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Structural and Computationally Driven Molecule Design in Drug Discovery: 2nd...
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Structural and Computationally Driven Molecule Design in Drug Discovery: 2nd Edition

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

Deadline for manuscript submissions: 20 December 2025 | Viewed by 16573

Special Issue Editors

Dr. Halil İbrahim Ciftci

E-Mail Website
Guest Editor
1. Department of Molecular Biology and Genetics, Burdur Mehmet Akif Ersoy University, Burdur 15030, Türkiye
2. Department of Bioengineering Sciences, Izmir Katip Celebi University, Izmir 35620, Türkiye
3. Medicinal and Biological Chemistry Science Farm Joint Research Laboratory, Faculty of Life Sciences, Kumamoto University, Kumamoto 862-0976, Japan
4. Department of Drug Discovery, Science Farm Ltd., Kumamoto 862-0976, Japan
Interests: structure-based drug discovery; molecular simulations; drug repositioning; structural biology; molecular modelling; QSAR; virtual screening
Special Issues, Collections and Topics in MDPI journals
Dr. Belgin Sever

E-Mail Website
Guest Editor
Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Anadolu University, 26470 Eskisehir, Turkey
Interests: medicinal chemistry; computational chemistry; QSAR; molecular modelling; molecular simulations; virtual screening; in silico ADME analysis; drug design and development
Special Issues, Collections and Topics in MDPI journals
Dr. Hasan Demirci

E-Mail Website
Guest Editor
1. Department of Molecular Biology and Genetics, Koc University, Istanbul, Turkey
2. Stanford PULSE Institute, SLAC National Laboratory, Menlo Park, CA, USA
Interests: X-ray crystallography; antibiotics; time-resolved SFX; ribosome; RNA modifications; innovative drug development
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The compliance between computational and experimental outcomes is a mainstay for drug development, which is a complicated, high-risk, expensive, and lengthy process along with several stages such as target identification, lead discovery, and lead optimization.

In silico studies, which are used to define promising ligands in a target structure, shed light on further synthesis and evaluation of biological activities and consequently the identification of three-dimensional (3D) structures of the ligand–receptor complexes. The resolution of key macromolecular drug targets using the cutting-edge technology of X-ray crystallography and spectroscopic methods in molecular and structural biology also leads to an increase in the generation of diverse computational methods. Structure-based and ligand-based drug design strategies including molecular docking, molecular dynamics, quantitative structure–activity relationship (QSAR) modeling, and pharmacophore generation are implemented in computer-aided drug design.

Virtual screening is a versatile platform that enables the screening of a large number of compounds in a short period of time. Molecular docking is one of the virtual screening methods, which can anticipate the binding affinity of ligand and receptor. Thereafter, molecular dynamics simulations could be used to predict the stability of a ligand–receptor complex obtained from molecular docking assessment.

Furthermore, in the drug development process, many drug candidates could not pass the trials successfully due to the inadequate ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties. Therefore, in silico ADMET analysis is attractive and a cost-saving strategy for a large number of compounds prior to applying expensive and time-consuming in vitro and in vivo ADMET methods.

In recent years, Artificial Intelligence (AI) techniques utilize machines and/or computers to increase the field of personalized/precision medicine to the extent that it turns into common practice even in the treatment of simple diseases. AI methods are very useful in discovering drugs and estimating drug properties including binding affinities and interactions, toxicity issues, and physicochemical properties.

This Special Issue aims to provide deep mechanistic insights into strategies in structural dynamics studies and computational methods. It is our great pleasure to invite you to submit original research articles and reviews, which will be published in a Special Issue on “Structural and Computationally Driven Molecule Design in Drug Discovery: 2nd Edition”.

Dr. Halil İbrahim Ciftci
Dr. Belgin Sever
Dr. Hasan Demirci
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Pharmaceuticals is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

  • structural dynamics studies
  • computer-aided drug design
  • molecular dynamics simulations
  • molecular docking
  • virtual screening
  • QSAR
  • in silico ADMET
  • artificial intelligence (AI) techniques

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Published Papers (12 papers)

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31 pages, 7317 KiB  
Article
Synthesis, Biological Evaluation, and In Silico Characterization of Novel Imidazothiadiazole–Chalcone Hybrids as Multi-Target Enzyme Inhibitors
by Hakan Alici, Senol Topuz, Kadir Demir, Parham Taslimi and Hakan Tahtaci
Pharmaceuticals 2025, 18(7), 962; https://doi.org/10.3390/ph18070962 - 26 Jun 2025
Viewed by 420
Abstract
Background/Objectives: The need for dual-targeted enzyme inhibitors is critical in addressing complex diseases like Alzheimer’s and glaucoma. Imidazothiadiazole and chalcone moieties are known for diverse bioactivities. This study aimed to develop novel imidazothiadiazole–chalcone hybrids as potential inhibitors of acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and [...] Read more.
Background/Objectives: The need for dual-targeted enzyme inhibitors is critical in addressing complex diseases like Alzheimer’s and glaucoma. Imidazothiadiazole and chalcone moieties are known for diverse bioactivities. This study aimed to develop novel imidazothiadiazole–chalcone hybrids as potential inhibitors of acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and human carbonic anhydrase isoforms (hCAs), specifically hCA I and hCA II. Methods: Four hybrid molecules (8a–8d) were synthesized and structurally confirmed via 1H NMR, 13C NMR, FT-IR, MS, and elemental analysis techniques. Their enzyme inhibitory activities were assessed using Ellman’s and Verpoorte’s methods. Molecular docking and 100 ns molecular dynamics (MD) simulations were conducted to examine binding interactions. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties were predicted using the pkCSM platform. Results: All compounds showed strong enzyme inhibition: AChE (Ki: 3.86–11.35 nM), BChE (Ki: 1.01–1.78 nM), hCA I (Ki: 45.13–81.24 nM), and hCA II (Ki: 36.08–52.45 nM). Docking analyses confirmed favorable binding, particularly with active-site residues. MD simulations demonstrated stable interactions throughout 100 ns. Compound 8a exhibited the highest cholinesterase inhibition, while compounds 8d and 8c were the most potent against hCA I and hCA II, respectively. The ADMET results showed high absorption and acceptable safety, with mild mutagenicity or cardiotoxicity concerns in select compounds. Conclusions: These findings suggest that imidazothiadiazole–chalcone hybrids are promising multi-target enzyme inhibitors. Their potent activity, structural stability, and pharmacokinetic potential support their further development for therapeutic use in neurodegenerative and ocular diseases. Full article
(This article belongs to the Special Issue Structural and Computationally Driven Molecule Design in Drug Discovery: 2nd Edition)
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41 pages, 13934 KiB  
Article
Unveiling Palmitoyl Thymidine Derivatives as Antimicrobial/Antiviral Inhibitors: Synthesis, Molecular Docking, Dynamic Simulations, ADMET, and Assessment of Protein–Ligand Interactions
by Sarkar M. A. Kawsar, Samiah Hamad Al-mijalli, Gassoumi Bouzid, Emad M. Abdallah, Noimul H. Siddiquee, Mohammed A. Hosen, Mabrouk Horchani, Houcine Ghalla, Hichem B. Jannet, Yuki Fujii and Yasuhiro Ozeki
Pharmaceuticals 2025, 18(6), 806; https://doi.org/10.3390/ph18060806 - 27 May 2025
Viewed by 1707
Abstract
Background/Objectives: Nucleoside precursors and derivatives play pivotal roles in the development of antimicrobial and antiviral therapeutics. The 2022 global outbreak of monkeypox (Mpox) across more than 100 nonendemic countries underscores the urgent need for novel antiviral agents. This study aimed to synthesize and [...] Read more.
Background/Objectives: Nucleoside precursors and derivatives play pivotal roles in the development of antimicrobial and antiviral therapeutics. The 2022 global outbreak of monkeypox (Mpox) across more than 100 nonendemic countries underscores the urgent need for novel antiviral agents. This study aimed to synthesize and evaluate a series of 5′-O-(palmitoyl) derivatives (compounds 2–6), incorporating various aliphatic and aromatic acyl groups, for their potential antimicrobial activities. Methods: The structures of the synthesized derivatives were confirmed through physicochemical, elemental, and spectroscopic techniques. In vitro antibacterial efficacy was assessed, including minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) determinations for the most active compounds (4 and 5). The antifungal activity was evaluated based on mycelial growth inhibition. Density functional theory (DFT) calculations were employed to investigate the electronic and structural properties, including the global reactivity, frontier molecular orbital (FMO), natural bond orbital (NBO), and molecular electrostatic potential (MEP). Molecular docking studies were conducted against the monkeypox virus and the Marburg virus. The top-performing compounds (3, 5, and 6) were further evaluated via 200 ns molecular dynamics (MD) simulations. ADMET predictions were performed to assess drug-likeness and pharmacokinetic properties. Results: Compounds 4 and 5 demonstrated remarkable antibacterial activity compared with the precursor molecule, while most derivatives inhibited fungal mycelial growth by up to 79%. Structure-activity relationship (SAR) analysis highlighted the enhanced antibacterial/antifungal efficacy with CH3(CH2)10CO– and CH3(CH2)12CO–acyl chains. In silico docking revealed that compounds 3, 5, and 6 had higher binding affinities than the other derivatives. MD simulations confirmed the stability of the protein-ligand complexes. ADMET analyses revealed favorable drug-like profiles for all the lead compounds. Conclusions: The synthesized compounds 3, 5, and 6 exhibit promising antimicrobial and antiviral activities. Supported by both in vitro assays and comprehensive in silico analyses, these derivatives have emerged as potential candidates for the development of novel therapeutics against bacterial, fungal, and viral infections, including monkeypox and Marburg viruses. Full article
(This article belongs to the Special Issue Structural and Computationally Driven Molecule Design in Drug Discovery: 2nd Edition)
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33 pages, 7254 KiB  
Article
Structure-Based Design and In-Silico Evaluation of Computationally Proposed Curcumin Derivatives as Potential Inhibitors of the Coronaviral PLpro Enzymes
by Hakan Alici
Pharmaceuticals 2025, 18(6), 798; https://doi.org/10.3390/ph18060798 - 26 May 2025
Viewed by 653
Abstract
Background/Objectives: Highly pathogenic coronaviruses (CoVs), including SARS-CoV, MERS-CoV, and SARS-CoV-2, continue to pose a significant threat to global public health. Therefore, this situation highlights the urgent need for effective broad-spectrum antiviral agents. Curcumin, a naturally occurring polyphenol known for its antiviral and anti-inflammatory [...] Read more.
Background/Objectives: Highly pathogenic coronaviruses (CoVs), including SARS-CoV, MERS-CoV, and SARS-CoV-2, continue to pose a significant threat to global public health. Therefore, this situation highlights the urgent need for effective broad-spectrum antiviral agents. Curcumin, a naturally occurring polyphenol known for its antiviral and anti-inflammatory properties, faces limitations such as poor bioavailability and rapid metabolic degradation, restricting its practical therapeutic application. Methods: To address these limitations, this study introduces a novel design strategy aimed at 42 new curcumin derivatives with improved pharmacokinetic profiles, specifically targeting the conserved coronavirus enzyme papain-like protease (PLpro). A comprehensive in silico evaluation was performed, including ADMET (Absorption, Distribution, Metabolism, Elimination, and Toxicity) analysis, molecular docking, molecular dynamics (MD) simulations, and Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) calculations. Results: Extensive pharmacokinetic and toxicological assessments (ADMET analyses) identified 19 derivatives exhibiting optimal drug-like characteristics according to Lipinski’s Rule of Five (Ro5). Molecular docking analyses demonstrated that these novel derivatives possess significantly enhanced binding affinities to PLpro enzymes from SARS-CoV, MERS-CoV, and SARS-CoV-2 compared to standard antiviral agents and natural curcumin. Further validation through MD simulations and MM/PBSA calculations confirmed the structural stability and robust interactions of the most promising derivatives within the SARS-CoV PLpro active site. Conclusions: The results of this study provide essential structural and functional insights, reinforcing the potential of these newly developed curcumin derivatives as potent, broad-spectrum antiviral agents effective against current and future coronavirus threats. Full article
(This article belongs to the Special Issue Structural and Computationally Driven Molecule Design in Drug Discovery: 2nd Edition)
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26 pages, 11403 KiB  
Article
Unveiling the Polypharmacological Potency of FDA-Approved Rebamipide for Alzheimer’s Disease
by Israa J. Hakeem, Hadil Alahdal, Hanadi M. Baeissa, Tahani Bakhsh, Misbahuddin Rafeeq, Alaa Hamed Habib, Mohammed Matoog Karami, Maryam A. AL-Ghamdi, Ghadeer Abdullah and Abeer Al Tuwaijri
Pharmaceuticals 2025, 18(6), 772; https://doi.org/10.3390/ph18060772 - 22 May 2025
Viewed by 568
Abstract
Background: Alzheimer’s disease (AD) is a multifactorial neurodegenerative disorder characterised by the accumulation of neurotoxic substances in the brain, ultimately leading to progressive cognitive decline. The complex aetiology and involvement of multiple molecular targets in AD pathogenesis have made discovering effective therapeutic agents [...] Read more.
Background: Alzheimer’s disease (AD) is a multifactorial neurodegenerative disorder characterised by the accumulation of neurotoxic substances in the brain, ultimately leading to progressive cognitive decline. The complex aetiology and involvement of multiple molecular targets in AD pathogenesis have made discovering effective therapeutic agents particularly challenging. Targeting multiple proteins simultaneously with a single therapeutic agent may offer a promising strategy to address the disease’s multifaceted nature. Methods: This study employed advanced computational methodologies to perform multitargeted molecular docking of FDA-approved drugs against four key AD-associated proteins implicated in disease progression. Among the screened compounds, Rebamipide—a drug conventionally used for treating gastrointestinal disorders—demonstrated notable binding affinities across all targets. Pharmacokinetic predictions, interaction fingerprinting, WaterMap analysis, density functional theory (DFT) calculations, and 100 ns MD simulations were performed for each protein–ligand complex to evaluate its multitarget potential. Results: Rebamipide bound effectively to the NR1 ligand-binding core, suggesting modulation of glutamatergic signalling while reducing β-secretase production and regulating neurotransmitter homeostasis through inhibiting monoamine oxidase-A. Furthermore, Rebamipide enhanced cholinergic neurotransmission by inhibiting human acetylcholinesterase, potentially improving cognitive function. Pharmacokinetic analyses confirmed favourable drug-like properties. Molecular interaction fingerprints revealed consistent hydrogen bonding, hydrophobic contacts, and π-π stacking interactions. WaterMap analysis indicated thermodynamically favourable water displacement upon binding, enhancing ligand affinity. DFT analysis of Rebamipide showed a 4.24 eV HOMO-LUMO gap, with ESP values ranging from −6.63 × 10−2 to +6.63 × 10−2 A.U., indicating reactive sites. TDDFT predicted strong UV absorption at 314 nm with a peak intensity of ~6500 L mol−1 cm−1. MD simulations over 100 ns demonstrated minimal structural deviations and stable ligand–protein complexes, reinforcing its multitarget efficacy. Conclusions: The comprehensive in silico investigation highlights Rebamipide as a promising multitargeted therapeutic candidate for Alzheimer’s disease. Its ability to modulate multiple pathogenic pathways simultaneously underscores its potential utility; however, these computational findings warrant further experimental validation to confirm its efficacy and therapeutic relevance in AD. Full article
(This article belongs to the Special Issue Structural and Computationally Driven Molecule Design in Drug Discovery: 2nd Edition)
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44 pages, 11441 KiB  
Article
Identification of Bacterial Oligopeptidase B Inhibitors from Microbial Natural Products: Molecular Insights, Docking Studies, MD Simulations, and ADMET Predictions
by Malik Suliman Mohamed, Tilal Elsaman, Magdi Awadalla Mohamed, Eyman Mohamed Eltayib, Abualgasim Elgaili Abdalla and Mona Timan Idriss
Pharmaceuticals 2025, 18(5), 709; https://doi.org/10.3390/ph18050709 - 11 May 2025
Viewed by 710
Abstract
Background/Objectives: The increasing threat of antibiotic resistance and the declining efficiency of traditional drug discovery pipelines highlight the urgent need for novel drug targets and effective enzyme inhibitors against infectious diseases. Oligopeptidase B (OPB), a serine protease with trypsin-like specificity that processes low-molecular-weight [...] Read more.
Background/Objectives: The increasing threat of antibiotic resistance and the declining efficiency of traditional drug discovery pipelines highlight the urgent need for novel drug targets and effective enzyme inhibitors against infectious diseases. Oligopeptidase B (OPB), a serine protease with trypsin-like specificity that processes low-molecular-weight peptides and oligopeptides, is present in bacteria and certain parasites but absent in mammals. This unique distribution makes OPB an attractive and selective target for antimicrobial drug development. Methods: Three-dimensional models of OPB from Serratia marcescens and Stenotrophomonas maltophilia, previously identified by our research group, were constructed via homology modeling using the best available OPB template from the RCSB Protein Data Bank. The S. marcescens OPB model was subjected to high-throughput virtual screening (HTVS) against the Natural Products Atlas (npatlas) database. Top-ranking compounds were further evaluated using Glide standard precision (SP) and extra precision (XP) docking protocols. Binding affinities were refined using molecular mechanics with generalized born and surface area (MM–GBSA) calculations. Molecular dynamics (MD) simulations assessed binding stability, while absorption distribution metabolism excretion and toxicity (ADMET) profiling evaluated drug-likeness and pharmacokinetic properties. Results: Ten natural product compounds demonstrated stronger binding affinities than antipain, a well-known oligopeptide-based protease inhibitor, as indicated by their more favorable MM–GBSA scores of −60.90 kcal/mol (S. marcescens) and −27.07 kcal/mol (S. maltophilia). Among these, dichrysobactin and validamycin E consistently exhibited favorable binding profiles across both OPB models. MD simulations confirmed the stability of their interactions with OPB active sites, maintaining favorable binding conformations throughout the simulation period. ADMET analysis suggested that while both compounds show promise, lead optimization is required to enhance their drug-like characteristics. Conclusions: This study identifies dichrysobactin and validamycin E as promising OPB inhibitors with potential antimicrobial activity. These findings support their further development as selective and potent agents against bacterial pathogens, including resistant strains, and underscore the need for experimental validation to confirm their efficacy and safety. Full article
(This article belongs to the Special Issue Structural and Computationally Driven Molecule Design in Drug Discovery: 2nd Edition)
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21 pages, 3717 KiB  
Article
Design, Synthesis, and Mechanistic Anticancer Evaluation of New Pyrimidine-Tethered Compounds
by Farida Reymova, Belgin Sever, Edanur Topalan, Canan Sevimli-Gur, Mustafa Can, Amaç Fatih Tuyun, Faika Başoğlu, Abdulilah Ece, Masami Otsuka, Mikako Fujita, Hasan Demirci and Halilibrahim Ciftci
Pharmaceuticals 2025, 18(2), 270; https://doi.org/10.3390/ph18020270 - 19 Feb 2025
Cited by 4 | Viewed by 1449
Abstract
Background: Despite recent breakthroughs in cancer treatment, non-small cell lung cancer (NSCLC) and breast cancer remain major causes of death from all malignancies. The epidermal growth factor receptor (EGFR) is an important mediator of the pathways involved in cell proliferation, apoptosis, and angiogenesis. [...] Read more.
Background: Despite recent breakthroughs in cancer treatment, non-small cell lung cancer (NSCLC) and breast cancer remain major causes of death from all malignancies. The epidermal growth factor receptor (EGFR) is an important mediator of the pathways involved in cell proliferation, apoptosis, and angiogenesis. Thus, its overexpression triggers several types of cancer, including NSCLC and breast cancer. Methods: In the current study, we synthesized new pyrimidine-tethered compounds (chalcone derivative (B-4), pyrazoline–carbothioamide (B-9), and pyrazoline–thiazole hybrids (BH1-7)). These compounds were then tested for cytotoxicity against A549 NSCLC and MCF-7 breast cancer cells. Results: Of these, B-4 displayed significant cytotoxicity against both cells (IC50 = 6.70 ± 1.02 µM for MCF-7; IC50 = 20.49 ± 2.7 µM for A549) compared to the standard agent lapatinib (IC50 = 9.71 ± 1.12 µM for MCF-7; IC50 = 18.21 ± 3.25 µM for A549). The anticancer potential of B-4 between Jurkat leukemic T cells and peripheral blood mononuclear cells (PBMCs) (healthy) was found to be selective. Mechanistically, 11.9% and 10.2% of A549 and MCF-7 cells treated with B-4, respectively, underwent apoptosis and B-4 produced 46% EGFR inhibition at a concentration of 10 μM. The B-4/EGFR complex obtained after induced fit docking was subjected to 300 ns of molecular dynamics simulation, which confirmed the stability of the complex in a mimicked biological environment. On the other hand, B-4 was shown to have drug-like properties by in silico pharmacokinetic estimation. Conclusions: B-4 is an EGFR inhibitor and apoptosis inducer for future NSCLC and breast cancer studies. Full article
(This article belongs to the Special Issue Structural and Computationally Driven Molecule Design in Drug Discovery: 2nd Edition)
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30 pages, 8378 KiB  
Article
Examining Prenylated Xanthones as Potential Inhibitors Against Ketohexokinase C Isoform for the Treatment of Fructose-Driven Metabolic Disorders: An Integrated Computational Approach
by Tilal Elsaman and Magdi Awadalla Mohamed
Pharmaceuticals 2025, 18(1), 126; https://doi.org/10.3390/ph18010126 - 18 Jan 2025
Cited by 3 | Viewed by 1479
Abstract
Background/Objectives: Fructose-driven metabolic disorders, such as obesity, non-alcoholic fatty liver disease (NAFLD), dyslipidemia, and type 2 diabetes, are significant global health challenges. Ketohexokinase C (KHK-C), a key enzyme in fructose metabolism, is a promising therapeutic target. α-Mangostin, a naturally occurring prenylated xanthone, has [...] Read more.
Background/Objectives: Fructose-driven metabolic disorders, such as obesity, non-alcoholic fatty liver disease (NAFLD), dyslipidemia, and type 2 diabetes, are significant global health challenges. Ketohexokinase C (KHK-C), a key enzyme in fructose metabolism, is a promising therapeutic target. α-Mangostin, a naturally occurring prenylated xanthone, has been identified as an effective KHK-C inhibitor, prompting exploration of its analogs for enhanced efficacy. This study aimed to identify α-Mangostin analogs with improved inhibitory properties against KHK-C to address these disorders. Methods: A library of 1383 analogs was compiled from chemical databases and the literature. Molecular docking, binding free energy calculations, pharmacokinetic assessments, molecular dynamics simulations, and quantum mechani–cal analyses were used to screen and evaluate the compounds. α-Mangostin’s binding affinity (37.34 kcal/mol) served as the benchmark. Results: Sixteen analogs demonstrated binding affinities superior to α-Mangostin (from −45.51 to −61.3 kcal/mol), LY-3522348 (−45.36 kcal/mol), and reported marine-derived inhibitors (from −22.74 to −51.83 kcal/mol). Hits 7, 8, 9, 13, and 15 not only surpassed these benchmarks in binding affinity, but also exhibited superior pharmacokinetic properties compared to α-Mangostin, LY-3522348, and marine-derived inhibitors, indicating strong in vivo potential. Among these, hit 8 emerged as the best performer, achieving a binding free energy of −61.30 kcal/mol, 100% predicted oral absorption, enhanced metabolic stability, and stable molecular dynamics. Conclusions: Hit 8 emerged as the most promising candidate due to its superior binding affinity, favorable pharmacokinetics, and stable interactions with KHK-C. These findings highlight its potential for treating fructose-driven metabolic disorders, warranting further experimental validation. Full article
(This article belongs to the Special Issue Structural and Computationally Driven Molecule Design in Drug Discovery: 2nd Edition)
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17 pages, 3341 KiB  
Article
Targeting mTOR Kinase with Natural Compounds: Potent ATP-Competitive Inhibition Through Enhanced Binding Mechanisms
by Sulaiman K. Marafie, Eman Alshawaf, Fahd Al-Mulla, Jehad Abubaker and Anwar Mohammad
Pharmaceuticals 2024, 17(12), 1677; https://doi.org/10.3390/ph17121677 (registering DOI) - 12 Dec 2024
Viewed by 1476
Abstract
Background/Objectives: The mammalian target of the rapamycin (mTOR) signaling pathway is a central regulator of cell growth, proliferation, metabolism, and survival. Dysregulation of mTOR signaling contributes to many human diseases, including cancer, diabetes, and obesity. Therefore, inhibitors against mTOR’s catalytic kinase domain [...] Read more.
Background/Objectives: The mammalian target of the rapamycin (mTOR) signaling pathway is a central regulator of cell growth, proliferation, metabolism, and survival. Dysregulation of mTOR signaling contributes to many human diseases, including cancer, diabetes, and obesity. Therefore, inhibitors against mTOR’s catalytic kinase domain (KD) have been developed and have shown significant antitumor activities, making it a promising therapeutic target. The ATP–KD interaction is particularly important for mTOR to exert its cellular functions, and such inhibitors have demonstrated efficient attenuation of overall mTOR activity. Methods: In this study, we screened the Traditional Chinese Medicine (TCM) database, which enlists natural products that capture the relationships between drugs targets and diseases. Our aim was to identify potential ATP-competitive agonists that target the mTOR-KD and compete with ATP to bind the mTOR-KD serving as potential potent mTOR inhibitors. Results: We identified two compounds that demonstrated interatomic interactions similar to those of ATP–mTOR. The conformational stability and dynamic features of the mTOR-KD bound to the selected compounds were tested by subjecting each complex to 200 ns molecular dynamic (MD) simulations and molecular mechanics/generalized Born surface area (MM/GBSA) to extract free binding energies. We show the effectiveness of both compounds in forming stable complexes with the mTOR-KD, which is more effective than the mTOR-KD–ATP complex with more robust binding affinities. Conclusions: This study implies that both compounds could serve as potential therapeutic inhibitors of mTOR, regulating its function and, therefore, mitigating human disease progression. Full article
(This article belongs to the Special Issue Structural and Computationally Driven Molecule Design in Drug Discovery: 2nd Edition)
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22 pages, 5139 KiB  
Article
Evaluating the Binding Potential and Stability of Drug-like Compounds with the Monkeypox Virus VP39 Protein Using Molecular Dynamics Simulations and Free Energy Analysis
by Ahmed M. Hassan, Hattan S. Gattan, Arwa A. Faizo, Mohammed H. Alruhaili, Azzah S. Alharbi, Leena H. Bajrai, Ibrahim A. AL-Zahrani, Vivek Dhar Dwivedi and Esam I. Azhar
Pharmaceuticals 2024, 17(12), 1617; https://doi.org/10.3390/ph17121617 - 30 Nov 2024
Cited by 9 | Viewed by 3364
Abstract
Background/Objectives: Monkeypox is a re-emerging viral disease with features of infectiously transmitted zoonoses. It is now considered a public health priority because of its rising incidence and transmission from person to person. Monkeypox virus (MPXV) VP39 protein is identified as an essential protein [...] Read more.
Background/Objectives: Monkeypox is a re-emerging viral disease with features of infectiously transmitted zoonoses. It is now considered a public health priority because of its rising incidence and transmission from person to person. Monkeypox virus (MPXV) VP39 protein is identified as an essential protein for replication of the virus, and therefore, it is a potential target for antiviral drugs. Methods: This work analyzes the binding affinities and the differential conformational stability of three target compounds and one control compound with the VP39 protein through multiple computational methods. Results: The re-docking analysis revealed that the compounds had high binding affinities towards the target protein; among these compounds, compounds 1 and 2 showed the highest binding energies in the virtual screening, and thus, these were considered as the most active inhibitor candidates. Intermolecular interaction analysis revealed distinct binding mechanisms. While compound 1 had very strong hydrogen bonds and hydrophobic interactions, compound 2 had numerous water-mediated interactions, and compound 3 had only ionic and hydrophobic contacts. In molecular dynamic simulations, compounds 1 and 2 showed that the protein–ligand complexes had a stable conformation, with protein RMSD values around 2 Å for both compounds. In contrast, compound 3 was slightly flexible, and the control compound was more flexible. MM/GBSA analysis again supported these results, which gave the binding free energies that were also supportive for these compounds. Conclusions: Notably, all the selected compounds, especially compounds 1 and 2, demonstrate high binding affinity. Therefore, these compounds can be further tested as antiviral agents against monkeypox treatment. Full article
(This article belongs to the Special Issue Structural and Computationally Driven Molecule Design in Drug Discovery: 2nd Edition)
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19 pages, 9834 KiB  
Article
Identification of Potential Inhibitors of Histone Deacetylase 6 Through Virtual Screening and Molecular Dynamics Simulation Approach: Implications in Neurodegenerative Diseases
by Anas Shamsi, Moyad Shahwan, Azna Zuberi and Nojood Altwaijry
Pharmaceuticals 2024, 17(11), 1536; https://doi.org/10.3390/ph17111536 - 15 Nov 2024
Cited by 1 | Viewed by 1348
Abstract
Background: Histone deacetylase 6 (HDAC6) plays a crucial role in neurological, inflammatory, and other diseases; thus, it has emerged as an important target for therapeutic intervention. To date, there are no FDA-approved HDAC6-targeting drugs, and most pipeline candidates suffer from poor target engagement, [...] Read more.
Background: Histone deacetylase 6 (HDAC6) plays a crucial role in neurological, inflammatory, and other diseases; thus, it has emerged as an important target for therapeutic intervention. To date, there are no FDA-approved HDAC6-targeting drugs, and most pipeline candidates suffer from poor target engagement, inadequate brain penetration, and low tolerability. There are a few HDAC6 clinical candidates for the treatment of mostly non-CNS cancers as their pharmacokinetic liabilities exclude them from targeting HDAC6-implicated neurological diseases, urging development to address these challenges. They also demonstrate off-target toxicity due to limited selectivity, leading to adverse effects in patients. Selective inhibitors have thus been the focus of development over the past decade, though no selective and potent HDAC6 inhibitor has yet been approved. Methods: This study involved an integrated virtual screening against HDAC6 using the DrugBank database to identify repurposed drugs capable of inhibiting HDAC6 activity. The primary assessment involved the determination of the ability of molecules to bind with HDAC6. Subsequently, interaction analyses and 500 ns molecular dynamics (MD) simulations followed by essential dynamics were carried out to study the conformational flexibility and stability of HDAC6 in the presence of the screened molecules, i.e., penfluridol and pimozide. Results: The virtual screening results pinpointed penfluridol and pimozide as potential repurposed drugs against HDAC6 based on their binding efficiency and appropriate drug profiles. The docking results indicate that penfluridol and pimozide share the same binding site as the reference inhibitor with HDAC6. The MD simulation results showed that stable protein–ligand complexes of penfluridol and pimozide with HDAC6 were formed. Additionally, MMPBSA analysis revealed favorable binding free energies for all HDAC6–ligand complexes, confirming the stability of their interactions. Conclusions: The study implies that both penfluridol and pimozide have strong and favorable binding with HDAC6, which supports the idea of repositioning these drugs for the management of neurodegenerative disorders. However, further in-depth studies are needed to explore their efficacy and safety in biological systems. Full article
(This article belongs to the Special Issue Structural and Computationally Driven Molecule Design in Drug Discovery: 2nd Edition)
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26 pages, 10272 KiB  
Article
Pharmacophore-Based Study: An In Silico Perspective for the Identification of Potential New Delhi Metallo-β-lactamase-1 (NDM-1) Inhibitors
by Heba Ahmed Alkhatabi and Hisham N. Alatyb
Pharmaceuticals 2024, 17(9), 1183; https://doi.org/10.3390/ph17091183 - 9 Sep 2024
Viewed by 1785
Abstract
In the ongoing battle against antibiotic-resistant bacteria, New Delhi metallo-β-lactamase-1 (NDM-1) has emerged as a significant therapeutic challenge due to its ability to confer resistance to a broad range of β-lactam antibiotics. This study presents a pharmacophore-based virtual screening, docking, and molecular dynamics [...] Read more.
In the ongoing battle against antibiotic-resistant bacteria, New Delhi metallo-β-lactamase-1 (NDM-1) has emerged as a significant therapeutic challenge due to its ability to confer resistance to a broad range of β-lactam antibiotics. This study presents a pharmacophore-based virtual screening, docking, and molecular dynamics simulation approach for the identification of potential inhibitors targeting NDM-1, a critical enzyme associated with antibiotic resistance. Through the generation of a pharmacophore model and subsequent virtual screening of compound libraries, candidate molecules (ZINC29142850 (Z1), ZINC78607001 (Z2), and ZINC94303138 (Z3)) were prioritized based on their similarity to known NDM-1 binder (hydrolyzed oxacillin (0WO)). Molecular docking studies further elucidated the binding modes and affinities of the selected compounds towards the active site of NDM-1. These compounds demonstrated superior binding affinities to the enzyme compared to a control compound (−7.30 kcal/mol), with binding scores of −7.13, −7.92, and −8.10 kcal/mol, respectively. Binding interactions within NDM-1’s active site showed significant interactions with critical residues such as His250, Asn220, and Trp93 for these compounds. Subsequent molecular dynamics simulations were conducted to assess the stability of the ligand–enzyme complexes, showing low root mean square deviation (RMSD) values between 0.5 and 0.7 nm for Z1, Z2, which indicate high stability. Z2’s compactness in principal component analysis (PCA) suggests that it can stabilize particular protein conformations more efficiently. Z2 displays a very cohesive landscape with a notable deep basin, suggesting a very persistent conformational state induced by the ligand, indicating robust binding and perhaps efficient inhibition. Z2 demonstrates the highest binding affinity among the examined compounds with a binding free energy of −25.68 kcal/mol, suggesting that it could offer effective inhibition of NDM-1. This study highlights the efficacy of computational tools in identifying novel antimicrobial agents against resistant bacteria, accelerating drug discovery processes. Full article
(This article belongs to the Special Issue Structural and Computationally Driven Molecule Design in Drug Discovery: 2nd Edition)
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Review

Jump to: Research

20 pages, 1591 KiB  
Review
From Molecules to Medicines: The Role of AI-Driven Drug Discovery Against Alzheimer’s Disease and Other Neurological Disorders
by Mashael A. Alghamdi
Pharmaceuticals 2025, 18(7), 1041; https://doi.org/10.3390/ph18071041 - 14 Jul 2025
Viewed by 359
Abstract
The discovery of effective therapeutics against Alzheimer’s disease (AD) and other neurological disorders remains a significant challenge. Artificial intelligence (AI) tools are of considerable interest in modern drug discovery processes and, by exploiting machine learning (ML) algorithms and deep learning (DL) tools, as [...] Read more.
The discovery of effective therapeutics against Alzheimer’s disease (AD) and other neurological disorders remains a significant challenge. Artificial intelligence (AI) tools are of considerable interest in modern drug discovery processes and, by exploiting machine learning (ML) algorithms and deep learning (DL) tools, as well as data analytics, can expedite the identification of new drug targets and potential lead molecules. The current study was aimed at assessing the role of AI-based tools in the discovery of new drug targets against AD and other related neurodegenerative diseases and their efficacy in the discovery of new drugs against these diseases. AD represents a multifactorial neurological disease with limited therapeutics available for management and limited efficacy. The discovery of more effective medications is limited by the complicated pathophysiology of the disease, involving amyloid beta (Aβ), neurofibrillary tangles (NFTs), oxidative stress, and inflammation-induced damage in the brain. The integration of AI tools into the traditional drug discovery process against AD can help to find more effective, safe, highly potent compounds, identify new targets of the disease, and help in the optimization of lead molecules. A detailed literature review was performed to gather evidence regarding the most recent AI tools for drug discovery against AD, Parkinson’s disease (PD), multiple sclerosis (MLS), and epilepsy, focusing on biological markers, early diagnoses, and drug discovery using various databases like PubMed, Web of Science, Google Scholar, Scopus, and ScienceDirect to collect relevant literature. We evaluated the role of AI in analyzing multifaceted biological data and the properties of potential drug candidates and in streamlining the design of clinical trials. By exploring the intersection of AI and neuroscience, this review focused on providing insights into the future of AD treatment and the potential of AI to revolutionize the field of drug discovery. Our findings conclude that AI-based tools are not only cost-effective, but the success rate is extremely high compared to traditional drug discovery methods in identifying new therapeutic targets and in the screening of the majority of molecules for clinical trial purposes. Full article
(This article belongs to the Special Issue Structural and Computationally Driven Molecule Design in Drug Discovery: 2nd Edition)
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