scholarly journals 3D-VISUALIZATION OF MACROMOLECULES IN BIOINFORMATICS:

Author(s):  
Михаил Юрьевич Волошин

Биоинформатики часто описывают собственную научную деятельность как практику работы с большими объемами данных с помощью вычислительных устройств. Существенной частью этого самоопределения является создание способов визуального представления результатов такой работы, некоторые из которых направлены на построение удобных репрезентаций данных и демонстрацию закономерностей, присутствующих в них (графики, диаграммы, графы). Другие являются способами визуализации объектов, непосредственно не доступных человеческому восприятию (микрофотография, рентгенограмма). И создание визуализаций, и особенно создание новых компьютерных методов визуализации рассматриваются в биоинформатике как значимые научные достижения. Репрезентации трехмерной структуры белковых молекул занимают особое место в деятельности биоинформатиков. 3D-визуализация макромолекулы, с одной стороны, является, подобно графику, представлением результатов компьютерной обработки массивов данных, полученных материальными методами, – данных о взаимном расположении элементов молекулы. С другой стороны, подобно микрофотографии, такие 3D-структуры должны служить точными отображениями конкретных научных объектов. Это приводит к параллельному существованию двух противоречивых эпистемических режимов: творческий произвол в создании удобных, коммуникативно успешных моделей сочетается с верностью объекту «как он есть на самом деле». Парадокс усиливается тем, что научное исследование репрезентируемых объектов (определение свойств структуры, ее функций, сравнение с другими структурами) посредством компьютеров само по себе вообще не требует визуализации. Ее очевидно высокая ценность для биоинформатики не выглядит оправданной, если иметь в виду значительную искусственность и художественность получаемых изображений. Однако статус этих изображений становится яснее при соотнесении с более ранними представлениями о роли визуального в научном поиске. Высокая оценка визуализации как итогового результата научного исследования была характерна для науки эпохи Возрождения. Художественная репрезентация идеальных существенных свойств вместо строгого соответствия конкретному биологическому объекту – эпистемическая добродетель, типичная для натуралистов XVII–XVIII веков. И то и другое предполагало тесное сотрудничество ученого с художником; и стандарты визуализации макромолекул в биоинформатике вырастают из аналогичного сотрудничества (рисунки Гейса). Стремление же к максимальной точности и детализации наследует регулятиву «механической объективности» (как определяли это Л. Дастон и П. Галисон), для которого важным оказывается и устранение субъекта из процесса производства изображения (в биоинформатике – передача этих функций компьютерным программам). Таким образом, 3D-визуализация белковых структур несет на себе следы исторически разных ценностных ориентиров, но научная практика XX–XXI веков, дополненная компьютерными технологиями, позволяет им сочетаться в конкретных дисциплинарных единствах. Bioinformatics scientists often describe their own scientific activities as the practice of working with large amounts of data using computing devices. An essential part of their self-identification is also the development of ways to visually represent the results of this work. Some of these methods are aimed at building convenient representations of data and demonstrating patterns present in them (graphics, diagrams, graphs). Others are ways of visualizing objects that are not directly accessible to human perception (microphotography, X-ray). Both the construction of visualizations and (especially) the creation of new computer visualization methods are considered in bioinformatics as significant scientific achievements. Representations of the three-dimensional structure of protein molecules play a special role in the inquiries of bioinformatics scientists. 3D-visualization of a macromolecule, on the one hand, is, like a graph, a representation of the results of computer processing of data arrays obtained by material methods – spatiotemporal coordinates of structural elements of the molecule. On the other hand, like microphotography, these 3D structures should serve as accurate representations of specific scientific objects. This leads to the parallel existence of two contradictory epistemic regimes: creative arbitrariness in making convenient, communicatively successful models, is combined with commitment to the object “as it really is”. The paradox is reinforced by the fact that the scientific study of objects in question (determining the properties of the structure, its functions, comparison with other structures) by means of computers does not require visualization at all. Its obviously high value for bioinformatics does not look justified if we take into account the prominent artificiality and artistry of the resulting images. However, the status of these images becomes clearer if we relate them to earlier notions of the role of the visual in scientific discovery. The highest estimation of visualization as the final result of scientific research was characteristic of Renaissance science. The artistic representation of ideal essential properties, instead of a strict correspondence to a particular biological object, is an epistemic virtue typical of the naturalists of the 17th and 18th centuries. Both suggested a close collaboration between the scientist and the artist; and standards for visualizing macromolecules in bioinformatics grow out of a similar collaboration (Geis’ drawings). The desire for maximum accuracy and detail inherits the regulation of “mechanical objectivity” (as Daston and Galison put it into words), for which it is also important to eliminate humans from the image production process (in bioinformatics, to transfer these functions to computer programs). Thus, 3D-visualization of protein structures bears traces of historically different value orientations, but the scientific practice of the 20th and 21st centuries, supplemented by computer technologies, allows them to be intertwined in particular disciplinary units.

2011 ◽  
Vol 366 (1581) ◽  
pp. 3097-3105 ◽  
Author(s):  
Roberta L. Klatzky ◽  
Susan J. Lederman

Enabled by the remarkable dexterity of the human hand, specialized haptic exploration is a hallmark of object perception by touch. Haptic exploration normally takes place in a spatial world that is three-dimensional; nevertheless, stimuli of reduced spatial dimensionality are also used to display spatial information. This paper examines the consequences of full (three-dimensional) versus reduced (two-dimensional) spatial dimensionality for object processing by touch, particularly in comparison with vision. We begin with perceptual recognition of common human-made artefacts, then extend our discussion of spatial dimensionality in touch and vision to include faces, drawing from research on haptic recognition of facial identity and emotional expressions. Faces have often been characterized as constituting a specialized input for human perception. We find that contrary to vision, haptic processing of common objects is impaired by reduced spatial dimensionality, whereas haptic face processing is not. We interpret these results in terms of fundamental differences in object perception across the modalities, particularly the special role of manual exploration in extracting a three-dimensional structure.


2021 ◽  
pp. 88-95
Author(s):  
K.O. Malinina ◽  
◽  
T.A. Blynskaia

Discussed is upon the issue of state management of the socio-economic development of the Arctic zone of the Russian Federation. The special role of the Arctic territories in the economic development of our country is noted. The need is indicated to look at the problems of the Russian Arctic from the other side — from the side of human potential, which is one of the driving forces of the economy. The authors present some of the results of a sociological study conducted by them in the Arctic territories of Russia (in particular, in the Arkhangelsk region). The study is devoted to the intergenerational differentiation of value orientations. Its methodological basis, among others, was formed by the scientific views of R. Inglehart and K. Welzel, who believe that the condition that precedes socio-political and economic modernization is the transformation of the value orientations of the majority of the population. The value system, according to scientists, is quite stable within the life of one generation, and therefore, it makes sense to track changes based on the differences between generations. On the basis of the Theory of Generations, a toolkit was developed that makes it possible to identify the parameters of the value system of residents of the Arctic zone of the Russian Federation (AZRF) belonging to different generations. The main method for collecting empirical data was a semi-structured in-depth interview with representatives of the selected generations.


2021 ◽  
Vol 7 ◽  
Author(s):  
Castrense Savojardo ◽  
Matteo Manfredi ◽  
Pier Luigi Martelli ◽  
Rita Casadio

Solvent accessibility (SASA) is a key feature of proteins for determining their folding and stability. SASA is computed from protein structures with different algorithms, and from protein sequences with machine-learning based approaches trained on solved structures. Here we ask the question as to which extent solvent exposure of residues can be associated to the pathogenicity of the variation. By this, SASA of the wild-type residue acquires a role in the context of functional annotation of protein single-residue variations (SRVs). By mapping variations on a curated database of human protein structures, we found that residues targeted by disease related SRVs are less accessible to solvent than residues involved in polymorphisms. The disease association is not evenly distributed among the different residue types: SRVs targeting glycine, tryptophan, tyrosine, and cysteine are more frequently disease associated than others. For all residues, the proportion of disease related SRVs largely increases when the wild-type residue is buried and decreases when it is exposed. The extent of the increase depends on the residue type. With the aid of an in house developed predictor, based on a deep learning procedure and performing at the state-of-the-art, we are able to confirm the above tendency by analyzing a large data set of residues subjected to variations and occurring in some 12,494 human protein sequences still lacking three-dimensional structure (derived from HUMSAVAR). Our data support the notion that surface accessible area is a distinguished property of residues that undergo variation and that pathogenicity is more frequently associated to the buried property than to the exposed one.


Author(s):  
L. V. Batiev

The predominant interest of S.A. Muromtsev in Roman law and jurisprudence (legal thinking) in the 1870-1880s is due to their special role in the history of law and in the legal system of modern Europe, as well as the science of civil law. His research in this area was not so much historical as theoretical. It was works on Roman law that formed the S.A. Muromtsev’s scientific concept. Based on the analysis of the problem of the conservatism of Roman jurisprudence, S.A. Muromtsev, following R. Iering and contrary to the historical school, comes to the conclusion that the content of law is causally dependent on the needs of civil life and the activity of legal thinking (jurisprudence in the broad sense), formulating new standards in the struggle of ideas and goals. With this approach, along with economic and other factors of the development of society and its needs, to understand the development of law, it is important to study the properties of legal thinking in its historical development. The combination of historical and theoretical approaches to the study of law and legal thinking seems fruitful, but little realized in scientific practice.


Author(s):  
Arun G. Ingale

To predict the structure of protein from a primary amino acid sequence is computationally difficult. An investigation of the methods and algorithms used to predict protein structure and a thorough knowledge of the function and structure of proteins are critical for the advancement of biology and the life sciences as well as the development of better drugs, higher-yield crops, and even synthetic bio-fuels. To that end, this chapter sheds light on the methods used for protein structure prediction. This chapter covers the applications of modeled protein structures and unravels the relationship between pure sequence information and three-dimensional structure, which continues to be one of the greatest challenges in molecular biology. With this resource, it presents an all-encompassing examination of the problems, methods, tools, servers, databases, and applications of protein structure prediction, giving unique insight into the future applications of the modeled protein structures. In this chapter, current protein structure prediction methods are reviewed for a milieu on structure prediction, the prediction of structural fundamentals, tertiary structure prediction, and functional imminent. The basic ideas and advances of these directions are discussed in detail.


Author(s):  
Catherine Lantz ◽  
Paula R Dempsey

Results from focus groups with 23 second- and third-year biology students revealed gradual gains in information literacy (IL) abilities and dispositions needed for them to join the community of scientific practice as laid out in the ACRL Framework for Information Literacy for Higher Education. Students were consumers of information and not yet producers of information. They interacted often with primary research articles but struggled to use research tools effectively; remembered active learning vividly; and relied on video resources, Google, and discussions with peers and instructors to define terms and understand results. Findings support the value of collaboration between librarians and science faculty to incorporate IL skills in the process of scientific discovery.


2019 ◽  
Vol 52 (6) ◽  
pp. 1422-1426
Author(s):  
Rajendran Santhosh ◽  
Namrata Bankoti ◽  
Adgonda Malgonnavar Padmashri ◽  
Daliah Michael ◽  
Jeyaraman Jeyakanthan ◽  
...  

Missing regions in protein crystal structures are those regions that cannot be resolved, mainly owing to poor electron density (if the three-dimensional structure was solved using X-ray crystallography). These missing regions are known to have high B factors and could represent loops with a possibility of being part of an active site of the protein molecule. Thus, they are likely to provide valuable information and play a crucial role in the design of inhibitors and drugs and in protein structure analysis. In view of this, an online database, Missing Regions in Polypeptide Chains (MRPC), has been developed which provides information about the missing regions in protein structures available in the Protein Data Bank. In addition, the new database has an option for users to obtain the above data for non-homologous protein structures (25 and 90%). A user-friendly graphical interface with various options has been incorporated, with a provision to view the three-dimensional structure of the protein along with the missing regions using JSmol. The MRPC database is updated regularly (currently once every three months) and can be accessed freely at the URL http://cluster.physics.iisc.ac.in/mrpc.


Soil Systems ◽  
2020 ◽  
Vol 4 (1) ◽  
pp. 13 ◽  
Author(s):  
Stella Gribbe ◽  
Gesche Blume-Werry ◽  
John Couwenberg

Belowground plant structures are inherently difficult to observe in the field. Sedge peat that mainly consists of partly decayed roots and rhizomes offers a particularly challenging soil matrix to study (live) plant roots. To obtain information on belowground plant morphology, research commonly relies on rhizotrons, excavations, or computerized tomography scans (CT). However, all of these methods have certain limitations. For example, CT scans of peat cores cannot sharply distinguish between plant material and water, and rhizotrons do not provide a 3D structure of the root system. Here, we developed a low-cost approach for 3D visualization of the root system in peat monoliths. Two large diameter (20 cm) peat cores were extracted, frozen and two smaller peat monoliths (47 × 6.5 × 13 cm) were taken from each core. Slices of 0.5 mm or 1 mm were cut from one of the frozen monoliths, respectively, using a paper block cutter and the freshly cut surface of the monolith was photographed after each cut. A 3D model of the fresh (live) roots and rhizomes was reconstructed from the resulting images of the thinner slices based on computerized image analysis, including preprocessing, filtering, segmentation and 3D visualization using the open-source software Fiji, Drishti, and Ilastik. Digital volume measurements on the models produced similar data as manual washing out of roots from the adjacent peat monoliths. The constructed 3D models provide valuable insight into the three-dimensional structure of the root system in the peat matrix.


2018 ◽  
Vol 19 (11) ◽  
pp. 3401 ◽  
Author(s):  
Ashutosh Srivastava ◽  
Tetsuro Nagai ◽  
Arpita Srivastava ◽  
Osamu Miyashita ◽  
Florence Tama

Protein structural biology came a long way since the determination of the first three-dimensional structure of myoglobin about six decades ago. Across this period, X-ray crystallography was the most important experimental method for gaining atomic-resolution insight into protein structures. However, as the role of dynamics gained importance in the function of proteins, the limitations of X-ray crystallography in not being able to capture dynamics came to the forefront. Computational methods proved to be immensely successful in understanding protein dynamics in solution, and they continue to improve in terms of both the scale and the types of systems that can be studied. In this review, we briefly discuss the limitations of X-ray crystallography in studying protein dynamics, and then provide an overview of different computational methods that are instrumental in understanding the dynamics of proteins and biomacromolecular complexes.


2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Shambhu Malleshappa Gowder ◽  
Jhinuk Chatterjee ◽  
Tanusree Chaudhuri ◽  
Kusum Paul

The analysis of protein structures provides plenty of information about the factors governing the folding and stability of proteins, the preferred amino acids in the protein environment, the location of the residues in the interior/surface of a protein and so forth. In general, hydrophobic residues such as Val, Leu, Ile, Phe, and Met tend to be buried in the interior and polar side chains exposed to solvent. The present work depends on sequence as well as structural information of the protein and aims to understand nature of hydrophobic residues on the protein surfaces. It is based on the nonredundant data set of 218 monomeric proteins. Solvent accessibility of each protein was determined using NACCESS software and then obtained the homologous sequences to understand how well solvent exposed and buried hydrophobic residues are evolutionarily conserved and assigned the confidence scores to hydrophobic residues to be buried or solvent exposed based on the information obtained from conservation score and knowledge of flanking regions of hydrophobic residues. In the absence of a three-dimensional structure, the ability to predict surface accessibility of hydrophobic residues directly from the sequence is of great help in choosing the sites of chemical modification or specific mutations and in the studies of protein stability and molecular interactions.


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