IEV2Mol: Molecular Generative Model Considering Protein-Ligand Interaction Energy Vectors.

ABSTRACT: Generating drug candidates with desired protein-ligand interactions is a significant challenge in structure-based drug design. In this study, a new generative model, IEV2Mol, is proposed that incorporates interaction energy vectors (IEVs) between proteins and ligands obtained from docking simulations, which quantitatively capture the strength of each interaction type, such as hydrogen bonds, electrostatic interactions, and van der Waals forces. By integrating this IEV into an end-to-end variational autoencoder (VAE) framework that learns the chemical space from SMILES and minimizes the reconstruction error of the SMILES, the model can more accurately generate compounds with the desired interactions. To evaluate the effectiveness of IEV2Mol, we performed benchmark comparisons with randomly

SUBMITTER: Ozawa M 

PROVIDER: S-EPMC11423338 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature