Semicovariance Coefficient Analysis of Spike Proteins from SARS-CoV-2 and Other Coronaviruses for Viral Evolution and Characteristics Associated with Fatality

Complex modeling has received significant attention in recent years and is increasingly used to explain statistical phenomena with increasing and decreasing fluctuations, such as the similarity or difference of spike protein charge patterns of coronaviruses. Different from the existing covariance or correlation coefficient methods in traditional integer dimension construction, this study proposes a simplified novel fractional dimension derivation with the exact Excel tool algorithm. It involves the fractional center moment extension to covariance, which results in a complex covariance coefficient that is better than the Pearson correlation coefficient, in the sense that the nonlinearity relationship can be further depicted. The spike protein sequences of coronaviruses were obtained from the GenBank and GISAID databases, including the coronaviruses from pangolin, bat, canine, swine (three variants), feline, tiger, SARS-CoV-1, MERS, and SARS-CoV-2 (including the strains from Wuhan, Beijing, New York, German, and the UK variant B.1.1.7) which were used as the representative examples in this study. By examining the values above and below the average/mean based on the positive and negative charge patterns of the amino acid residues of the spike proteins from coronaviruses, the proposed algorithm provides deep insights into the nonlinear evolving trends of spike proteins for understanding the viral evolution and identifying the protein characteristics associated with viral fatality. The calculation results demonstrate that the complex covariance coefficient analyzed by this algorithm is capable of distinguishing the subtle nonlinear differences in the spike protein charge patterns with reference to Wuhan strain SARS-CoV-2, which the Pearson correlation coefficient may overlook. Our analysis reveals the unique convergent (positive correlative) to divergent (negative correlative) domain center positions of each virus. The convergent or conserved region may be critical to the viral stability or viability; while the divergent region is highly variable between coronaviruses, suggesting high frequency of mutations in this region. The analyses show that the conserved center region of SARS-CoV-1 spike protein is located at amino acid residues 900, but shifted to the amino acid residues 700 in MERS spike protein, and then to amino acid residues 600 in SARS-COV-2 spike protein, indicating the evolution of the coronaviruses. Interestingly, the conserved center region of the spike protein in SARS-COV-2 variant B.1.1.7 shifted back to amino acid residues 700, suggesting this variant is more virulent than the original SARS-COV-2 strain. Another important characteristic our study reveals is that the distance between the divergent mean and the maximal divergent point in each of the viruses (MERS > SARS-CoV-1 > SARS-CoV-2) is proportional to viral fatality rate. This algorithm may help to understand and analyze the evolving trends and critical characteristics of SARS-COV-2 variants, other coronaviral proteins and viruses.

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Semi-Covariance Coefficient Analysis of Spike Proteins from SARS-CoV-2 and other Coronaviruses for Viral Evolution and Characteristics Associated with Fatality

10.20944/preprints202103.0055.v1 ◽

2021 ◽

Author(s):

Jun Huang ◽

Rebecca Spencer ◽

Wangdong Zhang

Keyword(s):

Amino Acid ◽

Correlation Coefficient ◽

Pearson Correlation ◽

Viral Evolution ◽

Spike Protein ◽

Pearson Correlation Coefficient ◽

Amino Acid Residues ◽

Protein Charge ◽

Center Region ◽

Spike Proteins

Complex modeling has received significant attention in recent years and is increasingly used to explain the statistical phenomenon with increasing and decreasing fluctuations such as the similarity or difference of spike protein charge patterns of coronaviruses. Different from the existing covariance or correlation coefficient methods in traditional integer dimension construction, this study proposes a simplified novel fractional dimension derivation with the exact Excel tool algorithm. It involves the fractional center moment extension to covariance, which ends up a complex covariance coefficient that is better than the Pearson correlation coefficient, in the sense that the nonlinearity relationship can be further depicted. The spike protein sequences of coronaviruses were obtained from the GenBank and GISAID database, including the coronaviruses from pangolin, bat, canine, swine (three variants), feline, tiger, SARS-CoV-1, MERS, and SARS-CoV-2 (including the strains of Wuhan, Beijing, New York, German, and UK variant B.1.1.7) were used as the representative examples in this study. By examining the values above and below the average/mean based on the positive and negative charge patterns of the amino acid residues of the spike proteins from coronaviruses, the proposed algorithm provides deep insights into the nonlinear evolving trends of spike proteins for understanding the viral evolution and identifying the protein characteristics associated with viral fatality. The calculation results demonstrate that the complex covariance coefficient analyzed by this algorithm is capable of distinguishing the subtle nonlinear differences in the spike protein charge patterns with reference to Wuhan strain SARS-CoV-2 for which the Pearson correlation coefficient may overlook. Our analysis reveals the unique convergent (positive correlative) to divergent (negative correlative) domain center positions of each virus. The convergent or conserved region may be critical to the viral stability or viability; while the divergent region is highly variable between coronaviruses suggesting high frequency of mutations in this region. The analyses show that the conserved center region of SARS-CoV-1 spike protein is located at amino acid residues 900, but shifted to the amino acid residues 700 in MERS spike protein, and then to amino acid residues 600 in SARS-COV-2 spike protein, indicating the evolvement of the coronaviruses. Interestingly, the conserved center region of the spike protein in SARS-COV-2 variant B.1.1.7 shifted back to amino acid residues 700, suggesting this variant is more virulent than the original SARS-COV-2 strain. Another important characteristic our study reveals is that the distance between the divergent mean and the maximal divergent point in each of the viruses (MERS>SARS-CoV-1>SARS-CoV-2) is proportional to viral fatality rate. This algorithm may help to understand and analyze the evolving trends and critical characteristics of SARS-COV-2 variants, other coronaviral proteins and viruses.

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Recognition of Protein Pupylation Sites by Adopting Resampling Approach

Molecules ◽

10.3390/molecules23123097 ◽

2018 ◽

Vol 23 (12) ◽

pp. 3097

Author(s):

Tao Li ◽

Yan Chen ◽

Taoying Li ◽

Cangzhi Jia

Keyword(s):

Amino Acid ◽

Correlation Coefficient ◽

Posttranslational Modification ◽

Cross Validation ◽

Pearson Correlation ◽

Principal Component ◽

Pearson Correlation Coefficient ◽

Protein Ubiquitination ◽

Independent Test Dataset ◽

Fold Cross Validation

With the in-depth study of posttranslational modification sites, protein ubiquitination has become the key problem to study the molecular mechanism of posttranslational modification. Pupylation is a widely used process in which a prokaryotic ubiquitin-like protein (Pup) is attached to a substrate through a series of biochemical reactions. However, the experimental methods of identifying pupylation sites is often time-consuming and laborious. This study aims to propose an improved approach for predicting pupylation sites. Firstly, the Pearson correlation coefficient was used to reflect the correlation among different amino acid pairs calculated by the frequency of each amino acid. Then according to a descending ranked order, the multiple types of features were filtered separately by values of Pearson correlation coefficient. Thirdly, to get a qualified balanced dataset, the K-means principal component analysis (KPCA) oversampling technique was employed to synthesize new positive samples and Fuzzy undersampling method was employed to reduce the number of negative samples. Finally, the performance of our method was verified by means of jackknife and a 10-fold cross-validation test. The average results of 10-fold cross-validation showed that the sensitivity (Sn) was 90.53%, specificity (Sp) was 99.8%, accuracy (Acc) was 95.09%, and Matthews Correlation Coefficient (MCC) was 0.91. Moreover, an independent test dataset was used to further measure its performance, and the prediction results achieved the Acc of 83.75%, MCC of 0.49, which was superior to previous predictors. The better performance and stability of our proposed method showed it is an effective way to predict pupylation sites.

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On the Psychological Reality of the Pearson Correlation Coefficient: Effects of Objective Covariation on Subjective Estimates

PsycEXTRA Dataset ◽

10.1037/e537052012-416 ◽

2004 ◽

Author(s):

Richard B. Anderson ◽

Andrea M. Angott ◽

Michael E. Doherty

Keyword(s):

Correlation Coefficient ◽

Pearson Correlation ◽

Pearson Correlation Coefficient ◽

Psychological Reality ◽

Subjective Estimates

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Relationship between Invasive and Non-Invasive Hemodynamic Measures in Experimental Pulmonary Hypertension

Current Respiratory Medicine Reviews ◽

10.2174/1573398x16666200516180118 ◽

2020 ◽

Vol 16 (1) ◽

pp. 47-53

Author(s):

Vicente Benavides-Córdoba ◽

Mauricio Palacios Gómez

Keyword(s):

Heart Rate ◽

Pulmonary Hypertension ◽

Ejection Fraction ◽

Right Ventricle ◽

Correlation Coefficient ◽

Pearson Correlation ◽

Systolic Pressure ◽

Control Group ◽

Pearson Correlation Coefficient ◽

Non Invasive

Introduction: Animal models have been used to understand the pathophysiology of pulmonary hypertension, to describe the mechanisms of action and to evaluate promising active ingredients. The monocrotaline-induced pulmonary hypertension model is the most used animal model. In this model, invasive and non-invasive hemodynamic variables that resemble human measurements have been used. Aim: To define if non-invasive variables can predict hemodynamic measures in the monocrotaline-induced pulmonary hypertension model. Materials and Methods: Twenty 6-week old male Wistar rats weighing between 250-300g from the bioterium of the Universidad del Valle (Cali - Colombia) were used in order to establish that the relationships between invasive and non-invasive variables are sustained in different conditions (healthy, hypertrophy and treated). The animals were organized into three groups, a control group who was given 0.9% saline solution subcutaneously (sc), a group with pulmonary hypertension induced with a single subcutaneous dose of Monocrotaline 30 mg/kg, and a group with pulmonary hypertension with 30 mg/kg of monocrotaline treated with Sildenafil. Right ventricle ejection fraction, heart rate, right ventricle systolic pressure and the extent of hypertrophy were measured. The functional relation between any two variables was evaluated by the Pearson correlation coefficient. Results: It was found that all correlations were statistically significant (p <0.01). The strongest correlation was the inverse one between the RVEF and the Fulton index (r = -0.82). The Fulton index also had a strong correlation with the RVSP (r = 0.79). The Pearson correlation coefficient between the RVEF and the RVSP was -0.81, meaning that the higher the systolic pressure in the right ventricle, the lower the ejection fraction value. Heart rate was significantly correlated to the other three variables studied, although with relatively low correlation. Conclusion: The correlations obtained in this study indicate that the parameters evaluated in the research related to experimental pulmonary hypertension correlate adequately and that the measurements that are currently made are adequate and consistent with each other, that is, they have good predictive capacity.

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Bed-Based Ballistocardiography: Dataset and Ability to Track Cardiovascular Parameters

Sensors ◽

10.3390/s21010156 ◽

2020 ◽

Vol 21 (1) ◽

pp. 156

Author(s):

Charles Carlson ◽

Vanessa-Rose Turpin ◽

Ahmad Suliman ◽

Carl Ade ◽

Steve Warren ◽

...

Keyword(s):

Blood Pressure ◽

Stroke Volume ◽

Systolic Blood Pressure ◽

Correlation Coefficient ◽

Pearson Correlation ◽

Health Assessment ◽

Initial Study ◽

Pearson Correlation Coefficient ◽

Medical Systems ◽

Cardiovascular Parameters

Background: The goal of this work was to create a sharable dataset of heart-driven signals, including ballistocardiograms (BCGs) and time-aligned electrocardiograms (ECGs), photoplethysmograms (PPGs), and blood pressure waveforms. Methods: A custom, bed-based ballistocardiographic system is described in detail. Affiliated cardiopulmonary signals are acquired using a GE Datex CardioCap 5 patient monitor (which collects ECG and PPG data) and a Finapres Medical Systems Finometer PRO (which provides continuous reconstructed brachial artery pressure waveforms and derived cardiovascular parameters). Results: Data were collected from 40 participants, 4 of whom had been or were currently diagnosed with a heart condition at the time they enrolled in the study. An investigation revealed that features extracted from a BCG could be used to track changes in systolic blood pressure (Pearson correlation coefficient of 0.54 +/− 0.15), dP/dtmax (Pearson correlation coefficient of 0.51 +/− 0.18), and stroke volume (Pearson correlation coefficient of 0.54 +/− 0.17). Conclusion: A collection of synchronized, heart-driven signals, including BCGs, ECGs, PPGs, and blood pressure waveforms, was acquired and made publicly available. An initial study indicated that bed-based ballistocardiography can be used to track beat-to-beat changes in systolic blood pressure and stroke volume. Significance: To the best of the authors’ knowledge, no other database that includes time-aligned ECG, PPG, BCG, and continuous blood pressure data is available to the public. This dataset could be used by other researchers for algorithm testing and development in this fast-growing field of health assessment, without requiring these individuals to invest considerable time and resources into hardware development and data collection.

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Assessment of the Dissimilarities of EDI and SPI Measures for Drought Determination in South Africa

Water ◽

10.3390/w13010082 ◽

2021 ◽

Vol 13 (1) ◽

pp. 82

Author(s):

Omolola M. Adisa ◽

Muthoni Masinde ◽

Joel O. Botai

Keyword(s):

South Africa ◽

South African ◽

Correlation Coefficient ◽

Pearson Correlation ◽

Standardized Precipitation Index ◽

Drought Monitoring ◽

Drought Indices ◽

Drought Severity ◽

Pearson Correlation Coefficient ◽

Drought Duration

This study examines the (dis)similarity of two commonly used indices Standardized Precipitation Index (SPI) computed over accumulation periods 1-month, 3-month, 6-month, and 12-month (hereafter SPI-1, SPI-3, SPI-6, and SPI-12, respectively) and Effective Drought Index (EDI). The analysis is based on two drought monitoring indicators (derived from SPI and EDI), namely, the Drought Duration (DD) and Drought Severity (DS) across the 93 South African Weather Service’s delineated rainfall districts over South Africa from 1980 to 2019. In the study, the Pearson correlation coefficient dissimilarity and periodogram dissimilarity estimates were used. The results indicate a positive correlation for the Pearson correlation coefficient dissimilarity and a positive value for periodogram of dissimilarity in both the DD and DS. With the Pearson correlation coefficient dissimilarity, the study demonstrates that the values of the SPI-1/EDI pair and the SPI-3/EDI pair exhibit the highest similar values for DD, while the SPI-6/EDI pair shows the highest similar values for DS. Moreover, dissimilarities are more obvious in SPI-12/EDI pair for DD and DS. When a periodogram of dissimilarity is used, the values of the SPI-1/EDI pair and SPI-6/EDI pair exhibit the highest similar values for DD, while SPI-1/EDI displayed the highest similar values for DS. Overall, the two measures show that the highest similarity is obtained in the SPI-1/EDI pair for DS. The results obtainable in this study contribute towards an in-depth knowledge of deviation between the EDI and SPI values for South Africa, depicting that these two drought indices values are replaceable in some rainfall districts of South Africa for drought monitoring and prediction, and this is a step towards the selection of the appropriate drought indices.

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Fault Detection and Location Method for Mesh-type DC Microgrid using Pearson Correlation Coefficient

IEEE Transactions on Power Delivery ◽

10.1109/tpwrd.2020.3008924 ◽

2020 ◽

pp. 1-1 ◽

Cited By ~ 1

Author(s):

Liang Kong ◽

Heng Nian

Keyword(s):

Fault Detection ◽

Correlation Coefficient ◽

Pearson Correlation ◽

Pearson Correlation Coefficient ◽

Dc Microgrid ◽

Location Method

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Use of Multiple Visits to Increase Blood Pressure Tracking Correlations in Childhood

PEDIATRICS ◽

10.1542/peds.87.5.708 ◽

1991 ◽

Vol 87 (5) ◽

pp. 708-711

Author(s):

Matthew W. Gillman ◽

Bernard Rosner ◽

Denis A. Evans ◽

Laurel A. Smith ◽

James O. Taylor ◽

...

Keyword(s):

Blood Pressure ◽

Diastolic Blood Pressure ◽

Correlation Coefficient ◽

Diastolic Pressure ◽

Pearson Correlation ◽

Systolic Pressure ◽

Pearson Correlation Coefficient ◽

Increase Blood Pressure ◽

Multiple Visit

Previous studies of childhood blood pressure have shown tracking correlations, which estimate the magnitude of association between initial and subsequent measurements, to be lower than corresponding adult values. Inasmuch as this disparity could arise from failing to account for a larger week-to-week variability in children, blood pressure was measured for 4 successive years, on four weekly visits in each year, and with three measurements at each visit, using a random-zero sphygmomanometer, in a cohort of 333 schoolchildren aged 8 through 15 at entry. Ninety percent of subjects had measurements in 1 or more years of follow-up. For all follow-up periods (1, 2, and 3 years from baseline), the Pearson correlation coefficient (r) for both systolic and diastolic blood pressure rose substantially with the number of weekly visits used to calculate each subject's yearly blood pressure (P < .0001). For systolic pressure, the 3-year r values for 1, 2, 3, and 4 visits were .45, .55, .64, and .69, respectively. For diastolic pressure (Korotkoff phase 4), the corresponding values were .28, .41, .47, and .54. These higher multiple-visit estimates of tracking approximate published adult values and raise the possibility that prediction of adult blood pressure from childhood measurements may be improved by averaging readings from multiple weekly visits.

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ReaxFF-based molecular dynamics simulation of the interaction between plasma ROS and the receptor-binding domain of the spike protein in the capsid protein of SARS-CoV-2

Journal of Physics D Applied Physics ◽

10.1088/1361-6463/ac360e ◽

2021 ◽

Author(s):

Huichao Wang ◽

Tong Zhao ◽

Shuhui Yang ◽

Liang Zou ◽

Xiaolong Wang ◽

...

Keyword(s):

Molecular Dynamics ◽

Amino Acid ◽

Capsid Protein ◽

Receptor Binding ◽

Hydrogen Abstraction ◽

Binding Domain ◽

Spike Protein ◽

Receptor Binding Domain ◽

Amino Acid Residues ◽

Global Epidemic

Abstract Under the severe situation of the current global epidemic, researchers have been working hard to find a reliable way to suppress the infection of the virus and prevent the spread of the epidemic. Studies have shown that the recognition and binding of human angiotensin-converting enzyme 2 (ACE2) by the receptor-binding domain (BRD) of spike protein on the surface of SARS-CoV-2 is a crucial step for SARS-CoV-2 to invade human receptor cells, and blocking this process can inhibit the virus from invading human normal cells. Plasma treatment can disrupt the structure of the RBD and effectively block the binding process. However, the mechanism by which plasma blocks the recognition and binding between the two is not clear. In this study, reaction process between reactive oxygen species (ROS) in plasma and the molecular model of RBD was simulated using a reactive molecular dynamics method. The results showed that the destruction of RBD molecule by ROS was triggered by hydrogen abstraction reactions. O and OH abstracted H atoms from RBD, while the H atoms of H2O2 and HO2 were abstracted by RBD. The hydrogen abstraction resulted in the breakage of C-H, N-H, O-H and C=O bonds and the formation of C=C, C=N bonds. The addition reaction of OH increased the number of O-H bonds and caused the formation of C-O, N-O and O-H bonds. The dissociation of N-H bonds led to the destruction of the original structure of peptide bonds and amino acid residues, change the type of amino acid residues, and caused the conversion of N-C and N=C, C=O and C-O. The simulation partially elucidated the microscopic mechanism of the interaction between ROS in plasma and the capsid protein of SARS-CoV-2, providing theoretical support for the control of SARS-CoV-2 infection by plasma, a contribution to overcoming the global epidemic problem.

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