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1.
BMC Bioinformatics ; 22(1): 357, 2021 Jun 30.
Artigo em Inglês | MEDLINE | ID: mdl-34193046

RESUMO

BACKGROUND: An increasing number of studies have shown that lncRNAs are crucial for the control of hormones and the regulation of various physiological processes in the human body, and deletion mutations in RNA are related to many human diseases. LncRNA- disease association prediction is very useful for understanding pathogenesis, diagnosis, and prevention of diseases, and is helpful for labelling relevant biological information. RESULTS: In this manuscript, we propose a computational model named bidirectional generative adversarial network (BiGAN), which consists of an encoder, a generator, and a discriminator to predict new lncRNA-disease associations. We construct features between lncRNA and disease pairs by utilizing the disease semantic similarity, lncRNA sequence similarity, and Gaussian interaction profile kernel similarities of lncRNAs and diseases. The BiGAN maps the latent features of similarity features to predict unverified association between lncRNAs and diseases. The computational results have proved that the BiGAN performs significantly better than other state-of-the-art approaches in cross-validation. We employed the proposed model to predict candidate lncRNAs for renal cancer and colon cancer. The results are promising. Case studies show that almost 70% of lncRNAs in the top 10 prediction lists are verified by recent biological research. CONCLUSION: The experimental results indicated that our proposed model had an accurate predictive ability for the association of lncRNA-disease pairs.


Assuntos
Neoplasias , RNA Longo não Codificante , Algoritmos , Biologia Computacional , Humanos , Neoplasias/genética , RNA Longo não Codificante/genética , Semântica
2.
BMC Bioinformatics ; 22(1): 358, 2021 Jul 02.
Artigo em Inglês | MEDLINE | ID: mdl-34215183

RESUMO

BACKGROUND: A growing proportion of research has proved that microRNAs (miRNAs) can regulate the function of target genes and have close relations with various diseases. Developing computational methods to exploit more potential miRNA-disease associations can provide clues for further functional research. RESULTS: Inspired by the work of predecessors, we discover that the noise hiding in the data can affect the prediction performance and then propose an anti-noise algorithm (ANMDA) to predict potential miRNA-disease associations. Firstly, we calculate the similarity in miRNAs and diseases to construct features and obtain positive samples according to the Human MicroRNA Disease Database version 2.0 (HMDD v2.0). Then, we apply k-means on the undetected miRNA-disease associations and sample the negative examples equally from the k-cluster. Further, we construct several data subsets through sampling with replacement to feed on the light gradient boosting machine (LightGBM) method. Finally, the voting method is applied to predict potential miRNA-disease relationships. As a result, ANMDA can achieve an area under the receiver operating characteristic curve (AUROC) of 0.9373 ± 0.0005 in five-fold cross-validation, which is superior to several published methods. In addition, we analyze the predicted miRNA-disease associations with high probability and compare them with the data in HMDD v3.0 in the case study. The results show ANMDA is a novel and practical algorithm that can be used to infer potential miRNA-disease associations. CONCLUSION: The results indicate the noise hiding in the data has an obvious impact on predicting potential miRNA-disease associations. We believe ANMDA can achieve better results from this task with more methods used in dealing with the data noise.


Assuntos
MicroRNAs , Algoritmos , Área Sob a Curva , Biologia Computacional , Predisposição Genética para Doença , Humanos , MicroRNAs/metabolismo , Curva ROC
3.
BMC Bioinformatics ; 22(Suppl 7): 106, 2021 Jul 05.
Artigo em Inglês | MEDLINE | ID: mdl-34225648

RESUMO

BACKGROUND: Next-Generation-Sequencing (NGS) enables detection of microorganisms present in biological and other matrices of various origin and nature, allowing not only the identification of known phyla and strains but also the discovery of novel ones. The large amount of metagenomic shotgun data produced by NGS require comprehensive and user-friendly pipelines for data analysis, that speed up the bioinformatics steps, relieving the users from the need to manually perform complex and time-consuming tasks. RESULTS: We describe here HOME-BIO (sHOtgun MEtagenomic analysis of BIOlogical entities), an exhaustive pipeline for metagenomics data analysis, comprising three independent analytical modules designed for an inclusive analysis of large NGS datasets. CONCLUSIONS: HOME-BIO is a powerful and easy-to-use tool that can be run also by users with limited computational expertise. It allows in-depth analyses by removing low-complexity/ problematic reads, integrating the analytical steps that lead to a comprehensive taxonomy profile of each sample by querying different source databases, and it is customizable according to specific users' needs.


Assuntos
Análise de Dados , Metagenômica , Biologia Computacional , Sequenciamento de Nucleotídeos em Larga Escala , Metagenoma , Software
4.
BMC Genomics ; 22(1): 501, 2021 Jul 03.
Artigo em Inglês | MEDLINE | ID: mdl-34217223

RESUMO

BACKGROUND: Improving feed efficiency (FE) is an important goal due to its economic and environmental significance for farm animal production. The FE phenotype is complex and based on the measurements of the individual feed consumption and average daily gain during a test period, which is costly and time-consuming. The identification of reliable predictors of FE is a strategy to reduce phenotyping efforts. RESULTS: Gene expression data of the whole blood from three independent experiments were combined and analyzed by machine learning algorithms to propose molecular biomarkers of FE traits in growing pigs. These datasets included Large White pigs from two lines divergently selected for residual feed intake (RFI), a measure of net FE, and in which individual feed conversion ratio (FCR) and blood microarray data were available. Merging the three datasets allowed considering FCR values (Mean = 2.85; Min = 1.92; Max = 5.00) for a total of n = 148 pigs, with a large range of body weight (15 to 115 kg) and different test period duration (2 to 9 weeks). Random forest (RF) and gradient tree boosting (GTB) were applied on the whole blood transcripts (26,687 annotated molecular probes) to identify the most important variables for binary classification on RFI groups and a quantitative prediction of FCR, respectively. The dataset was split into learning (n = 74) and validation sets (n = 74). With iterative steps for variable selection, about three hundred's (328 to 391) molecular probes participating in various biological pathways, were identified as important predictors of RFI or FCR. With the GTB algorithm, simpler models were proposed combining 34 expressed unique genes to classify pigs into RFI groups (100% of success), and 25 expressed unique genes to predict FCR values (R2 = 0.80, RMSE = 8%). The accuracy performance of RF models was slightly lower in classification and markedly lower in regression. CONCLUSION: From small subsets of genes expressed in the whole blood, it is possible to predict the binary class and the individual value of feed efficiency. These predictive models offer good perspectives to identify animals with higher feed efficiency in precision farming applications.


Assuntos
Ração Animal , Transcriptoma , Ração Animal/análise , Animais , Biomarcadores , Biologia Computacional , Ingestão de Alimentos , Fenótipo , Suínos
5.
Comput Math Methods Med ; 2021: 5528144, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34194535

RESUMO

Pneumonia is an infamous life-threatening lung bacterial or viral infection. The latest viral infection endangering the lives of many people worldwide is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19. This paper is aimed at detecting and differentiating viral pneumonia and COVID-19 disease using digital X-ray images. The current practices include tedious conventional processes that solely rely on the radiologist or medical consultant's technical expertise that are limited, time-consuming, inefficient, and outdated. The implementation is easily prone to human errors of being misdiagnosed. The development of deep learning and technology improvement allows medical scientists and researchers to venture into various neural networks and algorithms to develop applications, tools, and instruments that can further support medical radiologists. This paper presents an overview of deep learning techniques made in the chest radiography on COVID-19 and pneumonia cases.


Assuntos
Teste para COVID-19/métodos , COVID-19/diagnóstico por imagem , Aprendizado Profundo , SARS-CoV-2 , Algoritmos , COVID-19/diagnóstico , Teste para COVID-19/estatística & dados numéricos , Biologia Computacional , Diagnóstico Diferencial , Humanos , Conceitos Matemáticos , Redes Neurais de Computação , Pneumonia Viral/diagnóstico , Pneumonia Viral/diagnóstico por imagem , Radiografia Torácica/estatística & dados numéricos , Tomografia Computadorizada por Raios X/estatística & dados numéricos
6.
Xi Bao Yu Fen Zi Mian Yi Xue Za Zhi ; 37(8): 710-715, 2021 Aug.
Artigo em Chinês | MEDLINE | ID: mdl-34236030

RESUMO

Objective To study the bioinformatics characteristics of HSP70 domain proteins derived from pollen of Populus deltoides (P. deltoides), optimize the prokaryotic expression methods, and identify the biological activity of these proteins. Methods Physicochemical characteristics of three kinds of HSP70 domain-containing proteins were analyzed by bioinformatics software. The T/B cell epitopes of these proteins were predicted by Immune Epitope Database and Analysis Resource (IEDB). According to the amino acid sequence provided by Uniprot database, their nucleotide sequences were synthesized and cloned into pET28a(+) plasmid for prokaryotic expression. Protein expression was detected by SDS-PAGE, then the expressed products were purified by nickel column and identified by Western blotting. The protein concentration was measured by protein quantitative kit. Then the three proteins were used as antigens to prepare mouse asthma models, and the concentration of serum total IgE antibody was determined by ELISA. Results The bioinformatics analysis showed that the relative molecular mass (Mr) of B9N9W6, B9GX02 and A0A2K2AYN8 were 71 900, 94 600 and 75 200, respectively. The 13 T-cell epitopes and 14 B-cell epitopes were identified in the three proteins which had high hydrophilia and stability. SDS-PAGE analysis revealed that the genes encoding the three proteins were expressed with three specific bands of approximately Mr 72 000, 95 000 and 75 000, respectively. Western blotting showed the specific bands at the corresponding sites. ELISA showed that the IgE level in the extract group and the A0A2K2AYN8 group were higher than that in the PBS group. Compared with the A0A2K2AYN8 group, the IgE concentration in the B9N9W6 group and B9GX02 group increased significantly. Conclusion The soluble HSP70 domain-containing proteins A0A2K2AYN8, B9GX02 and B9N9W6 derived from pollen of P. deltoides can be expressed as well as purified, and have the biological activity of producing IgE antibodies.


Assuntos
Populus , Alérgenos , Animais , Western Blotting , Biologia Computacional , Epitopos , Camundongos , Pólen/genética , Populus/genética
7.
Molecules ; 26(12)2021 Jun 09.
Artigo em Inglês | MEDLINE | ID: mdl-34207840

RESUMO

Statins have been widely used for the treatment of hypercholesterolemia due to their ability to inhibit HMG-CoA reductase, the rate-limiting enzyme of de novo cholesterol synthesis, via the so-called mevalonate pathway. However, their inhibitory action also causes depletion of downstream intermediates of the pathway, resulting in the pleiotropic effects of statins, including the beneficial impact in the treatment of cancer. In our study, we compared the effect of all eight existing statins on the expression of genes, the products of which are implicated in cancer inhibition and suggested the molecular mechanisms of their action in epigenetic and posttranslational regulation, and in cell-cycle arrest, death, migration, or invasion of the cancer cells.


Assuntos
Antineoplásicos/farmacologia , Biologia Computacional/métodos , Inibidores de Hidroximetilglutaril-CoA Redutases/farmacologia , Ácido Mevalônico/metabolismo , Neoplasias Pancreáticas/tratamento farmacológico , Transcriptoma/efeitos dos fármacos , Morte Celular , Linhagem Celular Tumoral , Movimento Celular , Proliferação de Células , Epigênese Genética , Humanos , Neoplasias Pancreáticas/genética , Neoplasias Pancreáticas/metabolismo , Neoplasias Pancreáticas/patologia
8.
Molecules ; 26(12)2021 Jun 09.
Artigo em Inglês | MEDLINE | ID: mdl-34207849

RESUMO

The ancient paralogs premelanosome protein (PMEL) and glycoprotein nonmetastatic melanoma protein B (GPNMB) have independently emerged as intriguing disease loci in recent years. Both proteins possess common functional domains and variants that cause a shared spectrum of overlapping phenotypes and disease associations: melanin-based pigmentation, cancer, neurodegenerative disease and glaucoma. Surprisingly, these proteins have yet to be shown to physically or genetically interact within the same cellular pathway. This juxtaposition inspired us to compare and contrast this family across a breadth of species to better understand the divergent evolutionary trajectories of two related, but distinct, genes. In this study, we investigated the evolutionary history of PMEL and GPNMB in clade-representative species and identified TMEM130 as the most ancient paralog of the family. By curating the functional domains in each paralog, we identified many commonalities dating back to the emergence of the gene family in basal metazoans. PMEL and GPNMB have gained functional domains since their divergence from TMEM130, including the core amyloid fragment (CAF) that is critical for the amyloid potential of PMEL. Additionally, the PMEL gene has acquired the enigmatic repeat domain (RPT), composed of a variable number of imperfect tandem repeats; this domain acts in an accessory role to control amyloid formation. Our analyses revealed the vast variability in sequence, length and repeat number in homologous RPT domains between craniates, even within the same taxonomic class. We hope that these analyses inspire further investigation into a gene family that is remarkable from the evolutionary, pathological and cell biology perspectives.


Assuntos
Melanócitos/metabolismo , Glicoproteínas de Membrana/metabolismo , Mutação , Doenças Neurodegenerativas/patologia , Antígeno gp100 de Melanoma/metabolismo , Sequência de Aminoácidos , Proteínas Amiloidogênicas/metabolismo , Animais , Biologia Computacional/métodos , Humanos , Glicoproteínas de Membrana/genética , Doenças Neurodegenerativas/genética , Doenças Neurodegenerativas/metabolismo , Filogenia , Pigmentação , Domínios Proteicos , Homologia de Sequência , Antígeno gp100 de Melanoma/genética
9.
Molecules ; 26(11)2021 Jun 07.
Artigo em Inglês | MEDLINE | ID: mdl-34200462

RESUMO

Gastropods are among the most diverse animals. Gastropod mucus contains several glycoproteins and peptides that vary by species and habitat. Some bioactive peptides from gastropod mucus were identified only in a few species. Therefore, using biochemical, mass spectrometric, and bioinformatics approaches, this study aimed to comprehensively identify putative bioactive peptides from the mucus proteomes of seven commonly found or commercially valuable gastropods. The mucus was collected in triplicate samples, and the proteins were separated by 1D-SDS-PAGE before tryptic digestion and peptide identification by nano LC-MS/MS. The mucus peptides were subsequently compared with R scripts. A total of 2818 different peptides constituting 1634 proteins from the mucus samples were identified, and 1218 of these peptides (43%) were core peptides found in the mucus of all examined species. Clustering and correspondence analyses of 1600 variable peptides showed unique mucous peptide patterns for each species. The high-throughput k-nearest neighbor and random forest-based prediction programs were developed with more than 95% averaged accuracy and could identify 11 functional categories of putative bioactive peptides and 268 peptides (9.5%) with at least five to seven bioactive properties. Antihypertensive, drug-delivering, and antiparasitic peptides were predominant. These peptides provide an understanding of gastropod mucus, and the putative bioactive peptides are expected to be experimentally validated for further medical, pharmaceutical, and cosmetic applications.


Assuntos
Gastrópodes/metabolismo , Muco/metabolismo , Peptídeos/metabolismo , Proteoma/metabolismo , Animais , Cromatografia Líquida/métodos , Biologia Computacional/métodos , Eletroforese em Gel de Poliacrilamida/métodos , Aprendizado de Máquina , Proteômica/métodos , Espectrometria de Massas em Tandem/métodos
10.
Int J Mol Sci ; 22(12)2021 Jun 15.
Artigo em Inglês | MEDLINE | ID: mdl-34203768

RESUMO

Mesembryanthemum crystallinum (common ice plant) is a halophyte species that has adapted to extreme conditions. In this study, we cloned a McHB7 transcription factor gene from the ice plant. The expression of McHB7 was significantly induced by 500 mM NaCl and it reached the peak under salt treatment for 7 days. The McHB7 protein was targeted to the nucleus. McHB7-overexpressing in ice plant leaves through Agrobacterium-mediated transformation led to 25 times more McHB7 transcripts than the non-transformed wild type (WT). After 500 mM NaCl treatment for 7 days, the activities of superoxide dismutase (SOD) and peroxidase (POD) and water content of the transgenic plants were higher than the WT, while malondialdehyde (MDA) was decreased in the transgenic plants. A total of 1082 and 1072 proteins were profiled by proteomics under control and salt treatment, respectively, with 22 and 11 proteins uniquely identified under control and salt stress, respectively. Among the 11 proteins, 7 were increased and 4 were decreased after salt treatment. Most of the proteins whose expression increased in the McHB7 overexpression (OE) ice plants under high salinity were involved in transport regulation, catalytic activities, biosynthesis of secondary metabolites, and response to stimulus. The results demonstrate that the McHB7 transcription factor plays a positive role in improving plant salt tolerance.


Assuntos
Mesembryanthemum/metabolismo , Proteínas de Plantas/metabolismo , Proteômica , Tolerância ao Sal/fisiologia , Sequência de Aminoácidos , Núcleo Celular/efeitos dos fármacos , Núcleo Celular/metabolismo , Biologia Computacional , Regulação da Expressão Gênica de Plantas/efeitos dos fármacos , Ontologia Genética , Mesembryanthemum/efeitos dos fármacos , Mesembryanthemum/genética , Filogenia , Folhas de Planta/efeitos dos fármacos , Folhas de Planta/metabolismo , Proteínas de Plantas/genética , Plantas Geneticamente Modificadas , Transporte Proteico/efeitos dos fármacos , Salinidade , Tolerância ao Sal/efeitos dos fármacos , Tolerância ao Sal/genética , Cloreto de Sódio/farmacologia , Estresse Fisiológico/efeitos dos fármacos , Estresse Fisiológico/genética , Frações Subcelulares/metabolismo , Fatores de Transcrição/metabolismo
11.
Int J Mol Sci ; 22(12)2021 Jun 15.
Artigo em Inglês | MEDLINE | ID: mdl-34203772

RESUMO

Protein-protein interactions (PPIs) are the basis of most biological functions determined by residue-residue interactions (RRIs). Predicting residue pairs responsible for the interaction is crucial for understanding the cause of a disease and drug design. Computational approaches that considered inexpensive and faster solutions for RRI prediction have been widely used to predict protein interfaces for further analysis. This study presents RRI-Meta, an ensemble meta-learning-based method for RRI prediction. Its hierarchical learning structure comprises four base classifiers and one meta-classifier to integrate predictive strengths from different classifiers. It considers multiple feature types, including sequence-, structure-, and neighbor-based features, for characterizing other properties of a residue interaction environment to better distinguish between noninteracting and interacting residues. We conducted the same experiments using the same data as previously reported in the literature to demonstrate RRI-Meta's performance. Experimental results show that RRI-Meta is superior to several current prediction tools. Additionally, to analyze the factors that affect the performance of RRI-Meta, we conducted a comparative case study using different protein complexes.


Assuntos
Algoritmos , Aminoácidos/metabolismo , Biologia Computacional/métodos , Área Sob a Curva , Modelos Moleculares , Curva ROC
12.
Int J Mol Sci ; 22(11)2021 Jun 03.
Artigo em Inglês | MEDLINE | ID: mdl-34205189

RESUMO

The triatomine Rhodnius prolixus is the main vector of Chagas disease in countries such as Colombia and Venezuela, and the first kissing bug whose genome has been sequenced and assembled. In the repetitive genome fraction (repeatome) of this species, the transposable elements represented 19% of R. prolixus genome, being mostly DNA transposon (Class II elements). However, scarce information has been published regarding another important repeated DNA fraction, the satellite DNA (satDNA), or satellitome. Here, we offer, for the first time, extended data about satellite DNA families in the R. prolixus genome using bioinformatics pipeline based on low-coverage sequencing data. The satellitome of R. prolixus represents 8% of the total genome and it is composed by 39 satDNA families, including four satDNA families that are shared with Triatoma infestans, as well as telomeric (TTAGG)n and (GATA)n repeats, also present in the T. infestans genome. Only three of them exceed 1% of the genome. Chromosomal hybridization with these satDNA probes showed dispersed signals over the euchromatin of all chromosomes, both in autosomes and sex chromosomes. Moreover, clustering analysis revealed that most abundant satDNA families configured several superclusters, indicating that R. prolixus satellitome is complex and that the four most abundant satDNA families are composed by different subfamilies. Additionally, transcription of satDNA families was analyzed in different tissues, showing that 33 out of 39 satDNA families are transcribed in four different patterns of expression across samples.


Assuntos
Doença de Chagas/genética , Elementos de DNA Transponíveis/genética , DNA Satélite/genética , Rhodnius/genética , Animais , Doença de Chagas/parasitologia , Doença de Chagas/transmissão , Biologia Computacional , Humanos , Anotação de Sequência Molecular , Rhodnius/parasitologia , Rhodnius/patogenicidade , Triatoma/genética , Triatoma/parasitologia , Sequenciamento Completo do Genoma
13.
Molecules ; 26(12)2021 Jun 16.
Artigo em Inglês | MEDLINE | ID: mdl-34208619

RESUMO

Skin pigment disorders are common cosmetic and medical problems. Many known compounds inhibit the key melanin-producing enzyme, tyrosinase, but their use is limited due to side effects. Natural-derived peptides also display tyrosinase inhibition. Abalone is a good source of peptides, and the abalone proteins have been used widely in pharmaceutical and cosmetic products, but not for melanin inhibition. This study aimed to predict putative tyrosinase inhibitory peptides (TIPs) from abalone, Haliotis diversicolor, using k-nearest neighbor (kNN) and random forest (RF) algorithms. The kNN and RF predictors were trained and tested against 133 peptides with known anti-tyrosinase properties with 97% and 99% accuracy. The kNN predictor suggested 1075 putative TIPs and six TIPs from the RF predictor. Two helical peptides were predicted by both methods and showed possible interaction with the predicted structure of mushroom tyrosinase, similar to those of the known TIPs. These two peptides had arginine and aromatic amino acids, which were common to the known TIPs, suggesting non-competitive inhibition on the tyrosinase. Therefore, the first version of the TIP predictors could suggest a reasonable number of the TIP candidates for further experiments. More experimental data will be important for improving the performance of these predictors, and they can be extended to discover more TIPs from other organisms. The confirmation of TIPs in abalone will be a new commercial opportunity for abalone farmers and industry.


Assuntos
Gastrópodes/metabolismo , Monofenol Mono-Oxigenase/antagonistas & inibidores , Monofenol Mono-Oxigenase/metabolismo , Algoritmos , Animais , Análise por Conglomerados , Biologia Computacional/métodos , Gastrópodes/química , Aprendizado de Máquina , Monofenol Mono-Oxigenase/farmacologia , Peptídeos/farmacologia
14.
Int J Mol Sci ; 22(11)2021 Jun 02.
Artigo em Inglês | MEDLINE | ID: mdl-34199658

RESUMO

Influenza A virus (IAV) causes seasonal epidemics and sporadic pandemics, therefore is an important research subject for scientists around the world. Despite the high variability of its genome, the structure of viral RNA (vRNA) possesses features that remain constant between strains and are biologically important for virus replication. Therefore, conserved structural motifs of vRNA can represent a novel therapeutic target. Here, we focused on the presence of G-rich sequences within the influenza A/California/07/2009(H1N1) genome and their ability to form RNA G-quadruplex structures (G4s). We identified 12 potential quadruplex-forming sequences (PQS) and determined their conservation among the IAV strains using bioinformatics tools. Then we examined the propensity of PQS to fold into G4s by various biophysical methods. Our results revealed that six PQS oligomers could form RNA G-quadruplexes. However, three of them were confirmed to adopt G4 structures by all utilized methods. Moreover, we showed that these PQS motifs are present within segments encoding polymerase complex proteins indicating their possible role in the virus biology.


Assuntos
Quadruplex G , Vírus da Influenza A Subtipo H1N1/genética , Vírus da Influenza A/genética , Influenza Humana/genética , Biologia Computacional , Genoma Viral/efeitos dos fármacos , Genoma Viral/genética , Humanos , Vírus da Influenza A/efeitos dos fármacos , Influenza Humana/patologia , RNA Viral/genética , Replicação Viral/efeitos dos fármacos , Replicação Viral/genética
15.
Int J Mol Sci ; 22(11)2021 Jun 02.
Artigo em Inglês | MEDLINE | ID: mdl-34199677

RESUMO

The new advances in deep learning methods have influenced many aspects of scientific research, including the study of the protein system. The prediction of proteins' 3D structural components is now heavily dependent on machine learning techniques that interpret how protein sequences and their homology govern the inter-residue contacts and structural organization. Especially, methods employing deep neural networks have had a significant impact on recent CASP13 and CASP14 competition. Here, we explore the recent applications of deep learning methods in the protein structure prediction area. We also look at the potential opportunities for deep learning methods to identify unknown protein structures and functions to be discovered and help guide drug-target interactions. Although significant problems still need to be addressed, we expect these techniques in the near future to play crucial roles in protein structural bioinformatics as well as in drug discovery.


Assuntos
Aprendizado Profundo , Aprendizado de Máquina , Conformação Proteica , Software , Sequência de Aminoácidos , Biologia Computacional , Bases de Dados de Proteínas , Evolução Molecular , Humanos , Redes Neurais de Computação , Alinhamento de Sequência/métodos
16.
Int J Mol Sci ; 22(12)2021 Jun 08.
Artigo em Inglês | MEDLINE | ID: mdl-34201152

RESUMO

With advanced technology and its development, bioinformatics is one of the avant-garde fields that has managed to make amazing progress in the pharmaceutical-medical field by modeling the infrastructural dimensions of healthcare and integrating computing tools in drug innovation, facilitating prevention, detection/more accurate diagnosis, and treatment of disorders, while saving time and money. By association, bioinformatics and pharmacovigilance promoted both sample analyzes and interpretation of drug side effects, also focusing on drug discovery and development (DDD), in which systems biology, a personalized approach, and drug repositioning were considered together with translational medicine. The role of bioinformatics has been highlighted in DDD, proteomics, genetics, modeling, miRNA discovery and assessment, and clinical genome sequencing. The authors have collated significant data from the most known online databases and publishers, also narrowing the diversified applications, in order to target four major areas (tetrad): DDD, anti-microbial research, genomic sequencing, and miRNA research and its significance in the management of current pandemic context. Our analysis aims to provide optimal data in the field by stratification of the information related to the published data in key sectors and to capture the attention of researchers interested in bioinformatics, a field that has succeeded in advancing the healthcare paradigm by introducing developing techniques and multiple database platforms, addressed in the manuscript.


Assuntos
Biologia Computacional , Desenvolvimento de Medicamentos , Descoberta de Drogas , MicroRNAs , Técnicas Microbiológicas/métodos , Sequenciamento Completo do Genoma , Animais , COVID-19 , Indústria Farmacêutica , Estudo de Associação Genômica Ampla , Humanos , Farmacovigilância , Saúde Pública , Pesquisa Médica Translacional
17.
Molecules ; 26(12)2021 Jun 21.
Artigo em Inglês | MEDLINE | ID: mdl-34205704

RESUMO

The discovery of drugs capable of inhibiting SARS-CoV-2 is a priority for human beings due to the severity of the global health pandemic caused by COVID-19. To this end, repurposing of FDA-approved drugs such as NSAIDs against COVID-19 can provide therapeutic alternatives that could be utilized as an effective safe treatment for COVID-19. The anti-inflammatory activity of NSAIDs is also advantageous in the treatment of COVID-19, as it was found that SARS-CoV-2 is responsible for provoking inflammatory cytokine storms resulting in lung damage. In this study, 40 FDA-approved NSAIDs were evaluated through molecular docking against the main protease of SARS-CoV-2. Among the tested compounds, sulfinpyrazone 2, indomethacin 3, and auranofin 4 were proposed as potential antagonists of COVID-19 main protease. Molecular dynamics simulations were also carried out for the most promising members of the screened NSAID candidates (2, 3, and 4) to unravel the dynamic properties of NSAIDs at the target receptor. The conducted quantum mechanical study revealed that the hybrid functional B3PW91 provides a good description of the spatial parameters of auranofin 4. Interestingly, a promising structure-activity relationship (SAR) was concluded from our study that could help in the future design of potential SARS-CoV-2 main protease inhibitors with expected anti-inflammatory effects as well. NSAIDs may be used by medicinal chemists as lead compounds for the development of potent SARS-CoV-2 (Mpro) inhibitors. In addition, some NSAIDs can be selectively designated for treatment of inflammation resulting from COVID-19.


Assuntos
Anti-Inflamatórios não Esteroides/química , Anti-Inflamatórios não Esteroides/uso terapêutico , COVID-19/tratamento farmacológico , Reposicionamento de Medicamentos/métodos , Anti-Inflamatórios não Esteroides/metabolismo , Antivirais/química , Antivirais/farmacologia , Auranofina/química , Auranofina/farmacologia , Sítios de Ligação , COVID-19/complicações , Biologia Computacional , Proteases 3C de Coronavírus/antagonistas & inibidores , Proteases 3C de Coronavírus/química , Síndrome da Liberação de Citocina/tratamento farmacológico , Síndrome da Liberação de Citocina/etiologia , Bases de Dados de Compostos Químicos , Humanos , Indometacina/química , Indometacina/farmacologia , Ligantes , Modelos Moleculares , Simulação de Acoplamento Molecular , Simulação de Dinâmica Molecular , Inibidores de Proteases/química , Inibidores de Proteases/farmacologia , Ligação Proteica , SARS-CoV-2/química , SARS-CoV-2/efeitos dos fármacos , Relação Estrutura-Atividade , Sulfimpirazona/química , Sulfimpirazona/farmacologia , Estados Unidos , United States Food and Drug Administration
18.
Molecules ; 26(12)2021 Jun 21.
Artigo em Inglês | MEDLINE | ID: mdl-34205768

RESUMO

Since December 2019, novel coronavirus disease 2019 (COVID-19) pandemic has caused tremendous economic loss and serious health problems worldwide. In this study, we investigated 14 natural compounds isolated from Amphimedon sp. via a molecular docking study, to examine their ability to act as anti-COVID-19 agents. Moreover, the pharmacokinetic properties of the most promising compounds were studied. The docking study showed that virtually screened compounds were effective against the new coronavirus via dual inhibition of SARS-CoV-2 RdRp and the 3CL main protease. In particular, nakinadine B (1), 20-hepacosenoic acid (11) and amphimedoside C (12) were the most promising compounds, as they demonstrated good interactions with the pockets of both enzymes. Based on the analysis of the molecular docking results, compounds 1 and 12 were selected for molecular dynamics simulation studies. Our results showed Amphimedon sp. to be a rich source for anti-COVID-19 metabolites.


Assuntos
Produtos Biológicos/química , Produtos Biológicos/farmacologia , Proteases 3C de Coronavírus/química , Poríferos/química , Poríferos/metabolismo , RNA Polimerase Dependente de RNA/química , SARS-CoV-2/efeitos dos fármacos , Amino Açúcares/química , Amino Açúcares/farmacologia , Animais , Antivirais/química , Antivirais/farmacologia , Sítios de Ligação , Produtos Biológicos/isolamento & purificação , Produtos Biológicos/farmacocinética , COVID-19/tratamento farmacológico , Biologia Computacional , Proteases 3C de Coronavírus/antagonistas & inibidores , Proteases 3C de Coronavírus/metabolismo , Humanos , Ligantes , Modelos Moleculares , Simulação de Acoplamento Molecular , Simulação de Dinâmica Molecular , Inibidores de Proteases/química , Inibidores de Proteases/farmacologia , Piridinas/química , Piridinas/farmacologia , RNA Polimerase Dependente de RNA/antagonistas & inibidores , RNA Polimerase Dependente de RNA/metabolismo , SARS-CoV-2/enzimologia , SARS-CoV-2/metabolismo
19.
BMC Res Notes ; 14(1): 273, 2021 Jul 15.
Artigo em Inglês | MEDLINE | ID: mdl-34266480

RESUMO

OBJECTIVE: Visualisation methods, primarily color-coded representation of sequence data, have been a predominant means of representation of DNA data. Algorithmic conversion of DNA sequence data to sound-sonification-represents an alternative means of representation that uses a different range of human sensory perception. We propose that sonification has value for public engagement with DNA sequence information because it has potential to be entertaining as well as informative. We conduct preliminary work to explore the potential of DNA sequence sonification in public engagement with bioinformatics. We apply a simple sonification technique for DNA, in which each DNA base is represented by a specific note. Additionally, a beat may be added to indicate codon boundaries or for musical effect. We report a brief analysis from public engagement events we conducted that featured this method of sonification. RESULTS: We report on use of DNA sequence sonification at two public events. Sonification has potential in public engagement with bioinformatics, both as a means of data representation and as a means to attract audience to a drop-in stand. We also discuss further directions for research on integration of sonification into bioinformatics public engagement and education.


Assuntos
Biologia Computacional , Som , DNA , Humanos
20.
Pak J Pharm Sci ; 34(1(Supplementary)): 345-352, 2021 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34275860

RESUMO

SARS-CoV-2, a new world coronavirus belonging to class Nidovirales of Coronaviridae family causes COVID-19 infection which is the leading cause of death worldwide. Currently there are no approved drugs and vaccines available for the prevention of COVID-19 infection, although couples of immunizations are being tested in clinical trials. However, the present efforts are focused on computational vaccination technique for evaluating candidates to design multi-epitope-based vaccine against pathogenic mechanism of novel SARS-COV-2. Based on recent published evidence, we recognized spike glycoprotein and envelope small membrane protein are the potential targets to combat the pathogenic mechanism of SARS-CoV-2. Similarly, in the present study we identified epitope of both B and T cell associated with these proteins. Extremely antigenic, conserve, immunogenic and nontoxic epitope of B and T cell of Spike protein are WPWYVWLGFI, SRVKNLNSSEGVPDLLV whereas the CWCARPTCIK and YCCNIVNVSL are associated with envelope small membrane protein were selected as potential candidate for vaccine designing. These epitopes show virtuous interaction with HLAA0201 during molecular docking analysis. Under simulation protocol the predicted vaccine candidates show stability. Collectively, this work provides novel potential candidates for epitope-based vaccine designing against COVID-19 infection.


Assuntos
Vacinas contra COVID-19/imunologia , Epitopos de Linfócito B/imunologia , Epitopos de Linfócito T/imunologia , Biologia Computacional/métodos , Epitopos de Linfócito B/química , Epitopos de Linfócito T/química , Antígeno HLA-A2/química , Antígeno HLA-A2/imunologia , Humanos , Imunogenicidade da Vacina , Modelos Moleculares , Simulação de Acoplamento Molecular , SARS-CoV-2/química , Termodinâmica , Proteínas Virais/imunologia
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