-
Journal of Molecular Biology Oct 2023The study of protein folding plays a crucial role in improving our understanding of protein function and of the relationship between genetics and phenotypes. In...
The study of protein folding plays a crucial role in improving our understanding of protein function and of the relationship between genetics and phenotypes. In particular, understanding the thermodynamics and kinetics of the folding process is important for uncovering the mechanisms behind human disorders caused by protein misfolding. To address this issue, it is essential to collect and curate experimental kinetic and thermodynamic data on protein folding. K-Pro is a new database designed for collecting and storing experimental kinetic data on monomeric proteins, with a two-state folding mechanism. With 1,529 records from 62 proteins corresponding to 65 structures, K-Pro contains various kinetic parameters such as the logarithm of the folding and unfolding rates, Tanford's β and the ϕ values. When available, the database also includes thermodynamic parameters associated with the kinetic data. K-Pro features a user-friendly interface that allows browsing and downloading kinetic data of interest. The graphical interface provides a visual representation of the protein and mutants, and it is cross-linked to key databases such as PDB, UniProt, and PubMed. K-Pro is open and freely accessible through https://folding.biofold.org/k-pro and supports the latest versions of popular browsers.
Topics: Humans; Databases, Protein; Kinetics; Protein Denaturation; Protein Folding; Proteins; Thermodynamics; Mutant Proteins
PubMed: 37625584
DOI: 10.1016/j.jmb.2023.168245 -
The Journal of Physical Chemistry. B Apr 2023Protein stability is important in many areas of life sciences. Thermal protein unfolding is investigated extensively with various spectroscopic techniques. The...
Protein stability is important in many areas of life sciences. Thermal protein unfolding is investigated extensively with various spectroscopic techniques. The extraction of thermodynamic properties from these measurements requires the application of models. Differential scanning calorimetry (DSC) is less common, but is unique as it measures directly a thermodynamic property, that is, the heat capacity (). The analysis of () is usually performed with the chemical equilibrium two-state model. This is not necessary and leads to incorrect thermodynamic consequences. Here we demonstrate a straightforward model-independent evaluation of heat capacity experiments in terms of protein unfolding enthalpy Δ(), entropy Δ(), and free energy Δ()). This now allows the comparison of the experimental thermodynamic data with the predictions of different models. We critically examined the standard chemical equilibrium two-state model, which predicts a positive free energy for the native protein, and diverges distinctly from the experimental temperature profiles. We propose two new models which are equally applicable to spectroscopy and calorimetry. The Θ()-weighted chemical equilibrium model and the statistical-mechanical two-state model provide excellent fits of the experimental data. They predict sigmoidal temperature profiles for enthalpy and entropy, and a trapezoidal temperature profile for the free energy. This is illustrated with experimental examples for heat and cold denaturation of lysozyme and β-lactoglobulin. We then show that the free energy is not a good criterion to judge protein stability. More useful parameters are discussed, including protein cooperativity. The new parameters are embedded in a well-defined thermodynamic context and are amenable to molecular dynamics calculations.
Topics: Hot Temperature; Protein Denaturation; Proteins; Thermodynamics; Cold Temperature; Protein Unfolding; Calorimetry, Differential Scanning; Protein Folding
PubMed: 37040567
DOI: 10.1021/acs.jpcb.3c00882 -
Communications Biology Mar 2023Recognition of remote homologous structures is a necessary module in AlphaFold2 and is also essential for the exploration of protein folding pathways. Here, we propose a...
Recognition of remote homologous structures is a necessary module in AlphaFold2 and is also essential for the exploration of protein folding pathways. Here, we propose a method, PAthreader, to recognize remote templates and explore folding pathways. Firstly, we design a three-track alignment between predicted distance profiles and structure profiles extracted from PDB and AlphaFold DB, to improve the recognition accuracy of remote templates. Secondly, we improve the performance of AlphaFold2 using the templates identified by PAthreader. Thirdly, we explore protein folding pathways based on our conjecture that dynamic folding information of protein is implicitly contained in its remote homologs. The results show that the average accuracy of PAthreader templates is 11.6% higher than that of HHsearch. In terms of structure modelling, PAthreader outperform AlphaFold2 and ranks first on the CAMEO blind test for the latest three months. Furthermore, we predict protein folding pathways for 37 proteins, in which the results of 7 proteins are almost consistent with those of biological experiments, and the other 30 human proteins have yet to be verified by biological experiments, revealing that folding information can be exploited from remote homologous structures.
Topics: Humans; Protein Folding; Recognition, Psychology
PubMed: 36871126
DOI: 10.1038/s42003-023-04605-8 -
ACS Nano Jul 2017Single-molecule studies of protein folding hold keys to unveiling protein folding pathways and elusive intermediate folding states-attractive pharmaceutical targets....
Single-molecule studies of protein folding hold keys to unveiling protein folding pathways and elusive intermediate folding states-attractive pharmaceutical targets. Although conventional single-molecule approaches can detect folding intermediates, they presently lack throughput and require elaborate labeling. Here, we theoretically show that measurements of ionic current through a nanopore containing a protein can report on the protein's folding state. Our all-atom molecular dynamics (MD) simulations show that the unfolding of a protein lowers the nanopore ionic current, an effect that originates from the reduction of ion mobility in proximity to a protein. Using a theoretical model, we show that the average change in ionic current produced by a folding-unfolding transition is detectable despite the orientational and conformational heterogeneity of the folded and unfolded states. By analyzing millisecond-long all-atom MD simulations of multiple protein transitions, we show that a nanopore ionic current recording can detect folding-unfolding transitions in real time and report on the structure of folding intermediates.
Topics: Databases, Protein; Ion Transport; Molecular Dynamics Simulation; Nanopores; Protein Conformation; Protein Folding; Protein Unfolding; Proteins
PubMed: 28693322
DOI: 10.1021/acsnano.7b02718 -
Journal of Chemical Theory and... Mar 2022Constantly advancing computer simulations of biomolecules provide huge amounts of data that are difficult to interpret. In particular, obtaining insights into functional...
Constantly advancing computer simulations of biomolecules provide huge amounts of data that are difficult to interpret. In particular, obtaining insights into functional aspects of macromolecular dynamics, often related to cascades of transient events, calls for methodologies that depart from the well-grounded framework of equilibrium statistical physics. One of the approaches toward the analysis of complex temporal data which has found applications in the fields of neuroscience and econometrics is Granger causality analysis. It allows determining which components of multidimensional time series are most influential for the evolution of the entire system, thus providing insights into causal relations within the dynamic structure of interest. In this work, we apply Granger analysis to a long molecular dynamics trajectory depicting repetitive folding and unfolding of a mini β-hairpin protein, CLN025. We find objective, quantitative evidence indicating that rearrangements within the hairpin turn region are determinant for protein folding and unfolding. On the contrary, interactions between hairpin arms score low on the causality scale. Taken together, these findings clearly favor the concept of zipperlike folding, which is one of two postulated β-hairpin folding mechanisms. More importantly, the results demonstrate the possibility of a conclusive application of Granger causality analysis to a biomolecular system.
Topics: Molecular Dynamics Simulation; Oligopeptides; Protein Folding
PubMed: 35167755
DOI: 10.1021/acs.jctc.1c00945 -
Journal of Chemical Information and... Apr 2023Recent advances in machine learning methods have had a significant impact on protein structure prediction, but accurate generation and characterization of...
Recent advances in machine learning methods have had a significant impact on protein structure prediction, but accurate generation and characterization of protein-folding pathways remains intractable. Here, we demonstrate how protein folding trajectories can be generated using a directed walk strategy operating in the space defined by the residue-level contact-map. This double-ended strategy views protein folding as a series of discrete transitions between connected minima on the potential energy surface. Subsequent reaction-path analysis for each transition enables thermodynamic and kinetic characterization of each protein-folding path. We validate the protein-folding paths generated by our discretized-walk strategy against direct molecular dynamics simulations for a series of model coarse-grained proteins constructed from hydrophobic and polar residues. This comparison demonstrates that ranking discretized paths based on the intermediate energy barriers provides a convenient route to identifying physically sensible folding ensembles. Importantly, by using directed walks in the protein contact-map space, we circumvent several of the traditional challenges associated with protein-folding studies, namely, long time scales required and the choice of a specific order parameter to drive the folding process. As such, our approach offers a useful new route for studying the protein-folding problem.
Topics: Proteins; Protein Folding; Molecular Dynamics Simulation; Thermodynamics; Hydrophobic and Hydrophilic Interactions; Protein Conformation
PubMed: 36995250
DOI: 10.1021/acs.jcim.3c00023 -
The International Journal of... Nov 2017The key role of monoamine transporters is to take up neurotransmitters from the synaptic cleft and rapidly terminate neurotransmission. Monoamine transporters begin... (Review)
Review
The key role of monoamine transporters is to take up neurotransmitters from the synaptic cleft and rapidly terminate neurotransmission. Monoamine transporters begin their journey by folding in the endoplasmic reticulum. Upon achieving their natively-folded state, the oligomerized transporters engage the coat protein complex II machinery and exit the endoplasmic reticulum compartment in a concentrative fashion. The transporters are subsequently sorted in the endoplasmic reticulum-Golgi intermediate complex and the Golgi apparatus, prior to reaching their pivotal site of action at the plasma membrane. Stringent quality-control mechanisms ensure that only the correctly-folded protein cargo departs the endoplasmic reticulum. Genetic point mutations in the coding sequences of monoamine transporters can trigger severe physiologic deficiencies by inducing folding defects. Protein misfolding precludes the delivery of functional monoamine transporters to the cell surface. Chemical- and/or pharmacological-chaperone molecules, which facilitate folding, have proven effective in restoring the activity of several misfolded pathological variants of monoamine transporters.
Topics: Animals; Endoplasmic Reticulum; Humans; Molecular Targeted Therapy; Neurotransmitter Transport Proteins; Protein Folding; Small Molecule Libraries
PubMed: 28890376
DOI: 10.1016/j.biocel.2017.09.004 -
BMC Bioinformatics Nov 2023Recently, significant progress has been made in the field of protein structure prediction by the application of artificial intelligence techniques, as shown by the...
BACKGROUND
Recently, significant progress has been made in the field of protein structure prediction by the application of artificial intelligence techniques, as shown by the results of the CASP13 and CASP14 (Critical Assessment of Structure Prediction) competition. However, the question of the mechanism behind the protein folding process itself remains unanswered. Correctly predicting the structure also does not solve the problem of, for example, amyloid proteins, where a polypeptide chain with an unaltered sequence adopts a different 3D structure.
RESULTS
This work was an attempt at explaining the structural variation by considering the contribution of the environment to protein structuring. The application of the fuzzy oil drop (FOD) model to assess the validity of the selected models provided in the CASP13, CASP14 and CASP15 projects reveals the need for an environmental factor to determine the 3D structure of proteins. Consideration of the external force field in the form of polar water (Fuzzy Oil Drop) and a version modified by the presence of the hydrophobic compounds, FOD-M (FOD-Modified) reveals that the protein folding process is environmentally dependent. An analysis of selected models from the CASP competitions indicates the need for structure prediction as dependent on the consideration of the protein folding environment.
CONCLUSIONS
The conditions governed by the environment direct the protein folding process occurring in a certain environment. Therefore, the variation of the external force field should be taken into account in the models used in protein structure prediction.
Topics: Artificial Intelligence; Models, Molecular; Proteins; Protein Folding; Hydrophobic and Hydrophilic Interactions; Protein Conformation
PubMed: 37950210
DOI: 10.1186/s12859-023-05559-8 -
Proceedings of the National Academy of... Aug 2020
Topics: Kinetics; Protein Conformation; Protein Folding; Radiography; X-Rays
PubMed: 32723817
DOI: 10.1073/pnas.2009596117 -
Proteins Sep 2022The contact topology of a protein determines important aspects of the folding process. The topological measure of contact order has been shown to be predictive of the...
The contact topology of a protein determines important aspects of the folding process. The topological measure of contact order has been shown to be predictive of the rate of folding. Circuit topology is emerging as another fundamental descriptor of biomolecular structure, with predicted effects on the folding rate. We analyze the residue-based circuit topological environments of 21 K mutations labeled as pathogenic or benign. Multiple statistical lines of reasoning support the conclusion that the number of contacts in two specific circuit topological arrangements, namely inverse parallel and cross relations, with contacts involving the mutated residue have discriminatory value in determining the pathogenicity of human variants. We investigate how results vary with residue type and according to whether the gene is essential. We further explore the relationship to a number of structural features and find that circuit topology provides nonredundant information on protein structures and pathogenicity of mutations. Results may have implications for the polymer physics of protein folding and suggest that "local" topological information, including residue-based circuit topology and residue contact order, could be useful in improving state-of-the-art machine learning algorithms for pathogenicity prediction.
Topics: Algorithms; Humans; Mutation, Missense; Protein Folding; Proteins; Virulence
PubMed: 35394672
DOI: 10.1002/prot.26342