scholarly journals Prediction of HIV drug resistance based on the 3D protein structure: Proposal of molecular field mapping

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255693
Author(s):  
Ryosaku Ota ◽  
Kanako So ◽  
Masahiro Tsuda ◽  
Yuriko Higuchi ◽  
Fumiyoshi Yamashita
Keyword(s):  
Drug Resistance ◽  
Protein Structure ◽  
Prediction Models ◽  
3D Structure ◽  
Field Potential ◽  
Amino Acid Sequences ◽  
Molecular Field ◽  
3D Protein Structure ◽  
Hiv Drug Resistance ◽  
Field Mapping

A method for predicting HIV drug resistance by using genotypes would greatly assist in selecting appropriate combinations of antiviral drugs. Models reported previously have had two major problems: lack of information on the 3D protein structure and processing of incomplete sequencing data in the modeling procedure. We propose obtaining the 3D structural information of viral proteins by using homology modeling and molecular field mapping, instead of just their primary amino acid sequences. The molecular field potential parameters reflect the physicochemical characteristics associated with the 3D structure of the proteins. We also introduce the Bayesian conditional mutual information theory to estimate the probabilities of occurrence of all possible protein candidates from an incomplete sequencing sample. This approach allows for the effective use of uncertain information for the modeling process. We applied these data analysis techniques to the HIV-1 protease inhibitor dataset and developed drug resistance prediction models with reasonable performance.

3D protein structure from genetic epistasis experiments

2018 ◽  
Author(s):  
Nathan J. Rollins ◽  
Kelly P. Brock ◽  
Frank J. Poelwijk ◽  
Michael A. Stiffler ◽  
Nicholas P. Gauthier ◽  
...  
Keyword(s):  
Protein Structure ◽  
3D Structure ◽  
Helical Conformation ◽  
Systematic Sampling ◽  
Sufficient Information ◽  
Single Mutation ◽  
Phenotypic Effect ◽  
3D Protein Structure ◽  
Small Proteins ◽  
The Individual

SummaryHigh-throughput experimental techniques have made possible the systematic sampling of the single mutation landscape for many proteins, defined as the change in protein fitness as the result of point mutation sequence changes. In a more limited number of cases, and for small proteins only, we also have nearly full coverage of all possible double mutants. By comparing the phenotypic effect of two simultaneous mutations with that of the individual amino acid changes, we can evaluate epistatic effects that reflect non-additive cooperative processes. The observation that epistatic residue pairs often are in contact in the 3D structure led to the hypothesis that a systematic epistatic screen contains sufficient information to identify the 3D fold of a protein. To test this hypothesis, we examined experimental double mutants for evidence of epistasis and identified residue contacts at 86% accuracy, including secondary structure elements and evidence for an alternative all-α-helical conformation. Positively epistatic contacts – corresponding to compensatory mutations, restoring fitness – were the most informative. Folded models generated from top-ranked epistatic pairs, when compared with the known structure, were accurate within 2.4 Å over 53 residues, indicating the possibility that 3D protein folds can be determined experimentally with good accuracy from functional assays of mutant libraries, at least for small proteins. These results suggest a new experimental approach for determining protein structure.

scholarly journals ANTIMICROBIAL POTENTIALS OF SOIL FUNGI METABOLITES, MOLECULAR DYNAMICS AND THEIR 3D PROTEIN STRUCTURAL PREDICTION USING BIOINFORMATICS TOOL

2020 ◽  
pp. 20-26
Author(s):  
MAJOLAGBE O. N. ◽  
AINA D. A. ◽  
OMOMOWO I. O. ◽  
THOMAS A.
Keyword(s):  
Escherichia Coli ◽  
Staphylococcus Aureus ◽  
Protein Structure ◽  
Secondary Metabolites ◽  
Soil Fungi ◽  
3D Structure ◽  
Antimicrobial Activities ◽  
Biological Properties ◽  
3D Protein Structure ◽  
Klebsiella Spp

Objective: To determine the antimicrobial potentials of secondary metabolite of soil fungi and predict their 3D structure and molecular identity. Methods: Pure soil fungi were isolated from soil samples and cultured under submerged fermentation (Smf) for their metabolites using Potato Dextrose Agar and Broth. The secondary metabolites of the isolated fungi were obtained intracellularly after 21 d of incubation in a rotary shaker incubator. The antimicrobial potentials of the metabolites were investigated against four (4) clinical isolates, namely: Staphylococcus aureus, Klebsiella spp, Candida albicans and Escherichia coli. These soil fungi were further characterized to the molecular level and their evolutionary relationships established using bioinformatics tools. Protein structure of each of the fungi isolates was predicted using PHYRE-2. Results: Out of all the soil fungi isolated, the metabolite of Aspergillus aculeatus showed the highest antimicrobial activities against Staphylococcus aureus (23.00±2.34 mm), Escherichia coli (9.00±1.44 mm) and Klebsiella spp (24.00±3.45 mm). The 3D protein structure predicted showed that each of the organisms consists of different amino-acid compositions such as: serine, tyrosine, proline, arginine, glycine, phenylalanine leucine with other notable biological properties. Conclusion: The work revealed that secondary metabolites of the isolated fungi carry an important role in combating infectious agents thereby, providing roadmaps for the biosynthesis of many synthetic and semi-synthetic drugs and bio-products which are environmentally friendly.

scholarly journals Pemodelan Protein dengan Homology Modeling menggunakan SWISS-MODEL

2020 ◽  
Vol 2 (2) ◽  
pp. 65-70
Author(s):  
Noer Komari ◽  
Samsul Hadi ◽  
Eko Suhartono
Keyword(s):  
Protein Structure ◽  
Homology Modeling ◽  
In Silico ◽  
3D Structure ◽  
Three Dimensional ◽  
Structure Model ◽  
3D Protein Structure ◽  
Laboratory Equipment ◽  
Model Visualization ◽  
Structure Of Proteins

The three-dimensional (3D) structure of proteins is necessary to understand the properties and functions of proteins. Determining protein structure by laboratory equipment is quite complicated and expensive. An alternative method to predict the 3D structure of proteins in the in silico method. One of the in silico methods is homology modeling. Homology modeling is done using the SWISS-MODEL server. Proteins that will be modeled in the 3D structure are proteins that do not yet have a structure in the RCSB PDB database. Protein sequences were obtained from the UniProt database with code A0A0B6VWS2. The results showed that there were two models selected, namely model-1 with the PDB code template 1q0e and model-2 with the PDB code template 3gtv. The results of sequence alignment and model visualization show that model-1 and model-2 are identical. The evaluation and assessment of model-1 on the Ramachandran Plot have a Favored area of ??97.36%, a MolProbity score of 0.79, and a QMEAN value is 1.13. Model-1 is a good 3D protein structure model.

scholarly journals Prediction of HIV drug resistance from genotype with encoded three-dimensional protein structure

BMC Genomics ◽  
2014 ◽  
Vol 15 (Suppl 5) ◽  
pp. S1 ◽  
Author(s):  
Xiaxia Yu ◽  
Irene T Weber ◽  
Robert W Harrison
Keyword(s):  
Drug Resistance ◽  
Protein Structure ◽  
Three Dimensional ◽  
Hiv Drug Resistance

scholarly journals iPBAvizu: a PyMOL plugin for an efficient 3D protein structure superimposition approach

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Guilhem Faure ◽  
Agnel Praveen Joseph ◽  
Pierrick Craveur ◽  
Tarun J. Narwani ◽  
Narayanaswamy Srinivasan ◽  
...  
Keyword(s):  
Protein Structure ◽  
Sequence Alignment ◽  
Protein Structures ◽  
3D Structure ◽  
Structural Features ◽  
Substitution Matrix ◽  
Structural Alphabet ◽  
3D Protein Structure ◽  
Alignment Procedure ◽  
Protein Alignments

Abstract Background Protein 3D structure is the support of its function. Comparison of 3D protein structures provides insight on their evolution and their functional specificities and can be done efficiently via protein structure superimposition analysis. Multiple approaches have been developed to perform such task and are often based on structural superimposition deduced from sequence alignment, which does not take into account structural features. Our methodology is based on the use of a Structural Alphabet (SA), i.e. a library of 3D local protein prototypes able to approximate protein backbone. The interest of a SA is to translate into 1D sequences into the 3D structures. Results We used Protein blocks (PB), a widely used SA consisting of 16 prototypes, each representing a conformation of the pentapeptide skeleton defined in terms of dihedral angles. Proteins are described using PB from which we have previously developed a sequence alignment procedure based on dynamic programming with a dedicated PB Substitution Matrix. We improved the procedure with a specific two-step search: (i) very similar regions are selected using very high weights and aligned, and (ii) the alignment is completed (if possible) with less stringent parameters. Our approach, iPBA, has shown to perform better than other available tools in benchmark tests. To facilitate the usage of iPBA, we designed and implemented iPBAvizu, a plugin for PyMOL that allows users to run iPBA in an easy way and analyse protein superimpositions. Conclusions iPBAvizu is an implementation of iPBA within the well-known and widely used PyMOL software. iPBAvizu enables to generate iPBA alignments, create and interactively explore structural superimposition, and assess the quality of the protein alignments.

Genotypic Methods for HIV Drug Resistance Monitoring: The Opportunities and Challenges Faced by China

2019 ◽  
Vol 17 (4) ◽  
pp. 225-239 ◽  
Author(s):  
Lulu Zuo ◽  
Ke Peng ◽  
Yihong Hu ◽  
Qinggang Xu
Keyword(s):  
Drug Resistance ◽  
Virological Suppression ◽  
Testing Methods ◽  
Hiv Drug Resistance ◽  
Advantages And Disadvantages ◽  
Hiv Epidemic ◽  
Routine Surveillance ◽  
The World ◽  
Global Project ◽  
Hiv 1

AIDS is a globalized infectious disease. In 2014, UNAIDS launched a global project of “90-90-90” to end the HIV epidemic by 2030. The second and third 90 require 90% of HIV-1 infected individuals receiving antiretroviral therapy (ART) and durable virological suppression. However, wide use of ART will greatly increase the emergence and spreading of HIV drug resistance and current HIV drug resistance test (DRT) assays in China are seriously lagging behind, hindering to achieve virological suppression. Therefore, recommending an appropriate HIV DRT method is critical for HIV routine surveillance and prevention in China. In this review, we summarized the current existing HIV drug resistance genotypic testing methods around the world and discussed the advantages and disadvantages of these methods.

HIV Drug Resistance Testing in a Resource Limited Setting with High Viral Diversity: The First Twenty Eight Months Experience

2017 ◽  
Vol 15 (4) ◽  
Author(s):  
Elodie Teclaire Ngo-Malabo ◽  
Paul Alain Ngoupo ◽  
Serge Alain Sadeuh-Mba ◽  
Emmanuel Akongnwi ◽  
Robert Banaï ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Resource Limited Setting ◽  
Resistance Testing ◽  
Viral Diversity ◽  
Hiv Drug Resistance ◽  
Drug Resistance Testing ◽  
Resource Limited ◽  
Limited Setting

scholarly journals HIV Drug Resistance Mutations Detection by Next-Generation Sequencing during Antiretroviral Therapy Interruption in China

Pathogens ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 264
Author(s):  
Miaomiao Li ◽  
Shujia Liang ◽  
Chao Zhou ◽  
Min Chen ◽  
Shu Liang ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Next Generation Sequencing ◽  
Antiretroviral Therapy ◽  
Detection Threshold ◽  
Next Generation ◽  
Resistance Mutations ◽  
Hiv Drug Resistance ◽  
Drug Resistance Mutations ◽  
Therapy Interruption ◽  
Generation Sequencing

Patients with antiretroviral therapy interruption have a high risk of virological failure when re-initiating antiretroviral therapy (ART), especially those with HIV drug resistance. Next-generation sequencing may provide close scrutiny on their minority drug resistance variant. A cross-sectional study was conducted in patients with ART interruption in five regions in China in 2016. Through Sanger and next-generation sequencing in parallel, HIV drug resistance was genotyped on their plasma samples. Rates of HIV drug resistance were compared by the McNemar tests. In total, 174 patients were included in this study, with a median 12 (interquartile range (IQR), 6–24) months of ART interruption. Most (86.2%) of them had received efavirenz (EFV)/nevirapine (NVP)-based first-line therapy for a median 16 (IQR, 7–26) months before ART interruption. Sixty-one (35.1%) patients had CRF07_BC HIV-1 strains, 58 (33.3%) CRF08_BC and 35 (20.1%) CRF01_AE. Thirty-four (19.5%) of the 174 patients were detected to harbor HIV drug-resistant variants on Sanger sequencing. Thirty-six (20.7%), 37 (21.3%), 42 (24.1%), 79 (45.4%) and 139 (79.9) patients were identified to have HIV drug resistance by next-generation sequencing at 20% (v.s. Sanger, p = 0.317), 10% (v.s. Sanger, p = 0.180), 5% (v.s. Sanger, p = 0.011), 2% (v.s. Sanger, p < 0.001) and 1% (v.s. Sanger, p < 0.001) of detection thresholds, respectively. K65R was the most common minority mutation, of 95.1% (58/61) and 93.1% (54/58) in CRF07_BC and CRF08_BC, respectively, when compared with 5.7% (2/35) in CRF01_AE (p < 0.001). In 49 patients that followed-up a median 10 months later, HIV drug resistance mutations at >20% frequency such as K103N, M184VI and P225H still existed, but with decreased frequencies. The prevalence of HIV drug resistance in ART interruption was higher than 15% in the survey. Next-generation sequencing was able to detect more minority drug resistance variants than Sanger. There was a sharp increase in minority drug resistance variants when the detection threshold was below 5%.

scholarly journals Factors Influencing HIV Drug Resistance among Pregnant Women in Luanda, Angola: Findings from a Cross-Sectional Study

2021 ◽  
Vol 6 (1) ◽  
pp. 29
Author(s):  
Cruz S. Sebastião ◽  
Joana Morais ◽  
Miguel Brito
Keyword(s):  
Drug Resistance ◽  
Pregnant Women ◽  
Rural Areas ◽  
Cross Sectional Study ◽  
Drug Resistant ◽  
Sectional Study ◽  
Cross Sectional ◽  
Hiv Drug Resistance ◽  
Hiv 1 ◽  
High Educational

The increase in HIV infection and drug-resistant strains is an important public health concern, especially in resource-limited settings. However, the identification of factors related to the propagation of infectious diseases represents a crucial target offering an opportunity to reduce health care costs as well as deepening the focus on preventing infection in high-risk groups. In this study, we investigate the factors related to drug resistance among HIV-infected pregnant women in Luanda, the capital city of Angola. This was a part of a cross-sectional study conducted with 42 HIV-positive pregnant women. A blood sample was collected, and HIV-1 genotyping was carried out using an in-house method. Multivariate analyses were performed to determine the interaction between sociodemographic characteristics and drug resistance. HIV drug resistance was detected in 44.1% of the studied population. High probabilities of drug resistance were observed for HIV-infected pregnant women living in rural areas (AOR: 2.73; 95% CI: 0.50–14.9) with high educational level (AOR: 6.27; 95% CI: 0.77–51.2) and comorbidities (AOR: 5.47; 95% CI: 0.28–106) and infected with a HIV-1 non-B subtype other than subtype C (AOR: 1.60; 95% CI: 0.25–10.3). The present study reports high HIV drug resistance. Furthermore, older-age, rural areas, high educational levels, unemployed status, having comorbidities, and HIV-1 subtypes were factors related to drug resistance. These factors impact on drug susceptibility and need to be urgently addressed in order to promote health education campaigns able to prevent the spread of drug-resistant HIV strains in Angola.

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