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Antibody discovery

Antibody Discovery

Computational support across antibody discovery, from lead refinement to candidate generation.

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Illustrative molecular dynamics visualization · drag to turn

Project offerings

Pick the card.

A single antibody structure with navy helices and gold sheets, standing for one lead
Illustrative AI render

Single Lead

One sequence

Variants of one lead are proposed and ordered for follow-up.

ExploreSingle Lead
One antibody structure branching into six variant antibodies of differing shade, with one picked out in glowing gold
Illustrative AI render

Lead Optimization

Several leads or a dataset

Compare and prioritise across leads using the data you supply.

ExploreLead Optimization
Many sequencing-read strands converging into a folded structure, with a small cluster of candidate antibodies emerging
Illustrative AI render

NGS Data Analysis

Sequencing-derived sequences

Sequences are translated, grouped and counted, and returned as frequency tables and exports.

ExploreNGS Data Analysis
A target epitope surface and a folded structure, with candidate antibodies materialising from gold particle sparkles
Illustrative AI render

De Novo

No starting antibody

Candidate sequences are generated against a region you specify. They are not confirmed binders.

ExploreDe Novo
A protein surface with two regions highlighted in gold, marking candidate epitopes, with an antibody approaching
Illustrative AI render

Epitope Identification

Epitope-focused

Surface regions of the antigen are computationally proposed. They are not confirmed epitopes.

ExploreEpitope Identification

Illustrative renders, not outputs from an actual run.

How it works

Discovery, in four frames

  1. 01Sequence diversity. Start from sequences you already have and see where they vary.
  2. 02Computational screening. Sequence-level descriptors narrow the set before any experiment.
  3. 03Candidates. Shortlisted candidates can be examined against the antigen where a structure or model is available.
  4. 04Shortlist. A short list moves to experimental testing, carried out by your team.
referenceHGGYYAMDY
cand_01HSGYFAMDY
cand_02HGNYYALDY
cand_03HSGYYALDY
cand_04HGGYFAMQY
cand_05HGNYWAMQY

The reference row is the real CDR-H3 of a deposited antibody, PDB 1IGT. The other rows are illustrative design proposals. Tinted columns are where the set varies.

Start from sequences you already have and see where they vary.

The antibody we work on

Four chains, two binding sites.

Two heavy chains (navy) and two light chains (pale blue) form each antibody. Discovery works on the variable ends of both arms; everything downstream depends on getting those right.

Drag to turn. Rendered live by IndiskaAI from PDB 1IGT

Computational analysis and design workflows for antibody research. The route is chosen to match the starting material you already have, and every output is a computational result for your team to test.

Three steps

Getting started with us

  1. 01

    Share your starting point

    Target, structures, sequences, or data, whatever you already have.

  2. 02

    Define the question

    We agree what decision the analysis needs to inform.

  3. 03

    Receive decision-ready outputs

    Results, figures, and a report stating what they do and don't show.

Scope & limitations

These are the computational entry points we accept. Experimental testing is carried out by your team or your partners.

Have an antibody discovery challenge?

AI-assisted computational workflows designed to explore, prioritise, and refine antibody candidates from your available starting data.

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