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An Efficient Protein Structure Prediction Using Genetic Algorithm
Published in Abdel-Badeeh M. Salem, Innovative Smart Healthcare and Bio-Medical Systems, 2020
Mohamad Yousef, Tamer Abdelkader, Khaled El-Bahnasy
With all the things proteins do to keep our body functioning and healthy, they can be harmful, damaging, and involved in many diseases in many ways. The better we understand protein folding mechanisms and pathways, the more novel proteins can be designed to combat the disease-related proteins and fix or even destroy them.
The Stress Response and Stress Proteins
Published in John J. Lemasters, Constance Oliver, Cell Biology of Trauma, 2020
Martin E. Feder, Dawn A. Parsell, Susan L. Lindquist
The primary structure of proteins contains all the information needed for acquisition of native structure, and many isolated polypeptides can fold correctly to achieve native structure in vitro. Molecular chaperones impart no steric information to their target proteins; chaperones simply facilitate the self-directed folding process. Nonetheless, molecular chaperones are extremely important, and a brief consideration of protein folding may clarify why this is so.
Disease Prediction and Drug Development
Published in Arvind Kumar Bansal, Javed Iqbal Khan, S. Kaisar Alam, Introduction to Computational Health Informatics, 2019
Arvind Kumar Bansal, Javed Iqbal Khan, S. Kaisar Alam
Protein-folding structure depends upon the property of amino acids' physical and biochemical properties. Amino-acids such as glycine are very flexible, while tryptophan and phenylalanine are rigid. Amino-acids such as leucine, isoleucine, valine, methionine and phenylalanine are hydrophobic (water avoiding). Amino-acids such as glutamine, asparagine, histidine, serine, threonine, tyrosine and cysteine are hydrophilic (affinity for water).
Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics
Published in mAbs, 2022
Rahul Khetan, Robin Curtis, Charlotte M. Deane, Johannes Thorling Hadsund, Uddipan Kar, Konrad Krawczyk, Daisuke Kuroda, Sarah A. Robinson, Pietro Sormanni, Kouhei Tsumoto, Jim Warwicker, Andrew C.R. Martin
Machine learning algorithms have been used for classification, regression, or clustering of biopharmaceutical experimental datasets. Machine learning models have been used for the prediction of protein secondary structure,174,175 relative solvent accessibility,176–179 protein folding,180–183 protein–protein interactions,184–188 and PTMs.189–192 Machine learning methods have also been applied to the prediction of aggregation using a classification tree ensemble with sequence-derived physicochemical properties.7,193 Other machine learning approaches such as gradient-boosting machines have been used for the prediction of CDR structure from protein sequence, particularly CDR-H3.194,195 The most common strategy used by these algorithms is the use of biophysical propensity scales as input features for machine learning methods to characterize the structural and functional properties of proteins.196
Chitooligosaccharide prevents vascular endothelial cell apoptosis by attenuation of endoplasmic reticulum stress via suppression of oxidative stress through Nrf2-SOD1 up-regulation
Published in Pharmaceutical Biology, 2022
Zin Zin Ei, Pilaiwanwadee Hutamekalin, Peerada Prommeenate, Avtar Singh, Soottawat Benjakul, Kittichate Visuttijai, Pithi Chanvorachote
The ER regulates protein post-translational modifications that control appropriate protein folding. During this process, disulphide bonds form the tertiary and quaternary structures of the protein and N-linked oligosaccharides attach to the nascent chain. A failure of appropriate protein folding triggers the degradation process of misfolded proteins called ER-associated degradation (Hampton 2002). Changes in ER function and misfolded proteins lead to ER stress. The cell attempts to restore ER homeostasis by triggering the unfolded protein response (UPR) pathway (Khanna et al. 2021). The UPR is a mechanism to remove unfolded/misfolded proteins and is a defense mechanism that prevents their accumulation. Two main degradation systems are involved in this defense mechanism, including proteasomes and autophagy. Cells determine the mechanism according to the type, severity, and duration of the stress (Ding et al. 2007).
Improvement of Naja haje snake antivenom production using gamma radiation and a biotechnological technique
Published in Toxin Reviews, 2021
Heba Karam, Esmat Shaaban, Aly Fahmy, Hala Zaki, Sanaa Kenawy
Protease and PLA2 enzymes are enzymes known to contribute in venom toxicity or pathophysiological process (Harris et al. 2000; Fuly et al. 2003). It seems conceivable that, the lethal effects of snake venom are largely attributed to its active ingredient phospholipase A2 (PLA2). Ojeda et al. (2017) reported that most snake PLA2s are made up of 120–135 amino acids with about seven disulfide bonds. They have conserved protein folding which consist of three major α-helices that have its catalytic residues, a Ca2+ binding loop, and a β-strand structure known as β-wing. Snake PLA2s can be monomeric, homodimeric or heterodimeric and their enzymatic activity ranges from strong to unmeasurable. They exert tremendous toxic effects not only to nerves and muscles, but also to platelets, leukocytes, and erythrocytes.