BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//SciLifeLab - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:SciLifeLab
X-ORIGINAL-URL:https://www.scilifelab.se
X-WR-CALDESC:Events for SciLifeLab
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/Stockholm
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20200329T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20201025T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20210328T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20211031T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20220327T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20221030T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20230326T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20231029T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20240331T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20241027T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20250330T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20251026T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20260329T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20261025T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20250612T150000
DTEND;TZID=Europe/Stockholm:20250612T160000
DTSTAMP:20260520T031814
CREATED:20250609T042830Z
LAST-MODIFIED:20250609T043118Z
UID:10001563-1749740400-1749744000@www.scilifelab.se
SUMMARY:Exploring the Protein Universe via Highly Accurate Structural Predictions
DESCRIPTION:Speaker\n\n\n\nMartin Steinegger\, Seoul National University \n\n\n\nAbstract\n\n\n\nUnderstanding relationships and functions of proteins at a global scale is key to unlocking newbiological insights. Through next-generation structure predictors like AlphaFold2 and ESMfold\,we now have access to an unprecedented volume of protein structures\, providing a crucialfoundation to address this challenge. In this talk\, I will present how our computationalmethods ColabFold\, MMseqs2\, and Foldseek together allow extraction of biological insightsfrom protein sequences and structures at nearly billion-scale. Additionally\, I will demonstratehow protein language models combined with sparse experimental data can guide andprioritize experimental efforts\, enabling efficient iterative “lab-in-the-loop” research.Together\, these tools democratize computational analysis and significantly acceleratediscoveries in protein biology.
URL:https://www.scilifelab.se/event/exploring-the-protein-universe-via-highly-accurate-structural-predictions/
LOCATION:Milkyway SciLifeLab Solna\, Tomtebodavägen 23\, Solna
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20250612T100000
DTEND;TZID=Europe/Stockholm:20250612T120000
DTSTAMP:20260520T031814
CREATED:20250603T140017Z
LAST-MODIFIED:20250603T140019Z
UID:10001562-1749722400-1749729600@www.scilifelab.se
SUMMARY:Towards Quantum Advantage by 2026: IBM’s Vision for Life Sciences
DESCRIPTION:Join us for a special guest talk with Dr. Gopal Karemore\, as he outlines how quantum computing is unlocking new possibilities in biomedical research and reshaping the future of healthcare innovation.With a background in data science and nearly a decade at Novo Nordisk\, Gopal now leads IBM Quantum’s global strategy for applying quantum technologies to challenges in drug discovery\, biomolecular simulation\, and precision medicine to help enterprise clients. His work includes advancing methods like Sample-Based Quantum Diagonalization (SBQD) and contributing in collaborations with organizations such as Moderna and Cleveland Clinic. In this session\, Gopal will: \n\n\n\n\nIntroduce IBM’s roadmap to achieving quantum advantage by 2026\n\n\n\nDiscuss how quantum technologies intersect with key challenges in healthcare and life sciences\n\n\n\nShare real-world use cases from IBM’s work in quantum simulation\, quantum optimization\, quantum machine learning and collaborative biomedical ecosystems\n\n\n\nExplore how researchers\, scientists\, and Nordic startups can engage with IBM — whether through programs like the Quantum Accelerator or other pathways — to gain access to quantum technologies already available today.\n\n\n\nThis talk is ideal for scientists\, clinicians\, data specialists\, and innovators interested in the next frontier of life science computation — and how Sweden’s research community can help shape it.\n\n\n\n\nPlace: SciLife Lab\, Tomtebodavägen 23\, Solna. Conference room “Air&Fire”. \n\n\n\nAgenda: 10.15 – 10:30 – Doors open & welcome10:30 – 11:30 – Presentation by Gopal Karemore followed by Q&A11:30 –12:00 – Lunch & networking mingleAbout the Speaker:Dr. Gopal Karemore is the Global Quantum Lead for Healthcare and Life Sciences at IBM Research\, based at the T.J. Watson Research Centre in New York. He leads efforts to drive the adoption of quantum computing in life sciences and healthcare\, working with IBM teams and external partners to deliver high-impact solutions. With over 14 years of experience in pharmaceutical research\, Dr. Karemore brings deep expertise in data science\, machine learning\, and quantum computing. He holds a Ph.D. in Computer Science from the University of Copenhagen and has contributed to shaping innovation and business development across pharmaceutical R&D. Prior to joining IBM\, he held research and leadership roles at Novo Nordisk\, Spanish National Centre for Cardiovascular Research\, Danish Stem Cell Centre\, Centre for Protein Research\, Fraunhofer Institute\, and Penn Medicine.
URL:https://www.scilifelab.se/event/towards-quantum-advantage-by-2026-ibms-vision-for-life-sciences/
LOCATION:Air&Fire\, SciLifeLab Stockholm\, Tomtebodavägen 23A\, Solna\, Sweden
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20240522T160000
DTEND;TZID=Europe/Stockholm:20240522T170000
DTSTAMP:20260520T031814
CREATED:20240402T112908Z
LAST-MODIFIED:20240402T112910Z
UID:10001223-1716393600-1716397200@www.scilifelab.se
SUMMARY:Insights into Human Atherosclerosis using novel tools for Spatial biology
DESCRIPTION:Sikander Hayat\, Translational Data Science\, Uniklinik Aachen \n\n\n\nInsights into Human Atherosclerosis using novel tools for Spatial biology \n\n\n\nSingle-cell and spatial technologies are paving the way to understand human health\, disease and aging at unprecedented resolution. How can we best leverage diverse multi-omics data to generate testable hypothesis and contribute to developing optimal precision therapies and biomarkers for human disease conditions? \n\n\n\nHayat lab is a new and interdisciplinary computational lab at the Institute of Experimental Medicine and Systems Biology\, UniKlinik Aachen. Our group focuses on developing computational tools for systematically analyzing\, interpreting and visualizing data from single-cell technologies such as single-cell transcriptomics\, spatial transcriptomics and high-content imaging. \n\n\n\nA key theme in our lab is to develop scalable and efficient tools to leverage data from millions of single-cells to understand disease\, health and aging. Some of the research areas we are working on include:   \n\n\n\n\nIdentifying novel targets and biomarkers for fibrosis in kidney and heart\,\n\n\n\nUnderstand mechanisms of heart failure at single-cell resolution\,\n\n\n\nElucidate processes involved in aging at single-cell resolution\,\n\n\n\nPrioritize high-impact mutations in cardio-renal disease\,\n\n\n\nDevelop tools for automated cell-type annotation\, multi-omics data integration\, and interactive data visualization\n\n\n\n\nWe work in very close collaboration with medical doctors and experimentalists in the Krammanlab (www.kramannlab.com) at UniKlinik RWTH Aachen.
URL:https://www.scilifelab.se/event/insights-into-human-atherosclerosis-using-novel-tools-for-spatial-biology/
LOCATION:Air&Fire\, SciLifeLab Stockholm\, Tomtebodavägen 23A\, Solna\, Sweden
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20240513T110000
DTEND;TZID=Europe/Stockholm:20240513T120000
DTSTAMP:20260520T031814
CREATED:20240430T071038Z
LAST-MODIFIED:20240513T045222Z
UID:10001247-1715598000-1715601600@www.scilifelab.se
SUMMARY:New insights into the lateral organization of biological membranes: Investigating the role of membrane dipole potential and the midplane interface
DESCRIPTION:Seminar by Frederick A. Heberle\, Department of Chemistry\, University of Tennessee\, Knoxville\, TN\, USA \n\n\n\nAbstract\n\n\n\nCells can dynamically alter the spatial organization of lipids and proteins in the plasma membrane to regulate processes including cell signaling. The size and morphology of membrane domains\, and how these depend on lipid composition\, have drawn attention as potentially key variables in these processes. Model membrane studies have proven invaluable for elucidating the influence of phospholipid chains and headgroups\, as well as cholesterol concentration\, on membrane properties and phase behavior. Using this kind of bottom-up approach\, my group employs a diverse set of biophysical techniques including fluorescence microscopy and spectroscopy\, small-angle neutron scattering\, and cryogenic electron microscopy to characterize the phase behavior of lipid bilayer mixtures. In this talk\, I will show how two important yet poorly understood features of lipid membranes—namely\, the membrane dipole potential and the midplane interface of a compositionally asymmetric bilayer—can profoundly affect lateral lipid organization. \n\n\n\nZoom link
URL:https://www.scilifelab.se/event/new-insights-into-the-lateral-organization-of-biological-membranes-investigating-the-role-of-membrane-dipole-potential-and-the-midplane-interface/
LOCATION:Air&Fire\, SciLifeLab Stockholm\, Tomtebodavägen 23A\, Solna\, Sweden
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20231006T110000
DTEND;TZID=Europe/Stockholm:20231006T120000
DTSTAMP:20260520T031814
CREATED:20230816T080538Z
LAST-MODIFIED:20231005T084643Z
UID:10000954-1696590000-1696593600@www.scilifelab.se
SUMMARY:From sequences to structures\, from structures to biology - On homo-oligomers and co-translational assembly
DESCRIPTION:Speaker: Emmanuel Levy\, Weizmann \n\n\n\nHost: Arne Elofsson \n\n\n\nIn this talk\, I will provide an overview of our research\, emphasizing two recent pieces of work. The first goes from sequences to structures\, with the development of an atlas of homo-oligomerization spanning proteomes and lineages (https://www.biorxiv.org/content/10.1101/2023.06.09.544317v1). The second goes from structures to biology\, leveraging protein complexes’ structures to crack the code of co-translational assembly.
URL:https://www.scilifelab.se/event/from-sequences-to-structures-from-structures-to-biology-on-homo-oligomers-and-co-translational-assembly/
LOCATION:Air&Fire\, SciLifeLab Stockholm\, Tomtebodavägen 23A\, Solna\, Sweden
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20230929T100000
DTEND;TZID=Europe/Stockholm:20230929T110000
DTSTAMP:20260520T031814
CREATED:20230816T080214Z
LAST-MODIFIED:20230922T144940Z
UID:10000952-1695981600-1695985200@www.scilifelab.se
SUMMARY:Computational Enzymology - Identifying Catalytic Modules and predicting Mechanisms
DESCRIPTION:Speaker: Janet Thornton\, EBI \n\n\n\nComputational Enzymology: Towards using knowledge of structure and function to predict enzyme transformations and mechanisms. \n\n\n\nJM Thornton\, AJM Ribeiro\, Ioannis Riziotis\, JD Tyzack\, Neera Borkakoti\, Roman Laskowski. European Bioinformatics Institute (EMBL-EBI)\, Wellcome Genome Campus\, Cambridge CB10 1SD\, UK \n\n\n\nEnzymes catalyse most of the chemical reactions which are essential for life. They are powerful catalysts that have evolved over millions of years to perform the functions in an organism that are necessary for survival. Using structural data and computational biology we seek to understand and predict how enzymes work and how they evolve to perform new enzyme functions. In this talk I will present our ongoing work to ‘perform catalysis’ in the computer. Using methods developed in cheminformatics\, combined with information derived from 3D enzyme structures\, we are developing tools to predict transformations and mechanisms.  \n\n\n\nHost: Arne Elofsson \n\n\n\nDame Janet M Thornton has contributed significantly to structural bioinformatics by increasing our fundamental understanding of the structure and function of proteins and how they contribute to disease and ageing. She has uniquely combined the analysis of structural features with the development of prediction methods. Together with Christine Orengo\, the popular database CATH was developed. Her studies of sidechain conformation and stereochemistry were developed with Roman Laskowski into a tool\,  PROCHECK\, widely used for evaluating the quality of experimentally defined protein structures. With Orengo and David Jones she developed methods for protein structure prediction. She was the director of the European Bioinformatics Institute from 2001 to 2015 and initiated the European infrastructure ELIXIR.
URL:https://www.scilifelab.se/event/computational-enzymology-identifying-catalytic-modules-and-predicting-mechanisms/
LOCATION:Gamma 2 Lunchroom\, SciLifeLab\, Tomtebodavägen 23\, Solna\, Sweden
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20230925T100000
DTEND;TZID=Europe/Stockholm:20230925T110000
DTSTAMP:20260520T031814
CREATED:20230816T080428Z
LAST-MODIFIED:20230816T080740Z
UID:10000953-1695636000-1695639600@www.scilifelab.se
SUMMARY:Dissecting peripheral protein-membrane interfaces
DESCRIPTION:Speaker: Nathalie Reuter\, Department of Chemistry and Computational Biology Unit\, University of Bergen \n\n\n\nHost: Arne Elofsson \n\n\n\nAbstract \n\n\n\nPeripheral membrane proteins (PMPs) are soluble proteins that bind transiently to the surface of cell membranes. Peripheral membrane proteins include a wide variety of proteins including membrane-targeting domains such as C1\, C2\, FYVE\, PH\, PX\, ENTH and GLA\, enzymes involved in lipid metabolism such as phospholipases\, membrane remodeling. machines such as BAR domains or ESCRTIII\, and lipid-transfer proteins to name a few. Having the ability to exist in both a soluble and a membrane-bound form their membrane-binding region is constrained to retain a fine balance of polar and hydrophobic character\, which makes it difficult to distinguish it from the rest of their surface. As a result peripheral membrane-binding sites are notoriously difficult to predict. \n\n\n\nWe collected and curated a dataset containing 2500 structures and compared their membrane-binding sites to the rest of their solvent-accessible surfaces\, in order to reveal features of PMPs’membrane-binding sites. We find that\, among positively charged amino acids\, lysines are significantly more present than arginines. Protruding hydrophobes are a landmark of the interfacial binding sites of ca. 2/3 of peripheral membrane binding proteins\, indicating that a majority of PMPs takes advantage of the hydrophobic effect while a non-negligeable minority (1/3) most likely relies on electrostatics interactions or other mechanisms. The IBS of peripheral membrane proteins contain significantly more glycines than the rest of their surface. Furthermore the analysis of 9 superfamilies revealed amino acid distribution patterns in agreement with their known functions and membrane-binding mechanisms. \n\n\n\nThese findings and the collected dataset will be useful for the development of prediction models for membrane-binding sites of PMPs.
URL:https://www.scilifelab.se/event/dissecting-peripheral-protein-membrane-interfaces/
LOCATION:Air&Fire\, SciLifeLab Stockholm\, Tomtebodavägen 23A\, Solna\, Sweden
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20230612T140000
DTEND;TZID=Europe/Stockholm:20230612T150000
DTSTAMP:20260520T031814
CREATED:20230609T113238Z
LAST-MODIFIED:20230609T113300Z
UID:10000911-1686578400-1686582000@www.scilifelab.se
SUMMARY:The first protein sweetener fit for the mass food market
DESCRIPTION:Speaker\n\n\n\nIlan Samish\, Amai Proteins \n\n\n\nHost\n\n\n\nArne Elofsson\, SciLifeLab \n\n\n\nAbstract\n\n\n\nSugar underlies the metabolic syndrome\, the topmost health problem of the world. Unfortunately\, the eight different categories of sugar reduction cannot reduce >30% of sugar without compromising the need for a tasty\, cost-efficient solution\, not to mention one which is healthy and sustainable. Hyper-sweet proteins\, found along the equatorial belt\, enable significant sugar reduction. Unlike small-molecule sweeteners\, they are digestible and consequently are not anticipated to ignite adverse effects inside our body. Yet\, they are costly\, unstable and have a compromised sensory profile. Here we present sweelin™\, a stable protein which enables up to 80% sugar reduction without compromising cost or taste as assessed by Amai’s supertaster panel. The novel protein was developed by optimizing the core\, loops\, and electrostatics of monellin\, a hyper-sweet and unstable protein. Following the AI-CPD (Computational Protein Design)\, the protein is manufactured via microbial precision fermentation. With numerous fee-bearing agreements with large food and beverage multinationals\, sweelin™ will be regulatory approved this year. The synergistic combination of AI-CPD\, microbial precision fermentation and food technology\, enables the development of numerous ‘super-proteins’ fit for the mass food market.
URL:https://www.scilifelab.se/event/the-first-protein-sweetener-fit-for-the-mass-food-market/
LOCATION:Air&Fire\, SciLifeLab Stockholm\, Tomtebodavägen 23A\, Solna\, Sweden
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20221021T110000
DTEND;TZID=Europe/Stockholm:20221021T120000
DTSTAMP:20260520T031814
CREATED:20221004T164130Z
LAST-MODIFIED:20221004T164133Z
UID:10000706-1666350000-1666353600@www.scilifelab.se
SUMMARY:3D-Equivariant Graph Neural Networks for Refining and Evaluating Protein Structures
DESCRIPTION:Speaker: \n\n\n\nJianlin Cheng\, Department of Electrical Engineering and Computer Science at the University of Missouri\, Columbia\, USA. \n\n\n\nTitle3D-Equivariant Graph Neural Networks for Refining and Evaluating Protein Structures \n\n\n\nAbstract \n\n\n\nDeep learning is revolutionizing the prediction of protein structure and is close to solve this grand challenge hanging over the scientific world for many years. In this talk\, I will describe how this technology emerged in the field\, how it overcame various technical hurdles to reach a high accuracy of predicting protein structures as demonstrated by AlphaFold2\, and where it is going now. I will present our latest work of applying 3D-equivariant graph neural networks with self- attention to evaluate and refine protein structural models. Our experiments demonstrate that 3D-equivariant graph network networks that are robust against the rotation and translation of 3D objects can evaluate and improve the quality of protein structures more effectively than the existing methods.
URL:https://www.scilifelab.se/event/3d-equivariant-graph-neural-networks-for-refining-and-evaluating-protein-structures/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20220926T090000
DTEND;TZID=Europe/Stockholm:20220926T100000
DTSTAMP:20260520T031814
CREATED:20220923T132853Z
LAST-MODIFIED:20220923T132926Z
UID:10000689-1664182800-1664186400@www.scilifelab.se
SUMMARY:Multiscale Modelling of Cancer Cell Motility and Tumour Evolution
DESCRIPTION:Paul Bates\, Cricks institute\, UK\n\n\n\n \n\n\n\n \n\n\n\n \n\n\n\nMultiscale Modelling of Cancer Cell Motility and Tumour Evolution \n\n\n\nSince Inhibiting metastasis is as crucial as minimising tumour growth for efficient treatment of cancer\, we constructed a multiscale model of cancer cell motility\, with our primary focus being on amoeboid type cell motility of metastasising tumour cells in the extracellular matrix (ECM).  Our model covered a wide parameter space and provided a deeper understanding of the conditions governing the motility of the cell at multiscale levels. Both the extracellular conditions (e.g. ECM density) and intrinsic cell properties (e.g. relative distribution of contractile and expanding regions of the cell membrane) were investigated.  The aim was to identify the combination of intrinsic properties metastasising cells are more likely to use under different extracellular conditions. After extensive benchmarking of the computational model using in vitro data\, we were able to predict cancer cell motility in vivo and under a number of different combinations of motility inhibitory\, such as key kinase inhibitors. We have also developed multiscale computer models to investigate how tumours evolve based upon Intra-tumour genetic heterogeneity (ITH)\, which fuels ongoing clonal evolution. Despite clarified clonal structure and acknowledged role of ITH in disease progression within our recent tumour study\, investigating clear-cell renal cell carcinomas (ccRCCs)\, there lacks characterisation of ongoing evolution that may inform future risk. By the combination of computer modelling and experimental analysis\, we investigated spatial features of narrow-scale clone diversity (microdiversity) and parallel evolution on the impact of spatial tumour growth. We observed frequent microdiversity hotspots and parallel evolution near the tumour margin and uncovered a scaling relationship between the area spanned by a genomic alteration and the number of subclones within that area\, in simulated tumours of 66 ccRCCs. Furthermore\, in-silico time-course studies showed that different modes of spatial growth caused varying extents and tempos of subclonal diversification.  Interestingly\, evolutionary trajectories were often predictable early\, suggesting that spatially resolved sampling combined with sequencing may enable identification of evolutionary potential in early-stage tumours.
URL:https://www.scilifelab.se/event/multiscale-modelling-of-cancer-cell-motility-and-tumour-evolution/
LOCATION:Air&Fire\, SciLifeLab Stockholm\, Tomtebodavägen 23A\, Solna\, Sweden
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20220519T140000
DTEND;TZID=Europe/Stockholm:20220519T180000
DTSTAMP:20260520T031814
CREATED:20220330T154729Z
LAST-MODIFIED:20220330T154904Z
UID:10000576-1652968800-1652983200@www.scilifelab.se
SUMMARY:Towards characterizing the human 3D-proteome - Nobel Symposium
DESCRIPTION:Public keynote lectures: 14:00-18:00 \n\n\n\nNo registration necessary\, but when the room is full\, it is full \n\n\n\nRead more\n\n\n\n\n\n\n\nProgram\n\n\n\n14:00 Introduction – Arne Elofsson14:15 Demis Hassabis\, DeepMind\, Using AI to model biology14:45 Sarah Teichmann\, Wellcome Sanger Institute\, TBD15:15 Sergey Ovchinnikov\, Harvard\, Inverting protein structure prediction models to solve problems in biology.For this talk I’ll describe some exciting applications of protein structure prediction models such as TrRosetta\, RoseTTAFold and AlphaFold. More specifically\, I’ll describe how we can invert these models for protein design\, generation of multiple sequence alignments and navigating the conformational landscape to predict structure(s) from single sequence\n\n\n\n15:45-16:15 Coffee \n\n\n\n16:15 Debora Marks\, Harvard\, TBD16:45 Alice Y Ting\, Stanford\, Spatial proteomics and transcriptomics via enzyme-catalyzed proximity labelingWhere a protein is localized in the cell exerts tremendous influence over its function\, interaction partners\, dynamics\, and modifications. Enzyme-catalyzed proximity labeling (PL) has emerged as a powerful and generalizable method to map the locations and interactions of endogenous proteins in the context of living cells\, applicable to even membraneless organelles and transient interactions that are inaccessible to traditional methods such as affinity purification. I will give a brief account of PL method development\, including directed evolution of the PL enzymes APEX and TurboID\, and then describe new efforts to extend PL to RNA and proteome trafficking.\n\n\n\n17:15 John Jumper\, DeepMind\, TBD17:45 Final Comments\n\n\n\nThe Nobel Foundation’s symposium activities were initiated in 1965. Over the years\, they have achieved a high international standing. The symposia are devoted to science areas where breakthroughs are occurring. \n\n\n\nThis symposium aims to bring together experts from various fields with the explicit goal of outlining a joint worldwide strategy to obtain a structural map of the human proteome. In addition to determining the structure and composition of all human proteins and their interactions\, it would also require understanding the flexible and dynamic supra-molecular structures in living cells\, such as multi-component membraneless organelles. A few key findings from the last years make us believe that this goal is achievable. First\, detailed knowledge of composition (splice forms\, PTMs) and expression levels in different cells are becoming available. Secondly\, Cryo-EM has revolutionized the structural determination of large protein complexes. Finally\, using co-evolution and advances in deep learning\, it is now possible to predict the structure of many individual proteins and complexes directly using no other information than the sequences and their evolutionary history. In the next few years\, combining the progress in these three areas will provide an opportunity to provide unprecedented molecular insights into the function of cells. Theoretical methods combined with ever-increasing sequence information will enable an understanding sequence and structural variation within populations\, both in humans and in disease-causing organisms.
URL:https://www.scilifelab.se/event/towards-characterizing-the-human-3d-proteome/
LOCATION:Beijersalen\, Kungl. Vetenskapakademien\, Lilla Frescativägen 4A\, Stockholm\, Sweden
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20211007T110000
DTEND;TZID=Europe/Stockholm:20211007T120000
DTSTAMP:20260520T031814
CREATED:20210930T131922Z
LAST-MODIFIED:20210930T132333Z
UID:10000458-1633604400-1633608000@www.scilifelab.se
SUMMARY:The current state of modeling protein motions : from physics to AI
DESCRIPTION:Location \n\n\n\nKinnekulle\, alfa 5\, Scilifelab (limited seatings) \n\n\n\n \n\n\n\n\n\n \n\n\n\nOnline \n\n\n\njoin zoom meeting\n\n\n\n \n\n\n\n \n\n\n\n\n\nInvited speaker: \n\n\n\nSergei Grudinin\, LJK CNRS Grenoble\, France\n\n\n\nArtificial intelligence\, and more specifically deep learning\, has recently emerged as a powerful approach to exploit the massive amounts of protein sequence and structure data available nowadays toward guiding biological intervention to improve human health. A couple of months ago\, the alphaFold2 architecture from DeepMind revolutionised the field of protein structure prediction by reaching unprecedented levels of near-experimental accuracy. This achievement has been made possible mostly thanks to the latest improvements in geometric learning and natural language processing (NLP) techniques.  \n\n\n\nWhile the problem of determining how a protein folds in three dimensions (3D) is essentially solved\,  accessing protein motions is becoming more central than ever before [1]. At the European level\, the ELIXIR community is investing efforts right  now to create a comprehensive resource for structural diversity and flexibility in the Protein Data Bank (PDB)\, which contains all experimentally-determined protein 3D structures. Indeed\, proteins are flexible biological objects\, constantly moving and changing their shape to interact with their environment and cellular partners. This inherent flexibility is highly relevant for protein functioning. Experimentally\, it is very difficult to observe proteins directly in action\, and we have mostly access to isolated clusters of “snapshots” (conformations) representative of a few functional states.  \n\n\n\nI will present relatively simple physics-based models developed in our team\, where the protein is represented by an elastic network. They have proven very useful to nonlinearly extrapolate functional motions\, starting from a single structure and predict structural protein transitions [2-4]. I will also show an extension of these developments to construct a multi-level representation of protein flexibility. Then\, I will outline the current state of AI methods to model protein structural heterogeneity and connect it with the physics-based models. \n\n\n\nReferences \n\n\n\n[1] Laine\, Elodie\, et al. “Protein sequence-to-structure learning: Is this the end (-to-end revolution)?.” Proteins in Press (2021).[2] Laine\, Elodie\, and Sergei Grudinin. “HOPMA: Boosting protein functional dynamics with colored contact maps.” The Journal of Physical Chemistry B 125.10 (2021): 2577-2588.[3] Grudinin\, Sergei\, Elodie Laine\, and Alexandre Hoffmann. “Predicting protein functional motions: an old recipe with a new twist.” Biophysical journal 118.10 (2020): 2513-2525.[4] Hoffmann\, Alexandre\, and Sergei Grudinin. “NOLB: Nonlinear rigid block normal-mode analysis method.” Journal of chemical theory and computation 13.5 (2017): 2123-2134.
URL:https://www.scilifelab.se/event/the-current-state-of-modeling-protein-motions-from-physics-to-ai/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
END:VCALENDAR