Developments in our scientific understanding of biological systems highlight the complexity and interconnected nature of such systems. When integration of biological systems fails, disease can result. Thus, to advance both our understanding of these fundamental mechanisms, scientists from different fields are working together to address these biological challenges, and in turn develop better treatments for a range of diseases. This project will integrate cell biology with biophysics, artificial intelligence, chemistry, computational modeling and physiology, termed a convergent or trans-disciplinary approach, to problem-solve the fundamental question: how do hormones act on the female ovary- a complex organ of distinct interconnected cells. The ovary is a hub of female reproduction. Within the ovary, each egg is encapsulated in a highly organized group of cells, termed the follicle. Different cell types within the follicle respond to hormonal cues, communicating with the egg to ensure a single mature egg is released each month for fertilisation. A key hormone that develops the egg, causes its release and provides the hormones critical in early pregnancy if the egg is fertilized, is luteinising hormone (LH). LH coordinates these functions by binding to its specific receptor on the surface of the cell, the LHR. LHR is part of a large family of receptors called G protein-coupled receptors (GPCRs) with more than 800 different types that respond to light, smells, taste, chemical transmitters in the brain and a variety of different hormones. Thus, GPCRs are a popular drug target, however, there is high demand for new drugs that are more specific, have fewer side effects, and that are active for longer. Such developments require an in-depth understanding of the molecular mechanisms from complex biological systems to control receptor activity in a highly controlled manner. One important way receptors can modify how they communicate is by associating with each other. Our previous BBSRC-funded studies have dissected how LHR signalling is altered via its association with itself (homomers) and another important reproductive hormone receptor, the follicle stimulating hormone (FSHR) as heteromers. We have visualised LHR homomers and LHR/FSHR heteromers by employing a form of microscopy called super resolution imaging- a technique called photoactivated dye localisation microscopy (PD-PALM), which provides the ability to image single receptors on the surface of the cell. Our work has revealed that LHR receptors exist as monomers and a range of size of homomers/heteromers. Altering the pattern of these receptor-receptor association can change the type, duration and magnitude of signals generated inside cells. An outstanding and important question that remains is how the organization of LHR complexes contributes to LHR's multiple functions in the follicle. We will use our single molecule microscopy technique of PD-PALM with machine learning technology to create a novel automated platform to visualize LHR molecular complexes (receptor with it's signaling machinery) in the different follicle cell types and 'open' follicles that retains the communication with the egg. Combining PD-PALM images from follicle cells with computational simulations will unpick how LHR engages with each other, and employ novel chemical, small molecule and antibody tools to disrupt or manipulate these interactions to understand their role in regulating multiple ovarian functions via biophysical, biochemical and genetic methods. We anticipate that in the future, the information generated can be directly applied to improve the quality of life of women with conditions such as polycystic ovarian syndrome, hormone-dependent cancer, infertility, premature ovarian failure, and potentially applied to other diseases that involve GPCRs.

United Kingdom

Structural biology concerns the study of the three-dimensional structure of biological macromolecules and their interactions. Biomolecular Nuclear Magnetic Resonance (NMR) spectroscopy is one of three core techniques in structural biology, and highly complementary to the other two, i.e. X-ray crystallography and Cryo EM. Extracting information from NMR data has traditionally been complex and non-intuitive. Many smart and innovative tools have been developed, which unfortunately often have been disconnected and not well integrated and sometimes hard to use. For nearly two decades, the Collaborative Computational Project for NMR (CCPN) has been central in providing a connecting interface between the NMR data and many of these tools. CCPN also actively promotes the sharing and exchange of knowledge and best practices. CCPN also actively engages with the UK and international research communities in all matters relating to research funding and policies. The CCPN aims to continue its immense value to the scientific community over the next 5 years by pursuing the following specific objectives: 1. Development of software relevant for NMR CCPN will improve, maintain and expand its programmes, to provide for new functionalities, improved handling, and better speeds. Through fortnightly updates and regular new releases, we will ensure the proper functioning of the software across multiple platforms. We will continuously work on interoperability of our software with other NMR programmes and implement relevant tools for reporting and research data management. 2. NMR in support of Biological Sciences We will facilitate and implement the latest computational tools and developments for NMR data analysis, automation, structure generation and validation. 3. NMR in support of Medicine NMR metabolomics is a thriving field that generates crucial knowledge on metabolic pathways from cells to organisms, including humans. We have designed AnalysisMetabolomics to leverage its power and we will focus on tools for non-expert users, streamlined annotation, assignment, metadata and deposition in public repositories. 4. NMR in support of Industry In collaboration with industrial and academic partners, we will test and enhance applications that are useful to industry. Examples are AnalysisScreen, small-molecule (NMR-assisted) docking procedures to optimise workflows and efficiency and ChemBuild to assist with fragment-based drug discovery. 5. Outreach and training Through its active outreach programme, engaging with all stakeholders including national and major international NMR facilities, CCPN will promote the continuous exchange of knowledge, provide training and support the adoption of best practices in NMR. There is a growing body of "how to" videos available on the website. CCPN will actively continue to promote and develop community data standards (NEF), and will take a leading role in discussions on research funding and policies. CCPN will continue its crucial role as intermediary between the UK and international NMR community, by fostering contacts with (inter-)national NMR facilities, other CCPs, the international wwPDB and NEF efforts. To strengthen the UK NMR community, we will continue the successful series of UK CCPN conferences and teaching programs, our comprehensive help and support for CCPN users, participate in international efforts in knowledge sharing and exchange of best practices, and engage in training and teaching through workshops, papers and (video) tutorials. In short, CCPN will continue to make a crucial difference to the biological NMR community in different fields such as Medicine and Industry as well as its traditional base of the biological sciences by acting as a focal point for technology development, collaboration and sharing best practices. Ultimately, researchers who are empowered with the best tools have more time to make new discoveries.