Bioinformatics

R346K Mutation in the Mu Variant of SARS-CoV-2 Alters the Interactions with Monoclonal Antibodies from Class 2: A Free Energy Perturbation Study

1. Filip Fratev

Reviewed by ScreenIT

SARS-CoV-2 PLpro whole human proteome cleavage prediction and enrichment/depletion analysis

1. Lucas Prescott

Reviewed by ScreenIT

Hierarchical Gaussian Processes and Mixtures of Experts to Model COVID-19 Patient Trajectories

1. Sunny Cui
2. Elizabeth C. Yoo
3. Didong Li
4. Krzysztof Laudanski
5. Barbara E. Engelhardt

Reviewed by ScreenIT

Characterization and Structural Prediction of ORF10, ORF7b, ORF7a, ORF6, Membrane Glycoprotein, and Envelope Protein in SARS-CoV-2 Bangladeshi Variant through Bioinformatics Approach

1. Pinky Debnath
2. Umama Khan
3. Md. Salauddin Khan

Reviewed by ScreenIT

A survey of optimal strategy for signature-based drug repositioning and an application to liver cancer

1. Chen Yang
2. Hailin Zhang
3. Mengnuo Chen
4. Siying Wang
5. Ruolan Qian
6. Linmeng Zhang
7. Xiaowen Huang
8. Jun Wang
9. Zhicheng Liu
10. Wenxin Qin
11. Cun Wang
12. Hualian Hang
13. Hui Wang

• Curated by eLife

  Evaluation Summary:

  This paper will be of interest to scientists across translational medicine and cancer treatment. It describes a standardized method to identify drugs that could be potentially repositioned for tumor treatment. In addition, using this new method and experimental manipulations the authors identify homoharringtonine as a new potential therapy for liver cancer and the underlying liver disease. However, while bioinformatic analysis was really comprehensive, the results and conclusions obtained are based on public datasets and therefore limited by the data available. In addition, the experimental approach to test the potential new treatments are currently based on in vitro assays and would be strengthened by in vivo validations.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

Reviewed by eLife

Data-driven approaches for genetic characterization of SARS-CoV-2 lineages

1. Fatima Mostefai
2. Isabel Gamache
3. Jessie Huang
4. Arnaud N’Guessan
5. Justin Pelletier
6. Ahmad Pesaranghader
7. David Hamelin
8. Carmen Lia Murall
9. Raphaël Poujol
10. Jean-Christophe Grenier
11. Martin Smith
12. Etienne Caron
13. Morgan Craig
14. Jesse Shapiro
15. Guy Wolf
16. Smita Krishnaswamy
17. Julie G. Hussin

Reviewed by ScreenIT

In silico screening of TMPRSS2 SNPs that affect its binding with SARS-CoV2 spike protein and directly involved in the interaction affinity changes

1. Fatma Nouira
2. Manel Hamdi
3. Alaeddine Redissi
4. Soumaya Kouidhi
5. Cherine Charfeddine
6. Meriem M’saad
7. Ameur Cherif
8. Sabri Messaoudi
9. Sarah Aldulaijan
10. Noureddine Raouafi
11. Adnene Dhouib
12. Amor Mosbah

Reviewed by ScreenIT

Analysis of the ARTIC Version 3 and Version 4 SARS-CoV-2 Primers and Their Impact on the Detection of the G142D Amino Acid Substitution in the Spike Protein

1. James J. Davis
2. S. Wesley Long
3. Paul A. Christensen
4. Randall J. Olsen
5. Robert Olson
6. Maulik Shukla
7. Sishir Subedi
8. Rick Stevens
9. James M. Musser

Reviewed by ScreenIT

Cytotoxic T-cell-based vaccine against SARS-CoV2: a hybrid immunoinformatic approach

1. Alexandru Tîrziu
2. Virgil Păunescu

Reviewed by ScreenIT

Screening key genes and signaling pathways in COVID-19 infection and its associated complications by integrated bioinformatics analysis

1. Basavaraj Vastrad
2. Chanabasayya Vastrad

Reviewed by ScreenIT