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Pharmaceuticals
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Computational Predictions of Molecules with Potential Therapeutic Effects
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Computational Predictions of Molecules with Potential Therapeutic Effects

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

Deadline for manuscript submissions: 30 September 2025 | Viewed by 9126

Special Issue Editor

Dr. Whelton Miller

E-Mail Website
Guest Editor
Department of Medicine, Loyola University Medical Center, Loyola University Chicago, Maywood, IL 60153, USA
Interests: biophysics; bioengineering; chemistry; drug discovery; computer-aided drug design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We invite submissions of original research, reviews, short communications, and perspectives on biophysics, medicinal chemistry, novel therapeutic agents, drug delivery systems, and computer-aided drug design (CADD) for our special issue. This issue also aims to highlight the latest advancements and innovative research driving the convergence of these fields, covering topics such as structural and functional studies of biomolecules, e.g., the identification of new proteins or protein targets, and integration of artificial intelligence (AI) & machine learning (ML) into the design and optimization of therapeutic agents, innovative drug delivery systems, and structure-activity relationships. We seek to disseminate cutting-edge research, promote interdisciplinary collaborations, and showcase practical applications in biomedical research, with a particular emphasis on advancing drug discovery and development. By showcasing expertise from diverse fields such as biophysics, medicinal chemistry, pharmacology, and computational biology, we aim to foster innovation and facilitate the translation of scientific discoveries into effective therapeutic strategies. Our goal is to highlight studies that not only contribute to the fundamental understanding of biological processes but also offer tangible solutions to current challenges in medicine. Manuscripts should be submitted through the online system per journal guidelines. Submission should contains validation studies. We look forward to your pioneering contributions.

Dr. Whelton Miller
Guest Editor

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Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biophysics
  • medicinal chemistry
  • drug discovery
  • molecular docking
  • molecular dynamics
  • structure-activity relationships
  • computer-aided drug design (CADD)

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Published Papers (6 papers)

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Research

29 pages, 2681 KiB  
Article
In Silico Prediction of Tetrastatin-Derived Peptide Interactions with αvβ3 and α5β1 Integrins
by Vivien Paturel, Stéphanie Baud, Christophe Schneider and Sylvie Brassart-Pasco
Pharmaceuticals 2025, 18(7), 940; https://doi.org/10.3390/ph18070940 - 21 Jun 2025
Viewed by 437
Abstract
Background/Objectives: Tetrastatin, the globular non collagenous (NC1) domain of the α4 chain of collagen IV, was previously demonstrated to inhibit melanoma progression. We identified the minimal active sequence (QKISRCQVCVKYS: QS-13) that reproduced the anti-tumor effects of whole Tetrastatin and demonstrated its anti-angiogenic [...] Read more.
Background/Objectives: Tetrastatin, the globular non collagenous (NC1) domain of the α4 chain of collagen IV, was previously demonstrated to inhibit melanoma progression. We identified the minimal active sequence (QKISRCQVCVKYS: QS-13) that reproduced the anti-tumor effects of whole Tetrastatin and demonstrated its anti-angiogenic activity mediated through αvβ3 and α5β1 binding. As QS-13 peptide was not fully soluble in aqueous solution, we designed new peptides with better water solubility. The present work aimed to investigate the interactions of ten QS-13-derived peptides, exhibiting improved hydro-solubility, with αvβ3 and α5β1 integrins. Methods: Using bioinformatics tools such as GROMACS, VMD, and the Autodock4 suite, we investigated the ability of the substituted peptides to bind αvβ3 and α5β1 integrins in silico. Results: We demonstrated in silico that all substituted peptides were able to bind both integrins at the RGD-binding site and determined their theoretical binding energy. Conclusions: The new soluble peptides should be able to compete with natural integrin ligands such as fibronectin, but also FGF1, FGF2, IGF1, and IGF2. Taken together, these findings suggest that the QS-13-derived peptides are reliable anti-angiogenic and anti-tumor agents. Full article
(This article belongs to the Special Issue Computational Predictions of Molecules with Potential Therapeutic Effects)
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18 pages, 1994 KiB  
Article
Prognostic Modeling of Deleterious IDUA Mutations L238Q and P385R in Hurler Syndrome Through Molecular Dynamics Simulations
by Madhana Priya Nanda Kumar, Esakki Dharsini Selvamani, Archana Pai Panemangalore, Sidharth Kumar Nanda Kumar, Vasundra Vasudevan and Magesh Ramasamy
Pharmaceuticals 2025, 18(6), 922; https://doi.org/10.3390/ph18060922 - 19 Jun 2025
Viewed by 536
Abstract
MPS I (Mucopolysaccharidosis type I) is a rare lysosomal storage disease originating from the deficiency of the enzyme alpha-L-iduronidase, encoded by the IDUA gene, which impairs the degradation of glycosaminoglycans (GAGs) and diminishes biological functioning across several organs. Background: Out of the eleven [...] Read more.
MPS I (Mucopolysaccharidosis type I) is a rare lysosomal storage disease originating from the deficiency of the enzyme alpha-L-iduronidase, encoded by the IDUA gene, which impairs the degradation of glycosaminoglycans (GAGs) and diminishes biological functioning across several organs. Background: Out of the eleven MPS disorders, MPS I includes three syndromes, of which the first, named Hurler syndrome, affects the most. Methods: Several in silico tools were used, such as ConSurf (73 variants), Mutation Assessor (69 variants), PredictSNP, MAPP, PhDSNP, Polyphen-1, Polyphen-2, SIFT, SNAP, PANTHER, MetaSNP (24 variants); Missense 3D-DB (11 variants) and AlignGVGD (eight variants) for physicochemical properties; and I-Mutant, Mupro, CUPSAT, and INPS for stability predictions (four variants). Results: A molecular docking study was performed for the two variants: L238Q and P385R scored −7.22 and −7.05 kcal/mol, respectively, and the native scored −7.14 kcal/mol with IDR as the ligand. Molecular dynamics anticipated how these molecules fluctuate over a period of 100 nanoseconds. Conclusions: Alpha-L-iduronidase enzyme has a critical role in the lysosomal degradation of glycosaminoglycans. According to the comparative analysis of the three structures by MDS, P385R had the least stability in all aspects of the plots. Our study demonstrates that the mutation significantly alters protein stability and binding efficiency with the ligands. Full article
(This article belongs to the Special Issue Computational Predictions of Molecules with Potential Therapeutic Effects)
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28 pages, 2420 KiB  
Article
Identification of Inhibitors with Potential Anti-Prostate Cancer Activity: A Chemoinformatics Approach
by Norberto S. Costa, Lúcio R. Lima, Jorddy N. Cruz, Igor V. F. Santos, Rai C. Silva, Alexandre A. Maciel, Elcimar S. Barros, Maracy L. D. S. Andrade, Ryan S. Ramos, Njogu M. Kimani, Alberto Aragón-Muriel, Juan M. Álvarez-Caballero, Joaquín M. Campos and Cleydson B. R. Santos
Pharmaceuticals 2025, 18(6), 888; https://doi.org/10.3390/ph18060888 - 13 Jun 2025
Viewed by 1756
Abstract
Background: Prostate cancer is the most common cancer in men, especially after the age of 50. It is a malignant disease that is increasing due to the increased life expectancy of the world population. Its development and progression are dependent on androgenic stimulation. [...] Read more.
Background: Prostate cancer is the most common cancer in men, especially after the age of 50. It is a malignant disease that is increasing due to the increased life expectancy of the world population. Its development and progression are dependent on androgenic stimulation. Objectives: This study aimed to identify potential inhibitors with anti-prostate cancer activity through the application of chemoinformatics tools, exploring the Princeton (~1.2 million compounds) and Zinc Drug (~175 million compounds) databases. Methods: The methodology used several computational techniques, such as ROCS (Rapid Chemical Structure Superposition) and EON (Electrostatic Potential Screening), predictions of pharmacokinetic and toxicological properties, molecular docking, synthetic accessibility, biological activity, and molecular dynamics. Results: At the end of all these virtual screening steps, the study resulted in four promising potential candidates for the treatment of prostate cancer: the molecules ZINC34176694, ZINC03876158, ZINC04097308, and ZINC03977981, which exhibited all the desirable pharmacokinetic parameters (ADME/Tox) for a potential drug. Conclusions: Docking and molecular dynamics studies demonstrate stability and interaction with the androgen receptor of the selected compounds, showing them to be promising candidates for the development of new drugs. Full article
(This article belongs to the Special Issue Computational Predictions of Molecules with Potential Therapeutic Effects)
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27 pages, 12620 KiB  
Article
Insights into the Therapeutic Targets and Molecular Mechanisms of Eruca sativa Against Colorectal Cancer: An Integrated Approach Combining Network Pharmacology, Molecular Docking and Dynamics Simulation
by Humera Banu, Eyad Al-Shammari, Syed Shahanawaz, Faizul Azam, Mitesh Patel, Naif Abdulrahman Alarifi, Md Faruque Ahmad, Mohd Adnan and Syed Amir Ashraf
Pharmaceuticals 2025, 18(4), 453; https://doi.org/10.3390/ph18040453 - 24 Mar 2025
Cited by 1 | Viewed by 1289
Abstract
Background/Objectives: This study presents a novel and comprehensive investigation into the anti-colorectal cancer (CRC) effects and underlying mechanisms of Eruca sativa (E. sativa) using an integrated approach combining network pharmacology, molecular docking and molecular dynamics simulation. Methods: Using an integrated approach, [...] Read more.
Background/Objectives: This study presents a novel and comprehensive investigation into the anti-colorectal cancer (CRC) effects and underlying mechanisms of Eruca sativa (E. sativa) using an integrated approach combining network pharmacology, molecular docking and molecular dynamics simulation. Methods: Using an integrated approach, six bioactive compounds and 40 potential targets were identified. A compound–target network was constructed, and enrichment analysis was performed to explore the key pathways influenced by E. sativa. Molecular docking analysis was used to evaluate the binding interactions between the identified compounds and key CRC-related targets (AKT1, PGR, MMP9, and PTGS2). Furthermore, molecular dynamics simulation was utilized to confirm the stability and reliability of these interactions. Results: The study found that E. sativa exhibits strong anticancer potential, particularly through major compounds such as β-ionone, 1-octanol, isorhamnetin, 2-hexenal, propionic acid, and quercetin. Molecular docking revealed favorable binding interactions between these compounds and key CRC targets, with quercetin and isorhamnetin showing the highest binding affinities. Additionally, molecular dynamics simulations validated the stability of these interactions, reinforcing their therapeutic relevance. Conclusions: This study provides valuable insights into the pharmacological mechanisms of E. sativa against CRC, highlighting its potential as a natural anticancer agent. These findings pave the way for future clinical studies to validate the efficacy and safety of E. sativa and its bioactive compounds, potentially contributing to the development of novel, plant-based therapeutic strategies for CRC treatment. Full article
(This article belongs to the Special Issue Computational Predictions of Molecules with Potential Therapeutic Effects)
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24 pages, 7028 KiB  
Article
Natural Product Identification and Molecular Docking Studies of Leishmania Major Pteridine Reductase Inhibitors
by Moses N. Arthur, George Hanson, Emmanuel Broni, Patrick O. Sakyi, Henrietta Mensah-Brown, Whelton A. Miller III and Samuel K. Kwofie
Pharmaceuticals 2025, 18(1), 6; https://doi.org/10.3390/ph18010006 - 24 Dec 2024
Cited by 2 | Viewed by 2080
Abstract
Background/Objectives: Pteridine reductase 1 (PTR1) has been one of the prime targets for discovering novel antileishmanial therapeutics in the fight against Leishmaniasis. This enzyme catalyzes the NADPH-dependent reduction of pterins to their tetrahydro forms. While chemotherapy remains the primary treatment, its effectiveness [...] Read more.
Background/Objectives: Pteridine reductase 1 (PTR1) has been one of the prime targets for discovering novel antileishmanial therapeutics in the fight against Leishmaniasis. This enzyme catalyzes the NADPH-dependent reduction of pterins to their tetrahydro forms. While chemotherapy remains the primary treatment, its effectiveness is constrained by drug resistance, unfavorable side effects, and substantial associated costs. Methods: This study addresses the urgent need for novel, cost-effective drugs by employing in silico techniques to identify potential lead compounds targeting the PTR1 enzyme. A library of 1463 natural compounds from AfroDb and NANPDB, prefiltered based on Lipinski’s rules, was used to screen against the LmPTR1 target. The X-ray structure of LmPTR1 complexed with NADP and dihydrobiopterin (Protein Data Bank ID: 1E92) was identified to contain the critical residues Arg17, Leu18, Ser111, Phe113, Pro224, Gly225, Ser227, Leu229, and Val230 including the triad of residues Asp181-Tyr194-Lys198, which are critical for the catalytic process involving the reduction of dihydrofolate to tetrahydrofolate. Results: The docking yielded 155 compounds meeting the stringent criteria of −8.9 kcal/mol instead of the widely used −7.0 kcal/mol. These compounds demonstrated binding affinities comparable to the known inhibitors; methotrexate (−9.5 kcal/mol), jatrorrhizine (−9.0 kcal/mol), pyrimethamine (−7.3 kcal/mol), hardwickiic acid (−8.1 kcal/mol), and columbamine (−8.6 kcal/mol). Protein–ligand interactions and molecular dynamics (MD) simulation revealed favorable hydrophobic and hydrogen bonding with critical residues, such as Lys198, Arg17, Ser111, Tyr194, Asp181, and Gly225. Crucial to the drug development, the compounds were physiochemically and pharmacologically profiled, narrowing the selection to eight compounds, excluding those with potential toxicities. The five selected compounds ZINC000095486253, ZINC000095486221, ZINC000095486249, 8alpha-hydroxy-13-epi-pimar-16-en-6,18-olide, and pachycladin D were predicted to be antiprotozoal (Leishmania) with Pa values of 0.642, 0.297, 0.543, 0.431, and 0.350, respectively. Conclusions: This study identified five lead compounds that showed substantial binding affinity against LmPTR1 as well as critical residue interactions. A 100 ns MD combined with molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) calculations confirmed the robust binding interactions and provided insights into the dynamics and stability of the protein–ligand complexes. Full article
(This article belongs to the Special Issue Computational Predictions of Molecules with Potential Therapeutic Effects)
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20 pages, 9396 KiB  
Article
Synthesis, Characterizations, Anti-Diabetic and Molecular Modeling Approaches of Hybrid Indole-Oxadiazole Linked Thiazolidinone Derivatives
by Shoaib Khan, Tayyiaba Iqbal, Rafaqat Hussain, Yousaf Khan, Zanib Fiaz, Fazal Rahim and Hany W. Darwish
Pharmaceuticals 2024, 17(11), 1428; https://doi.org/10.3390/ph17111428 - 24 Oct 2024
Cited by 3 | Viewed by 2098
Abstract
Objective: To synthesize hybrid compounds of indole and oxadiazole in search of highly effective anti-diabetic therapeutic agent. Methods: With the goal of advancing diabetes research, our group designed and synthesized a library of 15 compounds based on indole-derived oxadiazole bearing varied substituted thiazolidinone [...] Read more.
Objective: To synthesize hybrid compounds of indole and oxadiazole in search of highly effective anti-diabetic therapeutic agent. Methods: With the goal of advancing diabetes research, our group designed and synthesized a library of 15 compounds based on indole-derived oxadiazole bearing varied substituted thiazolidinone via a multistep synthetic route. 13C-NMR, 1H-NMR and HREI-MS were applied for the characterization of all the synthesized compounds. Their biological inhibitory activity against diabetic enzymes, i.e., α-amylase and α-glucosidase was also determined. Results: Compound 7, 9 and 15 exhibited excellent inhibition against α-amylase and α-glucosidase than the standard acarbose (IC50 = 8.50 ± 0.10 µM for α-amylase and 9.30 ± 0.30 µM for α-glucosidase. To ensure the inhibitory actions of these potent analogs in molecular docking, an in silico approach was used. To determine the drug likeness of the reported analogs, an ADMET investigation was also carried out to explore the nature of the designed compounds if used as a drug. Conclusion: Fluoro-substituted analog 15 has stronger inhibition profile against both enzymes. All the potent compounds can be used as effective anti-diabetic therapeutic agents in future. Full article
(This article belongs to the Special Issue Computational Predictions of Molecules with Potential Therapeutic Effects)
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