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Understanding the challenges of protein flexibility in drug design
(Taylor & Francis, 2015)
Introduction: Protein–ligand interactions play key roles in various metabolic pathways, and the proteins involved in these interactions represent major targets for drug discovery. Molecular docking is widely used to predict the structure of protein–ligand complexes, and protein flexibility stands out as one of the most important and challenging issues ...
DINC 2.0: A New Protein–Peptide Docking Webserver Using an Incremental Approach
(AACR, 2017)
Molecular docking is a standard computational approach to predict binding modes of protein–ligand complexes by exploring alternative orientations and conformations of the ligand (i.e., by exploring ligand flexibility). Docking tools are largely used for virtual screening of small drug-like molecules, but their accuracy and efficiency greatly decays ...
General Prediction of Peptide-MHC Binding Modes Using Incremental Docking: A Proof of Concept
(Springer Nature, 2018)
The class I major histocompatibility complex (MHC) is capable of binding peptides derived from intracellular proteins and displaying them at the cell surface. The recognition of these peptide-MHC (pMHC) complexes by T-cells is the cornerstone of cellular immunity, enabling the elimination of infected or tumoral cells. T-cell-based immunotherapies ...
Revealing Unknown Protein Structures Using Computational Conformational Sampling Guided by Experimental Hydrogen-Exchange Data
(MDPI, 2018)
Both experimental and computational methods are available to gather information about a protein's conformational space and interpret changes in protein structure. However, experimentally observing and computationally modeling large proteins remain critical challenges for structural biology. Our work aims at addressing these challenges by combining ...
Interpreting T-Cell Cross-reactivity through Structure: Implications for TCR-Based Cancer Immunotherapy
(Frontiers Media S.A., 2017)
Immunotherapy has become one of the most promising avenues for cancer treatment, making use of the patient’s own immune system to eliminate cancer cells. Clinical trials with T-cell-based immunotherapies have shown dramatic tumor regressions, being effective in multiple cancer types and for many different patients. Unfortunately, this progress was ...
Coarse-Grained Conformational Sampling of Protein Structure Improves the Fit to Experimental Hydrogen-Exchange Data
(Frontiers Media S.A., 2017)
Monitoring hydrogen/deuterium exchange (HDX) undergone by a protein in solution produces experimental data that translates into valuable information about the protein's structure. Data produced by HDX experiments is often interpreted using a crystal structure of the protein, when available. However, it has been shown that the correspondence between ...
Structure-based Methods for Binding Mode and Binding Affinity Prediction for Peptide-MHC Complexes
(Bentham Science, 2018)
Understanding the mechanisms involved in the activation of an immune response is essential to many fields in human health, including vaccine development and personalized cancer immunotherapy. A central step in the activation of the adaptive immune response is the recognition, by T-cell lymphocytes, of peptides displayed by a special type of receptor ...
HLA-Arena: A Customizable Environment for the Structural Modeling and Analysis of Peptide-HLA Complexes for Cancer Immunotherapy
(ASCO, 2020)
PURPOSE: HLA protein receptors play a key role in cellular immunity. They bind intracellular peptides and display them for recognition by T-cell lymphocytes. Because T-cell activation is partially driven by structural features of these peptide-HLA complexes, their structural modeling and analysis are becoming central components of cancer immunotherapy ...
Structural Modeling and Molecular Dynamics of the Immune Checkpoint Molecule HLA-G
(Frontiers, 2020)
HLA-G is considered to be an immune checkpoint molecule, a function that is closely linked to the structure and dynamics of the different HLA-G isoforms. Unfortunately, little is known about the structure and dynamics of these isoforms. For instance, there are only seven crystal structures of HLA-G molecules, being all related to a single isoform, ...
Large-Scale Structure-Based Prediction of Stable Peptide Binding to Class I HLAs Using Random Forests
(Frontiers, 2020)
Prediction of stable peptide binding to Class I HLAs is an important component for designing immunotherapies. While the best performing predictors are based on machine learning algorithms trained on peptide-HLA (pHLA) sequences, the use of structure for training predictors deserves further exploration. Given enough pHLA structures, a predictor based ...