Conserved coronavirus proteins as targets of broad-spectrum antivirals

Coronaviruses are a class of single-stranded, positive-sense RNA viruses that have caused three major outbreaks over the past two decades: Middle East respiratory syndrome-related coronavirus (MERS-CoV), severe acute respiratory syndrome coronavirus (SARS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). All outbreaks have been associated with significant morbidity and mortality. In this study, we have identified and explored conserved binding sites in the key coronavirus proteins for the development of broad-spectrum direct acting anti-coronaviral compounds and validated the significance of this conservation for drug discovery with existing experimental data. We have identified four coronaviral proteins with highly conserved binding site sequence and 3D structure similarity: PLpro, Mpro, nsp10-nsp16 complex(methyltransferase), and nsp15 endoribonuclease. We have compiled all available experimental data for known antiviral medications inhibiting these targets and identified compounds active against multiple coronaviruses. The identified compounds representing potential broad-spectrum antivirals include: GC376, which is active against six viral Mpro (out of six tested, as described in research literature); mycophenolic acid, which is active against four viral PLpro (out of four); and emetine, which is active against four viral RdRp (out of four). The approach described in this study for coronaviruses, which combines the assessment of sequence and structure conservation across a viral family with the analysis of accessible chemical structure - antiviral activity data, can be explored for the development of broad-spectrum drugs for multiple viral families.

Simplex representation of molecular structure as universal QSAR/QSPR tool

We review the development and application of the Simplex approach for the solution of various QSAR/QSPR problems. The general concept of the simplex method and its varieties are described. The advantages of utilizing this methodology, especially for the interpretation of QSAR/QSPR models, are presented in comparison to other fragmentary methods of molecular structure representation. The utility of SiRMS is demonstrated not only in the standard QSAR/QSPR applications, but also for mixtures, polymers, materials, and other complex systems. In addition to many different types of biological activity (antiviral, antimicrobial, antitumor, psychotropic, analgesic, etc.), toxicity and bioavailability, the review examines the simulation of important properties, such as water solubility, lipophilicity, as well as luminescence, and thermodynamic properties (melting and boiling temperatures, critical parameters, etc.). This review focuses on the stereochemical description of molecules within the simplex approach and details the possibilities of universal molecular stereo-analysis and stereochemical configuration description, along with stereo-isomerization mechanism and molecular fragment "topography" identification.

Selene-Ethylenelacticamides and N-Aryl-Propanamides as Broad-Spectrum Leishmanicidal Agents

The World Health Organization classifies Leishmania as one of the 17 “neglected diseases” that burden tropical and sub-tropical climate regions with over half a million diagnosed cases each year. Despite this, currently available anti-leishmania drugs have high toxicity and the potential to be made obsolete by parasite drug resistance. We chose to analyze organoselenides for leishmanicidal potential given the reduced toxicity inherent to selenium and the displayed biological activity of organoselenides against Leishmania. Thus, the biological activities of 77 selenoesters and their N-aryl-propanamide derivatives were predicted using robust in silico models of Leishmania infantum, Leishmania amazonensis, Leishmania major, and Leishmania (Viannia) braziliensis. The models identified 28 compounds with >60% probability of demonstrating leishmanicidal activity against L. infantum, and likewise, 26 for L. amazonesis, 25 for L. braziliensis, and 23 for L. major. The in silico prediction of ADMET properties suggests high rates of oral absorption and good bioavailability for these compounds. In the in silico toxicity evaluation, only seven compounds showed signs of toxicity in up to one or two parameters. The methodology was corroborated with the ensuing experimental validation, which evaluated the inhibition of the Promastigote form of the Leishmania species under study. The activity of the molecules was determined by the IC50 value (µM); IC50 values < 20 µM indicated better inhibition profiles. Sixteen compounds were synthesized and tested for their activity. Eight molecules presented IC50 values < 20 µM for at least one of the Leishmania species under study, with compound NC34 presenting the strongest parasite inhibition profile. Furthermore, the methodology used was effective, as many of the compounds with the highest probability of activity were confirmed by the in vitro tests performed.

Secondary Metabolites Extracted from Annonaceae and Chemotaxonomy Study of Terpenoids

The Annonaceae family of plants is one of the most anatomically and structurally uniform families. Chemotaxonomy is a common practice to determine the chemical patterns within these families at different phylogenetic levels. The aim of this study was to build a dataset of all the secondary metabolites isolated within the Annonaceae family and to perform the respective chemotaxonomic analysis using self-organizing maps (SOMs). This dataset is composed of 5321 botanical occurrences and 1860 unique molecules present in all subfamilies of the Annonaceae. Diterpenes account for 366 unique compounds and 533 botanical occurrences seen in both Annonoideae and Malmeoideae subfamilies. The Annoneae, Xylopieae and Miliuseae tribes had the highest number of botanical occurrences and were therefore selected for the analysis. Molecular descriptors of the diterpenes and their respective botanical occurrences were used to generate the SOMs. These SOMs demonstrated clear and indicative tribe separations, with a match rate higher than 70%. Our results corroborate with the morphological and molecular data. These models can be used to predict the phylogenetic location of certain diterpenes and to accelerate the research of Annonaceae secondary metabolites and their biological potentials.

Natural Products as Potential Agents Against SARS-CoV and SARS-CoV-2

BACKGROUND

Natural products are useful agents for the discovery of new lead-compounds and effective drugs to combat coronaviruses (CoV).

OBJECTIVE

The present work provides an overview of natural substances, plant extracts, and essential oils as potential antiSARS-CoV agents. In addition, this work evaluates their drug-like properties which are essential in the selection of compounds in order to accelerate the drug development process.

METHODS

The search was carried out using PubMed, ScienceDirect and SciFinder. Articles addressing plant-based natural products as potential SARS-CoV or SARS-CoV-2 agents within the last seventeen years were analyzed and selected. The descriptors for Chemometrics analyzes were obtained in alvaDesc and the principal component analyzes (PCA) were carried out in SIMCA version 13.0.

RESULTS

Based on in vitro assays and computational analyzes, this review covers twenty nine medicinal plant species and more than 300 isolated substances as potential anti-coronavirus agents. Among them, flavonoids and terpenes were the most promising compound classes. In silico analyses of drug-like properties corroborate these findings and indicate promising candidates for in vitro and in vivo studies to validate their activity.

CONCLUSION

This paper highlights the role of ethnopharmacology in drug discovery and simulates the use of integrative (in silico/ in vitro) and chemocentric approaches to strengthen current studies and guide future research in the field of antivirals agents.

Allosteric binders of ACE2 are promising anti-SARS-CoV-2 agents.. [PMID: 35313579 PMCID: PMC8936107 DOI: 10.1101/2022.03.15.484484]

The COVID-19 pandemic has had enormous health, economic, and social consequences. Vaccines have been successful in reducing rates of infection and hospitalization, but there is still a need for an acute treatment for the disease. We investigate whether compounds that bind the human ACE2 protein can interrupt SARS-CoV-2 replication without damaging ACE2’s natural enzymatic function. Initial compounds were screened for binding to ACE2 but little interruption of ACE2 enzymatic activity. This set of compounds was extended by application of quantitative structure-activity analysis, which resulted in 512 virtual hits for further confirmatory screening. A subsequent SARS-CoV-2 replication assay revealed that five of these compounds inhibit SARS-CoV-2 replication in human cells. Further effort is required to completely determine the antiviral mechanism of these compounds, but they serve as a strong starting point for both development of acute treatments for COVID-19 and research into the mechanism of infection.

Abstract Figure

TOC Graphic: Overall study design.

Praemonitus praemunitus: can we forecast and prepare for future viral disease outbreaks?

Understanding the origins of past and present viral epidemics is critical in preparing for future outbreaks. Many viruses, including SARS-CoV-2, have led to significant consequences not only due to their virulence, but also because we were unprepared for their emergence. We need to learn from large amounts of data accumulated from well-studied, past pandemics and employ modern informatics and therapeutic development technologies to forecast future pandemics and help minimize their potential impacts. While acknowledging the complexity and difficulties associated with establishing reliable outbreak predictions, herein we provide a perspective on the regions of the world that are most likely to be impacted by future outbreaks. We specifically focus on viruses with epidemic potential, namely SARS-CoV-2, MERS-CoV, DENV, ZIKV, MAYV, LASV, noroviruses, influenza, Nipah virus, hantaviruses, Oropouche virus, MARV, and Ebola virus, which all require attention from both the public and scientific community to avoid societal catastrophes like COVID-19. Based on our literature review, data analysis, and outbreak simulations, we posit that these future viral epidemics are unavoidable, but that their societal impacts can be minimized by strategic investment into basic virology research, epidemiological studies of neglected viral diseases, and antiviral drug discovery.

Allosteric Binders of ACE2 Are Promising Anti-SARS-CoV-2 Agents

The COVID-19 pandemic has had enormous health, economic, and social consequences. Vaccines have been successful in reducing rates of infection and hospitalization, but there is still a need for acute treatment of the disease. We investigate whether compounds that bind the human angiotensin-converting enzyme 2 (ACE2) protein can decrease SARS-CoV-2 replication without impacting ACE2's natural enzymatic function. Initial screening of a diversity library resulted in hit compounds active in an ACE2-binding assay, which showed little inhibition of ACE2 enzymatic activity (116 actives, success rate ∼4%), suggesting they were allosteric binders. Subsequent application of in silico techniques boosted success rates to ∼14% and resulted in 73 novel confirmed ACE2 binders with K d values as low as 6 nM. A subsequent SARS-CoV-2 assay revealed that five of these compounds inhibit the viral life cycle in human cells. Further effort is required to completely elucidate the antiviral mechanism of these ACE2-binders, but they present a valuable starting point for both the development of acute treatments for COVID-19 and research into the host-directed therapy.

Recent Studies on Neglected Drug Design

BACKGROUND

Neglected diseases require special attention when looking for new therapeutic alternatives, as these are diseases of extreme complexity and severity that affect populations belonging to lower social classes who lack access to basic rights, such as sanitation.

INTRODUCTION

Among the alternatives available for obtaining new drugs is Medicinal Chemistry, which is responsible for the discovery, identification, invention, and preparation of prototypes. In this perspective, the present work aims to make a bibliographic review on the recent studies of Medicinal Chemistry applied to neglected diseases.

METHODS

A literature review was carried out by searching the "Web of Sciences" database, including recent articles published on the Neglected Drug Design.

RESULTS

In general, it was noticed that the most studied neglected diseases corresponded to Chagas disease and leishmaniasis, with studies on organic synthesis, optimization of structures, and molecular hybrids being the most used strategies. It is also worth mentioning the growing number of computationally developed studies, providing speed and optimization of costs in the procurement process.

CONCLUSION

The CADD approach and organic synthesis studies, when applied in the area of Medicinal Chemistry, have proven to be important in the research and discovery of drugs for Neglected Diseases, both in terms of planning the experimental methodology used to obtain it and in the selection of compounds with higher activity potential.

Natural Products from Annonaceae as Potential Antichagasic Agents

Chagas disease, a neglected tropical disease, is endemic in 21 Latin American countries and particularly prevalent in Brazil. Chagas disease has drawn more attention in recent years due to its expansion into non-endemic areas. The aim of this work was to computationally identify and experimentally validate the natural products from an Annonaceae family as antichagasic agents. Through the ligand-based virtual screening, we identified 57 molecules with potential activity against the epimastigote form of T. cruzi. Then, 16 molecules were analyzed in the in vitro study, of which, six molecules displayed previously unknown antiepimastigote activity. We also evaluated these six molecules for trypanocidal activity. We observed that all six molecules have potential activity against the amastigote form, but no molecules were active against the trypomastigote form. 13-Epicupressic acid seems to be the most promising, as it was predicted as an active compound in the in silico study against the amastigote form of T. cruzi, in addition to having in vitro activity against the epimastigote form.

Four diterpenes identified in silico were isolated from Hyptidinae and demonstrated in vitro activity against Mycobacterium tuberculosis

Plants of Hyptidinae subtribe (Lamiaceae - family), as Mesosphaerum sidifolium, are a source of bioactive molecules. In the search for new drug candidates, we perform chemical characterization of diterpenes isolated from the aerial parts of M. sidifolium was carried out with uni- and bidimensional NMR spectral data, and evaluate in silico through the construction of a predictive model followed by in vitro testing Mycobacterium tuberculosis and Mycobacterium smegmatis. Resulted in the isolation of four components: Pomiferin D (1), Salviol (2), Pomiferin E (3) and 2α-hydroxysugiol (4), as well as two phenolic compounds, rosmarinic and caffeic acids. In silico model identified 48 diterpenes likely to have biological activity against M. tuberculosis. The diterpenes isolated were tested in vitro against M. tuberculosis demonstrating MIC = 125 µM for 4 and 1, while 2 and 3 -MIC = 250 µM. These compounds did not show biological activity at these concentrations for M. smegmatis.

Pharmacokinetics Profiler (PhaKinPro): Model Development, Validation, and Implementation as a Web Tool for Triaging Compounds with Undesired Pharmacokinetics Profiles

Computational models that predict pharmacokinetic properties are critical to deprioritize drug candidates that emerge as hits in high-throughput screening campaigns. We collected, curated, and integrated a database of compounds tested in 12 major end points comprising over 10,000 unique molecules. We then employed these data to build and validate binary quantitative structure-activity relationship (QSAR) models. All trained models achieved a correct classification rate above 0.60 and a positive predictive value above 0.50. To illustrate their utility in drug discovery, we used these models to predict the pharmacokinetic properties for drugs in the NCATS Inxight Drugs database. In addition, we employed the developed models to predict the pharmacokinetic properties of all compounds in the DrugBank. All models described in this paper have been integrated and made publicly available via the PhaKinPro Web-portal that can be accessed at https://phakinpro.mml.unc.edu/.