denovoX

Pipeline 1

Pipeline 1: molecules for your targets

Start with a target, for example a disease-relevant protein. denovoX applies high-level ML-driven generation and prioritization workflows to produce candidate molecules ranked for exploration.

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Input → process → output

High-level pipeline framing

Input

Target context defined by your team’s biological objective.

Process

Computational exploration with an ensemble of ML models and generative approaches, described at high level.

Output

Prioritized candidate molecules aligned to criteria for follow-up experimental planning.

Process

Three-step workflow

  1. 1

    Define target

    Provide the disease-relevant target and project constraints for computational prioritization.

  2. 2

    denovoX runs ML pipeline

    Explore chemical space and generate candidate sets through high-level machine-learning workflows.

  3. 3

    Prioritize candidates

    Rank generated options against project-relevant criteria to focus downstream experiments.

Benefits

Why teams use Pipeline 1

  • Faster early exploration cycles around biologically relevant targets.
  • Reduced cost pressure by narrowing candidate space before wet-lab expansion.
  • Improved focus of experimental work through ranked molecule outputs.

Applications

Example domains

Oncology Rare diseases Inflammation Neurodegeneration Cardiometabolic

Access

Create an account to reserve Pipeline 1 workspace access.

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Account workspace

Pipeline 1 entry point

Your denovoX account is now the front door for private-preview tool access and future target-to-molecule workflows.

Connected placeholders

Tools staged from the VPS workspace

  • AlphaFold 3
  • RFdiffusion
  • ProteinMPNN
  • Benchmark workspace