In Silico Drug Discovery Platform — Nuclyra
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Product · DRUG DISCOVERY AI

In Silico Drug Discovery Platform

An AI-powered workspace for virtual screening and candidate prioritization, combining molecular docking, ADMET prediction, and molecule generation in one workflow.

In Silico Drug Discovery Platform target analysis dashboard
Features

What’s inside

Integrated docking

Structure-based virtual screening against millions of compounds, ranked by predicted binding affinity.

Generative design

Property-guided generative models propose novel candidates directly inside the same workspace.

ADMET prediction

Early-stage developability prediction flags weak candidates before they reach a shortlist.

Shareable shortlists

Ranked, annotated shortlists export directly into formats your medicinal chemistry team already uses.

In practice

What a screening campaign actually looks like

Three concrete scenarios In Silico Drug Discovery Platform is built to handle.

An overnight screen against a novel target

A team loads a new target structure before leaving for the day, kicks off docking against a multi-million compound library, and comes back to a ranked list of binders with ADMET scores already attached.

Scaffold-hopping around a promising hit

Once a hit looks interesting, the generative model proposes structurally novel analogs constrained to the same property targets, and each one is scored by the same docking and ADMET pipeline live — no separate hand-off.

Handing a shortlist to medicinal chemistry

A ranked, annotated shortlist — binding score, ADMET flags, and generation lineage included — exports directly into the format the chemistry team already tracks candidates in.

Under the hood

Three models, one shared scorecard.

Docking, generative design and ADMET prediction usually live in separate tools, which means a candidate’s story gets assembled by hand from three exports. In Silico Drug Discovery Platform runs all three against the same target and the same candidate pool, so every score lands on one shared record.

The generative model isn’t generating blindly, either — it’s constrained by the property targets you set (potency range, solubility, synthetic accessibility), so the candidates it proposes are ones the ADMET model is more likely to pass, not just structurally novel ones.

What comes out the other end is a single ranked list where binding affinity, developability and origin are all visible on the same row — the comparison your team would otherwise be doing in a spreadsheet.

In Silico Drug Discovery Platform molecular dynamics dashboard
How it works

From connecting your data to sharing a result

Step 01 — Load

Load your target & library

Upload a target structure and compound library, or connect to a public database.

Step 02 — Screen

Screen & generate

Run docking and generative design side-by-side against the same target.

Step 03 — Predict

Predict developability

ADMET and selectivity scores are calculated automatically for every candidate.

Step 04 — Export

Export the shortlist

A ranked, annotated shortlist exports directly to your medicinal chemistry workflow.

The difference

Before and after In Silico Drug Discovery Platform.

Status quo

Disconnected tools

  • Separate docking software, generative model, ADMET predictor
  • Manual spreadsheet tracking across tools
  • Candidate profile assembled by hand
The In Silico Drug Discovery Platform way

With In Silico Drug Discovery Platform

  • Docking, generation and ADMET in one workspace
  • Every candidate’s full profile in one view
  • Ranked shortlist exports automatically
Works with

Plugs into what you already use

RDKitAutoDock VinaPDBChEMBLPubChemSchrödingerOpenEyeCSV/SDF export
In Silico Drug Discovery Platform cut our tool-switching time to zero — everything a candidate needs to prove is in one screen.
Questions we get

Before you reach out

Yes, you can upload a proprietary library or connect to public databases like ChEMBL or PubChem.

No, it narrows the search space and surfaces a ranked shortlist; the chemistry judgment still sits with your team.

Predictions are calibrated against public and proprietary benchmark datasets and reported with confidence intervals, not treated as ground truth.

See it live

Want to run In Silico Drug Discovery Platform against your own target?

Book a walkthrough — we’ll set up a screening run against a target you choose.