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A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Computational and Theoretical Chemistry".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 7298

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Special Issue Editors

Dr. Jinping Lei

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Guest Editor

School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou 510006, China
Interests: computer-aided drug design; computational biology; multi-scale modelling
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. John Zhang

E-Mail Website
Guest Editor

NYU-ECU Center for Computational Chemistry, NYU Shanghai, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, China
Interests: computational chemistry; MD simulation; computational drug design; protein–protein interaction; free energy calculation

Special Issue Information

Dear Colleagues,

Computer-Aided Drug Designing (CADD) has gained wide popularity among biologists and chemists as a part of an interdisciplinary drug discovery approach. It plays a vital role in the discovery, design and analysis of drugs in the pharmaceutical industry. It is extensively used to reduce costs and time and speed up the early-stage development of biologically new active molecules. Several approved drugs have been developed with the aid of CADD. In this Special Issue, we will present manuscripts on the following types of CADD: Structure-Based Drug Designing (SBDD) including molecular docking and molecular dynamic simulations, Ligand-Based Drug Designing (LBDD) including quantitative structure–activity relationship (QSAR) modelling, Pharmacophore-based drug designing (PBDD), and Fragment-Based Drug Designing (FBDD), in addition to the theory, including artificial intelligence (AI), behind the types of CADD and their applications.

Dr. Jinping Lei
Prof. Dr. John Zhang
Guest Editors

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Keywords

computer-aided drug design
structure-based drug design
ligand-based drug design
fragment-based drug design
pharmacophore
QSAR
molecular modelling
artificial intelligence

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Published Papers (6 papers)

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Research

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16 pages, 2933 KiB

Open AccessArticle

Discovery of Novel Antimicrobial-Active Compounds and Their Analogues by In Silico Small Chemical Screening Targeting Staphylococcus aureus MurB

by Saya Okubo, Shoki Hirose and Shunsuke Aoki

Molecules 2025, 30(7), 1477; https://doi.org/10.3390/molecules30071477 - 26 Mar 2025

Viewed by 329

Abstract

Methicillin-resistant Staphylococcus aureus is a serious problem in healthcare due to its lethal severe infections and resistance to most antimicrobial agents. The number of new approved antimicrobial agents is declining, and combined with the spread of drug-resistant bacteria, it is predicted that effective antimicrobial agents against multidrug-resistant bacteria will be exhausted. We conducted in silico and in vitro discovery of novel antimicrobial small molecules targeting the SaMurB enzyme involved in cell wall synthesis in Staphylococcus aureus (S. aureus). We performed hierarchical structure-based drug screenings to identify compounds and their analogues using a library of approximately 1.3 million compound structures. In vitro experiments with Staphylococcus epidermidis (S. epidermidis) identified three compounds (SH5, SHa6, and SHa13) that exhibit antibacterial activity. These three compounds do not have toxicity against human-derived cells. SHa13 exhibited remarkable activity (IC₅₀ value =1.64 ± 0.01 µM). The active compound was predicted to bind to the active site of SaMurB by forming a hydrogen bond with Arg188 in both R and S bodies. These data provide a starting point for the development of novel cell wall synthesis inhibitors as antimicrobial agents targeting SaMurB. Full article

(This article belongs to the Special Issue Recent Advances in Computer-Aided Drug Design and Drug Discovery)

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14 pages, 2207 KiB

Open AccessArticle

Natural Flavonoids from Licorice as Potent Inhibitors of β-Glucuronidase Elucidated Through Computational Studies

by Jingli Liu, Yingying Xue, Hao Yan, Jing Zhou, Xu Long and Yuping Tang

Molecules 2025, 30(6), 1324; https://doi.org/10.3390/molecules30061324 - 15 Mar 2025

Viewed by 677

Abstract

Gut bacterial β-glucuronidase is an important molecular target in several therapeutic applications. β-glucuronidase inhibitors can effectively alleviate gastrointestinal toxicity caused by certain drugs. Licorice, a traditional Chinese medicine, harmonizes various herbs and mitigates the toxicity of hundreds of herbs. In this study, a comprehensive computational strategy was employed to evaluate four licorice flavonoids (liquiritigenin, isoliquiritigenin, liquiritin, and isoliquiritin) as potential Escherichia coli β-glucuronidase (EcGUS) inhibitors. Density functional theory was used to determine their geometries, thermal parameters, dipole moments, polarizabilities, and molecular electrostatic potentials. The inhibitory mechanisms of these four flavonoids on EcGUS were investigated using molecular docking, molecular dynamics simulations, and free energy calculations. The results show that all four flavonoids stably bind to EcGUS. Moreover, all molecules, except liquiritigenin, are potent and selective inhibitors of EcGUS. Further calculations suggest that isoliquiritin exhibits the strongest binding affinity for EcGUS among the four licorice flavonoids. Thus, isoliquiritin is a promising candidate for the development of EcGUS inhibitors. These findings will aid in designing and developing novel flavonoid-based inhibitors of EcGUS to alleviate gastrointestinal toxicity caused by drugs. Full article

(This article belongs to the Special Issue Recent Advances in Computer-Aided Drug Design and Drug Discovery)

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11 pages, 2606 KiB

Open AccessArticle

Molecular Dynamics-Assisted Discovery of Novel Phosphodiesterase-5 Inhibitors Targeting a Unique Allosteric Pocket

by Weihao Luo, Runduo Liu, Xinlin Cai, Qian Zhou and Chen Zhang

Molecules 2025, 30(3), 588; https://doi.org/10.3390/molecules30030588 - 27 Jan 2025

Viewed by 828

Abstract

Phosphodiesterase-5 (PDE5) is a potent therapeutic target for the treatment of male erectile dysfunction and pulmonary arterial hypertension with several drugs available on the market. However, most of the reported PDE5 inhibitors lack specificity over PDE6, a holoenzyme in eleven PDE families, which may cause various adverse effects. Targeting a unique allosteric pocket has proved to be an effective approach to designing selective PDE5 inhibitors. In the present study, an integrated virtual screening procedure consisting of pharmacophore modeling screening, molecular docking, molecular dynamics simulations, and binding free energy calculations was applied to the discovery of novel PDE5 inhibitors targeting the allosteric pocket. Seven out of thirty-three molecules purchased from the SPECS database (a hitting accuracy of 21%) with novel scaffolds were PDE5 inhibitors with enzymatic inhibition ratios of more than 50% at a concentration of 10 μM. Predicted binding patterns indicate these hits fit well in the allosteric pocket in PDE5. In particular, compound AI-898/12177002 (IC₅₀ = 1.6 μM) demonstrates over 10-fold selectivity towards PDE6, providing a novel scaffold for the optimization of potent and selective PDE5 inhibitors with less adverse effects. Full article

(This article belongs to the Special Issue Recent Advances in Computer-Aided Drug Design and Drug Discovery)

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18 pages, 4005 KiB

Open AccessArticle

Discovery of Cyclic Peptide Inhibitors Targeted on TNFα-TNFR1 from Computational Design and Bioactivity Verification

by Jiangnan Zhang, Huijian Zhao, Qianqian Zhou, Xiaoyue Yang, Haoran Qi, Yongxing Zhao and Longhua Yang

Molecules 2024, 29(21), 5147; https://doi.org/10.3390/molecules29215147 - 31 Oct 2024

Cited by 1 | Viewed by 1948

Abstract

Activating tumor necrosis factor receptor 1 (TNFR1) with tumor necrosis factor alpha (TNFα) is one of the key pathological mechanisms resulting in the exacerbation of rheumatoid arthritis (RA) immune response. Despite various types of drugs being available for the treatment of RA, a series of shortcomings still limits their application. Therefore, developing novel peptide drugs that target TNFα-TNFR1 interaction is expected to expand therapeutic drug options. In this study, the detailed interaction mechanism between TNFα and TNFR1 was elucidated, based on which, a series of linear peptides were initially designed. To overcome its large conformational flexibility, two different head-to-tail cyclization strategies were adopted by adding a proline-glycine (GP) or cysteine-cysteine (CC) to form an amide or disulfide bond between the N-C terminal. The results indicate that two cyclic peptides, R1_CC4 and α_CC8, exhibit the strongest binding free energies. α_CC8 was selected for further optimization using virtual mutations through in vitro activity and toxicity experiments due to its optimal biological activity. The L16R mutant was screened, and its binding affinity to TNFR1 was validated using ELISA assays. This study designed a novel cyclic peptide structure with potential anti-inflammatory properties, possibly bringing an additional choice for the treatment of RA in the future. Full article

(This article belongs to the Special Issue Recent Advances in Computer-Aided Drug Design and Drug Discovery)

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20 pages, 32505 KiB

Open AccessArticle

Unraveling the Binding Mode of Cyclic Adenosine–Inosine Monophosphate (cAIMP) to STING through Molecular Dynamics Simulations

by Meiting Wang, Baoyi Fan, Wenfeng Lu, Ulf Ryde, Yuxiao Chang, Di Han, Jiarui Lu, Taigang Liu, Qinghe Gao, Changpo Chen and Yongtao Xu

Molecules 2024, 29(11), 2650; https://doi.org/10.3390/molecules29112650 - 4 Jun 2024

Cited by 1 | Viewed by 1262

Abstract

The stimulator of interferon genes (STING) plays a significant role in immune defense and protection against tumor proliferation. Many cyclic dinucleotide (CDN) analogues have been reported to regulate its activity, but the dynamic process involved when the ligands activate STING remains unclear. In this work, all-atom molecular dynamics simulations were performed to explore the binding mode between human STING (hSTING) and four cyclic adenosine–inosine monophosphate analogs (cAIMPs), as well as 2′,3′-cGMP-AMP (2′,3′-cGAMP). The results indicate that these cAIMPs adopt a U-shaped configuration within the binding pocket, forming extensive non-covalent interaction networks with hSTING. These interactions play a significant role in augmenting the binding, particularly in interactions with Tyr167, Arg238, Thr263, and Thr267. Additionally, the presence of hydrophobic interactions between the ligand and the receptor further contributes to the overall stability of the binding. In this work, the conformational changes in hSTING upon binding these cAIMPs were also studied and a significant tendency for hSTING to shift from open to closed state was observed after binding some of the cAIMP ligands. Full article

(This article belongs to the Special Issue Recent Advances in Computer-Aided Drug Design and Drug Discovery)

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19 pages, 1822 KiB

Open AccessReview

Uses of Molecular Docking Simulations in Elucidating Synergistic, Additive, and/or Multi-Target (SAM) Effects of Herbal Medicines

by Sean P. Rigby

Molecules 2024, 29(22), 5406; https://doi.org/10.3390/molecules29225406 - 16 Nov 2024

Cited by 2 | Viewed by 1520

Abstract

The philosophy of herbal medicines is that they contain multiple active components that target many aspects of a given disease. This is in line with the recent multiple-target strategy adopted due to shortcomings with the previous “magic bullet”, single-target strategy. The complexity of biological systems means it is often difficult to elucidate the mechanisms of synergistic, additive, and/or multi-target (SAM) effects. However, the use of methodologies employing molecular docking offers some insight into these. The aim of this work was to review the uses of molecular-docking simulations in the detection and/or elucidation of SAM effects with herbal medicines. Molecular docking has revealed the potential for SAM effects with many different, individual herbal medicines. Docking can also improve the fundamental understanding of SAM effects as part of systems biology approaches, such as providing quantitative weightings for the connections within static networks or supplying estimates of kinetic parameters for dynamic metabolic networks. Molecular docking can also be combined with pharmacophore modeling in a hybrid method that greatly improves the efficiency of screening. Overall, molecular docking has been shown to be a highly useful tool to provide evidence for the efficacy of herbal medicines, previously only supported by traditional usage. Full article

(This article belongs to the Special Issue Recent Advances in Computer-Aided Drug Design and Drug Discovery)

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