Structure-Guided Antiviral Discovery: From Target Validation to Drug Design to Candidate Selection

A special issue of Viruses (ISSN 1999-4915). This special issue belongs to the section "Viral Immunology, Vaccines, and Antivirals".

Deadline for manuscript submissions: closed (31 May 2024) | Viewed by 2143

Special Issue Editor


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Guest Editor
Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
Interests: design and discovery of novel agents; binding site identification for proteins; epitope identification; drug delivery

Special Issue Information

Dear Colleagues,

In this era of data-driven drug discovery, structure-based computational approaches are increasingly employed to advance drug discovery, from target selection and validation, to drug design and optimization, to candidate selection. The number of drug targets for which structural data are available has proliferated due to advances in cryo-electron microscopy, as well as recent breakthroughs in the application of artificial intelligence (AI) in the prediction of structures from sequences. These structural insights have been critical for previously difficult targets, including many of those relevant to antiviral discovery. This Special Issue will highlight the utilization of structural data and the application and development of structure-guided approaches for the design of antiviral drugs. Articles that describe advances in structure determination related to viral pathogens, applications of novel structure-guided computational approaches that elucidate the mechanism of viral pathogenesis relevant to drug discovery, validate target selection, or accelerate antiviral design, and those that highlight case studies involving the use of structural data for antiviral discovery are within the scope of this Special Issue. In particular, the computational drug discovery technologies employed may include, but are not limited to, hot spot mapping, molecular docking, molecular dynamics, free energy perturbation, and artificial intelligence/machine learning approaches that utilize structural inputs or integrate a range of structural data.

We welcome submissions of cutting-edge primary research and reviews.

Prof. Dr. Diane Joseph-McCarthy
Guest Editor

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Published Papers (2 papers)

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Research

31 pages, 29387 KiB  
Article
The Chameleon Strategy—A Recipe for Effective Ligand Screening for Viral Targets Based on Four Novel Structure–Binding Strength Indices
by Magdalena Latosińska and Jolanta Natalia Latosińska
Viruses 2024, 16(7), 1073; https://doi.org/10.3390/v16071073 - 3 Jul 2024
Cited by 1 | Viewed by 560
Abstract
The RNA viruses SARS-CoV, SARS-CoV-2 and MERS-CoV encode the non-structural Nsp16 (2′-O-methyltransferase) that catalyzes the transfer of a methyl group from S-adenosylmethionine (SAM) to the first ribonucleotide in mRNA. Recently, it has been found that breaking the bond between Nsp16 and SAM substrate [...] Read more.
The RNA viruses SARS-CoV, SARS-CoV-2 and MERS-CoV encode the non-structural Nsp16 (2′-O-methyltransferase) that catalyzes the transfer of a methyl group from S-adenosylmethionine (SAM) to the first ribonucleotide in mRNA. Recently, it has been found that breaking the bond between Nsp16 and SAM substrate results in the cessation of mRNA virus replication. To date, only a limited number of such inhibitors have been identified, which can be attributed to a lack of an effective “recipe”. The aim of our study was to propose and verify a rapid and effective screening protocol dedicated to such purposes. We proposed four new indices describing structure-binding strength (structure–binding affinity, structure–hydrogen bonding, structure–steric and structure–protein–ligand indices) were then applied and shown to be extremely helpful in determining the degree of increase or decrease in binding affinity in response to a relatively small change in the ligand structure. After initial pre-selection, based on similarity to SAM, we limited the study to 967 compounds, so-called molecular chameleons. They were then docked in the Nsp16 protein pocket, and 10 candidate ligands were selected using the novel structure-binding affinity index. Subsequently the selected 10 candidate ligands and 8 known inhibitors and were docked to Nsp16 pockets from SARS-CoV-2, MERS-CoV and SARS-CoV. Based on the four new indices, the best ligands were selected and a new one was designed by tuning them. Finally, ADMET profiling and molecular dynamics simulations were performed for the best ligands. The new structure-binding strength indices can be successfully applied not only to screen and tune ligands, but also to determine the effectiveness of the ligand in response to changes in the target viral entity, which is particularly useful for assessing drug effectiveness in the case of alterations in viral proteins. The developed approach, the so-called chameleon strategy, has the capacity to introduce a novel universal paradigm to the field of drugs design, including RNA antivirals. Full article
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17 pages, 4334 KiB  
Article
Elucidating the Molecular Determinants of the Binding Modes of a Third-Generation HIV-1 Integrase Strand Transfer Inhibitor: The Importance of Side Chain and Solvent Reorganization
by Qinfang Sun, Avik Biswas, Dmitry Lyumkis, Ronald Levy and Nanjie Deng
Viruses 2024, 16(1), 76; https://doi.org/10.3390/v16010076 - 2 Jan 2024
Cited by 1 | Viewed by 1243
Abstract
The first- and second-generation clinically used HIV-1 integrase (IN) strand transfer inhibitors (INSTIs) are key components of antiretroviral therapy (ART), which work by blocking the integration step in the HIV-1 replication cycle that is catalyzed by a nucleoprotein assembly called an intasome. However, [...] Read more.
The first- and second-generation clinically used HIV-1 integrase (IN) strand transfer inhibitors (INSTIs) are key components of antiretroviral therapy (ART), which work by blocking the integration step in the HIV-1 replication cycle that is catalyzed by a nucleoprotein assembly called an intasome. However, resistance to even the latest clinically used INSTIs is beginning to emerge. Developmental third-generation INSTIs, based on naphthyridine scaffolds, are promising candidates to combat drug-resistant viral variants. Among these novel INSTIs, compound 4f exhibits two distinct conformations when binding with intasomes from HIV-1 and the closely related prototype foamy virus (PFV) despite the high structural similarity of their INSTI binding pockets. The molecular mechanism and the key active site residues responsible for these differing binding modes in closely related intasomes remain elusive. To unravel the molecular determinants governing the two distinct binding modes, we applied a novel molecular dynamics-based free energy method that utilizes alchemical pathways to overcome the sampling challenges associated with transitioning between the two bound conformations of ligand 4f within the crowded environments of the INSTI binding pockets in these intasomes. The calculated conformational free energies successfully recapitulate the experimentally observed binding mode preferences in the two viral intasomes. Analysis of the simulated structures suggests that the observed binding mode preferences are caused by amino acid residue differences in both the front and the central catalytic sub-pocket of the INSTI binding site in HIV-1 and PFV. Additional free energy calculations on mutants of HIV-1 and PFV revealed that while both sub-pockets contribute to binding mode selection, the central sub-pocket plays a more important role. These results highlight the importance of both side chain and solvent reorganization, as well as the conformational entropy in determining the ligand binding mode, and will help inform the development of more effective INSTIs for combatting drug-resistant viral variants. Full article
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