{"id":142061,"date":"2026-09-16T08:34:37","date_gmt":"2026-09-16T08:34:37","guid":{"rendered":"https:\/\/www.embl.org\/about\/info\/arise\/?p=142061"},"modified":"2026-09-16T11:03:38","modified_gmt":"2026-09-16T11:03:38","slug":"inside-big-pharma-arise-fellow-grisell-diaz-leines-on-her-journey-at-johnson-johnson","status":"publish","type":"post","link":"https:\/\/www.embl.org\/about\/info\/arise\/blog\/2026\/09\/inside-big-pharma-arise-fellow-grisell-diaz-leines-on-her-journey-at-johnson-johnson\/","title":{"rendered":"Inside big pharma: ARISE fellow Grisell Diaz Leines on her journey at Johnson & Johnson"},"content":{"rendered":"\n

During her secondment at Johnson & Johnson, ARISE fellow Grisell Diaz Leines developed computational methods to identify and characterise protein-binding sites, accelerating advances in drug discovery.<\/h2>\n\n\n\n
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Grisell Diaz Leines is developing tools to deepen our understanding of protein surfaces and molecular interactions by characterising the geometry and dynamics of protein pockets and binding sites. Credit: Sudakshina Ganguly\/EMBL-EBI, Lis Albert\/EMBL.<\/figcaption><\/figure>\n\n\n\n

Grisell’s scientific path has been quite interdisciplinary. Her journey began at the National Autonomous University of Mexico<\/a>, where she earned her bachelor’s degree in physics. Later, she completed a PhD in molecular simulation at the University of Amsterdam<\/a>. Throughout her academic career, she has worked on protein folding, crystallisation,  and phase transformations, using molecular simulations and enhanced sampling methods to investigate complex molecular systems and materials across multiple spatial and temporal scales. <\/p>\n\n\n\n

Fascinated by understanding complex systems at the molecular and atomic levels and by developing computational approaches to study them, Grisell then pursued her interest in biological systems and data-driven approaches. As an ARISE fellow in the team of Sameer Velankar at the Protein Data Bank in Europe (PDBe<\/a>), and in close collaboration with Dr. Virginie Uhlmannat at EMBL-EBI<\/a>,  she integrates her background in physics, molecular modelling and artificial intelligence (AI) to develop computational tools that help researchers extract biological insights from large datasets. Ultimately, her research aims to enhance our understanding of biomolecular interactions and contribute to future therapeutic discovery and drug development efforts.<\/p>\n\n\n\n

Could you share what motivated you to apply to the ARISE programme, and give us a brief overview of your current project?<\/h3>\n\n\n\n

What attracted me to the ARISE programme<\/a> was its unique combination of scientific research, technology development, and training within a world-leading research infrastructure. Coming from a background in physics and molecular simulation, I was excited by the opportunity to apply my computational expertise to large-scale biological data and contribute to resources that support scientists worldwide. The programme also offered a valuable chance to broaden my perspective through interdisciplinary collaborations and exposure to different sectors, including industry.<\/p>\n\n\n\n

My project focuses on developing AI-powered computer vision methods to compare and classify macromolecular structures at scale. With the rapid growth of structural biology data from both experimental techniques and AI-based predictions, there is an increasing need for tools that can efficiently identify structural similarities and functional relationships across millions of protein structures. To address this challenge, I combine machine learning and geometric approaches to analyse protein surfaces and detect similarities in their shape and functional regions. The long-term goal is to improve the classification of macromolecular structural data in resources such as the Protein Data Bank<\/a>, PDBe<\/a>, EMDB<\/a>, and AlphaFoldDB<\/a>. This work will enable researchers to more easily discover connections and similarities among biomolecules, thereby deepening our understanding of protein interactions with other molecules, complex assemblies, and leveraging structural information for functional annotation and drug discovery efforts.<\/p>\n\n\n\n

Why did you decide to go to Johnson & Johnson, and what did you do during your secondment?<\/h3>\n\n\n\n

My secondment at Johnson & Johnson<\/a> (J&J) actually started through a conversation at the Industry Programme<\/a> Quarter meeting at EBI. My presentation at the meeting sparked the interest of Prof. Dr. Herman van Vlijmen, who approached me over lunch, where we discussed protein structure, dynamics, and the challenges of understanding protein flexibility. We then identified an exciting opportunity to design a project that combined my expertise in protein shape analysis, protein dynamics, and enhanced sampling simulations with their interests in computational drug discovery within the In Silico Discovery-Therapeutics Discovery team led by Dr. Vineet Pande.<\/p>\n\n\n\n

During the secondment, I worked on developing computational methods to identify and characterise protein-binding pockets from molecular dynamics simulations. Beyond studying protein flexibility, I was particularly interested in how pocket shape, volume, and geometry evolve over long simulation trajectories and how these changes can reveal ligandable or cryptic binding sites that are not apparent in static structures. To address this challenge, I developed a workflow that combines geometry-based pocket detection with automated clustering approaches to analyse large conformational ensembles and identify recurring pocket states with minimal user intervention. This experience gave me valuable insight into how computational methods are developed and applied within a multidisciplinary pharmaceutical research environment.<\/p>\n\n\n\n

What are you bringing back to EMBL from this experience?<\/h3>\n\n\n\n

One of the most valuable outcomes I have brought back to EMBL is a new perspective on how protein pocket geometry and conformational flexibility can be analysed at scale to support both functional annotation and drug discovery. While my work at PDBe focuses on AI-driven and bioimage analysis of macromolecular structures, the secondment also allowed me to revisit molecular simulations and explore how dynamic structural information can reveal biologically relevant binding sites often hidden in static protein structures.<\/p>\n\n\n\n

During the project, I developed expertise in characterising protein pockets across large-scale molecular dynamics trajectories, investigating how their shape and geometric properties evolve. This work opened up exciting new research directions that complement and expand my current activities in the ARISE programme and create opportunities to combine dynamic pocket information with AI-based methods for protein function prediction and ligand-binding site identification. Something particularly relevant to my upcoming projects.<\/p>\n\n\n\n

What are your thoughts on J&J as a secondment option for ARISE?<\/h3>\n\n\n\n

I think J&J is an excellent secondment option for ARISE fellows, particularly for those interested in drug discovery. One of its greatest strengths is the opportunity to see how cutting-edge research is translated into therapeutic development, from target identification and validation to drug discovery and clinical applications.<\/p>\n\n\n\n

For researchers working in areas such as structural biology, bioinformatics, or AI, a secondment at J&J provides valuable exposure to the application of computational methods in an industrial setting. It offers insights into how companies evaluate biological targets, manage projects, and integrate diverse data to drive research and development. Beyond the scientific experience, J&J offers the chance to work in multidisciplinary teams, gain a broader understanding of the industrial sector, and build connections beyond academia. Overall, I see J&J as a highly valuable ARISE secondment partner that provides a perspective to academic research while helping fellows develop skills and networks that can shape their future careers.<\/p>\n\n\n\n

What are your plans after ARISE?<\/h3>\n\n\n\n

Looking ahead, I am excited to continue developing the research directions established during my ARISE fellowship. After ARISE, I will participate as a researcher in the LIGMAP, a Wellcome Discovery Award project funded this year in our team, which aims to use AI to map protein pockets and their endogenous ligands. I will continue advancing methods for protein pocket characterisation and the analysis of molecular interactions using bioimage analysis approaches, geometric representations, and AI encoders. Building on my ARISE work, I aim to develop new methods for comparing and retrieving protein-binding sites based on their shape and interaction patterns, enabling large-scale studies of molecular recognition and protein function.<\/p>\n\n\n\n

The secondment also opened up exciting future research directions in protein dynamics. Particularly, I am interested in exploring how molecular simulations can help identify alternative conformations, flexible regions, and transient binding-site states that may not be apparent in static structures. Integrating this dynamic information with AI-based representations of protein surfaces and pockets could provide a richer understanding of molecular recognition and improve our ability to identify biologically relevant binding sites and functional relationships between proteins.<\/p>\n\n\n\n

Outside of your work at J&J, what have you experienced or enjoyed living in Belgium?<\/h3>\n\n\n\n

Although I have been working partly remotely during my secondment due to family commitments, I have combined this with several visits to Belgium over the six months of my secondment. I particularly enjoyed visiting Antwerp and Brugge, each with its own unique character and charm, but I mostly stayed in Turnhout, a small, quiet town near J&J. I also enjoyed discovering some of Belgium\u2019s culinary highlights, from its famous fries and chocolate to a wonderful Persian restaurant in Turnhout that became one of my favourite finds. A visit to the Chocolate Nation museum in Antwerp was another nice experience. I also enjoyed hanging out with my colleagues outside of work. Sharing dinners and informal conversations was a great way to learn about different perspectives, cultures, and career paths, and it helped me build connections that I hope will continue beyond the secondment. <\/p>\n\n\n\n

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During her time in Belgium, Grisell explored Antwerp and Turnhout, including a visit to the Chocolate Nation Museum in Antwerp. Credit: Giovanella Dell\u2019Orto, Grisell Diaz Leines\/EMBL.<\/figcaption><\/figure>\n\n\n\n
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\n \n About \u00a0Johnson & Johnson\n <\/h3>\n \n \n

J & J is a global healthcare company that focuses on developing innovative medical solutions in two core areas: Innovative Medicine for drug development and MedTech for medical equipment. As a partner in the ARISE Programme,\u00a0 J & J collaborates with EMBL to support the training of fellows by hosting them for their secondments. EMBL is grateful to J & J for its support of the ARISE mission.\u00a0 Applications for the ARISE2 programme<\/a> will be open from June 30 to September 30.<\/p>\n <\/div>\n<\/article>\n","protected":false},"excerpt":{"rendered":"

During her secondment at Johnson & Johnson, ARISE fellow Grisell Diaz Leines developed computational methods to identify and characterise protein-binding sites, accelerating advances in drug discovery.<\/p>\n","protected":false},"author":21,"featured_media":142075,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1,3127,2513],"tags":[],"embl_taxonomy":[],"class_list":["post-142061","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-general","category-project","category-secondment"],"acf":[],"embl_taxonomy_terms":[],"featured_image_src":"https:\/\/www.embl.org\/about\/info\/arise\/wp-content\/uploads\/2026\/09\/Grisell-Proteins-greenredyellow2000.png","_links":{"self":[{"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/posts\/142061","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/users\/21"}],"replies":[{"embeddable":true,"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/comments?post=142061"}],"version-history":[{"count":18,"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/posts\/142061\/revisions"}],"predecessor-version":[{"id":142325,"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/posts\/142061\/revisions\/142325"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/media\/142075"}],"wp:attachment":[{"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/media?parent=142061"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/categories?post=142061"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/tags?post=142061"},{"taxonomy":"embl_taxonomy","embeddable":true,"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/embl_taxonomy?post=142061"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}