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Zhu J, Gu Z, Pei J, Lai L. DiffBindFR: an SE(3) equivariant network for flexible protein-ligand docking. Chem Sci 2024; 15:7926-7942. [PMID: 38817560 PMCID: PMC11134415 DOI: 10.1039/d3sc06803j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 04/07/2024] [Indexed: 06/01/2024] Open
Abstract
Molecular docking, a key technique in structure-based drug design, plays pivotal roles in protein-ligand interaction modeling, hit identification and optimization, in which accurate prediction of protein-ligand binding mode is essential. Conventional docking approaches perform well in redocking tasks with known protein binding pocket conformation in the complex state. However, in real-world docking scenario without knowing the protein binding conformation for a new ligand, accurately modeling the binding complex structure remains challenging as flexible docking is computationally expensive and inaccurate. Typical deep learning-based docking methods do not explicitly consider protein side chain conformations and fail to ensure the physical plausibility and detailed atomic interactions. In this study, we present DiffBindFR, a full-atom diffusion-based flexible docking model that operates over the product space of ligand overall movements and flexibility and pocket side chain torsion changes. We show that DiffBindFR has higher accuracy in producing native-like binding structures with physically plausible and detailed interactions than available docking methods. Furthermore, in the Apo and AlphaFold2 modeled structures, DiffBindFR demonstrates superior advantages in accurate ligand binding pose and protein binding conformation prediction, making it suitable for Apo and AlphaFold2 structure-based drug design. DiffBindFR provides a powerful flexible docking tool for modeling accurate protein-ligand binding structures.
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Affiliation(s)
- Jintao Zhu
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University Beijing 100871 China
| | - Zhonghui Gu
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University Beijing 100871 China
| | - Jianfeng Pei
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University Beijing 100871 China
| | - Luhua Lai
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University Beijing 100871 China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University Beijing 100871 China
- BNLMS, College of Chemistry and Molecular Engineering, Peking University Beijing 100871 China
- Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies Chengdu Sichuan China
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2
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Nagavarapu S, Kumar J, Biswal PK. Molecular docking based comparative study of antiviral compounds on SARS-CoV-2 spike protein. Nat Prod Res 2024:1-9. [PMID: 38759218 DOI: 10.1080/14786419.2024.2355589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Accepted: 05/09/2024] [Indexed: 05/19/2024]
Abstract
The urgent need for effective therapeutic interventions against SARS-CoV-2 has prompted extensive exploration of potential drug candidates. Among the viral proteins, the spike (S) protein presents an attractive target due to its critical role in viral entry and infection. In this study, we employed molecular docking techniques to investigate the binding affinities and interaction profiles of a panel of active compounds against the SARS-CoV-2 spike protein. Utilising computational simulations, we assessed the binding properties of these compounds within the receptor-binding domain (RBD) and other key regions of the spike protein. Our comparative analysis elucidates the differential binding patterns and identifies promising lead compounds with high binding affinity and favourable interaction profiles. Furthermore, we discuss the implications of these findings for the development of potential therapeutics targeting the SARS-CoV-2 spike protein. Using molecular docking and the Lipinski five rule, this study illustrates possible compounds with strong binding affinities, their molecular interactions, for both naturally occurring and man-made drugs. Computational approach is applied, and it is concluded that, drugs like Withanolide, Dihydroergocristine, Fenebrutinib, and Ergotamine shows binding energies between -8.3 and -9.1 kcal/mol, and are possible candidate for anti covid drug.
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Affiliation(s)
- Sowmya Nagavarapu
- Department of Electronics and Communication Engineering, GIET University Gunupur, Odisha, India
| | - Jitendra Kumar
- Department of Electronics and Communication Engineering, GIET University Gunupur, Odisha, India
| | - Pradyut K Biswal
- Department of Electronics and Communication Engineering, IIIT Bhubaneswar, Odisha, India
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3
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Vergoten G, Bailly C. Interaction of Norsecurinine-Type Oligomeric Alkaloids with α-Tubulin: A Molecular Docking Study. PLANTS (BASEL, SWITZERLAND) 2024; 13:1269. [PMID: 38732484 PMCID: PMC11085049 DOI: 10.3390/plants13091269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 04/29/2024] [Accepted: 05/01/2024] [Indexed: 05/13/2024]
Abstract
The medicinal plant Securinega virosa (Roxb ex. Willd) Baill., also known as Flueggea virosa (Roxb. ex Willd.) Royle, is commonly used in traditional medicine in Africa and Asia for the management of diverse pathologies, such as parasite infections, diabetes, and gastrointestinal diseases. Numerous alkaloids have been isolated from the twigs and leaves of the plant, notably a variety of oligomeric indolizidine alkaloids derived from the monomers securinine and norsecurinine which both display anticancer properties. The recent discovery that securinine can bind to tubulin and inhibit microtubule assembly prompted us to investigate the potential binding of two series of alkaloids, fluevirosines A-H and fluevirosinine A-J, with the tubulin dimer by means of molecular modeling. These natural products are rare high-order alkaloids with tri-, tetra-, and pentameric norsecurinine motifs. Despite their large size (up to 2500 Å3), these alkaloids can bind easily to the large drug-binding cavity (about 4800 Å3) on α-tubulin facing the β-tubulin unit. The molecular docking analysis suggests that these hydrophobic macro-alkaloids can form stable complexes with α/β-tubulin. The tubulin-binding capacity varies depending on the alkaloid size and structure. Structure-binding relationships are discussed. The docking analysis identifies the trimer fluevirosine D, tetramer fluevirosinine D, and pentamer fluevirosinine H as the most interesting tubulin ligands in the series. This study is the first to propose a molecular target for these atypical oligomeric Securinega alkaloids.
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Affiliation(s)
- Gérard Vergoten
- U1286—INFINITE, Lille Inflammation Research International Center, Institut de Chimie Pharmaceutique Albert Lespagnol (ICPAL), Faculté de Pharmacie, University of Lille, 3 rue du Professeur Laguesse, 59006 Lille, France
| | - Christian Bailly
- CNRS, Inserm, CHU Lille, UMR9020-U1277-CANTHER—Cancer Heterogeneity Plasticity and Resistance to Therapies, OncoLille Institut, University of Lille, 59000 Lille, France
- Institute of Pharmaceutical Chemistry Albert Lespagnol (ICPAL), Faculty of Pharmacy, University of Lille, 59006 Lille, France
- OncoWitan, Scientific Consulting Office, 59290 Lille, France
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4
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Li X, Shen C, Zhu H, Yang Y, Wang Q, Yang J, Huang N. A High-Quality Data Set of Protein-Ligand Binding Interactions Via Comparative Complex Structure Modeling. J Chem Inf Model 2024; 64:2454-2466. [PMID: 38181418 DOI: 10.1021/acs.jcim.3c01170] [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: 01/07/2024]
Abstract
High-quality protein-ligand complex structures provide the basis for understanding the nature of noncovalent binding interactions at the atomic level and enable structure-based drug design. However, experimentally determined complex structures are scarce compared with the vast chemical space. In this study, we addressed this issue by constructing the BindingNet data set via comparative complex structure modeling, which contains 69,816 modeled high-quality protein-ligand complex structures with experimental binding affinity data. BindingNet provides valuable insights into investigating protein-ligand interactions, allowing visual inspection and interpretation of structural analogues' structure-activity relationships. It can also be used for evaluating machine-learning-based scoring functions. Our results indicate that machine learning models trained on BindingNet could reduce the bias caused by buried solvent-accessible surface area, as we previously found for models trained on the PDBbind data set. We also discussed strategies to improve BindingNet and its potential utilization for benchmarking the molecular docking methods and ligand binding free energy calculation approaches. The BindingNet complements PDBbind in constructing a sufficient and unbiased protein-ligand binding data set and is freely available at http://bindingnet.huanglab.org.cn.
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Affiliation(s)
- Xuelian Li
- National Institute of Biological Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
- National Institute of Biological Sciences, 7 Science Park Road, Zhongguancun Life Science Park, Beijing 102206, China
| | - Cheng Shen
- National Institute of Biological Sciences, 7 Science Park Road, Zhongguancun Life Science Park, Beijing 102206, China
| | - Hui Zhu
- National Institute of Biological Sciences, 7 Science Park Road, Zhongguancun Life Science Park, Beijing 102206, China
- Tsinghua Institute of Multidisciplinary Biomedical Research, Tsinghua University, Beijing 102206, China
| | - Yujian Yang
- National Institute of Biological Sciences, 7 Science Park Road, Zhongguancun Life Science Park, Beijing 102206, China
| | - Qing Wang
- National Institute of Biological Sciences, 7 Science Park Road, Zhongguancun Life Science Park, Beijing 102206, China
| | - Jincai Yang
- National Institute of Biological Sciences, 7 Science Park Road, Zhongguancun Life Science Park, Beijing 102206, China
| | - Niu Huang
- National Institute of Biological Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
- National Institute of Biological Sciences, 7 Science Park Road, Zhongguancun Life Science Park, Beijing 102206, China
- Tsinghua Institute of Multidisciplinary Biomedical Research, Tsinghua University, Beijing 102206, China
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5
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Fantacuzzi M, Agamennone M. Computational Methods in the Design of Anticancer Drugs. Pharmaceuticals (Basel) 2024; 17:404. [PMID: 38675367 PMCID: PMC11053996 DOI: 10.3390/ph17040404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Accepted: 03/20/2024] [Indexed: 04/28/2024] Open
Abstract
In recent years, continuous progress has been made in the development of new anticancer drugs, and several compounds (small molecules, engineered antibodies, immunomodulators, etc [...].
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Affiliation(s)
- Marialuigia Fantacuzzi
- Department of Pharmacy, University “G. d’Annunzio” of Chieti-Pescara, Via Dei Vestini, 31, 66100 Chieti, Italy
| | - Mariangela Agamennone
- Department of Pharmacy, University “G. d’Annunzio” of Chieti-Pescara, Via Dei Vestini, 31, 66100 Chieti, Italy
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6
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Knight IS, Mailhot O, Tang KG, Irwin JJ. DockOpt: A Tool for Automatic Optimization of Docking Models. J Chem Inf Model 2024; 64:1004-1016. [PMID: 38206771 PMCID: PMC10865354 DOI: 10.1021/acs.jcim.3c01406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 12/17/2023] [Accepted: 12/26/2023] [Indexed: 01/13/2024]
Abstract
Molecular docking is a widely used technique for leveraging protein structure for ligand discovery, but it remains difficult to utilize due to limitations that have not been adequately addressed. Despite some progress toward automation, docking still requires expert guidance, hindering its adoption by a broader range of investigators. To make docking more accessible, we developed a new utility called DockOpt, which automates the creation, evaluation, and optimization of docking models prior to their deployment in large-scale prospective screens. DockOpt outperforms our previous automated pipeline across all 43 targets in the DUDE-Z benchmark data set, and the generated models for 84% of targets demonstrate sufficient enrichment to warrant their use in prospective screens, with normalized LogAUC values of at least 15%. DockOpt is available as part of the Python package Pydock3 included in the UCSF DOCK 3.8 distribution, which is available for free to academic researchers at https://dock.compbio.ucsf.edu and free for everyone upon registration at https://tldr.docking.org.
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Affiliation(s)
- Ian S. Knight
- Department of Pharmaceutical Chemistry, UCSF, 1700 Fourth Street, San Francisco, California 94158-2330, United States
| | - Olivier Mailhot
- Department of Pharmaceutical Chemistry, UCSF, 1700 Fourth Street, San Francisco, California 94158-2330, United States
| | - Khanh G. Tang
- Department of Pharmaceutical Chemistry, UCSF, 1700 Fourth Street, San Francisco, California 94158-2330, United States
| | - John J. Irwin
- Department of Pharmaceutical Chemistry, UCSF, 1700 Fourth Street, San Francisco, California 94158-2330, United States
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7
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Wang Q, Fu X, Yan Y, Liu T, Xie Y, Song X, Zhou Y, Xu M, Wang P, Fu P, Huang J, Huang N. Structure-Based Identification of Organoruthenium Compounds as Nanomolar Antagonists of Cannabinoid Receptors. J Chem Inf Model 2024; 64:761-774. [PMID: 38215394 DOI: 10.1021/acs.jcim.3c01282] [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: 01/14/2024]
Abstract
Metal complexes exhibit a diverse range of coordination geometries, representing novel privileged scaffolds with convenient click types of preparation inaccessible for typical carbon-centered organic compounds. Herein, we explored the opportunity to identify biologically active organometallic complexes by reverse docking of a rigid, minimum-size octahedral organoruthenium scaffold against thousands of protein-binding pockets. Interestingly, cannabinoid receptor type 1 (CB1) was identified based on the docking scores and the degree of overlap between the docked organoruthenium scaffold and the hydrophobic scaffold of the cocrystallized ligand. Further structure-based optimization led to the discovery of organoruthenium complexes with nanomolar binding affinities and high selectivity toward CB2. Our work indicates that octahedral organoruthenium scaffolds may be advantageous for targeting the large and hydrophobic binding pockets and that the reverse docking approach may facilitate the discovery of novel privileged scaffolds, such as organometallic complexes, for exploring chemical space in lead discovery.
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Affiliation(s)
- Qing Wang
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin 300072, China
- National Institute of Biological Sciences, No. 7 Science Park Road, Zhongguancun Life Science Park, Beijing 102206, China
| | - Xuegang Fu
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin 300072, China
| | - Yuting Yan
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin 300072, China
| | - Tao Liu
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin 300072, China
- National Institute of Biological Sciences, No. 7 Science Park Road, Zhongguancun Life Science Park, Beijing 102206, China
| | - Yuting Xie
- National Institute of Biological Sciences, No. 7 Science Park Road, Zhongguancun Life Science Park, Beijing 102206, China
| | - Xiaoqing Song
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin 300072, China
| | - Yu Zhou
- National Institute of Biological Sciences, No. 7 Science Park Road, Zhongguancun Life Science Park, Beijing 102206, China
| | - Min Xu
- National Institute of Biological Sciences, No. 7 Science Park Road, Zhongguancun Life Science Park, Beijing 102206, China
| | - Ping Wang
- National Institute of Biological Sciences, No. 7 Science Park Road, Zhongguancun Life Science Park, Beijing 102206, China
| | - Peng Fu
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin 300072, China
| | - Jianhui Huang
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin 300072, China
| | - Niu Huang
- National Institute of Biological Sciences, No. 7 Science Park Road, Zhongguancun Life Science Park, Beijing 102206, China
- Tsinghua Institute of Multidisciplinary Biomedical Research, Tsinghua University, Beijing 102206, China
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8
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Charbe NB, Zacconi FC, Kowthavarapu VK, Gupta C, Palakurthi SS, Satheeshkumar R, Lokwani DK, Tambuwala MM, Palakurthi S. Targeting Allosteric Site of PCSK9 Enzyme for the Identification of Small Molecule Inhibitors: An In Silico Drug Repurposing Study. Biomedicines 2024; 12:286. [PMID: 38397888 PMCID: PMC10887305 DOI: 10.3390/biomedicines12020286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 12/29/2023] [Accepted: 01/23/2024] [Indexed: 02/25/2024] Open
Abstract
The primary cause of atherosclerotic cardiovascular disease (ASCVD) is elevated levels of low-density lipoprotein cholesterol (LDL-C). Proprotein convertase subtilisin/kexin type 9 (PCSK9) plays a crucial role in this process by binding to the LDL receptor (LDL-R) domain, leading to reduced influx of LDL-C and decreased LDL-R cell surface presentation on hepatocytes, resulting higher circulating levels of LDL-C. As a consequence, PCSK9 has been identified as a crucial target for drug development against dyslipidemia and hypercholesterolemia, aiming to lower plasma LDL-C levels. This research endeavors to identify promising inhibitory candidates that target the allosteric site of PCSK9 through an in silico approach. To start with, the FDA-approved Drug Library from Selleckchem was selected and virtually screened by docking studies using Glide extra-precision (XP) docking mode and Smina software (Version 1.1.2). Subsequently, rescoring of 100 drug compounds showing good average docking scores were performed using Gnina software (Version 1.0) to generate CNN Score and CNN binding affinity. Among the drug compounds, amikacin, bestatin, and natamycin were found to exhibit higher docking scores and CNN affinities against the PCSK9 enzyme. Molecular dynamics simulations further confirmed that these drug molecules established the stable protein-ligand complexes when compared to the apo structure of PCSK9 and the complex with the co-crystallized ligand structure. Moreover, the MM-GBSA calculations revealed binding free energy values ranging from -84.22 to -76.39 kcal/mol, which were found comparable to those obtained for the co-crystallized ligand structure. In conclusion, these identified drug molecules have the potential to serve as inhibitors PCSK9 enzyme and these finding could pave the way for the development of new PCSK9 inhibitory drugs in future in vitro research.
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Affiliation(s)
- Nitin Bharat Charbe
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics (Lake Nona), University of Florida, Orlando, FL 32827, USA; (V.K.K.); (C.G.)
| | - Flavia C. Zacconi
- Facultad de Química y de Farmacia, Pontificia Universidad Católica de Chile, Santiago 8320000, Chile;
- Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological Sciences, Pontificia Universidad Católica de Chile, Santiago 8320000, Chile
| | - Venkata Krishna Kowthavarapu
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics (Lake Nona), University of Florida, Orlando, FL 32827, USA; (V.K.K.); (C.G.)
| | - Churni Gupta
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics (Lake Nona), University of Florida, Orlando, FL 32827, USA; (V.K.K.); (C.G.)
| | - Sushesh Srivatsa Palakurthi
- Department of Pharmaceutical Sciences, Rangel College of Pharmacy, Texas A&M University, Kingsville, TX 78363, USA; (S.S.P.); (R.S.); (S.P.)
| | - Rajendran Satheeshkumar
- Department of Pharmaceutical Sciences, Rangel College of Pharmacy, Texas A&M University, Kingsville, TX 78363, USA; (S.S.P.); (R.S.); (S.P.)
| | - Deepak K. Lokwani
- Department of Pharmaceutical Chemistry, Rajarshi Shahu College of Pharmacy, Buldana 443001, India;
| | - Murtaza M. Tambuwala
- Lincoln Medical School, University of Lincoln, Brayford Pool Campus, Lincoln LN6 7TS, UK
| | - Srinath Palakurthi
- Department of Pharmaceutical Sciences, Rangel College of Pharmacy, Texas A&M University, Kingsville, TX 78363, USA; (S.S.P.); (R.S.); (S.P.)
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9
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Balius TE, Tan YS, Chakrabarti M. DOCK 6: Incorporating hierarchical traversal through precomputed ligand conformations to enable large-scale docking. J Comput Chem 2024; 45:47-63. [PMID: 37743732 DOI: 10.1002/jcc.27218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 08/17/2023] [Indexed: 09/26/2023]
Abstract
To allow DOCK 6 access to unprecedented chemical space for screening billions of small molecules, we have implemented features from DOCK 3.7 into DOCK 6, including a search routine that traverses precomputed ligand conformations stored in a hierarchical database. We tested them on the DUDE-Z and SB2012 test sets. The hierarchical database search routine is 16 times faster than anchor-and-grow. However, the ability of hierarchical database search to reproduce the experimental pose is 16% worse than that of anchor-and-grow. The enrichment performance is on average similar, but DOCK 3.7 has better enrichment than DOCK 6, and DOCK 6 is on average 1.7 times slower. However, with post-docking torsion minimization, DOCK 6 surpasses DOCK 3.7. A large-scale virtual screen is performed with DOCK 6 on 23 million fragment molecules. We use current features in DOCK 6 to complement hierarchical database calculations, including torsion minimization, which is not available in DOCK 3.7.
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Affiliation(s)
- Trent E Balius
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, Maryland, USA
| | - Y Stanley Tan
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, Maryland, USA
| | - Mayukh Chakrabarti
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, Maryland, USA
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10
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Du H, Jiang D, Zhang O, Wu Z, Gao J, Zhang X, Wang X, Deng Y, Kang Y, Li D, Pan P, Hsieh CY, Hou T. A flexible data-free framework for structure-based de novo drug design with reinforcement learning. Chem Sci 2023; 14:12166-12181. [PMID: 37969589 PMCID: PMC10631243 DOI: 10.1039/d3sc04091g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Accepted: 10/11/2023] [Indexed: 11/17/2023] Open
Abstract
Contemporary structure-based molecular generative methods have demonstrated their potential to model the geometric and energetic complementarity between ligands and receptors, thereby facilitating the design of molecules with favorable binding affinity and target specificity. Despite the introduction of deep generative models for molecular generation, the atom-wise generation paradigm that partially contradicts chemical intuition limits the validity and synthetic accessibility of the generated molecules. Additionally, the dependence of deep learning models on large-scale structural data has hindered their adaptability across different targets. To overcome these challenges, we present a novel search-based framework, 3D-MCTS, for structure-based de novo drug design. Distinct from prevailing atom-centric methods, 3D-MCTS employs a fragment-based molecular editing strategy. The fragments decomposed from small-molecule drugs are recombined under predefined retrosynthetic rules, offering improved drug-likeness and synthesizability, overcoming the inherent limitations of atom-based approaches. Leveraging multi-threaded parallel simulations combined with a real-time energy constraint-based pruning strategy, 3D-MCTS achieves remarkable efficiency. At a fixed computational cost, it outperforms other state-of-the-art (SOTA) methods by producing molecules with enhanced binding affinity. Furthermore, its fragment-based approach ensures the generation of more dependable binding conformations, exhibiting a success rate 43.6% higher than that of other SOTAs. This advantage becomes even more pronounced when handling targets that significantly deviate from the training dataset. 3D-MCTS is capable of achieving thirty times more hits with high binding affinity than traditional virtual screening methods, which demonstrates the superior ability of 3D-MCTS to explore chemical space. Moreover, the flexibility of our framework makes it easy to incorporate domain knowledge during the process, thereby enabling the generation of molecules with desirable pharmacophores and enhanced binding affinity. The adaptability of 3D-MCTS is further showcased in metalloprotein applications, highlighting its potential across various drug design scenarios.
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Affiliation(s)
- Hongyan Du
- College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
| | - Dejun Jiang
- College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
| | - Odin Zhang
- College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
| | - Zhenxing Wu
- College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
| | - Junbo Gao
- College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
| | - Xujun Zhang
- College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
| | - Xiaorui Wang
- Hangzhou Carbonsilicon AI Technology Co., Ltd Hangzhou 310018 Zhejiang China
- Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology Macao 999078 China
| | - Yafeng Deng
- Hangzhou Carbonsilicon AI Technology Co., Ltd Hangzhou 310018 Zhejiang China
| | - Yu Kang
- College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
| | - Dan Li
- College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
| | - Peichen Pan
- College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
| | - Chang-Yu Hsieh
- College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
| | - Tingjun Hou
- College of Pharmaceutical Sciences, Zhejiang University Hangzhou 310058 Zhejiang China
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11
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Wang G, Moitessier N, Mittermaier AK. Computational and biophysical methods for the discovery and optimization of covalent drugs. Chem Commun (Camb) 2023; 59:10866-10882. [PMID: 37609777 DOI: 10.1039/d3cc03285j] [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: 08/24/2023]
Abstract
Drugs that act by covalently attaching to their targets have been used to treat human diseases for over a hundred years. However, the deliberate design of covalent drugs was discouraged due to concerns of toxicity and off-target effects. Recent successes in covalent drug discovery have sparked fresh interest in this field. New screening and testing methods aimed at covalent inhibitors can play pivotal roles in facilitating the discovery process. This feature article focuses on computational and biophysical advances originating from our labs over the past decade and how these approaches have contributed to the design of prolyl oligopeptidase (POP) and SARS-CoV-2 3CLpro covalent inhibitors.
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Affiliation(s)
- Guanyu Wang
- Department of Chemistry, McGill University, 801 Sherbrooke Street West, Montreal, Quebec H3A 0B8, Canada.
| | - Nicolas Moitessier
- Department of Chemistry, McGill University, 801 Sherbrooke Street West, Montreal, Quebec H3A 0B8, Canada.
| | - Anthony K Mittermaier
- Department of Chemistry, McGill University, 801 Sherbrooke Street West, Montreal, Quebec H3A 0B8, Canada.
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12
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Cai H, Wang Y, Zhang J, Wei Z, Yan T, Feng C, Xu Z, Zhou A, Wu Y. Discovery of Novel SIRT1/2 Inhibitors with Effective Cytotoxicity against Human Leukemia Cells. J Chem Inf Model 2023; 63:4780-4790. [PMID: 37486605 DOI: 10.1021/acs.jcim.3c00556] [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: 07/25/2023]
Abstract
The sirtuin enzyme family members, SIRT1 and SIRT2, play both tumor-promoting and tumor-suppressing roles, depending on the context and experimental conditions. Compounds that inhibit either SIRT1 or SIRT2 show promising antitumor effects in several types of cancer models, both in vitro and in vivo. The simultaneous inhibition of SIRT1 and SIRT2 is helpful in treating cancer by completely blocking p53 deacetylation, leading to cell death. However, only a few SIRT1/2 dual inhibitors have been developed. Here, we report the discovery of a novel series of SIRT1/2 dual inhibitors via a rational drug design that involved virtual screening and a substructure search. Eleven of the derived compounds exhibited high inhibitory activities, with IC50 < 5 μM and high specificity for both SIRT1 and SIRT2. Compounds hsa55 and PS9 strongly induced apoptosis and showed antiproliferative effects against human leukemia cell lines, which could be due to their ability to increase of p53 and α-tubulin acetylation, as we observed in MOLM-13 cells. Therefore, the new scaffolds of these compounds and their efficacy in leukemia cell lines provide important clues for the further development of novel anti-leukemia drugs.
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Affiliation(s)
- Haiyan Cai
- Department of Hematology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai 200120, China
- Key Laboratory of Cell Differentiation and Apoptosis of the Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yingying Wang
- Key Laboratory of Cell Differentiation and Apoptosis of the Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Hongqiao International Institute of Medicine, Shanghai Tongren Hospital/Faculty of Basic Medicine, Shanghai 200025, China
| | - Jing Zhang
- Key Laboratory of Cell Differentiation and Apoptosis of the Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Zhenquan Wei
- Key Laboratory of Cell Differentiation and Apoptosis of the Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Teng Yan
- Key Laboratory of Cell Differentiation and Apoptosis of the Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Chenxi Feng
- Key Laboratory of Cell Differentiation and Apoptosis of the Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Zhijian Xu
- Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Aiwu Zhou
- Key Laboratory of Cell Differentiation and Apoptosis of the Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yingli Wu
- Key Laboratory of Cell Differentiation and Apoptosis of the Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Hongqiao International Institute of Medicine, Shanghai Tongren Hospital/Faculty of Basic Medicine, Shanghai 200025, China
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13
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Santos VC, Leite PG, Santos LH, Pascutti PG, Kolb P, Machado FS, Ferreira RS. Structure-based discovery of novel cruzain inhibitors with distinct trypanocidal activity profiles. Eur J Med Chem 2023; 257:115498. [PMID: 37290182 DOI: 10.1016/j.ejmech.2023.115498] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 05/10/2023] [Accepted: 05/15/2023] [Indexed: 06/10/2023]
Abstract
Over 110 years after the first formal description of Chagas disease, the trypanocidal drugs thus far available have limited efficacy and several side effects. This encourages the search for novel treatments that inhibit T. cruzi targets. One of the most studied anti-T. cruzi targets is the cysteine protease cruzain; it is associated with metacyclogenesis, replication, and invasion of the host cells. We used computational techniques to identify novel molecular scaffolds that act as cruzain inhibitors. First, with a docking-based virtual screening, we identified compound 8, a competitive cruzain inhibitor with a Ki of 4.6 μM. Then, aided by molecular dynamics simulations, cheminformatics, and docking, we identified the analog compound 22 with a Ki of 27 μM. Surprisingly, despite sharing the same isoquinoline scaffold, compound 8 presented higher trypanocidal activity against the epimastigote forms, while compound 22, against the trypomastigotes and amastigotes. Taken together, compounds 8 and 22 represent a promising scaffold for further development of trypanocidal compounds as drug candidates for treating Chagas disease.
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Affiliation(s)
- Viviane Corrêa Santos
- Laboratório de Modelagem Molecular e Planejamento de Fármacos, Departamento de Bioquímica e Imunologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Avenida Antônio Carlos 6627, Belo Horizonte, MG, 31270-901, Brazil
| | - Paulo Gaio Leite
- Departamento de Bioquímica e Imunologia, Universidade Federal de Minas Gerais, Avenida Antonio Carlos 6627, Belo Horizonte, MG, 31270-901, Brazil
| | - Lucianna Helene Santos
- Laboratório de Modelagem Molecular e Planejamento de Fármacos, Departamento de Bioquímica e Imunologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Avenida Antônio Carlos 6627, Belo Horizonte, MG, 31270-901, Brazil
| | - Pedro Geraldo Pascutti
- Laboratório de Modelagem e Dinâmica Molecular, Instituto de Biofísica, Universidade Federal do Rio de Janeiro, Av. Carlos Chagas Filho, 373, Rio de Janeiro, RJ, CEP 21944-970, Brazil
| | - Peter Kolb
- Pharmaceutical Chemistry, Philipps-University Marburg, Marbacher Weg 6, 35037, Marburg, Germany
| | - Fabiana Simão Machado
- Departamento de Bioquímica e Imunologia, Universidade Federal de Minas Gerais, Avenida Antonio Carlos 6627, Belo Horizonte, MG, 31270-901, Brazil
| | - Rafaela Salgado Ferreira
- Laboratório de Modelagem Molecular e Planejamento de Fármacos, Departamento de Bioquímica e Imunologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Avenida Antônio Carlos 6627, Belo Horizonte, MG, 31270-901, Brazil.
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14
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Lauritano C, Montuori E, De Falco G, Carrella S. In Silico Methodologies to Improve Antioxidants' Characterization from Marine Organisms. Antioxidants (Basel) 2023; 12:710. [PMID: 36978958 PMCID: PMC10045275 DOI: 10.3390/antiox12030710] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 03/02/2023] [Accepted: 03/07/2023] [Indexed: 03/17/2023] Open
Abstract
Marine organisms have been reported to be valuable sources of bioactive molecules that have found applications in different industrial fields. From organism sampling to the identification and bioactivity characterization of a specific compound, different steps are necessary, which are time- and cost-consuming. Thanks to the advent of the -omic era, numerous genome, metagenome, transcriptome, metatranscriptome, proteome and microbiome data have been reported and deposited in public databases. These advancements have been fundamental for the development of in silico strategies for basic and applied research. In silico studies represent a convenient and efficient approach to the bioactivity prediction of known and newly identified marine molecules, reducing the time and costs of "wet-lab" experiments. This review focuses on in silico approaches applied to bioactive molecule discoveries from marine organisms. When available, validation studies reporting a bioactivity assay to confirm the presence of an antioxidant molecule or enzyme are reported, as well. Overall, this review suggests that in silico approaches can offer a valuable alternative to most expensive approaches and proposes them as a little explored field in which to invest.
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Affiliation(s)
- Chiara Lauritano
- Ecosustainable Marine Biotechnology Department, Stazione Zoologica Anton Dohrn, Via Acton 55, 80133 Napoli, Italy
| | - Eleonora Montuori
- Ecosustainable Marine Biotechnology Department, Stazione Zoologica Anton Dohrn, Via Acton 55, 80133 Napoli, Italy
- Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, University of Messina, Viale F. Stagno d’Alcontres 31, 98166 Messina, Italy
| | - Gabriele De Falco
- Ecosustainable Marine Biotechnology Department, Stazione Zoologica Anton Dohrn, Via Acton 55, 80133 Napoli, Italy
| | - Sabrina Carrella
- Ecosustainable Marine Biotechnology Department, Stazione Zoologica Anton Dohrn, Via Acton 55, 80133 Napoli, Italy
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