Neuralocity

Computationally prioritized molecule data for discovery

Neuralocity packages AI-generated molecules into searchable, versioned opportunity sets with target-class rankings, safety signals, drug-likeness scores, and full provenance — ready for your screening pipeline.

Platform

Intelligence layer on a generative catalog

Searchable molecule catalog

Browse and filter 2M+ computationally generated molecules by molecular weight, LogP, QED, SA score, and target-class relevance — paginated, sortable, and metadata-driven.

Curated opportunity sets

Versioned molecule sets selected by drug-likeness, synthesis accessibility, and target-class fit — with inclusion criteria, distributions, and release provenance.

Multi-dimensional safety overlay

Toxicity and ADME risk signals applied at catalog scale so teams start from molecules that already pass computational safety screens.

Provenance & claim control

Every annotation carries source class, model version, and catalog release. Ranks and tiers — never unsupported IC50 or assay claims.

Data product

From catalog search to licensed export

Novel molecule supply

Generated, filtered, and deduplicated internally — not scraped from public catalogs.

Target-class scoring

Kinase-like, GPCR-like, and protease-like relevance — publishable triage signals, not potency claims.

Licensed datasets

Named opportunity sets with CSV export, provenance metadata, and entitlement controls.

Workflow

How discovery teams use Neuralocity

  1. 01

    Pick a target class or property thesis

    Filter the catalog by kinase-like, GPCR-like, protease-like relevance — or by safety, drug-likeness, and novelty envelopes.

  2. 02

    Review ranked candidates

    Inspect molecule detail pages with structure, properties, class-relevance percentiles, safety signals, and provenance per dimension.

  3. 03

    Build a shortlist

    Save promising molecules into named collections, add notes, and compare candidates before committing assay budget.

  4. 04

    License and export

    Export opportunity sets or collections as CSV with full audit logging, field registry metadata, and research-use disclaimers.