scholarly journals Bone structural similarity score: a multiparametric tool to match properties of biomimetic bone substitutes with their target tissues

2016 ◽  
Vol 14 (3) ◽  
pp. 0-0 ◽  
Author(s):  
Giuseppe Falvo D’Urso Labate ◽  
Francesco Baino ◽  
Mara Terzini ◽  
Alberto Audenino ◽  
Chiara Vitale-Brovarone ◽  
...  
Keyword(s):  
Structural Similarity ◽  
Bone Substitutes ◽  
Similarity Score

Assessing the Prediction Quality of the Anti-SARS-CoV-2 Activity Using the D3Targets-2019-nCoV Web Service

2020 ◽  
Vol 3 (4) ◽  
pp. e00140
Author(s):  
N.S. Ionov ◽  
P.V. Pogodin ◽  
V.V. Poroikov
Keyword(s):  
Molecular Docking ◽  
Web Service ◽  
Scoring Function ◽  
Chemical Compounds ◽  
Structural Similarity ◽  
Similarity Score ◽  
Test Set ◽  
Target Proteins ◽  
Similarity Assessment

The D3Targets-2019-nCoV web service predicting the interaction of chemical compounds with SARS-CoV-2 virus proteins and human proteins involved in the pathogenesis of COVID-19 by structural similarity and molecular docking was evaluated. The quality of the prediction was assessed as a balanced accuracy, which was calculated based on the results of the prediction for the structures of chemical compounds from the test set we compiled. The test set consisted of 35 active and 59 inactive molecules, including compounds with the experimetnaly confirmed absence of activity against the selected targets and compounds active against SARS-CoV-2 targets, not presented in the CoViLigands database. The authors of the analyzed web service did not indicate the thresholds for the values of the similarity score and the docking scoring function, using which it would be possible to reliably divide the compounds into active and inactive with respect to target proteins. Therefore, we assessed the balanced accuracy of the predictive methods D3Targets-2019-nCoV at various thresholds for cutting off active substances from inactive ones. Using our test set it was found that the highest value of balanced accuracy (0.59) was achieved when choosing active molecules based on the results of 2D similarity assessment (cutoff threshold was 46%). Assessment of 3D similarity did not allow achieving balanced accuracy values exceeding 0.5. It is shown that using the 2Dх3D integral similarity assessment recommended by the authors, the maximum value of the balanced accuracy 0.57 was achieved at a threshold of 31%. The calculated balanced accuracy for molecular docking results does not exceed 0.51. On the case study for the tideglusib, it was shown that the values of the scoring function for two target proteins, the activity against which was confirmed in the experiment (3CLpro and GSK3B), do not differ significantly from the values of the scoring function for the remaining 44 targets were not confirmed.

scholarly journals Bioactivity assessment of natural compounds using machine learning models based on drug target similarity

2020 ◽  
Author(s):  
Vinita Periwal ◽  
Stefan Bassler ◽  
Sergej Andrejev ◽  
Natalia Gabrielli ◽  
Athanasios Typas ◽  
...  
Keyword(s):  
Therapeutic Potential ◽  
Structural Diversity ◽  
Structural Similarity ◽  
Natural Compounds ◽  
Similarity Score ◽  
Therapeutic Drugs ◽  
Common Substructure ◽  
Random Forest Models ◽  
Control Compound ◽  
Cox 1

SummaryNatural products constitute a vast yet largely untapped resource of molecules with therapeutic properties. Computational approaches based on structural similarity offer a scalable approach for evaluating their bioactivity potential. However, this remains challenging due to the immense structural diversity of natural compounds and the complexity of structure-activity relationships. We here assess the bioactivity potential of natural compounds using random forest models utilizing structural fingerprints, maximum common substructure, and molecular descriptors. The models are trained with small-molecule drugs for which the corresponding protein targets are known (1,410 drugs, 0.9 million pairs). Using these models, we evaluated circa 11k natural compounds for functional similarity with therapeutic drugs (1.7 million pairs). The resulting natural compound-drug similarity network consists of several links with support from the published literature as well as links suggestive of unexplored bioactivity of natural compounds. As a proof of concept, we experimentally validated the model-predicted Cox-1 inhibitory activity of 5-methoxysalicylic acid, a compound commonly found in tea, herbs and spices. In contrast, a control compound, with the highest similarity score when using the most weighted fingerprint metric, did not inhibit Cox-1. Our results illustrate the importance of complementing structural similarity with the prior data on molecular interactions, and presents a resource for exploring the therapeutic potential of natural compounds.

scholarly journals Spec2Vec: Improved mass spectral similarity scoring through learning of structural relationships

2020 ◽  
Author(s):  
Florian Huber ◽  
Lars Ridder ◽  
Stefan Verhoeven ◽  
Jurriaan H. Spaaks ◽  
Faruk Diblen ◽  
...  
Keyword(s):  
Language Processing ◽  
Structural Similarity ◽  
Similarity Score ◽  
Large Set ◽  
Molecular Networking ◽  
Spectral Similarity ◽  
Mass Spectral ◽  
Structural Relationships ◽  
Large Databases ◽  
Using Data

AbstractSpectral similarity is used as a proxy for structural similarity in many tandem mass spectrometry (MS/MS) based metabolomics analyses such as library matching and molecular networking. Although weaknesses in the relationship between spectral similarity scores and the true structural similarities have been described, little development of alternative scores has been undertaken. Here, we introduce Spec2Vec, a novel spectral similarity score inspired by a natural language processing algorithm -- Word2Vec. Spec2Vec learns fragmental relationships within a large set of spectral data to derive abstract spectral embeddings that can be used to assess spectral similarities. Using data derived from GNPS MS/MS libraries including spectra for nearly 13,000 unique molecules, we show how Spec2Vec scores correlate better with structural similarity than cosine-based scores. We demonstrate the advantages of Spec2Vec in library matching and molecular networking. Spec2Vec is computationally more scalable allowing structural analogue searches in large databases within seconds.

scholarly journals “Evacuate everyone south of that line” Analyzing structural communication patterns during natural disasters

2020 ◽  
Author(s):  
Ema Kušen ◽  
Mark Strembeck
Keyword(s):  
Natural Disasters ◽  
Positive Emotions ◽  
Data Extraction ◽  
Structural Similarity ◽  
Similarity Score ◽  
Emotional Expressions ◽  
Basic Emotions ◽  
Media Messages ◽  
The Social ◽  
Extraction Period

Abstract In this paper, we analyze more than 16 million tweets that have been sent from 6.1 million Twitter accounts and are related to nine natural disasters. As part of our analysis, we identify eight basic emotions conveyed in these tweets. We found that during natural disasters, social media messages at first predominantly express fear, while sadness and positive emotions increase in the immediate aftermath of the event. In this context, positive emotions contribute to the social phenomenon of emotional bonding and are often related to compassion, gratitude, as well as donations for disaster relief. In our analysis, we found that the users’ emotional expressions directly contribute to the emergence of the underlying communication network. In particular, we identified statistically significant structural patterns that we call emotion-exchange motifs and show that: (1) the motifs 021U and 021D are common for the communication of all eight emotions considered in this study, (2) motifs which include bidirectional edges (i.e. online conversations) are generally not characteristic for the communication of surprise, sadness, and disgust, (3) the structural analysis of a set of emotions (rather than a single emotion) leads to the formation of more complex motifs representing more complex social interactions, and (4) the messaging patterns emerging from the communication of joy and sadness show the highest structural similarity, even reaching a perfect similarity score at some point during the data-extraction period.

scholarly journals Objective Numerical Evaluation of Diffuse, Optically Reconstructed Images Using Structural Similarity Index

Biosensors ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 504
Author(s):  
Vicky Mudeng ◽  
Minseok Kim ◽  
Se-woon Choe
Keyword(s):  
Structural Information ◽  
Optical Tomography ◽  
Similarity Index ◽  
Structural Similarity ◽  
Similarity Score ◽  
Human Visual Perception ◽  
Structural Similarity Index ◽  
Non Invasive ◽  
Numerical Assessment ◽  
Sharpness Parameter

Diffuse optical tomography is emerging as a non-invasive optical modality used to evaluate tissue information by obtaining the optical properties’ distribution. Two procedures are performed to produce reconstructed absorption and reduced scattering images, which provide structural information that can be used to locate inclusions within tissues with the assistance of a known light intensity around the boundary. These methods are referred to as a forward problem and an inverse solution. Once the reconstructed image is obtained, a subjective measurement is used as the conventional way to assess the image. Hence, in this study, we developed an algorithm designed to numerically assess reconstructed images to identify inclusions using the structural similarity (SSIM) index. We compared four SSIM algorithms with 168 simulated reconstructed images involving the same inclusion position with different contrast ratios and inclusion sizes. A multiscale, improved SSIM containing a sharpness parameter (MS-ISSIM-S) was proposed to represent the potential evaluation compared with the human visible perception. The results indicated that the proposed MS-ISSIM-S is suitable for human visual perception by demonstrating a reduction of similarity score related to various contrasts with a similar size of inclusion; thus, this metric is promising for the objective numerical assessment of diffuse, optically reconstructed images.

Preparation and Characterization of Calcium Hydroxyphosphate (Hydroxyapatite) from Tilapia Fish Bones and Scales via Calcination Method

2020 ◽  
Vol 1010 ◽  
pp. 596-601
Author(s):  
Nor Hakimin Abdullah ◽  
An'amt Mohamed Noor ◽  
Mohd Sukhairi Mat Rasat ◽  
Sarizam Mamat ◽  
Mazlan Mohamed ◽  
...  
Keyword(s):  
Biomedical Application ◽  
Structural Similarity ◽  
Bone Substitutes ◽  
Proximate Analysis ◽  
Attenuated Total Reflection ◽  
Hydroxyl Group ◽  
Potential Candidate ◽  
Fish Bones ◽  
Hydroxyapatite Powder ◽  
Calcination Method

Calcium hydroxyphosphate (hydroxyapatite) is a calcium phosphate that is widely used in biomedical application. Hydroxyapatite is an excellent component for bone substitutes for their chemical and structural similarity to natural bone component. In this research, hydroxyapatite was synthesized from tilapia fish bones and scales using calcination method with 3 different temperatures namely 1000 °C, 900 °C and 800 °C. The obtained hydroxyapatite powder was characterized using several techniques such as Fourier-Transform infrared spectroscopy Attenuated total reflection (FTIR-ATR), scanning electron microscope (SEM), proximate analysis and X-ray diffraction (XRD). The results indicated that temperature 1000 °C has the highest weight loss with 21.825 g compared to the temperature 800 °C and 900 °C. From FTIR-ATR analysis, the presence of characteristic peaks for hydroxyl group, phosphate groups and water molecule indicated that the powder were hydroxyapatite. SEM results showed that increasing temperature had led to more dense structure. The hydroxyapatite powder were further analysed for their proximate analysis. The results proved that the highest contents of ash, fat, moisture and crude protein were observed at 1000 °C as compared to 900 °C and 800 °C. Based on this study, it revealed that produced pure hydroxyapatite from natural resources could be a potential candidate for food industry as protein enhancer.

scholarly journals Spec2Vec: Improved mass spectral similarity scoring through learning of structural relationships

2021 ◽  
Vol 17 (2) ◽  
pp. e1008724 ◽  
Author(s):  
Florian Huber ◽  
Lars Ridder ◽  
Stefan Verhoeven ◽  
Jurriaan H. Spaaks ◽  
Faruk Diblen ◽  
...  
Keyword(s):  
Language Processing ◽  
Structural Similarity ◽  
Similarity Score ◽  
Large Set ◽  
Molecular Networking ◽  
Spectral Similarity ◽  
Mass Spectral ◽  
Structural Relationships ◽  
Large Databases ◽  
Using Data

Spectral similarity is used as a proxy for structural similarity in many tandem mass spectrometry (MS/MS) based metabolomics analyses such as library matching and molecular networking. Although weaknesses in the relationship between spectral similarity scores and the true structural similarities have been described, little development of alternative scores has been undertaken. Here, we introduce Spec2Vec, a novel spectral similarity score inspired by a natural language processing algorithm—Word2Vec. Spec2Vec learns fragmental relationships within a large set of spectral data to derive abstract spectral embeddings that can be used to assess spectral similarities. Using data derived from GNPS MS/MS libraries including spectra for nearly 13,000 unique molecules, we show how Spec2Vec scores correlate better with structural similarity than cosine-based scores. We demonstrate the advantages of Spec2Vec in library matching and molecular networking. Spec2Vec is computationally more scalable allowing structural analogue searches in large databases within seconds.

Virus-Like Particles in a Human Breast Cancer: Structural Similarity to Previously Reported Particles

1973 ◽  
Vol 31 ◽  
pp. 378-379
Author(s):  
G. Kasnic ◽  
S. E. Stewart ◽  
C. Urbanski
Keyword(s):  
Breast Cancer ◽  
Biological Activity ◽  
Human Breast Cancer ◽  
Osteogenic Sarcoma ◽  
Human Tumor ◽  
Structural Similarity ◽  
Cell Tumor ◽  
Human Breast ◽  
Human Tumor Cell ◽  
Type Particle

We have reported the maturation of an intracisternal A-type particle in murine plasma cell tumor cultures and three human tumor cell cultures (rhabdomyosarcoma, lung adenocarcinoma, and osteogenic sarcoma) after IUDR-DMSO activation. In all of these studies the A-type particle seems to develop into a form with an electron dense nucleoid, presumably mature, which is also intracisternal. A similar intracisternal A-type particle has been described in leukemic guinea pigs. Although no biological activity has yet been demonstrated for these particles, on morphologic grounds, and by the manner in which they develop within the cell, they may represent members of the same family of viruses.

Structural similarity of ribosomes from E. coli and A. salina

1978 ◽  
Vol 36 (2) ◽  
pp. 242-243
Author(s):  
M. Boublik ◽  
R.M. Wydro ◽  
W. Hellmann ◽  
F. Jenkins
Keyword(s):  
Ribosomal Proteins ◽  
Direct Evidence ◽  
Structural Similarity ◽  
Carbon Support ◽  
Artemia Salina ◽  
Uranyl Acetate ◽  
Biological Assays ◽  
E Coli ◽  
And Function ◽  
Fine Carbon

Ribosomes are ribonucleoprotein particles necessary for processing the genetic information of mRNA into proteins. Analogy in composition and function of ribosomes from diverse species, established by biochemical and biological assays, implies their structural similarity. Direct evidence obtained by electron microscopy seems to be of increasing relevance in understanding the structure of ribosomes and the mechanism of their role in protein synthesis.The extent of the structural homology between prokaryotic and eukaryotic ribosomes has been studied on ribosomes of Escherichia coli (E.c.) and Artemia salina (A.s.). Despite the established differences in size and in the amount and proportion of ribosomal proteins and RNAs both types of ribosomes show an overall similarity. The monosomes (stained with 0.5% aqueous uranyl acetate and deposited on a fine carbon support) appear in the electron micrographs as round particles with a diameter of approximately 225Å for the 70S E.c. (Fig. 1) and 260Å for the 80S A.s. monosome (Fig. 2).

Role of the Small (40S) Subunits in the Structure of the Interface of Eukaryotic Ribosomes

1980 ◽  
Vol 38 ◽  
pp. 548-549
Author(s):  
M. Boublik ◽  
N. Robakis ◽  
W. Hellmann ◽  
F. Jenkins
Keyword(s):  
Structural Similarity ◽  
High Resolution Electron Microscopy ◽  
Peptide Bond ◽  
Uranyl Acetate ◽  
Mutual Orientation ◽  
Mutual Position ◽  
Peptide Bond Formation ◽  
Resolution Electron ◽  
Direct Technique ◽  
Structural Details

Ribosomes are ribonucleoprotein particles which process the genetic information coded in mRNA into protein synthesis. The analogy in function and composition of ribosomes from various sources, both prokaryotic and eukaryo-tic, imply a structural similarity. At present, high resolution electron microscopy is the most direct technique with a potential to resolve the extent of the structural homology of ribosomal particles at a macromolecular level. The structure of ribosomes is highly complex as a result of the large number of their constituents. In general, 80S eukaryotic monosomes consist of two uneven subunits - large (60S) and small (40S) - accomodating four different RNAs and approximately 80 different proteins. Mutual orientation of both subunits on the monosome is of particular interest because it determines the interface, the supposed site of interactions of ribosomes with other macro-molecules involved in peptide bond formation. Since entrapping of the contrasting solution (0.5% aqueous uranyl acetate) obscures all structural details in the interface, information on its architecture is limited to an indirect reconstruction based on the established 3-D structure of both sub-units and their mutual position after association.

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