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Borsatto A, Gianquinto E, Rizzi V, Gervasio FL. SWISH-X, an Expanded Approach to Detect Cryptic Pockets in Proteins and at Protein-Protein Interfaces. J Chem Theory Comput 2024; 20:3335-3348. [PMID: 38563746 PMCID: PMC11044271 DOI: 10.1021/acs.jctc.3c01318] [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: 12/01/2023] [Revised: 03/22/2024] [Accepted: 03/23/2024] [Indexed: 04/04/2024]
Abstract
Protein-protein interactions mediate most molecular processes in the cell, offering a significant opportunity to expand the set of known druggable targets. Unfortunately, targeting these interactions can be challenging due to their typically flat and featureless interaction surfaces, which often change as the complex forms. Such surface changes may reveal hidden (cryptic) druggable pockets. Here, we analyze a set of well-characterized protein-protein interactions harboring cryptic pockets and investigate the predictive power of current computational methods. Based on our observations, we developed a new computational strategy, SWISH-X (SWISH Expanded), which combines the established cryptic pocket identification capabilities of SWISH with the rapid temperature range exploration of OPES MultiThermal. SWISH-X is able to reliably identify cryptic pockets at protein-protein interfaces while retaining its predictive power for revealing cryptic pockets in isolated proteins, such as TEM-1 β-lactamase.
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Affiliation(s)
- Alberto Borsatto
- School
of Pharmaceutical Sciences, University of
Geneva, 1205 Geneva, Switzerland
- Institute
of Pharmaceutical Sciences of Western Switzerland, University of Geneva, 1205 Geneva, Switzerland
- Swiss
Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Eleonora Gianquinto
- Department
of Drug Science and Technology, University
of Turin, 10125 Turin, Italy
| | - Valerio Rizzi
- School
of Pharmaceutical Sciences, University of
Geneva, 1205 Geneva, Switzerland
- Institute
of Pharmaceutical Sciences of Western Switzerland, University of Geneva, 1205 Geneva, Switzerland
- Swiss
Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Francesco Luigi Gervasio
- School
of Pharmaceutical Sciences, University of
Geneva, 1205 Geneva, Switzerland
- Institute
of Pharmaceutical Sciences of Western Switzerland, University of Geneva, 1205 Geneva, Switzerland
- Swiss
Institute of Bioinformatics, 1015 Lausanne, Switzerland
- Department
of Chemistry, University College London, WC1 H0AJ London, United Kingdom
- Institute
of Structural and Molecular Biology, University
College London, WC1E7JE London, United Kingdom
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Islam MR, Osman OI, Hassan WMI. Identifying novel therapeutic inhibitors to target FMS-like tyrosine kinase-3 (FLT3) against acute myeloid leukemia: a molecular docking, molecular dynamics, and DFT study. J Biomol Struct Dyn 2024; 42:82-100. [PMID: 36995071 DOI: 10.1080/07391102.2023.2192798] [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: 12/15/2022] [Accepted: 03/10/2023] [Indexed: 03/31/2023]
Abstract
Around 30% of acute myeloid leukemia (AML) patients have triggering mutations in Feline McDonough Sarcoma (FMS)-like tyrosine kinase 3 (FLT3), which has been suggested as a possible therapeutic candidate for AML therapy. Many tyrosine kinase inhibitors are available and have a wide variety of applications in the treatment of cancer by inhibiting subsequent steps of cell proliferation. Therefore, our study aims to identify effective antileukemic agents against FLT3 gene. Initially, well-known antileukemic drug candidates have been chosen to generate a structure-based pharmacophore model to assist the virtual screening of 217,77,093 compounds from the Zinc database. The final hits compounds were retrieved and evaluated by docking against the target protein, where the top four compounds have been selected for the analysis of ADMET. Based on the density functional theory (DFT), the geometry optimization, frontier molecular orbital (FMO), HOMO-LUMO, and global reactivity descriptor values have been evaluated that confirming a satisfactory profile and reactivity order for the selected candidates. In comparison to control compounds, the docking results revealed that the four compounds had substantial binding energies (-11.1 to -11.5 kcal/mol) with FLT3. The physicochemical and ADMET (adsorption, distribution, metabolism, excretion, toxicity) prediction results corresponded to the bioactive and safe candidates. Molecular dynamics (MD) confirmed the better binding affinity and stability compared to gilteritinib as a potential FLT3 inhibitor. In this study, a computational approach has been performed that found a better docking and dynamics score against target proteins, indicating potent and safe antileukemic agents, furthermore in-vivo and in-vitro investigations are recommended.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Md Rashedul Islam
- Department of Chemistry, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
- Advanced Biological Invention Centre (Bioinventics), Rajshahi, Bangladesh
| | - Osman I Osman
- Department of Chemistry, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
- Department of Chemistry, Faculty of Science, University of Khartoum, Khartoum, Sudan
| | - Walid M I Hassan
- Department of Chemistry, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
- Department of Chemistry, Faculty of Science, Cairo University, Giza, Egypt
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3
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Tsuchiya Y, Yamamori Y, Tomii K. Protein-protein interaction prediction methods: from docking-based to AI-based approaches. Biophys Rev 2022; 14:1341-1348. [PMID: 36570321 PMCID: PMC9759050 DOI: 10.1007/s12551-022-01032-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 11/30/2022] [Indexed: 12/23/2022] Open
Abstract
Protein-protein interactions (PPIs), such as protein-protein inhibitor, antibody-antigen complex, and supercomplexes play diverse and important roles in cells. Recent advances in structural analysis methods, including cryo-EM, for the determination of protein complex structures are remarkable. Nevertheless, much room remains for improvement and utilization of computational methods to predict PPIs because of the large number and great diversity of unresolved complex structures. This review introduces a wide array of computational methods, including our own, for estimating PPIs including antibody-antigen interactions, offering both historical and forward-looking perspectives.
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Affiliation(s)
- Yuko Tsuchiya
- grid.208504.b0000 0001 2230 7538Artificial Intelligence Research Center (AIRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-Ku, Tokyo, 135-0064 Japan
| | - Yu Yamamori
- grid.208504.b0000 0001 2230 7538Artificial Intelligence Research Center (AIRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-Ku, Tokyo, 135-0064 Japan
| | - Kentaro Tomii
- grid.208504.b0000 0001 2230 7538Artificial Intelligence Research Center (AIRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-Ku, Tokyo, 135-0064 Japan
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Wakefield AE, Kozakov D, Vajda S. Mapping the binding sites of challenging drug targets. Curr Opin Struct Biol 2022; 75:102396. [PMID: 35636004 PMCID: PMC9790766 DOI: 10.1016/j.sbi.2022.102396] [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] [Received: 02/17/2022] [Revised: 04/20/2022] [Accepted: 04/25/2022] [Indexed: 02/03/2023]
Abstract
An increasing number of medically important proteins are challenging drug targets because their binding sites are too shallow or too polar, are cryptic and thus not detectable without a bound ligand or located in a protein-protein interface. While such proteins may not bind druglike small molecules with sufficiently high affinity, they are frequently druggable using novel therapeutic modalities. The need for such modalities can be determined by experimental or computational fragment based methods. Computational mapping by mixed solvent molecular dynamics simulations or the FTMap server can be used to determine binding hot spots. The strength and location of the hot spots provide very useful information for selecting potentially successful approaches to drug discovery.
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Affiliation(s)
- Amanda E. Wakefield
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215,Department of Chemistry, Boston University, Boston, Massachusetts 02215
| | - Dima Kozakov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA,Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, USA NY, USA
| | - Sandor Vajda
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215,Department of Chemistry, Boston University, Boston, Massachusetts 02215
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Cong X, Zhang X, Liang X, He X, Tang Y, Zheng X, Lu S, Zhang J, Chen T. Delineating the conformational landscape and intrinsic properties of the angiotensin II type 2 receptor using a computational study. Comput Struct Biotechnol J 2022; 20:2268-2279. [PMID: 35615027 PMCID: PMC9117689 DOI: 10.1016/j.csbj.2022.05.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 05/04/2022] [Accepted: 05/06/2022] [Indexed: 12/22/2022] Open
Abstract
As a key regulator for the renin-angiotensin system, a class A G protein-coupled receptor (GPCR), AngII type 2 receptor (AT2R), plays a pivotal role in the homeostasis of the cardiovascular system. Compared with other GPCRs, AT2R has a unique antagonist-bound conformation and its mechanism is still an enigma. Here, we applied combined dynamic and evolutional approaches to investigate the conformational space and intrinsic properties of AT2R. With molecular dynamic simulations, Markov State Models, and statistics coupled analysis, we captured the conformational landscape of AT2R and identified its uniquity from both dynamical and evolutional viewpoints. A cryptic pocket was also discovered in the intermediate state during conformation transitions. These findings offer a deeper understanding of the AT2R mechanism at an atomic level and provide hints for the design of novel AT2R modulators.
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Affiliation(s)
- Xiaoliang Cong
- Department of Cardiology, Shanghai Changzheng Hospital, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China
| | - Xiaogang Zhang
- Department of Cardiology, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Shanghai 201318, China
| | - Xin Liang
- Department of Cardiology, Shanghai Changzheng Hospital, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China
| | - Xinheng He
- Medicinal Chemistry and Bioinformatics Centre, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Yehua Tang
- Department of Cardiology, Shanghai Changzheng Hospital, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China
| | - Xing Zheng
- Department of Cardiology, Changhai Hospital, Naval Medical University, Shanghai 200433, China
| | - Shaoyong Lu
- Medicinal Chemistry and Bioinformatics Centre, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
- Corresponding authors.
| | - Jiayou Zhang
- Department of Cardiology, Shanghai Changzheng Hospital, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China
- Corresponding authors.
| | - Ting Chen
- Department of Cardiology, Shanghai Changzheng Hospital, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China
- Corresponding authors.
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Singh N, Villoutreix BO. Resources and computational strategies to advance small molecule SARS-CoV-2 discovery: Lessons from the pandemic and preparing for future health crises. Comput Struct Biotechnol J 2021; 19:2537-2548. [PMID: 33936562 PMCID: PMC8074526 DOI: 10.1016/j.csbj.2021.04.059] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 04/22/2021] [Accepted: 04/24/2021] [Indexed: 12/11/2022] Open
Abstract
There is an urgent need to identify new therapies that prevent SARS-CoV-2 infection and improve the outcome of COVID-19 patients. This pandemic has thus spurred intensive research in most scientific areas and in a short period of time, several vaccines have been developed. But, while the race to find vaccines for COVID-19 has dominated the headlines, other types of therapeutic agents are being developed. In this mini-review, we report several databases and online tools that could assist the discovery of anti-SARS-CoV-2 small chemical compounds and peptides. We then give examples of studies that combined in silico and in vitro screening, either for drug repositioning purposes or to search for novel bioactive compounds. Finally, we question the overall lack of discussion and plan observed in academic research in many countries during this crisis and suggest that there is room for improvement.
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Affiliation(s)
- Natesh Singh
- Université de Paris, Inserm UMR 1141 NeuroDiderot, Robert-Debré Hospital, 75019 Paris, France
| | - Bruno O. Villoutreix
- Université de Paris, Inserm UMR 1141 NeuroDiderot, Robert-Debré Hospital, 75019 Paris, France
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