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Abstract:: The structural ensembles of intrinsically disordered proteins (IDPs) and proteins with intrinsically disordered regions (IDRs) cannot be easily characterized using conventional experimental techniques. Computational techniques complement experiments and provide useful insights into the structural ensembles of IDPs and proteins with IDRs. Herein, we discuss computational techniques such as homology modeling, molecular dynamics simulations, machine learning with molecular dynamics, and quantum computing that can be applied to the studies of IDPs and hybrid proteins with IDRs. We also provide useful future perspectives for computational techniques that can be applied to IDPs and hybrid proteins containing ordered domains and IDRs.
Machine learning with molecular dynamics, Intrinsically disordered proteins, Molecular dynamics simulations, Protein Conformation, Homology modeling, Quantum computing, Molecular Dynamics Simulation, Computing Methodologies, Intrinsically Disordered Proteins, Machine Learning, Proteins with intrinsically disordered regions, Quantum Theory
Machine learning with molecular dynamics, Intrinsically disordered proteins, Molecular dynamics simulations, Protein Conformation, Homology modeling, Quantum computing, Molecular Dynamics Simulation, Computing Methodologies, Intrinsically Disordered Proteins, Machine Learning, Proteins with intrinsically disordered regions, Quantum Theory
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