Harmonization of QSAR Best Practices and Molecular Docking Provides an Efficient Virtual Screening Tool for Discovering New G-Quadruplex Ligands

Maximizing the integration of virtual and experimental screening in hit discovery

INTRODUCTION

Experimental and virtual screening contributes to the discovery of more than 50% of clinical candidates. Considering the similar concept and goals, early-phase drug discovery would benefit from the effective integration of these approaches.

AREAS COVERED

After reviewing the recent trends in both experimental and virtual screening, the authors discuss different integration strategies from parallel, focused, sequential, and iterative screening. Strategic considerations are demonstrated in a number of real-life case studies.

EXPERT OPINION

Experimental and virtual screening are complementary approaches that should be integrated in lead discovery settings. Virtual screening can access extremely large synthetically feasible chemical space that can be effectively searched on GPU clusters or cloud architectures. Experimental screening provides reliable datasets by quantitative HTS applications, and DNA-encoded libraries (DEL) have enlarged the chemical space covered by these technologies. These developments, together with the use of artificial intelligence methods, represent new options for their efficient integration. The case studies discussed here demonstrate the benefits of complementary strategies, such as focused and iterative screening.

Identification of Kukoamine A, Zeaxanthin, and Clexane as New Furin Inhibitors

The endogenous protease furin is a key protein in many different diseases, such as cancer and infections. For this reason, a wide range of studies has focused on targeting furin from a therapeutic point of view. Our main objective consisted of identifying new compounds that could enlarge the furin inhibitor arsenal; secondarily, we assayed their adjuvant effect in combination with a known furin inhibitor, CMK, which avoids the SARS-CoV-2 S protein cleavage by means of that inhibition. Virtual screening was carried out to identify potential furin inhibitors. The inhibition of physiological and purified recombinant furin by screening selected compounds, Clexane, and these drugs in combination with CMK was assayed in fluorogenic tests by using a specific furin substrate. The effects of the selected inhibitors from virtual screening on cell viability (293T HEK cell line) were assayed by means of flow cytometry. Through virtual screening, Zeaxanthin and Kukoamine A were selected as the main potential furin inhibitors. In fluorogenic assays, these two compounds and Clexane inhibited both physiological and recombinant furin in a dose-dependent way. In addition, these compounds increased physiological furin inhibition by CMK, showing an adjuvant effect. In conclusion, we identified Kukoamine A, Zeaxanthin, and Clexane as new furin inhibitors. In addition, these drugs were able to increase furin inhibition by CMK, so they could also increase its efficiency when avoiding S protein proteolysis, which is essential for SARS-CoV-2 cell infection.

Triazolyl Dibenzo[a,c]phenazines Stabilize Telomeric G-quadruplex and Inhibit Telomerase

We herein report the synthesis and biophysical evaluation of triazolyl dibenzo[a,c]phenazine derivatives as a novel class of G-quadruplex ligands. The aromatic core facilitates π-π interaction and the flexible, protonatable side chains interact with the phosphate backbone of DNA via electrostatic interactions. Förster resonance energy transfer (FRET) melting assay and isothermal titration calorimetry (ITC) studies suggest that these ligands show binding preference for the hTELO G-quadruplex over G-quadruplexes found in the promoter region of various oncogenes and duplex DNA. The in vitro telomeric repeat amplification protocol (Q-TRAP) assay reveals that these ligands reduce telomerase activity in cancer cells.

Selection of antileishmanial sesquiterpene lactones from SistematX database using a combined ligand-/structure-based virtual screening approach

Leishmaniasis refers to a complex of diseases, caused by the intracellular parasitic protozoans belonging to the genus Leishmania. Among the three types of disease manifestations, the most severe type is visceral leishmaniasis, which is caused by Leishmania donovani, and is diagnosed in more than 20,000 cases annually, worldwide. Because the current therapeutic options for disease treatment are associated with several limitations, the identification of new potential leads/drugs remains necessary. In this study, a combined approach was used, based on two different virtual screening (VS) methods, which were designed to select promising antileishmanial agents from among the entire sesquiterpene lactone (SL) dataset registered in SistematX, a web interface for managing a secondary metabolite database that is accessible by multiple platforms on the Internet. Thus, a ChEMBL dataset, including 3159 and 1569 structures that were previously tested against L. donovani amastigotes and promastigotes in vitro, respectively, was used to develop two random forest models, which performed with greater than 74% accuracy in both the cross-validation and test sets. Subsequently, a ligand-based VS assay was performed against the 1306 SistematX-registered SLs. In parallel, the crystal structures of three L. donovani target proteins, N-myristoyltransferase, ornithine decarboxylase, and mitogen-activated protein kinase 3, and a homology model of pteridine reductase 1 were used to perform a structure-based VS, using molecular docking, of the entire SistematX SL dataset. The consensus analysis of these two VS approaches resulted in the normalization of probability scores and identified 13 promising, enzyme-targeting, antileishmanial SLs from SistematX that may act against L. donovani. A combined approach based on two different virtual screening methods (structure-based and ligand-based) was performed using an in-house dataset composed of 1306 sesquiterpene lactones to identify potential antileishmanial (Leishmania donovani) structures.

Targeting the KRAS oncogene: Synthesis, physicochemical and biological evaluation of novel G-Quadruplex DNA binders

The oncogene KRAS is involved in the pathogenesis of many tumors such as pancreatic, lung and colorectal cancers, thereby representing a relevant target for the treatment of these diseases. The KRAS P1 promoter contains a nuclease hypersensitive, guanine-rich sequence able to fold into a G-quadruplex motif (G4). The stabilization of this G4 structure by small molecules is emerging as a feasible approach to downregulate KRAS expression. Here, a set of novel stabilizing molecules was identified through a virtual screening campaign on the NMR structure of the 22-mer KRAS G4. The most promising hits were then submitted to structure-activity relationships studies which allowed improving their binding affinity and selectivity over double helix DNA and different G4 topologies. The best derivative (19) underwent fluorescence titration experiments and further computational studies to disclose its binding mechanism to KRAS G4. Finally, biological assays showed that this compound is capable to reduce the viability of colorectal cancer cells in which mutated KRAS acts as a driver oncogene. Thus, 19 might represent the prototype of a new class of drugs for the treatment of tumors that, expressing mutated forms of KRAS, are refractory to current therapeutic regimens.

G-quadruplex virtual drug screening: A review

Over the past two decades biologists and bioinformaticians have unearthed substantial evidence supporting a role for G-quadruplexes as important mediators of biological processes. This includes telomere damage signaling, transcriptional activity, and splicing. Both their structural heterogeneity and their abundance in oncogene promoters makes them ideal targets for drug discovery. Currently, there are hundreds of deposited DNA and RNA quadruplex atomic structures which have allowed researchers to begin using in silico drug screening approaches to develop novel stabilizing ligands. Here we provide a review of the past decade of G-quadruplex virtual drug discovery approaches and campaigns. With this we introduce relevant virtual screening platforms followed by a discussion of best practices to assist future G4 VS campaigns.

In Silico Studies Designed to Select Sesquiterpene Lactones with Potential Antichagasic Activity from an In-House Asteraceae Database

Chagas disease is an endemic disease caused by Trypanosoma cruzi, which affects more than eight million people, mostly in the Americas. A search for new treatments is necessary to control and eliminate this disease. Sesquiterpene lactones (SLs) are an interesting group of secondary metabolites characteristic of the Asteraceae family that have presented a wide range of biological activities. From the ChEMBL database, we selected a diverse set of 4452, 1635, and 1322 structures with tested activity against the three T. cruzi parasitic forms: amastigote, trypomastigote, and epimastigote, respectively, to create random forest (RF) models with an accuracy of greater than 74 % for cross-validation and test sets. Afterward, a ligand-based virtual screen of the entire SLs of the Asteraceae database stored in SistematX (1306 structures) was performed. In addition, a structure-based virtual screen was also performed for the same set of SLs using molecular docking. Finally, using an approach combining ligand-based and structure-based virtual screening along with the equations proposed in this study to normalize the probability scores, we verified potentially active compounds and established a possible mechanism of action.

Strategies of Virtual Screening in Medicinal Chemistry

Virtual screening represents an effective computational strategy to rise-up the chances of finding new bioactive compounds by accelerating the time needed to move from an initial intuition to market. Classically, the most pursued approaches rely on ligand- and structure-based studies, the former employed when structural data information about the target is missing while the latter employed when X-ray/NMR solved or homology models are instead available for the target. The authors will focus on the most advanced techniques applied in this area. In particular, they will survey the key concepts of virtual screening by discussing how to properly select chemical libraries, how to make database curation, how to applying and- and structure-based techniques, how to wisely use post-processing methods. Emphasis will be also given to the most meaningful databases used in VS protocols. For the ease of discussion several examples will be presented.

Systemic QSAR and phenotypic virtual screening: chasing butterflies in drug discovery

Current advances in systems biology suggest a new change of paradigm reinforcing the holistic nature of the drug discovery process. According to the principles of systems biology, a simple drug perturbing a network of targets can trigger complex reactions. Therefore, it is possible to connect initial events with final outcomes and consequently prioritize those events, leading to a desired effect. Here, we introduce a new concept, 'Systemic Chemogenomics/Quantitative Structure-Activity Relationship (QSAR)'. To elaborate on the concept, relevant information surrounding it is addressed. The concept is challenged by implementing a systemic QSAR approach for phenotypic virtual screening (VS) of candidate ligands acting as neuroprotective agents in Parkinson's disease (PD). The results support the suitability of the approach for the phenotypic prioritization of drug candidates.

High-throughput identification of telomere-binding ligands based on the fluorescence regulation of DNA-copper nanoparticles

Formation of the G-quadruplex in the human telomeric DNA is an effective way to inhibit telomerase activity. Therefore, screening ligands of G-quadruplex has potential applications in the treatment of cancer by inhibit telomerase activity. Although several techniques have been explored for screening of telomeric G-quadruplexes ligands, high-throughput screening method for fast screening telomere-binding ligands from the large compound library is still urgently needed. Herein, a label-free fluorescence strategy has been proposed for high-throughput screening telomere-binding ligands by using DNA-copper nanoparticles (DNA-CuNPs) as a signal probe. In the absence of ligands, human telomeric DNA (GDNA) hybridized with its complementary DNA (cDNA) to form double stranded DNA (dsDNA) which can act as an efficient template for the formation of DNA-CuNPs, leading to the high fluorescence of DNA-CuNPs. In the presence of ligands, GDNA folded into G-quadruplex. Single-strdanded cDNA does not support the formation of DNA-CuNP, resulting in low fluorescence of DNA-CuNPs. Therefore, telomere-binding ligands can be high-throughput screened by monitoring the change in the fluorescence of DNA-CuNPs. Thirteen traditional chinese medicines were screened. Circular dichroism (CD) measurements demonstrated that the selected ligands could induce single-stranded telomeric DNA to form G-quadruplex. The telomere repeat amplification protocol (TRAP) assay demonstrated that the selected ligands can effectively inhibit telomerase activity. Therefore, it offers a cost-effective, label-free and reliable high-throughput way to identify G-quadruplex ligands, which holds great potential in discovering telomerase-targeted anticancer drugs.

Optimized Virtual Screening Workflow for the Identification of Novel G-Quadruplex Ligands

G-quadruplexes, alternative DNA secondary structures present in telomeres, emerge as promising targets for the treatment of cancer, because they prevent telomere elongation and accordingly cell proliferation. Within this study, theoretically validated pharmacophore- and shape-based models as well as a theoretically validated docking protocol were generated and applied in parallel for virtual screening and the identification of novel G-quadruplex ligands. Top-ranked hits retrieved with all methods independently and in addition in a consensus approach were selected for biological testing. Of the 32 tested virtual hits seven selectively stabilized G-quadruplexes over duplex DNA in the fluorescence melting assay. For the five most active compounds, chemically closely related analogues were collected and subjected to in vitro analysis. Thereby, seven further novel G-quadruplex ligands could be identified. These molecules do not only represent novel scaffolds, but some of them are in addition even more potent G-quadruplex stabilizers than the established reference compound berberine. This study proposes an optimized in silico workflow for the identification of novel G-quadruplex stabilizers, which can also be applied in future studies. In addition, structurally novel and promising lead candidates with strong and selective G-quadruplex stabilizing properties are reported.