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8th and Final ERNEST Meeting to Take Place in Crete with Participation from GPCR Drug Discovery Group
The 8th and final meeting of the European Research
Network on Signal Transduction (ERNEST) is set to take place from May 3-7, 2023 in Crete.
This event promises to be an exciting gathering of scientists from around the world who are
interested in the latest developments in signal transduction research. Among the attendees
will be several members of the G protein-coupled receptor (GPCR) Drug Discovery Group from
the GRIB in Barcelona...Show all
The 8th and final meeting of the European Research
Network on Signal Transduction (ERNEST) is set to take place from May 3-7, 2023 in Crete.
This event promises to be an exciting gathering of scientists from around the world who are
interested in the latest developments in signal transduction research. Among the attendees
will be several members of the G protein-coupled receptor (GPCR) Drug Discovery Group from
the GRIB in Barcelona.
ERNEST is a collaborative network of European research institutions that was established to
promote scientific excellence and cooperation in the field of signal transduction. The network
has been in operation for eight years, during which time it has fostered numerous successful
collaborations and research projects. The final meeting of ERNEST promises to be a fitting
conclusion to this productive period, and will feature presentations from some of the leading
lights in the field of signal transduction research. Hide
Revolutionary Alpha Fold Algorithm Unveiled: A Game-Changer for Protein Folding and Drug Discovery
In a groundbreaking new publication, researchers have unveiled
the latest advancements in the field of protein folding. The publication, titled "Alpha Fold: a
solution to a 50-year-old grand challenge in biology," details the creation of a powerful algorithm
that can predict the three-dimensional structures of proteins with unprecedented accuracy. This
breakthrough has the potential to revolutionize drug discovery, as it provides a more efficient way
to design and develop new drugs that can target specific proteins...Show all
In a groundbreaking new publication, researchers have unveiled
the latest advancements in the field of protein folding. The publication, titled "Alpha Fold: a
solution to a 50-year-old grand challenge in biology," details the creation of a powerful algorithm
that can predict the three-dimensional structures of proteins with unprecedented accuracy. This
breakthrough has the potential to revolutionize drug discovery, as it provides a more efficient way
to design and develop new drugs that can target specific proteins.
The research was carried out by a team at the University of Cambridge, led by Dr. Demis Hassabis,
co-founder of DeepMind, and Dr. John Jumper. The team used artificial intelligence to analyze the
genetic code of proteins and predict their structure. This is a significant development because,
until now, scientists have struggled to determine the structure of proteins, which has limited their
ability to understand how they function and develop drugs that can target them.
The publication has already generated a great deal of excitement in the scientific community, with
many experts hailing it as a major breakthrough in the field. The ability to predict protein
structures with such accuracy has the potential to revolutionize drug discovery and lead to the
development of more effective treatments for a range of diseases. The research has been widely
praised for its innovative use of AI and for the significant advances it represents in our
understanding of protein folding. Hide
Second simulation round
After our first successful publication in Nature
Methods, we are back to increase the data coverage of GPCRmd in a 2nd simulation
round...Show all
After our first successful publication in Nature
Methods, we are back to increase the data coverage of GPCRmd in a 2nd simulation
round.
In this round, we will focus on simulating all remaining PDB IDs which correspond to
GPCRs which are not in complex with G proteins, arrestins, or nanobodies.
Note that GPCR-G protein/arrestin/nanobody complexes will be addressed in the 3rd simulation
round starting in January 2021.
Hide
Nature publication: GPCRmd uncovers the dynamics
of the 3D-GPCRom
A groundbreaking paper titled "GPCRmd uncovers the dynamics
of the 3D-GPCRome" has just been published, offering new insights into the dynamics of G
protein-coupled receptors (GPCRs), a class of proteins that play a crucial role in signaling
pathways. The paper details the findings of the GPCRmd project, a collaborative effort between
several research institutions to create a comprehensive database of GPCR molecular dynamics
simulations...Show all
A groundbreaking paper titled "GPCRmd uncovers the dynamics
of the 3D-GPCRome" has just been published, offering new insights into the dynamics of G
protein-coupled receptors (GPCRs), a class of proteins that play a crucial role in signaling
pathways. The paper details the findings of the GPCRmd project, a collaborative effort between
several research institutions to create a comprehensive database of GPCR molecular dynamics
simulations.
The GPCRmd project used state-of-the-art molecular dynamics simulations to explore the behavior of
GPCRs in 3D space. The project was led by researchers from the Institute of Institut Hospital del Mar
d'Investigacions Mèdiques (IMIM) and the University Pompeu Fabra of Barcelona, in collaboration with several other institutions.
The resulting database provides a wealth of information about the behavior of GPCRs, including their
interactions with ligands and their structural changes over time.
The publication of this paper is a significant milestone in the field of GPCR research, offering new
insights into the dynamics of these important proteins. The findings of the GPCRmd project have the
potential to drive the development of new drugs that target GPCRs, which are involved in a wide range
of physiological processes. The database created by the project is freely available in our website to the scientific
community, providing a valuable resource for future research into GPCR dynamics and signaling
pathways. Hide