Bruce et al. 2019

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Regulation of adenylyl cyclase 5 in striatal neurons confers the ability to detect coincident neuromodulatory signals

Authors: Neil J. Bruce^1*, Daniele Narzi^2*, Daniel Trpevski^3*, Siri Camee van Keulen^2,4*, Anu G. Nair¹⁰, Ursula Roethlisberger², Rebecca C. Wade^1,5,6, Paolo Carloni^7,8, and Jeanette Hellgren Kotaleski^3,9

Author information: ¹ Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS), Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany. ² Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland ³ Science for Life Laboratory, School of Computer Science and Communication, KTH Royal Institute of Technology, 10044, Stockholm, Sweden. ⁴ Department of Computer Science, Stanford University, Stanford, California 94305, USA ⁵ Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Im Neuenheimer Feld 282, 69120 Heidelberg, Germany ⁶ Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Im Neuenheimer Feld 368, 69120 Heidelberg, Germany ⁷ Department of Physics and Department of Neurobiology, RWTH Aachen University, 52078 Aachen, Germany ⁸ Institute for Neuroscience and Medicine (INM)-11, Forschungszentrum Jülich, 52428 Jülich, Germany, Institute of Neuroscience and Medicine (INM-9) and Institute for Advanced Simulation (IAS-5), Forschungszentrum Jülich, Wilhelm-Johnen-Strasse, 52425 Jülich, Germany ⁹ Department of Neuroscience, Karolinska Institutet, 17177, Solna, Sweden. ¹⁰ Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland

^* Joint first authors

Corresponding authors: Jeanette Hellgren Kotaleski (jeanette@csc.kth.se), Paolo Carloni (p.carloni@fz-juelich.de), Rebecca C. Wade (rebecca.wade@h-its.org) and Ursula Roethlisberger (ursula.roethlisberger@epfl.ch)

Journal: PLOS Computational Biology

Download Url: https://doi.org/10.1371/journal.pcbi.1007382

Citation: Bruce NJ, Narzi D, Trpevski D, van Keulen SC, Nair AG, Röthlisberger U, et al. (2019) Regulation of adenylyl cyclase 5 in striatal neurons confers the ability to detect coincident neuromodulatory signals. PLoS Comput Biol 15(10): e1007382.

DOI: https://doi.org/10.1371/journal.pcbi.1007382

Licence: CC BY 4.0 International license

Abstract:

Long-term potentiation and depression of synaptic activity in response to stimuli is a key factor in reinforcement learning. Strengthening of the corticostriatal synapses depends on the second messenger cAMP, whose synthesis is catalysed by the enzyme adenylyl cyclase 5 (AC5), which is itself regulated by the stimulatory Gα_olf and inhibitory Gα_i proteins. AC isoforms have been suggested to act as coincidence detectors, promoting cellular responses only when convergent regulatory signals occur close in time. However, the mechanism for this is currently unclear, and seems to lie in their diverse regulation patterns. Despite attempts to isolate the ternary complex, it is not known if Gα_olf and Gα_i can bind to AC5 simultaneously, nor what activity the complex would have. Using protein structure-based molecular dynamics simulations, we show that this complex is stable and inactive. These simulations, along with Brownian dynamics simulations to estimate protein association rates constants, constrain a kinetic model that shows that the presence of this ternary inactive complex is crucial for AC5’s ability to detect coincident signals, producing a synergistic increase in cAMP. These results reveal some of the prerequisites for corticostriatal synaptic plasticity, and explain recent experimental data on cAMP concentrations following receptor activation. Moreover, they provide insights into the regulatory mechanisms that control signal processing by different AC isoforms.

Resources

Here you can find the data used and generated in this work, along with the model produced.

Input structural data

3D experimental structural data used as input data for this work

Complex of Gs-alpha with the catalytic domains of mammalian adenylyl cyclase	PDB: 1AZS	Download	View
Complex of Gs-alpha with the catalytic domains of mammalian adenylyl cyclase: complex with adenosine 5'-(alpha thio)-triphosphate (RP), Mg, and Mn	PDB: 1CJK	Download	View

Molecular dynamics simulation trajectories

Select molecular dynamics trajectories of complexes including apo or holo AC5

apo AC5
holo AC5

AC5 - Gα_olf binary complex	PDB structure file	XTC trajectory file	View
AC5 - Gα_i binary complex	PDB structure file	XTC trajectory file	View
Gα_olf - AC5 - Gα_i ternary complex	PDB structure file	XTC trajectory file	View

AC5 - Gα_olf binary complex	PDB structure file	XTC trajectory file	View
AC5 - Gα_i binary complex	PDB structure file	XTC trajectory file	View
Gα_olf - AC5 - Gα_i ternary complex	PDB structure file	XTC trajectory file	View

Or download a zip file containing all molecular dynamics trajectories

MD snapshots and electrostatic grid files used in Brownian dynamics simulations

Select electrostatic grid files calculated using snapshots from molecular dynamics trajectories of complexes including apo or holo AC5

apo AC5
holo AC5

Select a pair of interacting species

AC5 - Gα_olf

Snapshot 1	AC5 PQR	AC5 grid	Gα_olf PQR	Gα_olf Grid	View
Snapshot 2	AC5 PQR	AC5 grid	Gα_olf PQR	Gα_olf Grid	View
Snapshot 3	AC5 PQR	AC5 grid	Gα_olf PQR	Gα_olf Grid	View
Snapshot 4	AC5 PQR	AC5 grid	Gα_olf PQR	Gα_olf Grid	View

AC5 - Gα_i

Snapshot 1	AC5 PQR	AC5 grid	Gα_i PQR	Gα_i Grid	View
Snapshot 2	AC5 PQR	AC5 grid	Gα_i PQR	Gα_i Grid	View
Snapshot 3	AC5 PQR	AC5 grid	Gα_i PQR	Gα_i Grid	View
Snapshot 4	AC5 PQR	AC5 grid	Gα_i PQR	Gα_i Grid	View
Snapshot 5	AC5 PQR	AC5 grid	Gα_i PQR	Gα_i Grid	View
Snapshot 6	AC5 PQR	AC5 grid	Gα_i PQR	Gα_i Grid	View
Snapshot 7	AC5 PQR	AC5 grid	Gα_i PQR	Gα_i Grid	View

AC5⋅Gα_i - Gα_olf

Snapshot 1	AC5⋅Gα_i PQR	AC5⋅Gα_i grid	Gα_olf PQR	Gα_olf Grid	View
Snapshot 2	AC5⋅Gα_i PQR	AC5⋅Gα_i grid	Gα_olf PQR	Gα_olf Grid	View
Snapshot 3	AC5⋅Gα_i PQR	AC5⋅Gα_i grid	Gα_olf PQR	Gα_olf Grid	View
Snapshot 4	AC5⋅Gα_i PQR	AC5⋅Gα_i grid	Gα_olf PQR	Gα_olf Grid	View
Snapshot 5	AC5⋅Gα_i PQR	AC5⋅Gα_i grid	Gα_olf PQR	Gα_olf Grid	View

AC5⋅Gα_olf - Gα_i

Snapshot 1	AC5⋅Gα_olf PQR	AC5⋅Gα_olf grid	Gα_i PQR	Gα_i Grid	View
Snapshot 2	AC5⋅Gα_olf PQR	AC5⋅Gα_olf grid	Gα_i PQR	Gα_i Grid	View
Snapshot 3	AC5⋅Gα_olf PQR	AC5⋅Gα_olf grid	Gα_i PQR	Gα_i Grid	View
Snapshot 4	AC5⋅Gα_olf PQR	AC5⋅Gα_olf grid	Gα_i PQR	Gα_i Grid	View
Snapshot 5	AC5⋅Gα_olf PQR	AC5⋅Gα_olf grid	Gα_i PQR	Gα_i Grid	View

Select a pair of interacting species

AC5 - Gα_olf

Snapshot 1	AC5 PQR	AC5 grid	Gα_olf PQR	Gα_olf Grid	View
Snapshot 2	AC5 PQR	AC5 grid	Gα_olf PQR	Gα_olf Grid	View
Snapshot 3	AC5 PQR	AC5 grid	Gα_olf PQR	Gα_olf Grid	View

AC5 - Gα_i

Snapshot 1	AC5 PQR	AC5 grid	Gα_i PQR	Gα_i Grid	View
Snapshot 2	AC5 PQR	AC5 grid	Gα_i PQR	Gα_i Grid	View
Snapshot 3	AC5 PQR	AC5 grid	Gα_i PQR	Gα_i Grid	View
Snapshot 4	AC5 PQR	AC5 grid	Gα_i PQR	Gα_i Grid	View

AC5⋅Gα_i - Gα_olf

Snapshot 1	AC5⋅Gα_i PQR	AC5⋅Gα_i grid	Gα_olf PQR	Gα_olf Grid	View
Snapshot 2	AC5⋅Gα_i PQR	AC5⋅Gα_i grid	Gα_olf PQR	Gα_olf Grid	View
Snapshot 3	AC5⋅Gα_i PQR	AC5⋅Gα_i grid	Gα_olf PQR	Gα_olf Grid	View
Snapshot 4	AC5⋅Gα_i PQR	AC5⋅Gα_i grid	Gα_olf PQR	Gα_olf Grid	View

AC5⋅Gα_olf - Gα_i

Snapshot 1	AC5⋅Gα_olf PQR	AC5⋅Gα_olf grid	Gα_i PQR	Gα_i Grid	View
Snapshot 2	AC5⋅Gα_olf PQR	AC5⋅Gα_olf grid	Gα_i PQR	Gα_i Grid	View
Snapshot 3	AC5⋅Gα_olf PQR	AC5⋅Gα_olf grid	Gα_i PQR	Gα_i Grid	View
Snapshot 4	AC5⋅Gα_olf PQR	AC5⋅Gα_olf grid	Gα_i PQR	Gα_i Grid	View

Or download a zip file containing all snapshots and grid files

Rate constants derived from Brownian dynamics simulations

The following forward rate constants (nM^-1s^-1, standard errors in parentheses) were calculated using Brownian dynamics (BD) simulations. For each snapshot the rate constant was estimated from four simulations of 50 000 BD trajectories. The headings of each column show the two reactive species and the rate constant name used the mathematical modelling.

apo AC5
holo AC5

Snapshot	AC5 - Gα_olf (k_f1)	AC5 - Gα_i (k_f2)	AC5⋅Gα_olf - Gα_i (k_f3)	AC5⋅Gα_i - Gα_olf (k_f4)
1	0.003 (0.002)	0.015 (0.002)	0.009 (0.003)	0.037 (0.004)
2	0.011 (0.003)	0.018 (0.006)	0.004 (0.001)	0.007 (0.003)
3	0.038 (0.003)	0.036 (0.006)	0.011 (0.005)	0.007 (0.003)
4	0.022 (0.006)	0.008 (0.003)	0.005 (0.002)	0.0087 (0.0007)
5		0.016 (0.003)	0.030 (0.004)	0.06 (0.01)
6		0.013 (0.003)
7		0.027 (0.005)
Mean	0.018 (0.007)	0.02 (0.01)	0.012 (0.008)	0.02 (0.01)

Snapshot	AC5 - Gα_olf (k_f1)	AC5 - Gα_i (k_f2)	AC5⋅Gα_olf - Gα_i (k_f3)	AC5⋅Gα_i - Gα_olf (k_f4)
1	0.013 (0.004)	0.005 (0.002)	0.004 (0.001)	0.035 (0.004)
2	0.045 (0.007)	0.028 (0.004)	0.017 (0.004)	0.016 (0.003)
3	0.019 (0.002)	0.10 (0.01)	0.032 (0.004)	0.013 (0.002)
4		0.061 (0.006)	0.016 (0.002)	0.016 (0.003)
Mean	0.026 (0.009)	0.05 (0.01)	0.017 (0.006)	0.020 (0.006)

Model

The kinetic model and related scripts to produce some of the figures shown in the published paper are available from GitHub.