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Pathogens
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Computational Approaches to Understand the Mechanisms of Diseases at Molecular...
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Computational Approaches to Understand the Mechanisms of Diseases at Molecular Level

A special issue of Pathogens (ISSN 2076-0817).

Deadline for manuscript submissions: closed (20 June 2022) | Viewed by 5316

Special Issue Editors

Dr. Lin Li

E-Mail Website
Guest Editor
Department of Physics, University of Texas, 500 West University Ave, El Paso, TX 79968, USA
Interests: protein-protein interactions; molecular dynamic simulations;Covid-19;protein-DNA/RNA interactions ;molecular motor; viral capsid assembly
Special Issues, Collections and Topics in MDPI journals
Dr. Yi He

E-Mail Website
Guest Editor
Department of Chemistry & Chemical Biology, The University of New Mexico, Albuquerque, NM 87131, USA
Interests: chemical biology and biochemistry; physical chemistry; theoretical and computational chemistry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid advancement of computational techniques brings computational biology to the forefront in the race to understand the mechanisms of disease at a molecular level. Cutting-edge computational tools have been widely used to solve problems in biology, including protein structure prediction, protein–protein complex structure prediction, pKa prediction, drug design, simulations of biomolecules, etc. With the structures of biomolecules in hand, atomic simulations, coarse-grained models, and other computational approaches have been successfully implemented to study health-related problems. This Special Issue shall focus on advanced computational approaches and their applications in understanding the mechanisms of disease at a molecular level. This Special Issue aims at developing and utilizing state-of-the-art computational algorithms to study a wide range of diseases.

Original papers and high-quality review articles are welcome in this Special Issue. Potential topics include but are not limited to:

  • Molecular dynamic simulations;
  • Coarse grained approaches;
  • Software or database development for biology research;
  • Protein–protein/DNA/RNA interactions;
  • Prediction of protein–ligand interaction energies;
  • Drug design.

Dr. Lin Li
Dr. Yi He
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Pathogens is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • disease-related proteins
  • protein–protein interactions
  • protein–NDA/RNA interactions
  • COVID-19
  • molecular dynamic simulations
  • coarse-grained models

Published Papers (2 papers)

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Research

14 pages, 6339 KiB  
Article
The pH Effects on SARS-CoV and SARS-CoV-2 Spike Proteins in the Process of Binding to hACE2
by Yixin Xie, Wenhan Guo, Alan Lopez-Hernadez, Shaolei Teng and Lin Li
Pathogens 2022, 11(2), 238; https://doi.org/10.3390/pathogens11020238 - 11 Feb 2022
Cited by 17 | Viewed by 2242
Abstract
COVID-19 has been threatening human health since the late 2019, and has a significant impact on human health and economy. Understanding SARS-CoV-2 and other coronaviruses is important to develop effective treatments for COVID-19 and other coronavirus-caused diseases. In this work, we applied multi-scale [...] Read more.
COVID-19 has been threatening human health since the late 2019, and has a significant impact on human health and economy. Understanding SARS-CoV-2 and other coronaviruses is important to develop effective treatments for COVID-19 and other coronavirus-caused diseases. In this work, we applied multi-scale computational approaches to study the electrostatic features of spike (S) proteins for SARS-CoV and SARS-CoV-2. From our results, we found that SARS-CoV and SARS-CoV-2 have similar charge distributions and electrostatic features when binding with the human angiotensin-converting enzyme 2 (hACE2). Energy pH-dependence calculations revealed that the complex structures of hACE2 and the S proteins of SARS-CoV/SARS-CoV-2 are stable at pH values ranging from 7.5 to 9. Three independent 100 ns molecular dynamics (MD) simulations were performed using NAMD to investigate the hydrogen bonds between S proteins RBD and hACE2 RBD. From MD simulations, we found that SARS-CoV-2 forms 19 pairs (average of three simulations) of hydrogen bonds with high occupancy (>50%) to hACE2, compared to 16 pairs between SARS-CoV and hACE2. Additionally, SARS-CoV viruses prefer sticking to the same hydrogen bond pairs, while SARS-CoV-2 tends to have a larger range of selections on hydrogen bonds acceptors. We also labelled key residues involved in forming the top five hydrogen bonds that were found in all three independent 100 ns simulations. This identification is important to potential drug designs for COVID-19 treatments. Our work will shed the light on current and future coronavirus-caused diseases. Full article
(This article belongs to the Special Issue Computational Approaches to Understand the Mechanisms of Diseases at Molecular Level)
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11 pages, 1551 KiB  
Article
Insights into Temperature and Hypoxia Tolerance in Cowpea Weevil via HIF-1
by Qin Liu, Zhichao Liu, Zhipeng Gao, Guanjun Chen, Changyan Liu, Zhenghuang Wan, Chanyou Chen, Chen Zeng, Yunjie Zhao and Lei Pan
Pathogens 2021, 10(6), 704; https://doi.org/10.3390/pathogens10060704 - 5 Jun 2021
Cited by 1 | Viewed by 2302
Abstract
Cowpea weevil (Callosobruchus maculatus) is a major pest that leads to severe damage of the stored leguminous grains. Several management approaches, including physical barriers, biological or chemical methods, are used for controlling bruchid in cowpea. These methods usually target the metabolically [...] Read more.
Cowpea weevil (Callosobruchus maculatus) is a major pest that leads to severe damage of the stored leguminous grains. Several management approaches, including physical barriers, biological or chemical methods, are used for controlling bruchid in cowpea. These methods usually target the metabolically active state of weevil. However, it becomes less effective at early stages as egg, larva, or pupa under low temperature and oxygen conditions. Since hypoxia-inducible factor-1 (HIF-1) is known to coordinate multiple gene responses to low oxygen or low temperature signals, we examined the HIF-1α gene expression under low temperature and hypoxic treatments. At −20 °C, it took 4 h to reduce the survival rate for eggs, larvae, and pupae down to 10%, while at 4 °C and 15 °C, the survival rate remained higher than 50% even after 128 h as HIF-1α gene expression peaked at 15 °C. Moreover, HIF-1 protein offers a valuable target for early stage pest control complementary to traditional methods. In particular, HIF-1 inhibitor camptothecin (CPT), one of the five HIF-1 inhibitors examined, achieved a very significant reduction of 96.2% and 95.5% relative to the control in weevil survival rate into adult at 4 °C and 30 °C, respectively. Our study can be used as one model system for drug development in virus infections and human cancer. Full article
(This article belongs to the Special Issue Computational Approaches to Understand the Mechanisms of Diseases at Molecular Level)
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