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 ◽  
...  

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.


Author(s):  
MAJOLAGBE O. N. ◽  
AINA D. A. ◽  
OMOMOWO I. O. ◽  
THOMAS A.

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.



2020 ◽  
Vol 2 (2) ◽  
pp. 65-70
Author(s):  
Noer Komari ◽  
Samsul Hadi ◽  
Eko Suhartono

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.



PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255693
Author(s):  
Ryosaku Ota ◽  
Kanako So ◽  
Masahiro Tsuda ◽  
Yuriko Higuchi ◽  
Fumiyoshi Yamashita

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.



Author(s):  
Guilhem Faure ◽  
Agnel Praveen Joseph ◽  
Pierrick Craveur ◽  
Tarun J. Narwani ◽  
Narayanaswamy Srinivasan ◽  
...  

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.



2013 ◽  
Vol 9 (2) ◽  
pp. 58-64
Author(s):  
Jayanti Bandyopadhyay ◽  
Paul F. McGee ◽  
Linda A. Hall

Case description This case illustrates the tax implications of a movie produced in a foreign country that resulted in a loss. Teaching opportunities include the application of tax rules to a Schedule C business loss and a resulting net operating loss (NOL) deduction, the consideration of hobby and passive activity losses, the tax treatment of funds received in a divorce settlement, and how an individual might handle a possible IRS examination. Students are asked to prepare a revised Form 1040 for the movie business loss and the individual NOL deduction based on evidence provided in the case. Sufficient information is provided in the case to identify audit “red flags” in a tax return. Using the tale of an actual movie production in a foreign country and its consequent tax implications can provide an attractive alternative to teaching tax accounting rules that are often considered by students as “dry”.



2021 ◽  
Author(s):  
Ho-min Park ◽  
Yunseol Park ◽  
Joris Vankerschaver ◽  
Arnout Van Messem ◽  
Wesley De Neve ◽  
...  

Protein therapeutics play an important role in controlling the functions and activities of disease-causing proteins in modern medicine. Despite protein therapeutics having several advantages over traditional small-molecule therapeutics, further development has been hindered by drug complexity and delivery issues. However, recent progress in deep learning-based protein structure prediction approaches such as AlphaFold opens new opportunities to exploit the complexity of these macro-biomolecules for highly-specialised design to inhibit, regulate or even manipulate specific disease-causing proteins. Anti-CRISPR proteins are small proteins from bacteriophages that counter-defend against the prokaryotic adaptive immunity of CRISPR-Cas systems. They are unique examples of natural protein therapeutics that have been optimized by the host-parasite evolutionary arms race to inhibit a wide variety of host proteins. Here, we show that these Anti-CRISPR proteins display diverse inhibition mechanisms through accurate structural prediction and functional analysis. We find that these phage-derived proteins are extremely distinct in structure, some of which have no homologues in the current protein structure domain. Furthermore, we find a novel family of Anti-CRISPR proteins which are structurally homologous to the recently-discovered mechanism of manipulating host proteins through enzymatic activity, rather than through direct inference. Using highly accurate structure prediction, we present a wide variety of protein-manipulating strategies of anti-CRISPR proteins for future protein drug design.





Author(s):  
Chendra Hadi Suryanto ◽  
Hiroto Saigo ◽  
Kazuhiro Fukui


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