scholarly journals A Multiscale Model for Quantitative Prediction of Insulin Aggregation Nucleation Kinetics

2021 ◽  
Author(s):  
Rit Pratik Mishra ◽  
Gaurav Goel
Keyword(s):  
Kinetic Parameters ◽  
Single Molecule ◽  
Native Species ◽  
Structural Information ◽  
Quantitative Prediction ◽  
Balance Model ◽  
Nucleation Kinetics ◽  
Empirical Parameter ◽  
Computational Screening ◽  
Association Kinetics

We combined kinetic, thermodynamic, and structural information from single molecule (protein folding) and two molecule (protein association) explicit-solvent simulations for determination of kinetic parameters in protein aggregation nucleation with insulin as model protein. A structural bioinformatics approach was developed to account for heterogeneity of aggregation-prone species with the transition complex theory, developed for native protein-receptor interactions, found applicable in modeling association kinetics involving this non-native species. We show that a key simplification arises from presence of only a few relevant modes for non-native association kinetics and that it is necessary to explicitly account for conformational rearrangement of a diffusional intermediate leading to the formation of aggregation pathway dimer and small oligomers. The kinetic parameters thus obtained were used in a population balance model and very accurate predictions for aggregation nucleation time varying over two orders of magnitude with changes in concentration of insulin or an aggregation-inhibitor ligand were obtained while an empirical parameter set was not found to be transferable for prediction of ligand effects. This physically determined kinetic parameter set also provided several insights into the mechanism of aggregation nucleation. Finally we discuss a route for application of our approach in high-throughput computational screening of ligands for inhibiting aggregation.

scholarly journals Anharmonicity and Spectra–Structure Correlations in MIR and NIR Spectra of Crystalline Menadione (Vitamin K3)

Molecules ◽  
2021 ◽  
Vol 26 (22) ◽  
pp. 6779
Author(s):  
Krzysztof B. Beć ◽  
Justyna Grabska ◽  
Christian W. Huck ◽  
Sylwester Mazurek ◽  
Mirosław A. Czarnecki
Keyword(s):  
Single Molecule ◽  
Near Infrared ◽  
Structural Information ◽  
Molecular System ◽  
Theoretical Calculations ◽  
Vitamin K3 ◽  
Structure Correlations ◽  
Mir Spectra ◽  
Combination Bands ◽  
The Relationship

Mid-infrared (MIR) and near-infrared (NIR) spectra of crystalline menadione (vitamin K3) were measured and analyzed with aid of quantum chemical calculations. The calculations were carried out using the harmonic approach for the periodic model of crystal lattice and the anharmonic DVPT2 calculations applied for the single molecule model. The theoretical spectra accurately reconstructed the experimental ones permitting for reliable assignment of the MIR and NIR bands. For the first time, a detailed analysis of the NIR spectrum of a molecular system based on a naphthoquinone moiety was performed to elucidate the relationship between the chemical structure of menadione and the origin of the overtones and combination bands. In addition, the importance of these bands during interpretation of the MIR spectrum was demonstrated. The overtones and combination bands contribute to 46.4% of the total intensity of menadione in the range of 3600–2600 cm−1. Evidently, these bands play a key role in shaping of the C-H stretching region of MIR spectrum. We have shown also that the spectral regions without fundamentals may provide valuable structural information. For example, the theoretical calculations reliably reconstructed numerous overtones and combination bands in the 4000–3600 and 2800–1800 cm−1 ranges. These results, provide a comprehensive origin of the fundamentals, overtones and combination bands in the NIR and MIR spectra of menadione, and the relationship of these spectral features with the molecular structure.

scholarly journals Hierarchical coupling between ATP hydrolysis and Hsp90’s client binding site

2020 ◽  
Author(s):  
Steffen Wolf ◽  
Benedikt Sohmen ◽  
Björn Hellenkamp ◽  
Johann Thurn ◽  
Gerhard Stock ◽  
...  
Keyword(s):  
Binding Site ◽  
Single Molecule ◽  
Information Transfer ◽  
Atp Hydrolysis ◽  
Structural Information ◽  
Substrate Binding ◽  
Signal Propagation ◽  
Nonequilibrium Molecular Dynamics ◽  
Time Resolved ◽  
Substrate Binding Site

I.ABSTRACTSeveral indicators for a signal propagation from a binding site to a distant functional site have been found in the Hsp90 dimer. Here we determined a time-resolved pathway from ATP hydrolysis to changes in a distant folding substrate binding site. This was possible by combining single-molecule fluorescence-based methods with extensive atomistic nonequilibrium molecular dynamics simulations. We find that hydrolysis of one ATP effects a structural asymmetry in the full Hsp90 dimer that leads to the collapse of a central folding substrate binding site. Arg380 is the major mediator in transferring structural information from the nucleotide to the substrate binding site. This allosteric process occurs via hierarchical dynamics that involve timescales from picoto milliseconds and length scales from Ångstroms to several nanometers. We presume that similar hierarchical mechanisms are fundamental for information transfer through many other proteins.

scholarly journals Data Mining Crystallization Kinetics

2020 ◽  
Author(s):  
Cameron Brown ◽  
Diego Maldonado ◽  
Antony Vassileiou ◽  
Blair Johnston ◽  
Alastair Florence
Keyword(s):  
Random Forest ◽  
Kinetic Parameters ◽  
Crystallization Kinetics ◽  
Balance Model ◽  
Forest Models ◽  
Vast Literature ◽  
Random Forest Models ◽  
Kinetic Expression ◽  
Population Balances ◽  
Different Sources

<p>Population balance model is a valuable modelling tool which facilitates the optimization and understanding of crystallization processes. However, in order to use this tool, it is necessary to have previous knowledge of the crystallization kinetics, specifically crystal growth and nucleation. The majority of approaches to achieve proper estimations of kinetic parameters required experimental data. Across time, a vast literature about the estimation of kinetic parameters and population balances have been published. Considering the availability of data, this work built a database with information on solute, solvent, kinetic expression, parameters, crystallization method and seeding. Correlations were assessed and clusters structures identified by hierarchical clustering analysis. The final database contains 336 data of kinetic parameters from 185 different sources. The data were analysed using kinetic parameters of the most common expressions. Subsequently, clusters were identified for each kinetic model. With these clusters, classification random forest models were made using solute descriptors, seeding, solvent, and crystallization methods as classifiers. Random forest models had an overall classification accuracy higher than 70% whereby they were useful to provide rough estimates of kinetic parameters, although these methods have some limitations.</p>

scholarly journals Structural insights into the effect of active-site mutation on the catalytic mechanism of carbonic anhydrase

IUCrJ ◽  
2020 ◽  
Vol 7 (6) ◽  
pp. 985-994 ◽  
Author(s):  
Jin Kyun Kim ◽  
Cheol Lee ◽  
Seon Woo Lim ◽  
Jacob T. Andring ◽  
Aniruddha Adhikari ◽  
...  
Keyword(s):  
Carbonic Anhydrase ◽  
Kinetic Parameters ◽  
Active Site ◽  
Systematic Approach ◽  
Catalytic Mechanism ◽  
Structural Information ◽  
Site Directed Mutagenesis ◽  
Site Mutation ◽  
Functional Changes ◽  
Reaction Rate Constants

Enzymes are catalysts of biological processes. Significant insight into their catalytic mechanisms has been obtained by relating site-directed mutagenesis studies to kinetic activity assays. However, revealing the detailed relationship between structural modifications and functional changes remains challenging owing to the lack of information on reaction intermediates and of a systematic way of connecting them to the measured kinetic parameters. Here, a systematic approach to investigate the effect of an active-site-residue mutation on a model enzyme, human carbonic anhydrase II (CA II), is described. Firstly, structural analysis is performed on the crystallographic intermediate states of native CA II and its V143I variant. The structural comparison shows that the binding affinities and configurations of the substrate (CO2) and product (HCO3 −) are altered in the V143I variant and the water network in the water-replenishment pathway is restructured, while the proton-transfer pathway remains mostly unaffected. This structural information is then used to estimate the modifications of the reaction rate constants and the corresponding free-energy profiles of CA II catalysis. Finally, the obtained results are used to reveal the effect of the V143I mutation on the measured kinetic parameters (k cat and k cat/K m) at the atomic level. It is believed that the systematic approach outlined in this study may be used as a template to unravel the structure–function relationships of many other biologically important enzymes.

Quantitative single molecule FRET efficiencies using TIRF microscopy

2015 ◽  
Vol 184 ◽  
pp. 131-142 ◽  
Author(s):  
Lasse L. Hildebrandt ◽  
Søren Preus ◽  
Victoria Birkedal
Keyword(s):  
Single Molecule ◽  
Structural Information ◽  
Resonance Energy Transfer ◽  
Resonance Energy ◽  
Molecular Complexes ◽  
Distance Information ◽  
Single Molecule Level ◽  
Single Molecule Fret ◽  
Wide Range ◽  
Intermolecular Distances

Förster resonance energy transfer (FRET) microscopy at the single molecule level has the potential to yield information on intra and intermolecular distances within the 2–10 nm range of molecules or molecular complexes that undergo frequent conformation changes. A pre-requirement for obtaining accurate distance information is to determine quantitative instrument independent FRET efficiency values. Here, we applied and evaluated a procedure to determine quantitative FRET efficiencies directly from individual fluorescence time traces of surface immobilized DNA molecules without the need for external calibrants. To probe the robustness of the approach over a wide range of FRET efficiencies we used a set of doubly labelled double stranded DNA samples, where the acceptor position was varied systematically. Interestingly, we found that fluorescence contributions arising from direct acceptor excitation following donor excitation are intrinsically taken into account in these conditions as other correction factors can compensate for inaccurate values of these parameters. We give here guidelines, that can be used through tools within the iSMS software (http://www.isms.au.dk), for determining quantitative FRET and assess uncertainties linked with the procedure. Our results provide insights into the experimental parameters governing quantitative FRET determination, which is essential for obtaining accurate structural information from a wide range of biomolecules.

Quantitative structural information from single-molecule FRET

2015 ◽  
Vol 184 ◽  
pp. 117-129 ◽  
Author(s):  
M. Beckers ◽  
F. Drechsler ◽  
T. Eilert ◽  
J. Nagy ◽  
J. Michaelis
Keyword(s):  
Single Molecule ◽  
Structural Information ◽  
Monte Carlo Sampling ◽  
Dye Molecules ◽  
Distance Information ◽  
Single Molecule Fret ◽  
Single Molecule Studies ◽  
Archaeal Transcription ◽  
Short Time ◽  
Fluorescence Energy

Single-molecule studies can be used to study biological processes directly and in real-time. In particular, the fluorescence energy transfer between reporter dye molecules attached to specific sites on macromolecular complexes can be used to infer distance information. When several measurements are combined, the information can be used to determine the position and conformation of certain domains with respect to the complex. However, data analysis schemes that include all experimental uncertainties are highly complex, and the outcome depends on assumptions about the state of the dye molecules. Here, we present a new analysis algorithm using Bayesian parameter estimation based on Markov Chain Monte Carlo sampling and parallel tempering termed Fast-NPS that can analyse large smFRET networks in a relatively short time and yields the position of the dye molecules together with their respective uncertainties. Moreover, we show what effects different assumptions about the dye molecules have on the outcome. We discuss the possibilities and pitfalls in structure determination based on smFRET using experimental data for an archaeal transcription pre-initiation complex, whose architecture has recently been unravelled by smFRET measurements.

scholarly journals High-Definition Electronic Genome Maps from Single Molecule Data

2017 ◽  
Author(s):  
John S. Oliver ◽  
Anthony Catalano ◽  
Jennifer R. Davis ◽  
Boris S. Grinberg ◽  
Timothy E. Hutchins ◽  
...  
Keyword(s):  
Single Molecule ◽  
Structural Information ◽  
Signal To Noise Ratio ◽  
Physical Distance ◽  
Viscous Drag ◽  
High Signal ◽  
High Definition ◽  
Base Pairs ◽  
Solid State Detector ◽  
Genome Maps

With the advent of routine short-read genome sequencing has come a growing recognition of the importance of long-range, structural information in applications ranging from sequence assembly to the detection of structural variation. Here we describe the Nabsys solid-state detector capable of detecting tags on single molecules of DNA 100s of kilobases in length as they translocate through the detector at a velocity greater than 1 megabase pair per second. Sequence-specific tags are detected with a high signal-to-noise ratio. The physical distance between tags is determined after accounting for viscous drag-induced intramolecular velocity fluctuations. The accurate measurement of the physical distance between tags on each molecule and the ability of the detector to resolve distances between tags of less than 300 base-pairs enables the construction of high-density genome maps.

scholarly journals Data Mining Crystallization Kinetics

2020 ◽  
Author(s):  
Cameron Brown ◽  
Diego Maldonado ◽  
Antony Vassileiou ◽  
Blair Johnston ◽  
Alastair Florence
Keyword(s):  
Random Forest ◽  
Kinetic Parameters ◽  
Crystallization Kinetics ◽  
Balance Model ◽  
Forest Models ◽  
Vast Literature ◽  
Random Forest Models ◽  
Kinetic Expression ◽  
Population Balances ◽  
Different Sources

<p>Population balance model is a valuable modelling tool which facilitates the optimization and understanding of crystallization processes. However, in order to use this tool, it is necessary to have previous knowledge of the crystallization kinetics, specifically crystal growth and nucleation. The majority of approaches to achieve proper estimations of kinetic parameters required experimental data. Across time, a vast literature about the estimation of kinetic parameters and population balances have been published. Considering the availability of data, this work built a database with information on solute, solvent, kinetic expression, parameters, crystallization method and seeding. Correlations were assessed and clusters structures identified by hierarchical clustering analysis. The final database contains 336 data of kinetic parameters from 185 different sources. The data were analysed using kinetic parameters of the most common expressions. Subsequently, clusters were identified for each kinetic model. With these clusters, classification random forest models were made using solute descriptors, seeding, solvent, and crystallization methods as classifiers. Random forest models had an overall classification accuracy higher than 70% whereby they were useful to provide rough estimates of kinetic parameters, although these methods have some limitations.</p>

scholarly journals Ab Initio Prediction of High-Temperature Magnetic Relaxation Rates in Single-Molecule Magnets

2021 ◽  
Author(s):  
Daniel Reta ◽  
Jon G. C. Kragskow ◽  
Nicholas Chilton
Keyword(s):  
High Temperature ◽  
Ab Initio ◽  
Single Molecule ◽  
Magnetic Relaxation ◽  
Quantitative Prediction ◽  
Relaxation Dynamics ◽  
Efficient Design ◽  
Relaxation Rates ◽  
Design Strategies ◽  
Single Molecule Magnets

<p>Organometallic molecules based on [Dy(Cp<sup>R</sup>)<sub>2</sub>]<sup>+</sup> cations have emerged as clear front-runners in the search for high-temperature single-molecule magnets. However, despite a growing family of structurally-similar molecules, these molecules show significant variations in their magnetic properties, demonstrating the importance of understanding magneto-structural relationships towards developing more efficient design strategies. Here we refine our <i>ab initio</i> spin dynamics methodology and show that it is capable of quantitative prediction of relative relaxation rates in the Orbach region. Applying it to all reported [Dy(Cp<sup>R</sup>)<sub>2</sub>]<sup>+</sup> cations allows us to tease out differences in their relaxation dynamics, highlighting that the main discriminant is the magnitude of the crystal field splitting. We subsequently employ the method to predict relaxation rates for a series of hypothetical organometallic sandwich compounds, revealing an upper limit to the effective barrier to magnetic relaxation of around 2200 K, which has been reached. However, we show that further improvements to single-molecule magnets can be made by moving vibrational modes off-resonance with electronic excitations.</p>

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