Search Results for molecular-visualization

Abstract

The expansion of chemical and pharmaceutical data increases the need for enhanced computational systems that can interpret molecule structures and forecast chemical properties. Due to the fact that molecular visualization or prediction of chemical properties are presently performed separately during the chemical research and initial drug development processes, chemical research and the initial drug development process are not as efficient as possible. As such, the research presents a fully integrated model that predicts chemical properties with a single input method (SMILES strings) for both 2D and 3D representations of molecular structure, while at the same time utilizing SMILES strings to reconstruct the molecule and extract the features from the molecule. The research develops physicochemical descriptors and circular (Morgan) fingerprints which scientists use to create features for training ensemble-based machine learning models that predict essential molecular properties. The framework enables users to create interactive two-dimensional and three-dimensional molecular visualizations which show the molecular structure in an intuitive way while displaying the results of quantitative prediction methods. The proposed method enhances usability and analytical efficiency through its unified visualization system for prediction and interpretation which outperforms current standalone tools. The Python prediction and visualization pipeline with MATLAB verification tool enables independent assessment of three-dimensional molecular geometries to confirm spatial structure representation and conformer generation while maintaining model training and inference integrity. The framework enables organizations to incorporate new datasets and molecular descriptors and learning algorithms through its modular scalable and extensible design which demonstrates the successful application of cheminformatics-based representations and machine learning to drive data-based molecular research and decision-making in chemical and pharmaceutical fields.