Computational identification of protein S-sulfenylation sites by incorporating the multiple sequence features information

2017 ◽  
Vol 13 (12) ◽  
pp. 2545-2550 ◽  
Author(s):  
Md. Mehedi Hasan ◽  
Dianjing Guo ◽  
Hiroyuki Kurata

Cysteine S-sulfenylation is a major type of posttranslational modification that contributes to protein structure and function regulation in many cellular processes.

2013 ◽  
Vol 42 (1) ◽  
pp. 289-314 ◽  
Author(s):  
André Schönichen ◽  
Bradley A. Webb ◽  
Matthew P. Jacobson ◽  
Diane L. Barber

2021 ◽  
Author(s):  
Liang Hong ◽  
Siqi Sun ◽  
Liangzhen Zheng ◽  
Qingxiong Tan ◽  
Yu Li

Evolutionarily related sequences provide information for the protein structure and function. Multiple sequence alignment, which includes homolog searching from large databases and sequence alignment, is efficient to dig out the information and assist protein structure and function prediction, whose efficiency has been proved by AlphaFold. Despite the existing tools for multiple sequence alignment, searching homologs from the entire UniProt is still time-consuming. Considering the success of AlphaFold, foreseeably, large- scale multiple sequence alignments against massive databases will be a trend in the field. It is very desirable to accelerate this step. Here, we propose a novel method, fastMSA, to improve the speed significantly. Our idea is orthogonal to all the previous accelerating methods. Taking advantage of the protein language model based on BERT, we propose a novel dual encoder architecture that can embed the protein sequences into a low-dimension space and filter the unrelated sequences efficiently before running BLAST. Extensive experimental results suggest that we can recall most of the homologs with a 34-fold speed-up. Moreover, our method is compatible with the downstream tasks, such as structure prediction using AlphaFold. Using multiple sequence alignments generated from our method, we have little performance compromise on the protein structure prediction with much less running time. fastMSA will effectively assist protein sequence, structure, and function analysis based on homologs and multiple sequence alignment.


2020 ◽  
Author(s):  
Khondker Rufaka Hossain ◽  
Daniel Clayton ◽  
Sophia C Goodchild ◽  
Alison Rodger ◽  
Richard James Payne ◽  
...  

Membrane protein structure and function are modulated via interactions with their lipid environment. This is particularly true for the integral membrane pumps, the P-type ATPases. These ATPases play vital roles...


2017 ◽  
Vol 6 (1) ◽  
pp. 75-92 ◽  
Author(s):  
Elka R. Georgieva

AbstractCellular membranes and associated proteins play critical physiological roles in organisms from all life kingdoms. In many cases, malfunction of biological membranes triggered by changes in the lipid bilayer properties or membrane protein functional abnormalities lead to severe diseases. To understand in detail the processes that govern the life of cells and to control diseases, one of the major tasks in biological sciences is to learn how the membrane proteins function. To do so, a variety of biochemical and biophysical approaches have been used in molecular studies of membrane protein structure and function on the nanoscale. This review focuses on electron paramagnetic resonance with site-directed nitroxide spin-labeling (SDSL EPR), which is a rapidly expanding and powerful technique reporting on the local protein/spin-label dynamics and on large functionally important structural rearrangements. On the other hand, adequate to nanoscale study membrane mimetics have been developed and used in conjunction with SDSL EPR. Primarily, these mimetics include various liposomes, bicelles, and nanodiscs. This review provides a basic description of the EPR methods, continuous-wave and pulse, applied to spin-labeled proteins, and highlights several representative applications of EPR to liposome-, bicelle-, or nanodisc-reconstituted membrane proteins.


2021 ◽  
Vol 28 (1) ◽  
Author(s):  
Kavita Sharma ◽  
Kanipakam Hema ◽  
Naveen Kumar Bhatraju ◽  
Ritushree Kukreti ◽  
Rajat Subhra Das ◽  
...  

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