Invited speakers
Prof. Yinglong Miao
Computational Medicine Program and Department of Pharmacology, University of North Carolina – Chapel Hill, Chapel Hill, North Carolina, 27599, USA
Accelerated Molecular Simulations and Drug Discovery
Remarkable advances of supercomputing and Artificial Intelligence are transforming computational chemistry and biology in studies of molecules to cells. However, large gaps remain between the time scales of supercomputer simulations (typically microseconds) and those of biological processes (milliseconds or even longer). To bridge these gaps, our research is focused on the development of novel computational methods and Deep Learning (DL) techniques, including Gaussian accelerated molecular dynamics (GaMD) and Deep Boosted Molecular Dynamics (DBMD). Our recently developed selective GaMD algorithms have unprecedentedly enabled microsecond atomic simulations to capture repetitive dissociation and binding of small-molecule ligands, highly flexible peptides and proteins, thereby allowing for highly efficient and accurate calculations of their binding free energies and kinetics. In DBMD, probabilistic Bayesian neural network models are implemented to construct boost potentials that exhibit Gaussian distribution with minimized anharmonicity, which enables more accurate energetic reweighting and further enhanced simulations. Finally, we apply these new methods in advanced biomolecular modeling and computer-aided drug discovery. In collaboration with leading experimental groups, we combine complementary simulations and experiments to decipher functional mechanisms and design novel drug molecules of important biomolecules. Systems of our interest include G-protein-coupled receptors (GPCRs), membrane-embedded proteases, RNA-Binding Proteins and RNA
Prof. Sandra Macedo-Ribeiro
Instituto de Investigação e Inovação em Saúde (i3S)
Instituto de Biologia Molecular e Celular (IBMC)
Rua Alfredo Allen 208, 4200-135 Porto, Portugal
Pathogen-specific structural features in C. albicans Ras1 activation complex
Candida albicans, part of most individuals’ commensal microbiota, is a well-known opportunistic human pathogen. It causes more than 150 million mucosal infections per annum, and invasive Candidiasis in immunocompromised patients has a very high mortality rate (~60%).
The pathogenic potential of C. albicans is associated with its ability to switch between yeast and hyphal forms, a morphogenetic switch triggered by multiple signaling pathways, where the Ras-like protein 1 (CaRas1), activated by the Ras-guanine nucleotide exchange factor (GEF) CaCdc25, plays a central role. Although this central signaling complex constitutes an attractive target for drug development, the high amino acid sequence conservation of the G-domain of CaRas1 relative to its human homologs and the lack of structural information on both proteins (either isolated or in the complex) has so far impeded progress in this direction. Here, we use an integrative structural biology approach combining biochemical and biophysical experiments with structure predictions to report structural and functional features of CaRas1 and CaCdc25 proteins that are unique to pathogenic members of the Candida genus. The structural and biochemical analysis of CaRas1 and CaCdc25 revealed that the polyglutamine-rich hypervariable region of CaRas1, conserved in pathogenic Candida species, predominantly adopts a coiled-coil helical conformation and that CaCdc25 is a highly effective activator of CaRas1, with key residues for its activity located in a specific region of the α-helical hairpin of CaCdc25, exclusively conserved in the most common pathogenic Candida species. The new structural and functional information on the unique structural features of the hypervariable region of CaRas1 and of the α-helical hairpin of CaCdc25, conserved in pathogenic Candida species, provides new clues for antifungal drug development.
Prof. Massimo Aureli
Università degli Studi di Milano, Italy
Neuronal Differentiation and Degeneration: Role of the Plasma Membrane
Although we have made significant progress in understanding brain function, the cellular processes governing neuronal differentiation and degeneration remain largely unknown. One long-established fact, however, is that neurons undergo substantial changes in their morphology throughout their life cycle. The most prominent changes include neurite and axonal arborization, along with synapse formation during differentiation, and conversely, reduction and fragmentation during neurodegeneration and senescence. Given that these structures are extensions of the plasma membrane, it is clear that the plasma membrane plays a key role in these processes.
Neuronal plasma membranes differ from those of other cell types due to their enrichment in a specific class of lipids called glycosphingolipids. These amphiphilic molecules are located in the outer layer of the membrane and are concentrated in specialized microdomains known as “lipid rafts.” Within these lipid rafts, glycosphingolipids are believed to regulate various proteins associated with the plasma membrane, actively contributing to the “neuronal social life.”
In this lecture, I will try to present new findings on the role of glycosphingolipid composition in the regulation of plasma membrane-mediated signaling, which is crucial for neuronal differentiation and senescence.
Special Topic
Dr. Fabio Gasparini
Università degli Studi di Trento, Italy
A Tool is a tool is a tool. The alignment of computational methods and clinical and laboratory practices in biomedical experimental arrangements
In recent decades, research in biomedicine has undergone profound transformations in knowledge production methods and practices. The irruption of computational methods, such as the bioinformatic tools, and the use of algorithms and large databases is producing a reconfiguration of the biomedical field, capable of generating new questions and modifying experimental sets. Some authors have framed these changes by proposing provocative rhetoric of “the end of theory” or the end of the “experimental” way of reasoning (see Stevens 2013). That is, the computational exploration of large dataset would have substituted the formulation of hypothesis and the same practice of experimentation. This exploratory study challenges these rhetorics showing that knowledge production in biomedicine is still a matter of experimental arrangements. Based on ethnographic observation in a precision oncology laboratory and semi-structured interviews with biologists, bioinformaticians and data managers, this research has investigated the articulation of experimental practices and computational tools (the so-called distinction between “wet” and “dry” laboratories) in biomedical knowledge production and in its clinical application.
This lecture deal with the following research questions:
• How does a biomedical laboratory produce scientific knowledge that is qualified as evidence?
• What is the place of bioinformatics tools within the experimental arrangements of a translational research programme?