scholarly journals Microscopic Characterization of the Chloride Permeation Pathway in the Human Excitatory Amino Acid Transporter 1 (EAAT1)

2021 ◽  
Author(s):  
Shashank Pant ◽  
Qianyi Wu ◽  
Renae M Ryan ◽  
Emad Tajkhorshid
Keyword(s):  
Free Energy ◽  
Amino Acid ◽  
Conformational Changes ◽  
Large Scale ◽  
Excitatory Amino Acid ◽  
Free Energy Calculations ◽  
Amino Acid Transporters ◽  
Coupled Transport ◽  
Energy Calculations ◽  
Transport Cycle

Excitatory amino acid transporters (EAATs) are glutamate transporters that belong to the solute carrier 1A (SLC1A) family. They couple glutamate transport to the co-transport of three sodium (Na+) ions and one proton (H+) and the counter-transport of one potassium (K+) ion. In addition to this coupled transport, binding of substrate and Na+ ions to EAATs activates a thermodynamically uncoupled chloride (Cl-) conductance. Structures of SLC1A family members have revealed that these transporters use a twisting elevator mechanism of transport, where a mobile transport domain carries substrate and coupled ions across the membrane, while a static scaffold domain anchors the transporter in the membrane. We have recently demonstrated that the uncoupled Cl- conductance is activated by the formation of an aqueous pore at the domain interface during the transport cycle in archaeal GltPh. However, a pathway for the uncoupled Cl- conductance has not been reported for the EAATs and it is unclear if such a pathway is conserved. Here, we employ all-atom molecular dynamics (MD) simulations combined with enhanced sampling, free-energy calculations, and experimental mutagenesis to approximate large-scale conformational changes during the transport process and identified a Cl- conducting conformation in human EAAT1. We were able to extensively sample the large-scale structural transitions, allowing us to capture an intermediate conformation formed during the transport cycle with a continuous aqueous pore at the domain interface. The free-energy calculations performed for the conduction of Cl- and Na+ ions through the captured conformation, highlight the presence of two hydrophobic gates which control the selective movement of Cl- through the aqueous pathway. Overall, our findings provide insights into the mechanism by which a human glutamate transporter can support the dual functions of active transport and passive Cl- permeation and confirming the commonality of this mechanism in different members of the SLC1A family.

Reaction-based Enumeration, Active Learning, and Free Energy Calculations to Rapidly Explore Synthetically Tractable Chemical Space and Optimize Potency of Cyclin Dependent Kinase 2 Inhibitors

2019 ◽  
Author(s):  
Kyle Konze ◽  
Pieter Bos ◽  
Markus Dahlgren ◽  
Karl Leswing ◽  
Ivan Tubert-Brohman ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Active Learning ◽  
Large Scale ◽  
Chemical Space ◽  
Population Based ◽  
Free Energy Calculations ◽  
Computational Technique ◽  
Cyclin Dependent Kinase ◽  
Energy Calculations

We report a new computational technique, PathFinder, that uses retrosynthetic analysis followed by combinatorial synthesis to generate novel compounds in synthetically accessible chemical space. Coupling PathFinder with active learning and cloud-based free energy calculations allows for large-scale potency predictions of compounds on a timescale that impacts drug discovery. The process is further accelerated by using a combination of population-based statistics and active learning techniques. Using this approach, we rapidly optimized R-groups and core hops for inhibitors of cyclin-dependent kinase 2. We explored greater than 300 thousand ideas and identified 35 ligands with diverse commercially available R-groups and a predicted IC<sub>50</sub> < 100 nM, and four unique cores with a predicted IC<sub>50</sub> < 100 nM. The rapid turnaround time, and scale of chemical exploration, suggests that this is a useful approach to accelerate the discovery of novel chemical matter in drug discovery campaigns.

Reaction-based Enumeration, Active Learning, and Free Energy Calculations to Rapidly Explore Synthetically Tractable Chemical Space and Optimize Potency of Cyclin Dependent Kinase 2 Inhibitors

2019 ◽  
Author(s):  
Kyle Konze ◽  
Pieter Bos ◽  
Markus Dahlgren ◽  
Karl Leswing ◽  
Ivan Tubert-Brohman ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Active Learning ◽  
Large Scale ◽  
Chemical Space ◽  
Population Based ◽  
Free Energy Calculations ◽  
Computational Technique ◽  
Cyclin Dependent Kinase ◽  
Energy Calculations

We report a new computational technique, PathFinder, that uses retrosynthetic analysis followed by combinatorial synthesis to generate novel compounds in synthetically accessible chemical space. Coupling PathFinder with active learning and cloud-based free energy calculations allows for large-scale potency predictions of compounds on a timescale that impacts drug discovery. The process is further accelerated by using a combination of population-based statistics and active learning techniques. Using this approach, we rapidly optimized R-groups and core hops for inhibitors of cyclin-dependent kinase 2. We explored greater than 300 thousand ideas and identified 35 ligands with diverse commercially available R-groups and a predicted IC<sub>50</sub> < 100 nM, and four unique cores with a predicted IC<sub>50</sub> < 100 nM. The rapid turnaround time, and scale of chemical exploration, suggests that this is a useful approach to accelerate the discovery of novel chemical matter in drug discovery campaigns.

Reaction-based Enumeration, Active Learning, and Free Energy Calculations to Rapidly Explore Synthetically Tractable Chemical Space and Optimize Potency of Cyclin Dependent Kinase 2 Inhibitors

2019 ◽  
Author(s):  
Kyle Konze ◽  
Pieter Bos ◽  
Markus Dahlgren ◽  
Karl Leswing ◽  
Ivan Tubert-Brohman ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Active Learning ◽  
Large Scale ◽  
Chemical Space ◽  
Population Based ◽  
Free Energy Calculations ◽  
Computational Technique ◽  
Cyclin Dependent Kinase ◽  
Energy Calculations

We report a new computational technique, PathFinder, that uses retrosynthetic analysis followed by combinatorial synthesis to generate novel compounds in synthetically accessible chemical space. Coupling PathFinder with active learning and cloud-based free energy calculations allows for large-scale potency predictions of compounds on a timescale that impacts drug discovery. The process is further accelerated by using a combination of population-based statistics and active learning techniques. Using this approach, we rapidly optimized R-groups and core hops for inhibitors of cyclin-dependent kinase 2. We explored greater than 300 thousand ideas and identified 35 ligands with diverse commercially available R-groups and a predicted IC<sub>50</sub> < 100 nM, and four unique cores with a predicted IC<sub>50</sub> < 100 nM. The rapid turnaround time, and scale of chemical exploration, suggests that this is a useful approach to accelerate the discovery of novel chemical matter in drug discovery campaigns.

scholarly journals Large scale free energy calculations for blind predictions of protein–ligand binding: the D3R Grand Challenge 2015

2016 ◽  
Vol 30 (9) ◽  
pp. 743-751 ◽  
Author(s):  
Nanjie Deng ◽  
William F. Flynn ◽  
Junchao Xia ◽  
R. S. K. Vijayan ◽  
Baofeng Zhang ◽  
...  
Keyword(s):  
Free Energy ◽  
Ligand Binding ◽  
Large Scale ◽  
Free Energy Calculations ◽  
Grand Challenge ◽  
Energy Calculations ◽  
Scale Free ◽  
D3r Grand Challenge 2015

Large-Scale Assessment of Binding Free Energy Calculations in Active Drug Discovery Projects

2020 ◽  
Vol 60 (11) ◽  
pp. 5457-5474 ◽  
Author(s):  
Christina E. M. Schindler ◽  
Hannah Baumann ◽  
Andreas Blum ◽  
Dietrich Böse ◽  
Hans-Peter Buchstaller ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Large Scale ◽  
Active Drug ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Energy Calculations ◽  
Large Scale Assessment ◽  
Scale Assessment ◽  
Binding Free Energy Calculations
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