Quantum mechanical analysis of newly synthesized HIV-1 protease inhibitors: evaluation of wild-type and resistant strain binding interactions.

Inhibition of HIV-1 protease is a cornerstone of antiretroviral therapy. However, the notorious ability of HIV-1 to develop resistance to protease inhibitors (PIs), particularly darunavir (DRV), poses a major challenge. Using quantum chemistry and computer simulations, this study aims to investigate the interactions between two novel PIs, GRL-004 and GRL-063, as well as a wild-type (WT) HIV strain and a DRV-resistant mutant strain. To do this, we used molecular docking, molecular dynamics simulations, and quantum mechanical calculations to check how well GRL-004 and GRL-063 bound to both WT and DRV-resistant proteases. The results show that GRL-004 and GRL-063 bind very well to ASP29 in the WT strain. ASP29 is an important amino acid in the HIV protease dimer. Remarkably, amino acids such as ILE50 in the WT strains showed substantial binding energies to both drugs. Quantum energy calculations showed a slight reduction in the energy affinity of the interaction between the MUT strain and the ligand GRL-063, compared to the WT strain. GRL-004 showed similar interaction energy for both strains, suggesting that it has greater plasticity than GRL-063 despite its lower interaction affinity. Furthermore, GLY49B demonstrated strong binding energies regardless of mutations. Other relevant residues with strong binding energies include GLY49B, PHE82A, PRO81A, ASP29A, ASP25A and ALA28B. This study improves our understanding of receptor-ligand dynamics and the adaptability of new protease inhibitors (PIs), which has profound implications for the innovation of future antiretroviral drugs.

In Silico Comparative Analysis of Ivermectin and Nirmatrelvir Inhibitors Interacting with the SARS-CoV-2 Main Protease.

Exploring therapeutic options is crucial in the ongoing COVID-19 pandemic caused by SARS-CoV-2. Nirmatrelvir, which is a potent inhibitor that targets the SARS-CoV-2 Mpro, shows promise as an antiviral treatment. Additionally, Ivermectin, which is a broad-spectrum antiparasitic drug, has demonstrated effectiveness against the virus in laboratory settings. However, its clinical implications are still debated. Using computational methods, such as molecular docking and 100 ns molecular dynamics simulations, we investigated how Nirmatrelvir and Ivermectin interacted with SARS-CoV-2 Mpro(A). Calculations using density functional theory were instrumental in elucidating the behavior of isolated molecules, primarily by analyzing the frontier molecular orbitals. Our analysis revealed distinct binding patterns: Nirmatrelvir formed strong interactions with amino acids, like MET49, MET165, HIS41, HIS163, HIS164, PHE140, CYS145, GLU166, and ASN142, showing stable binding, with a root-mean-square deviation (RMSD) of around 2.0 Å. On the other hand, Ivermectin interacted with THR237, THR239, LEU271, LEU272, and LEU287, displaying an RMSD of 1.87 Å, indicating enduring interactions. Both ligands stabilized Mpro(A), with Ivermectin showing stability and persistent interactions despite forming fewer hydrogen bonds. These findings offer detailed insights into how Nirmatrelvir and Ivermectin bind to the SARS-CoV-2 main protease, providing valuable information for potential therapeutic strategies against COVID-19.

Antiviral Activity and Molecular Dynamics Simulation of Hops Compounds against Oropouche Virus (Peribunyaviridae).

The Oropouche virus (OROV) is a member of the family Peribunyaviridae (order Bunyavirales) and the cause of a dengue-like febrile illness transmitted mainly by biting midges and mosquitoes. In this study, we aimed to explore acylphloroglucinols and xanthohumol from hops (Humulus lupulus L.) as a promising alternative for antiviral therapies. The evaluation of the inhibitory potential of hops compounds on the viral cycle of OROV was performed through two complementary approaches. The first approach applies cell-based assay post-inoculation experiments to explore the inhibitory potential on the latest steps of the viral cycle, such as genome translation, replication, virion assembly, and virion release from the cells. The second part covers in silico methods evaluating the ability of those compounds to inhibit the activity of the endonuclease domain, which is essential for transcription, binding, and cleaving RNA. In conclusion, the beta acids showed strongest inhibitory potential in post-treatment assay (EC50 = 26.7 µg/mL). Xanthohumol had the highest affinity for OROV endonuclease followed by colupulone and cohumulone. This result contrasts with that observed for docking and MM/PBSA analysis, where cohumulone was found to have a higher affinity. Finally, among the three tested ligands, Lys92 and Arg33 exhibited the highest affinity with the protein.

Deciphering Interactions between Potential Inhibitors and the Plasmodium falciparum DHODH Enzyme: A Computational Perspective.

Malaria is a parasitic disease that, in its most severe form, can even lead to death. Insect-resistant vectors, insufficiently effective vaccines, and drugs that cannot stop parasitic infestations are making the fight against the disease increasingly difficult. It is known that the enzyme dihydroorotate dehydrogenase (DHODH) is of paramount importance for the synthesis of pyrimidine from the Plasmodium precursor, that is, for its growth and reproduction. Therefore, its blockade can lead to disruption of the parasite's life cycle in the vertebrate host. In this scenario, PfDHODH inhibitors have been considered candidates for a new therapy to stop the parasitic energy source. Given what is known, in this work, we applied molecular fractionation with conjugated caps (MFCC) in the framework of the quantum formalism of density functional theory (DFT) to evaluate the energies of the interactions between the enzyme and the different triazolopyrimidines (DSM483, DMS557, and DSM1), including a complex carrying the mutation C276F. From these results, it was possible to identify the main features of each system, focusing on the wild-type and mutant PfDHODH and examining the major amino acid residues that are part of the four complexes. Our analysis provides new information that can be used to develop new drugs that could prove to be more effective alternatives to present antimalarial drugs.

In Silico Evaluation of the Binding Energies of Androgen Receptor Agonists in Wild-Type and Mutational Models.

Anabolic androgenic steroids (AAS) are substances with androgenic and anabolic characteristics. Among the many side effects of hormone therapy with AAS, the following stand out: heart problems, adrenal gland disorders, aggressive behavior, increased risk of prostate cancer, problems related to lack of libido and impotence. Such substances vary in the relationship between androgenic activity, and the activation of the androgen receptor (AR) is of fundamental importance for the singularity of the action of each AAS. In this sense, our study evaluates the aspects that comprise the interactions of testosterone agonists (TES), dihydrotestosterone (DHT) and tetrahydrogestrinone (THG) in complex with the AR. In addition, we also evaluated the impact of ligand-receptor affinity differences in a mutation model. We apply computational techniques based on density functional theory (DFT) and use, as methodology, Molecular Fractionation with Conjugate Caps (MFCC). The energetic specificities present in the interaction between the analyzed complexes attest that the highest affinity with the AR receptor is found for AR-THG, followed by AR-DHT, AR-TES and AR-T877A-DHT, respectively. Our results also show the differences and equivalences between the different agonists, in addition to evaluating the difference between the DHT ligand in complex with the wild-type and mutant receptor, presenting the main amino acid residues that involve the interaction with the ligands. The computational methodology used proves to be an operative and sophisticated choice to help in the search for pharmacological agents for various therapies that have androgen as a target.

Investigation of protein-protein interactions and hotspot region on the NSP7-NSP8 binding site in NSP12 of SARS-CoV-2.

Background: The RNA-dependent RNA polymerase (RdRp) complex, essential in viral transcription and replication, is a key target for antiviral therapeutics. The core unit of RdRp comprises the nonstructural protein NSP12, with NSP7 and two copies of NSP8 (NSP81 and NSP82) binding to NSP12 to enhance its affinity for viral RNA and polymerase activity. Notably, the interfaces between these subunits are highly conserved, simplifying the design of molecules that can disrupt their interaction. Methods: We conducted a detailed quantum biochemical analysis to characterize the interactions within the NSP12-NSP7, NSP12-NSP81, and NSP12-NSP82 dimers. Our objective was to ascertain the contribution of individual amino acids to these protein-protein interactions, pinpointing hotspot regions crucial for complex stability. Results: The analysis revealed that the NSP12-NSP81 complex possessed the highest total interaction energy (TIE), with 14 pairs of residues demonstrating significant energetic contributions. In contrast, the NSP12-NSP7 complex exhibited substantial interactions in 8 residue pairs, while the NSP12-NSP82 complex had only one pair showing notable interaction. The study highlighted the importance of hydrogen bonds and π-alkyl interactions in maintaining these complexes. Intriguingly, introducing the RNA sequence with Remdesivir into the complex resulted in negligible alterations in both interaction energy and geometric configuration. Conclusion: Our comprehensive analysis of the RdRp complex at the protein-protein interface provides invaluable insights into interaction dynamics and energetics. These findings can guide the design of small molecules or peptide/peptidomimetic ligands to disrupt these critical interactions, offering a strategic pathway for developing effective antiviral drugs.