Dependence of protein-induced lipid bilayer deformations on protein shape [PDF]
, 2022 Membrane proteins typically deform the surrounding lipid bilayer membrane, which can play an important role in the function, regulation, and organization of membrane proteins. Membrane elasticity theory provides a beautiful description of protein-induced lipid bilayer deformations, in which all physical parameters can be directly determined from ...
arxiv +1 more source
In silico evidence that protein unfolding is as a precursor of the protein aggregation [PDF]
ChemPhysChem 2020, 21, 377, 2019 We present a computational study on the folding and aggregation of proteins in aqueous environment, as function of its concentration. We show how the increase of the concentration of individual protein species can induce a partial unfolding of the native conformation without the occurrence of aggregates. A further increment of the protein concentration
arxiv +1 more source
Conformational ensembles of intrinsically disordered proteins and flexible multidomain proteins [PDF]
arXiv, 2021 Intrinsically disordered proteins (IDPs) and multidomain proteins with flexible linkers show a high level of structural heterogeneity and are best described by ensembles consisting of multiple conformations with associated thermodynamic weights.
arxiv
Ligand Binding, Protein Fluctuations, and Allosteric Free Energy [PDF]
, 2006 Although the importance of protein dynamics in protein function is generally recognized, the role of protein fluctuations in allosteric effects scarcely has been considered. To address this gap, the Kullback-Leibler divergence (Dx) between protein conformational distributions before and after ligand binding was proposed as a means of quantifying ...
arxiv +1 more source
Lipid-protein interaction induced domains: kinetics and conformational changes in multicomponent vesicles [PDF]
, 2018 The spatio-temporal organization of proteins and the associated morphological changes in membranes are of importance in cell signaling. Several mechanisms that promote the aggregation of proteins at low cell surface concentrations have been investigated in the past.
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Prompt-Guided Injection of Conformation to Pre-trained Protein Model [PDF]
arXiv, 2022 Pre-trained protein models (PTPMs) represent a protein with one fixed embedding and thus are not capable for diverse tasks. For example, protein structures can shift, namely protein folding, between several conformations in various biological processes.
arxiv
Cooperative Gating and Spatial Organization of Membrane Proteins through Elastic Interactions [PDF]
, 2007 Biological membranes are elastic media in which the presence of a transmembrane protein leads to local bilayer deformation. The energetics of deformation allow two membrane proteins in close proximity to influence each other's equilibrium conformation via their local deformations, and spatially organize the proteins based on their geometry.
arxiv +1 more source
Systematic conformation-to-phenotype mapping via limited deep-sequencing of proteins [PDF]
arXiv, 2022 Non-native conformations drive protein misfolding diseases, complicate bioengineering efforts, and fuel molecular evolution. No current experimental technique is well-suited for elucidating them and their phenotypic effects. Especially intractable are the transient conformations populated by intrinsically disordered proteins. We describe an approach to
arxiv
Predicting mutational effects on protein-protein binding via a side-chain diffusion probabilistic model [PDF]
arXiv, 2023 Many crucial biological processes rely on networks of protein-protein interactions. Predicting the effect of amino acid mutations on protein-protein binding is vital in protein engineering and therapeutic discovery. However, the scarcity of annotated experimental data on binding energy poses a significant challenge for developing computational ...
arxiv
Learning Geometrically Disentangled Representations of Protein Folding Simulations [PDF]
arXiv, 2022 Massive molecular simulations of drug-target proteins have been used as a tool to understand disease mechanism and develop therapeutics. This work focuses on learning a generative neural network on a structural ensemble of a drug-target protein, e.g. SARS-CoV-2 Spike protein, obtained from computationally expensive molecular simulations.
arxiv