Pub Date : 2022-10-10DOI: 10.2174/1570164619666221010100406
D. Mehrotra, Charu Kathuria, N. Misra
The machine learning computation paradigm touched new horizons with the development of deep learning architectures. It is widely used in complex problems and achieved significant results in many traditional applications like protein structure prediction, speech recognition, traffic management, health diagnostic systems and many more. Especially, Convolution neural network (CNN) has revolutionized visual data processing tasks. Protein structure is an important research area in various domains extending from medical science, health sectors to drug designing. Fourier Transform Infrared Spectroscopy (FTIR) is the leading tool for protein structure determination. This review aims to study the existing deep learning approaches proposed in the literature to predict proteins' secondary structure and to develop a conceptual relation between FTIR spectra images and deep learning models to predict the structure of proteins. Various pre-trained CNN models are identified and interpreted to correlate the FTIR images of proteins containing Amide-I and Amide-II absorbance values and their secondary structure. The concept of transfer learning is efficiently incorporated using the models like Visual Geometry Group (VGG), Inception, Resnet, and Efficientnet. The dataset of protein spectra images is applied as input, and these models act significantly to predict the secondary structure of proteins. As deep learning is recently being explored in this field of research, it worked remarkably in this application and needs continuous improvement with the development of new models.
{"title":"Predicting the Secondary Structure of Proteins: A Deep Learning Approach","authors":"D. Mehrotra, Charu Kathuria, N. Misra","doi":"10.2174/1570164619666221010100406","DOIUrl":"https://doi.org/10.2174/1570164619666221010100406","url":null,"abstract":"\u0000\u0000The machine learning computation paradigm touched new horizons with the development of deep learning architectures. It is widely used in complex problems and achieved significant results in many traditional applications like protein structure prediction, speech recognition, traffic management, health diagnostic systems and many more. Especially, Convolution neural network (CNN) has revolutionized visual data processing tasks.\u0000\u0000\u0000\u0000Protein structure is an important research area in various domains extending from medical science, health sectors to drug designing. Fourier Transform Infrared Spectroscopy (FTIR) is the leading tool for protein structure determination. This review aims to study the existing deep learning approaches proposed in the literature to predict proteins' secondary structure and to develop a conceptual relation between FTIR spectra images and deep learning models to predict the structure of proteins.\u0000\u0000\u0000\u0000Various pre-trained CNN models are identified and interpreted to correlate the FTIR images of proteins containing Amide-I and Amide-II absorbance values and their secondary structure.\u0000\u0000\u0000\u0000The concept of transfer learning is efficiently incorporated using the models like Visual Geometry Group (VGG), Inception, Resnet, and Efficientnet. The dataset of protein spectra images is applied as input, and these models act significantly to predict the secondary structure of proteins.\u0000\u0000\u0000\u0000As deep learning is recently being explored in this field of research, it worked remarkably in this application and needs continuous improvement with the development of new models.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73641549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-08DOI: 10.2174/1570164619666220908141130
D. Bisht, Rananjay Singh, D. Sharma, D. Sharma, S. Gautam, Mahendra K. Gupta
Although treatable, resistant form of tuberculosis has posed a major impediment to the effective TB control programme. As the Mycobacterium tuberculosis cell envelope is closely associated with its virulence and resistance, it is very important to understand the cell envelope for better treatment of causative pathogens. Cell membrane plays a crucial role in imparting various cell functions. Proteins being the functional moiety, it is impossible to characterize the functional properties based on genetic analysis alone. Proteomic based research has indicated mycobacterial envelope as a good source of antigens/proteins. Envelope/membrane and associated proteins have an anticipated role in biological processes which could be of vital importance to the microbe and hence could qualify as drug targets. This review provides an overview of the prominent and biologically important cell envelope and highlights the different functions offered by the proteins associated with it. Selective targeting of the mycobacterial envelope offers an untapped opportunity to address the problems associated with the current drugs regimen and also will lead to the development of more potent and safer drugs against all forms of tuberculous infections.
{"title":"Unraveling major proteins of Mycobacterium tuberculosis envelope","authors":"D. Bisht, Rananjay Singh, D. Sharma, D. Sharma, S. Gautam, Mahendra K. Gupta","doi":"10.2174/1570164619666220908141130","DOIUrl":"https://doi.org/10.2174/1570164619666220908141130","url":null,"abstract":"\u0000\u0000Although treatable, resistant form of tuberculosis has posed a major impediment to the effective TB control programme. As the Mycobacterium tuberculosis cell envelope is closely associated with its virulence and resistance, it is very important to understand the cell envelope for better treatment of causative pathogens. Cell membrane plays a crucial role in imparting various cell functions. Proteins being the functional moiety, it is impossible to characterize the functional properties based on genetic analysis alone. Proteomic based research has indicated mycobacterial envelope as a good source of antigens/proteins. Envelope/membrane and associated proteins have an anticipated role in biological processes which could be of vital importance to the microbe and hence could qualify as drug targets. This review provides an overview of the prominent and biologically important cell envelope and highlights the different functions offered by the proteins associated with it. Selective targeting of the mycobacterial envelope offers an untapped opportunity to address the problems associated with the current drugs regimen and also will lead to the development of more potent and safer drugs against all forms of tuberculous infections.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72914178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-17DOI: 10.2174/1570164619666220617145437
Z. Basharat, K. Moon, L. Foster, A. Yasmin
Heavy metals impact living organism deleteriously when exceed the required limits. Their remediation by bacteria is a much pursued area of environmental research. In this study, we explored the quantitative changes for four heavy metals (Cadmium, Chromium, Zinc, Copper), on global and membrane proteome of gram negative S. nematodiphila MB307. This is a versatile bacterium, isolated from rhizosphere of heavy metal tolerating plant and equipped with characteristics ranging from useful biopeptide production to remediation of metals. We explored changes in its static end products of coding DNA sequences i.e. proteins after 24 incubation under metal stress, using LC-MS/MS. Data analysis was done using MaxQuant software coupled with Perseus package. Up and downregulated protein fractions consisted prominently of chaperones, membrane integrity proteins, mobility or transporter proteins. Comparative analysis with previously studied bacteria and functional contribution of these proteins in metal stress offers evidence for survival of S. nematodiphila under high concentrations of selected metals. The outcomes validate that this soil derived bacterium is well attuned to remove these metals from soil, water and may be additionally useful for boosting phytoremediation of metals. This study delivers interesting insights and overlays ground for further investigations into mechanistic activity of this bacterium under pollutant stress.
{"title":"Heavy metal stress tolerance by Serratia nematodiphila sp. MB307: insights from mass spectrometry based proteomics","authors":"Z. Basharat, K. Moon, L. Foster, A. Yasmin","doi":"10.2174/1570164619666220617145437","DOIUrl":"https://doi.org/10.2174/1570164619666220617145437","url":null,"abstract":"\u0000\u0000Heavy metals impact living organism deleteriously when exceed the required limits. Their remediation by bacteria is a much pursued area of environmental research. In this study, we explored the quantitative changes for four heavy metals (Cadmium, Chromium, Zinc, Copper), on global and membrane proteome of gram negative S. nematodiphila MB307. This is a versatile bacterium, isolated from rhizosphere of heavy metal tolerating plant and equipped with characteristics ranging from useful biopeptide production to remediation of metals.\u0000\u0000\u0000\u0000We explored changes in its static end products of coding DNA sequences i.e. proteins after 24 incubation under metal stress, using LC-MS/MS. Data analysis was done using MaxQuant software coupled with Perseus package.\u0000\u0000\u0000\u0000Up and downregulated protein fractions consisted prominently of chaperones, membrane integrity proteins, mobility or transporter proteins. Comparative analysis with previously studied bacteria and functional contribution of these proteins in metal stress offers evidence for survival of S. nematodiphila under high concentrations of selected metals.\u0000\u0000\u0000\u0000The outcomes validate that this soil derived bacterium is well attuned to remove these metals from soil, water and may be additionally useful for boosting phytoremediation of metals. This study delivers interesting insights and overlays ground for further investigations into mechanistic activity of this bacterium under pollutant stress.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72448184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-31DOI: 10.2174/1570164619666220531113704
Rui Wang, Lei Chen
Protein function is closely related to its location within the cell. Determination of protein subcellular location is helpful to uncover its functions. However, traditional biological experiments to determine the subcellular location are of high cost and low efficiency, which cannot meet today’s needs. In recent years, lots of computational models have been set up to identify protein subcellular locations. Most models used features derived from protein sequences. Recently, features extracted from protein-protein interaction (PPI) network become popular to study various protein-related problems. A novel model with features derived from multiple PPI networks was proposed to predict protein subcellular location. Protein features were obtained by a new designed network embedding algorithm, Mnode2vec, which was a generalized version of the classic Node2vec algorithm. Two classic classification algorithms: support vector machine and random forest, were employed to build the model. Such model provided good performance and was superior to the model with features extracted by Node2vec. Also, this model outperformed some classic models. Furthermore, Mnode2vec can produce powerful features when the path length was small. The proposed model can be a powerful tool to determine protein subcellular location and Mnode2vec can efficiently extract informative features from multiple networks.
{"title":"Identification of human protein subcellular location with multiple networks","authors":"Rui Wang, Lei Chen","doi":"10.2174/1570164619666220531113704","DOIUrl":"https://doi.org/10.2174/1570164619666220531113704","url":null,"abstract":"\u0000\u0000Protein function is closely related to its location within the cell. Determination of protein subcellular location is helpful to uncover its functions. However, traditional biological experiments to determine the subcellular location are of high cost and low efficiency, which cannot meet today’s needs. In recent years, lots of computational models have been set up to identify protein subcellular locations. Most models used features derived from protein sequences. Recently, features extracted from protein-protein interaction (PPI) network become popular to study various protein-related problems.\u0000\u0000\u0000\u0000A novel model with features derived from multiple PPI networks was proposed to predict protein subcellular location.\u0000\u0000\u0000\u0000Protein features were obtained by a new designed network embedding algorithm, Mnode2vec, which was a generalized version of the classic Node2vec algorithm. Two classic classification algorithms: support vector machine and random forest, were employed to build the model.\u0000\u0000\u0000\u0000Such model provided good performance and was superior to the model with features extracted by Node2vec. Also, this model outperformed some classic models. Furthermore, Mnode2vec can produce powerful features when the path length was small.\u0000\u0000\u0000\u0000The proposed model can be a powerful tool to determine protein subcellular location and Mnode2vec can efficiently extract informative features from multiple networks.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73668864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-13DOI: 10.2174/1570164619666220513123509
M. Zarei, S. Sabetian, M. Rahbar, M. Negahdaripour
Arginine deiminase enzyme of Mycoplasma arginini (MaADI) is a potential anti-cancer agent for treating arginine-auxotrophic cancers. Investigating the protein stability in the presence of osmolytes can help to increase protein stability under various stressed conditions. In this study, the stability and dynamics of MaADI were investigated in pure water and solutions of 1 M sorbitol, 10% (v/v) methanol, and 50% (v/v) methanol using molecular dynamics simulation. Sorbitol was found to stabilize the protein, whereas high-concentrated methanol destabilized it. Sorbitol molecules interacted with the protein through hydrogen bonding and reduced the protein fluctuations as well. At 50% methanol, the flexibility of regions 4-8, 195-201, 314-324, and 332-337 in the MaADI was increased; whereas residues 195-201 showed the highest variations. Thus, these regions of MaADI, especially 195-201, are the most sensitive regions in the presence of denaturing agents and can be subjected to protein engineering toward improving the stability of MaADI.
{"title":"Methanol and sorbitol affect the molecular dynamics of arginine deiminase: insights for improving its stability","authors":"M. Zarei, S. Sabetian, M. Rahbar, M. Negahdaripour","doi":"10.2174/1570164619666220513123509","DOIUrl":"https://doi.org/10.2174/1570164619666220513123509","url":null,"abstract":"\u0000\u0000Arginine deiminase enzyme of Mycoplasma arginini (MaADI) is a potential anti-cancer agent for treating arginine-auxotrophic cancers. Investigating the protein stability in the presence of osmolytes can help to increase protein stability under various stressed conditions.\u0000\u0000\u0000\u0000In this study, the stability and dynamics of MaADI were investigated in pure water and solutions of 1 M sorbitol, 10% (v/v) methanol, and 50% (v/v) methanol using molecular dynamics simulation.\u0000\u0000\u0000\u0000Sorbitol was found to stabilize the protein, whereas high-concentrated methanol destabilized it. Sorbitol molecules interacted with the protein through hydrogen bonding and reduced the protein fluctuations as well. At 50% methanol, the flexibility of regions 4-8, 195-201, 314-324, and 332-337 in the MaADI was increased; whereas residues 195-201 showed the highest variations.\u0000\u0000\u0000\u0000Thus, these regions of MaADI, especially 195-201, are the most sensitive regions in the presence of denaturing agents and can be subjected to protein engineering toward improving the stability of MaADI.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86905155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Spider venom show abundant diversity in both peptides and proteins, which play essential roles in new drug development and agrochemistry. The venoms of Macrothele yani species have strong toxicity on the victims. Objective: The purpose of this study is to comprehensively characterize the profile of venom proteins and peptides of spider Macrothele yani mainly inhabiting in Yunnan province, China. Using a combination of RNA sequencing of the venom glands and venom proteomics based on Liquid Chromatography-Electrospray Ionization-Tandem Mass Spectrometry (LC-ESI-MS/MS), we provide the first overview of the peptides and proteins produced by Macrothele yani. A total of 116 peptide sequences were analyzed, and 43 homologous proteins were matched, of which 38.10% were toxin proteins. High-throughput sequencing by the HiSeq-2000 (Illumina), followed by de novo assembly. As a result, 301,024 similar protein sequences were annotated in the available databases. A total of 68 toxins-related sequences were identified, comparative sequence analyses of these sequences indicated the presence of different types of enzymes and toxin-like genes, including Acetylcholinesterase, Hyaluronidase, cysteine-rich secretory proteins (CRISP), Astacin metalloprotease and other venom components. The venom of spider is a very abundant resources in nature. They were analyzed in order to determine their function in pathophysiology. Molecular templates with potential application value in medical and biological fields were obtained by classifying and characterizing the presumed components about spider venom of Macrothele yani, which laid a foundation for further study of the venom in the future.
{"title":"Proteomics, Peptidomics and Transcriptomic Analysis of the Venom from the Spider Macrothele yani (Mygalomorphae: Macrothelidae)","authors":"X. Gu, Ying Wang, Chenggui Zhang, Xiu-Mei Wu, Huai Xiao, Yinnan Yang, Dasong Yang, Zhi-Bin Yang, Zijin Yang, Yu Zhao","doi":"10.2174/1570164619666220430151150","DOIUrl":"https://doi.org/10.2174/1570164619666220430151150","url":null,"abstract":"\u0000\u0000Spider venom show abundant diversity in both peptides and proteins, which play essential roles in new drug development and agrochemistry. The venoms of Macrothele yani species have strong toxicity on the victims.\u0000Objective: The purpose of this study is to comprehensively characterize the profile of venom proteins and peptides of spider Macrothele yani mainly inhabiting in Yunnan province, China.\u0000\u0000\u0000\u0000Using a combination of RNA sequencing of the venom glands and venom proteomics based on Liquid Chromatography-Electrospray Ionization-Tandem Mass Spectrometry (LC-ESI-MS/MS), we provide the first overview of the peptides and proteins produced by Macrothele yani.\u0000\u0000\u0000\u0000A total of 116 peptide sequences were analyzed, and 43 homologous proteins were matched, of which 38.10% were toxin proteins. High-throughput sequencing by the HiSeq-2000 (Illumina), followed by de novo assembly. As a result, 301,024 similar protein sequences were annotated in the available databases. A total of 68 toxins-related sequences were identified, comparative sequence analyses of these sequences indicated the presence of different types of enzymes and toxin-like genes, including Acetylcholinesterase, Hyaluronidase, cysteine-rich secretory proteins (CRISP), Astacin metalloprotease and other venom components.\u0000\u0000\u0000\u0000The venom of spider is a very abundant resources in nature. They were analyzed in order to determine their function in pathophysiology. Molecular templates with potential application value in medical and biological fields were obtained by classifying and characterizing the presumed components about spider venom of Macrothele yani, which laid a foundation for further study of the venom in the future.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89617330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-29DOI: 10.2174/1570164619666220429121247
N. Singhal, Anjali Garg, Nirpendra Singh, Manish Kumar, M. Goel
Picrophilus torridus is a thermoacidophilic archaeon which thrives in an extremely low pH (0-1) and high temperatures (50-60°C). Thus, it is a suitable organism to study microbial genetics and metabolic adaptations to extreme acidic and moderate thermal environment. In the present study we have conducted a global proteome analysis of P. torridus and discerned the cytosolic proteome of P. torridus using gel-free, liquid chromatography mass spectrometry (LC-MS/MS). The cytosolic proteins of P. torridus were extracted and identified using gel-free, LC-MS/MS. Gene Ontology based pathway analysis and protein-protein interaction studies were performed to understand the role of various cytosolic proteins in sustaining the thermoacidophilic environment. Also, domain analysis of hypothetical/uncharacterized proteins was performed. Using gel-free LC-MS/MS, 408 cytosolic proteins of P. torridus were identified, including 36 hypothetical/uncharacterized proteins. Thus, we could identify 26.58 % of the theoretical proteome of P. torridus. Majority of the cytosolic proteins were observed to be multi-functional and involved in activities related to microbial metabolism. Comparison with an earlier study which used gel-based LC-MS analysis to identify cytosolic proteins of P. torridus revealed that gel-free LC-MS was better in identifying more number of proteins and also, higher/lower molecular weight proteins. The information discerned in this study might add to the knowledge-base of P. torridus proteome and provide a useful basis for further proteomic studies on other thermoacidophilic archaea.
{"title":"Proteomics and Computational Analysis of Cytosolic Proteome of a Thermoacidophilic Euryarchaeon Picrophilus torridus","authors":"N. Singhal, Anjali Garg, Nirpendra Singh, Manish Kumar, M. Goel","doi":"10.2174/1570164619666220429121247","DOIUrl":"https://doi.org/10.2174/1570164619666220429121247","url":null,"abstract":"\u0000\u0000Picrophilus torridus is a thermoacidophilic archaeon which thrives in an extremely low pH (0-1) and high temperatures (50-60°C). Thus, it is a suitable organism to study microbial genetics and metabolic adaptations to extreme acidic and moderate thermal environment.\u0000\u0000\u0000\u0000In the present study we have conducted a global proteome analysis of P. torridus and discerned the cytosolic proteome of P. torridus using gel-free, liquid chromatography mass spectrometry (LC-MS/MS).\u0000\u0000\u0000\u0000The cytosolic proteins of P. torridus were extracted and identified using gel-free, LC-MS/MS. Gene Ontology based pathway analysis and protein-protein interaction studies were performed to understand the role of various cytosolic proteins in sustaining the thermoacidophilic environment. Also, domain analysis of hypothetical/uncharacterized proteins was performed.\u0000\u0000\u0000\u0000Using gel-free LC-MS/MS, 408 cytosolic proteins of P. torridus were identified, including 36 hypothetical/uncharacterized proteins. Thus, we could identify 26.58 % of the theoretical proteome of P. torridus. Majority of the cytosolic proteins were observed to be multi-functional and involved in activities related to microbial metabolism.\u0000\u0000\u0000\u0000Comparison with an earlier study which used gel-based LC-MS analysis to identify cytosolic proteins of P. torridus revealed that gel-free LC-MS was better in identifying more number of proteins and also, higher/lower molecular weight proteins. The information discerned in this study might add to the knowledge-base of P. torridus proteome and provide a useful basis for further proteomic studies on other thermoacidophilic archaea.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81245736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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