2D/3D RDKit descriptors + QSAR modeling

ChemBlast molecular design intelligence.

A chemical QSAR platform for compound datasets, molecular descriptors, 3D conformer shape analysis, activity prediction, similarity alignment, and activity-guided design criteria.

Built for practical compound screening.

ChemBlast combines physicochemical descriptors, molecular fingerprints, functional-group patterns, ETKDG-based 3D conformer descriptors, model comparison, and interpretable visual analytics.

Input chemistry data

Works with molecular records such as SMILES, SDF properties, activities, docking scores, toxicity labels, and physicochemical endpoints.

2D and 3D descriptors

Combines RDKit 2D descriptors with 3D shape descriptors such as PMI, NPR, radius of gyration, asphericity, and spherocity.

Design guidance

Uses similarity, MCS alignment, scaffold comparison, and enriched functional groups to suggest activity-guided molecular criteria.

Developer

ChemBlast is developed by Ahmed G. Soliman for cheminformatics, QSAR modeling, and molecular design workflows.

Ahmed G. Soliman MEXT master's student at Kyutech, Japan, School of Life Science and Engineering. Academic background Biotechnology Program, Faculty of Agriculture, Ain Shams University, Cairo, Egypt. Experience Previous instructor at ACGEB in in-silico drug design and immune-informatics. Research identifiers Scopus ID: 58569160700
ResearcherID (WOS): ABE-8406-2021
ORCID: 0000-0002-1122-3993 Portfolio Ahmed G. Soliman portfolio