scholarly journals The influence of new SARS-CoV-2 variant Omicron (B.1.1.529) on vaccine efficacy, its correlation to Delta Variants: a computational approach

2021 ◽  
Author(s):  
Prashant Ranjan ◽  
Neha ◽  
Chandra Devi ◽  
Kaviyapriya Arulmozhi Devar ◽  
Parimal Das
Keyword(s):  
Binding Affinity ◽  
Immune Evasion ◽  
Structure Prediction ◽  
Structural Modification ◽  
Md Simulation ◽  
Secondary Structure Prediction ◽  
Wild Type ◽  
Human Monoclonal Antibodies ◽  
Neutralising Antibodies ◽  
Docking Analysis

The newly discovered COVID variant B.1.1.529 in Botswana has more than 30 mutations in spike and many other in non-spike proteins, far more than any other SARS-CoV-2 variant accepted as a variant of concern by the WHO and officially named Omicron, and has sparked concern among scientists and the general public. Our findings provide insights into structural modification caused by the mutations in the Omicrons receptor-binding domain and look into the effects on interaction with the hosts neutralising antibodies CR3022, B38, CB6, P2B-2F6, and REGN, as well as ACE2R using an in silico approach. We have employed secondary structure prediction, structural superimposition, protein disorderness, molecular docking, and MD simulation to investigate host-pathogen interactions, immune evasion, and transmissibility caused by mutations in the RBD region of the spike protein of the Omicron variant and compared it to the Delta variants (AY.1, AY.2, & AY.3) and wild type. Computational analysis revealed that the Omicron variant has a higher binding affinity for the human ACE2 receptor than the wild and Delta (AY.1 and AY.2 strains), but lower than the Delta AY.3 strain. MD simulation and docking analysis suggest that the omicron and Delta AY.3 were found to have relatively unstable and compact RBD structures and hampered interactions with antibodies more than wild and Delta (AY.1 and AY.2), which may lead to relatively more pathogenicity and antibody escape. In addition, we observed lower binding affinity of Omicron for human monoclonal antibodies (CR3022, B38, CB6, and P2B2F6) when compared to wild and Delta (AY.1 & AY.2). However, the binding affinity of Omicron RBD variants for CR3022, B38, and P2B2F6 antibodies is lower as compared to Delta AY.3, which might promote immune evasion and reinfection and needs further experimental investigation.

scholarly journals Helical conformation of the AD1 peptide in the AML1-ETO–E-protein complex

2009 ◽  
Vol 23 (3-4) ◽  
pp. 123-129
Author(s):  
Horea Porumb
Keyword(s):  
Synthetic Peptides ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Transcription Activation ◽  
Helical Conformation ◽  
Wild Type ◽  
E Proteins ◽  
E Protein ◽  
Structural Details ◽  
Acute Myeloid

The AML1-ETO fusion protein is responsible for 15% of the acute myeloid leukaemias due to its interference with transcription activation by E-proteins. The eTAFH region of the AML1-ETO competes for the AD1 domain of E-protein, thereby preventing wild-type transcription activation. The structural details concerning the eTAFH–bound AD1 domain are not known. We have previously shown that the eTAFH–AD1 interaction is strong (Kd=28 nM, H. Porumb,Spectroscopy22 (2008), 251–260). The secondary structure prediction algorithms are undecided as to the conformation of bound AD1 peptide. Here we demonstrate by circular dichroism that the bound AD1 peptide is fully helical. This will facilitate modeling of the interaction and launches a challenge as to using synthetic peptides to out compete the eTAFH–E-protein interaction.

scholarly journals Homology modeling of actin protein in Leishmania donovani and in silico prediction of active drugs

2020 ◽  
Vol 2 ◽  
pp. 52-57
Author(s):  
Dimpal Rani Bansal ◽  
Hanumanthrao Chandershekar Patil ◽  
Rajesh Kumari Patil
Keyword(s):  
Homology Modeling ◽  
Binding Affinity ◽  
In Silico ◽  
Structure Prediction ◽  
Leishmania Donovani ◽  
Secondary Structure Prediction ◽  
3D Structure ◽  
Data Bank ◽  
Discovery Studio ◽  
Actin Protein

Objectives: Leishmaniasis is a disease caused by leishmania parasite which is genus of trypanosome protozoa. Leishmania donovani promastigote inhibits biogenesis of phagolysosome due to the accumulation of periphagosomal F-actin. This inhibition of phagosome maturation gives favorable environment for differentiation of promastigote-to-amastigote and causes disease progression. L. donovani actin (LdACT) has been found to have unconventional biochemical behavior due to the different amino acid region in its sequence suggesting that it must have a three-dimensional (3D) structure different from eukaryotic actins making it a more specific for predication of antileishmanial drugs which is main objective of this study. Material and Methods: For carrying out this study, protein sequence was retrieved from the database SWISSPROT, analyzed by BIOEDIT software followed by primary and secondary structure prediction by PROTPARAM and SOPMA. A 3D structure of same was constructed by homology modeling using the yeast actin-human gelsolin segment 1 complex (protein data bank [PDB] ID:1yag) as a template with the help of Swiss model. The final model obtained was further accessed by PROCHECK and VERIFY 3D software which ensured the reliability of the model. This model of actin protein was further used for screening different chemical compounds with high binding affinity by GOLD and DISCOVERY STUDIO. Results: The results give information about the some inhibitors having highest binding affinity to the actin protein. Conclusion: This study will be useful for the development of pharmacophore models for in silico predication of active drugs as a part of antileishmanial drug therapy.

scholarly journals Isolating SARS-CoV-2 Strains From Countries in the Same Meridian: Genome Evolutionary Analysis

10.2196/25995 ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. e25995
Author(s):  
Emilio Mastriani ◽  
Alexey V Rakov ◽  
Shu-Lin Liu
Keyword(s):  
Secondary Structure ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Protein Structures ◽  
Data Repository ◽  
Evolutionary Analysis ◽  
Wild Type ◽  
Uncharacterized Protein ◽  
Climate Conditions

Background COVID-19, caused by the novel SARS-CoV-2, is considered the most threatening respiratory infection in the world, with over 40 million people infected and over 0.934 million related deaths reported worldwide. It is speculated that epidemiological and clinical features of COVID-19 may differ across countries or continents. Genomic comparison of 48,635 SARS-CoV-2 genomes has shown that the average number of mutations per sample was 7.23, and most SARS-CoV-2 strains belong to one of 3 clades characterized by geographic and genomic specificity: Europe, Asia, and North America. Objective The aim of this study was to compare the genomes of SARS-CoV-2 strains isolated from Italy, Sweden, and Congo, that is, 3 different countries in the same meridian (longitude) but with different climate conditions, and from Brazil (as an outgroup country), to analyze similarities or differences in patterns of possible evolutionary pressure signatures in their genomes. Methods We obtained data from the Global Initiative on Sharing All Influenza Data repository by sampling all genomes available on that date. Using HyPhy, we achieved the recombination analysis by genetic algorithm recombination detection method, trimming, removal of the stop codons, and phylogenetic tree and mixed effects model of evolution analyses. We also performed secondary structure prediction analysis for both sequences (mutated and wild-type) and “disorder” and “transmembrane” analyses of the protein. We analyzed both protein structures with an ab initio approach to predict their ontologies and 3D structures. Results Evolutionary analysis revealed that codon 9628 is under episodic selective pressure for all SARS-CoV-2 strains isolated from the 4 countries, suggesting it is a key site for virus evolution. Codon 9628 encodes the P0DTD3 (Y14_SARS2) uncharacterized protein 14. Further investigation showed that the codon mutation was responsible for helical modification in the secondary structure. The codon was positioned in the more ordered region of the gene (41-59) and near to the area acting as the transmembrane (54-67), suggesting its involvement in the attachment phase of the virus. The predicted protein structures of both wild-type and mutated P0DTD3 confirmed the importance of the codon to define the protein structure. Moreover, ontological analysis of the protein emphasized that the mutation enhances the binding probability. Conclusions Our results suggest that RNA secondary structure may be affected and, consequently, the protein product changes T (threonine) to G (glycine) in position 50 of the protein. This position is located close to the predicted transmembrane region. Mutation analysis revealed that the change from G (glycine) to D (aspartic acid) may confer a new function to the protein—binding activity, which in turn may be responsible for attaching the virus to human eukaryotic cells. These findings can help design in vitro experiments and possibly facilitate a vaccine design and successful antiviral strategies.

Distinct Modulation of Wild-Type and Selective Gene Mutated Vitamin D Receptor by Essential Poly Unsaturated Fatty Acids

2021 ◽  
Vol 21 ◽  
Author(s):  
Hari Balaji ◽  
Selvaraj Ayyamperuma ◽  
Niladri Saha ◽  
Shyam Sundar Pottabathula ◽  
Jubie Selvaraj ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Vitamin D ◽  
Ligand Binding ◽  
Vitamin D Deficiency ◽  
Binding Affinity ◽  
Unsaturated Fatty Acids ◽  
Binding Domain ◽  
Ligand Binding Domain ◽  
Binding Energies ◽  
Wild Type

: Vitamin-D deficiency is a global concern. Gene mutations in the vitamin D receptor’s (VDR) ligand binding domain (LBD) variously alter the ligand binding affinity, heterodimerization with retinoid X receptor (RXR) and inhibit coactivator interactions. These LBD mutations may result in partial or total hormone unresponsiveness. A plethora of evidence report that selective long chain polyunsaturated fatty acids (PUFAs) including eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA) and arachidonic acid (AA) bind to the ligand-binding domain of VDR and lead to transcriptional activation. We therefore hypothesize that selective PUFAs would modulate the dynamics and kinetics of VDRs, irrespective bioactive of vitamin-D binding. The spatial arrangements of the selected PUFAs in VDR active site were examined by in-silico docking studies. The docking results revealed that PUFAs have fatty acid structure-specific binding affinity towards VDR. The calculated EPA, DHA & AA binding energies (Cdocker energy) were lesser compared to vitamin-D in wild type of VDR (PDB id: 2ZLC). Of note, the DHA has higher binding interactions to the mutated VDR (PDB id: 3VT7) when compared to the standard Vitamin-D. Molecular dynamic simulation was utilized to confirm the stability of potential compound binding of DHA with mutated VDR complex. These findings suggest the unique roles of PUFAs in VDR activation and may offer alternate strategy to circumvent vitamin-D deficiency.

A Systematic Review on Popularity, Application and Characteristics of Protein Secondary Structure Prediction Tools

2019 ◽  
Vol 16 (2) ◽  
pp. 159-172 ◽  
Author(s):  
Elaheh Kashani-Amin ◽  
Ozra Tabatabaei-Malazy ◽  
Amirhossein Sakhteman ◽  
Bagher Larijani ◽  
Azadeh Ebrahim-Habibi
Keyword(s):  
Systematic Review ◽  
Secondary Structure ◽  
Structure Prediction ◽  
Web Of Science ◽  
Secondary Structure Prediction ◽  
Structural Information ◽  
Protein Secondary Structure ◽  
Structural Features ◽  
Prediction Tools ◽  
Insight Into

Background: Prediction of proteins’ secondary structure is one of the major steps in the generation of homology models. These models provide structural information which is used to design suitable ligands for potential medicinal targets. However, selecting a proper tool between multiple Secondary Structure Prediction (SSP) options is challenging. The current study is an insight into currently favored methods and tools, within various contexts. Objective: A systematic review was performed for a comprehensive access to recent (2013-2016) studies which used or recommended protein SSP tools. Methods: Three databases, Web of Science, PubMed and Scopus were systematically searched and 99 out of the 209 studies were finally found eligible to extract data. Results: Four categories of applications for 59 retrieved SSP tools were: (I) prediction of structural features of a given sequence, (II) evaluation of a method, (III) providing input for a new SSP method and (IV) integrating an SSP tool as a component for a program. PSIPRED was found to be the most popular tool in all four categories. JPred and tools utilizing PHD (Profile network from HeiDelberg) method occupied second and third places of popularity in categories I and II. JPred was only found in the two first categories, while PHD was present in three fields. Conclusion: This study provides a comprehensive insight into the recent usage of SSP tools which could be helpful for selecting a proper tool.

Sign in / Sign up

Export Citation Format

Share Document