A new collaborative research paper sheds light on the way antibodies distinguish between different but closely related ‘biomarkers’ – in this case protein fragments which reveal information about the condition of the human body. This new understanding could enable pharmaceutical companies to develop new technologies for quickly diagnosing and treating fatal diseases.

This paper is a part of an international research project ‘Multiscale measurements in biophysical systems’, which is led by the National Physical Laboratory (NPL), UK, and jointly funded by NPL and the Scottish Universities Physics Alliance.

The research was carried out by the NPL, the University of Edinburgh and industrial partners from the UK (Mologic Ltd), US (IBM’s Watson Research Center) and the Netherlands (Pepscan Presto BV). The collaborative approach bought together world leading expertise in a number of areas, including biological measurements, computer modelling and medical research and technology.

The research in context

All diseases exhibit one or more molecular species, often proteins, which act as unique identifiers or biological markers. Detection of these ‘biomarkers’, among other closely related compounds, is a powerful and much sought after diagnostic capability. These biomarkers are detected by immunoassays – a test which mixes a substance (eg blood, urine) with antibodies, which bind to the protein if it is present. The antibodies can then be measured to identify the level of the biomarker, which in turn indicates the presence and extent of an illness.

Antibodies bind with high specificity to one protein molecule or a limited group of molecules (eg hormones), which is why antibodies can be used to test for specific biomarkers. Problems arise when they bind to groups of similar hormones that are associated with normal functions thereby leading to false positives and unreliable information. The highly sought solution is ‘intelligent selection’ of antibody-specific interaction sites on hormones that may differ from similar sites in other hormones by just one molecule – a ‘so called’ point mutation.

The findings

The research focused on hCG (human chorionic gonadotropin), a hormone normally produced during pregnancy. A subunit of hCG – hCG – is secreted by some cancers, meaning detection can give early warning of tumours. hCG is very similar to other reproductive hormones, known as LH and FSH, which are always present in the body. Reliable discrimination of hCG among these other hormones is a significant challenge and unreliable results are inevitable unless very high-fidelity tests can be developed.

The immunoassay antibodies bind to a tiny part of the hormone called an epitope. Hormones are made up of amino acids, with epitopes making up less than 10 of these blocks. These epitope regions are critical for the molecular-level recognition process and small differences in structure in these regions can have a major effect on the process of recognition and antibody binding.

The team showed how very subtle, atomic level characteristics define the antibody selectivity in closely related epitopes of different proteins. They identified that specific antibodies are highly selective in immunoassays and can distinguish between hCG and closely related LH fragments. Understanding these structural differences is likely to be the origin of the observed selectivity in the full hormones.

Armed with this knowledge, scientists can develop intelligent epitope selection to achieve clinically relevant assay performance. This means reliable tests can be developed to identify the presence of different hormones – in this case the presence of hCG which indicates cancer, as opposed to LH, which is always present.

The advances described in this research will enable the development of further immunoassays to identify other biomarkers from similar groups. Pharmaceutical companies could use this to develop new technologies for diagnostics and clinical disease treatments, for example tests for tumours as part of routine screenings. This work answers one of the big questions in distinguishing biomarkers which are critical for identifying and treating serious diseases. NPL hopes this breakthrough will underpin the development of a range of new diagnostic techniques and treatment.

Drawing together expertise

The research was a great example of an effective multidisciplinary collaboration. The various parties brought different areas of expertise to the project which worked together very well. The research was partly carried out with a view to proving a concept which would help Mologic, a UK biotechnology SME, to develop new diagnostic tools. Mologic, along with Pepscan Presto, a Dutch specialty-peptide company, worked together on the binding data measurements and the experimental design.

NPL provided the accurate experimental measurement of molecular structure, and IBM and the University of Edinburgh developed and ran powerful computer models to refine the experimental interpretation with structural data at atomic- level detail.

One of the problems with collaborations is that of finding a common language. Often different experts have a different understanding of the problem and different approaches to formulating a solution. Biologists approach problems in completely different ways to physicists. Industry often wants quick results, while academia wants to test it from every possible angle. People have different focuses and different motivations. But in this case it all came together perfectly. Despite having physicists, biologists, biophysicists and IT specialists, from academia and business, it all worked.

The reason for this was a comprehensive vision of the overall goal and a willingness to understand and benefit from each other’s expertise. There was a clear format – design the experiment, take the measurements, analyse the data – where everyone recognised their role.

The collaborative process

Biological target – Mologic determined which linear sequential epitopes were recognised by various antibody preparations, a library of overlapping peptides representing the entire sequence of hCG was created in several wells.

The first well was endowed with an array of identical immobilised peptides consisting of amino acids 1-12, the second well carried peptides consisting of amino acids 2-13, the third 3- 14, etc. In conjunction with further libraries constructed with longer peptides, these libraries were used to determine which host species (eg, mouse, rabbit or sheep) were able to produce antibodies that recognised the linear sequence of the 3-loop. From these findings a panel of candidate monoclonal antibodies with binding specificity for the 3-region were selected. The binding of antibodies to each peptide was tested in an Enzyme-linked immunosorbent assay (ELISA) at Pepscan.

The covalently linked peptides were incubated with primary antibody 8G5 (obtained from sheep) diluted in blocking solution. After the wells had been washed, the peptides were incubated with a 1/1,000 dilution of secondary antibody peroxidase to detect and quantify the binding of 8G5 antibodies. One peptide gave notable binding responses. This peptide was found to be identical to an LH fragment, with the only difference being an atomic detail in the side chain of one amino acid. Therefore, the two peptides (one from hCG and one from LH) were selected for comparative biophysical and molecular dynamics studies to reveal the structural rationale of the activity.

After a further washing step, a peroxidase substrate was added to provide fluorescence. Colour development was measured by means of an NPL charge coupled device (CCD) – a camera and an image processing system. Measurement – The biotechnology team at NPL provided expertise in an array of spectroscopic techniques. These techniques can be utilised to study the structure of proteins as structural changes can have a major impact on their activity, stability and toxicity, and consequently can compromise the efficacy and shelf life of products.

NPL characterised peptides in situ using two techniques, for which it has some of the world’s leading facilities. First measurements were carried out using circular dichroism (CD) spectroscopy. CD in the far UV region (180-260nm) provides information regarding different forms of regular secondary structure found in proteins. In the near UV region it can provide detailed fingerprints of tertiary structures, DNA-protein interactions and can also be very useful in the comparison of batches of pharmaceuticals.

Next, Fourier Transform Infrared (FTIR) Spectroscopy was used to facilitate the structural analysis of the proteins in different chemical environments. This technique is needed to analyse the structure of proteins at higher concentrations than CD and gives more detailed information about specific conformers and their relative ratios in a given peptide population. Molecular dynamics (MD) – Once measurements had been taken of the peptides they were passed on to IBM’s Watson Research Centre and The University of Edinburgh physics department to create models using molecular dynamics – a computer simulation of physical movements of atoms and molecules.

MD simulations offer powerful support to experimental programmes in biomolecular structure. In principle, MD simulations can provide ‘ultimate’ detail concerning individual molecular movement at full atomic resolution; thus, they can be used to answer specific questions about the properties of a system often more readily than experiments on the actual system, provided forces are accurately described and the sampling of configurations is sufficiently extensive.

In order to analyse the structure of the peptide using molecular dynamics simulations, the team made use of techniques known as Ramachandran plots and bond probability distribution functions. The former allows for the assignment of secondary structure motifs based on dihedral angles, while providing a clear illustration of the conformational space explored during the course of the simulation. The latter allows for the probability distribution of selected atomic contacts as a function of inter-atomic separation to be assessed.

The analysis was carried out on IBM’s machines, which are some of the most powerful modelling machines available, and some of the most advanced algorithms. Combined, the data revealed that hCG epitope adopts a very specific spatial arrangement, a -turn conformation, which stabilises it into an active form (Figure 1).

It is this form that is recognised by the antibodies. In contrast, the LH fragment does not have the same structure and cannot fix in space thus failing to bind the antibodies.

The benefits of collaboration

Essentially the benefits of collaboration are being able to share expertise and equipment. The people involved in this project are leaders in their area so drawing on their expertise is more efficient than going it alone. Beyond the joining together of expertise, it is also beneficial to have different perspectives. When you are working on your own you can become very focused on your area, which can make you a bit isolated.

Having a team around you, who understand the work but who have different areas of expertise is very valuable because you have input in each other’s work, and ask relevant questions. You also learn about each of their issues which can be valuable in leading to future collaborations.

A lot of small companies have brilliant ideas but do not have the facilities to develop them or to provide the data to support them. Even big companies rarely have the measurement expertise or facilities available at NPL. This is the value that large, public sector research organisations such as NPL can add. Excellent ideas are important, but understanding of all the complex factors that go into healthcare technology, from the behaviour of proteins to designing the technology, cannot be achieved by one organisation.

There is a critical need to draw on the expertise of the wider scientific community to make the kind of breakthroughs required to develop new medical techniques and provide the scientific rigour to take them to market.

NPL is a strong advocate of collaboration and is regularly involved in collaborations with industry and academia across all areas of science. NPL’s expertise in measurement, and the facilities it has access to are beyond the reach of most organisations. Yet accurate measurement is an important part of any research, from understanding complex atomic level interactions to providing rigorous data needed to take data to the next stage. Measurement also stimulates innovation in key areas such as diagnostics and drug development.

If the research is to inspire a product which will be sold to the medical industry, and become something on which life and death decisions are made, it must be backed by rigorous data, and that data can only come from the highest standards of measurement.

Open innovation

This kind of research is often funded at least for the initial stage. Organisations such as NPL can often work with smaller companies to access funding, either internally or externally, if there is expected value in pursuing a project. The advantage of publicly funded research is that it can contribute to overall understanding. In some cases the research may provide important data which will underpin new drug or diagnostics development. In other cases, initial funded research will be designed to prove a concept.

Here for example Mologic, which initiated the research, benefitted by proving its concept, which provides the underpinning to take the research to the next stage. If funded privately, this will provide it with valuable intellectual property to develop new products. However, the initial piece of research is now publicly available and other drug and diagnostic companies are free to use it to develop their own products, or to approach one or more of the consortium to fund further research into this area.

There was a huge amount of data created from the project, so it will probably be several months before other companies can start using it in a meaningful way, but it is now out there and can help companies in this area to develop new drugs or diagnostics based around how antibodies distinguish between closely related biomarkers.

Mologic, meanwhile, has gained valuable insight into an area of business interest, both from the results of the research and from the experience of taking part. It has proved its initial concept without great expense on its part, and is now in a sound position to take the idea forward, and hopefully turn the research into commercial technology which will improve the lives of those suffering from disease. Prof Paul Davis, Chief Scientific Officer of Mologic Ltd, was also delighted with the outcome. “It was a great collaborative effort and it stands as a fine example of what can be achieved when motivated scientists work together openly across boundaries,” he said.

This research was part of a larger project called ‘Multiscale measurements in biophysical systems’. The overall goal of the project, to be achieved through a range of research collaborations, is to sequence the structure of relevant peptides. This will help design peptides and sequences that can be selectively recognised to improve overall understanding of targeting disease. DDW

The full paper – Antibody recognition of a human chorionic gonadotropin epitope (hCG 66- 80) depends on local structure retained in the free peptide – will be published by the Journal of Biological Chemistry, the world’s premier and most cited forum for biological chemistry and molecular biology on July 15, 2011. www.ncbi.nlm.nih.gov/pubmed/21592960.

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This article originally featured in the DDW Spring 2012 Issue

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Dr Max Ryadnov obtained his PhD from Lomonosov Moscow State University and Russian Academy of Sciences in 2000. After a postdoctorate in Sussex, he pursued his independent research in Bristol prior to moving to Leicester as a University Lecturer. In 2010, he was appointed at NPL as a Principal Research Scientist to lead a technical research area focused on the analytical and engineering aspects of biomolecular metrology, and since 2011 he has held a joint lectureship in Chemical Physics with the University of Edinburgh. His main research aims at revealing the first design principles of polypeptide structure and recognition to enable prescriptive molecular diagnostics and therapy.

Professor Jason Crain is Professor of Applied Physics at the University of Edinburgh. His background is in condensed matter physics and disordered and exotic materials studied using experimental and computational techniques. He has made major contributions in elucidating structure property relationships in complex materials using simple or minimal model systems. He is founding Director of the COSMIC Research Center at the University of Edinburgh, Fellow of the Institute of Physics(IOP), Visiting Professor at the IBM T.J. Watson Research Center in New York, member of the steering committees of the IOP Liquids Group and the Scottish Bioinformatics Forum and former Royal Society of Edinburgh Research Fellow. He is currently on part-time secondment as Head of Physical Sciences at the UK’s National Physical Laboratory in London. He has authored more than 120 publications and holds five patents.