A major threat to world health is the high death rate from gastrointestinal (GI) cancer, especially in Asia, South America, and Europe. The new approaches are needed because of the complexity and heterogeneity of gastrointestinal (GI) cancer, which has made the development of effective treatments difficult. To investigate the potential of peptide-based therapies that target the P21 Activated Kinase 1 (PAK1) in GI cancer, we are using the DBsORF database to predict peptides from the genomes of two bacterial strains: Lactobacillus plantarum and Pediococcus pentosaceus. Energy minimization is then applied for stability after the three-dimensional (3D) structures of these peptides are modeled using the Swiss Model tool. ToxinPred is used for toxicity analysis to verify the safety profiles of the identified peptides. The three-dimensional structure of the target protein PAK1 is taken out of the Protein Data Bank (PDB) and ready for computer analyses. To identify the top-performing peptides for each strain that have good PAK1 binding properties, molecular docking analysis is performed using the ClusPro server. The peptide repertoires of L.plantarum and P. pentosaceus are distinct, and some candidates display low toxicity; for instance, VOIOYA_1513 from P. pentosaceus and BVNTGZ_2921 from L. plantarum demonstrate high binding energies and stable interactions with PAK1. Once the binding energies, hydrogen bonds, and non-bonded contacts have been evaluated, promising peptide candidates are selected. Understanding the dynamics of the peptide-PAK1 complexes is achieved through molecular dynamics simulations performed with the Groningen machine for molecular simulation (Gromacs). Trajectory analysis measures like Radius of Gyration (Rg), Root Mean Square Deviation (RMSD), and Root Mean Square Fluctuation (RMSF) provide insight into the stability and fluctuations of the structure during a 100 ns simulation. Molecular dynamics simulations validate the stability of these complexes, suggesting that, subject to further experimental validation, they could be promising therapeutic candidates. Future research projects and drug development initiatives will benefit from the detailed computational approach, which offers information about the design and evaluation of peptide-based treatments that target PAK1 in GI cancer.

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http://dx.doi.org/10.1016/j.compbiolchem.2025.108345DOI Listing

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