scholarly journals Flawed methods in “COVID-19: Attacks the 1-Beta Chain of Hemoglobin and Captures the Porphyrin to Inhibit Human Heme Metabolism”

2020 ◽  
Author(s):  
Randy Read
Keyword(s):  
Molecular Modeling ◽  
Viral Proteins ◽  
Functional Domains ◽  
Computational Docking ◽  
Critical Commentary ◽  
Human Proteins ◽  
Docking Calculations ◽  
Fundamental Error ◽  
Protein Models ◽  
Atomic Coordinates

<div>This is a critical commentary on an earlier submission by Liu and Li. The preprint from Liu & Li (<a href="https://doi.org/10.26434/chemrxiv.11938173.v7">https://doi.org/10.26434/chemrxiv.11938173.v7</a>) puts forward hypotheses about a proposed role for proteins of SARS-CoV-2, the virus associated with Covid-19, in directly attacking haemoglobin in patients’ blood. Arguments for the hypotheses are based on computational methods: bioinformatics calculations searching for evidence that viral proteins share functional domains related to haem binding with human proteins, molecular modeling of viral proteins, and computational docking of these protein models with models of haem, porphyrin and haemoglobin. No experimental evidence is provided to support any of the conclusions. When interpreted according to accepted standards, these computational results do not hold up and do not provide support for the hypotheses. The interpretation of the search for shared functional domains suffers from a fundamental error in how the significance of the results is judged; when interpreted correctly, there is no evidence for these shared functional domains. Molecular modeling is carried out with tools that are easy to use but not best-in-class, and no allowance is made for uncertainty in the resulting atomic coordinates. Finally, the docking results are invalidated by a catastrophic error in their interpretation: the authors choose the docking trials that have the highest energies, whereas the most stable complexes are actually the ones that have the lowest energies and are therefore least strained. An addendum addresses flaws in a new version 8 from Liu & Li (<a href="https://doi.org/10.26434/chemrxiv.11938173.v8">https://doi.org/10.26434/chemrxiv.11938173.v8</a>), which retracts most of their results from earlier versions but nonetheless continues to put forward the same conclusions on the basis of poorly-controlled docking calculations.</div>

scholarly journals Flawed methods in “COVID-19: Attacks the 1-Beta Chain of Hemoglobin and Captures the Porphyrin to Inhibit Human Heme Metabolism”

2020 ◽  
Author(s):  
Randy Read
Keyword(s):  
Molecular Modeling ◽  
Viral Proteins ◽  
Functional Domains ◽  
Computational Docking ◽  
Critical Commentary ◽  
Human Proteins ◽  
Docking Calculations ◽  
Fundamental Error ◽  
Protein Models ◽  
Atomic Coordinates

<div>This is a critical commentary on an earlier submission by Liu and Li. The preprint from Liu & Li (<a href="https://doi.org/10.26434/chemrxiv.11938173.v7">https://doi.org/10.26434/chemrxiv.11938173.v7</a>) puts forward hypotheses about a proposed role for proteins of SARS-CoV-2, the virus associated with Covid-19, in directly attacking haemoglobin in patients’ blood. Arguments for the hypotheses are based on computational methods: bioinformatics calculations searching for evidence that viral proteins share functional domains related to haem binding with human proteins, molecular modeling of viral proteins, and computational docking of these protein models with models of haem, porphyrin and haemoglobin. No experimental evidence is provided to support any of the conclusions. When interpreted according to accepted standards, these computational results do not hold up and do not provide support for the hypotheses. The interpretation of the search for shared functional domains suffers from a fundamental error in how the significance of the results is judged; when interpreted correctly, there is no evidence for these shared functional domains. Molecular modeling is carried out with tools that are easy to use but not best-in-class, and no allowance is made for uncertainty in the resulting atomic coordinates. Finally, the docking results are invalidated by a catastrophic error in their interpretation: the authors choose the docking trials that have the highest energies, whereas the most stable complexes are actually the ones that have the lowest energies and are therefore least strained. An addendum addresses flaws in a new version 8 from Liu & Li (<a href="https://doi.org/10.26434/chemrxiv.11938173.v8">https://doi.org/10.26434/chemrxiv.11938173.v8</a>), which retracts most of their results from earlier versions but nonetheless continues to put forward the same conclusions on the basis of poorly-controlled docking calculations.</div>

scholarly journals Flawed methods in “COVID-19: Attacks the 1-Beta Chain of Hemoglobin and Captures the Porphyrin to Inhibit Human Heme Metabolism”

2020 ◽  
Author(s):  
Randy Read
Keyword(s):  
Molecular Modeling ◽  
Viral Proteins ◽  
Functional Domains ◽  
Computational Results ◽  
Computational Docking ◽  
Critical Commentary ◽  
Human Proteins ◽  
Fundamental Error ◽  
Protein Models ◽  
Atomic Coordinates

<div>This is a critical commentary on an earlier submission by Liu and Li: https://doi.org/10.26434/chemrxiv.11938173 The preprint from Liu & Li (https://doi.org/10.26434/chemrxiv.11938173) puts forward hypotheses about a proposed role for proteins of SARS-CoV-2, the virus associated with Covid-19, in directly attacking haemoglobin in patients’ blood. Arguments for the hypotheses are based on computational methods: bioinformatics calculations searching for evidence that viral proteins share functional domains related to haem binding with human proteins, molecular modeling of viral proteins, and computational docking of these protein models with models of haem, porphyrin and haemoglobin. No experimental evidence is provided to support any of the conclusions. When interpreted according to accepted standards, these computational results do not hold up and do not provide support for the hypotheses. The interpretation of the search for shared functional domains suffers from a fundamental error in how the significance of the results is judged; when interpreted correctly, there is no evidence for these shared functional domains. Molecular modeling is carried out with tools that are easy to use but not best-in-class, and no allowance is made for uncertainty in the resulting atomic coordinates. Finally, the docking results are invalidated by a catastrophic error in their interpretation: the authors choose the docking trials that have the highest energies, whereas the most stable complexes are actually the ones that have the lowest energies and are therefore least strained.</div>

scholarly journals In-silico Study of the Developed Hydroxychloroquine-based ACE2 Inhibitor Molecules Against COVID-19: Molecular Modeling and Docking

2021 ◽  
Vol 11 (4) ◽  
pp. 7336-7342
Author(s):  
K. Zaher ◽  
N. E. Masango ◽  
W. Sobhi ◽  
K. E. Kanouni ◽  
A. Semmeq ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Modeling ◽  
In Silico ◽  
Viral Proteins ◽  
In Silico Study ◽  
Docking Calculations ◽  
Portal Of Entry ◽  
Molecular Modeling And Docking ◽  
Materials Studio

In the present study, we will verify the action of hydroxychloroquine-based derivatives on ACE2 which is considered to be the main portal of entry of the SARS-CoV-2 virus and constitutes an exciting target given its relative genetic stability compared to viral proteins. Thus, 81 molecules derived from hydroxychloroquine by substitutions at 4 different positions were generated in-silico and then studied for their affinity for ACE2 by molecular docking. Only 4 molecules were retained because of their affinity and bioavailability demonstrated by molecular dynamics and molecular docking calculations using COSMOtherm and Materials Studio software.

cDNA cloning, molecular modeling and docking calculations of L -type lectins from Swartzia simplex var. grandiflora (Leguminosae, Papilionoideae), a member of the tribe Swartzieae

2017 ◽  
Vol 139 ◽  
pp. 60-71 ◽  
Author(s):  
Paulo A.C. Maranhão ◽  
Claudener S. Teixeira ◽  
Bruno L. Sousa ◽  
Ito L. Barroso-Neto ◽  
José E. Monteiro-Júnior ◽  
...  
Keyword(s):  
Molecular Modeling ◽  
Cdna Cloning ◽  
Docking Calculations ◽  
Molecular Modeling And Docking

scholarly journals Identification of Drugs Targeting Multiple Viral and Human Proteins Using Computational Analysis for Repurposing Against COVID-19

2020 ◽  
Author(s):  
Sugandh Kumar ◽  
Pratima Kumari ◽  
Geetanjali Agnihotri ◽  
Preethy VijayKumar ◽  
Shaheerah Khan ◽  
...  
Keyword(s):  
Interaction Network ◽  
Viral Proteins ◽  
Inhibitory Effect ◽  
Host Proteins ◽  
Disease Manifestation ◽  
Protein Protein Interaction ◽  
Human Proteins ◽  
Approved Drugs ◽  
Viral Lifecycle ◽  
Fda Approved Drugs

<p>The SARS-CoV2 is a highly contagious pathogen that causes a respiratory disease named COVID-19. The COVID-19 was declared a pandemic by the WHO on 11th March 2020. It has affected about 5.38 million people globally (identified cases as on 24th May 2020), with an average lethality of ~3%. Unfortunately, there is no standard cure for the disease, although some drugs are under clinical trial. Thus, there is an urgent need of drugs for the treatment of COVID-19. The molecularly targeted therapies have proven their utility in various diseases such as HIV, SARS, and HCV. Therefore, a lot of efforts are being directed towards the identification of molecules that can be helpful in the management of COVID-19. </p> <p>In the current studies, we have used state of the art bioinformatics techniques to screen the FDA approved drugs against thirteen SARS-CoV2 proteins in order to identify drugs for quick repurposing. The strategy was to identify potential drugs that can target multiple viral proteins simultaneously. Our strategy originates from the fact that individual viral proteins play specific role in multiple aspects of viral lifecycle such as attachment, entry, replication, morphogenesis and egress and targeting them simultaneously will have better inhibitory effect.</p> <p>Additionally, we analyzed if the identified molecules can also affect the host proteins whose expression is differentially modulated during SARS-CoV2 infection. The differentially expressed genes (DEGs) were identified using analysis of NCBI-GEO data (GEO-ID: GSE-147507). A pathway and protein-protein interaction network analysis of the identified DEGs led to the identification of network hubs that may play important roles in SARS-CoV2 infection. Therefore, targeting such genes may also be a beneficial strategy to curb disease manifestation. We have identified 29 molecules that can bind to various SARS-CoV2 and human host proteins. We hope that this study will help researchers in the identification and repurposing of multipotent drugs, simultaneously targeting the several viral and host proteins, for the treatment of COVID-19.</p>

scholarly journals Identification of Drugs Targeting Multiple Viral and Human Proteins Using Computational Analysis for Repurposing Against COVID-19

2020 ◽  
Author(s):  
Sugandh Kumar ◽  
Pratima Kumari ◽  
Geetanjali Agnihotri ◽  
Preethy VijayKumar ◽  
Shaheerah Khan ◽  
...  
Keyword(s):  
Interaction Network ◽  
Viral Proteins ◽  
Inhibitory Effect ◽  
Host Proteins ◽  
Disease Manifestation ◽  
Protein Protein Interaction ◽  
Human Proteins ◽  
Approved Drugs ◽  
Viral Lifecycle ◽  
Fda Approved Drugs

<p>The SARS-CoV2 is a highly contagious pathogen that causes a respiratory disease named COVID-19. The COVID-19 was declared a pandemic by the WHO on 11th March 2020. It has affected about 5.38 million people globally (identified cases as on 24th May 2020), with an average lethality of ~3%. Unfortunately, there is no standard cure for the disease, although some drugs are under clinical trial. Thus, there is an urgent need of drugs for the treatment of COVID-19. The molecularly targeted therapies have proven their utility in various diseases such as HIV, SARS, and HCV. Therefore, a lot of efforts are being directed towards the identification of molecules that can be helpful in the management of COVID-19. </p> <p>In the current studies, we have used state of the art bioinformatics techniques to screen the FDA approved drugs against thirteen SARS-CoV2 proteins in order to identify drugs for quick repurposing. The strategy was to identify potential drugs that can target multiple viral proteins simultaneously. Our strategy originates from the fact that individual viral proteins play specific role in multiple aspects of viral lifecycle such as attachment, entry, replication, morphogenesis and egress and targeting them simultaneously will have better inhibitory effect.</p> <p>Additionally, we analyzed if the identified molecules can also affect the host proteins whose expression is differentially modulated during SARS-CoV2 infection. The differentially expressed genes (DEGs) were identified using analysis of NCBI-GEO data (GEO-ID: GSE-147507). A pathway and protein-protein interaction network analysis of the identified DEGs led to the identification of network hubs that may play important roles in SARS-CoV2 infection. Therefore, targeting such genes may also be a beneficial strategy to curb disease manifestation. We have identified 29 molecules that can bind to various SARS-CoV2 and human host proteins. We hope that this study will help researchers in the identification and repurposing of multipotent drugs, simultaneously targeting the several viral and host proteins, for the treatment of COVID-19.</p>

scholarly journals Modification of Remdesivir as a Better Inhibitor of COVID-19: A Computational Docking Study

2020 ◽  
Author(s):  
Mita Shikder ◽  
Kazi Ahsan Ahmed ◽  
Tasnin Al Hasib ◽  
Md. Lutful Kabir
Keyword(s):  
Rna Polymerase ◽  
Antiviral Drug ◽  
Antiviral Agent ◽  
Respiratory Illness ◽  
Docking Study ◽  
New Drugs ◽  
Computational Docking ◽  
Recent Success ◽  
Trial Basis ◽  
Docking Calculations

<div>Coronavirus (COVID-19) mediated infection is a highly contagious respiratory illness that was initially found in Wuhan city of Hubei Province in China. The ongoing pandemic of the novel SARS-CoV-2 virus is affecting global health. Despite the recent success in vaccination on a trial basis, there is no treatment of the infection. Thus, establishing an effective therapeutic measure is of apex priority among biologists and healthcare professionals. Re-purposing Remdesivir, a broad-spectrum antiviral agent that inhibits viral RNA polymerase, has been found effective for the treatment of COVID-19. In this study, modification of the existing drug Remdesivir was done. In logical drug designing and development, molecular recognition plays a central role in this sphere. The anti viral function of Remdesivir is achieved by binding to RNA polymerase enzyme. The protein 7BTF is an RNA-dependent RNA polymerase that plays a crucial role in coronavirus replication and transcription machinery and it appears to be the primary target of the antiviral drug Remdesivir. The study intend to design derivative compounds form Remdesivir to screen out the a better drug against the SARS-CoV-2 virus by inhibiting the targeted protein. The efficacy of these new drugs was also tested by molecular docking calculations. The drug derivatives were docked for binding affinity and non-bond interactions. Pharmacokinetic activities of the designed drugs are also predicted. All the drugs are non-carcinogenic and chemically reactive. In our study, modified compound D-I has exhibited the best performance among Remdesivir and it’s derivatives. This study might provide an insight into the potential of a Remdesivir derivative in treating SARS-CoV-2 infection<br></div>

Josephin domain-containing proteins from a variety of species are active de-ubiquitination enzymes

2007 ◽  
Vol 388 (9) ◽  
pp. 973-978 ◽  
Author(s):  
Nikolay Tzvetkov ◽  
Peter Breuer
Keyword(s):  
Plasmodium Falciparum ◽  
Enzyme Activity ◽  
Neurodegenerative Disease ◽  
Spinocerebellar Ataxia ◽  
Spinocerebellar Ataxia Type ◽  
Functional Domains ◽  
Spinocerebellar Ataxia Type 3 ◽  
C Terminus ◽  
Human Proteins ◽  
Type 3

Abstract The neurodegenerative disease spinocerebellar ataxia type 3 (SCA3) is caused by the presence of an extended polyglutamine stretch (polyQ) in the unstructured C-terminus of the human ataxin-3 (AT3) protein. The structured N-terminal Josephin domain (JD) of AT3 is conserved within a novel family of potential ubiquitin proteases, the JD-containing proteins, which are sub-divided into two groups termed ataxins and Josephins. These AT3 orthologs are encoded by the genomes of organisms ranging from Plasmodium falciparum to humans, with most species possessing more than one homolog. While Josephins consist of JDs alone, ataxins contain additional functional domains that may influence their enzyme activity. Here, we show that the enzyme activity of human AT3 (hAT3) is not affected by the length of polyQ in its C-terminus, even when it is in the range associated with SCA3. We also show that JDs of all human proteins with homology to AT3 and its homologs from various species possess de-ubiquitination activity. These results establish JD-containing proteins as a novel family of active de-ubiquitination enzymes with wide phylogenic distribution.

scholarly journals Different Subtypes of Influenza Viruses Target Different Human Proteins and Pathways Leading to Different Pathogenic Phenotypes

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Yujie Wang ◽  
Ting Song ◽  
Kaiwu Li ◽  
Yuan Jin ◽  
Junjie Yue ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Influenza A ◽  
Viral Proteins ◽  
Influenza Viruses ◽  
Host Protein ◽  
Protein Protein Interactions ◽  
Influenza A Viruses ◽  
Host Proteins ◽  
Pathogenic Mechanisms ◽  
Human Proteins

Different subtypes of influenza A viruses (IAVs) cause different pathogenic phenotypes after infecting human bodies. Analysis of the interactions between viral proteins and the host proteins may provide insights into the pathogenic mechanisms of the virus. In this paper, we found that the same proteins (nucleoprotein and neuraminidase) of H1N1 and H5N1 have different impacts on the NF-κB activation. By further examining the virus–host protein–protein interactions, we found that both NP and NA proteins of the H1N1 and H5N1 viruses target different host proteins. These results indicate that different subtypes of influenza viruses target different human proteins and pathways leading to different pathogenic phenotypes.

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