The clustered regularly interspaced short palindromic repeats/CRISPR-associated protein (CRISPR/Cas) system has revolutionized genome editing through programmable, sequence-specific deoxyribonucleic acid (DNA) targeting. Yet, its broader application remains limited by off-target effects and context-dependent efficiency. To address these challenges, we present an integrated computational protocol with easy-to-do steps for researchers to guide the rational design of CRISPR/Cas variants with improved stability and specificity. The integrated workflow begins with coevolutionary coupling analysis to identify conserved and covarying residues critical for function. These residues are then evaluated for energetically favorable substitutions through mutant stability prediction, followed by network centrality analysis to evaluate the impact of mutations on intramolecular communication pathways, preserving key allosteric interactions. Finally, molecular dynamics (MD) simulations validate the structural integrity and dynamic behavior of the selected variants. Network analysis and molecular dynamics (MD) simulations are applied iteratively, allowing insights from MD to refine network-based evaluations and vice versa. This multiscale strategy offers a streamlined and systematic approach for engineering optimized Cas proteins for genome editing applications.

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Computational Methods to Engineer Cas Proteins for Efficient Genome Editing

  • Muhammad Qaiser Fatmi,
  • Aneeqa Nadeem,
  • Mehraj Abbasov,
  • Muhammad Sajjad

摘要

The clustered regularly interspaced short palindromic repeats/CRISPR-associated protein (CRISPR/Cas) system has revolutionized genome editing through programmable, sequence-specific deoxyribonucleic acid (DNA) targeting. Yet, its broader application remains limited by off-target effects and context-dependent efficiency. To address these challenges, we present an integrated computational protocol with easy-to-do steps for researchers to guide the rational design of CRISPR/Cas variants with improved stability and specificity. The integrated workflow begins with coevolutionary coupling analysis to identify conserved and covarying residues critical for function. These residues are then evaluated for energetically favorable substitutions through mutant stability prediction, followed by network centrality analysis to evaluate the impact of mutations on intramolecular communication pathways, preserving key allosteric interactions. Finally, molecular dynamics (MD) simulations validate the structural integrity and dynamic behavior of the selected variants. Network analysis and molecular dynamics (MD) simulations are applied iteratively, allowing insights from MD to refine network-based evaluations and vice versa. This multiscale strategy offers a streamlined and systematic approach for engineering optimized Cas proteins for genome editing applications.