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Liu Y(L, Moretti R, Wang Y, Dong H, Yan B, Bodenheimer B, Derr T, Meiler J. Advancements in Ligand-Based Virtual Screening through the Synergistic Integration of Graph Neural Networks and Expert-Crafted Descriptors. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.04.17.537185. [PMID: 37131837 PMCID: PMC10153143 DOI: 10.1101/2023.04.17.537185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The fusion of traditional chemical descriptors with Graph Neural Networks (GNNs) offers a compelling strategy for enhancing ligand-based virtual screening methodologies. A comprehensive evaluation revealed that the benefits derived from this integrative strategy vary significantly among different GNNs. Specifically, while GCN and SchNet demonstrate pronounced improvements by incorporating descriptors, SphereNet exhibits only marginal enhancement. Intriguingly, despite SphereNet's modest gain, all three models-GCN, SchNet, and SphereNet-achieve comparable performance levels when leveraging this combination strategy. This observation underscores a pivotal insight: sophisticated GNN architectures may be substituted with simpler counterparts without sacrificing efficacy, provided that they are augmented with descriptors. Furthermore, our analysis reveals a set of expert-crafted descriptors' robustness in scaffold-split scenarios, frequently outperforming the combined GNN-descriptor models. Given the critical importance of scaffold splitting in accurately mimicking real-world drug discovery contexts, this finding accentuates an imperative for GNN researchers to innovate models that can adeptly navigate and predict within such frameworks. Our work not only validates the potential of integrating descriptors with GNNs in advancing ligand-based virtual screening but also illuminates pathways for future enhancements in model development and application. Our implementation can be found at https://github.com/meilerlab/gnn-descriptor.
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Affiliation(s)
- Yunchao (Lance) Liu
- Department of Computer Science, Vanderbilt University, 2201 West End Ave Nashville, Tennessee 37235, USA
| | - Rocco Moretti
- Department of Chemistry, Center for Structural Biology, Vanderbilt University, 2201 West End Ave Nashville, Tennessee 37235, USA
| | - Yu Wang
- Department of Computer Science, Vanderbilt University, 2201 West End Ave Nashville, Tennessee 37235, USA
| | - Ha Dong
- Department of Neural Science, Amherst College, 220 South Pleasant Street Amherst, Massachusetts 01002, USA
| | - Bailu Yan
- Department of Biostatistics, Vanderbilt University, 2201 West End Ave Nashville, Tennessee 37235, USA
| | - Bobby Bodenheimer
- Department of Computer Science, Electrical Engineering and Computer Engineering, Vanderbilt University, 2201 West End Ave Nashville, Tennessee 37235, USA
| | - Tyler Derr
- Department of Computer Science, Data Science Institute, Data Science Institute, Vanderbilt University, 2201 West End Ave Nashville, Tennessee 37235, USA
| | - Jens Meiler
- Department of Chemistry, Center for Structural Biology, Vanderbilt University, 2201 West End Ave Nashville, Tennessee 37235, USA, Institute of Drug Discovery, Leipzig University Medical School, Härtelstraße 16-18, Leipzig, 04103, Germany, Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), Humboldtstraße 25, Leipzig, 04105, Germany
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Meng Q, Moinuddin SGA, Celoy RM, Smith CA, Young RP, Costa MA, Freeman RA, Fukaya M, Kim DN, Cort JR, Hawes MC, van Etten HD, Pandey P, Chittiboyina AG, Ferreira D, Davin LB, Lewis NG. Dirigent isoflavene-forming PsPTS2: 3D structure, stereochemical, and kinetic characterization comparison with pterocarpan-forming PsPTS1 homolog in pea. J Biol Chem 2024; 300:105647. [PMID: 38219818 PMCID: PMC10882141 DOI: 10.1016/j.jbc.2024.105647] [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] [Received: 08/03/2023] [Revised: 12/21/2023] [Accepted: 01/05/2024] [Indexed: 01/16/2024] Open
Abstract
Pea phytoalexins (-)-maackiain and (+)-pisatin have opposite C6a/C11a configurations, but biosynthetically how this occurs is unknown. Pea dirigent-protein (DP) PsPTS2 generates 7,2'-dihydroxy-4',5'-methylenedioxyisoflav-3-ene (DMDIF), and stereoselectivity toward four possible 7,2'-dihydroxy-4',5'-methylenedioxyisoflavan-4-ol (DMDI) stereoisomers was investigated. Stereoisomer configurations were determined using NMR spectroscopy, electronic circular dichroism, and molecular orbital analyses. PsPTS2 efficiently converted cis-(3R,4R)-DMDI into DMDIF 20-fold faster than the trans-(3R,4S)-isomer. The 4R-configured substrate's near β-axial OH orientation significantly enhanced its leaving group abilities in generating A-ring mono-quinone methide (QM), whereas 4S-isomer's α-equatorial-OH was a poorer leaving group. Docking simulations indicated that the 4R-configured β-axial OH was closest to Asp51, whereas 4S-isomer's α-equatorial OH was further away. Neither cis-(3S,4S)- nor trans-(3S,4R)-DMDIs were substrates, even with the former having C3/C4 stereochemistry as in (+)-pisatin. PsPTS2 used cis-(3R,4R)-7,2'-dihydroxy-4'-methoxyisoflavan-4-ol [cis-(3R,4R)-DMI] and C3/C4 stereoisomers to give 2',7-dihydroxy-4'-methoxyisoflav-3-ene (DMIF). DP homologs may exist in licorice (Glycyrrhiza pallidiflora) and tree legume Bolusanthus speciosus, as DMIF occurs in both species. PsPTS1 utilized cis-(3R,4R)-DMDI to give (-)-maackiain 2200-fold more efficiently than with cis-(3R,4R)-DMI to give (-)-medicarpin. PsPTS1 also slowly converted trans-(3S,4R)-DMDI into (+)-maackiain, reflecting the better 4R configured OH leaving group. PsPTS2 and PsPTS1 provisionally provide the means to enable differing C6a and C11a configurations in (+)-pisatin and (-)-maackiain, via identical DP-engendered mono-QM bound intermediate generation, which PsPTS2 either re-aromatizes to give DMDIF or PsPTS1 intramolecularly cyclizes to afford (-)-maackiain. Substrate docking simulations using PsPTS2 and PsPTS1 indicate cis-(3R,4R)-DMDI binds in the anti-configuration in PsPTS2 to afford DMDIF, and the syn-configuration in PsPTS1 to give maackiain.
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Affiliation(s)
- Qingyan Meng
- Institute of Biological Chemistry, Washington State University, Pullman, Washington, USA
| | - Syed G A Moinuddin
- Institute of Biological Chemistry, Washington State University, Pullman, Washington, USA
| | - Rhodesia M Celoy
- School of Plant Sciences, University of Arizona, Tucson, Arizona, USA
| | - Clyde A Smith
- Stanford Synchrotron Radiation Lightsource, Stanford University, Menlo Park, California, USA
| | - Robert P Young
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Michael A Costa
- Institute of Biological Chemistry, Washington State University, Pullman, Washington, USA
| | - Rachel A Freeman
- Institute of Biological Chemistry, Washington State University, Pullman, Washington, USA
| | - Masashi Fukaya
- Institute of Biological Chemistry, Washington State University, Pullman, Washington, USA
| | - Doo Nam Kim
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - John R Cort
- Institute of Biological Chemistry, Washington State University, Pullman, Washington, USA; Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Martha C Hawes
- School of Plant Sciences, University of Arizona, Tucson, Arizona, USA
| | - Hans D van Etten
- School of Plant Sciences, University of Arizona, Tucson, Arizona, USA
| | - Pankaj Pandey
- National Center for Natural Products Research, School of Pharmacy, University of Mississippi, University, Mississippi, USA
| | - Amar G Chittiboyina
- National Center for Natural Products Research, School of Pharmacy, University of Mississippi, University, Mississippi, USA
| | - Daneel Ferreira
- National Center for Natural Products Research, School of Pharmacy, University of Mississippi, University, Mississippi, USA; Division of Pharmacognosy, Department of BioMolecular Sciences, School of Pharmacy, University of Mississippi, University, Mississippi, USA
| | - Laurence B Davin
- Institute of Biological Chemistry, Washington State University, Pullman, Washington, USA
| | - Norman G Lewis
- Institute of Biological Chemistry, Washington State University, Pullman, Washington, USA.
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Schüß C, Vu O, Mishra NM, Tough IR, Du Y, Stichel J, Cox HM, Weaver CD, Meiler J, Emmitte KA, Beck-Sickinger AG. Structure-Activity Relationship Study of the High-Affinity Neuropeptide Y 4 Receptor Positive Allosteric Modulator VU0506013. J Med Chem 2023. [PMID: 37339079 DOI: 10.1021/acs.jmedchem.3c00383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/22/2023]
Abstract
Positive allosteric modulators targeting the Y4 receptor (Y4R), a G protein-coupled receptor (GPCR) involved in the regulation of satiety, offer great potential in anti-obesity research. In this study, we selected 603 compounds by using quantitative structure-activity relationship (QSAR) models and tested them in high-throughput screening (HTS). Here, the novel positive allosteric modulator (PAM) VU0506013 was identified, which exhibits nanomolar affinity and pronounced selectivity toward the Y4R in engineered cell lines and mouse descending colon mucosa natively expressing the Y4R. Based on this lead structure, we conducted a systematic SAR study in two regions of the scaffold and presented a series of 27 analogues with modifications in the N- and C-terminal heterocycles of the molecule to obtain insight into functionally relevant positions. By mutagenesis and computational docking, we present a potential binding mode of VU0506013 in the transmembrane core of the Y4R. VU0506013 presents a promising scaffold for developing in vivo tools to move toward anti-obesity drug research focused on the Y4R.
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Affiliation(s)
- Corinna Schüß
- Institute of Biochemistry, Leipzig University, Leipzig 04103, Germany
| | - Oanh Vu
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States
| | - Nigam M Mishra
- Department of Pharmaceutical Sciences, UNT System College of Pharmacy, University of North Texas Health Science Center, Fort Worth, Texas 76107, United States
| | - Iain R Tough
- King's College London, Wolfson Centre for Age-Related Diseases, Institute of Psychiatry, Psychology & Neuroscience, London SE1 1UL, U.K
| | - Yu Du
- Department of Pharmacology, Vanderbilt University, Nashville, Tennessee 37232, United States
| | - Jan Stichel
- Institute of Biochemistry, Leipzig University, Leipzig 04103, Germany
| | - Helen M Cox
- King's College London, Wolfson Centre for Age-Related Diseases, Institute of Psychiatry, Psychology & Neuroscience, London SE1 1UL, U.K
| | - C David Weaver
- Department of Pharmacology, Vanderbilt University, Nashville, Tennessee 37232, United States
- Institute of Chemical Biology, Vanderbilt University, Nashville, Tennessee 37232, United States
| | - Jens Meiler
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States
- Department of Pharmacology, Vanderbilt University, Nashville, Tennessee 37232, United States
- Institute for Drug Discovery, Leipzig University, Leipzig 04103, Germany
| | - Kyle A Emmitte
- Department of Pharmaceutical Sciences, UNT System College of Pharmacy, University of North Texas Health Science Center, Fort Worth, Texas 76107, United States
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Li S, Nguyen PT, Vu S, Yarov-Yarovoy V, Zheng J. Opening of capsaicin receptor TRPV1 is stabilized equally by its four subunits. J Biol Chem 2023; 299:104828. [PMID: 37196769 PMCID: PMC10318505 DOI: 10.1016/j.jbc.2023.104828] [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: 02/25/2023] [Revised: 05/04/2023] [Accepted: 05/10/2023] [Indexed: 05/19/2023] Open
Abstract
Capsaicin receptor TRPV1 is a nociceptor for vanilloid molecules, such as capsaicin and resiniferatoxin (RTX). Even though cryo-EM structures of TRPV1 in complex with these molecules are available, how their binding energetically favors the open conformation is not known. Here, we report an approach to control the number of bound RTX molecules (0-4) in functional rat TRPV1. The approach allowed direct measurements of each of the intermediate open states under equilibrium conditions at both macroscopic and single-molecule levels. We found that RTX binding to each of the four subunits contributes virtually the same activation energy, which we estimated to be 1.70 to 1.86 kcal/mol and found to arise predominately from destabilizing the closed conformation. We further showed that sequential bindings of RTX increase open probability without altering single-channel conductance, confirming that there is likely a single open-pore conformation for TRPV1 activated by RTX.
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Affiliation(s)
- Shisheng Li
- Department of Physiology and Membrane Biology, School of Medicine, University of California at Davis, Davis, California, USA
| | - Phuong T Nguyen
- Department of Physiology and Membrane Biology, School of Medicine, University of California at Davis, Davis, California, USA
| | - Simon Vu
- Department of Physiology and Membrane Biology, School of Medicine, University of California at Davis, Davis, California, USA
| | - Vladimir Yarov-Yarovoy
- Department of Physiology and Membrane Biology, School of Medicine, University of California at Davis, Davis, California, USA
| | - Jie Zheng
- Department of Physiology and Membrane Biology, School of Medicine, University of California at Davis, Davis, California, USA.
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Liessmann F, Künze G, Meiler J. Improving the Modeling of Extracellular Ligand Binding Pockets in RosettaGPCR for Conformational Selection. Int J Mol Sci 2023; 24:7788. [PMID: 37175495 PMCID: PMC10178219 DOI: 10.3390/ijms24097788] [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: 04/03/2023] [Revised: 04/19/2023] [Accepted: 04/22/2023] [Indexed: 05/15/2023] Open
Abstract
G protein-coupled receptors (GPCRs) are the largest class of drug targets and undergo substantial conformational changes in response to ligand binding. Despite recent progress in GPCR structure determination, static snapshots fail to reflect the conformational space of putative binding pocket geometries to which small molecule ligands can bind. In comparative modeling of GPCRs in the absence of a ligand, often a shrinking of the orthosteric binding pocket is observed. However, the exact prediction of the flexible orthosteric binding site is crucial for adequate structure-based drug discovery. In order to improve ligand docking and guide virtual screening experiments in computer-aided drug discovery, we developed RosettaGPCRPocketSize. The algorithm creates a conformational ensemble of biophysically realistic conformations of the GPCR binding pocket between the TM bundle, which is consistent with a knowledge base of expected pocket geometries. Specifically, tetrahedral volume restraints are defined based on information about critical residues in the orthosteric binding site and their experimentally observed range of Cα-Cα-distances. The output of RosettaGPCRPocketSize is an ensemble of binding pocket geometries that are filtered by energy to ensure biophysically probable arrangements, which can be used for docking simulations. In a benchmark set, pocket shrinkage observed in the default RosettaGPCR was reduced by up to 80% and the binding pocket volume range and geometric diversity were increased. Compared to models from four different GPCR homology model databases (RosettaGPCR, GPCR-Tasser, GPCR-SSFE, and GPCRdb), the here-created models showed more accurate volumes of the orthosteric pocket when evaluated with respect to the crystallographic reference structure. Furthermore, RosettaGPCRPocketSize was able to generate an improved realistic pocket distribution. However, while being superior to other homology models, the accuracy of generated model pockets was comparable to AlphaFold2 models. Furthermore, in a docking benchmark using small-molecule ligands with a higher molecular weight between 400 and 700 Da, a higher success rate in creating native-like binding poses was observed. In summary, RosettaGPCRPocketSize can generate GPCR models with realistic orthosteric pocket volumes, which are useful for structure-based drug discovery applications.
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Affiliation(s)
- Fabian Liessmann
- Institute for Drug Discovery, Medical Faculty, Leipzig University, 04103 Leipzig, Germany; (F.L.)
| | - Georg Künze
- Institute for Drug Discovery, Medical Faculty, Leipzig University, 04103 Leipzig, Germany; (F.L.)
| | - Jens Meiler
- Institute for Drug Discovery, Medical Faculty, Leipzig University, 04103 Leipzig, Germany; (F.L.)
- Department of Chemistry, Vanderbilt University, Nashville, TN 37235, USA
- Center for Structural Biology, Vanderbilt University, Nashville, TN 37235, USA
- Center for Scalable Data Analytics and Artificial Intelligence, Leipzig University, 04105 Leipzig, Germany
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Li S, Nguyen PT, Vu S, Yarov-Yarovoy V, Zheng J. TRPV1 Opening is Stabilized Equally by Its Four Subunits. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.26.525787. [PMID: 36747729 PMCID: PMC9900918 DOI: 10.1101/2023.01.26.525787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Capsaicin receptor TRPV1 is a nociceptor for vanilloid molecules such as capsaicin and resiniferatoxin (RTX). Even though cryo-EM structures of TRPV1 in complex with these molecules are available, how their binding energetically favors the open conformation is not known. Here we report an approach to control the number of bound RTX molecules (0-to-4) in functional mouse TRPV1. The approach allowed direct measurements of each of the intermediate open states under equilibrium conditions at both macroscopic and single-molecule levels. We found that RTX binding to each of the four subunits contributes virtually the same activation energy, which we estimated to be 1.86 kcal/mol and found to arise predominately from destabilizing the closed conformation. We further showed that sequential bindings of RTX increase open probability without altering single-channel conductance, confirming that there is likely a single open-pore conformation for TRPV1 activated by RTX.
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In-Silico Drug Toxicity and Interaction Prediction for Plant Complexes Based on Virtual Screening and Text Mining. Int J Mol Sci 2022; 23:ijms231710056. [PMID: 36077464 PMCID: PMC9456415 DOI: 10.3390/ijms231710056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 08/30/2022] [Accepted: 09/01/2022] [Indexed: 11/16/2022] Open
Abstract
Potential drug toxicities and drug interactions of redundant compounds of plant complexes may cause unexpected clinical responses or even severe adverse events. On the other hand, super-additivity of drug interactions between natural products and synthetic drugs may be utilized to gain better performance in disease management. Although without enough datasets for prediction model training, based on the SwissSimilarity and PubChem platforms, for the first time, a feasible workflow of prediction of both toxicity and drug interaction of plant complexes was built in this study. The optimal similarity score threshold for toxicity prediction of this system is 0.6171, based on an analysis of 20 different herbal medicines. From the PubChem database, 31 different sections of toxicity information such as "Acute Effects", "NIOSH Toxicity Data", "Interactions", "Hepatotoxicity", "Carcinogenicity", "Symptoms", and "Human Toxicity Values" sections have been retrieved, with dozens of active compounds predicted to exert potential toxicities. In Spatholobus suberectus Dunn (SSD), there are 9 out of 24 active compounds predicted to play synergistic effects on cancer management with various drugs or factors. The synergism between SSD, luteolin and docetaxel in the management of triple-negative breast cancer was proved by the combination index assay, synergy score detection assay, and xenograft model.
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