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Xu M, Xiao X, Chen Y, Zhou X, Parisi L, Ma R. 3D physiologically-informed deep learning for drug discovery of a novel vascular endothelial growth factor receptor-2 (VEGFR2). Heliyon 2024; 10:e35769. [PMID: 39220924 PMCID: PMC11365333 DOI: 10.1016/j.heliyon.2024.e35769] [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: 06/11/2024] [Revised: 08/01/2024] [Accepted: 08/02/2024] [Indexed: 09/04/2024] Open
Abstract
Angiogenesis is an essential process in tumorigenesis, tumor invasion, and metastasis, and is an intriguing pathway for drug discovery. Targeting vascular endothelial growth factor receptor 2 (VEGFR2) to inhibit tumor angiogenic pathways has been widely explored and adopted in clinical practice. However, most drugs, such as the Food and Drug Administration -approved drug axitinib (ATC code: L01EK01), have considerable side effects and limited tolerability. Therefore, there is an urgent need for the development of novel VEGFR2 inhibitors. In this study, we propose a novel strategy to design potential candidates targeting VEGFR2 using three-dimensional (3D) deep learning and structural modeling methods. A geometric-enhanced molecular representation learning method (GEM) model employing a graph neural network (GNN) as its underlying predictive algorithm was used to predict the activity of the candidates. In the structural modeling method, flexible docking was performed to screen data with high affinity and explore the mechanism of the inhibitors. Small -molecule compounds with consistently improved properties were identified based on the intersection of the scores obtained from both methods. Candidates identified using the GEM-GNN model were selected for in silico modeling using molecular dynamics simulations to further validate their efficacy. The GEM-GNN model enabled the identification of candidate compounds with potentially more favorable properties than the existing drug, axitinib, while achieving higher efficacy.
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Affiliation(s)
- Mengyang Xu
- Faculty of Biology, Shenzhen MSU-BIT University, Shenzhen, 518172, Guangdong, China
| | - Xiaoyue Xiao
- Faculty of Biology, Shenzhen MSU-BIT University, Shenzhen, 518172, Guangdong, China
| | - Yinglu Chen
- Faculty of Biology, Shenzhen MSU-BIT University, Shenzhen, 518172, Guangdong, China
| | - Xiaoyan Zhou
- Faculty of Biology, Shenzhen MSU-BIT University, Shenzhen, 518172, Guangdong, China
| | - Luca Parisi
- Department of Computer Science, Tutorantis, Edinburgh, EH2 4AN, Scotland, United Kingdom
| | - Renfei Ma
- Faculty of Biology, Shenzhen MSU-BIT University, Shenzhen, 518172, Guangdong, China
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Aguilar-Pineda J, González-Melchor M. Influence of the Water Model on the Structure and Interactions of the GPR40 Protein with the Lipid Membrane and the Solvent: Rigid versus Flexible Water Models. J Chem Theory Comput 2024; 20:6369-6387. [PMID: 38991114 PMCID: PMC11270832 DOI: 10.1021/acs.jctc.4c00571] [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: 04/28/2024] [Revised: 06/07/2024] [Accepted: 06/21/2024] [Indexed: 07/13/2024]
Abstract
G protein-coupled receptors (GPCR) are responsible for modulating various physiological functions and are thus related to the pathophysiology of different diseases. Being potential therapeutic targets, multiple computational methodologies have been developed to analyze their behavior and interactions with other species. The solvent, on the other hand, has received much less attention. In this work, we analyzed the effect of four explicit water models on the structure and interactions of the GPR40 receptor in its apo form. We employed the rigid SPC/E and TIP4P models, and their flexible versions, the FBA/ϵ and TIP4P/ϵflex. We explored the structural changes and their correlation with some bulk dynamic properties of water. Our results showed an adverse effect on the conservation of the secondary structure of the receptor with all the models due to the breaking of the intramolecular hydrogen bond network, being more evident for the TIP4P models. Notably, all four models brought the receptor to states similar to the active one, modifying the intracellular part of the TM5 and TM6 domains in a "hinge" type movement, allowing the opening of the structure. Regarding the dynamic properties, the rigid models showed results comparable to those obtained in other studies on membrane systems. However, flexible models exhibit disparities in the molecular representation of systems. Surprisingly, the FBA/ϵ model improves the molecular picture of several properties, even though their agreement with bulk diffusion is poorer. These findings reinforce our idea that exploring other water models or improving the current ones, to better represent the membrane interface, can lead to a positive impact on the description of the signal transduction mechanisms and the search of new drugs by targeting these receptors.
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Affiliation(s)
- Jorge
Alberto Aguilar-Pineda
- Instituto de Física
“Luis Rivera Terrazas”, Benemérita Universidad
Autónoma de Puebla, Av San Claudio, Cd Universitaria, Apdo. Postal
J-48, Puebla 72570, México
| | - Minerva González-Melchor
- Instituto de Física
“Luis Rivera Terrazas”, Benemérita Universidad
Autónoma de Puebla, Av San Claudio, Cd Universitaria, Apdo. Postal
J-48, Puebla 72570, México
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Chen Z, Li Y, Wang X, Qiu X, Wang C, Wang Z, Chen X, Wang J. A high-throughput molecular dynamics screening (HTMDS) approach to the design of novel cyclopeptide inhibitors of ATAD2B based on the non-canonical combinatorial library. J Biomol Struct Dyn 2024; 42:2809-2824. [PMID: 37194299 DOI: 10.1080/07391102.2023.2212796] [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: 03/20/2023] [Accepted: 04/19/2023] [Indexed: 05/18/2023]
Abstract
Cyclic peptides (CPs) are a promising class of drugs because of their high biological activity and specificity. However, the design of CP remains challenging due to their conformational flexibility and difficulties in designing stable binding conformation. Herein, we present a high-throughput MD screening (HTMDS) process for the iterative design of stable CP binders with a combinatorial CP library composed of canonical and non-canonical amino acids. As a proof of concept, we apply our methods to design CP inhibitors for the bromodomain (BrD) of ATAD2B. 698,800 CP candidates with a total of 25,570 ns MD simulations were performed to study the protein-ligand binding interactions. The binding free energies (ΔGbind) estimated by MM/PBSA approach for eight lead CP designs were found to be low. CP-1st.43 was the best CP candidate with an estimated ΔGbind of -28.48 kcal/mol when compared to the standard inhibitor C-38 which has been experimentally validated and shown to exhibit ΔGbind of -17.11 kcal/mol. The major contribution of binding sites for BrD of ATAD2B involved the hydrogen-bonding anchor within the Aly-binding pocket, salt bridging, and hydrogen-bonding mediated stabilization of the ZA loop and BC loop, and the complementary Van der Waals attraction. Our methods demonstrate encouraging results by yielding conformationally stable and high-potential CP binders that should have potential applicability in future CP drug development.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Zhidong Chen
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Yongxiao Li
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Xinpei Wang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Xiaohui Qiu
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Chenglin Wang
- Shenzhen Qiyu Biotechnology Co., Ltd, Shenzhen, China
| | - Zhe Wang
- Department of Pathology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Xu Chen
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Junqing Wang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
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Gupta T, Rani D, Nainwal LM, Badhwar R. Advancement in chiral heterocycles for the antidiabetic activity. Chirality 2024; 36:e23637. [PMID: 38384150 DOI: 10.1002/chir.23637] [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: 08/27/2023] [Revised: 11/19/2023] [Accepted: 12/11/2023] [Indexed: 02/23/2024]
Abstract
For the synthesis and development of pharmaceuticals, chirality is an important structural component. Chiral heterocyclic compounds have annoyed the interest of synthetic chemists who are working to create useful and efficient techniques for these molecules. As indicated by the expanding number of chiral drugs created in the last two decades, the link between chirality and pharmacological activity has become more important in the pharmaceutical and biopharmaceutical industries. Approximately 65% of currently used drugs are chiral, and many of them are promoted as racemates in many circumstances. There are a growing number of new chiral heterocyclic compounds with important biological properties and intriguing uses in medical chemistry and drug discovery. In this study, we review current breakthroughs in chiral heterocycles and their different physiological activities that have been published in the last year (from 2010 to early 2023). This study focuses on the current trends in the use of chiral heterocycles in drug design and the creation of several powerful and competent candidates for diabetic illnesses.
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Affiliation(s)
- Tinku Gupta
- Department of Pharmacognosy & Phytochemistry, School of Pharmaceutical Education & Research, Jamia Hamdard, New Delhi, India
| | - Dimpy Rani
- School of Medical and Allied Sciences, G.D. Goenka University, Haryana, India
| | - Lalit Mohan Nainwal
- Department of Pharmaceutical Chemistry, KIET School of Pharmacy, KIET Group of Institutions, Ghaziabad, India
| | - Reena Badhwar
- Department of Pharmacy, SGT University, Budhera, Haryana, India
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Wang J, Chen C, Yao G, Ding J, Wang L, Jiang H. Intelligent Protein Design and Molecular Characterization Techniques: A Comprehensive Review. Molecules 2023; 28:7865. [PMID: 38067593 PMCID: PMC10707872 DOI: 10.3390/molecules28237865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 11/13/2023] [Accepted: 11/23/2023] [Indexed: 12/18/2023] Open
Abstract
In recent years, the widespread application of artificial intelligence algorithms in protein structure, function prediction, and de novo protein design has significantly accelerated the process of intelligent protein design and led to many noteworthy achievements. This advancement in protein intelligent design holds great potential to accelerate the development of new drugs, enhance the efficiency of biocatalysts, and even create entirely new biomaterials. Protein characterization is the key to the performance of intelligent protein design. However, there is no consensus on the most suitable characterization method for intelligent protein design tasks. This review describes the methods, characteristics, and representative applications of traditional descriptors, sequence-based and structure-based protein characterization. It discusses their advantages, disadvantages, and scope of application. It is hoped that this could help researchers to better understand the limitations and application scenarios of these methods, and provide valuable references for choosing appropriate protein characterization techniques for related research in the field, so as to better carry out protein research.
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Affiliation(s)
| | | | | | - Junjie Ding
- State Key Laboratory of NBC Protection for Civilian, Beijing 102205, China; (J.W.); (C.C.); (G.Y.)
| | - Liangliang Wang
- State Key Laboratory of NBC Protection for Civilian, Beijing 102205, China; (J.W.); (C.C.); (G.Y.)
| | - Hui Jiang
- State Key Laboratory of NBC Protection for Civilian, Beijing 102205, China; (J.W.); (C.C.); (G.Y.)
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Saldívar-González FI, Navarrete-Vázquez G, Medina-Franco JL. Design of a multi-target focused library for antidiabetic targets using a comprehensive set of chemical transformation rules. Front Pharmacol 2023; 14:1276444. [PMID: 38027021 PMCID: PMC10651762 DOI: 10.3389/fphar.2023.1276444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
Virtual small molecule libraries are valuable resources for identifying bioactive compounds in virtual screening campaigns and improving the quality of libraries in terms of physicochemical properties, complexity, and structural diversity. In this context, the computational-aided design of libraries focused against antidiabetic targets can provide novel alternatives for treating type II diabetes mellitus (T2DM). In this work, we integrated the information generated to date on compounds with antidiabetic activity, advances in computational methods, and knowledge of chemical transformations available in the literature to design multi-target compound libraries focused on T2DM. We evaluated the novelty and diversity of the newly generated library by comparing it with antidiabetic compounds approved for clinical use, natural products, and multi-target compounds tested in vivo in experimental antidiabetic models. The designed libraries are freely available and are a valuable starting point for drug design, chemical synthesis, and biological evaluation or further computational filtering. Also, the compendium of 280 transformation rules identified in a medicinal chemistry context is made available in the linear notation SMIRKS for use in other chemical library enumeration or hit optimization approaches.
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Affiliation(s)
- Fernanda I. Saldívar-González
- Department of Pharmacy, DIFACQUIM Research Group, School of Chemistry, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | | | - José L. Medina-Franco
- Department of Pharmacy, DIFACQUIM Research Group, School of Chemistry, Universidad Nacional Autónoma de México, Mexico City, Mexico
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Song X, Liu L, Wang C, Zhang W, Li Y, Zhu J, Liu P, Li X. Real-time determination of flowering period for field wheat based on improved YOLOv5s model. FRONTIERS IN PLANT SCIENCE 2023; 13:1025663. [PMID: 36714714 PMCID: PMC9874244 DOI: 10.3389/fpls.2022.1025663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 12/13/2022] [Indexed: 06/18/2023]
Abstract
The flowering period is one of the important indexes of wheat breeding. The early or late flowering affects the final yield and character stability of wheat. In order to solve the problem that it is difficult to accurately and quickly detect the flowering period of a large number of wheat breeding materials, a determination method of flowering period for field wheat based on the improved You Only Look Once (YOLO) v5s model was proposed. Firstly, a feature fusion (FF) method combing RGB images and corresponding comprehensive color features was proposed to highlight more texture features and reduce the distortion caused by light on the extracted feature images. Second, the YOLOv5s model was selected as a base version of the improved model and the convolutional block attention model (CBAM) was adopted into the feature fusion layer of YOLOV5s model. Florets and spikelets were given greater weight along the channel and spatial dimensions to further refine their effective feature information. At the same time, an integrated Transformer small-target detection head (TSDH) was added to solve the high miss rate of small targets in wheat population images. The accurate and rapid detection of florets and spikelets was realized, and the flowering period was determined according to the proportion of florets and spikelets. The experimental results showed that the average computing time of the proposed method was 11.5ms, and the average recognition accuracy of florets and spikelets was 88.9% and 96.8%, respectively. The average difference between the estimated flowering rate and the actual flowering rate was within 5%, and the determination accuracy of the flowering period reached 100%, which met the basic requirements of the flowering period determination of wheat population in the field.
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Affiliation(s)
- Xubin Song
- College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian, China
| | - Lipeng Liu
- College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian, China
| | - Chunying Wang
- College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian, China
| | - Wanteng Zhang
- College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian, China
| | - Yang Li
- College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian, China
| | - Junke Zhu
- School of Agricultural and Food Engineering, Shandong University of Technology, Zibo, China
| | - Ping Liu
- College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian, China
| | - Xiang Li
- State Key Laboratory of Crop Biology, College of Life Sciences, Shandong Agricultural University, Taian, China
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Wang D, Liu J, Zhou L, Zhang Q, Li M, Xiao X. Effects of Oral Glucose-Lowering Agents on Gut Microbiota and Microbial Metabolites. Front Endocrinol (Lausanne) 2022; 13:905171. [PMID: 35909556 PMCID: PMC9326154 DOI: 10.3389/fendo.2022.905171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 06/14/2022] [Indexed: 11/30/2022] Open
Abstract
The current research and existing facts indicate that type 2 diabetes mellitus (T2DM) is characterized by gut microbiota dysbiosis and disturbed microbial metabolites. Oral glucose-lowering drugs are reported with pleiotropic beneficial effects, including not only a decrease in glucose level but also weight loss, antihypertension, anti-inflammation, and cardiovascular protection, but the underlying mechanisms are still not clear. Evidence can be found showing that oral glucose-lowering drugs might modify the gut microbiome and thereby alter gastrointestinal metabolites to improve host health. Although the connections among gut microbial communities, microbial metabolites, and T2DM are complex, figuring out how antidiabetic agents shape the gut microbiome is vital for optimizing the treatment, meaningful for the instruction for probiotic therapy and gut microbiota transplantation in T2DM. In this review, we focused on the literatures in gut microbiota and its metabolite profile alterations beneficial from oral antidiabetic drugs, trying to provide implications for future study in the developing field of these drugs, such as combination therapies, pre- and probiotics intervention in T2DM, and subjects with pregestational diabetes and gestational diabetes mellitus.
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Affiliation(s)
- Dongmei Wang
- Department of Endocrinology, National Health Commission (NHC) Key Laboratory of Endocrinology, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Peking Union Medical College, Beijing, China
| | - Jieying Liu
- Department of Endocrinology, National Health Commission (NHC) Key Laboratory of Endocrinology, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Peking Union Medical College, Beijing, China
- Department of Medical Research Center, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Peking Union Medical College, Beijing, China
| | - Liyuan Zhou
- Department of Endocrinology, National Health Commission (NHC) Key Laboratory of Endocrinology, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Peking Union Medical College, Beijing, China
| | - Qian Zhang
- Department of Endocrinology, National Health Commission (NHC) Key Laboratory of Endocrinology, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Peking Union Medical College, Beijing, China
| | - Ming Li
- Department of Endocrinology, National Health Commission (NHC) Key Laboratory of Endocrinology, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Peking Union Medical College, Beijing, China
| | - Xinhua Xiao
- Department of Endocrinology, National Health Commission (NHC) Key Laboratory of Endocrinology, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Peking Union Medical College, Beijing, China
- *Correspondence: Xinhua Xiao,
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