scholarly journals Virtual Quantification of Protein Stability Using Applied Kinetic and Thermodynamic Parameters

IIOAB Letters ◽  
2011 ◽  
Vol 1 (1) ◽  
Author(s):  
S. Prasanth Kumar ◽  
Muthusamy Meenatchi
Keyword(s):  
Amino Acid ◽  
Protein Stability ◽  
Energy Requirement ◽  
Single Point ◽  
Point Mutations ◽  
Accessible Surface Area ◽  
Protein Stabilization ◽  
Solvent Accessible Surface Area ◽  
Thermodynamic Quantities ◽  
Solvation Energies

Protein stability, the most important aspect of molecular dynamics and simulations, requires sophisticated instrumentations of molecular biology to analyze its kinetic and thermodynamic background. Sequence- and structure-based programs on protein stability exist which relies only on single point mutations and sequence optimality. The energy distribution conferred by each hydrophobic amino acid in the protein essentially paves way for understanding its stability. To the best of our knowledge, Protein Stability is a first program of its kind, developed to explore the energy requirement of each amino acid in the protein sequence derived from various applied kinetic and thermodynamic quantities. The algorithm is strongly dependent both on kinetic quantities such as atomic solvation energies and solvent accessible surface area and thermodynamic quantities viz. enthalpy, entropy, heat capacity, etc. The hydrophobicity pattern of protein was considered as the important component of protein stabilization.

scholarly journals Intrinsic resistance to terbinafine among human and animal isolates of Trichophyton mentagrophytes related to amino acid substitution in the squalene epoxidase

Infection ◽  
2020 ◽  
Vol 48 (6) ◽  
pp. 889-897 ◽  
Author(s):  
Dominik Łagowski ◽  
Sebastian Gnat ◽  
Aneta Nowakiewicz ◽  
Marcelina Osińska ◽  
Mariusz Dyląg
Keyword(s):  
Amino Acid ◽  
Fungal Infections ◽  
Single Point ◽  
Antifungal Susceptibility ◽  
Point Mutations ◽  
Trichophyton Mentagrophytes ◽  
Single Amino Acid ◽  
Squalene Epoxidase ◽  
Intrinsic Resistance ◽  
Resistant Strains

Abstract Background Dermatomycoses are the most common fungal infections in the world affecting a significant part of the human and animal population. The majority of zoophilic infections in humans are caused by Trichophyton mentagrophytes. Currently, the first-line drug for both oral and topical therapy is terbinafine. However, an increasing number of cases that are difficult to be cured with this drug have been noted in Europe and Asia. Resistance to terbinafine and other allylamines is very rare and usually correlated with point mutations in the squalene epoxidase gene resulting in single amino acid substitutions in the enzyme, which is crucial in the ergosterol synthesis pathway. Purpose Here, we report terbinafine-resistant T. mentagrophytes isolates among which one was an etiological factor of tinea capitis in a man and three were obtained from asymptomatic foxes in Poland. Methods We used the CLSI protocol to determine antifungal susceptibility profiles of naftifine, amphotericin B, griseofulvin, ketoconazole, miconazole, itraconazole, voriconazole, and ciclopirox. Moreover, the squalene epoxidase gene of the terbinafine-resistant strains was sequenced and analysed. Results In the genomes of all four resistant strains exhibiting elevated MICs to terbinafine (16 to 32 µg/ml), single-point mutations leading to Leu393Phe substitution in the squalene epoxidase enzyme were revealed. Among the other tested substances, a MIC50 value of 1 µg/ml was shown only for griseofulvin. Conclusion Finally, our study revealed that the terbinafine resistance phenomenon might not be acquired by exposure to the drug but can be intrinsic. This is evidenced by the description of the terbinafine-resistant strains isolated from the asymptomatic animals.

Human Coagulation Factor Va Interaction with Phospholipid Vesicles: A Molecular Dynamics Study.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 1699-1699
Author(s):  
Tivadar Orban ◽  
Michael Kalafatis
Keyword(s):  
Amino Acid ◽  
Lipid Bilayer ◽  
Factor Xa ◽  
Accessible Surface Area ◽  
Fatty Acyl ◽  
Phospholipid Bilayer ◽  
Solvent Accessible Surface Area ◽  
Factor Va ◽  
Accessible Surface ◽  
Simulation Time

Abstract The prothrombinase complex, the enzyme responsible for the timely conversion of prothrombin to thrombin, is composed of factor Xa (the enzyme), factor Va (the cofactor) assembled on the activated cell surface in the presence of divalent metal ions. In our quest to propose a model of the prothrombinase complex we first created a homology model in solution of factor Va (pdb code 1y61). Next we created a mixed phospholipid bilayer model composed of 1-palmitoyl, 2-oleoyl-sn-glycero-3-phosphatidylcholine (POPC) and 1-palmitoyl, 2-oleoyl-sn-glycero-3-phosphatidylserine (POPS) in a 4:1 ratio. The lipid bilayer was equilibrated for 10 ns. The data showed that the average area per head group and the deuterium order parameters of the fatty acyl chains compare well with the previously reported nuclear magnetic resonance data. We next created a system composed of factor Va, water molecules, phospholipid bilayer composed of POPS/POPC and sodium ions. Factor Va was placed at the near interface of the equilibrated POPC/POPS phospholipid bilayer but making sure that the two entities were not interacting. Molecular dynamics simulation was then performed on the entire system. Distance analysis performed between the center of masses of the factor Va molecule and the lipid bilayer revealed that during the 4.5 ns simulation time, the factor Va molecule gets inserted into the interface of the hydrophobic core of the bilayer. The distance between the two centers of masses decreased during the 4.5 ns simulation time from 92 Å to 78 Å. At the end of the 4.5 ns simulation time the indole moieties of Trp2063 and Trp2064 were found to be in the vicinity of the ester and the fatty acyl chain moieties of the phospholipids. Factor Va was found to participate in hydrogen bonds formation with both the carboxylate and the phosphate groups of POPS. Following 4.5 ns simulation time the farthest amino acid residue away from the membrane is located at ~ 100 Å from the lipid bilayer plane. This result is in agreement with previous fluorescence energy transfer studies that concluded that a domain of membrane-bound factor Va is positioned at a minimum distance of 90 Å above the membrane surface. It is noteworthy that the amino acid sequence comprising Pro1663 to Val1672 of factor Va had a root mean square displacemenent (RMSD) 4.5 times higher as the average RMSD of the other residues, i.e., 9 Å. This sequence is highly hydrophobic in nature and it was previously shown to contain a membrane binding site on factor Va. However, the present placement of factor Va on the lipid bilayer does not allow the insertion of this hydrophobic patch into the lipid bilayer. We next tested the hypothesis whether the region encompassing amino acid residues Glu323 to Val331 gets exposed to solvent following the interaction of factor Va with the phospholipids. This region was shown to contain a binding site of factor Xa on factor Va. Solvent accessible surface area calculated for each amino acid residue of the Glu323 to Val331 sequence revealed that during the 4.5 ns simulation time the solvent accessible surface area does not increase. In conclusion, our work proposes for the first time a model of factor Va bound to a mixed POPC/POPS lipid bilayer and provides the necessary framework that accounts for the presence of phospholipids as a major regulatory component of a protein complex. This model can be extrapolated to the study of the dynamics of other membrane associated complexes involved in blood coagulation.

scholarly journals A three-state prediction of single point mutations on protein stability changes

2008 ◽  
Vol 9 (Suppl 2) ◽  
pp. S6 ◽  
Author(s):  
Emidio Capriotti ◽  
Piero Fariselli ◽  
Ivan Rossi ◽  
Rita Casadio
Keyword(s):  
Protein Stability ◽  
Single Point ◽  
Point Mutations ◽  
State Prediction ◽  
Single Point Mutations

scholarly journals Robust Prediction of Single and Multiple Point Protein Mutations Stability Changes

Biomolecules ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 67 ◽  
Author(s):  
Óscar Álvarez-Machancoses ◽  
Enrique J. De Andrés-Galiana ◽  
Juan Luis Fernández-Martínez ◽  
Andrzej Kloczkowski
Keyword(s):  
Neural Network ◽  
Amino Acid ◽  
Network Model ◽  
Neural Network Model ◽  
Pearson Correlation ◽  
Single Point ◽  
Point Mutations ◽  
Cumulative Distribution ◽  
Multiple Point ◽  
Protein Mutations

Accurate prediction of protein stability changes resulting from amino acid substitutions is of utmost importance in medicine to better understand which mutations are deleterious, leading to diseases, and which are neutral. Since conducting wet lab experiments to get a better understanding of protein mutations is costly and time consuming, and because of huge number of possible mutations the need of computational methods that could accurately predict effects of amino acid mutations is of greatest importance. In this research, we present a robust methodology to predict the energy changes of a proteins upon mutations. The proposed prediction scheme is based on two step algorithm that is a Holdout Random Sampler followed by a neural network model for regression. The Holdout Random Sampler is utilized to analysis the energy change, the corresponding uncertainty, and to obtain a set of admissible energy changes, expressed as a cumulative distribution function. These values are further utilized to train a simple neural network model that can predict the energy changes. Results were blindly tested (validated) against experimental energy changes, giving Pearson correlation coefficients of 0.66 for Single Point Mutations and 0.77 for Multiple Point Mutations. These results confirm the successfulness of our method, since it outperforms majority of previous studies in this field.

USING RIGIDITY ANALYSIS TO PROBE MUTATION-INDUCED STRUCTURAL CHANGES IN PROTEINS

2012 ◽  
Vol 10 (03) ◽  
pp. 1242010 ◽  
Author(s):  
FILIP JAGODZINSKI ◽  
JEANNE HARDY ◽  
ILEANA STREINU
Keyword(s):  
Amino Acid ◽  
Amino Acid Substitution ◽  
Structural Changes ◽  
Protein Structures ◽  
Data Bank ◽  
Accessible Surface Area ◽  
Solvent Accessible Surface Area ◽  
Single Amino Acid ◽  
Fast Evaluation

Predicting the effect of a single amino acid substitution on the stability of a protein structure is a fundamental task in macromolecular modeling. It has relevance to drug design and understanding of disease-causing protein variants. We present KINARI-Mutagen, a web server for performing in silico mutation experiments on protein structures from the Protein Data Bank. Our rigidity-theoretical approach permits fast evaluation of the effects of mutations that may not be easy to perform in vitro, because it is not always possible to express a protein with a specific amino acid substitution. We use KINARI-Mutagen to identify critical residues, and we show that our predictions correlate with destabilizing mutations to glycine. In two in-depth case studies we show that the mutated residues identified by KINARI-Mutagen as critical correlate with experimental data, and would not have been identified by other methods such as Solvent Accessible Surface Area measurements or residue ranking by contributions to stabilizing interactions. We also generate 48 mutants for 14 proteins, and compare our rigidity-based results against experimental mutation stability data. KINARI-Mutagen is available at http://kinari.cs.umass.edu .

scholarly journals Molecular dynamics approach to the I431V mutational impact on thyroid hormone receptor-beta

BIBECHANA ◽  
2018 ◽  
Vol 16 ◽  
pp. 79-91
Author(s):  
Tika Ram Lamichhane ◽  
Sharma Paudel ◽  
Binod Kumar Yadav ◽  
Hari Prasad Lamichhane
Keyword(s):  
Thyroid Hormone ◽  
Hormone Receptor ◽  
Thyroid Hormone Receptor ◽  
Point Mutations ◽  
Binding Pocket ◽  
Accessible Surface Area ◽  
Thyroid Stimulating Hormone ◽  
Solvent Accessible Surface Area ◽  
Free Triiodothyronine ◽  
Receptor Beta

The point mutations like I431V on thyroid hormone receptor-beta (THR-β) gene cause resistance to thyroid hormones (RTH) with the clinical diagnosis of elevated free triiodothyronine (T3) and free thyroxin (T4) but not suppressed thyroid stimulating hormone (TSH) on the blood serum. Some ultrasonographic (USG) reports of the patients with RTH show thyroid gland disorder with goiter or nodule(s) or cyst(s) and some USG reports even with RTH are normal. I431V-mutant causes more steric hindrance while binding T3 into THR-β than the native wild type THRT3. The residue on the 431-codon is dynamic in nature showing its flexibility over the course of entry and release of T3-hormone into/from the ligand binding pocket. The more increased solvent accessible surface area of I431V-mutant than that of native I431-residue makes the partial unfolding of the globular THR-β protein. The smaller height of radial distribution function between I431-mutant and T3 shows the decrease in probability of finding the atomic particles nearby T3-hormone in THRT3-MT than in THRT3-WT. The electrostatic interaction energy between native I431 and T3 is negative, but it is positive between I431V and T3. Moreover, the internal energy of I431V-mutant has been found smaller than that of native I431-residue in THRT3 systems.BIBECHANA 16 (2019) 79-91

Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins

2015 ◽  
Vol 32 (6) ◽  
pp. 843-849 ◽  
Author(s):  
Rhys Heffernan ◽  
Abdollah Dehzangi ◽  
James Lyons ◽  
Kuldip Paliwal ◽  
Alok Sharma ◽  
...  
Keyword(s):  
Protein Structure ◽  
Amino Acid ◽  
Structure Prediction ◽  
Protein Structures ◽  
Correlation Coefficients ◽  
Accessible Surface Area ◽  
Solvent Accessible Surface Area ◽  
Supplementary Information ◽  
Amino Acid Residues ◽  
Solvent Exposure

Abstract Motivation: Solvent exposure of amino acid residues of proteins plays an important role in understanding and predicting protein structure, function and interactions. Solvent exposure can be characterized by several measures including solvent accessible surface area (ASA), residue depth (RD) and contact numbers (CN). More recently, an orientation-dependent contact number called half-sphere exposure (HSE) was introduced by separating the contacts within upper and down half spheres defined according to the Cα-Cβ (HSEβ) vector or neighboring Cα-Cα vectors (HSEα). HSEα calculated from protein structures was found to better describe the solvent exposure over ASA, CN and RD in many applications. Thus, a sequence-based prediction is desirable, as most proteins do not have experimentally determined structures. To our best knowledge, there is no method to predict HSEα and only one method to predict HSEβ. Results: This study developed a novel method for predicting both HSEα and HSEβ (SPIDER-HSE) that achieved a consistent performance for 10-fold cross validation and two independent tests. The correlation coefficients between predicted and measured HSEβ (0.73 for upper sphere, 0.69 for down sphere and 0.76 for contact numbers) for the independent test set of 1199 proteins are significantly higher than existing methods. Moreover, predicted HSEα has a higher correlation coefficient (0.46) to the stability change by residue mutants than predicted HSEβ (0.37) and ASA (0.43). The results, together with its easy Cα-atom-based calculation, highlight the potential usefulness of predicted HSEα for protein structure prediction and refinement as well as function prediction. Availability and implementation: The method is available at http://sparks-lab.org. Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

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