Selection of protein conformations for structure-based polypharmacology studies

Optimization of the Flavonoid Extraction Process from the Stem and Leaves of Epimedium Brevicornum and Its Effects on Cyclophosphamide-Induced Renal Injury

Cyclophosphamide (CTX) is a broad-spectrum alkylated antitumor drug. It is clinically used in the treatment of a variety of cancers, and renal toxicity is one of the adverse reactions after long-term or repeated use, which not only limits the therapeutic effect of CTX, but also increases the probability of kidney lesions. The total flavonoids of Epimedium stem and leaf (EBF) and Icariin (ICA) are the main medicinal components of Epimedium, and ICA is one of the main active substances in EBF. Modern pharmacological studies have shown that EBF has a variety of biological activities such as improving osteoporosis, promoting cell proliferation, antioxidant and anti-inflammatory properties, etc. However, few studies have been conducted on the nephrotoxicity caused by optimized CTX extraction, and protein-ligand binding has not been involved. This research, through the response surface optimization extraction of EBF, obtained the best extraction conditions: ethanol concentration was 60%, solid-liquid ratio of 25:1, ultrasonic time was about 25 min. Combined with mass spectrometry (MS) analysis, EBF contained ICA, ichopidin A, ichopidin B, ichopidin C, and other components. In this study, we adopted a computational chemistry method called molecular docking, and the results show that Icariin was well bound to the antioxidant target proteins KEAP1 and NRF2, and the anti-inflammatory target proteins COX-2 and NF-κB, with free binding energies of -9.8 kcal/mol, -11.0 kcal/mol, -10.0 kcal/mol, and -8.1 kcal/mol, respectively. To study the protective effect of EBF on the nephrotoxicity of CTX, 40 male Kunming mice (weight 18 ± 22) were injected with CTX (80 mg/kg) for 7 days to establish the nephrotoxicity model and were treated with EBF (50 mg/kg, 100 mg/kg) for 8 days by gavage. After CTX administration, MDA, BUN, Cre, and IL-6 levels in serum increased, MDA increased in kidney, GPT/ALT and IL-6 increased in liver, and IL-6 increased in spleen and was significant ((p < 0.05 or (p < 0.01)). Histopathological observation showed that renal cortex glomerular atrophy necrosis, medullary inflammatory cell infiltration, and other lesions. After administration of EBF, CTX-induced increase in serum level of related indexes was reduced, and MDA in kidney, GPT/ALT and IL-6 in liver, and IL-6 in spleen were increased. At the same time, histopathological findings showed that the necrosis of medullary and corticorenal tubular epithelium was relieved at EBF (50 mg/kg) dose compared with the CTX group, and the glomerular tubular necrosis gradually became normal at EBF (100 mg/kg) dose. Western blot analysis of Keap1 and Nrf2 protein expression in kidney tissue showed that compared with model CTX group, the drug administration group could alleviate the high expression of Keap1 protein and low expression of Nrf2 protein in kidney tissue. Conclusion: After the optimal extraction of total flavonoids from the stems and leaves of Epimedium, the molecular docking technique combined with animal experiments suggested that the effective component of the total flavonoids of Epimedium might activate the Keap1-Nrf2 signaling pathway after treatment to reduce the inflammation and oxidative stress of kidney tissue, so as to reduce kidney damage and improve kidney function. Therefore, EBF may become a new natural protective agent for CTX chemotherapy in the future.

Novel Sulfonamide-Triazine Hybrid Derivatives: Docking, Synthesis, and Biological Evaluation as Anticancer Agents

The biological benefits of trisubstituted 1,3,5-triazine derivatives include their ability to reduce inflammation and fight cancer. A unique series of sulfonamide-triazine hybrid molecules were produced chemically by synthesizing triazine derivatives utilizing the usual nucleophilic aromatic substitution of cyanuric chloride via the solvent-free/neat fusion method. Fourier-transform infrared spectroscopy (FTIR), ¹H NMR, and ¹³C NMR spectroscopic analyses were used to identify novel trisubstituted synthetic compounds. The synthesized compounds have a moderate inhibition percentage when tested at 100 μM against the phosphoinositol 3-kinases (PI3Kα) enzyme; compounds 20 and 34 showed 46 and 68% anti-PI3Kα activity, respectively. To comprehend the anticipated interactions, the most successful compounds were subsequently docked into a PI3Kα protein's binding site (PDB code: 6OAC, resolution: 3.15 Å). The final synthetic compounds' anticancer activity was tested on the breast (MCF-7) and lung (A549) cancer cell lines at doses of 100 and 50 μM for additional evaluation of anticancer characteristics. The IC₅₀ values for the sulfaguanidine-triazine derivatives 27, 28, 29, 31, and 35 ranged from 14.8 to 33.2 μM, showing that compounds containing sulfaguanidine and diethylamine in their structures significantly inhibited the activity. Compound 34 could be a promising lead compound for developing new target-selected anticancer compounds with low toxicity and high selectivity.

Study of MDM2 as Prognostic Biomarker in Brain-LGG Cancer and Bioactive Phytochemicals Inhibit the p53-MDM2 Pathway: A Computational Drug Development Approach

An evaluation of the expression and predictive significance of the MDM2 gene in brain lower-grade glioma (LGG) cancer was carried out using onco-informatics pipelines. Several transcriptome servers were used to measure the differential expression of the targeted MDM2 gene and search mutations and copy number variations. GENT2, Gene Expression Profiling Interactive Analysis, Onco-Lnc, and PrognoScan were used to figure out the survival rate of LGG cancer patients. The protein–protein interaction networks between MDM2 gene and its co-expressed genes were constructed by Gene-MANIA tool. Identified bioactive phytochemicals were evaluated through molecular docking using Schrödinger Suite Software, with the MDM2 (PDB ID: 1RV1) target. Protein–ligand interactions were observed with key residues of the macromolecular target. A molecular dynamics simulation of the novel bioactive compounds with the targeted protein was performed. Phytochemicals targeting MDM2 protein, such as Taxifolin and (-)-Epicatechin, have been shown with more highly stable results as compared to the control drug, and hence, concluded that phytochemicals with bioactive potential might be alternative therapeutic options for the management of LGG patients. Our once informatics-based designed pipeline has indicated that the MDM2 gene may have been a predictive biomarker for LGG cancer and selected phytochemicals possessed outstanding interaction results within the macromolecular target’s active site after utilizing in silico approaches. In vitro and in vivo experiments are recommended to confirm these outcomes.

Design, synthesis, biological evaluation and crystal structure determination of dual modulators of carbonic anhydrases and estrogen receptors

Multi-target compounds have become increasingly important for the development of safer and more effective drug candidates. In this work, we devised a combined ligand-based and structure-based multi-target repurposing strategy and applied it to a series of hexahydrocyclopenta[c]quinoline compounds synthesized previously. The in silico analyses identified human Carbonic Anhydrases (hCA) and Estrogen Receptors (ER) as top scoring candidates for dual modulation. hCA isoforms IX and XII, and ER subtypes ER⍺ and/or ERβ are co-expressed in various cancer cell types, including breast and prostate cancer cells. ER⍺ is the primary target of anti-estrogen therapy in breast cancer, and the hCA IX isoform is a therapeutic target in triple-negative breast cancer. ER⍺-mediated transcriptional programs and hCA activity in cancer cells promote favorable microenvironments for cell proliferation. Interestingly, several lines of evidence indicate that the combined modulation of these two targets may provide significant therapeutic benefits. Moving from these first results, two additional hexahydrocyclopenta[c]quinoline derivatives bearing a sulfonamide zinc binding group (hCA) and a phenolic hydroxyl (ER) pharmacophoric group placed at the appropriate locations were designed and synthesized. Interestingly, these compounds were able to directly modulate the activities of both hCA and ER targets. In cell-based assays, they inhibited proliferation of breast and prostate cancer cells with micromolar potency and cell type-selective efficacy. The compounds inhibited hCA activity with nanomolar potency and isoform-selectivity. In transactivation assays, they reduced estrogen-driven ER activity with micro-molar potency. Finally, crystal structures of the synthesized ligands in complex with the two targets revealed that the compounds bind directly to the hCA active site, as well as to the ER ligand-binding domain, providing structural explanation to the observed activity and a rationale for optimization of their dual activity. To the best of our knowledge, this work describes the design, synthesis and biological characterization of the first dual modulators of hCA and ER, laying the ground for the structure-based optimization of their multi-target activity.

On the development of B-Raf inhibitors acting through innovative mechanisms

B-Raf is a protein kinase participating to the regulation of many biological processes in cells. Several studies have demonstrated that this protein is frequently upregulated in human cancers, especially when it bears activating mutations. In the last years, few ATP-competitive inhibitors of B-Raf have been marketed for the treatment of melanoma and are currently under clinical evaluation on a variety of other types of cancer. Although the introduction of drugs targeting B-Raf has provided significant advances in cancer treatment, responses to ATP-competitive inhibitors remain limited, mainly due to selectivity issues, side effects, narrow therapeutic windows, and the insurgence of drug resistance.

Impressive research efforts have been made so far towards the identification of novel ATP-competitive modulators with improved efficacy against cancers driven by mutant Raf monomers and dimers, some of them showing good promises. However, several limitations could still be envisioned for these compounds, according to literature data. Besides, increased attentions have arisen around approaches based on the design of allosteric modulators, polypharmacology, proteolysis targeting chimeras (PROTACs) and drug repurposing for the targeting of B-Raf proteins. The design of compounds acting through such innovative mechanisms is rather challenging. However, valuable therapeutic opportunities can be envisioned on these drugs, as they act through innovative mechanisms in which limitations typically observed for approved ATP-competitive B-Raf inhibitors are less prone to emerge. In this article, current approaches adopted for the design of non-ATP competitive inhibitors targeting B-Raf are described, discussing also on the possibilities, ligands acting through such innovative mechanisms could provide for the obtainment of more effective therapies.

Deadenylase-dependent mRNA decay of GDF15 and FGF21 orchestrates food intake and energy expenditure

Hepatokines, secretory proteins from the liver, mediate inter-organ communication to maintain a metabolic balance between food intake and energy expenditure. However, molecular mechanisms by which hepatokine levels are rapidly adjusted following stimuli are largely unknown. Here, we unravel how CNOT6L deadenylase switches off hepatokine expression after responding to stimuli (e.g., exercise and food) to orchestrate energy intake and expenditure. Mechanistically, CNOT6L inhibition stabilizes hepatic Gdf15 and Fgf21 mRNAs, increasing corresponding serum protein levels. The resulting upregulation of GDF15 stimulates the hindbrain to suppress appetite, while increased FGF21 affects the liver and adipose tissues to induce energy expenditure and lipid consumption. Despite the potential of hepatokines to treat metabolic disorders, their administration therapies have been challenging. Using small-molecule screening, we identified a CNOT6L inhibitor enhancing GDF15 and FGF21 hepatokine levels, which dramatically improves diet-induced metabolic syndrome. Our discovery, therefore, lays the foundation for an unprecedented strategy to treat metabolic syndrome.

Dual Targeting Strategies On Histone Deacetylase 6 (HDAC6) And Heat Shock Protein 90 (Hsp90)

The design of multi-target drugs acting simultaneously on multiple signaling pathways is a growing field in medicinal chemistry, especially for the treatment of complex diseases such as cancer. Histone deacetylase 6 (HDAC6) is an established anticancer drug target involved in tumor cells transformation. Being an epigenetic enzyme at the interplay of many biological processes, HDAC6 has become an attractive target for polypharmacology studies aimed at improving therapeutic efficacy of anticancer drugs. For example, the molecular chaperone Heat shock protein 90 (Hsp90) is a substrate of HDAC6 deacetylation, and several lines of evidence demonstrate that simultaneous inhibition of HDAC6 and Hsp90 promote synergistic antitumor effects on different cancer cell lines, highlighting the potential benefits of developing a single molecule endowed with multi-target activity. This review will summarize the complex interplay between HDAC6 and Hsp90, providing also useful hints for multi-target drug design and discovery approaches in this field. To this end, crystallographic structures of HDAC6 and Hsp90 complexes will be extensively reviewed in the light of discussing binding pockets features and pharmacophore requirements and providing useful guidelines for the design of dual inhibitors. The few examples of multi-target inhibitors obtained so far, mostly based on chimeric approaches, will be summarized and put into context. Finally, the main features of HDAC6 and Hsp90 inhibitors will be compared, and ligand- and structure-based strategies potentially useful for the development of small molecular weight dual inhibitors will be proposed and discussed.

LigAdvisor: a versatile and user-friendly web-platform for drug design

Although several tools facilitating in silico drug design are available, their results are usually difficult to integrate with publicly available information or require further processing to be fully exploited. The rational design of multi-target ligands (polypharmacology) and the repositioning of known drugs towards unmet therapeutic needs (drug repurposing) have raised increasing attention in drug discovery, although they usually require careful planning of tailored drug design strategies. Computational tools and data-driven approaches can help to reveal novel valuable opportunities in these contexts, as they enable to efficiently mine publicly available chemical, biological, clinical, and disease-related data. Based on these premises, we developed LigAdvisor, a data-driven webserver which integrates information reported in DrugBank, Protein Data Bank, UniProt, Clinical Trials and Therapeutic Target Database into an intuitive platform, to facilitate drug discovery tasks as drug repurposing, polypharmacology, target fishing and profiling. As designed, LigAdvisor enables easy integration of similarity estimation results with clinical data, thereby allowing a more efficient exploitation of information in different drug discovery contexts. Users can also develop customizable drug design tasks on their own molecules, by means of ligand- and target-based search modes, and download their results. LigAdvisor is publicly available at https://ligadvisor.unimore.it/.

Prediction of Promiscuity Cliffs Using Machine Learning

Compounds with the ability to interact with multiple targets, also called promiscuous compounds, provide the basis for polypharmacological drug discovery. In recent years, a plethora of structural analogs with different promiscuity has been identified. Nevertheless, the molecular origins of promiscuity remain to be elucidated. In this study, we systematically extracted different structural analogs with varying promiscuity using the matched molecular pair (MMP) formalism from public biological screening and medicinal chemistry data. Care was taken to eliminate all compounds with potential false-positive activity annotations from the analysis. Promiscuity predictions were then attempted at the level of compound pairs representing promiscuity cliffs (PCs; formed by analogs with large promiscuity differences) and corresponding non-PC MMPs (analog pairs without significant promiscuity differences). To address this prediction task, different machine learning models were generated and the results were compared with single compound predictions. PCs encoding promiscuity differences were found to contain more structure-promiscuity relationship information than sets of individual promiscuous compounds. In addition, feature analysis was carried out revealing key contributions to the correct prediction of PCs and non-PC MMPs via machine learning.

An up-to-date overview of computational polypharmacology in modern drug discovery

INTRODUCTION

In recent years, computational polypharmacology has gained significant attention to study the promiscuous nature of drugs. Despite tremendous challenges, community-wide efforts have led to a variety of novel approaches for predicting drug polypharmacology. In particular, some rapid advances using machine learning and artificial intelligence have been reported with great success.

AREAS COVERED

In this article, the authors provide a comprehensive update on the current state-of-the-art polypharmacology approaches and their applications, focusing on those reports published after our 2017 review article. The authors particularly discuss some novel, groundbreaking concepts, and methods that have been developed recently and applied to drug polypharmacology studies.

EXPERT OPINION

Polypharmacology is evolving and novel concepts are being introduced to counter the current challenges in the field. However, major hurdles remain including incompleteness of high-quality experimental data, lack of in vitro and in vivo assays to characterize multi-targeting agents, shortage of robust computational methods, and challenges to identify the best target combinations and design effective multi-targeting agents. Fortunately, numerous national/international efforts including multi-omics and artificial intelligence initiatives as well as most recent collaborations on addressing the COVID-19 pandemic have shown significant promise to propel the field of polypharmacology forward.

Design of Dual Inhibitors of Histone Deacetylase 6 and Heat Shock Protein 90

Histone deacetylase 6 (HDAC6) and heat shock protein 90 (Hsp90) are widely investigated anticancer drug targets. Importantly, several lines of evidence indicate that their regulation and activity are intimately linked, and that their combined inhibition may lead to impressive therapeutic benefits. In this study, we developed and applied an integrated computational strategy to design dual inhibitors of HDAC6 and Hsp90. Although the two targets share very little homology, an integrated ligand-based and structure-based virtual screening approach indicated a subset of compounds possessing the key structural requirements for binding at both targets. In vitro tests demonstrated that some of the selected candidates are able to selectively inhibit HDAC6 over HDAC1, to increase the acetylation levels of tubulin on cell assays and to reduce cell proliferation. The discovered compounds represent valuable starting points for further hit optimization.

Cyclin-Dependent Kinase 5 Inhibitor Butyrolactone I Elicits a Partial Agonist Activity of Peroxisome Proliferator-Activated Receptor γ

Adiponectin is an adipocyte-derived cytokine having an insulin-sensitizing activity. During the phenotypic screening of secondary metabolites derived from the marine fungus Aspergillus terreus, a poly cyclin-dependent kinase (CDK) inhibitor butyrolactone I affecting CDK1 and CDK5 was discovered as a potent adiponectin production-enhancing compound in the adipogenesis model of human bone marrow-derived mesenchymal stem cells (hBM-MSCs). CDK5 inhibitors exhibit insulin-sensitizing activities by suppressing the phosphorylation of peroxisome proliferator-activated receptor γ (PPARγ). However, the adiponectin production-enhancing activities of butyrolactone I have not been correlated with the potency of CDK5 inhibitor activities. In a target identification study, butyrolactone I was found to directly bind to PPARγ. In the crystal structure of the human PPARγ, the ligand-binding domain (LBD) in complex with butyrolactone I interacted with the amino acid residues located in the hydrophobic binding pockets of the PPARγ LBD, which is a typical binding mode of the PPARγ partial agonists. Therefore, the adiponectin production-enhancing effect of butyrolactone I was mediated by its polypharmacological dual modulator activities as both a CDK5 inhibitor and a PPARγ partial agonist.

Identification of Target Associations for Polypharmacology from Analysis of Crystallographic Ligands of the Protein Data Bank

The design of a chemical entity that potently and selectively binds to a biological target of therapeutic relevance has dominated the scene of drug discovery so far. However, recent findings suggest that multitarget ligands may be endowed with superior efficacy and be less prone to drug resistance. The Protein Data Bank (PDB) provides experimentally validated structural information about targets and bound ligands. Therefore, it represents a valuable source of information to help identifying active sites, understanding pharmacophore requirements, designing novel ligands, and inferring structure-activity relationships. In this study, we performed a large-scale analysis of the PDB by integrating different ligand-based and structure-based approaches, with the aim of identifying promising target associations for polypharmacology based on reported crystal structure information. First, the 2D and 3D similarity profiles of the crystallographic ligands were evaluated using different ligand-based methods. Then, activity data of pairs of similar ligands binding to different targets were inspected by comparing structural information with bioactivity annotations reported in the ChEMBL, BindingDB, BindingMOAD, and PDBbind databases. Afterward, extensive docking screenings of ligands in the identified cross-targets were made in order to validate and refine the ligand-based results. Finally, the therapeutic relevance of the identified target combinations for polypharmacology was evaluated from comparison with information on therapeutic targets reported in the Therapeutic Target Database (TTD). The results led to the identification of several target associations with high therapeutic potential for polypharmacology.

Molecular Docking: Shifting Paradigms in Drug Discovery

Molecular docking is an established in silico structure-based method widely used in drug discovery. Docking enables the identification of novel compounds of therapeutic interest, predicting ligand-target interactions at a molecular level, or delineating structure-activity relationships (SAR), without knowing a priori the chemical structure of other target modulators. Although it was originally developed to help understanding the mechanisms of molecular recognition between small and large molecules, uses and applications of docking in drug discovery have heavily changed over the last years. In this review, we describe how molecular docking was firstly applied to assist in drug discovery tasks. Then, we illustrate newer and emergent uses and applications of docking, including prediction of adverse effects, polypharmacology, drug repurposing, and target fishing and profiling, discussing also future applications and further potential of this technique when combined with emergent techniques, such as artificial intelligence.

In Silico Repositioning of Cannabigerol as a Novel Inhibitor of the Enoyl Acyl Carrier Protein (ACP) Reductase (InhA)

Cannabigerol (CBG) and cannabichromene (CBC) are non-psychoactive cannabinoids that have raised increasing interest in recent years. These compounds exhibit good tolerability and low toxicity, representing promising candidates for drug repositioning. To identify novel potential therapeutic targets for CBG and CBC, an integrated ligand-based and structure-based study was performed. The results of the analysis led to the identification of CBG as a low micromolar inhibitor of the Enoyl acyl carrier protein (ACP) reductase (InhA) enzyme.