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The Research about Computer-Aided Drug Design
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The Research about Computer-Aided Drug Design

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Biophysics".

Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 21448

Special Issue Editor

Dr. Dharmendra Kumar Yadav

E-Mail Website
Guest Editor
College of Pharmacy, Gachon University of Medicine and Science, Room # 502, Hambakmoeiro 191, Yeonsu-gu, Incheon City 21924, Korea
Interests: cheminformatics; machine learning; bioinformatics; plasma medicine
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Machine learning (ML) enables modeling of quantitative structure–activity relationships (QSAR) and compound potency predictions. Recently, multi-target QSAR models have been gaining increasing attention. Simultaneous compound potency predictions for multiple targets can be carried out using ensembles of independently derived target-based QSAR models or in a more integrated and advanced manner using multi-target deep neural networks (MT-DNNs). In drug discovery, chembioinformatics (QSAR, docking, homology modeling, MD simulations, ADME/Tox) play a very significant role in aiding and expediting the same. The integration of in silico studies with the wet lab experiment (in vitro/in vivo) provides in-depth molecular target information and pharmacophore mapping, aiming to design a better drug for a target-specific action. This research topic should collect new approaches developed to overcome the main issues faced by medicinal chemists in the design, synthesis and biological evaluation of these promising but extremely challenging new chemical entities. The first issue to overcome is the identification of new multi-target-directed ligands (MTDL) derived from either natural sources or synthetic procedures. The next issue to overcome will be related to the-state-of-the-art biological, biophysical and advanced methods for chemoinformatic tools tests particularly suited to rapidly explore a multi-target profile. Contributions covering multiple topics are particularly welcome.

Dr. Dharmendra K. Yadav
Guest Editor

Manuscript Submission Information

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Keywords

  • Machine learning
  • MD simulations
  • QSAR
  • Drug discovery
  • Rational drug design
  • Multi-target paradigms
  • In silico target deconvolution
  • Multidisciplinary cooperation

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Published Papers (5 papers)

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Research

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35 pages, 8733 KiB  
Article
Design and Identification of Inhibitors for the Spike-ACE2 Target of SARS-CoV-2
by Ruan S. Bastos, Lúcio R. de Lima, Moysés F. A. Neto, Maryam, Numan Yousaf, Jorddy N. Cruz, Joaquín M. Campos, Njogu M. Kimani, Ryan S. Ramos and Cleydson B. R. Santos
Int. J. Mol. Sci. 2023, 24(10), 8814; https://doi.org/10.3390/ijms24108814 - 16 May 2023
Cited by 9 | Viewed by 2175
Abstract
When an epidemic started in the Chinese city of Wuhan in December 2019, coronavirus was identified as the cause. Infection by the virus occurs through the interaction of viral S protein with the hosts’ angiotensin-converting enzyme 2. By leveraging resources such as the [...] Read more.
When an epidemic started in the Chinese city of Wuhan in December 2019, coronavirus was identified as the cause. Infection by the virus occurs through the interaction of viral S protein with the hosts’ angiotensin-converting enzyme 2. By leveraging resources such as the DrugBank database and bioinformatics techniques, ligands with potential activity against the SARS-CoV-2 spike protein were designed and identified in this investigation. The FTMap server and the Molegro software were used to determine the active site of the Spike-ACE2 protein’s crystal structure. Virtual screening was performed using a pharmacophore model obtained from antiparasitic drugs, obtaining 2000 molecules from molport®. The ADME/Tox profiles were used to identify the most promising compounds with desirable drug characteristics. The binding affinity investigation was then conducted with selected candidates. A molecular docking study showed five structures with better binding affinity than hydroxychloroquine. Ligand_003 showed a binding affinity of −8.645 kcal·mol−1, which was considered an optimal value for the study. The values presented by ligand_033, ligand_013, ligand_044, and ligand_080 meet the profile of novel drugs. To choose compounds with favorable potential for synthesis, synthetic accessibility studies and similarity analyses were carried out. Molecular dynamics and theoretical IC50 values (ranging from 0.459 to 2.371 µM) demonstrate that these candidates are promising for further tests. Chemical descriptors showed that the candidates had strong molecule stability. Theoretical analyses here show that these molecules have potential as SARS-CoV-2 antivirals and therefore warrant further investigation. Full article
(This article belongs to the Special Issue The Research about Computer-Aided Drug Design)
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29 pages, 5042 KiB  
Article
Identification of Potential New Aedes aegypti Juvenile Hormone Inhibitors from N-Acyl Piperidine Derivatives: A Bioinformatics Approach
by Lúcio R. Lima, Ruan S. Bastos, Elenilze F. B. Ferreira, Rozires P. Leão, Pedro H. F. Araújo, Samuel S. da R. Pita, Humberto F. De Freitas, José M. Espejo-Román, Edla L. V. S. Dos Santos, Ryan da S. Ramos, Williams J. C. Macêdo and Cleydson B. R. Santos
Int. J. Mol. Sci. 2022, 23(17), 9927; https://doi.org/10.3390/ijms23179927 - 1 Sep 2022
Cited by 11 | Viewed by 2718
Abstract
Aedes aegypti mosquitoes transmit several human pathogens that cause millions of deaths worldwide, mainly in Latin America. The indiscriminate use of insecticides has resulted in the development of species resistance to some such compounds. Piperidine, a natural alkaloid isolated from Piper nigrum, [...] Read more.
Aedes aegypti mosquitoes transmit several human pathogens that cause millions of deaths worldwide, mainly in Latin America. The indiscriminate use of insecticides has resulted in the development of species resistance to some such compounds. Piperidine, a natural alkaloid isolated from Piper nigrum, has been used as a hit compound due to its larvicidal activity against Aedes aegypti. In the present study, piperidine derivatives were studied through in silico methods: pharmacophoric evaluation (PharmaGist), pharmacophoric virtual screening (Pharmit), ADME/Tox prediction (Preadmet/Derek 10.0®), docking calculations (AutoDock 4.2) and molecular dynamics (MD) simulation on GROMACS-5.1.4. MP-416 and MP-073 molecules exhibiting ΔG binding (MMPBSA −265.95 ± 1.32 kJ/mol and −124.412 ± 1.08 kJ/mol, respectively) and comparable to holo (ΔG binding = −216.21 ± 0.97) and pyriproxyfen (a well-known larvicidal, ΔG binding= −435.95 ± 2.06 kJ/mol). Considering future in vivo assays, we elaborated the theoretical synthetic route and made predictions of the synthetic accessibility (SA) (SwissADME), lipophilicity and water solubility (SwissADME) of the promising compounds identified in the present study. Our in silico results show that MP-416 and MP-073 molecules could be potent insecticides against the Aedes aegypti mosquitoes. Full article
(This article belongs to the Special Issue The Research about Computer-Aided Drug Design)
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14 pages, 5005 KiB  
Article
MAP/Microtubule Affinity Regulating Kinase 4 Inhibitory Potential of Irisin: A New Therapeutic Strategy to Combat Cancer and Alzheimer’s Disease
by Rashid Waseem, Saleha Anwar, Shama Khan, Anas Shamsi, Md. Imtaiyaz Hassan, Farah Anjum, Alaa Shafie, Asimul Islam and Dharmendra Kumar Yadav
Int. J. Mol. Sci. 2021, 22(20), 10986; https://doi.org/10.3390/ijms222010986 - 12 Oct 2021
Cited by 28 | Viewed by 2984
Abstract
Irisin is a clinically significant protein playing a valuable role in regulating various diseases. Irisin attenuates synaptic and memory dysfunction, highlighting its importance in Alzheimer’s disease. On the other hand, Microtubule Affinity Regulating Kinase 4 (MARK4) is associated with various cancer types, uncontrolled [...] Read more.
Irisin is a clinically significant protein playing a valuable role in regulating various diseases. Irisin attenuates synaptic and memory dysfunction, highlighting its importance in Alzheimer’s disease. On the other hand, Microtubule Affinity Regulating Kinase 4 (MARK4) is associated with various cancer types, uncontrolled neuronal migrations, and disrupted microtubule dynamics. In addition, MARK4 has been explored as a potential drug target for cancer and Alzheimer’s disease therapy. Here, we studied the binding and subsequent inhibition of MARK4 by irisin. Irisin binds to MARK4 with an admirable affinity (K = 0.8 × 107 M−1), subsequently inhibiting its activity (IC50 = 2.71 µm). In vitro studies were further validated by docking and simulations. Molecular docking revealed several hydrogen bonds between irisin and MARK4, including critical residues, Lys38, Val40, and Ser134. Furthermore, the molecular dynamic simulation showed that the binding of irisin resulted in enhanced stability of MARK4. This study provides a rationale to use irisin as a therapeutic agent to treat MARK4-associated diseases. Full article
(This article belongs to the Special Issue The Research about Computer-Aided Drug Design)
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Review

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16 pages, 2730 KiB  
Review
Recent Advances in Application of Computer-Aided Drug Design in Anti-Influenza A Virus Drug Discovery
by Dahai Yu, Linlin Wang and Ye Wang
Int. J. Mol. Sci. 2022, 23(9), 4738; https://doi.org/10.3390/ijms23094738 - 25 Apr 2022
Cited by 14 | Viewed by 5875
Abstract
Influenza A is an acute respiratory infectious disease caused by the influenza A virus, which seriously threatens global human health and causes substantial economic losses every year. With the emergence of new viral strains, anti-influenza drugs remain the most effective treatment for influenza [...] Read more.
Influenza A is an acute respiratory infectious disease caused by the influenza A virus, which seriously threatens global human health and causes substantial economic losses every year. With the emergence of new viral strains, anti-influenza drugs remain the most effective treatment for influenza A. Research on traditional, innovative small-molecule drugs faces many challenges, while computer-aided drug design (CADD) offers opportunities for the rapid and effective development of innovative drugs. This literature review describes the general process of CADD, the viral proteins that play an essential role in the life cycle of the influenza A virus and can be used as therapeutic targets for anti-influenza drugs, and examples of drug screening of viral target proteins by applying the CADD approach. Finally, the main limitations of current CADD strategies in anti-influenza drug discovery and the field’s future directions are discussed. Full article
(This article belongs to the Special Issue The Research about Computer-Aided Drug Design)
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18 pages, 7335 KiB  
Review
Opioid Receptors and Protonation-Coupled Binding of Opioid Drugs
by Samo Lešnik, Éva Bertalan, Urban Bren and Ana-Nicoleta Bondar
Int. J. Mol. Sci. 2021, 22(24), 13353; https://doi.org/10.3390/ijms222413353 - 12 Dec 2021
Cited by 11 | Viewed by 5189
Abstract
Opioid receptors are G-protein-coupled receptors (GPCRs) part of cell signaling paths of direct interest to treat pain. Pain may associate with inflamed tissue characterized by acidic pH. The potentially low pH at tissue targeted by opioid drugs in pain management could impact drug [...] Read more.
Opioid receptors are G-protein-coupled receptors (GPCRs) part of cell signaling paths of direct interest to treat pain. Pain may associate with inflamed tissue characterized by acidic pH. The potentially low pH at tissue targeted by opioid drugs in pain management could impact drug binding to the opioid receptor, because opioid drugs typically have a protonated amino group that contributes to receptor binding, and the functioning of GPCRs may involve protonation change. In this review, we discuss the relationship between structure, function, and dynamics of opioid receptors from the perspective of the usefulness of computational studies to evaluate protonation-coupled opioid-receptor interactions. Full article
(This article belongs to the Special Issue The Research about Computer-Aided Drug Design)
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