DelivEnz
Cutting-edge software for DELIVering industry’ ENZymes
The Objective
Scientific, technical or international impact
Gender dimension
Project Details
In a world facing major environmental threats, Europe (and Spain as part of it) stands by its commitments from the Paris Climate Conference and has agreed concrete measures in the European Green Deal: become the world’s first climate-neutral continent by 2050 while improving economic competitiveness. In this direction Spain submitted to the Commission its comprehensive National Energy and Climate Plan 2021-2030. These mediations are now marked by the necessary recovery after the COVID-19 crisis for which a Recovery, Transformation and Resilience plan has been agreed.
In this context, enzymes undoubtedly have a central role as green catalysts operating efficiently at low energy needs and enabling novel functionalities. However, one of the current main bottlenecks in the implementation of enzymes in greener industry processes and products, hindering economic competitiveness and greater sustainability, is that, although, bio-prospecting and engineering technology is enjoying a high level of sophistication, we are unable to accurately predict enzyme parameters from a protein sequence. This limits the exploitation of the existing large sequence databases for searching enzymes with industrial and manufacturing requirements. Succeeding in this undertaking would revolutionize the possibilities of industry to better recover the needed enzymes from the ever-increasing amount of sequencing data, which can be generated at an ever-lower price compared to any other method.
The Objective
In this Proof of Concept (PoC) we will develop and implement a user-friendly and predictive Machine Learning Metapredictor software prototype that has the capacity to pre-select in time frames as short as seconds, enzymes that meet the key performance indicators (KPIs) requested by industry from any sequence database.
More information
The input will be any type of amino acid sequence, structure or Protein Data Bank (PDB) code, and the on-demand manufacturers’ needs and specifications (e.g., the enzyme needed, the conditions at which the enzyme should work and be stable (pH, temperature, time, additives) and the substrate/s to convert). The output will consist in a list of the most confident sequences encoding enzymes that most likely will convert the requested molecules under the requested conditions, that is, a list of sequences encoding enzymes fitting the industry or manufacturers’ specifications. We anticipate that this prototype will offer, to industries and manufacturers that operate in multi-sectors, a platform to screen internal and public sequence repositories for those encoding enzymes with high probability to meet their specific demands. We expect the platform to be versatile and to be adapted to multiple industrial sectors and will be easily transferred to any industry, manufacturer or actor interested in implementing enzymes for specific purposes with which to support low emission, low-carbon circular economy and sustainable bio-based economy. This prototype will be applied to cover the search for enzymes that are at least among the highest priorities for industry, namely esterases/lipases, transaminases and aldo/keto-reductases, that are appropriate biocatalysts to improve competitiveness, innovation capacity, and sustainability in a modern low emission, low-carbon circular economy and sustainable bio-based economy. We expect the prototype to be versatile and to be adapted to the request of industries in multi-sectors, and its development is a very attractive idea which can have a fast transfer to industry.
Scientific, technical or international impact
The expected impacts are the scientific-technical, environmental, economic, business, market and social beneficial impacts derived from the computational integration of enzymatic datasets to develop a user-friendly and predictive Machine Learning Metapredictor software prototype through which enzyme properties can be predicted from sequence information. This prototype will have a direct impact of the way one can select, from any sequence database, enzymes that meet the key performance indicators requested by multi-sector industries.
En blanco
Scientific innovation
A better framework will be created for scientific innovation; it consists in a new software to screen enzymes, particularly esterases/lipases, transaminases and aldo keto-reductases, with industrial specifications.
Environment
The overall sustainability and innovation capacity of the bio-based sector will be improved through the use of an innovative software to screen enzyme with direct use by industry. The innovative platform will allow searching for industrial enzymes which will have a high positive environmental impact because of the possibility to make greener and more innovative real-life products and processes, whose production and use is associated with a very high impact on greenhouse gases (e.g., CO2) and chemical emissions, as well as the consumption of large amounts of energy, water and chemicals.
Economy
Awareness will be raised, and a better framework will be created for systemic innovation and uptake through increasing broad stakeholder and public engagement. This will be achieved by establishing an Open Access/Science, Digitalisation and Data Management, Intellectual Property Rights, Exploitation, Transfer and Market Plans.
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Society
The dissemination, communication and exploitation of the software and enzymes to be discovered using it and cross-sector interconnections with industries will be established. Stakeholders, scientists, and end-users will be involved in order to promote society’s perception and the implementation of global, National and European policies, specifically the COP21, European Green Deal, PENIEC, Recovery, Transformation and Resilience plans.
Innovation
Social innovation will be supported; this will apply if the enzyme which can be identified by the predictive software and the products and processes that can be made with those respond (at least in part) to social + citizen’s interests. These social impacts are important given that ca. 90% of consumers have a more positive image of a company that supports biotechnology, that 50% of European consumers are willing to recognise a green premium for a more sustainable greener alternative, and consumer behaviour can significantly decrease environmental impacts.
Cooperation
Through closer cooperation with industry, strategies will be developed to speed up the lab to market transition in the development of a software to search enzymes with which to achieve innovation and economic gain. This will be achieved because enzymes, products and processes that can enhance the competitiveness & sustainability of national and EU industry will be searched with the software to be implemented in the PoC. Delivenz will design a software that will promote the search and incorporation of a higher number of enzymes into the environment-friendly products and processes (actually <10% of consumer products contain enzymes). An exploitation plan to best explore market and business opportunities for the software and the enzymes that may derived from its use will be defined.
Gender dimension
Consistent with the priorities outlined in the EU’s and National’s objectives (including the promotion of gender equality in the I+D+i system and of the Integration of Gender Analysis in Research (IAGI)), Delivenz will establish as a priority an inclusive and transparent environment that, aligned to principles of Responsible Research and Innovation (RRI), recognises that the efforts of finding more sustainable alternatives should be aligned with a society in which gender equality as well as the rights of individuals, regardless of their racial, ethnic, cultural and educational backgrounds, are defended and integrated. Of the 4 researchers involved in MetaMorph (1 PI and 3 members in the Team), the gender ratio is 50% female and 50% male; the goal within this project is to maintain this percentage and reach after the recruitment stage also a minimum of 50% female researchers comprising PhDs and postdocs. A Gender, Ethics and Rights Task Force (described in Section 8a of the PoC), which will be managed by Dr M. Ferrer (MALE) and Dr. C. Coscolín (FEMALE), will be
implemented to defend gender equality, to improve the position and progression of women in science, to take into account gender issues when project information is communicated through providing an extensive communication network to promote gender equality (e.g. taking into account gender issues and possible different behaviour during the communication of the project), to continuously evaluate how Delivenz research affects gender issues, to collect statistics, and to solve problems or conflicts due to equality issues. The Gender, Ethics and Rights Committee will ensure that individuals of both genders, regardless of their racial, ethnic, cultural and educational backgrounds, will be integrated in all PoC. Finally, we would like to mention that members of the team will participate in events organized in the frame of the International Day of Women and Girls in Science.
Project Details
Reference: PDC2021-121534-I00
Starting date: 01.12.2021
End date: 30.11.2023
Name of the call: Proyectos de I+D+i de «Pruebas de Concepto», Programa estatal de I+D+i orientada a los Retos de la Sociedad – Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020, AEI / DOI (Digital Object Identifier) 10.13039/501100011033.
DelivEnz Cutting-edge software for DELIVering industry’ ENZymes
(ICP-CSIC)
28049-Madrid-Spain
