Evaluation of pH change effects on the HSA folding and its drug binding characteristics, a computational biology investigation.

The binding of therapeutics to human serum albumin (HSA), which is an abundant protein in plasma poses a major challenge in drug discovery. Although HSA has several binding pockets, the binding site I on D2 and binding site II on D3 are the main binding pockets of HSA. To date, a few experiments have been conducted to examine the effects of the potential of hydrogen (pH) changes on HSA attributes. In the present investigation, the effect of acidic (pH 7.1) and basic states (pH 7.7) on HSA structure and its drug binding potency were examined in comparison with the physiological state (pH 7.4). For this purpose, molecular dynamics (MD), free energy landscape (FEL), principal component analysis (PCA), probability distribution function (PDF), tunnel-cavity investigation, secondary structure analysis, docking study, and free energy investigation were employed to investigate the effect of pH changes on the structural characteristics of HSA at the atomic level. The results obtained from this study revealed the significant effect of pH alterations on the secondary and tertiary structure of HSA. In addition, HSA stability and its drug binding ability can be severely affected following pH changes. Given that pH change frequently occurs in various diseases such as cancer, diabetes, and kidney failure, therefore, pharmaceutical companies should allocate specific consideration to this subject throughout their drug design experiments.

A pairwise residue contact area-based mean force potential for discrimination of native protein structure.

BACKGROUND: Considering energy function to detect a correct protein fold from incorrect ones is very important for protein structure prediction and protein folding. Knowledge-based mean force potentials are certainly the most popular type of interaction function for protein threading. They are derived from statistical analyses of interacting groups in experimentally determined protein structures. These potentials are developed at the atom or the amino acid level. Based on orientation dependent contact area, a new type of knowledge-based mean force potential has been developed. RESULTS: We developed a new approach to calculate a knowledge-based potential of mean-force, using pairwise residue contact area. To test the performance of our approach, we performed it on several decoy sets to measure its ability to discriminate native structure from decoys. This potential has been able to distinguish native structures from the decoys in the most cases. Further, the calculated Z-scores were quite high for all protein datasets. CONCLUSIONS: This knowledge-based potential of mean force can be used in protein structure prediction, fold recognition, comparative modelling and molecular recognition. The program is available at http://www.bioinf.cs.ipm.ac.ir/softwares/surfield.

STON: A novel method for protein three-dimensional structure comparison.

Protein structure comparison is an important problem in bioinformatics and has many applications in the study of structural and functional genomics. During the last decades, various heuristic methods have been developed to solve the protein structure comparison problem. Most of the protein structure comparison methods give the alignment based on the minimum RMSD (root mean square deviation) and ignore many significant local alignments that may be important for evolutional or functional studies. We have developed a new algorithm to find aligned residues in two proteins with desired RMSD value. The parameterized distance and rotation in this program enable us to search for strongly or weakly similar aligned fragments in two proteins.

A tale of two symmetrical tails: structural and functional characteristics of palindromes in proteins.

BACKGROUND: It has been previously shown that palindromic sequences are frequently observed in proteins. However, our knowledge about their evolutionary origin and their possible importance is incomplete. RESULTS: In this work, we tried to revisit this relatively neglected phenomenon. Several questions are addressed in this work. (1) It is known that there is a large chance of finding a palindrome in low complexity sequences (i.e. sequences with extreme amino acid usage bias). What is the role of sequence complexity in the evolution of palindromic sequences in proteins? (2) Do palindromes coincide with conserved protein sequences? If yes, what are the functions of these conserved segments? (3) In case of conserved palindromes, is it always the case that the whole conserved pattern is also symmetrical? (4) Do palindromic protein sequences form regular secondary structures? (5) Does sequence similarity of the two "sides" of a palindrome imply structural similarity? For the first question, we showed that the complexity of palindromic peptides is significantly lower than randomly generated palindromes. Therefore, one can say that palindromes occur frequently in low complexity protein segments, without necessarily having a defined function or forming a special structure. Nevertheless, this does not rule out the possibility of finding palindromes which play some roles in protein structure and function. In fact, we found several palindromes that overlap with conserved protein Blocks of different functions. However, in many cases we failed to find any symmetry in the conserved regions of corresponding Blocks. Furthermore, to answer the last two questions, the structural characteristics of palindromes were studied. It is shown that palindromes may have a great propensity to form alpha-helical structures. Finally, we demonstrated that the two sides of a palindrome generally do not show significant structural similarities. CONCLUSION: We suggest that the puzzling abundance of palindromic sequences in proteins is mainly due to their frequent concurrence with low-complexity protein regions, rather than a global role in the protein function. In addition, palindromic sequences show a relatively high tendency to form helices, which might play an important role in the evolution of proteins that contain palindromes. Moreover, reverse similarity in peptides does not necessarily imply significant structural similarity. This observation rules out the importance of palindromes for forming symmetrical structures. Although palindromes frequently overlap with conserved Blocks, we suggest that palindromes overlap with Blocks only by coincidence, rather than being involved with a certain structural fold or protein domain.

A method for protein accessibility prediction based on residue types and conformational states.

Prediction of protein accessibility from sequence, as prediction of protein secondary structure is an intermediate step for predicting structures and consequently functions of proteins. Most of the currently used methods are based on single residue prediction, either by statistical means or evolutionary information, and accessibility state of central residue in a window predicted. By expansion of databases of proteins with known 3D structures, we extracted information of pairwise residue types and conformational states of pairs simultaneously. For solving the problem of ambiguity in state prediction by one residue window sliding, we used dynamic programming algorithm to find the path with maximum score. The three state overall per-residue accuracy, Q(3), of this method in a Jackknife test with dataset of known proteins is more than 65% which is an improvement on results of methods based on evolutionary information.

Prediction of protein secondary structure based on residue pair types and conformational states using dynamic programming algorithm.

We have used a statistical approach for protein secondary structure prediction based on information theory and simultaneously taking into consideration pairwise residue types and conformational states. Since the prediction of residue secondary structure by one residue window sliding make ambiguity in state prediction, we used a dynamic programming algorithm to find the path with maximum score. A score system for residue pairs in particular conformations is derived for adjacent neighbors up to ten residue apart in sequence. The three state overall per-residue accuracy, Q3, of this method in a jackknife test with dataset created from PDBSELECT is more than 70%.