scholarly journals Computational Analysis of Dynamical Fluctuations of Oncoprotein E7 (HPV) for the Hot Spot Residue Identification Using Elastic Network Model

2018 ◽  
Author(s):  
R. M. Malik ◽  
F. Nazir ◽  
S. Fazal ◽  
A. Bhatti ◽  
M. Ullah ◽  
...  
Keyword(s):  
Human Body ◽  
Protein Interactions ◽  
Computational Study ◽  
Hot Spot ◽  
Network Models ◽  
Biologically Active ◽  
Host Protein ◽  
Elastic Network Model ◽  
Elastic Network ◽  
Topological Features

AbstractVirus proteins after invading human body alter host protein-protein interaction networks, resulting in the creation of new interactions, along with destroying or modifying other interactions or proteins. Topological features of new or modified networks compromise the host system causing increased production of viral particles. The molecular basis for this alteration of proteins interactivity is short linear peptide motifs similar in both virus and humans. These motifs are identified by modular domains, which are the subunits of a protein, in the human body, resulting in stabilization or moderation of these protein interactions Protein molecules can be modeled by elastic network models showing the fluctuations of residues when they are biologically active. We focused our computational study on the binding and competing interactions of the E7 protein of HPV with Rb protein. Our study was based on analysis of dynamic fluctuations of E7 in host cell and correlation analysis of specific residue found in motif of LxCxE, that is the key region in stabilizing interaction between E7 and Rb. Hot spot residue of E7 were also identified which could provide platform for drug prediction in future. Nevertheless, our study validates the role of linear binding motifs LxCxE of E7 of HPV in interacting with Rb as an important event in propagation of HPV in human cells and transformation of infection into cervical cancer.

scholarly journals Estimating the Directional Flexibility of Proteins from Equilibrium Thermal Fluctuations

2020 ◽  
Author(s):  
SANJOY PAUL ◽  
Ravindra Venkatramani
Keyword(s):  
Experimental Data ◽  
Single Molecule ◽  
Protein Interactions ◽  
Thermal Fluctuations ◽  
Globular Proteins ◽  
Mechanical Anisotropy ◽  
Elastic Network Model ◽  
Protein Protein Interactions ◽  
Elastic Network ◽  
Spring Constants

<b><i>In this manuscript, we demonstrate the abilities of atomistic MD trajectories to estimate the directional spring constants of proteins. The MD-derived spring constants are cross-correlated with single-molecule force spectropcopy (SMFS) experimental data for 5 different globular proteins. We employ the framework to predict the mechanical anisotropy of ubiquitin and associated changes in the anisotropy with functionally relevant protein-protein interactions. Finally, we use the MD-based framework to benchmark and improve computationally inexpensive and scalable elastic network model (ENM) based methods to estimate protein directional flexibility.</i></b>

Computational analysis of domains vulnerable To HPV-16 E6 Oncoprotein and corresponding hot spot residues.

2020 ◽  
Vol 27 ◽  
Author(s):  
Rabbiah Manzoor Malik ◽  
Sahar Fazal ◽  
Mohammad Amjad Kamal
Keyword(s):  
Cervical Cancer ◽  
Hot Spot ◽  
Network Models ◽  
Host Protein ◽  
Hpv 16 ◽  
Protein Protein Interaction ◽  
Linear Peptide ◽  
Peptide Motifs ◽  
E6 Oncoprotein ◽  
Human Proteins

Background: Human Papilloma Virus (HPV) is the primary cause of cancers in cervix, head and neck regions. Oncoprotein E6 of HPV-16, after infecting human body, alters host protein-protein interaction networks. E6 interacts with several proteins, causing the infection to progress into cervical cancer. The molecular basis for these interactions is the presence of short linear peptide motifs on E6 identical to those on human proteins. Methods: Motifs of LXXLL and E/DLLL/V-G after identification on E6, were analyzed for their dynamic fluctuations by use of elastic network models. Correlation analysis of amino acid residues of E6 was also performed in specific regions of motifs. Results: Arginine, Leucine, Glutamine, Threonine and Glutamic acid have been identified as hot spot residues of E6 which can subsequently provide a platform for drug designing and understanding of pathogenesis of cervical cancer. These amino acids play a significant role in stabilizing interactions with host proteins, ultimately causing infections and cancers. Conclusion: Our study validates the role of linear binding motifs of E6 of HPV in interacting with these proteins as an important event in the propagation of HPV in human cells and its transformation into cervical cancer. The study further predicts the domains of protein kinase and armadillo as part of the regions involved in the interaction of E6AP, Paxillin and TNF R1, with viral E6.

scholarly journals Computational Analysis of Dynamical Fluctuations of Oncoprotein E7 (HPV 16) for the Hot Spot Residue Identification Using Elastic Network Model

2020 ◽  
Vol 17 (11) ◽  
pp. 1393-1400
Author(s):  
Rabbiah Malik ◽  
Sahar Fazal ◽  
Mohammad Amjad Kamal
Keyword(s):  
Cervical Cancer ◽  
Computational Analysis ◽  
Hot Spot ◽  
Human Cells ◽  
Host Protein ◽  
Elastic Network Model ◽  
Hpv 16 ◽  
Binding Motifs ◽  
Rb Protein ◽  
Human Host

Aims: To find out Potential Drug targets against HPV E7. Background: Oncoprotein E7 of Human Papilloma Virus (HPV-16), after invading human body alter host protein-protein interaction networks caused by the fluctuations of amino acid residues present in E7. E7 interacts with Rb protein of human host with variable residual fluctuations, leading towards the progression of cervical cancer. Objective: Our study was focused our computational analysis of the binding and competing interactions of the E7 protein of HPV with Rb protein. Methods: Our study is based on analysis of dynamic fluctuations of E7 in host cell and correlation analysis of specific residue found in motif of LxCxE, that is the key region in stabilizing interaction between E7 and Rb. Results and Discussion: Cysteine, Leucine and Glutamic acid have been identified as hot spot residues of E7 which can provide platform for drug designing and understanding of pathogenesis of cervical cancer, in future. Our study shows validation of the vitality of linear binding motifs LxCxE of E7 of HPV in interacting with Rb as an important event in propagation of HPV in human cells and transformation of infection into cervical cancer. Conclusion: Our study shows validation of the vitality of linear binding motifs LxCxE of E7 of HPV in interacting with Rb as an important event in propagation of HPV in human cells and transformation of infection into cervical cancer. Other: E7 interacts with Rb protein of human host with variable residual fluctuations, leading towards the progression of cervical cancer.

scholarly journals Estimating the Directional Flexibility of Proteins from Equilibrium Thermal Fluctuations

2020 ◽  
Author(s):  
SANJOY PAUL ◽  
Ravindra Venkatramani
Keyword(s):  
Experimental Data ◽  
Single Molecule ◽  
Protein Interactions ◽  
Thermal Fluctuations ◽  
Globular Proteins ◽  
Mechanical Anisotropy ◽  
Elastic Network Model ◽  
Protein Protein Interactions ◽  
Elastic Network ◽  
Spring Constants

<b><i>In this manuscript, we demonstrate the abilities of atomistic MD trajectories to estimate the directional spring constants of proteins. The MD-derived spring constants are cross-correlated with single-molecule force spectropcopy (SMFS) experimental data for 5 different globular proteins. We employ the framework to predict the mechanical anisotropy of ubiquitin and associated changes in the anisotropy with functionally relevant protein-protein interactions. Finally, we use the MD-based framework to benchmark and improve computationally inexpensive and scalable elastic network model (ENM) based methods to estimate protein directional flexibility.</i></b>

Forces mediating protein–protein interactions: a computational study of p53 “approaching” MDM2

2009 ◽  
Vol 125 (3-6) ◽  
pp. 621-635 ◽  
Author(s):  
Shubhra Ghosh Dastidar ◽  
Arumugam Madhumalar ◽  
Gloria Fuentes ◽  
David P. Lane ◽  
Chandra S. Verma
Keyword(s):  
Protein Interactions ◽  
Computational Study ◽  
Protein Protein Interactions

scholarly journals New Mechanistic Insights on Carbon Nanotubes’ Nanotoxicity Using Isolated Submitochondrial Particles, Molecular Docking, and Nano-QSTR Approaches

Biology ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 171
Author(s):  
Michael González-Durruthy ◽  
Riccardo Concu ◽  
Juan M. Ruso ◽  
M. Natália D. S. Cordeiro
Keyword(s):  
Carbon Nanotubes ◽  
Network Models ◽  
Single Walled Carbon Nanotubes ◽  
Docking Studies ◽  
Fractal Surface ◽  
Submitochondrial Particles ◽  
Elastic Network ◽  
Elastic Network Models ◽  
Walled Carbon Nanotubes

Single-walled carbon nanotubes can induce mitochondrial F0F1-ATPase nanotoxicity through inhibition. To completely characterize the mechanistic effect triggering the toxicity, we have developed a new approach based on the combination of experimental and computational study, since the use of only one or few techniques may not fully describe the phenomena. To this end, the in vitro inhibition responses in submitochondrial particles (SMP) was combined with docking, elastic network models, fractal surface analysis, and Nano-QSTR models. In vitro studies suggest that inhibition responses in SMP of F0F1-ATPase enzyme were strongly dependent on the concentration assay (from 3 to 5 µg/mL) for both pristine and COOH single-walled carbon nanotubes types (SWCNT). Besides, both SWCNTs show an interaction inhibition pattern mimicking the oligomycin A (the specific mitochondria F0F1-ATPase inhibitor blocking the c-ring F0 subunit). Performed docking studies denote the best crystallography binding pose obtained for the docking complexes based on the free energy of binding (FEB) fit well with the in vitro evidence from the thermodynamics point of view, following an affinity order such as: FEB (oligomycin A/F0-ATPase complex) = −9.8 kcal/mol > FEB (SWCNT-COOH/F0-ATPase complex) = −6.8 kcal/mol ~ FEB (SWCNT-pristine complex) = −5.9 kcal/mol, with predominance of van der Waals hydrophobic nano-interactions with key F0-ATPase binding site residues (Phe 55 and Phe 64). Elastic network models and fractal surface analysis were performed to study conformational perturbations induced by SWCNT. Our results suggest that interaction may be triggering abnormal allosteric responses and signals propagation in the inter-residue network, which could affect the substrate recognition ligand geometrical specificity of the F0F1-ATPase enzyme in order (SWCNT-pristine > SWCNT-COOH). In addition, Nano-QSTR models have been developed to predict toxicity induced by both SWCNTs, using results of in vitro and docking studies. Results show that this method may be used for the fast prediction of the nanotoxicity induced by SWCNT, avoiding time- and money-consuming techniques. Overall, the obtained results may open new avenues toward to the better understanding and prediction of new nanotoxicity mechanisms, rational drug design-based nanotechnology, and potential biomedical application in precision nanomedicine.

scholarly journals Edge-based formulation of elastic network models

2019 ◽  
Vol 1 (3) ◽  
Author(s):  
Maxwell Hodges ◽  
Sophia N. Yaliraki ◽  
Mauricio Barahona
Keyword(s):  
Network Models ◽  
Elastic Network ◽  
Elastic Network Models ◽  
Edge Based

scholarly journals Native Structure-Based Peptides as Potential Protein–Protein Interaction Inhibitors of SARS-CoV-2 Spike Protein and Human ACE2 Receptor

Molecules ◽  
2021 ◽  
Vol 26 (8) ◽  
pp. 2157
Author(s):  
Norbert Odolczyk ◽  
Ewa Marzec ◽  
Maria Winiewska-Szajewska ◽  
Jarosław Poznański ◽  
Piotr Zielenkiewicz
Keyword(s):  
Drug Development ◽  
Protein Interactions ◽  
Rna Virus ◽  
Antiviral Drug ◽  
Host Protein ◽  
Host Cells ◽  
Cell Surface Receptor ◽  
Short Peptides ◽  
Virus Protein ◽  
Positive Strand Rna

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is a positive-strand RNA virus that causes severe respiratory syndrome in humans, which is now referred to as coronavirus disease 2019 (COVID-19). Since December 2019, the new pathogen has rapidly spread globally, with over 65 million cases reported to the beginning of December 2020, including over 1.5 million deaths. Unfortunately, currently, there is no specific and effective treatment for COVID-19. As SARS-CoV-2 relies on its spike proteins (S) to bind to a host cell-surface receptor angiotensin-converting enzyme-2(ACE2), and this interaction is proved to be responsible for entering a virus into host cells, it makes an ideal target for antiviral drug development. In this work, we design three very short peptides based on the ACE2 sequence/structure fragments, which may effectively bind to the receptor-binding domain (RBD) of S protein and may, in turn, disrupt the important virus-host protein–protein interactions, blocking early steps of SARS-CoV-2 infection. Two of our peptides bind to virus protein with affinity in nanomolar range, and as very short peptides have great potential for drug development.

Sign in / Sign up

Export Citation Format

Share Document