Study of the Rv1417 and Rv2617c Membrane Proteins and Their Interactions with Nicotine Derivatives as Potential Inhibitors of Erp Virulence-Associated Factor in Mycobacterium tuberculosis: An In Silico Approach

Aguilar-Pineda, Jorge Alberto; Febres-Molina, Camilo; Cordova-Barrios, Cinthia C.; Campos-Olazával, Lizbeth M.; Del-Carpio-M, Bruno A.; Ayqui-Cueva, Flor; Gamero-Begazo, Pamela L.; Gómez, Badhin

doi:10.3390/biom13020248

Cited by 3 publications

(1 citation statement)

References 89 publications

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“…The lowest densities occurred in the TIP4P/ϵ flex system, meaning a greater distribution of lipids along the z -axis and, consequently, a greater membrane thickness. These values are consistent with previous in-silico studies, which used the DPPC membrane and SPC, SPC/E, and TIP4P water models at temperatures close to 310 K. − …”

Section: Resultssupporting

confidence: 91%

Influence of the Water Model on the Structure and Interactions of the GPR40 Protein with the Lipid Membrane and the Solvent: Rigid versus Flexible Water Models

Aguilar-Pineda,

González-Melchor

2024

J. Chem. Theory Comput.

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G protein-coupled receptors (GPCR) are responsible for modulating various physiological functions and are thus related to the pathophysiology of different diseases. Being potential therapeutic targets, multiple computational methodologies have been developed to analyze their behavior and interactions with other species. The solvent, on the other hand, has received much less attention. In this work, we analyzed the effect of four explicit water models on the structure and interactions of the GPR40 receptor in its apo form. We employed the rigid SPC/E and TIP4P models, and their flexible versions, the FBA/ϵ and TIP4P/ϵ flex . We explored the structural changes and their correlation with some bulk dynamic properties of water. Our results showed an adverse effect on the conservation of the secondary structure of the receptor with all the models due to the breaking of the intramolecular hydrogen bond network, being more evident for the TIP4P models. Notably, all four models brought the receptor to states similar to the active one, modifying the intracellular part of the TM5 and TM6 domains in a "hinge" type movement, allowing the opening of the structure. Regarding the dynamic properties, the rigid models showed results comparable to those obtained in other studies on membrane systems. However, flexible models exhibit disparities in the molecular representation of systems. Surprisingly, the FBA/ϵ model improves the molecular picture of several properties, even though their agreement with bulk diffusion is poorer. These findings reinforce our idea that exploring other water models or improving the current ones, to better represent the membrane interface, can lead to a positive impact on the description of the signal transduction mechanisms and the search of new drugs by targeting these receptors.

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Section: Resultssupporting

confidence: 91%

Influence of the Water Model on the Structure and Interactions of the GPR40 Protein with the Lipid Membrane and the Solvent: Rigid versus Flexible Water Models

Aguilar-Pineda,

González-Melchor

2024

J. Chem. Theory Comput.

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Modulators targeting protein-protein interactions in Mycobacterium tuberculosis

Luo,

Ming,

Yang

et al. 2024

Microbiological Research

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Advances in computational frameworks in the fight against TB: The way forward

Naidu

Nayak

et al. 2023

Front. Pharmacol.

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Around 1.6 million people lost their life to Tuberculosis in 2021 according to WHO estimates. Although an intensive treatment plan exists against the causal agent, Mycobacterium Tuberculosis, evolution of multi-drug resistant strains of the pathogen puts a large number of global populations at risk. Vaccine which can induce long-term protection is still in the making with many candidates currently in different phases of clinical trials. The COVID-19 pandemic has further aggravated the adversities by affecting early TB diagnosis and treatment. Yet, WHO remains adamant on its “End TB” strategy and aims to substantially reduce TB incidence and deaths by the year 2035. Such an ambitious goal would require a multi-sectoral approach which would greatly benefit from the latest computational advancements. To highlight the progress of these tools against TB, through this review, we summarize recent studies which have used advanced computational tools and algorithms for—early TB diagnosis, anti-mycobacterium drug discovery and in the designing of the next-generation of TB vaccines. At the end, we give an insight on other computational tools and Machine Learning approaches which have successfully been applied in biomedical research and discuss their prospects and applications against TB.

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Study of the Rv1417 and Rv2617c Membrane Proteins and Their Interactions with Nicotine Derivatives as Potential Inhibitors of Erp Virulence-Associated Factor in Mycobacterium tuberculosis: An In Silico Approach

Cited by 3 publications

References 89 publications

Influence of the Water Model on the Structure and Interactions of the GPR40 Protein with the Lipid Membrane and the Solvent: Rigid versus Flexible Water Models

Influence of the Water Model on the Structure and Interactions of the GPR40 Protein with the Lipid Membrane and the Solvent: Rigid versus Flexible Water Models

Modulators targeting protein-protein interactions in Mycobacterium tuberculosis

Advances in computational frameworks in the fight against TB: The way forward

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