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Molecular Structure and Simulation: Unraveling the Basis of Disease
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Molecular Structure and Simulation: Unraveling the Basis of Disease

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Biophysics".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 6536

Special Issue Editor

Dr. Paulino Gómez-Puertas

E-Mail Website
Guest Editor
Molecular Modeling Group, Centro de Biologia Molecular Severo Ochoa (CBM, CSIC-UAM). CL Nicolas Cabrera, 1. Campus UAM, 28049 Madrid, Spain
Interests: computational biology; molecular dynamics; rare diseases; antimicrobials; antivirals; cancer
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Structural information at the atomic scale of macromolecules allows a precise understanding of the mechanisms underlying different types of diseases, including infectious diseases (viral, bacterial, or parasitic), disorders such as cancer, and others of genetic origin (e.g., rare diseases).

Knowledge of this information, as well as techniques capable of computationally simulating the movement of these macromolecules in their cellular environment, helps us to rationalize the causes of diseases and to design possible treatments. In the case of diseases caused by pathogens, the structural information of key enzymes in the functioning of these viruses, bacteria, or eukaryotic parasites allows us to know how these pathogens function, and to design specific ligands that can later give rise to new drugs.

This Special Issue welcomes papers using 3D molecular structure and/or virtual modeling techniques in computational biology, alone or in combination with in vitro or in vivo strategies. The aim of these techniques may be the characterization and therapy of diseases, including cancers, genetic diseases, or those related to viral or bacterial infections. We also welcome papers addressing 3D screening strategies and the design of new drugs and therapies.

Dr. Paulino Gómez-Puertas
Guest Editor

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Keywords

  • macromolecular structure
  • computational biology
  • drug design
  • molecular dynamics
  • genetic diseases
  • virus infection
  • antimicrobials
  • antibiotic resistance

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Published Papers (3 papers)

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24 pages, 15573 KiB  
Article
Structural and pKa Estimation of the Amphipathic HR1 in SARS-CoV-2: Insights from Constant pH MD, Linear vs. Nonlinear Normal Mode Analysis
by Dayanara Lissette Yánez Arcos and Saravana Prakash Thirumuruganandham
Int. J. Mol. Sci. 2023, 24(22), 16190; https://doi.org/10.3390/ijms242216190 - 10 Nov 2023
Viewed by 1398
Abstract
A comprehensive understanding of molecular interactions and functions is imperative for unraveling the intricacies of viral protein behavior and conformational dynamics during cellular entry. Focusing on the SARS-CoV-2 spike protein (SARS-CoV-2 sp), a Principal Component Analysis (PCA) on a subset comprising 131 A-chain [...] Read more.
A comprehensive understanding of molecular interactions and functions is imperative for unraveling the intricacies of viral protein behavior and conformational dynamics during cellular entry. Focusing on the SARS-CoV-2 spike protein (SARS-CoV-2 sp), a Principal Component Analysis (PCA) on a subset comprising 131 A-chain structures in presence of various inhibitors was conducted. Our analyses unveiled a compelling correlation between PCA modes and Anisotropic Network Model (ANM) modes, underscoring the reliability and functional significance of low-frequency modes in adapting to diverse inhibitor binding scenarios. The role of HR1 in viral processing, both linear Normal Mode Analysis (NMA) and Nonlinear NMA were implemented. Linear NMA exhibited substantial inter-structure variability, as evident from a higher Root Mean Square Deviation (RMSD) range (7.30 Å), nonlinear NMA show stability throughout the simulations (RMSD 4.85 Å). Frequency analysis further emphasized that the energy requirements for conformational changes in nonlinear modes are notably lower compared to their linear counterparts. Using simulations of molecular dynamics at constant pH (cpH-MD), we successfully predicted the pKa order of the interconnected residues within the HR1 mutations at lower pH values, suggesting a transition to a post-fusion structure. The pKa determination study illustrates the profound effects of pH variations on protein structure. Key results include pKa values of 9.5179 for lys-921 in the D936H mutant, 9.50 for the D950N mutant, and a slightly higher value of 10.49 for the D936Y variant. To further understand the behavior and physicochemical characteristics of the protein in a biologically relevant setting, we also examine hydrophobic regions in the prefused states of the HR1 protein mutants D950N, D936Y, and D936H in our study. This analysis was conducted to ascertain the hydrophobic moment of the protein within a lipid environment, shedding light on its behavior and physicochemical properties in a biologically relevant context. Full article
(This article belongs to the Special Issue Molecular Structure and Simulation: Unraveling the Basis of Disease)
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16 pages, 4413 KiB  
Article
Mechanistic Investigation of the Androgen Receptor DNA-Binding Domain and Modulation via Direct Interactions with DNA Abasic Sites: Understanding the Mechanisms Involved in Castration-Resistant Prostate Cancer
by Shangze Xu, Matthew D. Kondal, Ayaz Ahmad, Ruidi Zhu, Lanyu Fan, Piotr Zaborniak, Katrina S. Madden, João V. de Souza and Agnieszka K. Bronowska
Int. J. Mol. Sci. 2023, 24(2), 1270; https://doi.org/10.3390/ijms24021270 - 9 Jan 2023
Cited by 4 | Viewed by 2564
Abstract
The androgen receptor (AR) is an important drug target in prostate cancer and a driver of castration-resistant prostate cancer (CRPC). A significant challenge in designing effective drugs lies in targeting constitutively active AR variants and, most importantly, nearly all AR variants lacking the [...] Read more.
The androgen receptor (AR) is an important drug target in prostate cancer and a driver of castration-resistant prostate cancer (CRPC). A significant challenge in designing effective drugs lies in targeting constitutively active AR variants and, most importantly, nearly all AR variants lacking the ligand-binding domain (LBD). Recent findings show that an AR’s constitutive activity may occur in the presence of somatic DNA mutations within non-coding regions, but the role of these mutations remains elusive. The discovery of new drugs targeting CRPC is hampered by the limited molecular understanding of how AR binds mutated DNA sequences, frequently observed in prostate cancer, and how mutations within the protein and DNA regulate AR-DNA interactions. Using atomistic molecular dynamics (MD) simulations and quantum mechanical calculations, we focused our efforts on (i) rationalising the role of several activating DBD mutations linked to prostate cancer, and (ii) DBD interactions in the presence of abasic DNA lesions, which frequently occur in CRPC. Our results elucidate the role of mutations within DBD through their modulation of the intrinsic dynamics of the DBD-DNA ternary complex. Furthermore, our results indicate that the DNA apurinic lesions occurring in the androgen-responsive element (ARE) enhance direct AR-DNA interactions and stabilise the DBD homodimerisation interface. Moreover, our results strongly suggest that those abasic lesions may form reversible covalent crosslinks between DNA and lysine residues of an AR via a Schiff base. In addition to providing an atomistic model explaining how protein mutations within the AR DNA-binding domain affect AR dimerisation and AR-DNA interactions, our findings provide insight into how somatic mutations occurring in DNA non-coding regions may activate ARs. These mutations are frequently observed in prostate cancer and may contribute to disease progression by enhancing direct AR-DNA interactions. Full article
(This article belongs to the Special Issue Molecular Structure and Simulation: Unraveling the Basis of Disease)
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Other

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6 pages, 10789 KiB  
Commentary
Computational Modeling and Design of New Inhibitors of Carbapenemases: A Discussion from the EPIC Alliance Network
by Elias Dahdouh, Lisa Allander, Linda Falgenhauer, Bogdan I. Iorga, Stefano Lorenzetti, Íñigo Marcos-Alcalde, Nathaniel I. Martin, Luis Martínez-Martínez, Jesús Mingorance, Thierry Naas, Joseph E. Rubin, Francesca Spyrakis, Thomas Tängdén and Paulino Gómez-Puertas
Int. J. Mol. Sci. 2022, 23(17), 9746; https://doi.org/10.3390/ijms23179746 - 28 Aug 2022
Viewed by 1949
Abstract
The EPIC consortium brings together experts from a wide range of fields that include clinical, molecular and basic microbiology, infectious diseases, computational biology and chemistry, drug discovery and design, bioinformatics, biochemistry, biophysics, pharmacology, toxicology, veterinary sciences, environmental sciences, and epidemiology. The main question [...] Read more.
The EPIC consortium brings together experts from a wide range of fields that include clinical, molecular and basic microbiology, infectious diseases, computational biology and chemistry, drug discovery and design, bioinformatics, biochemistry, biophysics, pharmacology, toxicology, veterinary sciences, environmental sciences, and epidemiology. The main question to be answered by the EPIC alliance is the following: “What is the best approach for data mining on carbapenemase inhibitors and how to translate this data into experiments?” From this forum, we propose that the scientific community think up new strategies to be followed for the discovery of new carbapenemase inhibitors, so that this process is efficient and capable of providing results in the shortest possible time and within acceptable time and economic costs. Full article
(This article belongs to the Special Issue Molecular Structure and Simulation: Unraveling the Basis of Disease)
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