Evidence map›Paper›PMID 41174319›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Computational Methods to Engineer Cas Proteins for Efficient Genome Editing.

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

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Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Muhammad Qaiser FatmiDepartment of Biosciences, COMSATS University Islamabad, Islamabad, Pakistan. qaiser.fatmi@comsats.edu.pk.
Aneeqa NadeemDepartment of Biosciences, COMSATS University Islamabad, Islamabad, Pakistan.
Mehraj AbbasovGenetic Resources Institute of the Ministry of Science and Education, Baku, Azerbaijan.
Muhammad SajjadDepartment of Biosciences, COMSATS University Islamabad, Islamabad, Pakistan. muhammad.sajjad@comsats.edu.pk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Computational BiologyCRISPR-Associated ProteinsCRISPR-Cas SystemsGene EditingProtein EngineeringMolecular Dynamics SimulationMutationCRISPR-Associated ProteinsCoevolutionary couplingCRISPR/Cas9Genome editingMolecular dynamics simulationMutant stability predictionNetwork centralityProtein engineering

Identifiers

PMID41174319

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.