Effect of Binding of Ions and Other Small Molecules on Protein Structure. III. Influence of Amino Acids on the Isomerization of Proteins1

1957 ◽  
Vol 79 (17) ◽  
pp. 4677-4679 ◽  
Author(s):  
Robert A. Phelps ◽  
John R. Cann
Keyword(s):  
Amino Acids ◽  
Protein Structure ◽  
Small Molecules

Analysis of Oncogene Protein Structure Using Small World Network Concept

2020 ◽  
Vol 15 (7) ◽  
pp. 732-740
Author(s):  
Neetu Kumari ◽  
Anshul Verma
Keyword(s):  
Amino Acids ◽  
Protein Structure ◽  
Degree Distribution ◽  
Protein Structures ◽  
Small World ◽  
Extreme Condition ◽  
Centrality Measures ◽  
Small World Network ◽  
Network Concept ◽  
Oncogene Protein

Background: The basic building block of a body is protein which is a complex system whose structure plays a key role in activation, catalysis, messaging and disease states. Therefore, careful investigation of protein structure is necessary for the diagnosis of diseases and for the drug designing. Protein structures are described at their different levels of complexity: primary (chain), secondary (helical), tertiary (3D), and quaternary structure. Analyzing complex 3D structure of protein is a difficult task but it can be analyzed as a network of interconnection between its component, where amino acids are considered as nodes and interconnection between them are edges. Objective: Many literature works have proven that the small world network concept provides many new opportunities to investigate network of biological systems. The objective of this paper is analyzing the protein structure using small world concept. Methods: Protein is analyzed using small world network concept, specifically where extreme condition is having a degree distribution which follows power law. For the correct verification of the proposed approach, dataset of the Oncogene protein structure is analyzed using Python programming. Results: Protein structure is plotted as network of amino acids (Residue Interaction Graph (RIG)) using distance matrix of nodes with given threshold, then various centrality measures (i.e., degree distribution, Degree-Betweenness correlation, and Betweenness-Closeness correlation) are calculated for 1323 nodes and graphs are plotted. Conclusion: Ultimately, it is concluded that there exist hubs with higher centrality degree but less in number, and they are expected to be robust toward harmful effects of mutations with new functions.

A pair-to-pair amino acids substitution matrix and its applications for protein structure prediction

2007 ◽  
Vol 67 (1) ◽  
pp. 142-153 ◽  
Author(s):  
Eran Eyal ◽  
Milana Frenkel-Morgenstern ◽  
Vladimir Sobolev ◽  
Shmuel Pietrokovski
Keyword(s):  
Amino Acids ◽  
Protein Structure ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Substitution Matrix

3. Proteins

2021 ◽  
pp. 34-51
Author(s):  
Mark Lorch
Keyword(s):  
Amino Acids ◽  
Protein Folding ◽  
Protein Structure ◽  
Protein Structures ◽  
Structure And Function ◽  
Vast Array ◽  
A Cell ◽  
Cellular Machinery ◽  
And Function ◽  
The Relationship

This chapter examines proteins, the dominant proportion of cellular machinery, and the relationship between protein structure and function. The multitude of biological processes needed to keep cells functioning are managed in the organism or cell by a massive cohort of proteins, together known as the proteome. The twenty amino acids that make up the bulk of proteins produce the vast array of protein structures. However, amino acids alone do not provide quite enough chemical variety to complete all of the biochemical activity of a cell, so the chapter also explores post-translation modifications. It finishes by looking as some dynamic aspects of proteins, including enzyme kinetics and the protein folding problem.

scholarly journals A defined structural unit enables de novo design of small-molecule–binding proteins

Science ◽  
2020 ◽  
Vol 369 (6508) ◽  
pp. 1227-1233 ◽  
Author(s):  
Nicholas F. Polizzi ◽  
William F. DeGrado
Keyword(s):  
Protein Structure ◽  
Amino Acid ◽  
Small Molecules ◽  
Structural Unit ◽  
De Novo ◽  
Computational Design ◽  
De Novo Design ◽  
X Ray ◽  
X Ray Crystallography ◽  
Chemical Groups

The de novo design of proteins that bind highly functionalized small molecules represents a great challenge. To enable computational design of binders, we developed a unit of protein structure—a van der Mer (vdM)—that maps the backbone of each amino acid to statistically preferred positions of interacting chemical groups. Using vdMs, we designed six de novo proteins to bind the drug apixaban; two bound with low and submicromolar affinity. X-ray crystallography and mutagenesis confirmed a structure with a precisely designed cavity that forms favorable interactions in the drug–protein complex. vdMs may enable design of functional proteins for applications in sensing, medicine, and catalysis.

scholarly journals Different Synergy in Amyloids and Biologically Active Forms of Proteins

2019 ◽  
Vol 20 (18) ◽  
pp. 4436 ◽  
Author(s):  
Piotr Fabian ◽  
Katarzyna Stapor ◽  
Mateusz Banach ◽  
Magdalena Ptak-Kaczor ◽  
Leszek Konieczny ◽  
...  
Keyword(s):  
Amino Acids ◽  
Comparative Analysis ◽  
Protein Structure ◽  
Tertiary Structure ◽  
Protein Structures ◽  
Water Environment ◽  
Biologically Active ◽  
Radius Of Curvature ◽  
Hydrophobic Core ◽  
Structural Form

Protein structure is the result of the high synergy of all amino acids present in the protein. This synergy is the result of an overall strategy for adapting a specific protein structure. It is a compromise between two trends: The optimization of non-binding interactions and the directing of the folding process by an external force field, whose source is the water environment. The geometric parameters of the structural form of the polypeptide chain in the form of a local radius of curvature that is dependent on the orientation of adjacent peptide bond planes (result of the respective Phi and Psi rotation) allow for a comparative analysis of protein structures. Certain levels of their geometry are the criteria for comparison. In particular, they can be used to assess the differences between the structural form of biologically active proteins and their amyloid forms. On the other hand, the application of the fuzzy oil drop model allows the assessment of the role of amino acids in the construction of tertiary structure through their participation in the construction of a hydrophobic core. The combination of these two models—the geometric structure of the backbone and the determining of the participation in the construction of the tertiary structure that is applied for the comparative analysis of biologically active and amyloid forms—is presented.

scholarly journals Escherichia coli amino acid auxotrophic expression host strains for investigating protein structure-function relationships

2020 ◽  
Author(s):  
Toshio Iwasaki ◽  
Yoshiharu Miyajima-Nakano ◽  
Risako Fukazawa ◽  
Myat T Lin ◽  
Shin-Ichi Matsushita ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Amino Acids ◽  
Protein Structure ◽  
Amino Acid ◽  
Structure Function ◽  
Growth Medium ◽  
Isotope Labeling ◽  
Water Soluble ◽  
Expression Host ◽  
Host Strains

Abstract A set of C43(DE3) and BL21(DE3) Escherichia coli host strains that are auxotrophic for various amino acids is briefly reviewed. These strains require the addition of a defined set of one or more amino acids in the growth medium, and have been specifically designed for overproduction of membrane or water-soluble proteins selectively labeled with stable isotopes such as 2H, 13C and 15N. The strains described here are available for use and have been deposited into public strain banks. Although they cannot fully eliminate the possibility of isotope dilution and mixing, metabolic scrambling of the different amino acid types can be minimized through a careful consideration of the bacterial metabolic pathways. The use of a suitable auxotrophic expression host strain with an appropriately isotopically labeled growth medium ensures high levels of isotope labeling efficiency as well as selectivity for providing deeper insight into protein structure-function relationships.

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