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1.
biorxiv; 2022.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2022.06.29.498153

ABSTRACT

Mycobacterium tuberculosis ( Mtb ) is the causative agent of tuberculosis, a disease that claims ~1.5 million lives annually. The current treatment regime is long and expensive, and missed doses contribute to drug resistance. There is much to be understood about the Mtb cell envelope, a complicated barrier that antibiotics need to negotiate to enter the cell. Within this envelope, the plasma membrane is the ultimate obstacle and is proposed to be comprised of over 50% mannosylated phosphatidylinositol lipids (phosphatidyl- myo inositol mannosides, PIMs), whose role in the membrane structure remains elusive. Here we used multiscale molecular dynamics (MD) simulations to understand the structure-function relationship of the PIM lipid family and decipher how they self-organize to drive biophysical properties of the Mycobacterial plasma membrane. To validate the model, we tested known anti-tubercular drugs and replicated previous experimental results. Our results shed new light into the organization of the Mycobacterial plasma membrane and provides a working model of this complex membrane to use for in silico studies. This opens the door for new methods to probe potential antibiotic targets and further understand membrane protein function. Abstract Figure


Subject(s)
Tuberculosis , Genetic Diseases, Inborn
2.
biorxiv; 2021.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2021.06.23.449544

ABSTRACT

ABSTRACT A lipid nanoparticle (LNP) formulation is a state-of-the-art delivery system for genetic drugs such as DNA, mRNA, and siRNA, which is successfully applied to COVID-19 vaccines and gains tremendous interest in therapeutic applications. Despite its importance, a molecular-level understanding of the LNP structures and dynamics is still lacking, which makes a rational LNP design almost impossible. In this work, we present an extension of CHARMM-GUI Membrane Builder to model and simulate all-atom LNPs with various (ionizable) cationic lipids and PEGylated lipids (PEG-lipids). These new lipid types can be mixed with any existing lipid types with or without a biomolecule of interest, and the generated systems can be simulated using various molecular dynamics engines. As a first illustration, we considered model LNP membranes with DLin-KC2-DMA (KC2) or DLin-MC3-DMA (MC3) without PEG-lipids. The results from these model membranes are consistent with those from the two previous studies albeit with mild accumulation of neutral MC3 in the bilayer center. To demonstrate Membrane Builder ’s capability of building a realistic LNP patch, we generated KC2- or MC3-containing LNP membranes with high concentrations of cholesterol and ionizable cationic lipids together with 2 mol% PEG-lipids. We observe that PEG-chains are flexible, which can be more preferentially extended laterally in the presence of cationic lipids due to the attractive interactions between their head groups and PEG oxygen. The presence of PEG-lipids also relaxes the lateral packing in LNP membranes, and the area compressibility modulus ( K A ) of LNP membranes with cationic lipids fit into typical K A of fluid-phase membranes. Interestingly, the interactions between PEG oxygen and head group of ionizable cationic lipids induce a negative curvature. We hope that this LNP capability in Membrane Builder can be useful to better characterize various LNPs with or without genetic drugs for a rational LNP design.


Subject(s)
COVID-19
3.
biorxiv; 2021.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2021.05.10.443519

ABSTRACT

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents a public health crisis, and the vaccines that can induce highly potent neutralizing antibodies are essential for ending the pandemic. The spike (S) protein on the viral envelope mediates human angiotensin-converting enzyme 2 (ACE2) binding and thus is the target of a variety of neutralizing antibodies. In this work, we built various S trimer-antibody complex structures on the basis of the fully glycosylated S protein models described in our previous work, and performed all-atom molecular dynamics simulations to get insight into the structural dynamics and interactions between S protein and antibodies. Investigation of the residues critical for S-antibody binding allows us to predict the potential influence of mutations in SARS-CoV-2 variants. Comparison of the glycan conformations between S-only and S-antibody systems reveals the roles of glycans in S-antibody binding. In addition, we explored the antibody binding modes, and the influences of antibody on the motion of S protein receptor binding domains. Overall, our analyses provide a better understanding of S-antibody interactions, and the simulation-based S-antibody interaction maps could be used to predict the influences of S mutation on S-antibody interactions, which will be useful for the development of vaccine and antibody-based therapy.


Subject(s)
Coronavirus Infections , Severe Acute Respiratory Syndrome
4.
biorxiv; 2020.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2020.10.18.343715

ABSTRACT

The spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mediates host cell entry by binding to angiotensin-converting enzyme 2 (ACE2), and is considered the major target for drug and vaccine development. We previously built fully-glycosylated full-length SARS-CoV-2 S protein models in a viral membrane including both open and closed conformations of receptor binding domain (RBD) and different templates for the stalk region. In this work, multiple s-long all-atom molecular dynamics simulations were performed to provide deeper insight into the structure and dynamics of S protein, and glycan functions. Our simulations reveal that the highly flexible stalk is composed of two independent joints and most probable S protein orientations are competent for ACE2 binding. We identify multiple glycans stabilizing the open and/or closed states of RBD, and demonstrate that the exposure of antibody epitopes can be captured by detailed antibody-glycan clash analysis instead of a commonly-used accessible surface area analysis that tends to overestimate the impact of glycan shielding and neglect possible detailed interactions between glycan and antibody. Overall, our observations offer structural and dynamic insight into SARS-CoV-2 S protein and potentialize for guiding the design of effective antiviral therapeutics.

5.
biorxiv; 2020.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2020.05.20.103325

ABSTRACT

This technical study describes all-atom modeling and simulation of a fully-glycosylated full-length SARS-CoV-2 spike (S) protein in a viral membrane. First, starting from PDB:6VSB and 6VXX, full-length S protein structures were modeled using template-based modeling, de-novo protein structure prediction, and loop modeling techniques in GALAXY modeling suite. Then, using the recently-determined most occupied glycoforms, 22 N-glycans and 1 O-glycan of each monomer were modeled using Glycan Reader & Modeler in CHARMM-GUI. These fully-glycosylated full-length S protein model structures were assessed and further refined against the low-resolution data in their respective experimental maps using ISOLDE. We then used CHARMM-GUI Membrane Builder to place the S proteins in a viral membrane and performed all-atom molecular dynamics simulations. All structures are available in CHARMM-GUI COVID-19 Archive (http://www.charmm-gui.org/docs/archive/covid19), so researchers can use these models to carry out innovative and novel modeling and simulation research for the prevention and treatment of COVID-19.


Subject(s)
COVID-19
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