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An Analysis of Protein Interaction and Its Methods, Metabolite Pathway and Drug Discovery
Published in Ayodeji Olalekan Salau, Shruti Jain, Meenakshi Sood, Computational Intelligence and Data Sciences, 2022
Protein is used to build and repair tissues, and it is the basic structure of all cells in our body. It is a macromolecule that helps in the effective functioning of cells, and it performs a specific function in the body. The biological or biochemical role of a protein is assigned using protein function prediction [60]. Heterogeneous data are used in computational methods for protein function prediction. To create a protein interaction network, a number of top threshold measures are considered, such as protein sequences, building blocks of the protein structures and expressions of the genes [61]. In cell life cycle, with the combination of unknown proteins with its amino acids, photo- and chemical cross-linking is the broad application of protein interactions. It captures the highlights and maps the surface of the protein interactions, which can examine the analysis of photo-cross-linking and mass spectrometric combination. Some of the applications and improved areas of protein interactions with ncAAs are protein stapling, protein conformation with photo-control, cross-linking with two-dimensionality, transient stabilization and less affinity of protein interactions [62].
First study to describe a novel HbA2: c.400A > C mutation and Hb Dongguan heterozygote in two unrelated Chinese families
Published in Hematology, 2022
Cuize Yao, Danqing Qin, Jicheng Wang, Xiuqin Bao, Jie Liang, Li Du
Regarding the second variant in Family 2 that we reported, Hb Dongguan was first described in a 67-year-old Chinese male, who was compound heterozygous for Hb Dongguan and – –SEA α-thal deletion with an anomalous peak accounting for 37.8% of the total Hb and presented typical microcytic hypochromic anaemia [12]. However, the previous study did not provide a haematological phenotype of the simple heterozygous Hb Dongguan. This limitation has been addressed in the current report. Our description of the haematological and molecular features of individuals carrying only the Hb Dongguan variant could facilitate laboratory detection and clinical understanding of this variant. Moreover, it has been reported that the isopropanol test is strongly positive [12], indicating that Hb Dongguan is unstable in nature. Although the heterozygous state of the two variants in this study did not lead to obvious symptoms of anaemia, these variants did cause some functional changes, such as affinity changes and the generation of unstable Hb according to the literature [12] and protein function prediction.
Deep learning approaches for data-independent acquisition proteomics
Published in Expert Review of Proteomics, 2021
During the past decades, deep learning has advanced rapidly, showed superior performance in various fields, enabled many practical applications, and attracted extensive attention. Deep neural networks (DNNs), including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), can learn different representations of objects automatically to recognize complex patterns from large datasets [17]. CNNs can learn to capture local patterns in spatially arranged data and have been widely used for image data analysis. RNNs, and specifically variants with gated recurrent units (GRUs) [18] or long short-term memory (LSTM) [19], can capture long-range interactions within sequential data, such as text, audio, and DNA/protein sequences. LeCun et al [17] have systematically reviewed the principles and typical applications of CNNs and RNNs. Deep learning has already been applied to various aspects of biomedical research [20], including protein function prediction [21], protein post-translational modifications (PTMs) site prediction [22], tumor classification, and biomarker discovery [23]. Other recent reviews cover basic concept of deep learning and its more generally applications in proteomics [24], as well as deep learning approaches specifically for peptide property prediction and peptide/protein identification [25].
A Newborn with Congenital Hyperinsulinism
Published in Fetal and Pediatric Pathology, 2019
Yiting Du, Rong Ju, Yufeng Xi, Peng Gou
For the current case, the patient had developed recurrent and severe hypoglycemia shortly after birth. Related gene mutations were detected in the child and his parents by next-generation sequencing combined with Sanger sequencing. As a result, a compound heterozygous mutation in the child’s ABCC8 gene was found, namely, c.4412delT and c.3979G > A, inherited from the father and mother, respectively. According to SIFT, PolyPhen_2 and REVEL protein function prediction software, c.4412delT (deletion of thymidine) results in the amino acid change p.L1471Pfs*27 (frameshift mutation).The frequency of c.4412delT in the general population is almost nonexistent. C.3979G > A (nucleotide no. 3979 in the coding region is changed from guanine to adenine) leads to the amino acid change p.E1327K (amino acid no. 1327 is mutated from glutamic acid to lysine), a missense mutation. The frequency of c.3979G > A mutation in the general population is 0.00190. The Human Gene Mutation Database (HGMD), a professional disease database, reported that the c.4412delT variant of the ABCC8 gene is associated with CHI [11]. The researchers also analyzed 59 patients who had been diagnosed with diabetes within 6 months after birth by genetic testing, and found that there were complex heterozygous mutations, one of which was the c.3979G > A in the ABCC8 gene [12]. Genealogical analysis of the patient’s family showed recessive inheritance, the c.3979G > A mutation originated from the mother. This suggests that the c.3979G > A mutation is closely related to abnormal insulin secretion.