In Silico Plasticity Ceiling Mapping of the MERS-CoV Nucleocapsid SR-Linker (aa 181 - 248): CPS-Guided Boundary Instantiation Reveals Structural Constraints That Block Autonomous Backbone Optimization

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Authors: Tahir Bhatti
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Abstract

This dataset documents in-silico boundary mapping of the MERS-CoV nucleocapsid (N) gene's sole permissive zone that is the SR-linker (aa 181-248) using Codon Permissiveness Score (CPS) constraints derived from 1,746 global isolates (Zenodo 10.5281/zenodo.18209279). We computationally instantiate four theoretical enhancement vectors at the absolute viable limit permitted by purifying selection: (1) phase separation via S/T expansion, (2) nuclear localization signal (NLS) gain via K/R enrichment, (3) weak IFN antagonism via phospho-mimetic D/E substitutions, (4) silent codon optimization for human adaptation. Critically, the SR-linker's architecture permissive residues (σ ≥ 0.15) interspersed with constrained "guardrails" (σ < 0.15) structurally blocks contiguous homopolymer expansion and dense basic residue clustering, permitting only dispersed substitutions (e.g., 5 phospho-mimetics viable; ≥8 contiguous S/T residues impossible). This constraint architecture acts as an evolutionary brake against autonomous N-mediated backbone enhancement. Outputs include boundary-sequence FASTAs, residue-level CPS annotations, and sentinel rules for genomic surveillance (e.g., N-SR-IFN-1: ≥3 D/E at positions 192/195/198/204/210). All instantiations are strictly computational, no experimental protocols or synthesis instructions are provided. This work supports defensive anticipatory surveillance logic for early-warning detection of natural isolates approaching theoretical fitness ceilings.Note:This dataset is part of a series of MERS-CoV genomic surveillance studies conducted independently by Tahir HB for pandemic preparedness, acknowledging that historically constrained pathogens may pose global risk under exceptional evolutionary or epidemiological conditions.

Fields of Study & Subjects

SARS-CoV-2 and COVID-19 Research RNA and protein synthesis mechanisms Protein Structure and Dynamics

Publication details

Journal / source
Figshare
Publication date
1 January 2026
Document type
Dataset