Structure-based discovery of conformationally selective inhibitors of the serotonin transporter

Singh, Isha; Seth, Anubha; Billesbølle, Christian B.; Bráz, Joao; Rodriguiz, Ramona M.; Roy, Kasturi; Bekele, Bethlehem; Craik, Veronica; Huang, Xi‐Ping; Boytsov, Danila; Pogorelov, Vladimir M.; Lak, Parnian; O'Donnell, Henry R; Sandtner, Walter; Irwin, John J.; Roth, Bryan L.; Basbaum, Allan I.; Wetsel, William C.; Manglik, Aashish; Shoichet, Brian K; Rudnick, Gary

doi:10.1016/j.cell.2023.04.010

Cited by 25 publications

(18 citation statements)

References 128 publications

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“…Additionally, docking was used to reveal the potential binding sites , or investigate the interacting mechanism of ligands on targets, such as apical sodium-dependent bile acid transporter (ASBT, SLC10A2), norepinephrine transporter (NET), organic cation transporter 1 (OCT1, SLC22A1), and so on. , More recently, a systematic structure-based method combing Gaussian-accelerated molecular dynamics (GaMD) simulation and docking was performed to explore allosteric sites on DAT in inward-open conformation and to screen hit compounds with allosteric affinity . Meanwhile, docking of 200 million small molecules against the inward-open state of the SERT identified lead compound stabilized an outward-closed state of the SERT with little activity against common off-targets which confirmed by cryo-EM structure …”

Section: Drug Design Targeting Slcsmentioning

confidence: 99%

“…39 Meanwhile, docking of 200 million small molecules against the inwardopen state of the SERT identified lead compound stabilized an outward-closed state of the SERT with little activity against common off-targets which confirmed by cryo-EM structure. 44 Ligand-Based Virtual Screening. Ligand-based virtual screening (LBVS) relies on the structural information and physicochemical properties of the chemical scaffold of known active and inactive molecules, which are examined under the molecular similarity principle.…”

Section: ■ Drug Design Targeting Slcsmentioning

confidence: 99%

“…Despite the fact that the method still has some shortcomings, protein–ligand docking plays a significant role in early stage drug discovery. For example, Singh et al applied molecular docking approaches to screen several novel SERT inhibitors from ∼20 billion small molecules and further identified two of them to have significant antidepressant effects and inhibitory effects on withdrawal symptoms associated with drug addiction through mouse behavioral assays …”

Section: Introductionmentioning

confidence: 99%

“…MD simulation is an important computational approach used to study the atomistic-level behavior and movement of molecular systems over time . MD simulation assists scientists in obtaining the microscopic mechanism of structural dynamics information, including the key intermediate conformational states and interactions of molecular systems, which are difficult to capture by experimental methods. , For SLCs, recent developments of the structures of human SERT have been solved in the presence of ligands in three conformations, ,, which provide a basis for the application of MD simulations in drug design. Chan et al systematically studied the mechanism of how glycosylation affected the SLC6 transporters over a total of 1 ms MD simulation .…”

Section: Introductionmentioning

confidence: 99%

“…For example, Singh et al applied molecular docking approaches to screen several novel SERT inhibitors from ∼20 billion small molecules and further identified two of them to have significant antidepressant effects and inhibitory effects on withdrawal symptoms associated with drug addiction through mouse behavioral assays. 44 Molecular Dynamics Simulation. MD simulation is an important computational approach used to study the atomisticlevel behavior and movement of molecular systems over time.…”

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confidence: 99%

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Computational Chemistry in Structure-Based Solute Carrier Transporter Drug Design: Recent Advances and Future Perspectives

Tu,

Fu,

Zheng

et al. 2024

J. Chem. Inf. Model.

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Solute carrier transporters (SLCs) are a class of important transmembrane proteins that are involved in the transportation of diverse solute ions and small molecules into cells. There are approximately 450 SLCs within the human body, and more than a quarter of them are emerging as attractive therapeutic targets for multiple complex diseases, e.g., depression, cancer, and diabetes. However, only 44 unique transporters (∼9.8% of the SLC superfamily) with 3D structures and specific binding sites have been reported. To design innovative and effective drugs targeting diverse SLCs, there are a number of obstacles that need to be overcome. However, computational chemistry, including physics-based molecular modeling and machine learning-and deep learning-based artificial intelligence (AI), provides an alternative and complementary way to the classical drug discovery approach. Here, we present a comprehensive overview on recent advances and existing challenges of the computational techniques in structure-based drug design of SLCs from three main aspects: (i) characterizing multiple conformations of the proteins during the functional process of transportation, (ii) identifying druggability sites especially the cryptic allosteric ones on the transporters for substrates and drugs binding, and (iii) discovering diverse small molecules or synthetic protein binders targeting the binding sites. This work is expected to provide guidelines for a deep understanding of the structure and function of the SLC superfamily to facilitate rational design of novel modulators of the transporters with the aid of state-of-the-art computational chemistry technologies including artificial intelligence.

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Section: Drug Design Targeting Slcsmentioning

confidence: 99%

Section: ■ Drug Design Targeting Slcsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Computational Chemistry in Structure-Based Solute Carrier Transporter Drug Design: Recent Advances and Future Perspectives

Tu,

Fu,

Zheng

et al. 2024

J. Chem. Inf. Model.

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Large library docking for novel SARS‐CoV‐2 main protease non‐covalent and covalent inhibitors

et al. 2023

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Antiviral therapeutics to treat SARS‐CoV‐2 are needed to diminish the morbidity of the ongoing COVID‐19 pandemic. A well‐precedented drug target is the main viral protease (MPro), which is targeted by an approved drug and by several investigational drugs. Emerging viral resistance has made new inhibitor chemotypes more pressing. Adopting a structure‐based approach, we docked 1.2 billion non‐covalent lead‐like molecules and a new library of 6.5 million electrophiles against the enzyme structure. From these, 29 non‐covalent and 11 covalent inhibitors were identified in 37 series, the most potent having an IC50 of 29 and 20 μM, respectively. Several series were optimized, resulting in low micromolar inhibitors. Subsequent crystallography confirmed the docking predicted binding modes and may template further optimization. While the new chemotypes may aid further optimization of MPro inhibitors for SARS‐CoV‐2, the modest success rate also reveals weaknesses in our approach for challenging targets like MPro versus other targets where it has been more successful, and versus other structure‐based techniques against MPro itself.

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Neuroscience in addiction research

Valentino,

Nair,

Volkow

2023

J Neural Transm

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Structure-based discovery of conformationally selective inhibitors of the serotonin transporter

Cited by 25 publications

References 128 publications

Computational Chemistry in Structure-Based Solute Carrier Transporter Drug Design: Recent Advances and Future Perspectives

Computational Chemistry in Structure-Based Solute Carrier Transporter Drug Design: Recent Advances and Future Perspectives

Large library docking for novel SARS‐CoV‐2 main protease non‐covalent and covalent inhibitors

Neuroscience in addiction research

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