Virtual screening
Prepare targets, rank compounds with complementary methods, inspect poses, and review developability signals in one computational workspace.
Trusted by researchers at leading biotech, pharmaceutical, academic, and materials organizations
Screen with context
Use preparation, complementary ranking methods, pose review, and property checks to produce a traceable shortlist for experimental testing.
Repair structures, identify plausible pockets, generate ligand conformers, and preserve the molecular states used in every downstream calculation.
Compare physics-based, learned, blind, and sequence-driven rankings without treating unlike scores as interchangeable.
Inspect poses and interactions, check property and ADMET signals, and export a bounded set for experimental validation.
Designed around the research
Available now
Choose methods based on your available evidence, preserve native scores, and experimentally test the resulting shortlist.
Generate and CNN-score protein-ligand docking poses.
Run customizable Vina-family docking workflows.
Predict poses without a predefined binding site.
Sample ligands or peptides in a specified pocket.
Rank a molecular panel against a protein sequence.
Find related compounds from known hits.
From the Neurosnap blog
Docking tutorial
Walk through a protein-ligand docking study and the evidence needed to interpret predicted poses.
Read articleDrug discovery guide
Review the concepts behind molecular recognition, energetic favorability, and conformational effects.
Read articlePrioritization guide
Understand why a promising computational hit must also be practical to synthesize and test.
Read articleSecurity & privacy
Submitted data and generated results remain confidential, with ownership retained by your team.
Only you and authorized colleagues can access submitted data and results.
Your results and intellectual property remain yours. No royalties or equity.
Platform controls help protect sensitive computational research.
Onboarding and integration support help organizations scale confidently.
Screen with purpose
Build a traceable computational shortlist, then carry the strongest hypotheses into the assay.
