The druggable antimalarial target PfDXR : overproduction strategies and kinetic characterization

Plasmodium falciparum 1–deoxy–D–xylulose–5–phosphate reductoisomerase (PfDXR) is a key enzyme in the synthesis of isoprenoids in the malaria parasite, using a pathway that is absent in the human host. This enzyme is receiving attention as it has been validated as a promising drug target. However, an impediment to the characterisation of this enzyme has been the inability to obtain sufficient quantities of the enzyme in a soluble and functional form. The expression of PfDXR from the codon harmonised coding region, under conditions of strongly controlled transcription and induction, resulted in a yield of 2 – 4 mg/L of enzyme, which is 8 to 10–fold higher than previously reported yields. The kinetic parameters Km, Vmax and kcat were determined for PfDXR using an NADPH–dependent assay. Residues K295 and K297, unique to species of Plasmodium and located in the catalytic hatch region; and residues V114 and N115, essential for NADPH binding, were mutated to resemble those found in E. coli DXR. Interestingly, these mutations decreased the substrate affinity of PfDXR to values resembling that of E. coli DXR. PfDXR-K295N, K297S and PfDXR-V114A, N115G demonstrated a decreased ability to turnover substrate by 4–fold and 2-fold respectively in comparison to PfDXR. This study indicates a difference in the role of the catalytic hatch in capturing substrate by species of Plasmodium. The results of this study could contribute to the development of inhibitors of PfDXR.National Research Foundation Grant awarded to AB (Thuthuka Programme) and a SAMI Grant awarded to GLB. LSS was awarded a post–doctoral bursary by the South African Malaria Initiative programme; JG was awarded a PhD bursary by SAMI and National Research Foundation and HJ was awarded an Honours bursary by Rhodes University.http://www.eurekaselect.com/628/journal/protein-amp-peptide-lettershb201

The Malarial Drug Target Plasmodium falciparum 1-Deoxy-D-Xylulose-5- Phosphate Reductoisomerase (PfDXR): Development of a 3-D Model for Identification of Novel, Structural and Functional Features and for Inhibitor Screening

A three-dimensional model of the malarial drug target protein PfDXR was generated, and validated using structure-checking programs and protein docking studies. Structural and functional features unique to PfDXR were identified using the model and comparative sequence analyses with apicomplexan and non-apicomplexan DXR proteins. Furthermore, we have used the model to develop an efficient approach to screen for potential tool compounds for use in the rational design of novel DXR inhibitors

“Be sustainable”: EOSC‐Life recommendations for implementation of FAIR principles in life science data handling

The main goals and challenges for the life science communities in the Open Science framework are to increase reuse and sustainability of data resources, software tools, and workflows, especially in large‐scale data‐driven research and computational analyses. Here, we present key findings, procedures, effective measures and recommendations for generating and establishing sustainable life science resources based on the collaborative, cross‐disciplinary work done within the EOSC‐Life (European Open Science Cloud for Life Sciences) consortium. Bringing together 13 European life science research infrastructures, it has laid the foundation for an open, digital space to support biological and medical research. Using lessons learned from 27 selected projects, we describe the organisational, technical, financial and legal/ethical challenges that represent the main barriers to sustainability in the life sciences. We show how EOSC‐Life provides a model for sustainable data management according to FAIR (findability, accessibility, interoperability, and reusability) principles, including solutions for sensitive‐ and industry‐related resources, by means of cross‐disciplinary training and best practices sharing. Finally, we illustrate how data harmonisation and collaborative work facilitate interoperability of tools, data, solutions and lead to a better understanding of concepts, semantics and functionalities in the life sciences

Preprint: "Be Sustainable", Recommendations for FAIR Resources in Life Sciences research: EOSC-Life's Lessons

"Be SURE - Be SUstainable REcommendations" The main goals and challenges for the Life Science (LS) communities in the Open Science framework are to increase reuse and sustainability of data resources, software tools, and workflows, especially in large-scale data-driven research and computational analyses. Here, we present key findings, procedures, effective measures and recommendations for generating and establishing sustainable LS resources based on the collaborative, cross-disciplinary work done within the EOSC-Life (European Open Science Cloud for Life Sciences) consortium. Bringing together 13 European LS Research Infrastructures (RIs), it has laid the foundation for an open, digital space to support biological and medical research. Using lessons learned from 27 selected projects, we describe the organisational, technical, financial and legal/ethical challenges that represent the main barriers to sustainability in the life sciences. We show how EOSC-Life provides a model for sustainable FAIR data management, including solutions for sensitive- and industry-related resources, by means of cross-disciplinary training and best practices sharing. Finally, we illustrate how data harmonisation and collaborative work facilitate interoperability of tools, data, solutions and lead to a better understanding of concepts, semantics and functionalities in the life sciences. IN PRESS EMBO Journal: https://www.embopress.org/journal/14602075This research is mainly a product of the EOSC-Life European programme funding from the European Union's Horizon Europe research and innovation programme under grant agreement Nº824087. Complementary support was provided through EU funded project AgroServ (grant agreement Nº101058020), EU funded project BY-COVID (grant agreement Nº101046203), EU funded project DANUBIUS-IP (grant agreement Nº101079778), EU funded project EMPHASIS-GO (grant agreement Nº101079772), EU funded project FAIRplus (IMI grant agreement Nº802750), EU funded project FAIRsharing (Wellcome grant agreement Nº212930/Z/18/Z), EU funded project ISIDORe (grant agreement Nº101046133), EU funded project Precision Toxicology (grant agreement Nº965406), UKRI DASH (grant agreement NºMR/V038966/1). Special thanks to T. Biro and her radical collaboration team from Research Data Alliance who gave us great inspiration on how to lead this radical collaboration work

“Be sustainable”: EOSC‐Life recommendations for implementation of FAIR principles in life science data handling

The main goals and challenges for the life science communities in the Open Science framework are to increase reuse and sustainability of data resources, software tools, and workflows, especially in large-scale data-driven research and computational analyses. Here, we present key findings, procedures, effective measures and recommendations for generating and establishing sustainable life science resources based on the collaborative, cross-disciplinary work done within the EOSC-Life (European Open Science Cloud for Life Sciences) consortium. Bringing together 13 European life science research infrastructures, it has laid the foundation for an open, digital space to support biological and medical research. Using lessons learned from 27 selected projects, we describe the organisational, technical, financial and legal/ethical challenges that represent the main barriers to sustainability in the life sciences. We show how EOSC-Life provides a model for sustainable data management according to FAIR (findability, accessibility, interoperability, and reusability) principles, including solutions for sensitive- and industry-related resources, by means of cross-disciplinary training and best practices sharing. Finally, we illustrate how data harmonisation and collaborative work facilitate interoperability of tools, data, solutions and lead to a better understanding of concepts, semantics and functionalities in the life sciences