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Matchpoint Therapeutics

Matchpoint Therapeutics utilizes chemoproteomics and machine learning to discover precision small molecule covalent medicines that target disease-causing proteins in immune diseases. By forming irreversible bonds with specific protein targets, their approach enhances potency and selectivity, enabling the treatment of conditions previously deemed untreatable with traditional small molecule therapies.

Cambridge, United KingdomFounded 2021331K+ followers
Updated 20 months ago

Funding

$100M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Many disease-causing proteins, particularly in immune-related disorders, are considered undruggable by traditional small molecule therapies due to challenges in achieving sufficient potency, selectivity, and duration of action. Conventional high-throughput screening methods often fail to identify binding pockets on these proteins, limiting therapeutic options.

Solution

Matchpoint Therapeutics is developing precision small molecule covalent medicines that target previously undruggable proteins implicated in immune diseases. Their approach utilizes chemoproteomics and machine learning to discover and design covalent drugs that form irreversible bonds with specific protein targets. This covalent binding enhances potency, improves selectivity by targeting unique reactive amino acids, and decouples pharmacokinetics from pharmacodynamics, leading to sustained efficacy. The Matchpoint ACE (Advanced Covalent Exploration) platform combines chemoproteomic screening, machine learning, and a proprietary covalent library to accelerate the discovery of these precision medicines.

Target Audience

The primary target audience includes patients suffering from immune diseases and pharmaceutical companies seeking novel therapeutic approaches for previously undruggable targets.

Features

  • Agnostic and targeted chemoproteomic screening to identify novel binding sites on disease-causing proteins.
  • Machine learning algorithms to prioritize targets and guide medicinal chemistry efforts.
  • Proprietary library of covalent compounds, ranging from fragments to lead-like molecules.
  • Covalent molecules designed for increased potency through durable target engagement.
  • Enhanced selectivity by targeting unique reactive amino acids present only in the disease-causing protein.
  • PK-PD decoupling for sustained efficacy after metabolic clearance.
This profile is AI-generated and may contain inaccuracies.