Structure and Ligand Based Drug Design

A special issue of Pharmaceuticals (ISSN 1424-8247). This special issue belongs to the section "Medicinal Chemistry".

Deadline for manuscript submissions: closed (10 June 2024) | Viewed by 22713

Special Issue Editor


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Guest Editor
Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410083, China
Interests: cheminformatics; computer aided drug design; drug discovery

Special Issue Information

Dear Colleagues,

Current pharmaceutical R&D faces outstanding challenges, as the scientific breakthroughs made in the past two decades have completely changed the field. Core methods such as high-throughput screening (HTS) are increasingly used in conjunction with emerging strategies that rely on genomics, chemical biology, and molecular modeling. These cutting-edge techniques have substantially contributed to our understanding of key biological processes, as well as important advances in the arsenal of methods that can be used for drug research. Together with synthetic strategies such as combinatorial chemistry, these state-of-the-art technologies are shaping the future of the pharmaceutical industry, supporting the continued expansion of the chemical space explored in drug discovery.

Usually, these computer-aided works combine ligand and structure-based drug design strategies (LBDD and SBDD, respectively) with a large number of experimental techniques. The widely used SBDD method, molecular docking, homology modeling, molecular dynamics and structure-based virtual screening provide relevant insights into ligand–receptor interactions. LBDD methods such as pharmacophore modeling, quantitative structure–activity relationship (QSAR), and ligand-based virtual screening are equally important, and have been used to explore small molecule databases and generate correlations between chemical characteristics and pharmacological activities. A quantitative structure–property relationship model (QSPR) is also a hot topic of LBDD, and it is the core of predicting pharmacokinetics and toxicity-related characteristics based on various machine learning or artificial intelligence (AI) methods. This research topic includes the latest applications of LBDD and SBDD in drug activity research and drug absorption, distribution, metabolism, excretion, and toxicity (ADME / Tox). Including original and review articles, it also reports the latest developments in novel software, tools, resources, and algorithms in drug discovery.

Pharmaceuticals invites both reviews and original articles regarding the advancement of high-throughput genetic and chemical screening and novel areas of applications. Topics include, but are not limited to: ligand-based drug design; structure-based drug design; molecular modeling; drug discovery; medicinal chemistry; pharmaceutical chemistry; cheminformatics; ADEMT prediction; molecular generation and optimization, and artificial intelligence-based drug design (AIDD). Submissions from authors in both academic and industrial domains are welcome. The collection of manuscripts will be published as a Special Issue.

Prof. Dr. Dongsheng Cao
Guest Editor

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Published Papers (9 papers)

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Research

21 pages, 7175 KiB  
Article
A Hybrid Approach Combining Shape-Based and Docking Methods to Identify Novel Potential P2X7 Antagonists from Natural Product Databases
by Natiele Carla da Silva Ferreira, Lucas Gasparello Viviani, Lauro Miranda Lima, Antonia Tavares do Amaral, João Victor Paiva Romano, Anderson Lage Fortunato, Rafael Ferreira Soares, Anael Viana Pinto Alberto, Jose Aguiar Coelho Neto and Luiz Anastacio Alves
Pharmaceuticals 2024, 17(5), 592; https://0-doi-org.brum.beds.ac.uk/10.3390/ph17050592 - 7 May 2024
Viewed by 825
Abstract
P2X7 is an ATP-activated purinergic receptor implicated in pro-inflammatory responses. It is associated with the development of several diseases, including inflammatory and neurodegenerative conditions. Although several P2X7 receptor antagonists have recently been reported in the literature, none of them is approved for clinical [...] Read more.
P2X7 is an ATP-activated purinergic receptor implicated in pro-inflammatory responses. It is associated with the development of several diseases, including inflammatory and neurodegenerative conditions. Although several P2X7 receptor antagonists have recently been reported in the literature, none of them is approved for clinical use. However, the structure of the known antagonists can serve as a scaffold for discovering effective compounds in clinical therapy. This study aimed to propose an improved virtual screening methodology for the identification of novel potential P2X7 receptor antagonists from natural products through the combination of shape-based and docking approaches. First, a shape-based screening was performed based on the structure of JNJ-47965567, a P2X7 antagonist, using two natural product compound databases, MEGx (~5.8 × 103 compounds) and NATx (~32 × 103 compounds). Then, the compounds selected by the proposed shape-based model, with Shape–Tanimoto score values ranging between 0.624 and 0.799, were filtered for drug-like properties. Finally, the compounds that met the drug-like filter criteria were docked into the P2X7 allosteric binding site, using the docking programs GOLD and DockThor. The docking poses with the best score values were submitted to careful visual inspection of the P2X7 allosteric binding site. Based on our established visual inspection criteria, four compounds from the MEGx database and four from the NATx database were finally selected as potential P2X7 receptor antagonists. The selected compounds are structurally different from known P2X7 antagonists, have drug-like properties, and are predicted to interact with key P2X7 allosteric binding pocket residues, including F88, F92, F95, F103, M105, F108, Y295, Y298, and I310. Therefore, the combination of shape-based screening and docking approaches proposed in our study has proven useful in selecting potential novel P2X7 antagonist candidates from natural-product-derived compounds databases. This approach could also be useful for selecting potential inhibitors/antagonists of other receptors and/or biological targets. Full article
(This article belongs to the Special Issue Structure and Ligand Based Drug Design)
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16 pages, 3959 KiB  
Article
Discovery of AI-2 Quorum Sensing Inhibitors Targeting the LsrK/HPr Protein–Protein Interaction Site by Molecular Dynamics Simulation, Virtual Screening, and Bioassay Evaluation
by Yijie Xu, Chunlan Zeng, Huiqi Wen, Qianqian Shi, Xu Zhao, Qingbin Meng, Xingzhou Li and Junhai Xiao
Pharmaceuticals 2023, 16(5), 737; https://0-doi-org.brum.beds.ac.uk/10.3390/ph16050737 - 12 May 2023
Cited by 1 | Viewed by 1755
Abstract
Quorum sensing (QS) is a cell-to-cell communication mechanism that regulates bacterial pathogenicity, biofilm formation, and antibiotic sensitivity. Among the identified quorum sensing, AI-2 QS exists in both Gram-negative and Gram-positive bacteria and is responsible for interspecies communication. Recent studies have highlighted the connection [...] Read more.
Quorum sensing (QS) is a cell-to-cell communication mechanism that regulates bacterial pathogenicity, biofilm formation, and antibiotic sensitivity. Among the identified quorum sensing, AI-2 QS exists in both Gram-negative and Gram-positive bacteria and is responsible for interspecies communication. Recent studies have highlighted the connection between the phosphotransferase system (PTS) and AI-2 QS, with this link being associated with protein-protein interaction (PPI) between HPr and LsrK. Here, we first discovered several AI-2 QSIs targeting the LsrK/HPr PPI site through molecular dynamics (MD) simulation, virtual screening, and bioassay evaluation. Of the 62 compounds purchased, eight compounds demonstrated significant inhibition in LsrK-based assays and AI-2 QS interference assays. Surface plasmon resonance (SPR) analysis confirmed that the hit compound 4171-0375 specifically bound to the LsrK-N protein (HPr binding domain, KD = 2.51 × 10−5 M), and therefore the LsrK/HPr PPI site. The structure-activity relationships (SARs) emphasized the importance of hydrophobic interactions with the hydrophobic pocket and hydrogen bonds or salt bridges with key residues of LsrK for LsrK/HPr PPI inhibitors. These new AI-2 QSIs, especially 4171-0375, exhibited novel structures, significant LsrK inhibition, and were suitable for structural modification to search for more effective AI-2 QSIs. Full article
(This article belongs to the Special Issue Structure and Ligand Based Drug Design)
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20 pages, 4068 KiB  
Article
Integrative Ligand-Based Pharmacophore Modeling, Virtual Screening, and Molecular Docking Simulation Approaches Identified Potential Lead Compounds against Pancreatic Cancer by Targeting FAK1
by Mohammad Habibur Rahman Molla, Mohammed Othman Aljahdali, Md Afsar Ahmed Sumon, Amer H. Asseri, Hisham N. Altayb, Md. Shafiqul Islam, Ahad Amer Alsaiari, F. A. Dain Md Opo, Nushrat Jahan, Foysal Ahammad and Farhan Mohammad
Pharmaceuticals 2023, 16(1), 120; https://0-doi-org.brum.beds.ac.uk/10.3390/ph16010120 - 13 Jan 2023
Cited by 9 | Viewed by 4413
Abstract
Pancreatic cancer is a very deadly disease with a 5-year survival rate, making it one of the leading causes of cancer-related deaths globally. Focal adhesion kinase 1 (FAK1) is a ubiquitously expressed protein in pancreatic cancer. FAK, a tyrosine kinase that is overexpressed [...] Read more.
Pancreatic cancer is a very deadly disease with a 5-year survival rate, making it one of the leading causes of cancer-related deaths globally. Focal adhesion kinase 1 (FAK1) is a ubiquitously expressed protein in pancreatic cancer. FAK, a tyrosine kinase that is overexpressed in cancer cells, is crucial for the development of tumors into malignant phenotypes. FAK functions in response to extracellular signals by triggering transmembrane receptor signaling, which enhances focal adhesion turnover, cell adhesion, cell migration, and gene expression. The ligand-based drug design approach was used to identify potential compounds against the target protein, which included molecular docking: ADME (absorption, distribution, metabolism, and excretion), toxicity, molecular dynamics (MD) simulation, and molecular mechanics generalized born surface area (MM-GBSA). Following the retrieval of twenty hits, four compounds were selected for further evaluation based on a molecular docking approach. Three newly discovered compounds, including PubChem CID24601203, CID1893370, and CID16355541, with binding scores of −10.4, −10.1, and −9.7 kcal/mol, respectively, may serve as lead compounds for the treatment of pancreatic cancer associated with FAK1. The ADME (absorption, distribution, metabolism, and excretion) and toxicity analyses demonstrated that the compounds were effective and nontoxic. However, further wet laboratory investigations are required to evaluate the activity of the drugs against the cancer. Full article
(This article belongs to the Special Issue Structure and Ligand Based Drug Design)
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19 pages, 4581 KiB  
Article
Structure-Guide Design and Optimization of Potential Druglikeness Inhibitors for TGFβRI with the Pyrrolopyrimidine Scaffold
by Dan Meng, Jiali Xie, Yihao Li, Ruoyu Li, Hui Zhou and Ping Deng
Pharmaceuticals 2022, 15(10), 1264; https://0-doi-org.brum.beds.ac.uk/10.3390/ph15101264 - 13 Oct 2022
Viewed by 1680
Abstract
Among all types of TGFβ signal blockers, small molecule kinase inhibitors (SMKIs) have attracted wide attention due to their economical production, obvious stability, and ease of oral administration. Nevertheless, SMKIs of TGFβRItypically have low druggability so there are none on the market. In [...] Read more.
Among all types of TGFβ signal blockers, small molecule kinase inhibitors (SMKIs) have attracted wide attention due to their economical production, obvious stability, and ease of oral administration. Nevertheless, SMKIs of TGFβRItypically have low druggability so there are none on the market. In this study, structure-based drug design (SBDD) was performed focusing on the pyrrolopyrimidin scaffold of BMS22 to find TGFβRIinhibitors with excellent medical potential. The binding mode, druggability, and target affinity were assessed by molecular docking, ADMET predictions, and molecular dynamics (MD) simulations for the designed TGFβRIinhibitors. Finally, the highly druggable compound W8 was discovered and then synthesized, which inhibited TGFβRIwith an IC50 value of about 10 μM. In addition, the binding free energies (ΔGbind) of W8 (−42.330 ± 3.341 kcal/mol) and BMS22 (−30.560 ± 6.076 kcal/mol) indicate that the high binding affinity is not necessarily accompanied by high inhibitory activity. Last but not least, the per-residue interaction analysis revealed that the contribution energy of ASP351 to binding was the most significant difference between BMS22 and W8, −2.195 kcal/mol and 1.707 kcal/mol, respectively. As a result, increasing the affinity between SMKIs and ASP351 of TGFβRImay effectively improve the inhibitory activity. The insights gained from this study could help with structure-guided optimization in searching for better SMKIs of TGFβRI. Full article
(This article belongs to the Special Issue Structure and Ligand Based Drug Design)
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14 pages, 2462 KiB  
Article
Deconstructing Markush: Improving the R&D Efficiency Using Library Selection in Early Drug Discovery
by Leticia Manen-Freixa, José I. Borrell, Jordi Teixidó and Roger Estrada-Tejedor
Pharmaceuticals 2022, 15(9), 1159; https://0-doi-org.brum.beds.ac.uk/10.3390/ph15091159 - 18 Sep 2022
Cited by 2 | Viewed by 2080
Abstract
Most of the product patents claim a large number of compounds based on a Markush structure. However, the identification and optimization of new principal active ingredients is frequently driven by a simple Free Wilson approach, leading to a highly focused study only involving [...] Read more.
Most of the product patents claim a large number of compounds based on a Markush structure. However, the identification and optimization of new principal active ingredients is frequently driven by a simple Free Wilson approach, leading to a highly focused study only involving the chemical space nearby a hit compound. This fact raises the question: do the tested compounds described in patents really reflect the full molecular diversity described in the Markush structure? In this study, we contrast the performance of rational selection to conventional approaches in seven real-case patents, assessing their ability to describe the patent’s chemical space. Results demonstrate that the integration of computer-aided library selection methods in the early stages of the drug discovery process would boost the identification of new potential hits across the chemical space. Full article
(This article belongs to the Special Issue Structure and Ligand Based Drug Design)
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17 pages, 8125 KiB  
Article
Chelation of Zinc with Biogenic Amino Acids: Description of Properties Using Balaban Index, Assessment of Biological Activity on Spirostomum Ambiguum Cellular Biosensor, Influence on Biofilms and Direct Antibacterial Action
by Alla V. Marukhlenko, Mariya A. Morozova, Arsène M. J. Mbarga, Nadezhda V. Antipova, Anton V. Syroeshkin, Irina V. Podoprigora and Tatiana V. Maksimova
Pharmaceuticals 2022, 15(8), 979; https://0-doi-org.brum.beds.ac.uk/10.3390/ph15080979 - 9 Aug 2022
Cited by 7 | Viewed by 3318
Abstract
The complexation of biogenic molecules with metals is the widespread strategy in screening for new pharmaceuticals with improved therapeutic and physicochemical properties. This paper demonstrates the possibility of using simple QSAR modeling based on topological descriptors for chelates study. The presence of a [...] Read more.
The complexation of biogenic molecules with metals is the widespread strategy in screening for new pharmaceuticals with improved therapeutic and physicochemical properties. This paper demonstrates the possibility of using simple QSAR modeling based on topological descriptors for chelates study. The presence of a relationship between the structure (J) and lipophilic properties (logP) of zinc complexes with amino acids, where two molecules coordinate the central atom through carboxyl oxygen and amino group nitrogen, and thus form a double ring structure, was predicted. Using a cellular biosensor model for Gly, Ala, Met, Val, Phe and their complexes Zn(AA)2, we experimentally confirmed the existence of a direct relationship between logP and biological activity (Ea). The results obtained using topological analysis, Spirotox method and microbiological testing allowed us to assume and prove that the chelate complex of zinc with methionine has the highest activity of inhibiting bacterial biofilms, while in aqueous solutions it does not reveal direct antibacterial effect. Full article
(This article belongs to the Special Issue Structure and Ligand Based Drug Design)
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18 pages, 43373 KiB  
Article
Perceiving the Concealed and Unreported Pharmacophoric Features of the 5-Hydroxytryptamine Receptor Using Balanced QSAR Analysis
by Syed Nasir Abbas Bukhari, Mervat Abdelaziz Elsherif, Kashaf Junaid, Hasan Ejaz, Pravej Alam, Abdul Samad, Rahul D. Jawarkar and Vijay H. Masand
Pharmaceuticals 2022, 15(7), 834; https://0-doi-org.brum.beds.ac.uk/10.3390/ph15070834 - 5 Jul 2022
Cited by 5 | Viewed by 1799
Abstract
The 5-hydroxytryptamine receptor 6 (5-HT6) has gained attention as a target for developing therapeutics for Alzheimer’s disease, schizophrenia, cognitive dysfunctions, anxiety, and depression, to list a few. In the present analysis, a larger and diverse dataset of 1278 molecules covering a broad chemical [...] Read more.
The 5-hydroxytryptamine receptor 6 (5-HT6) has gained attention as a target for developing therapeutics for Alzheimer’s disease, schizophrenia, cognitive dysfunctions, anxiety, and depression, to list a few. In the present analysis, a larger and diverse dataset of 1278 molecules covering a broad chemical and activity space was used to identify visual and concealed structural features associated with binding affinity for 5-HT6. For this, quantitative structure–activity relationships (QSAR) and molecular docking analyses were executed. This led to the development of a statistically robust QSAR model with a balance of excellent predictivity (R2tr = 0.78, R2ex = 0.77), the identification of unreported aspects of known features, and also novel mechanistic interpretations. Molecular docking and QSAR provided similar as well as complementary results. The present analysis indicates that the partial charges on ring carbons present within four bonds from a sulfur atom, the occurrence of sp3-hybridized carbon atoms bonded with donor atoms, and a conditional occurrence of lipophilic atoms/groups from nitrogen atoms, which are prominent but unreported pharmacophores that should be considered while optimizing a molecule for 5-HT6. Thus, the present analysis led to identification of some novel unreported structural features that govern the binding affinity of a molecule. The results could be beneficial in optimizing the molecules for 5-HT6. Full article
(This article belongs to the Special Issue Structure and Ligand Based Drug Design)
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16 pages, 4347 KiB  
Article
In Silico Prediction of Plasmodium falciparum Cytoadherence Inhibitors That Disrupt Interaction between gC1qR-DBLβ12 Complex
by Abdul Hafiz, Rowaida Bakri, Mohammad Alsaad, Obadah M. Fetni, Lojain I. Alsubaihi and Hina Shamshad
Pharmaceuticals 2022, 15(6), 691; https://0-doi-org.brum.beds.ac.uk/10.3390/ph15060691 - 31 May 2022
Cited by 3 | Viewed by 2058
Abstract
Malaria causes about half a million deaths per year, mainly in children below 5 years of age. Cytoadherence of Plasmodium falciparum infected erythrocytes in brain and placenta has been linked to severe malaria and malarial related deaths. Cytoadherence is mediated by binding of [...] Read more.
Malaria causes about half a million deaths per year, mainly in children below 5 years of age. Cytoadherence of Plasmodium falciparum infected erythrocytes in brain and placenta has been linked to severe malaria and malarial related deaths. Cytoadherence is mediated by binding of human receptor gC1qR to the DBLβ12 domain of a P. falciparum erythrocyte membrane protein family 1 (PfEMP1) protein. In the present work, molecular dynamic simulation was extensively studied for the gC1qR-DBLβ12 complex. The stabilized protein complex was used to study the protein–protein interface interactions and mapping of interactive amino acid residues as hotspot were performed. Prediction of inhibitors were performed by using virtual protein–protein inhibitor database Timbal screening of about 15,000 compounds. In silico mutagenesis studies, binding profile and protein ligand interaction fingerprinting were used to strengthen the screening of the potential inhibitors of gC1qR-DBLβ12 interface. Six compounds were selected and were further subjected to the MAIP analysis and ADMET studies. From these six compounds, the compounds 3, 5, and 6 were found to outperform on all screening criteria from the rest selected compounds. These compounds may provide novel drugs to treat and manage severe falciparum malaria. Additionally. the identified hotspots can be used in future for designing novel interventions for disruption of interface interactions, such as through peptides or vaccines. Futher in vitro and in vivo studies are required for the confirmation of these compounds as potential inhibitors of gC1qR-DBLβ12 interaction. Full article
(This article belongs to the Special Issue Structure and Ligand Based Drug Design)
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18 pages, 4229 KiB  
Article
Design, Synthesis, and Biological Evaluation of 4,4’-Difluorobenzhydrol Carbamates as Selective M1 Antagonists
by Jonas Kilian, Marius Ozenil, Marlon Millard, Dorka Fürtös, Verena Maisetschläger, Wolfgang Holzer, Wolfgang Wadsak, Marcus Hacker, Thierry Langer and Verena Pichler
Pharmaceuticals 2022, 15(2), 248; https://0-doi-org.brum.beds.ac.uk/10.3390/ph15020248 - 18 Feb 2022
Cited by 4 | Viewed by 2271
Abstract
Due to their important role in mediating a broad range of physiological functions, muscarinic acetylcholine receptors (mAChRs) have been a promising target for therapeutic and diagnostic applications alike; however, the list of truly subtype-selective ligands is scarce. Within this work, we have identified [...] Read more.
Due to their important role in mediating a broad range of physiological functions, muscarinic acetylcholine receptors (mAChRs) have been a promising target for therapeutic and diagnostic applications alike; however, the list of truly subtype-selective ligands is scarce. Within this work, we have identified a series of twelve 4,4’-difluorobenzhydrol carbamates through a rigorous docking campaign leveraging commercially available amine databases. After synthesis, these compounds have been evaluated for their physico–chemical property profiles, including characteristics such as HPLC-logD, tPSA, logBB, and logPS. For all the synthesized carbamates, these characteristics indicate the potential for BBB permeation. In competitive radioligand binding experiments using Chinese hamster ovary cell membranes expressing the individual human mAChR subtype hM1-hM5, the most promising compound 2 displayed a high binding affinitiy towards hM1R (1.2 nM) while exhibiting modest-to-excellent selectivity versus the hM2-5R (4–189-fold). All 12 compounds were shown to act in an antagonistic fashion towards hM1R using a dose-dependent calcium mobilization assay. The structural eligibility for radiolabeling and their pharmacological and physico–chemical property profiles render compounds 2, 5, and 7 promising candidates for future position emission tomography (PET) tracer development. Full article
(This article belongs to the Special Issue Structure and Ligand Based Drug Design)
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