Evaluation of drug repositioning by molecular docking of pharmaceutical resources available in the Brazilian healthcare system against SARS-CoV-2

Investigation of substituent effects on the electronic structure and antiviral activity of favipiravir derivatives for Covid-19 treatment using DFT and molecular docking

In this study, Density-functional theory/Time-dependent density-functional theory (DFT/TDDFT) and Molecular docking method was used to investigate the effect of methyl acetate, tetrahydrofuran and cyanobenzylidene substituents on the electronic structure and antiviral activity of favipiravir for treating COVID-19. The DFT and TDDFT computations were employed using the Gaussian 09 software package. The values were calculated using the 6-311++G(d, p) basis set and the hybrid B3LYP functional method. Autodock vina software was used for simulations to better predictions and to validate the modified compounds' binding affinities and poses. Results of the study indicate that compounds 1 to 6 all displayed a planar structure, where the pyrazine ring, carboxamide, hydroxyl groups, and other substituents are all situated within the same plane. In addition, the energy gaps (Egap) of these six compounds (Cpd 1, 2, 3, 4, 5, and 6) were compared. The significant dipole moment and binding affinity achieved implies a particular orientation for binding within the target protein, signaling the anticipated strength of the binding interaction. In all six compounds, the electrophilic domain is situated in the vicinity of the amine functional group within the carboxamide compound, whereas the nucleophilic domain encompasses both the carbonyl and hydroxyl groups. The most negatively charged sites are susceptible to electrophilic interactions. In conclusion, compounds 5 and 6 exhibit a high binding affinity of the target protein, while compound 6 has a high energy gap, which could enhance its antiviral activity against the COVID-19 virus.

Repurposing of neprilysin inhibitor 'sacubitrilat' as an anti-cancer drug by modulating epigenetic and apoptotic regulators

Modifications in the epigenetic landscape have been considered a hallmark of cancer. Histone deacetylation is one of the crucial epigenetic modulations associated with the aggressive progression of various cancer subtypes. Herein, we have repurposed the neprilysin inhibitor sacubitrilat as a potent anticancer agent using in-silico protein-ligand interaction profiler (PLIP) analysis, molecular docking, and in vitro studies. The screening of PLIP profiles between vorinostat/panobinostat and HDACs/LTA4H followed by molecular docking resulted in five (Sacubitrilat, B65, BDS, BIR, and NPV) FDA-approved, experimental and investigational drugs. Sacubitrilat has demonstrated promising anticancer activity against colorectal cancer (SW-480) and triple-negative breast cancer (MDA-MB-231) cells, with IC₅₀ values of 14.07 μg/mL and 23.02 μg/mL, respectively. FACS analysis revealed that sacubitrilat arrests the cell cycle at the G0/G1 phase and induces apoptotic-mediated cell death in SW-480 cells. In addition, sacubitrilat inhibited HDAC isoforms at the transcriptomic level by 0.7-0.9 fold and at the proteomic level by 0.5-0.6 fold as compared to the control. Sacubitrilat increased the protein expression of tumor-suppressor (p53) and pro-apoptotic makers (Bax and Bid) by 0.2-2.5 fold while decreasing the expression of anti-apoptotic Bcl2 and Nrf2 proteins by 0.2-0.5 fold with respect to control. The observed cleaved PARP product indicates that sacubitrilat induces apoptotic-mediated cell death. This study may pave the way to identify the anticancer potential of sacubitrilat and can be explored in human clinical trials.

Intrinsic Dynamics of the ClpXP Proteolytic Machine Using Elastic Network Models

ClpXP complex is an ATP-dependent mitochondrial matrix protease that binds, unfolds, translocates, and subsequently degrades specific protein substrates. Its mechanisms of operation are still being debated, and several have been proposed, including the sequential translocation of two residues (SC/2R), six residues (SC/6R), and even long-pass probabilistic models. Therefore, it has been suggested to employ biophysical-computational approaches that can determine the kinetics and thermodynamics of the translocation. In this sense, and based on the apparent inconsistency between structural and functional studies, we propose to apply biophysical approaches based on elastic network models (ENM) to study the intrinsic dynamics of the theoretically most probable hydrolysis mechanism. The proposed models ENM suggest that the ClpP region is decisive for the stabilization of the ClpXP complex, contributing to the flexibility of the residues adjacent to the pore, favoring the increase in pore size and, therefore, with the energy of interaction of its residues with a larger portion of the substrate. It is predicted that the complex may undergo a stable configurational change once assembled and that the deformability of the system once assembled is oriented, to increase the rigidity of the domains of each region (ClpP and ClpX) and to gain flexibility of the pore. Our predictions could suggest under the conditions of this study the mechanism of the interaction of the system, of which the substrate passes through the unfolding of the pore in parallel with a folding of the bottleneck. The variations in the distance calculated by molecular dynamics could allow the passage of a substrate with a size equivalent to ∼3 residues. The theoretical behavior of the pore and the stability and energy of binding to the substrate based on ENM models suggest that in this system, there are thermodynamic, structural, and configurational conditions that allow a possible translocation mechanism that is not strictly sequential.

Interaction of the renin inhibitor aliskiren with the SARS-CoV-2 main protease: a molecular docking study

The renin protein is an upstream enzymatic regulator of the renin-aldosterone-angiotensin system (RAAS) essential for the maintenance of blood pressure. The angiotensin-converting enzyme-2 (ACE2) is a major component of the RAAS and a cell surface receptor exploited by the SARS-CoV-2 virus to enter host cells. A recent molecular modeling study has revealed that the direct renin peptide inhibitor remikiren can bind to the catalytic site of SARS-CoV-2 main protease (M^pro). By analogy, we postulated that the non-peptidic drug aliskiren, a more potent renin inhibitor than remikiren and a drug routinely used to treat hypertension, may also be able to interact with M^pro. An in silico comparison of the binding of the two compounds to M^pro indicates that aliskiren (ΔE = -75.9 kcal/mol) can form stable complexes with the main viral protease, binding to the active site, as remikiren (ΔE = -83.2 kcal/mol). The comparison with a panoply of 30 references compounds (mainly antiviral drugs) indicated that remikiren is a potent M^pro binder comparable to drugs like glecaprevir and pibrentasvir (ΔE = -96.5 kcal/mol). The energy of interaction (ΔE) of aliskiren with M^pro is about 10% lower than with remikiren, comparable to that calculated with drugs like velpatasvir and sofosbuvir. A model is proposed to define the drug binding site, with the best binders (including remikiren) penetrating deeply into the site, whereas the less potent binders (including aliskiren) interact more superficially with the protein.Communicated by Ramaswamy H. Sarma.

A review on computer-aided chemogenomics and drug repositioning for rational COVID-19 drug discovery

Application of materials capable of energy harvesting to increase the efficiency and environmental adaptability is sometimes reflected in the ability of discovery of some traces in an environment-either experimentally or computationally-to enlarge practical application window. The emergence of computational methods, particularly computer-aided drug discovery (CADD), provides ample opportunities for the rapid discovery and development of unprecedented drugs. The expensive and time-consuming process of traditional drug discovery is no longer feasible, for nowadays the identification of potential drug candidates is much easier for therapeutic targets through elaborate in silico approaches, allowing the prediction of the toxicity of drugs, such as drug repositioning (DR) and chemical genomics (chemogenomics). Coronaviruses (CoVs) are cross-species viruses that are able to spread expeditiously from the into new host species, which in turn cause epidemic diseases. In this sense, this review furnishes an outline of computational strategies and their applications in drug discovery. A special focus is placed on chemogenomics and DR as unique and emerging system-based disciplines on CoV drug and target discovery to model protein networks against a library of compounds. Furthermore, to demonstrate the special advantages of CADD methods in rapidly finding a drug for this deadly virus, numerous examples of the recent achievements grounded on molecular docking, chemogenomics, and DR are reported, analyzed, and interpreted in detail. It is believed that the outcome of this review assists developers of energy harvesting materials and systems for detection of future unexpected kinds of CoVs or other variants.

Virtual screening of substances used in the treatment of SARS-CoV-2 infection and analysis of compounds with known action on structurally similar proteins from other viruses

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is considered the etiological agent of the disease that caused the COVID-19 pandemic, and for which there is currently no effective treatment. This pandemic has shown that the rapid identification of therapeutic compounds is critical (when a new virus with high transmissibility occurs) to prevent or reduce as much as possible the loss of human lives. To meet the urgent need for drugs, many strategies were applied for the discovery, respectively the identification of potential therapies / drugs for SARS-CoV-2. Molecular docking and virtual screening are two of the in silico tools/techniques that provided the identification of few SARS-CoV-2 inhibitors, removing ineffective or less effective drugs and thus preventing the loss of resources such as time and additional costs. The main target of this review is to provide a comprehensive overview of how in-silico tools have been used in the crisis management of anti-SARS-CoV-2 drugs, especially in virtual screening of substances used in the treatment of SARS-CoV-2 infection and analysis of compounds with known action on structurally similar proteins from other viruses; also, completions were added to the way in which these methods came to meet the requirements of biomedical research in the field. Moreover, the importance and impact of the topic approached for researchers was highlighted by conducting an extensive bibliometric analysis.

Screening of SARS-CoV-2 antivirals through a cell-based RNA-dependent RNA polymerase (RdRp) reporter assay

COVID-19 (Coronavirus Disease 2019) caused by SARS-CoV-2 (Severe Acute Respiratory Syndrome CoronaVirus-2) continues to pose an international public health threat and thus far, has resulted in greater than 6.4 million deaths worldwide. Vaccines are critical tools to limit COVID-19 spread, but antiviral drug development is an ongoing global priority due to fast-spreading COVID-19 variants that may elude vaccine efficacies. The RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 is an essential enzyme of viral replication and transcription machinery complex. Therefore, the RdRp is an attractive target for the development of effective anti-COVID-19 therapeutics. In this study, we developed a cell-based assay to determine the enzymatic activity of SARS-CoV-2 RdRp through a luciferase reporter system. The SARS-CoV-2 RdRp reporter assay was validated using known inhibitors of RdRp polymerase, remdesivir along with other anti-virals including ribavirin, penciclovir, rhoifolin, 5′CT, and dasabuvir. Dasabuvir (an FDA-approved drug) exhibited promising RdRp inhibitory activity among these inhibitors. Anti-viral activity of dasabuvir was also tested on the replication of SARS-CoV-2 through infection of Vero E6 cells. Dasabuvir inhibited the replication of SARS-CoV-2, USA-WA1/2020 as well as B.1.617.2 (delta variant) in Vero E6 cells in a dose-dependent manner with EC₅₀ values 9.47 μM and 10.48 μM, for USA-WA1/2020 and B.1.617.2 variants, respectively. Our results suggest that dasabuvir can be further evaluated as a therapeutic drug for COVID-19. Importantly, this system provides a robust, target-specific, and high-throughput screening compatible (z- and z’-factors of >0.5) platforms that will be a valuable tool for screening SARS-CoV-2 RdRp inhibitors.

Interaction of the new inhibitor paxlovid (PF-07321332) and ivermectin with the monomer of the main protease SARS-CoV-2: A volumetric study based on molecular dynamics, elastic networks, classical thermodynamics and SPT

The COVID-19 pandemic has accelerated the study of drugs, most notably ivermectin and more recently Paxlovid (PF-07321332) which is in phase III clinical trials with experimental data showing covalent binding to the viral protease Mpro. Theoretical developments of catalytic site-directed docking support thermodynamically feasible non-covalent binding to Mpro. Here we show that Paxlovid binds non-covalently at regions other than the catalytic sites with energies stronger than reported and at the same binding site as the ivermectin B1a homologue, all through theoretical methodologies, including blind docking. We volumetrically characterize the non-covalent interaction of the ivermectin homologues (avermectins B1a and B1b) and Paxlovid with the mMpro monomer, through molecular dynamics and scaled particle theory (SPT). Using the fluctuation-dissipation theorem (FDT), we estimated the electric dipole moment fluctuations at the surface of each of complex involved in this study, with similar trends to that observed in the interaction volume. Using fluctuations of the intrinsic volume and the number of flexible fragments of proteins using anisotropic and Gaussian elastic networks (ANM+GNM) suggests the complexes with ivermectin are more dynamic and flexible than the unbound monomer. In contrast, the binding of Paxlovid to mMpro shows that the mMpro-PF complex is the least structurally dynamic of all the species measured in this investigation. The results support a differential molecular mechanism of the ivermectin and PF homologues in the mMpro monomer. Finally, the results showed that Paxlovid despite beingbound in different sites through covalent or non-covalent forms behaves similarly in terms of its structural flexibility and volumetric behaviour.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

In Silico Studies of Tumor Targeted Peptide-Conjugated Natural Products for Targeting Over-Expressed Receptors in Breast Cancer Cells Using Molecular Docking, Molecular Dynamics and MMGBSA Calculations

In this work, in silico studies were carried out for the design of diterpene and polyphenol-peptide conjugates to potentially target over-expressed breast tumor cell receptors. Four point mutations were induced into the known tumor-targeting peptide sequence YHWYGYTPQN at positions 1, 2, 8 and 10, resulting in four mutated peptides. Each peptide was separately conjugated with either chlorogenate, carnosate, gallate, or rosmarinate given their known anti-tumor activities, creating dual targeting compounds. Molecular docking studies were conducted with the epidermal growth factor receptor (EGFR), to which the original peptide sequence is known to bind, as well as the estrogen receptor (ERα) and peroxisome proliferator-activated receptor (PPARα) using both Autodock Vina and FireDock. Based on docking results, peptide conjugates and peptides were selected and subjected to molecular dynamics simulations. MMGBSA calculations were used to further probe the binding energies. ADME studies revealed that the compounds were not CYP substrates, though most were Pgp substrates. Additionally, most of the peptides and conjugates showed MDCK permeability. Our results indicated that several of the peptide conjugates enhanced binding interactions with the receptors and resulted in stable receptor-ligand complexes; Furthermore, they may successfully target ERα and PPARα in addition to EGFR and may be further explored for synthesis and biological studies for therapeutic applications.

Computational Discovery of SARS-CoV-2 NSP 16 Drug Candidates Based on Pharmacophore Modeling and Molecular Dynamics Simulation

Non-Structural Protein 16 (NSP-16) is one of the most suitable targets for discovery of drugs for corona viruses including SARS-CoV-2. In this study, drug discovery of SARS-CoV-2 nsp-16 has been accomplished by pharmacophore-based virtual screening among some analogs (FDA approved drugs) and marine natural plants (MNP). The comparison of the binding energies and the inhibition constants was determined using molecular docking method. Three compounds including two FDA approved (Ibrutinib, Idelalisib) and one MNP (Kumusine) were selected for further investigation using the molecular dynamics simulations. The results indicated that Ibrutinib and Idelalisib are oral medications while Kumusine, with proper hydrophilic and solubility properties, is an appropriate candidate for nsp-16 inhibitor and can be effective to control COVID-19 disease.

Tenofovir, Another Inexpensive, Well-Known and Widely Available Old Drug Repurposed for SARS-COV-2 Infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is spreading worldwide with different clinical manifestations. Age and comorbidities may explain severity in critical cases and people living with human immunodeficiency virus (HIV) might be at particularly high risk for severe progression. Nonetheless, current data, although sometimes contradictory, do not confirm higher morbidity, risk of more severe COVID-19 or higher mortality in HIV-infected people with complete access to antiretroviral therapy (ART). A possible protective role of ART has been hypothesized to explain these observations. Anti-viral drugs used to treat HIV infection have been repurposed for COVID-19 treatment; this is also based on previous studies on severe acute respiratory syndrome virus (SARS-CoV) and Middle East respiratory syndrome virus (MERS-CoV). Among them, lopinavir/ritonavir, an inhibitor of viral protease, was extensively used early in the pandemic but it was soon abandoned due to lack of effectiveness in clinical trials. However, remdesivir, a nucleotide analog that acts as reverse-transcriptase inhibitor, which was tested early during the pandemic because of its wide range of antiviral activity against several RNA viruses and its safety profile, is currently the only antiviral medication approved for COVID-19. Tenofovir, another nucleotide analog used extensively for HIV treatment and pre-exposure prophylaxis (PrEP), has also been hypothesized as effective in COVID-19. No data on tenofovir's efficacy in coronavirus infections other than COVID-19 are currently available, although information relating to SARS-CoV-2 infection is starting to come out. Here, we review the currently available evidence on tenofovir's efficacy against SARS-CoV-2.