Biomedical subjects

K Saraboji

Publications and source records attributed to K Saraboji.

8 recordsLinked to original sources

PubMed2006

Prediction of protein mutant stability using classification and regression tool.

Prediction of protein stability upon amino acid substitutions is an important problem in molecular biology and the solving of which would help for designing stable mutants. In this work, we have analyzed the stability of protein mutants using two different datasets of 1396 and 2204 mutants obtained from ProTherm database, respectively for free energy change due to thermal (DeltaDeltaG) and denaturant denaturations (DeltaDeltaG(H(2)O)). We have used a set of 48 physical, chemical energetic and conformational properties of amino acid residues and computed the difference of amino acid properties for each mutant in both sets of data. These differences in amino acid properties have been related to protein stability (DeltaDeltaG and DeltaDeltaG(H(2)O)) and are used to train with classification and regression tool for predicting the stability of protein mutants. Further, we have tested the method with 4 fold, 5 fold and 10 fold cross validation procedures. We found that the physical properties, shape and flexibility are important determinants of protein stability. The classification of mutants based on secondary structure (helix, strand, turn and coil) and solvent accessibility (buried, partially buried, partially exposed and exposed) distinguished the stabilizing/destabilizing mutants at an average accuracy of 81% and 80%, respectively for DeltaDeltaG and DeltaDeltaG(H(2)O). The correlation between the experimental and predicted stability change is 0.61 for DeltaDeltaG and 0.44 for DeltaDeltaG(H(2)O). Further, the free energy change due to the replacement of amino acid residue has been predicted within an average error of 1.08 kcal/mol and 1.37 kcal/mol for thermal and chemical denaturation, respectively. The relative importance of secondary structure and solvent accessibility, and the influence of the dataset on prediction of protein mutant stability have been discussed.

Amino Acid Substitution↗

PubMed2006

Crystal structure of haemoglobin from donkey (Equus asinus) at 3A resolution.

Haemoglobin from donkey was purified and crystallized in space group C2. The present donkey haemoglobin model comprises of two subunits alpha and beta. These alpha and beta subunits comprise of 141 and 146 amino acid residues, respectively, and the haem groups. The donkey haemoglobin differs from horse only in two amino acids of alpha-chain (His20 to Asn and Tyr24 to Phe) and these substitutions do not significantly change the secondary structural features of donkey haemoglobin. The haem group region and subunit contacts are closely resemble with that of horse methaemoglobin.

Amino Acid Sequence↗

PubMed2006

Average assignment method for predicting the stability of protein mutants.

Prediction of protein stability upon amino acid substitutions is an important problem in molecular biology and it will be helpful for designing stable mutants. In this work, we have analyzed the stability of protein mutants using three different data sets of 1791, 1396, and 2204 mutants, respectively, for thermal stability (DeltaTm), free energy change due to thermal (DeltaDeltaG), and denaturant denaturations (DeltaDeltaGH2O), obtained from the ProTherm database. We have classified the mutants into 380 possible substitutions and assigned the stability of each mutant using the information obtained with similar type of mutations. We observed that this assignment could distinguish the stabilizing and destabilizing mutants to an accuracy of 70-80% at different measures of stability. Further, we have classified the mutants based on secondary structure and solvent accessibility (ASA) and observed that the classification significantly improved the accuracy of prediction. The classification of mutants based on helix, strand, and coil distinguished the stabilizing/destabilizing mutants at an average accuracy of 82% and the correlation is 0.56; information about the location of residues at the interior, partially buried, and surface regions of a protein correctly identified the stabilizing/destabilizing residues at an average accuracy of 81% and the correlation is 0.59. The nine subclassifications based on three secondary structures and solvent accessibilities improved the accuracy of assigning stabilizing/destabilizing mutants to an accuracy of 84-89% for the three data sets. Further, the present method is able to predict the free energy change (DeltaDeltaG) upon mutations within a deviation of 0.64 kcal/mol. We suggest that this method could be used for predicting the stability of protein mutants.

Amino Acid Substitution↗

PubMed2005

Role of amino acid properties to determine backbone tau(N-Calpha-C') stretching angle in peptides and proteins.

The analysis of the basic geometry of amino acid residues of protein structures has demonstrated the invariability of all the bond lengths and bond angles except for tau, the backbone N-Calpha-C' angle. This angle can be widened or contracted significantly from the tetrahedral geometry to accommodate various other strains in the structure. In order to accurately determine the cause for this deviation, a survey is made for the tau angles using the peptide structures and the ultrahigh resolution protein structures. The average deviation of N-Calpha-C' angles from tetrahedral geometry for each amino acid in all the categories were calculated and then correlated with forty-eight physiochemical, energetic and conformational properties of amino acids. Linear and multiple regression analysis were carried out between the amino acid deviation and the 48 properties. This study confirms the deviation of tau angles in both the peptide and protein structures but similar forces do not influence them. The peptide structures are influenced by physical properties whereas as expected the conformational properties influence the protein structures. And it is not any single property that dominates the deviation but the combination of different factors contributes to the tau angle deviation.

Algorithms↗

PubMed2005

Relative importance of secondary structure and solvent accessibility to the stability of protein mutants. A case study with amino acid properties and energetics on T4 and human lysozymes.

Understanding the factors influencing the stability of protein mutants is an important task in molecular and computational biology. In this work, we have approached this problem by examining the relative importance of secondary structure and solvent accessibility of the mutant residue for understanding/predicting the stability of protein mutants. We have used hydrophobic, electrostatic and hydrogen bond free energy terms and nine unique physicochemical, energetic and conformational properties of amino acids in the present study and these parameters have been related with changes in thermal stability (DeltaTm) of all the single mutants of lysozymes based on single and multiple correlation coefficients. As expected the properties reflecting hydrophobicity and hydrophobic free energy play a major role to distinguish stabilizing and destabilizing mutants. The hydrophobic free energy due to carbon and nitrogen atoms distinguish the stability of coil and strand mutations to the accuracy of 100 and 90%, respectively. In agreement with previous results, the subgroup classification based on secondary structure and the information about its location in the structure yielded good relationship with the experimental DeltaTm. We revealed that the secondary structure information is equally or more important than solvent accessibility for understanding the stability of protein mutants. The comparison of amino acid properties with free-energy terms indicate that the energetic contribution explains the mutant stability better in coil region whereas the amino acid properties do better in strand region. Further, the combination of free energies with amino acid properties increased the correlation significantly. The present study demonstrates the importance of classifying the mutants based on secondary structure to the stability of proteins upon mutations.

Amino Acids↗

PubMed2005

Importance of main-chain hydrophobic free energy to the stability of thermophilic proteins.

Living organisms are found in the most unexpected places, including deep-sea vents at 100 degrees C and several hundred bars pressure, in hot springs. Needless to say, the proteins found in thermophilic species are much more stable than their mesophilic counterparts. There are no obvious reasons to say that one would be more stable than others. Even examination of the amino acids and comparison of structural features of thermophiles with mesophilies cannot bring satisfactory explanation for the thermal stability of such proteins. In order to bring out the hidden information behind the thermal stabilization of such proteins in terms of energy factors and their combinations, analysis were made on good resolution structures of thermophilic and their mesophilic homologous from 23 different families. From the structural coordinates, free energy contributions due to hydrophobic, electrostatic, hydrogen bonding, disulfide bonding and van der Waals interactions are computed. In this analysis, a vast majority of thermophilic proteins adopt slightly lower free energy contribution in each energy terms than its mesophilic counterparts. The major observation noted from this study is the lower hydrophobic free energy contribution due to carbon atoms and main-chain nitrogen atoms in all the thermophilic proteins. The possible combination of different free energy terms shows majority of the thermophilic proteins have lower free energy strategy than their mesophilic homologous. The derived results show that the hydrophobic free energy due to carbon and nitrogen atoms and such combinations of free energy components play a vital role in the thermostablisation of such proteins.

Animals↗

PubMed2004

Role of non-covalent interactions for determining the folding rate of two-state proteins.

Understanding the factors influencing the folding rate of proteins is a challenging problem. In this work, we have analyzed the role of non-covalent interactions for the folding rate of two-state proteins by free-energy approach. We have computed the free-energy terms, hydrophobic, electrostatic, hydrogen-bonding and van der Waals free energies. The hydrophobic free energy has been divided into the contributions from different atoms, carbon, neutral nitrogen and oxygen, charged nitrogen and oxygen, and sulfur. All the free-energy terms have been related with the folding rates of 28 two-state proteins with single and multiple correlation coefficients. We found that the hydrophobic free energy due to carbon atoms and hydrogen-bonding free energy play important roles to determine the folding rate in combination with other free energies. The normalized energies with total number of residues showed better results than the total energy of the protein. The comparison of amino acid properties with free-energy terms indicates that the energetic terms explain better the folding rate than amino acid properties. Further, the combination of free energies with topological parameters yielded the correlation of 0.91. The present study demonstrates the importance of topology for determining the folding rate of two-state proteins.

Binding Sites↗

PubMed2004

Purification and crystallization of haemoglobin from donkey (Equus asinus).

Haemoglobin acts as an important protein for oxygen carrier in all living beings. Purification of donkey haemoglobin was done using PEG 4000 as a separating medium. Crystallization was achieved using hanging drop vapor diffusion method using 2.8 M phosphate buffer, pH 6.8. Data collection was done using mar345 image plate detector system. The crystals grown under 2.8 M phosphate buffer are monoclinic with space group C2 and cell dimensions a=107.664 A, b=63.084 A, c=54.042 A, and beta=111.747 degrees.

Animals↗