WITHDRAWN: A Novel Way of Comparing Protein Sequences Represented Under Physio-Chemical Properties of their Amino Acids

2017 ◽  
Author(s):  
Jayanta Pal ◽  
Soumen Ghosh ◽  
Bansibadan Maji ◽  
Dilip Kumar Bhattacharya
Keyword(s):  
Amino Acids ◽  
Chemical Properties ◽  
Protein Sequences

scholarly journals Sequence Characterization of Glutamate Receptor Genes of Rat a Vertebrate and Arabidopsis Thaliana a Plant

2018 ◽  
Author(s):  
Antara Sengupta ◽  
Pabitra Pal Choudhury ◽  
Subhadip Chakraborty
Keyword(s):  
Amino Acids ◽  
Arabidopsis Thaliana ◽  
Gene Family ◽  
Phylogenetic Trees ◽  
Chemical Properties ◽  
Protein Sequences ◽  
Data Set ◽  
Sequence Characterization ◽  
Conserved Regions ◽  
Long Course

AbstractiGluR gene family of a vertebrate, Rat and AtGLR gene family of a plant, Arabidopsis thaliana [4] perform some common functionalities in neuro-transmission, which have been compared quantitatively. Our attempt is based on the chemical properties of amino acids [6, 7, 8] comprising the primary protein sequences of the aforesaid genes. 19 AtGLR genes of length varying from 808 amino acid (aa) to 1039 aa and 16 iGluR genes length varying from 902aa to 1482 aa have been taken as data sets. Thus, we detected the commonalities (conserved elements) during the long evolution of plants and animals from a common ancestor [4]. Eight different conserved regions have been found based on individual amino acids. Two different conserved regions are also found, which are based on chemical groups of amino acids. We have tried too to find different possible patterns which are common throughout the data set taken. 9 such patterns have been found with size varying from 2 to 5 amino acids at different regions in each primary protein sequences. Phylogenetic trees of AtGLR and iGluR families have also been constructed. This approach is likely to shed light on the long course of evolution.

scholarly journals Chemical characterizations of Neurotransmission Receptors of human and plant to unfold the evolutionary relationships among them

2021 ◽  
Author(s):  
ANTARA SENGUPTA ◽  
SUBHADIP CHAKRABORTY ◽  
PABITRA PAL CHOUDHURY
Keyword(s):  
Amino Acids ◽  
Nervous System ◽  
Comparative Study ◽  
Phylogenetic Trees ◽  
Chemical Properties ◽  
Protein Sequences ◽  
Close Relation ◽  
Receptor Protein ◽  
Evolutionary Relationships ◽  
Numerical Representation

Abstract Vertebrates have very well defined nervous system. It is established that plant also has an alternative sort of sensitive nervous system. Researchers find a close relationship of the neurotransmission mechanism of animal with the plant and suspects close relation in amino acid transport mechanism among both the organisms. Along with the abilities of determining protein structure and various functions, the chemical properties of amino acids also have great contribution in molecular evolution. Hence, in this present work it is aimed at making comparative study on the distribution of amino acids in the neurotransmission receptors associated to animals and plants, based on the chemical properties the amino acids contain. It is possible to classify 20 amino acids into 8 chemical groups and are identified by specific numeric value. The common pattern finding procedure in numerical representation of protein sequences find some conserved regions in the receptor protein sequences of both the species. The comparative study has been made on distributions of chemical properties in protein sequences of ionotropic glutamate receptor protein sequences and GABA receptor protein sequences of two species namely human, a vertebrate and Arabidopsis thaliana, a plant. Experiments have been carried out to calculate proximity between protein sequences based on the distribution of each chemical group (in percentage) in them and phylogenetic trees have been constructed to find evolutionary relationships of neurotransmission receptors of both the spices.

ADAPTIVE CAPACITY OF EINKORN HUSKLESS IN THE SECOND, THIRD AND SEVENTH RUSSIAN FEDERATION REGIONS

1970 ◽  
pp. 34-38
Author(s):  
S. K. Temirbekova ◽  
M. Sh. Begeulov ◽  
Yu. V. Afanaseva ◽  
I. M. Kulikov ◽  
N. E. Ionova
Keyword(s):  
Amino Acids ◽  
Biochemical Analysis ◽  
Chemical Properties ◽  
First Grade ◽  
Essential Amino Acids ◽  
Wheat Grain ◽  
Volume Yield ◽  
Class 1 ◽  
Group B ◽  
Field And Laboratory Conditions

Biochemical, immunological and physico-chemical properties of an ancient wheat grain – hulless spelt cultivar Gremme are investigated. Biochemical analysis of grain revealed a high content of protein, fiber, macro-and microelements, a rich composition of essential amino acids, which is characteristic of ancient wheat species. Evaluated milling and baking properties of spelt flour. Physical and chemical parameters of spelt grain met the requirements for soft wheat grain class 1: the mass fraction of gluten-38.7 %, the nature of the grain-795 g / l, the number of drops-416 C, the total vitreousness-70 %. However, gluten had an increased stickiness, which is obviously due to the increased content of fiber and gliadin fraction. Grinding of spelt grain was carried out on the aggregate mill installation "Miller 100 Lux" to obtain baking flour of various cultivars. The overall yield of flour of the first grinding was 59.7 %. The highest volume yield (359 cm3) and the best organoleptic properties (total baking score – 3.6 points) were observed in a sample of bread baked from spelt flour that meets the requirements for wheat baking flour of the first grade. Studies have confirmed the possibility of using flour produced from the spelt grain of the Gremme variety for the production of bakery products of increased biological, therapeutic and prophylactic, nutritional value and with a high organoleptic rating. Cereals and flour are very rich in trace elements-manganese, selenium, zinc, potassium, iron, phosphorus, vitamins from group B and B, essential amino acids (biochemical analysis was carried out by the Cherkizovo Center). The cultivar is resistant to drought, heat, excessive moisture. Proved immunological properties to several diseases in the field and laboratory conditions-resistant to enzyme-mycotic seed depletion (EMIS), various types of rust, powdery mildew.

A Study on Host Tropism Determinants of Influenza Virus Using Machine Learning

2020 ◽  
Vol 15 (2) ◽  
pp. 121-134 ◽  
Author(s):  
Eunmi Kwon ◽  
Myeongji Cho ◽  
Hayeon Kim ◽  
Hyeon S. Son
Keyword(s):  
Machine Learning ◽  
Amino Acids ◽  
Influenza Virus ◽  
Random Forest ◽  
Physicochemical Properties ◽  
Protein Sequences ◽  
Influenza Viruses ◽  
Host Tropism ◽  
Post Hoc ◽  
Ha Protein

Background: The host tropism determinants of influenza virus, which cause changes in the host range and increase the likelihood of interaction with specific hosts, are critical for understanding the infection and propagation of the virus in diverse host species. Methods: Six types of protein sequences of influenza viral strains isolated from three classes of hosts (avian, human, and swine) were obtained. Random forest, naïve Bayes classification, and knearest neighbor algorithms were used for host classification. The Java language was used for sequence analysis programming and identifying host-specific position markers. Results: A machine learning technique was explored to derive the physicochemical properties of amino acids used in host classification and prediction. HA protein was found to play the most important role in determining host tropism of the influenza virus, and the random forest method yielded the highest accuracy in host prediction. Conserved amino acids that exhibited host-specific differences were also selected and verified, and they were found to be useful position markers for host classification. Finally, ANOVA analysis and post-hoc testing revealed that the physicochemical properties of amino acids, comprising protein sequences combined with position markers, differed significantly among hosts. Conclusion: The host tropism determinants and position markers described in this study can be used in related research to classify, identify, and predict the hosts of influenza viruses that are currently susceptible or likely to be infected in the future.

scholarly journals Synthesis, Characterization and Evaluation of Peptide Nanostructures for Biomedical Applications

Molecules ◽  
2021 ◽  
Vol 26 (15) ◽  
pp. 4587
Author(s):  
Fanny d’Orlyé ◽  
Laura Trapiella-Alfonso ◽  
Camille Lescot ◽  
Marie Pinvidic ◽  
Bich-Thuy Doan ◽  
...  
Keyword(s):  
Amino Acids ◽  
Biomedical Applications ◽  
Chemical Reactivity ◽  
Physical Stability ◽  
Chemical Properties ◽  
Building Blocks ◽  
Imaging Probes ◽  
Therapeutic Molecules

There is a challenging need for the development of new alternative nanostructures that can allow the coupling and/or encapsulation of therapeutic/diagnostic molecules while reducing their toxicity and improving their circulation and in-vivo targeting. Among the new materials using natural building blocks, peptides have attracted significant interest because of their simple structure, relative chemical and physical stability, diversity of sequences and forms, their easy functionalization with (bio)molecules and the possibility of synthesizing them in large quantities. A number of them have the ability to self-assemble into nanotubes, -spheres, -vesicles or -rods under mild conditions, which opens up new applications in biology and nanomedicine due to their intrinsic biocompatibility and biodegradability as well as their surface chemical reactivity via amino- and carboxyl groups. In order to obtain nanostructures suitable for biomedical applications, the structure, size, shape and surface chemistry of these nanoplatforms must be optimized. These properties depend directly on the nature and sequence of the amino acids that constitute them. It is therefore essential to control the order in which the amino acids are introduced during the synthesis of short peptide chains and to evaluate their in-vitro and in-vivo physico-chemical properties before testing them for biomedical applications. This review therefore focuses on the synthesis, functionalization and characterization of peptide sequences that can self-assemble to form nanostructures. The synthesis in batch or with new continuous flow and microflow techniques will be described and compared in terms of amino acids sequence, purification processes, functionalization or encapsulation of targeting ligands, imaging probes as well as therapeutic molecules. Their chemical and biological characterization will be presented to evaluate their purity, toxicity, biocompatibility and biodistribution, and some therapeutic properties in vitro and in vivo. Finally, their main applications in the biomedical field will be presented so as to highlight their importance and advantages over classical nanostructures.

scholarly journals Determinants of adenine-mutagenesis in diversity-generating retroelements

2020 ◽  
Author(s):  
Sumit Handa ◽  
Andres Reyna ◽  
Timothy Wiryaman ◽  
Partho Ghosh
Keyword(s):  
Amino Acids ◽  
Dark Matter ◽  
Reverse Transcription ◽  
Genetic Information ◽  
Human Microbiome ◽  
Protein Sequences ◽  
Catalytic Efficiency ◽  
Natural World ◽  
In Vitro System

Abstract Diversity-generating retroelements (DGRs) vary protein sequences to the greatest extent known in the natural world. These elements are encoded by constituents of the human microbiome and the microbial ‘dark matter’. Variation occurs through adenine-mutagenesis, in which genetic information in RNA is reverse transcribed faithfully to cDNA for all template bases but adenine. We investigated the determinants of adenine-mutagenesis in the prototypical Bordetella bacteriophage DGR through an in vitro system composed of the reverse transcriptase bRT, Avd protein, and a specific RNA. We found that the catalytic efficiency for correct incorporation during reverse transcription by the bRT-Avd complex was strikingly low for all template bases, with the lowest occurring for adenine. Misincorporation across a template adenine was only somewhat lower in efficiency than correct incorporation. We found that the C6, but not the N1 or C2, purine substituent was a key determinant of adenine-mutagenesis. bRT-Avd was insensitive to the C6 amine of adenine but recognized the C6 carbonyl of guanine. We also identified two bRT amino acids predicted to nonspecifically contact incoming dNTPs, R74 and I181, as promoters of adenine-mutagenesis. Our results suggest that the overall low catalytic efficiency of bRT-Avd is intimately tied to its ability to carry out adenine-mutagenesis.

STUDY OF AMINO ACID MODIFIERS IN GUAYULE NATURAL RUBBER

2015 ◽  
Vol 88 (2) ◽  
pp. 310-323 ◽  
Author(s):  
Colleen McMahan ◽  
Dhondup Lhamo
Keyword(s):  
Amino Acids ◽  
Natural Rubber ◽  
Oxidative Stability ◽  
Chemical Properties ◽  
The United States ◽  
Thermal Oxidative Stability ◽  
Green Strength ◽  
Strain Induced Crystallization ◽  
New Perspective ◽  
Physical And Chemical

ABSTRACT Guayule, a desert shrub indigenous to the United States, is under development as a source of natural rubber that can be used in place of petroleum-based rubber or Hevea rubber. In natural rubbers, physical and chemical properties can be strongly affected by nonrubber constituents, typically proteins and lipids, present in the material, depending on the plant species and postharvest processing. Hevea natural rubber typically contains high levels of nonrubber constituents that contribute to thermal-oxidative stability, cure acceleration, and especially strain-induced crystallization. The latter has been attributed to compound properties that render Hevea natural rubber uniquely suited for the most demanding rubber applications (e.g., aircraft tires). Hevea proteins are susceptible to hydrolysis, releasing free amino acids into the latex, which can affect rubber and compound properties. Here, low-protein guayule latex was blended with a series of amino acids varying in chemical structure. Bulk viscosity was reduced, thermal-oxidative stability was improved, and cure rate was influenced by the addition of amino acids. Generally, gel formation, green strength, and tensile strength were not affected. The results introduce a new perspective for amino acids as biobased rubber compound additives and provide insights into naturally occurring nonrubber constituents' interaction with natural rubber polymers.

scholarly journals Deep learning on chaos game representation for proteins

2019 ◽  
Vol 36 (1) ◽  
pp. 272-279 ◽  
Author(s):  
Hannah F Löchel ◽  
Dominic Eger ◽  
Theodor Sperlea ◽  
Dominik Heider
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Chemical Properties ◽  
Protein Sequences ◽  
Machine Learning Techniques ◽  
Supplementary Information ◽  
Support Vector ◽  
Chaos Game Representation ◽  
Chaos Game ◽  
Game Representation

AbstractMotivationClassification of protein sequences is one big task in bioinformatics and has many applications. Different machine learning methods exist and are applied on these problems, such as support vector machines (SVM), random forests (RF) and neural networks (NN). All of these methods have in common that protein sequences have to be made machine-readable and comparable in the first step, for which different encodings exist. These encodings are typically based on physical or chemical properties of the sequence. However, due to the outstanding performance of deep neural networks (DNN) on image recognition, we used frequency matrix chaos game representation (FCGR) for encoding of protein sequences into images. In this study, we compare the performance of SVMs, RFs and DNNs, trained on FCGR encoded protein sequences. While the original chaos game representation (CGR) has been used mainly for genome sequence encoding and classification, we modified it to work also for protein sequences, resulting in n-flakes representation, an image with several icosagons.ResultsWe could show that all applied machine learning techniques (RF, SVM and DNN) show promising results compared to the state-of-the-art methods on our benchmark datasets, with DNNs outperforming the other methods and that FCGR is a promising new encoding method for protein sequences.Availability and implementationhttps://cran.r-project.org/.Supplementary informationSupplementary data are available at Bioinformatics online.

scholarly journals Folding Rate Optimization Promotes Frustrated Interactions in Entangled Protein Structures

2019 ◽  
Vol 21 (1) ◽  
pp. 213
Author(s):  
Federico Norbiato ◽  
Flavio Seno ◽  
Antonio Trovato ◽  
Marco Baiesi
Keyword(s):  
Amino Acids ◽  
Structural Biology ◽  
Weak Interactions ◽  
Protein Structures ◽  
Protein Sequences ◽  
Control Case ◽  
Folding Rate ◽  
Empirical Observation ◽  
Rate Optimization ◽  
Kinetic Traps

Many native structures of proteins accomodate complex topological motifs such as knots, lassos, and other geometrical entanglements. How proteins can fold quickly even in the presence of such topological obstacles is a debated question in structural biology. Recently, the hypothesis that energetic frustration might be a mechanism to avoid topological frustration has been put forward based on the empirical observation that loops involved in entanglements are stabilized by weak interactions between amino-acids at their extrema. To verify this idea, we use a toy lattice model for the folding of proteins into two almost identical structures, one entangled and one not. As expected, the folding time is longer when random sequences folds into the entangled structure. This holds also under an evolutionary pressure simulated by optimizing the folding time. It turns out that optmized protein sequences in the entangled structure are in fact characterized by frustrated interactions at the closures of entangled loops. This phenomenon is much less enhanced in the control case where the entanglement is not present. Our findings, which are in agreement with experimental observations, corroborate the idea that an evolutionary pressure shapes the folding funnel to avoid topological and kinetic traps.

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