NCIVISION: A Siamese Neural Network for Molecular Similarity Prediction MEP and RDG Images.

ABSTRACT: Artificial neural networks in drug discovery have shown remarkable potential in various areas, including molecular similarity assessment and virtual screening. This study presents a novel multimodal Siamese neural network architecture. The aim was to join molecular electrostatic potential (MEP) images with the texture features derived from reduced density gradient (RDG) diagrams for enhanced molecular similarity prediction. On one side, the proposed model is combined with a convolutional neural network (CNN) for processing MEP visual information. This data is added to the multilayer perceptron (MLP) that extracts texture features from gray-level co-occurrence matrices (GLCM) computed from RDG diagrams. Both representations converge through a multimodal projector into a shared embedding spa

SUBMITTER: Vieira RC 

PROVIDER: S-EPMC12693297 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature