Computer-based technologies are becoming one of the most promising novel approaches due to continuously accelerated growth of both hardware processing power and software algorithm efficiency. One recent example includes machine learning algorithms that revolutionised data analysis in computer science, and lead to new computer games, visual recognition, and other applications that overtake human performance in many cases. Here, we propose to perform atomistic molecular simulations using novel enhanced sampling algorithms. Most biologically important processes take place on significantly longer timescales than those accessible to current computer simulations. Therefore, to obtain meaningful and accurate results regarding the kinetics and conformational dynamics of complex molecular systems, we use algorithms that enhance the sampling using parallel calculations with different biases. Developing more optimal biasing algorithms will allow us to model faster and more accurately the key biological processes of interest, including ligand binding, protein conformations, etc. Here we aim to use statistical algorithms inspired by machine learning to develop novel enhanced sampling methods for molecular simulations. Novel algorithms can be applied to a wide range of molecular modeling problems. We will focus on phosphate catalytic enzymes, and study key DNA processing enzymes to reveal the catalytic mechanism in these systems. Due to the essential nature of phosphate catalytic enzymes in most biological processes, a large number of drugs in current clinical practice also target phosphate-processing enzymes treating a wide range of diseases. Examples include reverse transcriptase and integrase inhibitors used against HIV and hepatitis B, proton pump inhibitors used in gastric diseases, kinase, PARP and topoisomerase inhibitors used against a large number of cancers. Studying phosphate catalytic systems with modern molecular modeling methods will enable fundamental advances in our current knowledge of the molecular basis of life. It will also create opportunities for rational development of better drugs to fight diseases.

Alcohol related liver disease (ALD) is responsible for more than 6000 deaths a year in the UK and costs the NHS £3.5 billion. Alcoholic hepatitis is a florid presentation of ALD in which patients present with jaundice and liver failure. Unfortunately, around 30% of people admitted to hospital with this condition will die within 3 months. The treatment of alcoholic hepatitis is complicated by the fact that there is tremendous inflammation within the liver whilst the patient is very susceptible to infection. As a result treatment with drugs, such as steroids, which suppress the immune system may exacerbate the risk of infection. In our recent trial we demonstrated that prednisolone (a steroid) reduced mortality by a small amount one month after admission but the advantage was lost at three months. Therefore, at present there is no effective treatment for this condition. The aim of this research is to develop clinical tests (biomarkers) which improve the management of alcoholic hepatitis and which help the pharmaceutical industry to run trials in this area. Firstly, we will use a test which measures the amount of bacterial DNA in blood to stratify the risk of infection. Identifying patients who are at high risk of infection will allow us to modify treatment, either by avoiding steroids or adding in prophylactic antibiotics. This test will also identify a group of patients who would benefit from new treatment options. Our second aim is to improve the way in which we predict the outcome of this disease. We have previously shown that low transferrin (a serum protein) and a variant of the gene PNPLA3 are associated with a poor prognosis. An existing blood test (ELF), which is a good prognostic test in chronic hepatitis, will be tested in alcoholic hepatitis patients. We propose to combine the new biomarkers with routine clinical data and, using sophisticated statistical techniques, generate a more accurate prognostic scoring system. This will allow us to select patients more carefully for clinical trials, for intensive care and for liver transplantation. Although it is possible to make a diagnosis of alcoholic hepatitis based on the clinical presentation, we sometimes need to perform a liver biopsy to confirm the diagnosis. Furthermore, a biopsy is usually required in clinical trials. We are planning to develop a blood test based on the levels of a bile acid, taurocholate, which will reduce or eliminate the need for liver biopsy. In patients with alcoholic hepatitis the immune system is impaired making them susceptible to infections that increase the risk of dying. Analysis of the characteristics of immune cells in the blood will allow us to identify immune profiles which confer susceptibility to infection. We will use these immune profiles to evaluate new drugs in order to assess whether they are likely to increase the risk of infection either by testing the drugs on immune cells in the laboratory or by conducting immune profiling in the early stages of clinical trials. If our programme of research is successful we should be able to use existing drugs more effectively by avoiding complication such as infection. In addition we will encourage and facilitate pharmaceutical companies to invest in this disease area where there is a substantial unmet medical need.

Living organisms are made up of a very large quantity of cells. Each of these cells contains machinery that is essential to maintain and develop the life of a particular organism. These cells are surrounded by a waterproof lipid membrane, which encapsulates the mostly aqueous interior of a cell that includes also the essential molecular machinery. Every process of life both on a large as well as on a small scale involves continuous adaptations to a changing environment. Following such changes and responding to the demands that arise through the activities of the organisms the conditions within the individual cells need to be continuously adjusted. Every cell needs to be supplemented with nutrients for energy and building materials, waste products need to be removed and instructions need to be given for the multitude of different processes to act in a concerted manner. To facilitate these requirements across the impenetrable lipid membrane a large number of proteins are embedded into the cell membrane. These proteins connect the cell exterior with the inside of the cell and are called membrane proteins. A particular group of these proteins is responsible for relaying information in form of control signals across the membrane. The cells are using these proteins as sensors that relay a message from the exterior to the inside of a cell, where a cell is then able to understand what adjustments need to be made. The range of such control signals can be very diverse and there are therefore several hundreds of these sensors making this a particularly important group of membrane proteins. In fact it turns out to be the largest family of proteins in humans. Our work is looking in more details at these proteins, the so-called G protein coupled receptors GPCRs. We are trying to understand how exactly it is that these proteins work and in particular how different external control signals for a given sensor facilitate the different responses on the inside of the cell. Exposure of these proteins on the surface of the cells makes them easily accessible, which is crucial for them to work properly. It makes them also ideal targets for drugs in situations when our body malfunctions and needs drug therapeutic help. Therefore next to the academic interest in understanding how these proteins work there is a large interest from the pharmaceutical industry for the development of newer and better drugs from which our general well being will benefit. To be able to address such questions typically requires biologists and chemists to zoom in on a molecular level using a range of biophysical techniques, which allow us to see what is happening on an atomic scale. Our lab is using a technique called nuclear magnetic resonance (NMR), which allows us to study these GPCR proteins in a nearly native environment. For the technique to work the GPCR under study is removed from the cell membrane but is still kept surrounded by a very small portion of it. These proteins are extremely unstable and hence very tricky to study. We are concentrating on a particular member of the GPCR family, which has been modified and displays enhanced properties to assist our investigations. These sensor proteins are considered to be highly mobile and their dynamic nature strongly influences how they function. NMR is an excellent method that can describe which parts of these proteins are flexible. We are particularly interested in studying how the mobility in these proteins changes in the presence of different external signals so that we can correlate these variations with the given responses inside the cell. Most likely our results will allow us to make conclusions that are very general in nature as it is highly likely that other GPCRs will function following a similar way of action. So far GPCRs have been elusive to such studies and our work intends to generate this novel insight.

Many bacterial pathogens colonise and persist in our bodies as harmless 'commensals' that do not cause disease. These bacteria persist even though our bodies produce antibodies against exposed structures on their surface. In this proposal, we aim to improve our understanding of how bacteria avoid these antibodies and whether these avoidance mechanisms influence the ability of bacteria to cause disease. Neisseria meningitidis is a bacterium that is a major cause of meningitis and blood-poisoning but is found in 10-30% of people (i.e. 'carriers') as a harmless commensal of the upper respiratory tract. This bacterial species is present on nasal tissues and at the back of the throat where it can persist for up to twelve months despite the generation of antibodies against surface antigens of the bacteria. One way these bacteria avoid deleterious effects of antibodies is by changing the structure or amounts of these surface antigens. These changes are controlled by repetitive DNA tracts, which mutate at high frequencies resulting in alterations in the expression of genes that make these surface antigens. We have shown that persistence of N. meningitidis in the upper respiratory tract is facilitated by high frequencies of mutations in these repetitive DNA tracts causing reductions in expression of some of the surface antigens. As many of these surface antigens help the bacteria to invade tissues and to survive killing by cells and molecules present in blood, this finding has led us to speculate that reductions in expression of surface antigens, due to mutations in repetitive DNA, affects the ability of N. meningitidis to cause blood poisoning and meningitis. We will test this hypothesis by comparing the repetitive DNA tracts in bacterial isolates from patients and carriers. We will also test whether reductions in expression of specific antigens during persistent carriage of N. meningitidis is correlated with the presence of antibodies against that surface antigen. We will use samples from previous studies in volunteers from whom bacterial isolates, serum and saliva extracts were obtained at three or more time points over a six to twelve month time period. Similarly we will use pre-existing collections of N. meningitidis isolates from disease cases. The repetitive DNA tracts of multiple genes will be analysed by sizing of DNA fragments spanning the repetitive region so that we can count the numbers of repeats and then use these numbers to determine whether a gene is expressed. We will examine if a gene changes as the bacteria persist within a carrier and if the genes are in different states in the disease isolates as compared to those of carriers. The amounts of antibodies will be measured using a microassay. For this, protein products of genes will be purified, linked to fluorescent microspheres and incubated with serum. This will result in specific binding of antibodies to the proteins on the microspheres. Antibodies will then be detected with a different fluorescent tag and quantified in a fluorescence detection machine. We anticipate two major outcomes. Firstly, evidence of whether repetitive DNA produces a particular pattern of gene expression that enables N. meningitidis to cause disease. Identification of a 'virulence-associated' pattern would lead to production of novel preventive measures (i.e. vaccines containing these virulence determinants) or management of disease-cases (i.e. identification of sources of infections and rational decisions on when to provide preventive therapeutic treatment to contacts). Secondly, a demonstration that antibodies are driving reductions in expression of N. meningitidis surface antigens in carriers. This finding will indicate that vaccines containing surface antigens could reduce persistence of disease-causing N. meningitidis strains on mucosal surfaces of carriers and would be important for assessing whether Bexsero (the new MenB vaccine) can prevent spread of disease-causing strain.

The Liverpool University Drug Interactions group has over twenty years' experience in developing prescribing support resources in infectious diseases, demonstrated by our world-renowned HIV and Hepatitis drug interaction websites (www.hiv-druginteractions.org and www.hep-druginteractions.org) and associated Apps. In 2019, these websites had over 50,000 unique monthly visitors searching for >4.5 million interactions. Our websites are recommended in over 30 international treatment guidelines and many national guidelines. In response to the COVID-19 pandemic and to address the pressing need for prescribing support for studies and clinical situations where experimental COVID-19 therapies are being used, we have developed a static drug interactions website (www.covid19-druginteractions.org) providing information on the likelihood of interactions between the experimental agents and commonly prescribed co-medications. We now have to move to develop a fully interactive and searchable website resource with an associated App. The website will be constantly updated and populated with the latest information on experimental therapies with guidance given to clinicians for managing complex patients.