Type 2 Diabetes · 17 targets · QSAR
Paste any SMILES and get activity predictions across 17 validated T2D targets — with applicability domain charts so you know when to trust each result.

How it works
Paste any valid SMILES — natural product, synthetic compound, or drug candidate.
Your molecule is encoded into Morgan ECFP4, AtomPair or MACCS fingerprints, depending on the best model for each target.
Each of the 17 target models (selected by MCC across 27 algorithm × fingerprint combinations) returns a probability of activity.
The Tanimoto similarity distribution of your molecule vs. the training set is shown per target — so you see exactly how reliably each prediction can be trusted.
17 validated T2D targets
The team
Carlos Seiti H. Shiraishi
QSAR Pipeline · Virtual Screening · CIMO, IPB¹
Dr. Cleber C. Melo-Filho
Molecular Modeling · Chemical Biology · UNC Chapel Hill³
Dr. Sandrina A. Heleno
Natural Products · Phytochemistry · CIMO, IPB¹
Dr. Miguel A. Prieto
Chemoinformatics · Food Science · Universidade de Vigo²
Dr. Lillian Barros
Natural Products · Bioactivity · CIMO, IPB¹
Dr. Marcus T. Scotti
Cheminformatics · Natural Products · UFPB⁴
Dr. Eugene N. Muratov
QSAR Methodology · Regulatory Science · UNC Chapel Hill³
Dr. Rui M. V. Abreu
Pharmacology · Project Coordination · CIMO, IPB¹
¹ CIMO, LA SusTEC, Instituto Politécnico de Bragança, 5300-253 Bragança, Portugal
² Nutrition and Bromatology Group, Universidade de Vigo, 36310 Vigo, Spain
³ UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599, USA
⁴ Laboratório de Quimioinformática, Universidade Federal da Paraíba, João Pessoa, PB, Brazil
Applicability domain
The AD histogram shows the distribution of Tanimoto similarities between your molecule and the training set. The colored line marks your molecule's position; the red dashed line marks the 0.40 threshold. Predictions to the left are marked Outside AD.