The Impact of Active Site Mutations of South African HIV PR on Drug Resistance: Insight from Molecular Dynamics Simulations, Binding Free Energy and Per-Residue Footprints

2014 ◽  
Vol 83 (4) ◽  
pp. 472-481 ◽  
Author(s):  
Shaimaa M. Ahmed ◽  
Glenn E. M. Maguire ◽  
Hendrik G. Kruger ◽  
Thirumala Govender
Keyword(s):  
Molecular Dynamics ◽  
Drug Resistance ◽  
Free Energy ◽  
Molecular Dynamics Simulations ◽  
South African ◽  
Active Site ◽  
Binding Free Energy ◽  
Dynamics Simulations ◽  
The Impact ◽  
Active Site Mutations

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.

Molecular dynamics simulations and binding free energy analysis of DNA minor groove complexes of curcumin

2011 ◽  
Vol 17 (11) ◽  
pp. 2805-2816 ◽  
Author(s):  
Mathew Varghese Koonammackal ◽  
Unnikrishnan Viswambharan Nair Nellipparambil ◽  
Chellappanpillai Sudarsanakumar
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Dynamics Simulations ◽  
Energy Analysis ◽  
Binding Free Energy ◽  
Minor Groove ◽  
Dna Minor Groove ◽  
Dynamics Simulations ◽  
Free Energy Analysis

scholarly journals How quickly can we predict trimethoprim resistance using alchemical free energy methods?

2020 ◽  
Vol 10 (6) ◽  
pp. 20190141
Author(s):  
Philip W. Fowler
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Dynamics Simulations ◽  
Clinical Microbiology ◽  
Binding Free Energy ◽  
Single Mutation ◽  
Energy Methods ◽  
Synonymous Mutations ◽  
Dynamics Simulations ◽  
Alchemical Free Energy

The emergence of antimicrobial resistance threatens modern medicine and necessitates more personalized treatment of bacterial infections. Sequencing the whole genome of the pathogen(s) in a clinical sample offers one way to improve clinical microbiology diagnostic services, and has already been adopted for tuberculosis in some countries. A key weakness of a genetics clinical microbiology is it cannot return a result for rare or novel genetic variants and therefore predictive methods are required. Non-synonymous mutations in the S. aureus dfrB gene can be successfully classified as either conferring resistance (or not) by calculating their effect on the binding free energy of the antibiotic, trimethoprim. The underlying approach, alchemical free energy methods, requires large numbers of molecular dynamics simulations to be run. We show that a large number ( N = 15) of binding free energies calculated from a series of very short (50 ps) molecular dynamics simulations are able to satisfactorily classify all seven mutations in our clinically derived testset. A result for a single mutation could therefore be returned in less than an hour, thereby demonstrating that this or similar methods are now sufficiently fast and reproducible for clinical use.

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