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Método muy preciso para predecir la capacidad ligadora de proteínas


Oferta Tecnológica
Una empresa inglesa ofrece el método más preciso de diseño racional de fármacos que permite investigar la capacidad ligadora de sitios de un tamaño, forma y energía de desplazamiento de agua predeterminados de entre todas las combinaciones posibles. Este método permite desarrollar fármacos 10 veces más rápido y ofrece resultados con un alto grado de confianza. La empresa busca compañías de biotecnología con el fin de establecer acuerdos de servicio o cooperación técnica.


The most accurate way to predict protein ligandability
An East of England company has put forward by far the most accurate method for rational drug design. It lets one investigate ligandability of sites of desired (predetermined) size, shape and water displacement energy, from amongst all the possible combinations. Early drug development will be 10 times faster and will give results with very high confidence. Service agreements or technical cooperation is sought with biotechnology companies.
A drug is typically a small molecule, or a peptide that binds to a specific site on a protein. In order to do so, it must be of a very specific size and shape, to match the exact binding site. It must also displace a cluster of water molecules from the protein´s surface.
In practice, it has been rather challenging to spot and characterise such sites (and develop corresponding ligands into drugs). Replacement of water molecules is a good starting point to identify potentially druggable sites or further modify ligands to enhance potency or selectivity. There are products on the market to predict what kind of water clusters are easy to displace from the protein´s surface. However, there are serious limitations to the power of these products though and medicinal chemists rely on their intuition and other tools such as high-throughput screening, to come up with some good candidate structures.
A Cambridge startup now has the tool to find the needle in the haystack. It predicts all the possible sizes and shapes of water clusters on the protein and their corresponding energy levels in order to be displaced.
The innovation lies in how this computational complex problem has been solved for the first time. As a proof of concept, the prediction was compared against known ligands and their dissociation constants on hundreds of proteins from a couple dozen protein families. The prediction was right in terms of confirming the actual drug binding site as the most favourable site in the vast majority of cases. In remaining cases, the most favourable site was found but the actual binding site was elsewhere as an allosteric site. Such understanding allows one to develop molecules of higher affinity. There were no false negatives. Please see the attached picture. The green spot is the hot spot of a cluster the size of 18 water molecules that is the easiest to displace. On the right hand side, the blue cloud shows one all the possible clusters of 18 that are above the "easy to displace" threshold. Please note: whenever such clusters tend to overlap, it is a strong signal that this area is rather unique and drugs can be developed of high specificity. If the clusters of 18 were all over the surface, the matching ligands would bind elsewhere as well, with low specificity.
The method works with all possible combinations out of which one can focus on desired subgroups. Existing products don´t provide for that. For example, one can start from rational drug design and do fragment based discovery. To start off, clusters of a size of 4-6 are desirable. Similarly to picture below, there would be a smaller (or several) green spot and blue clouds around them. It is very important to be able to predict, in which direction the fragment can be continued to be grown, and with which properties.
Again, if one looks at clusters of 18 that correspond to an average small molecule hit of molecular weight 500, one can see where the boundaries go. Equally, the method may highlight allosteric sites instead.
Again, the method lets one investigate binding sites for peptides, of water cluster size of 30-40.
Last but not least, if the predictive power continues to be this high, one can investigate unknown ligands and binding sites where there is no homology or precedent. One can still tell with very high confidence if the target protein is ligandable (a good representation for being druggable, or druggability) and if there is good specificity.
The Cambridge company wishes to collaborate with biotechnology companies, irrespective of their stage of development. A project can start from de novo, or as a support for stop/go decisions, or replacing some arduous reiterations in the lead generation and lead optimisation.
Advantages and Innovations:
The innovation lies in solving a complex or NP problem, letting one investigate all the possible sizes, shapes and displacement energies whilst not overlooking the "needle in the haystack".
The advantages come in at various drug development stages, whether de novo, or solving problems in lead generation and optimisation. The method saves a lot of time and money in abandoning programmes that will not lead to anything, or shortening the reiterations in early drug development of about 10 times.
Stage of Development:
Available for demonstration
Secret Know-how

Partner sought

Type and Role of Partner Sought:
The Cambridge company offers the method as a service, starting from X-ray crystallography, NMR or other protein 3D model. The cooperation type could be a service agreement or technical cooperation. The partner would use the result from the process in their drug discovery or development programme, or a joint programme will be considered as a research cooperation.


Type and Size of Client:
Industry SME <= 10
Already Engaged in Trans-National Cooperation:
Languages Spoken:


Technology Keywords:
06002009 Diseño molecular
06002007 Ensayos in vitro, experimentos
06002004 Ingeniería de proteínas
06001015 Productos farmacéuticos / medicamentos