molclaw-dleps

What problem does it solve?

Calculates disease reversal scores for candidate small molecules to prioritize compounds that could reverse disease-associated gene expression signatures, reducing manual interpretation and ad-hoc scoring work in early-stage screening.

Core Features & Use Cases

• Disease-aware scoring: Accepts lists of SMILES and a disease name to predict a reversal score per molecule reflecting potential to counteract disease gene expression changes.
• Batch screening support: Returns structured predictions (status, message, pred_scores with smiles and cs_score) suitable for downstream ranking and filtering in virtual screening pipelines.
• Use Case: Rank a library of compounds by predicted reversal score for diseases such as Aging, Gout, Pulmonary fibrosis, NAFLD, or Obesity to select candidates for follow-up validation.

Quick Start

Calculate DLEPS scores for a list of SMILES against "Gout" to obtain a prioritized list of candidate molecules.