scholarly journals A novel hyperthermophilic methylglyoxal synthase: molecular dynamic analysis on the regional fluctuations

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gyo-Yeon Seo ◽  
Hoe-Suk Lee ◽  
Hyeonsoo Kim ◽  
Sukhyeong Cho ◽  
Jeong-Geol Na ◽  
...  
Keyword(s):  
Protein Structure ◽  
Hydrogen Bonds ◽  
Root Mean Square ◽  
Residual Activity ◽  
Dynamics Simulation ◽  
Mean Square ◽  
Salt Bridges ◽  
Optimum Activity ◽  
Regional Fluctuations ◽  
Methylglyoxal Synthase

AbstractTwo putative methylglyoxal synthases, which catalyze the conversion of dihydroxyacetone phosphate to methylglyoxal, from Oceanithermus profundus DSM 14,977 and Clostridium difficile 630 have been characterized for activity and thermal stability. The enzyme from O. profundus was found to be hyperthermophilic, with the optimum activity at 80 °C and the residual activity up to 59% after incubation of 15 min at 95 °C, whereas the enzyme from C. difficile was mesophilic with the optimum activity at 40 °C and the residual activity less than 50% after the incubation at 55 °C or higher temperatures for 15 min. The structural analysis of the enzymes with molecular dynamics simulation indicated that the hyperthermophilic methylglyoxal synthase has a rigid protein structure with a lower overall root-mean-square-deviation value compared with the mesophilic or thermophilic counterparts. In addition, the simulation results identified distinct regions with high fluctuations throughout those of the mesophilic or thermophilic counterparts via root-mean-square-fluctuation analysis. Specific molecular interactions focusing on the hydrogen bonds and salt bridges in the distinct regions were analyzed in terms of interatomic distances and positions of the individual residues with respect to the secondary structures of the enzyme. Key interactions including specific salt bridges and hydrogen bonds between a rigid beta-sheet core and surrounding alpha helices were found to contribute to the stabilisation of the hyperthermophilic enzyme by reducing the regional fluctuations in the protein structure. The structural information and analysis approach in this study can be further exploited for the engineering and industrial application of the enzyme.

scholarly journals Molecular Dynamics Study of Insulin Mutants

2021 ◽  
Keyword(s):  
Molecular Dynamics ◽  
Protein Structure ◽  
Secondary Structure ◽  
Root Mean Square ◽  
Human Insulin ◽  
Dynamics Simulation ◽  
Solvent Accessible Surface Area ◽  
Mean Square ◽  
Wild Type ◽  
Secondary Structure Content

Human insulin, a small protein hormone consisting of A-chain (21 residues) and B-chain (30 residues) linked by three disulfide bonds, is crucial for controlling the hyperglycemia in type I diabetes. In the present work molecular dynamics simulation (MD) with human insulin and its mutants was used to assess the influence of 10 point mutations (HisA8, ValA10, AspB10, GlnB17, AlaB17, GlnB18, AspB25, ThrB26, GluB27, AspB28), 6 double mutations (GluA13+GluB10, SerA13+GluB27, GluB1+GluB27, SerB2+AspB10, AspB9+GluB27, GluB16+GluB27) and one triple mutation (GluA15+AspA18+AspB3) in the protein sequence on the structure and dynamics of human insulin. A series of thermal unfolding MD simulations with wild type (WT) human insulin and its mutants was performed at 400 K with GROMACS software (version 5.1) using the CHARMM36m force field. The MD results have been analyzed in terms of the parameters characterizing both the global and local protein structure, such as the backbone root mean-square deviation, gyration radius, solvent accessible surface area, the root mean-square fluctuations and the secondary structure content. The MD simulation data showed that depending on time evolution of integral characteristics, the examined mutants can be tentatively divided into three groups: 1) the mutants HisA8, ValA10, AlaB17, AspB25, ThrB26, GluB27, GluA13+GluB10, GluB1+GluB27 and GluB16+GluB27, which exert stabilizing effect on the protein structure in comparison with wild type insulin; 2) the mutants GlnB17, AspB10, SerB2+AspB10 and GluA15+AspA18+AspB3 that did not significantly affect the dynamical properties of human insulin with a minimal stabilizing impact; 3) the mutants AspB28, AspB9+GluB27 and SerA13+GluB27, GlnB18, destabilizing the protein structure. Analysis of the secondary structure content provided evidence for the influence of AspB28, AspB9+GluB27 and SerA13+GluB27, GlnB18 on the insulin unfolding. Our MD results indicate that the replacement of superficial nonpolar residues in the insulin structure by hydrophilic ones gives rise to the increase in protein stability in comparison with the wild type protein.

scholarly journals Effects of the Temperature and the pH on the Main Protease of SARS-CoV-2: A Molecular Dynamics Simulation Study

2021 ◽  
Vol 12 (6) ◽  
pp. 7239-7248
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Root Mean Square ◽  
Dynamics Simulation ◽  
Effect Of Temperature ◽  
Water Molecules ◽  
Mean Square ◽  
Main Protease ◽  
Decreasing Ph ◽  
Increasing Temperature

The novel coronavirus, recognized as COVID-19, is the cause of an infection outbreak in December 2019. The effect of temperature and pH changes on the main protease of SARS-CoV-2 were investigated using all-atom molecular dynamics simulation. The obtained results from the root mean square deviation (RMSD) and root mean square fluctuations (RMSF) analyses showed that at a constant temperature of 25℃ and pH=5, the conformational change of the main protease is more significant than that of pH=6 and 7. Also, by increasing temperature from 25℃ to 55℃ at constant pH=7, a remarkable change in protein structure was observed. The radial probability of water molecules around the main protease was decreased by increasing temperature and decreasing pH. The weakening of the binding energy between the main protease and water molecules due to the increasing temperature and decreasing pH has reduced the number of hydrogen bonds between the main protease and water molecules. Finding conditions that alter the conformation of the main protease could be fundamental because this change could affect the virus’s functionality and its ability to impose illness.

How root-mean-square distance (r.m.s.d.) values depend on the resolution of protein structures that are compared

2003 ◽  
Vol 36 (1) ◽  
pp. 125-128 ◽  
Author(s):  
Oliviero Carugo
Keyword(s):  
Protein Structure ◽  
Root Mean Square ◽  
Protein Pair ◽  
Protein Structures ◽  
Structural Similarity ◽  
Protein Crystal ◽  
Mean Square ◽  
Root Mean Square Distance ◽  
Open Question ◽  
Mean Square Distance

The most popular estimator of structural similarity is the root-mean-square distance (r.m.s.d.) between equivalent atoms, computed after optimal superposition of the two structures that are compared. It is known that r.m.s.d. values do not depend only on conformational differences but also on other features, for example the dimensions of the structures that are compared. An open question is how they might depend on the accuracy of the experimentally determined protein structures. Given that the accuracy of the protein crystal structures is generally estimated through the crystallographic resolution, it is important to know the dependence of the r.m.s.d. on the crystallographic resolution of the two structures that are compared. 14458 protein structure pairs of identical sequence were compared and the resulting r.m.s.d. values were normalized to 100-residue length to avoid the bias introduced by the dependence of the r.m.s.d. values on the protein-pair dimensions. On average, smaller r.m.s.d. values are associated with protein structure pairs at better resolution and the r.m.s.d. values tend to increase if the two proteins that are compared have been refined at different resolutions. For crystallographic resolutions ranging between 1.6 and 2.9 Å, both relationships appear to be linear: r.m.s.d. = −0.73 + 0.48 resolution and delta_r.m.s.d. = 0.20 + 0.30 delta_resolution (`delta' indicating difference). Although the linearity of these relationships is not expected to hold outside the 1.6–2.9 Å resolution range, they are useful in making the r.m.s.d. values more reliable.

scholarly journals Discovery of Potential Chemical Probe as Inhibitors of CXCL12 Using Ligand-Based Virtual Screening and Molecular Dynamic Simulation

Molecules ◽  
2020 ◽  
Vol 25 (20) ◽  
pp. 4829
Author(s):  
Sajjad Haider ◽  
Assem Barakat ◽  
Zaheer Ul-Haq
Keyword(s):  
Virtual Screening ◽  
Molecular Dynamic ◽  
Root Mean Square ◽  
Cancer Metastasis ◽  
Pharmacophore Model ◽  
Binding Mode ◽  
Dynamics Simulation ◽  
Radius Of Gyration ◽  
Mean Square ◽  
Dynamic Simulations

CXCL12 are small pro-inflammatory chemo-attractant cytokines that bind to a specific receptor CXCR4 with a role in angiogenesis, tumor progression, metastasis, and cell survival. Globally, cancer metastasis is a major cause of morbidity and mortality. In this study, we targeted CXCL12 rather than the chemokine receptor (CXCR4) because most of the drugs failed in clinical trials due to unmanageable toxicities. Until now, no FDA approved medication has been available against CXCL12. Therefore, we aimed to find new inhibitors for CXCL12 through virtual screening followed by molecular dynamics simulation. For virtual screening, active compounds against CXCL12 were taken as potent inhibitors and utilized in the generation of a pharmacophore model, followed by validation against different datasets. Ligand based virtual screening was performed on the ChEMBL and in-house databases, which resulted in successive elimination through the steps of pharmacophore-based and score-based screenings, and finally, sixteen compounds of various interactions with significant crucial amino acid residues were selected as virtual hits. Furthermore, the binding mode of these compounds were refined through molecular dynamic simulations. Moreover, the stability of protein complexes, Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), and radius of gyration were analyzed, which led to the identification of three potent inhibitors of CXCL12 that may be pursued in the drug discovery process against cancer metastasis.

scholarly journals Molecular Dynamics Simulation of Barnase: Contribution of Noncovalent Intramolecular Interaction to Thermostability

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Zhiguo Chen ◽  
Yi Fu ◽  
Wenbo Xu ◽  
Ming Li
Keyword(s):  
Molecular Dynamics ◽  
Thermal Stability ◽  
Molecular Dynamics Simulation ◽  
Root Mean Square ◽  
Clinical Medicine ◽  
Intramolecular Interaction ◽  
Salt Bridge ◽  
Dynamics Simulation ◽  
Mean Square ◽  
Thermal Stability Of

Bacillus amyloliquefaciensribonuclease Barnase (RNase Ba) is a 12 kD (kilodalton) small extracellular ribonuclease. It has broad application prospects in agriculture, clinical medicine, pharmaceutical, and so forth. In this work, the thermal stability of Barnase has been studied using molecular dynamics simulation at different temperatures. The present study focuses on the contribution of noncovalent intramolecular interaction to protein stability and how they affect the thermal stability of the enzyme. Profiles of root mean square deviation and root mean square fluctuation identify thermostable and thermosensitive regions of Barnase. Analyses of trajectories in terms of secondary structure content, intramolecular hydrogen bonds and salt bridge interactions indicate distinct differences in different temperature simulations. In the simulations, Four three-member salt bridge networks (Asp8-Arg110-Asp12, Arg83-Asp75-Arg87, Lys66-Asp93-Arg69, and Asp54-Lys27-Glu73) have been identified as critical salt bridges for thermostability which are maintained stably at higher temperature enhancing stability of three hydrophobic cores. The study may help enlighten our knowledge of protein structural properties, noncovalent interactions which can stabilize secondary peptide structures or promote folding, and also help understand their actions better. Such an understanding is required for designing efficient enzymes with characteristics for particular applications at desired working temperatures.

scholarly journals The Construction of Chimeric T-Cell Receptor with Spacer Base of Modeling Study of VHH and MUC1 Interaction

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
Nazanin Pirooznia ◽  
Sadegh Hasannia ◽  
Majid Taghdir ◽  
Fatemeh Rahbarizadeh ◽  
Morteza Eskandani
Keyword(s):  
Root Mean Square ◽  
Conformational Changes ◽  
Cell Receptor ◽  
Dynamics Simulation ◽  
Specific Response ◽  
Conformational Structure ◽  
Mean Square ◽  
Chimeric Receptors ◽  
Cell Immunotherapy ◽  
And Function

Adaptive cell immunotherapy with the use of chimeric receptors leads to the best and most specific response against tumors. Chimeric receptors consist of a signaling fragment, extracellular spacer, costimulating domain, and an antibody. Antibodies cause immunogenicity; therefore, VHH is a good replacement for ScFv in chimeric receptors. Since peptide sequences have an influence on chimeric receptors, the effect of peptide domains on each other's conformation were investigated. CD3Zeta, CD28, VHH and CD8α, and FcgIIα are used as signaling moieties, costimulating domain, antibody, and spacers, respectively. To investigate the influence of the ligation of spacers on the conformational structure of VHH, models of VHH were constructed. Molecular dynamics simulation was run to study the influence of the presence of spacers on the conformational changes in the binding sites of VHH. Root mean square deviation and root mean square fluctuation of critical segments in the binding site showed no noticeable differences with those in the native VHH. Results from molecular docking revealed that the presence of spacer FcgIIα causes an increasing effect on VHH with MUC1 interaction. Each of the constructs was transformed into the Jurkat E6.1. Expression analysis and evaluation of their functions were examined. The results showed good expression and function.

scholarly journals Screening of Potent Phytochemical Inhibitors Against SARS-CoV-2 Main Protease: An Integrative Computational Approach

2021 ◽  
Vol 1 ◽  
Author(s):  
Shafi Mahmud ◽  
Md. Robiul Hasan ◽  
Suvro Biswas ◽  
Gobindo Kumar Paul ◽  
Shamima Afrose ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Global Economy ◽  
Transmission Rate ◽  
Accessible Surface Area ◽  
Dynamics Simulation ◽  
Solvent Accessible Surface Area ◽  
Radius Of Gyration ◽  
Mean Square ◽  
Protease Inhibition ◽  
Main Protease

Coronavirus disease 2019 (COVID-19) is a potentially lethal and devastating disease that has quickly become a public health threat worldwide. Due to its high transmission rate, many countries were forced to implement lockdown protocols, wreaking havoc on the global economy and the medical crisis. The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative virus for COVID-19, represent an effective target for the development of a new drug/vaccine because it is well-conserved and plays a vital role in viral replication. Mpro inhibition can stop the replication, transcription as well as recombination of SARS-CoV-2 after the infection and thus can halt the formation of virus particles, making Mpro a viable therapeutic target. Here, we constructed a phytochemical dataset based on a rigorous literature review and explored the probability that various phytochemicals will bind with the main protease using a molecular docking approach. The top three hit compounds, medicagol, faradiol, and flavanthrin, had binding scores of −8.3, −8.6, and −8.8 kcal/mol, respectively, in the docking analysis. These three compounds bind to the active groove, consisting of His41, Cys45, Met165, Met49, Gln189, Thr24, and Thr190, resulting in main protease inhibition. Moreover, the multiple descriptors from the molecular dynamics simulation, including the root-mean-square deviation, root-mean-square fluctuation, solvent-accessible surface area, radius of gyration, and hydrogen bond analysis, confirmed the stable nature of the docked complexes. In addition, absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis confirmed a lack of toxicity or carcinogenicity for the screened compounds. Our computational analysis may contribute toward the design of an effective drug against the main protease of SARS-CoV-2.

scholarly journals Use of multiple picosecond high-mass molecular dynamics simulations to predict crystallographic B-factors of folded globular proteins

2016 ◽  
Author(s):  
Yuan-Ping Pang
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Molecular Dynamics Simulations ◽  
Root Mean Square ◽  
A Priori ◽  
Model Systems ◽  
Dynamics Simulation ◽  
High Mass ◽  
Mean Square ◽  
Dynamics Simulations

ABSTRACTPredicting crystallographic B-factors of a protein from a conventional molecular dynamics simulation is challenging in part because the B-factors calculated through sampling the atomic positional fluctuations in a picosecond molecular dynamics simulation are unreliable and the sampling of a longer simulation yields overly large root mean square deviations between calculated and experimental B-factors. This article reports improved B-factor prediction achieved by sampling the atomic positional fluctuations in multiple picosecond molecular dynamics simulations that use uniformly increased atomic masses by 100-fold to increase time resolution. Using the third immunoglobulin-binding domain of protein G, bovine pancreatic trypsin inhibitor, ubiquitin, and lysozyme as model systems, the B-factor root mean square deviations (mean ± standard error) of these proteins were 3.1 ± 0.2–9 ± 1 Å2for Cα and 7.3 ± 0.9–9.6 ± 0.2 Å2for Cγ, when the sampling was done, for each of these proteins, over 20 distinct, independent, and 50-picosecond high-mass molecular dynamics simulations using AMBER forcefield FF12MC or FF14SB. These results suggest that sampling the atomic positional fluctuations in multiple picosecond high-mass molecular dynamics simulations may be conducive toa prioriprediction of crystallographic B-factors of a folded globular protein.

scholarly journals Luteolin and abyssinone II as potential inhibitors of SARS-CoV-2: an in silico molecular modeling approach in battling the COVID-19 outbreak

2021 ◽  
Vol 45 (1) ◽  
Author(s):  
Mohammad Mahfuz Ali Khan Shawan ◽  
Sajal Kumar Halder ◽  
Md. Ashraful Hasan
Keyword(s):  
Molecular Dynamics ◽  
Root Mean Square ◽  
In Silico ◽  
Binding Free Energy ◽  
Biologically Active ◽  
Dynamics Simulation ◽  
Mean Square ◽  
Efficient Treatment ◽  
Target Proteins

Abstract Background At present, the entire world is in a war against COVID-19 pandemic which has gradually led us toward a more compromised “new normal” life. SARS-CoV-2, the pathogenic microorganism liable for the recent COVID-19 outbreak, is extremely contagious in nature resulting in an unusual number of infections and death globally. The lack of clinically proven therapeutic intervention for COVID-19 has dragged the world’s healthcare system into the biggest challenge. Therefore, development of an efficient treatment scheme is now in great demand. Screening of different biologically active plant-based natural compounds could be a useful strategy for combating this pandemic. In the present research, a collection of 43 flavonoids of 7 different classes with previously recorded antiviral activity was evaluated via computational and bioinformatics tools for their impeding capacity against SARS-CoV-2. In silico drug likeness, pharmacophore and Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) profile analysis of the finest ligands were carried out using DataWarrior, DruLiTo and admetSAR programs, respectively. Molecular docking was executed by AutoDock Vina, while molecular dynamics simulation of the target protein–ligand bound complexes was done using nanoscalable molecular dynamics and visual molecular dynamics software package. Finally, the molecular target analysis of the selected ligands within Homo sapiens was conducted with SwissTargetPredcition web server. Results Out of the forty-three flavonoids, luteolin and abyssinone II were found to develop successful docked complex within the binding sites of target proteins in terms of lowest binding free energy and inhibition constant. The root mean square deviation and root mean square fluctuation values of the docked complex displayed stable interaction and efficient binding between the ligands and target proteins. Both of the flavonoids were found to be safe for human use and possessed good drug likeness properties and target accuracy. Conclusions Conclusively, the current study proposes that luteolin and abyssinone II might act as potential therapeutic candidates for SARS-CoV-2 infection. In vivo and in vitro experiments, however, should be taken under consideration to determine the efficiency and to demonstrate the mechanism of action.

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