CCP-NC

Nuclear Magnetic Resonance (NMR) is a powerful tool for determining chemical structures, particularly in organic compounds where single crystals large enough for traditional diffraction techniques are difficult to obtain. NMR Crystallography combines high-precision quantum-mechanical simulations with experimental NMR data, opening new avenues to explore and understand previously unresolved crystal structures, including novel pharmaceuticals.

The Collaborative Computational Project for NMR Crystallography (CCP-NC) supports a multidisciplinary community of NMR spectroscopists, crystallographers, materials modelers, and application scientists. By developing and integrating software across the field of NMR crystallography, CCP-NC aims to advance both the science and accessibility of NMR data.

Funded by the Computational Science Centre for Research Communities (CoSeC), CCP-NC builds on over 40 years of CCP history, promoting collaboration and innovation among UK scientists and beyond.

Traditionally, crystallographers and chemists stored computational datasets independently- on local university servers or personal systems- creating isolated “data silos.” These silos slowed progress, duplicated effort, and limited opportunities for collaboration.

To tackle this, CCP-NC envisioned a centralized database for NMR crystallography data, enabling researchers to share datasets openly. This approach fosters:

• Transparency – making data visible and understandable to the wider community
• Reproducibility – allowing experiments to be verified and built upon
• Innovation – accelerating discovery through collaborative access to high-quality datasets

CCP-NC develops tools and workflows that integrate computational predictions with experimental NMR data. The project:

• Enables accurate prediction and interpretation of NMR spectra
• Supports research across pharmaceuticals, materials, and organic chemistry
• Builds a community of experts sharing knowledge, methods, and software
• Encourages open science principles to maximize research impact

Through these efforts, CCP-NC is helping the scientific community unlock structural insights that were previously inaccessible.

The formal collaboration between CCP-NC and the Physical Sciences Data Infrastructure (PSDI) began in September 2023. PSDI brought expertise in data ethics, metadata, and infrastructure design, helping CCP-NC take its prototype database to the next level. 

The partnership was founded on a shared vision:

Since the launch of the project, CCP-NC and PSDI have delivered several major milestones:

COMMUNITY ENGAGEMENT AND WORKSHOPS

A key milestone was the Advanced Materials Search Workshop held at CCDC headquarters in Cambridge (January 2025), which brought together bringing together domain experts from CCP-NC, CCDC, PSDI and OPTIMADE to discuss the best way to enable features like substructure searching in the upcoming version of the CCP-NC database.

FUTURE INTEGRATION WITH FUTURE PSDI CROSS-SEARCH PORTAL

The next phase will link the CCP-NC database to PSDI’s cross-search tools, allowing researchers to simultaneously search across multiple physical sciences datasets. Read more about PSDI’s Cross Data Search here.

Supporting the Machine Learning Revolution

In the past five years, machine learning interatomic potentials (MLIP) have emerged as a paradigm shift in atomistic molecular simulations. These models require large, computationally expensive training datasets, which are far more complex to store and distribute than older, analytical models.

To address these challenges, PSDI and CCP-NC are collaborating with community partners – including CCP5, MCC, and Professor Gábor Csányi (University of Cambridge) – to build dedicated hardware and data infrastructure to:

• Host and distribute machine learning training datasets.
• Act as a central hub for sharing ML models and data.
• Provide curation mechanisms to maintain high-quality, validated datasets.

This infrastructure will not only support the CCP-NC community but also drive innovation in machine learning-driven materials discovery.

The CCP-NC and PSDI collaboration is on track to create a world-class, open-access data resource for the NMR crystallography community. Upcoming goals include:

• Full integration with the PSDI cross-search portal to improve data discoverability.
• Expansion of advanced search functionalities for researchers worldwide.
• Continued support for machine learning initiatives, ensuring the infrastructure evolves with the needs of modern science.

By breaking down research silos and enabling open, collaborative access to data, CCP-NC and PSDI are accelerating progress in NMR crystallography and solidifying the UK’s leadership in this rapidly growing field.