scholarly journals De novo assembly and functional annotation of blood transcriptome of loggerhead turtle, and in silico characterization of peroxiredoxins and thioredoxins

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12395
Author(s):  
Javier Hernández-Fernández ◽  
Andrés Mauricio Pinzón Velasco ◽  
Ellie Anne López Barrera ◽  
María Del Pilar Rodríguez Becerra ◽  
José Luis Villanueva-Cañas ◽  
...  
Keyword(s):  
In Silico ◽  
Functional Annotation ◽  
Active Sites ◽  
De Novo ◽  
Loggerhead Turtle ◽  
Loggerhead Sea Turtles ◽  
Illumina Hiseq ◽  
Human Proteins ◽  
Amino Acid Mutations ◽  
Blood Transcriptome

The aim of this study was to generate and analyze the atlas of the loggerhead turtle blood transcriptome by RNA-seq, as well as identify and characterize thioredoxin (Tnxs) and peroxiredoxin (Prdxs) antioxidant enzymes of the greatest interest in the control of peroxide levels and other biological functions. The transcriptome of loggerhead turtle was sequenced using the Illumina Hiseq 2000 platform and de novo assembly was performed using the Trinity pipeline. The assembly comprised 515,597 contigs with an N50 of 2,631 bp. Contigs were analyzed with CD-Hit obtaining 374,545 unigenes, of which 165,676 had ORFs encoding putative proteins longer than 100 amino acids. A total of 52,147 (31.5%) of these transcripts had significant homology matches in at least one of the five databases used. From the enrichment of GO terms, 180 proteins with antioxidant activity were identified, among these 28 Prdxs and 50 putative Tnxs. The putative proteins of loggerhead turtles encoded by the genes Prdx1, Prdx3, Prdx5, Prdx6, Txn and Txnip were predicted and characterized in silico. When comparing Prdxs and Txns of loggerhead turtle with homologous human proteins, they showed 18 (9%), 52 (18%) 94 (43%), 36 (16%), 35 (33%) and 74 (19%) amino acid mutations respectively. However, they showed high conservation in active sites and structural motifs (98%), with few specific modifications. Of these, Prdx1, Prdx3, Prdx5, Prdx6, Txn and Txnip presented 0, 25, 18, three, six and two deleterious changes. This study provides a high quality blood transcriptome and functional annotation of loggerhead sea turtles.

scholarly journals An In-Silico Approach for Designing a Potential Antagonistic Molecule Targeting β2-adrenoreceptor Having Therapeutic Significance

2020 ◽  
Vol 10 (2) ◽  
pp. 2063-2069
Keyword(s):  
Drug Discovery ◽  
In Silico ◽  
Active Sites ◽  
De Novo ◽  
Cellular Level ◽  
Ligand Molecule ◽  
Best Fitting ◽  
Β2 Adrenergic Receptor ◽  
External Stimuli ◽  
G Protein Coupled

One of the largest families of membrane proteins, the G protein-coupled receptors (GPCRs) has been a very important target of drug discovery as they are involved in having a regulatory role in a variety of signaling pathways at the cellular level in response to external stimuli. Modern in-silico and crystallographic approaches have further made it easier to peep into their structures. In this study, β2 adrenergic receptor (β2AR) has been targeted, and a new ligand molecule using the de-novo approach has been proposed. Using 1-Amino-3-(2,3-dihydro-1H-indol-4-yloxy)-propan-2-ol, the best fitting binding fragments were established with a significant dissociation constant value of 5-7 nanomolar. The flexibility of specific active sites was also investigated, and it was observed that residues 114 (V), 117 (V), 203 (S), 286 (W), and 289 (F) played a crucial role in accommodating ligand for the best binding. Upon examination of the bioavailability parameters, the ligand var9 exhibited significant inhibitory characteristics having lower toxicity values and high drug likeliness properties. Findings certainly hold significance in terms of targeting GPCRs in getting insight into structure-based drug designing and drug discovery.

scholarly journals De-novo Drug Design, Molecular Docking and In-Silico Molecular Prediction of AChEI Analogues through CADD Approaches as Anti-Alzheimer’s Agents

2020 ◽  
Vol 16 (1) ◽  
pp. 54-72 ◽  
Author(s):  
Surabhi Pandey ◽  
B.K. Singh
Keyword(s):  
Molecular Docking ◽  
Drug Design ◽  
Inhibitory Activity ◽  
In Silico ◽  
Active Sites ◽  
De Novo ◽  
Docking Studies ◽  
Target Protein ◽  
Design And Development ◽  
Reference Drug

Background: There are over 44 million persons who suffer with Alzheimer’s disease (AD) worldwide, no existence of cure and only symptomatic treatments are available for it. The aim of this study is to evaluate the anti-Alzheimer potential of designed AChEI analogues using computer simulation docking studies. AChEIs are the most potential standards for treatment of AD, because they have proven efficacy. Among all AChEIs donepezil possesses lowest adverse effects, it can treat mildmoderate- severe AD and only once-daily dosing is required. Therefore, donepezil is recognized as a significant prototype for design and development of new drug molecule. Methods: In this study the Inhibitory potential of the design compounds on acetylcholinesterase enzyme has been evaluated. Docking studies has been performed which further analyzed by in-silico pharmacokinetic evaluation through pharmacopredicta after that Interaction modes with enzyme active sites were determined. Docking studies revealed that there is a strong interaction between the active sites of AChE enzyme and analyzed compounds. Results: As a result 26 compounds have been indicates better inhibitory activity on AChE enzyme and all the screening parameters have also been satisfied by all 26 compounds. From these 26 compounds, six compounds 17, 18, 24, 30, 36 and 56 are found to be the most potent inhibitors of this series by insilico study through INVENTUS v 1.1 software, having highest bio-affinities i.e. - 8.51, - 7.67, - 8.30, - 7.59, - 8.71 and -7.62 kcal/mol respectively, while the standard or reference drug donepezil had binding affinity of - 6.32 kcal/mol. Conclusion: Computer aided drug design approach has been playing an important role in the design and development of novel anti- AD drugs. With the help of structure based drug design some novel analogues of donepezil have been designed and the molecular docking studies with structure based ADME properties prediction studies is performed for prediction of AChE inhibitory activity. The binding mode of proposed compounds with target protein i.e. AChE has been evaluated and the resulting data from docking studies explains that all of the newly designed analogues had significantly high affinity towards target protein compared to donepezil as a reference ligand.

scholarly journals Characterization of the transcriptome and EST-SSR development in Boea clarkeana, a desiccation-tolerant plant endemic to China

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3422 ◽  
Author(s):  
Ying Wang ◽  
Kun Liu ◽  
De Bi ◽  
Shoubiao Zhou ◽  
Jianwen Shao
Keyword(s):  
Functional Annotation ◽  
De Novo ◽  
Gene Annotation ◽  
Sequence Similarity ◽  
Sequence Information ◽  
Sequencing Data ◽  
Protein Database ◽  
Illumina Hiseq ◽  
Significant Similarity ◽  
Assembly Technology

Background Desiccation-tolerant (DT) plants can recover full metabolic competence upon rehydration after losing most of their cellular water (>95%) for extended periods of time. Functional genomic approaches such as transcriptome sequencing can help us understand how DT plants survive and respond to dehydration, which has great significance for plant biology and improving the drought tolerance of crops. Boea clarkeana Hemsl. (Gesneriaceae) is a DT dicotyledonous herb. Its genomic sequences characteristics remain unknown. Based on transcriptomic analyses, polymorphic EST-SSR (simple sequence repeats in expressed sequence tags) molecular primers can be designed, which will greatly facilitate further investigations of the population genetics and demographic histories of DT plants. Methods In the present study, we used the platform Illumina HiSeq™2000 and de novo assembly technology to obtain leaf transcriptomes of B. clarkeana and conducted a BLASTX alignment of the sequencing data and protein databases for sequence classification and annotation. Then, based on the sequence information, the EST-SSR markers were developed, and the functional annotation of ESTs containing polymorphic SSRs were obtained through BLASTX. Results A total of 91,449 unigenes were generated from the leaf cDNA library of B. clarkeana. Based on a sequence similarity search with a known protein database, 72,087 unigenes were annotated. Among the annotated unigenes, a total of 71,170 unigenes showed significant similarity to the known proteins of 463 popular model species in the Nr database, and 59,962 unigenes and 32,336 unigenes were assigned to Gene Ontology (GO) classifications and Cluster of Orthologous Groups (COG), respectively. In addition, 44,924 unigenes were mapped in 128 KEGG pathways. Furthermore, a total of 7,610 unigenes with 8,563 microsatellites were found. Seventy-four primer pairs were selected from 436 primer pairs designed for polymorphism validation. SSRs with higher polymorphism rates were concentrated on dinucleotides, pentanucleotides and hexanucleotides. Finally, 17 pairs with stable, highly polymorphic loci were selected for polymorphism screening. There was a total of 65 alleles, with 2–6 alleles at each locus. Primarily due to the unique biological characteristics of plants, the HE (0–0.196), HO (0.082–0.14) and PIC (0–0.155) per locus were very low. The functional annotation distribution centered on ESTs containing di- and tri-nucleotide SSRs, and the ESTs containing primers BC2, BC4 and BC12 were annotated to vegetative dehydration/desiccation pathways. Discussion This work is the first genetic study of B. clarkeana as a new plant resource of DT genes. A substantial number of transcriptome sequences were generated in this study. These sequences are valuable resources for gene annotation and discovery as well as molecular marker development. These sequences could also provide a valuable basis for future molecular studies of B. clarkeana.

Towards the de novo design of DNA based catalytic sites using a combined NMR and in silico approach

2014 ◽  
Author(s):  
Dieter Buyst ◽  
V. Gheerardijn ◽  
J. Van Den Begin ◽  
A. Madder ◽  
J. C. Martins
Keyword(s):  
In Silico ◽  
De Novo ◽  
De Novo Design ◽  
Catalytic Sites

scholarly journals De Novo Sporophyte Transcriptome Assembly and Functional Annotation in the Endangered Fern Species Vandenboschia speciosa (Willd.) G. Kunkel

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 1017
Author(s):  
Mohammed Bakkali ◽  
Rubén Martín-Blázquez ◽  
Mercedes Ruiz-Estévez ◽  
Manuel A. Garrido-Ramos
Keyword(s):  
Functional Annotation ◽  
Vascular Plants ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Systematic Position ◽  
Important Data ◽  
Ecological Requirements ◽  
Physiological Adaptations ◽  
Fern Species ◽  
Go Terms

We sequenced the sporophyte transcriptome of Killarney fern (Vandenboschia speciosa (Willd.) G. Kunkel). In addition to being a rare endangered Macaronesian-European endemism, this species has a huge genome (10.52 Gb) as well as particular biological features and extreme ecological requirements. These characteristics, together with the systematic position of ferns among vascular plants, make it of high interest for evolutionary, conservation and functional genomics studies. The transcriptome was constructed de novo and contained 36,430 transcripts, of which 17,706 had valid BLAST hits. A total of 19,539 transcripts showed at least one of the 7362 GO terms assigned to the transcriptome, whereas 6547 transcripts showed at least one of the 1359 KEGG assigned terms. A prospective analysis of functional annotation results provided relevant insights on genes involved in important functions such as growth and development as well as physiological adaptations. In this context, a catalogue of genes involved in the genetic control of plant development, during the vegetative to reproductive transition, in stress response as well as genes coding for transcription factors is given. Altogether, this study provides a first step towards understanding the gene expression of a significant fern species and the in silico functional and comparative analyses reported here provide important data and insights for further comparative evolutionary studies in ferns and land plants in general.

scholarly journals Comprehensive Virtual Screening of the Antiviral Potentialities of Marine Polycyclic Guanidine Alkaloids against SARS-CoV-2 (COVID-19)

Biomolecules ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 460
Author(s):  
Amr El-Demerdash ◽  
Ahmed M. Metwaly ◽  
Afnan Hassan ◽  
Tarek Mohamed Abd El-Aziz ◽  
Eslam B. Elkaeed ◽  
...  
Keyword(s):  
In Silico ◽  
Active Sites ◽  
Specific Treatment ◽  
Aqueous Solubility ◽  
Maximum Tolerated Dose ◽  
Binding Energies ◽  
Log P ◽  
Binding Affinities ◽  
Structural Protein ◽  
Guanidine Alkaloids

The huge global expansion of the COVID-19 pandemic caused by the novel SARS-corona virus-2 is an extraordinary public health emergency. The unavailability of specific treatment against SARS-CoV-2 infection necessitates the focus of all scientists in this direction. The reported antiviral activities of guanidine alkaloids encouraged us to run a comprehensive in silico binding affinity of fifteen guanidine alkaloids against five different proteins of SARS-CoV-2, which we investigated. The investigated proteins are COVID-19 main protease (Mpro) (PDB ID: 6lu7), spike glycoprotein (PDB ID: 6VYB), nucleocapsid phosphoprotein (PDB ID: 6VYO), membrane glycoprotein (PDB ID: 6M17), and a non-structural protein (nsp10) (PDB ID: 6W4H). The binding energies for all tested compounds indicated promising binding affinities. A noticeable superiority for the pentacyclic alkaloids particularly, crambescidin 786 (5) and crambescidin 826 (13) has been observed. Compound 5 exhibited very good binding affinities against Mpro (ΔG = −8.05 kcal/mol), nucleocapsid phosphoprotein (ΔG = −6.49 kcal/mol), and nsp10 (ΔG = −9.06 kcal/mol). Compound 13 showed promising binding affinities against Mpro (ΔG = −7.99 kcal/mol), spike glycoproteins (ΔG = −6.95 kcal/mol), and nucleocapsid phosphoprotein (ΔG = −8.01 kcal/mol). Such promising activities might be attributed to the long ω-fatty acid chain, which may play a vital role in binding within the active sites. The correlation of c Log P with free binding energies has been calculated. Furthermore, the SAR of the active compounds has been clarified. The Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) studies were carried out in silico for the 15 compounds; most examined compounds showed optimal to good range levels of ADMET aqueous solubility, intestinal absorption and being unable to pass blood brain barrier (BBB), non-inhibitors of CYP2D6, non-hepatotoxic, and bind plasma protein with a percentage less than 90%. The toxicity of the tested compounds was screened in silico against five models (FDA rodent carcinogenicity, carcinogenic potency TD50, rat maximum tolerated dose, rat oral LD50, and rat chronic lowest observed adverse effect level (LOAEL)). All compounds showed expected low toxicity against the tested models. Molecular dynamic (MD) simulations were also carried out to confirm the stable binding interactions of the most promising compounds, 5 and 13, with their targets. In conclusion, the examined 15 alkaloids specially 5 and 13 showed promising docking, ADMET, toxicity and MD results which open the door for further investigations for them against SARS-CoV-2.

scholarly journals Potential Anticancer Lipoxygenase Inhibitors from the Red Sea-Derived Brown Algae Sargassum cinereum: An In-Silico-Supported In-Vitro Study

Antibiotics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 416
Author(s):  
Sami I. Alzarea ◽  
Abeer H. Elmaidomy ◽  
Hani Saber ◽  
Arafa Musa ◽  
Mohammad M. Al-Sanea ◽  
...  
Keyword(s):  
Red Sea ◽  
Antiproliferative Activity ◽  
Inhibitory Activity ◽  
Brown Algae ◽  
In Silico ◽  
Active Sites ◽  
In Vitro Study ◽  
Lipoxygenase Inhibitors ◽  
Phytochemical Investigation

LC-MS-assisted metabolomic profiling of the Red Sea-derived brown algae Sargassum cinereum “Sargassaceae” dereplicated eleven compounds 1–11. Further phytochemical investigation afforded two new aryl cresol 12–13, along with eight known compounds 14–21. Both new metabolites, along with 19, showed moderate in vitro antiproliferative activity against HepG2, MCF-7, and Caco-2. Pharmacophore-based virtual screening suggested both 5-LOX and 15-LOX as the most probable target linked to their observed antiproliferative activity. The in vitro enzyme assays revealed 12 and 13 were able to inhibit 5-LOX more preferentially than 15-LOX, while 19 showed a convergent inhibitory activity toward both enzymes. Further in-depth in silico investigation revealed the molecular interactions inside both enzymes’ active sites and explained the varying inhibitory activity for 12 and 13 toward 5-LOX and 15-LOX.

scholarly journals Machine learning differentiates enzymatic and non-enzymatic metals in proteins

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ryan Feehan ◽  
Meghan W. Franklin ◽  
Joanna S. G. Slusky
Keyword(s):  
Machine Learning ◽  
Metal Binding ◽  
Binding Sites ◽  
Active Sites ◽  
De Novo ◽  
Enzyme Design ◽  
Metal Binding Sites ◽  
Ensemble Machine Learning ◽  
Machine Learning Model ◽  
Physicochemical Features

AbstractMetalloenzymes are 40% of all enzymes and can perform all seven classes of enzyme reactions. Because of the physicochemical similarities between the active sites of metalloenzymes and inactive metal binding sites, it is challenging to differentiate between them. Yet distinguishing these two classes is critical for the identification of both native and designed enzymes. Because of similarities between catalytic and non-catalytic  metal binding sites, finding physicochemical features that distinguish these two types of metal sites can indicate aspects that are critical to enzyme function. In this work, we develop the largest structural dataset of enzymatic and non-enzymatic metalloprotein sites to date. We then use a decision-tree ensemble machine learning model to classify metals bound to proteins as enzymatic or non-enzymatic with 92.2% precision and 90.1% recall. Our model scores electrostatic and pocket lining features as more important than pocket volume, despite the fact that volume is the most quantitatively different feature between enzyme and non-enzymatic sites. Finally, we find our model has overall better performance in a side-to-side comparison against other methods that differentiate enzymatic from non-enzymatic sequences. We anticipate that our model’s ability to correctly identify which metal sites are responsible for enzymatic activity could enable identification of new enzymatic mechanisms and de novo enzyme design.

scholarly journals Dataset of de novo assembly and functional annotation of the transcriptomes of three native oleaginous microalgae from the Peruvian Amazon

Data in Brief ◽  
2020 ◽  
Vol 31 ◽  
pp. 105917
Author(s):  
Marianela Cobos ◽  
Hicler N. Rodríguez ◽  
Segundo L. Estela ◽  
Carlos G. Castro ◽  
J. Dylan Maddox ◽  
...  
Keyword(s):  
De Novo Assembly ◽  
Functional Annotation ◽  
De Novo ◽  
Peruvian Amazon ◽  
Oleaginous Microalgae
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