scholarly journals Deciphering complex mechanisms of resistance and loss of potency through coupled molecular dynamics and machine learning.

2020 ◽  
Author(s):  
Florian Leidner ◽  
Nese Kurt-Yilmaz ◽  
Celia A Schiffer
Keyword(s):  
Machine Learning ◽  
Molecular Dynamics ◽  
Drug Resistance ◽  
Active Site ◽  
Molecular Mechanisms ◽  
Learning Strategy ◽  
Drug Binding ◽  
Feature Reduction ◽  
Rigorous Model ◽  
Dynamics Simulations

Drug resistance threatens many critical therapeutics through mutations in the drug target. The molecular mechanisms by which combinations of mutations, especially involving those distal from the active site, alter drug binding to confer resistance are poorly understood and thus difficult to counteract. A machine learning strategy was developed that couples parallel molecular dynamics simulations and experimental potency to identify specific conserved mechanisms underlying resistance. A series of 28 HIV-1 protease variants with 0-24 substitutions each were used as a rigorous model of this strategy. Many of the mutations were distal from the active site and the potency of variants to a drug (darunavir) varied from low picomolar to near micromolar. With features extracted from the simulations, elastic network machine learning was applied to correlate physical interactions with loss of potency and succeeded to within 1 kcal/mol of experimental affinity for both the training and test sets, outperforming MM/GBSA calculations. Feature reduction resulted in a model with 4 specific features that describe interactions critical for potency for all 28 variants. These predictive features, that specifically vary with potency, occur throughout the enzyme and would not have been identified without dynamics and machine learning. This strategy thus captures the conserved dynamic mechanisms by which complex combinations of mutations confer resistance and identifies critical features that serve as bellwethers of loss of inhibitor potency. Machine learning models leveraging molecular dynamics can thus elucidate mechanisms of drug resistance that confer loss of affinity and will serve as predictive tools in future drug design.

scholarly journals Structural Basis for Antiarrhythmic Drug Interactions with the Human Cardiac Sodium Channel

2018 ◽  
Author(s):  
Phuong T. Nguyen ◽  
Kevin R. DeMarco ◽  
Igor Vorobyov ◽  
Colleen E. Clancy ◽  
Vladimir Yarov-Yarovoy
Keyword(s):  
Molecular Dynamics ◽  
Drug Interactions ◽  
Sodium Channel ◽  
Molecular Dynamics Simulations ◽  
Local Anesthetic ◽  
Molecular Mechanisms ◽  
Drug Binding ◽  
Structural Basis ◽  
Dynamics Simulations ◽  
Access Pathway

AbstractThe human voltage-gated sodium channel, hNav1.5, is responsible for the rapid upstroke of the cardiac action potential and is target for antiarrhythmic therapy. Despite the clinical relevance of hNav1.5 targeting drugs, structure-based molecular mechanisms of promising or problematic drugs have not been investigated at atomic scale to inform drug design. Here, we used Rosetta structural modeling and docking as well as molecular dynamics simulations to study the interactions of antiarrhythmic and local anesthetic drugs with hNav1.5. These calculations revealed several key drug binding sites formed within the pore lumen that can simultaneously accommodate up to two drug molecules. Molecular dynamics simulations identified a hydrophilic access pathway through the intracellular gate and a hydrophobic access pathway through a fenestration between domains III and IV. Our results advance the understanding of molecular mechanisms of antiarrhythmic and local anesthetic drug interactions with hNav1.5 and will be useful for rational design of novel therapeutics.

scholarly journals Structural basis for antiarrhythmic drug interactions with the human cardiac sodium channel

2019 ◽  
Vol 116 (8) ◽  
pp. 2945-2954 ◽  
Author(s):  
Phuong T. Nguyen ◽  
Kevin R. DeMarco ◽  
Igor Vorobyov ◽  
Colleen E. Clancy ◽  
Vladimir Yarov-Yarovoy
Keyword(s):  
Molecular Dynamics ◽  
Drug Interactions ◽  
Sodium Channel ◽  
Molecular Dynamics Simulations ◽  
Local Anesthetic ◽  
Molecular Mechanisms ◽  
Drug Binding ◽  
Structural Basis ◽  
Dynamics Simulations ◽  
Access Pathway

The human voltage-gated sodium channel, hNaV1.5, is responsible for the rapid upstroke of the cardiac action potential and is target for antiarrhythmic therapy. Despite the clinical relevance of hNaV1.5-targeting drugs, structure-based molecular mechanisms of promising or problematic drugs have not been investigated at atomic scale to inform drug design. Here, we used Rosetta structural modeling and docking as well as molecular dynamics simulations to study the interactions of antiarrhythmic and local anesthetic drugs with hNaV1.5. These calculations revealed several key drug binding sites formed within the pore lumen that can simultaneously accommodate up to two drug molecules. Molecular dynamics simulations identified a hydrophilic access pathway through the intracellular gate and a hydrophobic access pathway through a fenestration between DIII and DIV. Our results advance the understanding of molecular mechanisms of antiarrhythmic and local anesthetic drug interactions with hNaV1.5 and will be useful for rational design of novel therapeutics.

Use of Molecular Dynamics Simulations in Structure-Based Drug Discovery

2019 ◽  
Vol 25 (31) ◽  
pp. 3339-3349 ◽  
Author(s):  
Indrani Bera ◽  
Pavan V. Payghan
Keyword(s):  
Molecular Dynamics ◽  
Drug Discovery ◽  
Molecular Dynamics Simulations ◽  
Drug Target ◽  
Structural Information ◽  
Drug Binding ◽  
Structure Based Drug Design ◽  
Drug Designing ◽  
Target Binding ◽  
Dynamics Simulations

Background: Traditional drug discovery is a lengthy process which involves a huge amount of resources. Modern-day drug discovers various multidisciplinary approaches amongst which, computational ligand and structure-based drug designing methods contribute significantly. Structure-based drug designing techniques require the knowledge of structural information of drug target and drug-target complexes. Proper understanding of drug-target binding requires the flexibility of both ligand and receptor to be incorporated. Molecular docking refers to the static picture of the drug-target complex(es). Molecular dynamics, on the other hand, introduces flexibility to understand the drug binding process. Objective: The aim of the present study is to provide a systematic review on the usage of molecular dynamics simulations to aid the process of structure-based drug design. Method: This review discussed findings from various research articles and review papers on the use of molecular dynamics in drug discovery. All efforts highlight the practical grounds for which molecular dynamics simulations are used in drug designing program. In summary, various aspects of the use of molecular dynamics simulations that underline the basis of studying drug-target complexes were thoroughly explained. Results: This review is the result of reviewing more than a hundred papers. It summarizes various problems that use molecular dynamics simulations. Conclusion: The findings of this review highlight how molecular dynamics simulations have been successfully implemented to study the structure-function details of specific drug-target complexes. It also identifies the key areas such as stability of drug-target complexes, ligand binding kinetics and identification of allosteric sites which have been elucidated using molecular dynamics simulations.

WHICH IS THE PROTON-SHUTTLE IN ISOXANTHOPTERIN DEAMINASE? QM/MM MD UNDERSTANDING

2013 ◽  
Vol 12 (08) ◽  
pp. 1341002 ◽  
Author(s):  
XIN ZHANG ◽  
MING LEI
Keyword(s):  
Crystal Structure ◽  
Molecular Dynamics ◽  
Hydrogen Bonds ◽  
Proton Transfer ◽  
Glutamic Acid ◽  
Active Site ◽  
Nucleophilic Attack ◽  
Zinc Ions ◽  
Initial Model ◽  
Dynamics Simulations

The deamination process of isoxanthopterin catalyzed by isoxanthopterin deaminase was determined using the combined QM(PM3)/MM molecular dynamics simulations. In this paper, the updated PM3 parameters were employed for zinc ions and the initial model was built up based on the crystal structure. Proton transfer and following steps have been investigated in two paths: Asp336 and His285 serve as the proton shuttle, respectively. Our simulations showed that His285 is more effective than Aap336 in proton transfer for deamination of isoxanthopterin. As hydrogen bonds between the substrate and surrounding residues play a key role in nucleophilic attack, we suggested mutating Thr195 to glutamic acid, which could enhance the hydrogen bonds and help isoxanthopterin get close to the active site. The simulations which change the substrate to pterin 6-carboxylate also performed for comparison. Our results provide reference for understanding of the mechanism of deaminase and for enhancing the deamination rate of isoxanthopterin deaminase.

Machine learning and molecular dynamics simulations assisted evolutionary design and discovery pipeline to screen the efficient small molecule acceptors for PTB7-Th based organic solar cells with over 15% efficiency

2022 ◽  
Author(s):  
Jin-Liang Wang ◽  
Asif Mahmood ◽  
Ahmad Irfan
Keyword(s):  
Machine Learning ◽  
Molecular Dynamics ◽  
Solar Cells ◽  
Molecular Dynamics Simulations ◽  
Small Molecule ◽  
Organic Solar Cells ◽  
Evolutionary Design ◽  
New Materials ◽  
Dynamics Simulations ◽  
Discovery Pipeline

Organic solar cells are the most promising candidates for future commercialization. This goal can be quickly achieved by designing new materials and predicting their performance without experimentation to reduce the...

scholarly journals Exploiting correlated molecular-dynamics networks to counteract enzyme activity–stability trade-off

2018 ◽  
Vol 115 (52) ◽  
pp. E12192-E12200 ◽  
Author(s):  
Haoran Yu ◽  
Paul A. Dalby
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Active Site ◽  
Dynamic Networks ◽  
Aromatic Aldehydes ◽  
Active Site Residues ◽  
Trade Off ◽  
Highly Correlated ◽  
Dynamics Simulations ◽  
The Impact

The directed evolution of enzymes for improved activity or substrate specificity commonly leads to a trade-off in stability. We have identified an activity–stability trade-off and a loss in unfolding cooperativity for a variant (3M) of Escherichia coli transketolase (TK) engineered to accept aromatic substrates. Molecular dynamics simulations of 3M revealed increased flexibility in several interconnected active-site regions that also form part of the dimer interface. Mutating the newly flexible active-site residues to regain stability risked losing the new activity. We hypothesized that stabilizing mutations could be targeted to residues outside of the active site, whose dynamics were correlated with the newly flexible active-site residues. We previously stabilized WT TK by targeting mutations to highly flexible regions. These regions were much less flexible in 3M and would not have been selected a priori as targets using the same strategy based on flexibility alone. However, their dynamics were highly correlated with the newly flexible active-site regions of 3M. Introducing the previous mutations into 3M reestablished the WT level of stability and unfolding cooperativity, giving a 10.8-fold improved half-life at 55 °C, and increased midpoint and aggregation onset temperatures by 3 °C and 4.3 °C, respectively. Even the activity toward aromatic aldehydes increased up to threefold. Molecular dynamics simulations confirmed that the mutations rigidified the active-site via the correlated network. This work provides insights into the impact of rigidifying mutations within highly correlated dynamic networks that could also be useful for developing improved computational protein engineering strategies.

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