Computer-Aided Molecular Modeling and Simulation in Drug Design

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

Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 3103

Special Issue Editors


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Guest Editor
Laboratório de Planejamento e Desenvolvimento de Fármacos, Instituto de Ciências Exatas e Naturais, Federal University of Pará, Belém 66075-110, Brazil
Interests: molecular modeling; drug design; computational enzymology; binding free energy methods

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Guest Editor
School of Chemistry, University of KwaZulu-Natal, Durban 4001, South Africa
Interests: chiral catalysis; cage chemistry; pharmaceutical applications of cage compounds
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Special Issue Information

Dear Colleagues,

Computer-aided molecular modeling and simulation has become an essential tool in drug design, allowing researchers to study and understand molecular interactions between a drug candidate and its target. This field combines principles from computational chemistry, bioinformatics, and biophysics to simulate and visualize the behavior of molecules at the atomic level.

Many computational methods are also used to predict the toxicity and pharmacokinetic properties of drug candidates. For example, QSAR (quantitative structure–activity relationship) models can be used to predict the activity of a drug candidate based on its chemical structure, while ADME (absorption, distribution, metabolism, and excretion) models can predict how the drug candidate will behave in a person’s body.

Overall, computer-aided molecular modeling and simulation techniques are important tools in modern drug design, allowing researchers to identify potential drug candidates more efficiently and accurately than traditional experimental methods can.

In this Special Issue, we aim to draw together research from experts in the field that highlight traditional and new computational methods and strategies to discover and design new drugs for clinical treatments.

Dr. José Rogério A. Silva
Prof. Dr. Gert Gert Kruger
Guest Editors

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Keywords

  • computer-aided drug design
  • QSAR
  • ADMET
  • molecular docking
  • molecular dynamics
  • free energy

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Published Papers (2 papers)

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Research

38 pages, 24395 KiB  
Article
Computational Exploration of Potential Pharmacological Inhibitors Targeting the Envelope Protein of the Kyasanur Forest Disease Virus
by Sharanappa Achappa, Nayef Abdulaziz Aldabaan, Shivalingsarj V. Desai, Uday M. Muddapur, Ibrahim Ahmed Shaikh, Mater H. Mahnashi, Abdullateef A. Alshehri, Basheerahmed Abdulaziz Mannasaheb and Aejaz Abdullatif Khan
Pharmaceuticals 2024, 17(7), 884; https://doi.org/10.3390/ph17070884 - 3 Jul 2024
Viewed by 970
Abstract
The limitations of the current vaccination strategy for the Kyasanur Forest Disease virus (KFDV) underscore the critical need for effective antiviral treatments, highlighting the crucial importance of exploring novel therapeutic approaches through in silico drug design. Kyasanur Forest Disease, caused by KFDV, is [...] Read more.
The limitations of the current vaccination strategy for the Kyasanur Forest Disease virus (KFDV) underscore the critical need for effective antiviral treatments, highlighting the crucial importance of exploring novel therapeutic approaches through in silico drug design. Kyasanur Forest Disease, caused by KFDV, is a tick-borne disease with a mortality of 3–5% and an annual incidence of 400 to 500 cases. In the early stage of infection, the envelope protein plays a crucial role by facilitating host–virus interactions. The objective of this research is to develop effective antivirals targeting the envelope protein to disrupt the virus–host interaction. In line with this, the 3D structure of the envelope protein was modeled and refined through molecular modeling techniques, and subsequently, ligands were designed via de novo design and pharmacophore screening, yielding 12 potential hits followed by ADMET analysis. The top five candidates underwent geometry optimization and molecular docking. Notably, compounds L4 (SA28) and L3 (CNP0247967) are predicted to have significant binding affinities of −8.91 and −7.58 kcal/mol, respectively, toward the envelope protein, based on computational models. Both compounds demonstrated stability during 200 ns molecular dynamics simulations, and the MM-GBSA binding free-energy values were −85.26 ± 4.63 kcal/mol and −66.60 ± 2.92 kcal/mol for the envelope protein L3 and L4 complexes, respectively. Based on the computational prediction, it is suggested that both compounds have potential as drug candidates for controlling host–virus interactions by targeting the envelope protein. Further validation through in-vitro assays would complement the findings of the present in silico investigations. Full article
(This article belongs to the Special Issue Computer-Aided Molecular Modeling and Simulation in Drug Design)
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18 pages, 7105 KiB  
Article
In-Silico Mining of the Toxins Database (T3DB) towards Hunting Prospective Candidates as ABCB1 Inhibitors: Integrated Molecular Docking and Lipid Bilayer-Enhanced Molecular Dynamics Study
by Mahmoud A. A. Ibrahim, Khlood A. A. Abdeljawaad, Alaa H. M. Abdelrahman, Peter A. Sidhom, Ahmed M. Tawfeek, Gamal A. H. Mekhemer, Mohamed K. Abd El-Rahman, Eslam Dabbish and Tamer Shoeib
Pharmaceuticals 2023, 16(7), 1019; https://doi.org/10.3390/ph16071019 - 18 Jul 2023
Cited by 3 | Viewed by 1494
Abstract
Multidrug resistance (MDR) is one of the most problematic issues in chemotherapeutic carcinoma therapy. The ABCB1 transporter, a drug efflux pump overexpressed in cancer cells, has been thoroughly investigated for its association with MDR. Thus, discovering ABCB1 inhibitors can reverse the MDR in [...] Read more.
Multidrug resistance (MDR) is one of the most problematic issues in chemotherapeutic carcinoma therapy. The ABCB1 transporter, a drug efflux pump overexpressed in cancer cells, has been thoroughly investigated for its association with MDR. Thus, discovering ABCB1 inhibitors can reverse the MDR in cancer cells. In the current work, a molecular docking technique was utilized for hunting the most prospective ABCB1 inhibitors from the Toxin and Toxin-Target Database (T3DB). Based on the docking computations, the most promising T3DB compounds complexed with the ABCB1 transporter were subjected to molecular dynamics (MD) simulations over 100 ns. Utilizing the MM-GBSA approach, the corresponding binding affinities were computed. Compared to ZQU (calc. −49.8 kcal/mol), Emamectin B1a (T3D1043), Emamectin B1b (T3D1044), Vincristine (T3D4016), Vinblastine (T3D4017), and Vindesine (T3D2479) complexed with ABCB1 transporter demonstrated outstanding binding affinities with ΔGbinding values of −93.0, −92.6, −93.8, −92.2, and −90.8 kcal/mol, respectively. The structural and energetic investigations confirmed the constancy of the identified T3DB compounds complexed with the ABCB1 transporter during the 100 ns MD course. To mimic the physiological conditions, MD simulations were conducted for those identified inhibitors complexed with ABCB1 transporter in the presence of a POPC membrane. These findings revealed that Emamectin B1a, Emamectin B1b, Vincristine, Vinblastine, and Vindesine are promising ABCB1 inhibitors that can reverse the MDR. Therefore, subjecting those compounds to further in-vitro and in-vivo investigations is worthwhile. Full article
(This article belongs to the Special Issue Computer-Aided Molecular Modeling and Simulation in Drug Design)
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