Massive Compound Exploration
Search large chemical spaces to identify promising compounds for a target profile.
AI Solution
LM-VS™
Language Model-based Virtual Screening applies AI language-model methods to large-scale compound search for faster early-stage hit discovery.
Language Model-based Virtual Screening
High-throughput discovery with AI-scale search
LM-VS™ is designed for early-stage compound screening where speed, scale, and prioritization quality matter. It evaluates massive chemical spaces and surfaces candidate sets for downstream structural analysis.
The workflow connects naturally with SM-ARS® and DEEPMATCHER®, helping teams move from target input to ranked hit candidates with fewer manual screening cycles.
Platform Capabilities
Screening that moves at model scale
Language-Model Scoring
Use learned molecular representations to prioritize binding potential and synthetic feasibility.
Workflow Integration
Feed screened hits into docking, ADMET profiling, and candidate reporting.
Virtual Screening Flow
Core Process
01
Target Input
Prepare protein and target information for screening.
02
Candidate Search
Evaluate compound libraries with language-model-based scoring.
03
Prioritized Hit List
Generate ranked hits for structural simulation and validation.
04
Next-Step Analysis
Connect hits to DEEPMATCHER® or SM-ARS® workflows.