Investigating targets for neuropharmacological intervention by molecular dynamics simulations

2019 ◽  
Vol 47 (3) ◽  
pp. 909-918
Author(s):  
Giulia Rossetti ◽  
Achim Kless ◽  
Luhua Lai ◽  
Tiago F. Outeiro ◽  
Paolo Carloni

Abstract Medical research has identified over 500 brain disorders. Among these, there are still only very few neuropathologies whose causes are fully understood and, consequently, very few drugs whose mechanism of action is known. No FDA drug has been identified for major neurodegenerative diseases, such as Alzheimer's and Parkinson's. We still lack effective treatments and strategies for modulating progression or even early neurodegenerative disease onset diagnostic tools. A great support toward the highly needed identification of neuroactive drugs comes from computer simulation methods and, in particular, from molecular dynamics (MD). This provides insight into structure–function relationship of a target and predicts structure, dynamics and energetics of ligand/target complexes under biologically relevant conditions like temperature and physiological saline concentration. Here, we present examples of the predictive power of MD for neuroactive ligands/target complexes. This brief survey from our own research shows the usefulness of partnerships between academia and industry, and from joint efforts between experimental and theoretical groups.

2020 ◽  
Vol 21 (17) ◽  
pp. 6339
Author(s):  
Raudah Lazim ◽  
Donghyuk Suh ◽  
Sun Choi

Molecular dynamics (MD) simulation is a rigorous theoretical tool that when used efficiently could provide reliable answers to questions pertaining to the structure-function relationship of proteins. Data collated from protein dynamics can be translated into useful statistics that can be exploited to sieve thermodynamics and kinetics crucial for the elucidation of mechanisms responsible for the modulation of biological processes such as protein-ligand binding and protein-protein association. Continuous modernization of simulation tools enables accurate prediction and characterization of the aforementioned mechanisms and these qualities are highly beneficial for the expedition of drug development when effectively applied to structure-based drug design (SBDD). In this review, current all-atom MD simulation methods, with focus on enhanced sampling techniques, utilized to examine protein structure, dynamics, and functions are discussed. This review will pivot around computer calculations of protein-ligand and protein-protein systems with applications to SBDD. In addition, we will also be highlighting limitations faced by current simulation tools as well as the improvements that have been made to ameliorate their efficiency.


Author(s):  
Mohamed Naji ◽  
Othman El Kssiri ◽  
Sandra Ory ◽  
Aurélien Canizares ◽  
Mohammed Filali ◽  
...  

Based on a combination of molecular dynamics simulations, Raman and Brillouin light scattering spectroscopies, we investigate the structure and elastic properties relationship in an archetypical calcium silicate glass system. From...


RSC Advances ◽  
2021 ◽  
Vol 11 (15) ◽  
pp. 8718-8729
Author(s):  
Jixue Sun ◽  
Meijiang Liu ◽  
Na Yang

The origin of SARS-CoV-2 through structural analysis of receptor recognition was investigated by molecular dynamics simulations.


Molecules ◽  
2021 ◽  
Vol 26 (3) ◽  
pp. 721
Author(s):  
Srinivasaraghavan Kannan ◽  
Pietro G. A. Aronica ◽  
Thanh Binh Nguyen ◽  
Jianguo Li ◽  
Chandra S. Verma

S100B(ββ) proteins are a family of multifunctional proteins that are present in several tissues and regulate a wide variety of cellular processes. Their altered expression levels have been associated with several human diseases, such as cancer, inflammatory disorders and neurodegenerative conditions, and hence are of interest as a therapeutic target and a biomarker. Small molecule inhibitors of S100B(ββ) have achieved limited success. Guided by the wealth of available experimental structures of S100B(ββ) in complex with diverse peptides from various protein interacting partners, we combine comparative structural analysis and molecular dynamics simulations to design a series of peptides and their analogues (stapled) as S100B(ββ) binders. The stapled peptides were subject to in silico mutagenesis experiments, resulting in optimized analogues that are predicted to bind to S100B(ββ) with high affinity, and were also modified with imaging agents to serve as diagnostic tools. These stapled peptides can serve as theranostics, which can be used to not only diagnose the levels of S100B(ββ) but also to disrupt the interactions of S100B(ββ) with partner proteins which drive disease progression, thus serving as novel therapeutics.


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