at unequal levels during infection, giving rise to dynamic genome formulas. Although the replication of all segments relies on a common replication-associated protein (Rep), the molecular basis underlying segment-specific differences in genome abundance remains poorly understood. Here, we investigated whether protein-DNA interactions at conserved cis-regulatory elements are associated with this variability by focusing on the intergenic region (IR) of segment S of milk vetch dwarf virus (MDV). We used a structure-based computational approach to analyze interactions between the MDV S-IR and Rep or movement proteins (MPs) from MDV and faba bean necrotic yellows virus under a consistent computational framework. Molecular docking, molecular dynamics simulations, and molecular mechanics/generalized Born surface area-based interaction energy analyses showed that all complexes formed stable interactions with the MDV S-IR. ΔG bind values were broadly comparable across systems, whereas differences in interaction persistence, structural stability, and residue-level contributions were observed between Rep- and MP-containing complexes. In particular, Rep-IR interactions exhibited more consistent and distributed interaction patterns, while MP-IR interactions showed greater variability and more localized contacts. These interaction features were more consistent with previously reported MDV DNA-S abundance trends than docking geometry alone. Together, these findings provide a structural framework to interpret MDV DNA-S abundance patterns in a comparative and hypothesis-generating context rather than as direct evidence of causal regulation.
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