Achieve compounds with favorable potency, selectivity, and ADME profile by leveraging advanced computational drug design, ligand-based drug design, structure-based drug design, and state-of-the-art artificial intelligence.
Our proven expertise in cheminformatics services has been demonstrated by successful client projects, strong publication records, and top performance in global AI/ML competitions.
We deliver detailed analyses, regular project updates, prioritized compound lists, and actionable insights, all tailored to your project’s needs.
Our cheminformatic team covers different areas of expertise include:
Target structure validation
- Ligandability assessment: Ensure reasonable starting point for structure-guided drug design
- Homology modeling: Build 3D model of the target from a template
- Cryptic pocket detection: Identify potential pockets not visible in PDB structures using molecular dynamics
Hit identification and expansion
- Docking & pharmacophoric modeling: Predict ligand pose and identify key interactions
- Virtual screening: Identify hits from vast synthesizable commercial libraries by high throughput docking
- Molecular dynamics simulation: Study ligand stability, impact of water interactions, and induced-fit behavior
Lead generation and optimization
- Potency and ADME prediction: Build tailored predictive models from SAR & ADME data
- AI growing and scaffold hopping: Improve potency of initial hits by AI-driven chemical space exploration
- AI for patent scope expansion: Explore all potential isosteric replacements of your lead series, reducing the risk of patent-busting
Molecular Dynamics trajectory by cheminformatics team on cryo-EM structure released internally by Structural Biology and cryo-EM teams.
Proven Competition Results: AI-driven cheminformatics recognized for excellence
Projects leveraging Novalix’s cheminformatics services and AI have demonstrated improved hit rates and accelerated timelines, supporting client portfolio advancement. All approaches are grounded in validated methodologies and transparent reporting.
Our in-house machine learning pipelines achieved top international rankings in the Antiviral Competition organized by ASAP Discovery, OpenADMET, and Polaris.
Among more than 60 participating teams, our models ranked #1 for IC₅₀ prediction on the SARS-CoV-2 Mpro target and #4 for early ADME prediction, demonstrating the robustness and innovation of our computational drug discovery approaches.
Learn more about this achievement in our LinkedIn post.
Client benefits
- Enhanced data quality and reproducibility
- Reduced risk of artefacts and false positives
- Accelerated progression from hits to leads