<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-03T15:52:43Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/7D874BAF-20A4-46A8-83DC-43EBAB486230" ns1:id="7D874BAF-20A4-46A8-83DC-43EBAB486230"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/DC994274-9CBE-4DBE-98E0-206BDBCB4C7D" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/66194E65-5CD6-4038-92B4-A19D45E3FCDD" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/66194E65-5CD6-4038-92B4-A19D45E3FCDD" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2023-01-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/FA0B9B13-3FC1-4CEC-A469-9FA260BA92B6" ns1:rel="FUND" ns1:start="2021-07-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10002667</ns2:identifier></ns2:identifiers><ns2:title>Kuano: A novel second generation quantum computing technique using transition state modelling for efficient drug discovery</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>ISCF</ns2:leadFunder><ns2:abstractText>Kuano is a company dedicated to bringing the latest innovation and technology for drug discovery to the pharmaceutical industry. Kuano's unique approach tackles common challenges in both AI-driven drug design and target driven drug discovery.

This Feasibility Study seeks to exploit second generation quantum techniques to solve currently intractable problems associated with molecular simulation within the drug discovery sector.

Kuano will evaluate the feasibility of a second-generation quantum technology to overcome current limitations associated with accurately modeling the behaviour of the catalysis process: specifically, extracting a description of the transition state and understanding the binding mechanisms for metalloproteins. This would enable large-scale, precise molecular simulations and support broad application in the field of 'AI in drug discovery' (as well as other industrial applications).

The project output is a discovery platform that aims to unlock intermediate-to-high levels of entanglement, creating a step-change for Kuano and the UK drug development industry.</ns2:abstractText></ns2:project>