1
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Luo D, Zhang Y, Li Y, Liu Z, Wu H, Xue W. Structural Models of Human Norepinephrine Transporter Ensemble Reveal the Allosteric Sites and Ligand-Binding Mechanism. J Phys Chem B 2024; 128:8651-8661. [PMID: 39207306 DOI: 10.1021/acs.jpcb.4c03731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
The norepinephrine transporter (NET) plays a pivotal role in recycling norepinephrine (NE) from the synaptic cleft. However, the structures referring to the conformational heterogeneity of NET during the transport cycle remain poorly understood. Here, three structural models of NE bound to the orthosteric site of NET in outward-open (OOholo), outward-occluded (OCholo), and inward-open (IOholo) conformations were first obtained using the multistate structures of serotonin transporter as templates and further characterized through Gaussian-accelerated molecular dynamics and free energy reweighting. Analysis of the structures revealed eight potential allosteric sites on the functional-specific states of NET. One of the pharmacologically relevant pockets located at the extracellular vestibule was further verified by simulating the binding behaviors of a clinical trial drug χ-MrIA that is allosterically regulating NET. These structural and energetic insights into NET advanced our understanding of NE reuptake and paved the way for discovering novel molecules targeting the allosteric sites.
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Affiliation(s)
- Ding Luo
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Yang Zhang
- School of Pharmacy, Hebei Medical University, Shijiazhuang 050017, China
| | - Yinghong Li
- Chongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | - Zerong Liu
- Central Nervous System Drug Key Laboratory of Sichuan Province, Sichuan Credit Pharmaceutical Co., Ltd., Luzhou 646000, China
| | - Haibo Wu
- School of Life Sciences, Chongqing University, Chongqing 401331, China
| | - Weiwei Xue
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
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2
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Alves da Silva L, Lazzarin E, Gradisch R, Clarke A, Stockner T. Free energy profile of the substrate-induced occlusion of the human serotonin transporter. J Neurochem 2024; 168:1993-2006. [PMID: 38316690 DOI: 10.1111/jnc.16061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 12/05/2023] [Accepted: 01/15/2024] [Indexed: 02/07/2024]
Abstract
The serotonin transporter (SERT) is a member of the Solute Carrier 6 (SLC6) family and is responsible for maintaining the appropriate level of serotonin in the brain. Dysfunction of SERT has been linked to several neuropsychiatric disorders, including depression, anxiety and obsessive-compulsive disorder. Therefore, an in-depth understanding of the mechanism on an atomistic level, coupled with a quantification of transporter dynamics and the associated free energies is required. Here, we constructed Markov state models (MSMs) from extensive unbiased molecular dynamics simulations to quantify the free energy profile of serotonin (5HT) triggered SERT occlusion and explored the driving forces of the mechanism of occlusion. Our results reveal that SERT occludes via multiple intermediate conformations and show that the motion of occlusion is energetically downhill for the 5HT-bound transporter. Force distribution analyses show that the interactions of 5HT with the bundle domain are crucial. During occlusion, attractive forces steadily increase and pull on the bundle domain, which leads to SERT occlusion. Some interactions become repulsive upon full occlusion, suggesting that SERT creates pressure on 5HT to promote its movement towards the cytosol.
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Affiliation(s)
- Leticia Alves da Silva
- Centre for Physiology and Pharmacology, Institute of Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Erika Lazzarin
- Centre for Physiology and Pharmacology, Institute of Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Ralph Gradisch
- Centre for Physiology and Pharmacology, Institute of Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Amy Clarke
- Centre for Physiology and Pharmacology, Institute of Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Thomas Stockner
- Centre for Physiology and Pharmacology, Institute of Pharmacology, Medical University of Vienna, Vienna, Austria
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3
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Park H, Patel P, Haas R, Huerta EA. APACE: AlphaFold2 and advanced computing as a service for accelerated discovery in biophysics. Proc Natl Acad Sci U S A 2024; 121:e2311888121. [PMID: 38913887 PMCID: PMC11228474 DOI: 10.1073/pnas.2311888121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 12/25/2023] [Indexed: 06/26/2024] Open
Abstract
The prediction of protein 3D structure from amino acid sequence is a computational grand challenge in biophysics and plays a key role in robust protein structure prediction algorithms, from drug discovery to genome interpretation. The advent of AI models, such as AlphaFold, is revolutionizing applications that depend on robust protein structure prediction algorithms. To maximize the impact, and ease the usability, of these AI tools we introduce APACE, AlphaFold2 and advanced computing as a service, a computational framework that effectively handles this AI model and its TB-size database to conduct accelerated protein structure prediction analyses in modern supercomputing environments. We deployed APACE in the Delta and Polaris supercomputers and quantified its performance for accurate protein structure predictions using four exemplar proteins: 6AWO, 6OAN, 7MEZ, and 6D6U. Using up to 300 ensembles, distributed across 200 NVIDIA A100 GPUs, we found that APACE is up to two orders of magnitude faster than off-the-self AlphaFold2 implementations, reducing time-to-solution from weeks to minutes. This computational approach may be readily linked with robotics laboratories to automate and accelerate scientific discovery.
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Affiliation(s)
- Hyun Park
- Data Science and Learning Division, Argonne National Laboratory, Lemont, IL 60439
- Theoretical and Computational Biophysics Group, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801
| | - Parth Patel
- Data Science and Learning Division, Argonne National Laboratory, Lemont, IL 60439
- Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL 61801
| | - Roland Haas
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL 61801
| | - E A Huerta
- Data Science and Learning Division, Argonne National Laboratory, Lemont, IL 60439
- Department of Computer Science, The University of Chicago, Chicago, IL 60637
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801
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4
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Weigle AT, Shukla D. The Arabidopsis AtSWEET13 transporter discriminates sugars by selective facial and positional substrate recognition. Commun Biol 2024; 7:764. [PMID: 38914639 PMCID: PMC11196581 DOI: 10.1038/s42003-024-06291-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 05/03/2024] [Indexed: 06/26/2024] Open
Abstract
Transporters are targeted by endogenous metabolites and exogenous molecules to reach cellular destinations, but it is generally not understood how different substrate classes exploit the same transporter's mechanism. Any disclosure of plasticity in transporter mechanism when treated with different substrates becomes critical for developing general selectivity principles in membrane transport catalysis. Using extensive molecular dynamics simulations with an enhanced sampling approach, we select the Arabidopsis sugar transporter AtSWEET13 as a model system to identify the basis for glucose versus sucrose molecular recognition and transport. Here we find that AtSWEET13 chemical selectivity originates from a conserved substrate facial selectivity demonstrated when committing alternate access, despite mono-/di-saccharides experiencing differing degrees of conformational and positional freedom throughout other stages of transport. However, substrate interactions with structural hallmarks associated with known functional annotations can help reinforce selective preferences in molecular transport.
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Affiliation(s)
- Austin T Weigle
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Diwakar Shukla
- Department of Chemical & Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
- Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
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5
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Selvam B, Chiang N, Shukla D. Energetics of substrate transport in proton-dependent oligopeptide transporters. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.01.592129. [PMID: 38746282 PMCID: PMC11092630 DOI: 10.1101/2024.05.01.592129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
The PepT So transporter mediates the transport of peptides across biological membranes. Despite advancements in structural biology, including cryogenic electron microscopy structures resolving PepT So in different states, the molecular basis of peptide recognition and transport by PepT So is not fully elucidated. In this study, we employed molecular dynamics simulations, Markov State Models (MSMs), and Transition Path Theory (TPT) to investigate the transport mechanism of an alanine-alanine peptide (Ala-Ala) through the PepT So transporter. Our simulations revealed conformational changes and key intermediate states involved in peptide translocation. We observed that the presence of the Ala-Ala peptide substrate lowers the free energy barriers associated with transition to the inward-facing state. Furthermore, we elucidated the proton transport model and analyzed the pharmacophore features of intermediate states, providing insights for rational drug design. These findings highlight the significance of substrate binding in modulating the conformational dynamics of PepT So and identify critical residues that facilitate transport.
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6
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Hellsberg E, Boytsov D, Chen Q, Niello M, Freissmuth M, Rudnick G, Zhang YW, Sandtner W, Forrest LR. Identification of the potassium-binding site in serotonin transporter. Proc Natl Acad Sci U S A 2024; 121:e2319384121. [PMID: 38652746 PMCID: PMC11067047 DOI: 10.1073/pnas.2319384121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 03/11/2024] [Indexed: 04/25/2024] Open
Abstract
Clearance of serotonin (5-hydroxytryptamine, 5-HT) from the synaptic cleft after neuronal signaling is mediated by serotonin transporter (SERT), which couples this process to the movement of a Na+ ion down its chemical gradient. After release of 5-HT and Na+ into the cytoplasm, the transporter faces a rate-limiting challenge of resetting its conformation to be primed again for 5-HT and Na+ binding. Early studies of vesicles containing native SERT revealed that K+ gradients can provide an additional driving force, via K+ antiport. Moreover, under appropriate conditions, a H+ ion can replace K+. Intracellular K+ accelerates the resetting step. Structural studies of SERT have identified two binding sites for Na+ ions, but the K+ site remains enigmatic. Here, we show that K+ antiport can drive substrate accumulation into vesicles containing SERT extracted from a heterologous expression system, allowing us to study the residues responsible for K+ binding. To identify candidate binding residues, we examine many cation binding configurations using molecular dynamics simulations, predicting that K+ binds to the so-called Na2 site. Site-directed mutagenesis of residues in this site can eliminate the ability of both K+ and H+ to drive 5-HT accumulation into vesicles and, in patch clamp recordings, prevent the acceleration of turnover rates and the formation of a channel-like state by K+ or H+. In conclusion, the Na2 site plays a pivotal role in orchestrating the sequential binding of Na+ and then K+ (or H+) ions to facilitate 5-HT uptake in SERT.
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Affiliation(s)
- Eva Hellsberg
- Computational Structural Biology Section, National Institutes of Neurological Disorders and Stroke, NIH, Bethesda, MD20892
| | - Danila Boytsov
- Center of Physiology and Pharmacology, Department of Pharmacology, Medical University of Vienna, Vienna1090, Austria
| | - Qingyang Chen
- School of Life Sciences, Higher Education Mega Center, Guangzhou University, Guangzhou510006, China
| | - Marco Niello
- Center of Physiology and Pharmacology, Department of Pharmacology, Medical University of Vienna, Vienna1090, Austria
| | - Michael Freissmuth
- Center of Physiology and Pharmacology, Department of Pharmacology, Medical University of Vienna, Vienna1090, Austria
| | - Gary Rudnick
- Department of Pharmacology, Yale University, New Haven, CT06510
| | - Yuan-Wei Zhang
- School of Life Sciences, Higher Education Mega Center, Guangzhou University, Guangzhou510006, China
| | - Walter Sandtner
- Center of Physiology and Pharmacology, Department of Pharmacology, Medical University of Vienna, Vienna1090, Austria
| | - Lucy R. Forrest
- Computational Structural Biology Section, National Institutes of Neurological Disorders and Stroke, NIH, Bethesda, MD20892
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7
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Gradisch R, Schlögl K, Lazzarin E, Niello M, Maier J, Mayer FP, Alves da Silva L, Skopec SMC, Blakely RD, Sitte HH, Mihovilovic MD, Stockner T. Ligand coupling mechanism of the human serotonin transporter differentiates substrates from inhibitors. Nat Commun 2024; 15:417. [PMID: 38195746 PMCID: PMC10776687 DOI: 10.1038/s41467-023-44637-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 12/22/2023] [Indexed: 01/11/2024] Open
Abstract
The presynaptic serotonin transporter (SERT) clears extracellular serotonin following vesicular release to ensure temporal and spatial regulation of serotonergic signalling and neurotransmitter homeostasis. Prescription drugs used to treat neurobehavioral disorders, including depression, anxiety, and obsessive-compulsive disorder, trap SERT by blocking the transport cycle. In contrast, illicit drugs of abuse like amphetamines reverse SERT directionality, causing serotonin efflux. Both processes result in increased extracellular serotonin levels. By combining molecular dynamics simulations with biochemical experiments and using a homologous series of serotonin analogues, we uncovered the coupling mechanism between the substrate and the transporter, which triggers the uptake of serotonin. Free energy analysis showed that only scaffold-bound substrates could initiate SERT occlusion through attractive long-range electrostatic interactions acting on the bundle domain. The associated spatial requirements define substrate and inhibitor properties, enabling additional possibilities for rational drug design approaches.
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Affiliation(s)
- Ralph Gradisch
- Medical University of Vienna, Institute of Physiology and Pharmacology, Waehringer Straße 13A, 1090, Vienna, Austria
| | - Katharina Schlögl
- TU Wien, Institute of Applied Synthetic Chemistry, Getreidemarkt 9, 1060, Vienna, Austria
| | - Erika Lazzarin
- Medical University of Vienna, Institute of Physiology and Pharmacology, Waehringer Straße 13A, 1090, Vienna, Austria
| | - Marco Niello
- Medical University of Vienna, Institute of Physiology and Pharmacology, Waehringer Straße 13A, 1090, Vienna, Austria
- Genetics of Cognition Laboratory, Neuroscience area, Istituto Italiano di Tecnologia, via Morego, 30, 16163, Genova, Italy
| | - Julian Maier
- Medical University of Vienna, Institute of Physiology and Pharmacology, Waehringer Straße 13A, 1090, Vienna, Austria
| | - Felix P Mayer
- Florida Atlantic University, Department of Biomedical Science, Jupiter, FL, 33458, USA
- Stiles-Nicholson Brain Institute, Jupiter, FL, 33458, USA
- Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2200, Copenhagen, Denmark
| | - Leticia Alves da Silva
- Medical University of Vienna, Institute of Physiology and Pharmacology, Waehringer Straße 13A, 1090, Vienna, Austria
| | - Sophie M C Skopec
- Medical University of Vienna, Institute of Physiology and Pharmacology, Waehringer Straße 13A, 1090, Vienna, Austria
| | - Randy D Blakely
- Florida Atlantic University, Department of Biomedical Science, Jupiter, FL, 33458, USA
- Stiles-Nicholson Brain Institute, Jupiter, FL, 33458, USA
| | - Harald H Sitte
- Medical University of Vienna, Institute of Physiology and Pharmacology, Waehringer Straße 13A, 1090, Vienna, Austria
- Al-Ahliyya Amman University, Hourani Center for Applied Scientific Research, Amman, Jordan
- Medical University of Vienna, Center for Addiction Research and Science, Waehringer Straße 13A, 1090, Vienna, Austria
| | - Marko D Mihovilovic
- TU Wien, Institute of Applied Synthetic Chemistry, Getreidemarkt 9, 1060, Vienna, Austria
| | - Thomas Stockner
- Medical University of Vienna, Institute of Physiology and Pharmacology, Waehringer Straße 13A, 1090, Vienna, Austria.
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8
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Clarke A, Farr CV, El-Kasaby A, Szöllősi D, Freissmuth M, Sucic S, Stockner T. Probing binding and occlusion of substrate in the human creatine transporter-1 by computation and mutagenesis. Protein Sci 2024; 33:e4842. [PMID: 38032325 PMCID: PMC10751730 DOI: 10.1002/pro.4842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 11/16/2023] [Accepted: 11/18/2023] [Indexed: 12/01/2023]
Abstract
In chordates, energy buffering is achieved in part through phosphocreatine, which requires cellular uptake of creatine by the membrane-embedded creatine transporter (CRT1/SLC6A8). Mutations in human slc6a8 lead to creatine transporter deficiency syndrome, for which there is only limited treatment. Here, we used a combined homology modeling, molecular dynamics, and experimental approach to generate a structural model of CRT1. Our observations support the following conclusions: contrary to previous proposals, C144, a key residue in the substrate binding site, is not present in a charged state. Similarly, the side chain D458 must be present in a protonated form to maintain the structural integrity of CRT1. Finally, we identified that the interaction chain Y148-creatine-Na+ is essential to the process of occlusion, which occurs via a "hold-and-pull" mechanism. The model should be useful to study the impact of disease-associated point mutations on the folding of CRT1 and identify approaches which correct folding-deficient mutants.
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Affiliation(s)
- Amy Clarke
- Institute of Pharmacology and the Gaston H. Glock Research Laboratories for Exploratory Drug Development, Center of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Clemens V Farr
- Institute of Pharmacology and the Gaston H. Glock Research Laboratories for Exploratory Drug Development, Center of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Ali El-Kasaby
- Institute of Pharmacology and the Gaston H. Glock Research Laboratories for Exploratory Drug Development, Center of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Daniel Szöllősi
- Department of Theoretical and Computational Biophysics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Michael Freissmuth
- Institute of Pharmacology and the Gaston H. Glock Research Laboratories for Exploratory Drug Development, Center of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Sonja Sucic
- Institute of Pharmacology and the Gaston H. Glock Research Laboratories for Exploratory Drug Development, Center of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Thomas Stockner
- Institute of Pharmacology and the Gaston H. Glock Research Laboratories for Exploratory Drug Development, Center of Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
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9
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Paul A, Shukla D. Oligomerization of Monoamine Transporters. Subcell Biochem 2024; 104:119-137. [PMID: 38963486 DOI: 10.1007/978-3-031-58843-3_7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/05/2024]
Abstract
Transporters of the monoamine transporter (MAT) family regulate the uptake of important neurotransmitters like dopamine, serotonin, and norepinephrine. The MAT family functions using the electrochemical gradient of ions across the membrane and comprises three transporters, dopamine transporter (DAT), serotonin transporter (SERT), and norepinephrine transporter (NET). MAT transporters have been observed to exist in monomeric states to higher-order oligomeric states. Structural features, allosteric modulation, and lipid environment regulate the oligomerization of MAT transporters. NET and SERT oligomerization are regulated by levels of PIP2 present in the membrane. The kink present in TM12 in the MAT family is crucial for dimer interface formation. Allosteric modulation in the dimer interface hinders dimer formation. Oligomerization also influences the transporters' function, trafficking, and regulation. This chapter will focus on recent studies on monoamine transporters and discuss the factors affecting their oligomerization and its impact on their function.
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Affiliation(s)
- Arnav Paul
- Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Diwakar Shukla
- Department of Chemical and Biomolecular Engineering, Department of Bioengineering, Center for Biophysics and Quantitative Biology, Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
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10
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Kleiman DE, Nadeem H, Shukla D. Adaptive Sampling Methods for Molecular Dynamics in the Era of Machine Learning. J Phys Chem B 2023; 127:10669-10681. [PMID: 38081185 DOI: 10.1021/acs.jpcb.3c04843] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2023]
Abstract
Molecular dynamics (MD) simulations are fundamental computational tools for the study of proteins and their free energy landscapes. However, sampling protein conformational changes through MD simulations is challenging due to the relatively long time scales of these processes. Many enhanced sampling approaches have emerged to tackle this problem, including biased sampling and path-sampling methods. In this Perspective, we focus on adaptive sampling algorithms. These techniques differ from other approaches because the thermodynamic ensemble is preserved and the sampling is enhanced solely by restarting MD trajectories at particularly chosen seeds rather than introducing biasing forces. We begin our treatment with an overview of theoretically transparent methods, where we discuss principles and guidelines for adaptive sampling. Then, we present a brief summary of select methods that have been applied to realistic systems in the past. Finally, we discuss recent advances in adaptive sampling methodology powered by deep learning techniques, as well as their shortcomings.
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Affiliation(s)
- Diego E Kleiman
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Hassan Nadeem
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Diwakar Shukla
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
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11
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Salomon K, Abramyan AM, Plenge P, Wang L, Bundgaard C, Bang-Andersen B, Loland CJ, Shi L. Dynamic extracellular vestibule of human SERT: Unveiling druggable potential with high-affinity allosteric inhibitors. Proc Natl Acad Sci U S A 2023; 120:e2304089120. [PMID: 37792512 PMCID: PMC10576121 DOI: 10.1073/pnas.2304089120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 08/15/2023] [Indexed: 10/06/2023] Open
Abstract
The serotonin transporter (SERT) tightly regulates synaptic serotonin levels and has been the primary target of antidepressants. Binding of inhibitors to the allosteric site of human SERT (hSERT) impedes the dissociation of antidepressants bound at the central site and may enhance the efficacy of such antidepressants to potentially reduce their dosage and side effects. Here, we report the identification of a series of high-affinity allosteric inhibitors of hSERT in a unique scaffold, with the lead compound, Lu AF88273 (3-(1-(2-(1H-indol-3-yl)ethyl)piperidin-4-yl)-6-chloro-1H-indole), having 2.1 nM allosteric potency in inhibiting imipramine dissociation. In addition, we find that Lu AF88273 also inhibits serotonin transport in a noncompetitive manner. The binding pose of Lu AF88273 in the allosteric site of hSERT is determined with extensive molecular dynamics simulations and rigorous absolute binding free energy perturbation (FEP) calculations, which show that a part of the compound occupies a dynamically formed small cavity. The predicted binding location and pose are validated by site-directed mutagenesis and can explain much of the structure-activity relationship of these inhibitors using the relative binding FEP calculations. Together, our findings provide a promising lead compound and the structural basis for the development of allosteric drugs targeting hSERT. Further, they demonstrate that the divergent allosteric sites of neurotransmitter transporters can be selectively targeted.
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Affiliation(s)
- Kristine Salomon
- Laboratory for Membrane Protein Dynamics, Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2200Copenhagen N, Denmark
| | - Ara M. Abramyan
- Computational Chemistry and Molecular Biophysics Section, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse - Intramural Research Program, NIH, Baltimore, MD21224
- Schrödinger, Inc., San Diego, CA92121
| | - Per Plenge
- Laboratory for Membrane Protein Dynamics, Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2200Copenhagen N, Denmark
| | | | - Christoffer Bundgaard
- Medicinal Chemistry and Translational DMPK, H. Lundbeck A/S, DK-2500Copenhagen-Valby, Denmark
| | - Benny Bang-Andersen
- Medicinal Chemistry and Translational DMPK, H. Lundbeck A/S, DK-2500Copenhagen-Valby, Denmark
| | - Claus J. Loland
- Laboratory for Membrane Protein Dynamics, Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2200Copenhagen N, Denmark
| | - Lei Shi
- Computational Chemistry and Molecular Biophysics Section, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse - Intramural Research Program, NIH, Baltimore, MD21224
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12
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Bansal PD, Dutta S, Shukla D. Activation mechanism of the human Smoothened receptor. Biophys J 2023; 122:1400-1413. [PMID: 36883002 PMCID: PMC10111369 DOI: 10.1016/j.bpj.2023.03.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 01/17/2023] [Accepted: 03/02/2023] [Indexed: 03/08/2023] Open
Abstract
Smoothened (SMO) is a membrane protein of the class F subfamily of G protein-coupled receptors (GPCRs) and maintains homeostasis of cellular differentiation. SMO undergoes conformational change during activation, transmitting the signal across the membrane, making it amenable to bind to its intracellular signaling partner. Receptor activation has been studied at length for class A receptors, but the mechanism of class F receptor activation remains unknown. Agonists and antagonists bound to SMO at sites in the transmembrane domain (TMD) and the cysteine-rich domain have been characterized, giving a static view of the various conformations SMO adopts. Although the structures of the inactive and active SMO outline the residue-level transitions, a kinetic view of the overall activation process remains unexplored for class F receptors. We describe SMO's activation process in atomistic detail by performing 300 μs of molecular dynamics simulations and combining it with Markov state model theory. A molecular switch, conserved across class F and analogous to the activation-mediating D-R-Y motif in class A receptors, is observed to break during activation. We also show that this transition occurs in a stage-wise movement of the transmembrane helices: TM6 first, followed by TM5. To see how modulators affect SMO activity, we simulated agonist and antagonist-bound SMO. We observed that agonist-bound SMO has an expanded hydrophobic tunnel in SMO's core TMD, whereas antagonist-bound SMO shrinks this tunnel, further supporting the hypothesis that cholesterol travels through a tunnel inside Smoothened to activate it. In summary, this study elucidates the distinct activation mechanism of class F GPCRs and shows that SMO's activation process rearranges the core TMD to open a hydrophobic conduit for cholesterol transport.
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Affiliation(s)
- Prateek D Bansal
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois
| | - Soumajit Dutta
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois
| | - Diwakar Shukla
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois; Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois; Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois; Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, Illinois.
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13
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Mittal S, Dutta S, Shukla D. Reconciling membrane protein simulations with experimental DEER spectroscopy data. Phys Chem Chem Phys 2023; 25:6253-6262. [PMID: 36757376 DOI: 10.1039/d2cp02890e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Spectroscopy experiments are crucial to study membrane proteins for which traditional structure determination methods still prove challenging. Double electron-electron resonance (DEER) spectroscopy experiments provide protein residue-pair distance distributions that are indicative of their conformational heterogeneity. Atomistic molecular dynamics (MD) simulations are another tool that have been proven to be vital to study the structural dynamics of membrane proteins such as to identify inward-open, occluded, and outward-open conformations of transporter membrane proteins, among other partially open or closed states of the protein. Yet, studies have reported that there is no direct consensus between the distributional data from DEER experiments and MD simulations, which has challenged validation of structures obtained from long-timescale simulations and using simulations to design experiments. Current coping strategies for comparisons rely on heuristics, such as mapping the nearest matching peaks between two ensembles or biased simulations. Here we examine the differences in residue-pair distance distributions arising due to the choice of membranes around the protein and covalent modification of a pair of residues to nitroxide spin labels in DEER experiments. Through comparing MD simulations of two proteins, PepTSo and LeuT-both of which have been characterized using DEER experiments previously-we show that the proteins' dynamics are similar despite the choice of the detergent micelle as a membrane mimetic in DEER experiments. On the other hand, covalently modified residues show slight local differences in their dynamics and a huge divergence when the oxygen atom pair distances between spin labeled residues are measured rather than protein backbone distances. Given the computational expense associated with pairwise MTSSL labeled MD simulations, we examine the use of biased simulations to explore the conformational dynamics of the spin labels only to reveal that such simulations alter the underlying protein dynamics. Our study identifies the main cause for the mismatch between DEER experiments and MD simulations and will accelerate the development of potential mitigation strategies to improve the match.
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Affiliation(s)
- Shriyaa Mittal
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
| | - Soumajit Dutta
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Diwakar Shukla
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA. .,Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.,National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA.,Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.,NIH Center for Macromolecular Modeling and Bioinformatics, University of Illinois at Urbana-Champaign, Urbana, IL, USA
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14
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The Bright Side of Psychedelics: Latest Advances and Challenges in Neuropharmacology. Int J Mol Sci 2023; 24:ijms24021329. [PMID: 36674849 PMCID: PMC9865175 DOI: 10.3390/ijms24021329] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 12/31/2022] [Accepted: 01/05/2023] [Indexed: 01/12/2023] Open
Abstract
The need to identify effective therapies for the treatment of psychiatric disorders is a particularly important issue in modern societies. In addition, difficulties in finding new drugs have led pharmacologists to review and re-evaluate some past molecules, including psychedelics. For several years there has been growing interest among psychotherapists in psilocybin or lysergic acid diethylamide for the treatment of obsessive-compulsive disorder, of depression, or of post-traumatic stress disorder, although results are not always clear and definitive. In fact, the mechanisms of action of psychedelics are not yet fully understood and some molecular aspects have yet to be well defined. Thus, this review aims to summarize the ethnobotanical uses of the best-known psychedelic plants and the pharmacological mechanisms of the main active ingredients they contain. Furthermore, an up-to-date overview of structural and computational studies performed to evaluate the affinity and binding modes to biologically relevant receptors of ibogaine, mescaline, N,N-dimethyltryptamine, psilocin, and lysergic acid diethylamide is presented. Finally, the most recent clinical studies evaluating the efficacy of psychedelic molecules in some psychiatric disorders are discussed and compared with drugs already used in therapy.
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15
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Kleiman DE, Shukla D. Multiagent Reinforcement Learning-Based Adaptive Sampling for Conformational Dynamics of Proteins. J Chem Theory Comput 2022; 18:5422-5434. [PMID: 36044642 DOI: 10.1021/acs.jctc.2c00683] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Machine learning is increasingly applied to improve the efficiency and accuracy of molecular dynamics (MD) simulations. Although the growth of distributed computer clusters has allowed researchers to obtain higher amounts of data, unbiased MD simulations have difficulty sampling rare states, even under massively parallel adaptive sampling schemes. To address this issue, several algorithms inspired by reinforcement learning (RL) have arisen to promote exploration of the slow collective variables (CVs) of complex systems. Nonetheless, most of these algorithms are not well-suited to leverage the information gained by simultaneously sampling a system from different initial states (e.g., a protein in different conformations associated with distinct functional states). To fill this gap, we propose two algorithms inspired by multiagent RL that extend the functionality of closely related techniques (REAP and TSLC) to situations where the sampling can be accelerated by learning from different regions of the energy landscape through coordinated agents. Essentially, the algorithms work by remembering which agent discovered each conformation and sharing this information with others at the action-space discretization step. A stakes function is introduced to modulate how different agents sense rewards from discovered states of the system. The consequences are three-fold: (i) agents learn to prioritize CVs using only relevant data, (ii) redundant exploration is reduced, and (iii) agents that obtain higher stakes are assigned more actions. We compare our algorithm with other adaptive sampling techniques (least counts, REAP, TSLC, and AdaptiveBandit) to show and rationalize the gain in performance.
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Affiliation(s)
- Diego E Kleiman
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Diwakar Shukla
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
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16
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Horne J, Shukla D. Recent Advances in Machine Learning Variant Effect Prediction Tools for Protein Engineering. Ind Eng Chem Res 2022; 61:6235-6245. [PMID: 36051311 PMCID: PMC9432854 DOI: 10.1021/acs.iecr.1c04943] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Proteins are Nature's molecular machinery and comprise diverse roles while consisting of chemically similar building blocks. In recent years, protein engineering and design have become important research areas, with many applications in the pharmaceutical, energy, and biocatalysis fields, among others-where the aim is to ultimately create a protein given desired structural and functional properties. It is often critical to model the relationship between a protein's sequence, folded structure, and biological function to assist in such protein engineering pursuits. However, significant challenges remain in concretely mapping an amino acid sequence to specific protein properties and biological activities. Mutations may enhance or diminish molecular protein function, and the epistatic interactions between mutations result in an inherently complex mapping between genetic modifications and protein function. Therefore, estimating the quantitative effects of mutations on protein function(s) remains a grand challenge of biology, bioinformatics, and many related fields and would rapidly accelerate protein engineering tasks when successful. Such estimation is often known as variant effect prediction (VEP). However, progress has been demonstrated in recent years with the development of machine learning (ML) methods in modeling the relationship between mutations and protein function. In this Review, recent advances in variant effect prediction (VEP) are discussed as tools for protein engineering, focusing on techniques incorporating gains from the broader ML community and challenges in estimating biomolecular functional differences. Primary developments highlighted include convolutional neural networks, graph neural networks, and natural language embeddings for protein sequences.
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Affiliation(s)
- Jesse Horne
- Department of Chemical and Biomolecular Engineering, University of Illinois Urbana-Champaign, Champaign, Illinois 61801, United States
| | - Diwakar Shukla
- Department of Chemical and Biomolecular Engineering and Department of Bioengineering, University of Illinois Urbana-Champaign, Champaign, Illinois 61801, United States; Department of Plant Biology, Cancer Center at Illinois, and Center for Biophysics and Quantitative Biology, University of Illinois Urbana-Champaign, Champaign, Illinois 61801, United States
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17
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Chan MC, Procko E, Shukla D. Structural Rearrangement of the Serotonin Transporter Intracellular Gate Induced by Thr276 Phosphorylation. ACS Chem Neurosci 2022; 13:933-945. [PMID: 35258286 DOI: 10.1021/acschemneuro.1c00714] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
The reuptake of the neurotransmitter serotonin from the synaptic cleft by the serotonin transporter, SERT, is essential for proper neurological signaling. Biochemical studies have shown that Thr276 of transmembrane helix 5 is a site of PKG-mediated SERT phosphorylation, which has been proposed to shift the SERT conformational equilibria to promote inward-facing states, thus enhancing 5-HT transport. Recent structural and simulation studies have provided insights into the conformation transitions during substrate transport but have not shed light on SERT regulation via post-translational modifications. Using molecular dynamics simulations and Markov state models, we investigate how Thr276 phosphorylation impacts the SERT mechanism and its role in enhancing transporter stability and function. Our simulations show that Thr276 phosphorylation alters the hydrogen-bonding network involving residues on transmembrane helix 5. This in turn decreases the free energy barriers for SERT to transition to the inward-facing state, thus facilitating 5-HT import. The results provide atomistic insights into in vivo SERT regulation and can be extended to other pharmacologically important transporters in the solute carrier family.
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Affiliation(s)
- Matthew C. Chan
- Department of Chemical and Biomolecular Engineering, University of Illinois Urbana−Champaign, Urbana, Illinois 61801, United States
| | - Erik Procko
- Department of Biochemistry, University of Illinois Urbana−Champaign, Urbana, Illinois 61801, United States
- Center for Biophysics and Quantitative Biology, University of Illinois Urbana−Champaign, Urbana, Illinois 61801, United States
- Neuroscience Program, University of Illinois Urbana−Champaign, Urbana, Illinois 61801, United States
- Cancer Center at Illinois, University of Illinois Urbana−Champaign, Urbana, Illinois 61801, United States
| | - Diwakar Shukla
- Department of Chemical and Biomolecular Engineering, University of Illinois Urbana−Champaign, Urbana, Illinois 61801, United States
- Center for Biophysics and Quantitative Biology, University of Illinois Urbana−Champaign, Urbana, Illinois 61801, United States
- Cancer Center at Illinois, University of Illinois Urbana−Champaign, Urbana, Illinois 61801, United States
- National Center for Supercomputing Applications, University of Illinois Urbana−Champaign, Urbana, Illinois 61801, United States
- Department of Bioengineering, University of Illinois Urbana−Champaign, Urbana, Illinois 61801, United States
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