Abstract Introduction: Mutations in the KRAS, HRAS, and NRAS genes are frequently associated with worse patient outcomes. Previous analyses of the structure and function of the associated proteins have been explored but not conclusively. The actual binding conformations of the three isoforms, especially when mutated are essential in designing inhibitory drugs. Recent studies have identified important interactions between the three isoforms that affect the oncogenic strength of the others when they are mutated. We use a bioinformatics approach to examine the modifications of the structural properties, mechanisms, and kinetic energies of eight KRAS mutants interacting with wildtype HRAS, and again with wildtype NRAS. Methodology: AlphaFold AI predicted models of KRAS, HRAS, and NRAS were downloaded from Uniprot and relevant mutations were induced using PyMOL. Pairs of KRAS mutants and either HRAS or NRAS were submitted to ClusPro for docking. PyMOL was used to separate proteins by chain identities before being repaired in GROMACS. Molecular dynamics simulations (MDS) were performed between proteins using GROMACS, a Linux based MDS software that renders a topology regulated by Newton’s Laws. XmGrace was used to analyze structure, MMPBSA.py was used to derive energy calculations, and VMD was used to visualize the interaction mechanisms. Results: RMSF data indicated C-terminus residues in KRAS mutants and WT-HRAS and WT-NRAS are the most mobile in their interactions. Notably, when WT-HRAS interacts with G12R, G12S, G12V, and Q61H, its C-terminus decreases fluctuation. G13D had the greatest binding strength and strength fluctuation with WT-HRAS. G12V had the greatest binding strength with WT-NRAS. All other mutants had weaker binding with WT-NRAS than WT-KRAS. WT-HRAS had stronger binding at residue Val187 with WT-KRAS than all mutants did. WT-HRAS residues Cys184, Lys185, and Cys186 each had weaker binding energies with WT-KRAS than most mutants did. WT-KRAS residues Gln25 and Lys117 both exhibited stronger binding energy in interactions with WT-HRAS than most mutants did. WT-NRAS had stronger binding at residues Met182 and Met189 with WT-KRAS than all mutants did. Residue Pro185 in WT-NRAS did not have significant interaction with WT-KRAS, but had a strong interaction with all mutants. WT-NRAS residue Val187 had weaker binding energy with WT-KRAS than most mutants. WT-KRAS residues Tyr32 and Asp38 both exhibited weaker binding energy in interactions with WT-NRAS than most mutants did. Conclusion: MDS between KRAS mutants and WT-HRAS and WT-NRAS present notable structural modification and binding kinetics. In each KRAS mutation, different segments of the protein complexes are involved in the interaction, indicating unique inhibitory methods are required to approach each mutant. Citation Format: Isaac Silverman, Michael S. Gerber, Aaron Shaykevich, Yitzchak F. Stein, Alexander Siegman, Sanjay Goel, Radhashree Maitra. Molecular dynamic simulations of RAS family protein interactions: Mutant KRAS binding with wildtype HRAS and NRAS [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3487.