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Proteins and Proteomics
Published in Firdos Alam Khan, Biotechnology Fundamentals, 2020
There are various techniques available to analyze the structure of proteins because it is very important to know which protein is structurally normal or abnormal especially in the therapeutic proteins developed by using recombinant DNA technology. We will briefly describe a few techniques to analyze the protein structurally. Molecular dynamics (MD) is an important tool for studying protein folding and dynamics in silico. Because of computational cost, ab initio MD folding simulations with explicit water are limited to peptides and very small proteins. MD simulations of larger proteins remain restricted to dynamics of the experimental structure or its high temperature unfolding. To simulate long-time folding processes (beyond about 1 μs), like folding of small-size proteins (about 50 residues) or larger, some approximations or simplifications in protein models need to be introduced. An approach using reduced protein representation (pseudo-atoms representing groups of atoms are defined) and statistical potential is not only useful in protein structure prediction but is also capable of reproducing the folding pathways. There are distributed computing projects that use idle CPU time of personal computers to solve problems such as protein folding or prediction of protein structure. People can run these programs on their computer or PlayStation 3 to support them.
Proteins and proteomics
Published in Firdos Alam Khan, Biotechnology Fundamentals, 2018
Various techniques are available to analyze the structure of protein because it is very important to know which protein is structurally normal or abnormal, especially in the therapeutic proteins developed by using recombinant DNA technology. We will briefly describe a few techniques to analyze the protein structurally. Molecular dynamics (MD) are an important tool for studying protein folding and dynamics in silico. Because of computational cost, ab initio MD folding simulations with explicit water are limited to peptides and very small proteins. MD simulations of larger proteins remain restricted to dynamics of the experimental structure or its high-temperature unfolding. In order to simulate long-time folding processes (beyond about 1 μs), like folding of small-size proteins (about 50 residues) or larger, some approximations or simplifications in protein models need to be introduced. An approach using reduced protein representation (pseudo-atoms representing groups of atoms are defined), and statistical potential is not only useful in protein structure prediction but is also capable of reproducing the folding pathways. There are distributed computing projects that use idle CPU time of personal computers to solve problems such as protein folding or prediction of protein structure. People can run these programs on their computer or PlayStation 3 to support them.
The inhibitory effect of some natural bioactive compounds against SARS-CoV-2 main protease: insights from molecular docking analysis and molecular dynamic simulation
Published in Journal of Environmental Science and Health, Part A, 2020
Doaa A. Abdelrheem, Shimaa A. Ahmed, H. R. Abd El-Mageed, Hussein S. Mohamed, Aziz A. Rahman, Khaled N. M. Elsayed, Sayed A. Ahmed
It is noticed that SARS-CoV and SARS-CoV-2-3CLpro share remarkable 96.00% sequence alignment among all other human coronaviruses as shown in Figure 2, based on our homology modeling and sequence alignment of 2019-nCoV main protease. The crystal structure of SARS-CoV-2-3CLpro (PDB ID: 6LU7) is highly similar to its SARS-CoV sister (PDB ID: 3TNT) at high resolution with 1.59 Å. multiple additional sequencing studies have been performed for SARS-CoV-2, including a landmark preprint, which suggested renaming 2019-nCoV to SARS-CoV-2 on based on results similar to ours.[58] The highly conserved region of the structural elements was found, the least PDF total energy of 6LU7 and 3TNT are 2728.98 and 2881.43, respectively, that is, a reliable statistical potential to assess the quality of homology models in protein structure prediction. Also, DOPE score of 6LU7 and 3TNT are 70754.34 and 70644.22, respectively. SARS-CoV-2 and SARS-Cov-3CLpro have nine α-helices and 13 β-strands which make up three distinct domains, i.e., domain I, domain II, and domain III. All CoV proteases family consist of three domain, in which Domains I (residues 8–101) and II (residues 102–184) have one antiparallel β-barrel, that resemble the trypsin-like serine proteases structure. Domain III (residues 201–306) consists of 5 α-helices (α5-α9), that are connected by a long loop (residues185–200) with domain II as reported in this study.[6] There are only four mutated residues (Phe 13, Asn 65, Ala 94, and Val 35) between SARS-CoV-2 and SARS-CoV-2-3CLpro as shown in Figure 3. The Ramachandran plot built also, by discovery studio shows that 100% of the residues in the allowed regions, 97.0% in the most favored region as shown in Figure 4. Additionally, 88.2% of the residues have averaged 3D–1D score ≤ 0.3 based on the Verify 3D software, while the overall quality factor of ERRAT is 96.0%. Our homology modeling and sequence alignment of 2019-nCoV main protease is the best agreement with this study,[58,59] which confirmed that the structure of SARS-CoV (PDB Code 3TNT) and SARS-CoV-2-3CLpro (PDB Code 6LU7) share remarkable 96.75% sequence alignment. Due to the high sequence alignment between 3TNT and 2GTB with 6LU7, 3TNT, and 2GTB could be a potential drug target for 2019-nCoV and the inhibition of 3TNT and 2GTB protease would help to restrict the viral maturation thereby decreasing the SARS-CoV-2 infection in humans.