Dynamic Perturbation Analysis Research Articles

Quantitative Characterization of the Impact of Protein-Protein Interactions on Ligand-Protein Binding: A Multi-Chain Dynamics Perturbation Analysis Method.

Many protein-protein interactions (PPIs) affect the ways in which small molecules bind to their constituent proteins, which can impact drug efficacy and regulatory mechanisms. While recent advances have improved our ability to independently predict both PPIs and ligand-protein interactions (LPIs), a comprehensive understanding of how PPIs affect LPIs is still lacking. Here, we examined 63 pairs of ligand-protein complexes in a benchmark dataset for protein-protein docking studies and quantified six typical effects of PPIs on LPIs. A multi-chain dynamics perturbation analysis method, called mcDPA, was developed to model these effects and used to predict small-molecule binding regions in protein-protein complexes. Our results illustrated that the mcDPA can capture the impact of PPI on LPI to varying degrees, with six similar changes in its predicted ligand-binding region. The calculations showed that 52% of the examined complexes had prediction accuracy at or above 50%, and 55% of the predictions had a recall of not less than 50%. When applied to 33 FDA-approved protein-protein-complex-targeting drugs, these numbers improved to 60% and 57% for the same accuracy and recall rates, respectively. The method developed in this study may help to design drug-target interactions in complex environments, such as in the case of protein-protein interactions.

Drug Repurposing for COVID-19 by Constructing a Comorbidity Network with Central Nervous System Disorders.

In the post-COVID-19 era, treatment options for potential SARS-CoV-2 outbreaks remain limited. An increased incidence of central nervous system (CNS) disorders has been observed in long-term COVID-19 patients. Understanding the shared molecular mechanisms between these conditions may provide new insights for developing effective therapies. This study developed an integrative drug-repurposing framework for COVID-19, leveraging comorbidity data with CNS disorders, network-based modular analysis, and dynamic perturbation analysis to identify potential drug targets and candidates against SARS-CoV-2. We constructed a comorbidity network based on the literature and data collection, including COVID-19-related proteins and genes associated with Alzheimer's disease, Parkinson's disease, multiple sclerosis, and autism spectrum disorder. Functional module detection and annotation identified a module primarily involved in protein synthesis as a key target module, utilizing connectivity map drug perturbation data. Through the construction of a weighted drug-target network and dynamic network-based drug-repurposing analysis, ubiquitin-carboxy-terminal hydrolase L1 emerged as a potential drug target. Molecular dynamics simulations suggested pregnenolone and BRD-K87426499 as two drug candidates for COVID-19. This study introduces a dynamic-perturbation-network-based drug-repurposing approach to identify COVID-19 drug targets and candidates by incorporating the comorbidity conditions of CNS disorders.

Dynamic perturbation analysis of fractional order differential quasiperiodic Mathieu equation

The paper investigates the influence of parameters on the stability of fractional order differential quasiperiodic Mathieu equations. First, we use the perturbation method to obtain approximate expressions (i.e., transition curves) for the stability and unstable region boundaries of the equation. After obtaining the approximate expression of the transition curve, we use Lyapunov's first method to analyze the stability of the fractional order differential quasiperiodic Mathieu system, thereby obtaining the conditions for the stability of the fractional order differential quasiperiodic Mathieu equation system. Second, by comparing the approximate expressions of the transition curve of the steady-state periodic solution of the quasiperiodic Mathieu oscillator under different parameter conditions, we obtained the conclusion that the fractional order differential term exists in the form of equivalent stiffness and equivalent damping in the fractional order differential quasiperiodic Mathieu system. By comparison, we have summarized the general forms of equivalent linear damping and equivalent stiffness of the system. Through this general form, we can define an approximate expression for the thickness of unstable regions to better study the characteristics of fractional order differential quasiperiodic Mathieu systems. Finally, the influence of the parameters of the fractional order differential quasiperiodic Mathieu equation on the transition curve of the equation was intuitively analyzed through numerical simulation, to analyze the stability changes in the equation.

A multilayer dynamic perturbation analysis method for predicting ligand–protein interactions

BackgroundLigand–protein interactions play a key role in defining protein function, and detecting natural ligands for a given protein is thus a very important bioengineering task. In particular, with the rapid development of AI-based structure prediction algorithms, batch structural models with high reliability and accuracy can be obtained at low cost, giving rise to the urgent requirement for the prediction of natural ligands based on protein structures. In recent years, although several structure-based methods have been developed to predict ligand-binding pockets and ligand-binding sites, accurate and rapid methods are still lacking, especially for the prediction of ligand-binding regions and the spatial extension of ligands in the pockets.ResultsIn this paper, we proposed a multilayer dynamics perturbation analysis (MDPA) method for predicting ligand-binding regions based solely on protein structure, which is an extended version of our previously developed fast dynamic perturbation analysis (FDPA) method. In MDPA/FDPA, ligand binding tends to occur in regions that cause large changes in protein conformational dynamics. MDPA, examined using a standard validation dataset of ligand-protein complexes, yielded an averaged ligand-binding site prediction Matthews coefficient of 0.40, with a prediction precision of at least 50% for 71% of the cases. In particular, for 80% of the cases, the predicted ligand-binding region overlaps the natural ligand by at least 50%. The method was also compared with other state-of-the-art structure-based methods.ConclusionsMDPA is a structure-based method to detect ligand-binding regions on protein surface. Our calculations suggested that a range of spaces inside the protein pockets has subtle interactions with the protein, which can significantly impact on the overall dynamics of the protein. This work provides a valuable tool as a starting point upon which further docking and analysis methods can be used for natural ligand detection in protein functional annotation. The source code of MDPA method is freely available at: https://github.com/mingdengming/mdpa.

Phase structure and quasinormal modes of a charged AdS dilaton black hole

We investigate the phase structure of a charged AdS dilaton black hole in the extended phase space which takes the cosmological constant, i.e. the AdS-$\Lambda$ parameter as pressures. Through both thermal ensemble and quasinormal mode analysis, we find that stable phase of the black hole with non-trivial dilaton profiles always exists for both large and small couplings when the AdS-$\Lambda$ is considered dynamical degrees of freedom. This forms a somewhat contrast with previous works which does not do so. Our results provide new examples for the parallelism or equivalences between thermal ensemble methods and dynamic perturbation analysis for black hole phase structures.

Gust response analysis and wind tunnel test for a high-aspect ratio wing

A theoretical nonlinear aeroelastic response analysis for a flexible high-aspect ratio wing excited by harmonic gust load is presented along with a companion wind tunnel test. A multidisciplinary coupled numerical calculation is developed to simulate the flexible model wing undergoing gust load in the time domain via discrete nonlinear finite element structural dynamic analysis and nonplanar unsteady vortex lattice aerodynamic computation. A dynamic perturbation analysis about a nonlinear static equilibrium is also used to determine the small perturbation flutter boundary. A novel noncontact 3-D camera measurement analysis system is firstly used in the wind tunnel test to obtain the spatial large deformation and responses. The responses of the flexible wing under different static equilibrium states and frequency gust loads are discussed. The fair to good quantitative agreements between the theoretical and experimental results demonstrate that the presented analysis method is an acceptable way to predict the geometrically nonlinear gust response for flexible wings.

Text mining improves prediction of protein functional sites.

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions.

Gust Response for Flexibly Suspended High-Aspect Ratio Wings

A theoretical aeroelastic study for a flexibly suspended high-aspect ratio wing aeroelastic model excited by gust loads is presented along with a companion wind-tunnel test. A flexible support system at the wing root has been constructed to simulate a rigid body mode. Structural equations of motion based on a nonlinear beam theory are combined with the ONERA aerodynamic model. Also, a dynamic perturbation analysis about a nonlinear static equilibrium is used to determine the small perturbation flutter boundary and structural natural frequencies. The effects of the flexible support system (bi-beam system) on the wing structural dynamics, the static aeroelastic displacement at root, nonlinear flutter, and gust response to a harmonic or a frequency sweep excitation are discussed. Also the effect of gust distribution along the span on the response is described based upon computations. The fair to good quantitative agreement between theory and experiment demonstrates that the present analysis method has reasonable accuracy.

Flutter/LCO suppression for high-aspect ratio wings

AbstractAn experimental high-aspect ratio wing aeroelastic model with a device to provide a controllable slender body tip mass distribution has been constructed and the model response due to flutter and limit cycle oscillations has been measured in a wind tunnel test. A theoretical model has also been developed and calculations made to correlate with the experimental data. Structural equations of motion based on nonlinear beam theory are combined with the ONERA aerodynamic stall model (an empirical extension of Theodorsen aerodynamic theory that accounts for flow separation). A dynamic perturbation analysis about a nonlinear static equilibrium is used to determine the small perturbation flutter boundary which is compared to the experimentally determined flutter velocity and flutter frequency. Time simulation is used to compute the limit cycle oscillations response when the flutter/LCO control system is ON or OFF. Theory and experiment are in good agreement for predicting the flutter/LCO suppression that can be achieved with the control device.

Prediction of Functional Sites in 50,000 Protein Domains Using Dynamics Perturbation Analysis

Dynamics perturbation analysis (DPA) [1-3] finds regions in a protein structure where proteins are “ticklish,” i.e., where interactions cause a large change in protein dynamics. Such regions corresponded to native binding sites in a test set of hundreds of protein-ligand complexes [3]. We have further tested DPA for prediction of protein functional sites by applying an accelerated algorithm, Fast DPA [4], to over 50,000 structures of protein domains from the SCOP database [5]. We compared the predicted sites with known functional sites obtained from two sources: catalytic residues in the Catalytic Site Atlas; and putative binding sites identified by finding protein residues near small molecules in crystal structures. Combining predictions with information from sequence conservation and multiple sequence alignments reduced false positive rates. Overall, prediction of functional sites using DPA recapitulates much of the known information about functional sites in SCOP domains, and validates the use of DPA to predict functional sites in proteins. These results further suggest that functional sites in proteins tend to evolve at control points where interactions cause a large change in protein dynamics [1, 3].1. Ming D. and Wall M.E. Quantifying allosteric effects in proteins. 2005. Proteins 59:697-707.2. Ming D. and Wall M.E. Allostery in a coarse-grained model of protein dynamics. 2005. Phys Rev Lett 95:198301.3. Ming D. and Wall M.E. Interactions in native binding sites cause a large change in protein dynamics. 2006. J Mol Biol 358:213-223.4. Ming D., Cohn J.D. and Wall M.E. Fast dynamics perturbation analysis for prediction of functional sites. 2008. BMC Struct Biol 8:5.5. Murzin A.G., Brenner S.E., Hubbard T. and Chothia C. SCOP: a structural classification of proteins database for the investigation of sequences and structures. 1995. J Mol Biol 247:536-540.

Fast dynamics perturbation analysis for prediction of protein functional sites

BackgroundWe present a fast version of the dynamics perturbation analysis (DPA) algorithm to predict functional sites in protein structures. The original DPA algorithm finds regions in proteins where interactions cause a large change in the protein conformational distribution, as measured using the relative entropy Dx. Such regions are associated with functional sites.ResultsThe Fast DPA algorithm, which accelerates DPA calculations, is motivated by an empirical observation that Dx in a normal-modes model is highly correlated with an entropic term that only depends on the eigenvalues of the normal modes. The eigenvalues are accurately estimated using first-order perturbation theory, resulting in a N-fold reduction in the overall computational requirements of the algorithm, where N is the number of residues in the protein. The performance of the original and Fast DPA algorithms was compared using protein structures from a standard small-molecule docking test set. For nominal implementations of each algorithm, top-ranked Fast DPA predictions overlapped the true binding site 94% of the time, compared to 87% of the time for original DPA. In addition, per-protein recall statistics (fraction of binding-site residues that are among predicted residues) were slightly better for Fast DPA. On the other hand, per-protein precision statistics (fraction of predicted residues that are among binding-site residues) were slightly better using original DPA. Overall, the performance of Fast DPA in predicting ligand-binding-site residues was comparable to that of the original DPA algorithm.ConclusionCompared to the original DPA algorithm, the decreased run time with comparable performance makes Fast DPA well-suited for implementation on a web server and for high-throughput analysis.

Interactions in Native Binding Sites Cause a Large Change in Protein Dynamics

Cellular functions are regulated by molecules that interact with proteins and alter their activities. To enable such control, protein activity, and therefore protein conformational distributions, must be susceptible to alteration by molecular interactions at functional sites. Here we investigate whether interactions at functional sites cause a large change in the protein conformational distribution. We apply a computational method, called dynamics perturbation analysis (DPA), to identify sites at which interactions have a large allosteric potential D(x), which is the Kullback-Leibler divergence between protein conformational distributions with and without an interaction. In DPA, a protein is decorated with surface points that interact with neighboring protein atoms, and D(x) is calculated for each of the points in a coarse-grained model of protein vibrations. We use DPA to examine hundreds of protein structures from a standard small-molecule docking test set, and find that ligand-binding sites have elevated values of D(x): for 95% of proteins, the probability of randomly obtaining values as high as those in the binding site is 10(-3) or smaller. We then use DPA to develop a computational method to predict functional sites in proteins, and find that the method accurately predicts ligand-binding-site residues for proteins in the test set. The performance of this method compares favorably with that of a cleft analysis method. The results confirm that interactions at small-molecule binding sites cause a large change in the protein conformational distribution, and motivate using DPA for large-scale prediction of functional sites in proteins. They also suggest that natural selection favors proteins whose activities are capable of being regulated by molecular interactions.

Experimental and Theoretical Study of Gust Response for High-Aspect-Ratio Wing

A nonlinear response analysis of a high-aspect-ratio wing aeroelastic model excited by gust loads is presented along with a companion wind-tunnel test program. For the wind-tunnel tests, a high-aspect-ratio wing aeroelastic experimental model with a slender body at the tip has been constructed, and a rotating slotted cylinder gust generator has been used to generate a gust excitation field. A LabVIEW 5.1 measurement and analysis system is used to measure the gust response, flutter boundary, and limit-cycle oscillation behavior. Structural equations of motion based on a nonlinear beam theory are combined with the ONERA aerodynamic stall model to study the effects of geometric structural nonlinearity and steady angle of attack on nonlinear gust response of high-aspect-ratio wings. Also a dynamic perturbation analysis about a nonlinear static equilibrium is used to determine the small perturbation flutter boundary. The fair to good quantitative agreement between theory and experiment demonstrates that the present analysis method has reasonable accuracy.

Experimental and Theoretical Study on Aeroelastic Response of High-Aspect-Ratio Wings

An experimental high-aspect-ratio wing aeroelastic model with a slender body at the tip has been constructed, and the response due to flutter and limit-cycle oscillations (LCO) has been measured in a wind-tunnel test. A theoretical model has been developed and calculations made to correlate with the experimental data. Structural equations of motion based on nonlinear beam theory are combined with the ONERA aerodynamic stall model to study the effects of geometric structural nonlinearity and steady angle of attack on flutter and LCO of high-aspect-ratio wings. Static deformations in the vertical and torsional directions caused by a steady angle of attack and gravity are measured, and results from theory and experiment are compared. A dynamic perturbation analysis about a nonlinear static equilibrium is used to determine the small perturbation flutter boundary, which is compared to the experimentally determined flutter velocity and oscillation frequency. Time simulation is used to compute the LCO response. The results between the theory and experiment are in good agreement for static aeroelastic response, the onset of flutter, and dynamic LCO amplitude and frequency.