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Proteins and Proteomics
Published in Firdos Alam Khan, Biotechnology Fundamentals, 2020
After the first bond is synthesized, the RNA polymerase must clear the promoter. During this time, there is a tendency to release the RNA transcript and produce truncated transcripts. This is called abortive initiation and is common for both eukaryotes and prokaryotes. Abortive initiation continues to occur until the σ factor rearranges, resulting in the transcription elongation complex (which gives a 35 base pair moving footprint). The σ factor is released before 80 nucleotides of mRNA are synthesized. Once the transcript reaches approximately 23 nucleotides, it no longer slips, and elongation can occur. This, like most of the remainder of transcription, is an energy-dependent process, consuming ATP. Promoter clearance coincides with phosphorylation of serine 5 on the carboxyl terminal domain of RNA Pol in prokaryotes, which is phosphorylated by transcription factor II H (TFIIH).
Proteins and proteomics
Published in Firdos Alam Khan, Biotechnology Fundamentals, 2018
After the first bond is synthesized, the RNA polymerase must clear the promoter. During this time, there is a tendency to release the RNA transcript and produce truncated transcripts. This is called abortive initiation and is common for both eukary-otes and prokaryotes. Abortive initiation continues to occur until the a factor rearranges, resulting in the transcription elongation complex (which gives a 35-base-pair moving footprint). The σ factor is released before 80 nucleotides of mRNA are synthesized. Once the transcript reaches approximately 23 nucleotides, it no longer slips and elongation can occur. This, like most of the remainder of transcription, is an energy-dependent process, consuming adenosine triphosphate (ATP). Promoter clearance coincides with phosphorylation of serine 5 on the carboxyl terminal domain of RNA Pol in prokaryotes, which is phosphorylated by transcription factor II H (TFIIH).
Subsets of adjacent nodes (SOAN): a fast method for computing suboptimal paths in protein dynamic networks
Published in Molecular Physics, 2021
Thomas Dodd, Xin-Qiu Yao, Donald Hamelberg, Ivaylo Ivanov
We first tested the computational efficiency of each suboptimal path method using four distinct biological systems of increasing size: (i) acid-β-glucosidase (GlcCerase), a 497 amino acid lysosomal hydrolase [41], (ii) DNA polymerase III (Pol III), a 2033 residue replicative enzyme in E. Coli bacteria [42], (iii) human transcription factor IIH (TFIIH), a complex comprised of 10 protein subunits and 3995 amino acids involved in both transcription and nucleotide excision repair [43], and (iv) human pre-initiation complex (PIC), a massive 22-subunit and 9900 amino acid complex involved in transcription initiation [44]. All systems have been previously characterised using graph theory methods [21,37,38] and, therefore, serve as excellent test cases for comparison of methods for suboptimal path determination. For each system and method tested, we determined the runtime needed to compute 1000 shortest paths (Table 2 and Figure 2). In the case of Pol III, TFIIH and PIC, WISP did not finish in a practical amount of time (see note in Table 2) and was, therefore, excluded from direct efficiency comparison with the other methods. Overall, our results demonstrate that SOAN is remarkably fast compared to the other approaches. The only exception is the runtime of NetworkView for the smallest of our test systems, GlcCerase. However, even for GlcCerase, both NetworkView and SOAN performed within a negligible difference of ∼0.5 s. More importantly, as the number of edges in the simulated system increases, SOAN demonstrates the best scalability. In contrast, the runtime of CNAPATH and NetworkView increases faster with the increase in the total number of edges (Figure 2). NetworkView performs well on small to medium-size systems but its advantages disappear for protein networks the size of PIC with ∼35,000 edges. Moreover, SOAN still outperforms NetworkView for Pol III (7405 edges), TFIIH (12,896 edges) and PIC (32,851 edges), with speedups of ∼3× or greater. Thus, for larger systems SOAN appears to be an optimal choice.