Development of a multi-targeted chemotherapeutic approach based on G-quadruplex stabilisation and carbonic anhydrase inhibition

A novel class of compounds designed to hit two anti-tumour targets, G-quadruplex structures and human carbonic anhydrases (hCAs) IX and XII is proposed. The induction/stabilisation of G-quadruplex structures by small molecules has emerged as an anticancer strategy, disrupting telomere maintenance and reducing oncogene expression. hCAs IX and XII are well-established anti-tumour targets, upregulated in many hypoxic tumours and contributing to metastasis. The ligands reported feature a berberine G-quadruplex stabiliser scaffold connected to a moiety inhibiting hCAs IX and XII. In vitro experiments showed that our compounds selectively stabilise G-quadruplex structures and inhibit hCAs IX and XII. The crystal structure of a telomeric G-quadruplex in complex with one of these ligands was obtained, shedding light on the ligand/target interaction mode. The most promising ligands showed significant cytotoxicity against CA IX-positive HeLa cancer cells in hypoxia, and the ability to stabilise G-quadruplexes within tumour cells.

Dual Inhibitors of Brain Carbonic Anhydrases and Monoamine Oxidase-B Efficiently Protect against Amyloid-β-Induced Neuronal Toxicity, Oxidative Stress, and Mitochondrial Dysfunction

We report here the first dual inhibitors of brain carbonic anhydrases (CAs) and monoamine oxidase-B (MAO-B) for the management of Alzheimer's disease. Classical CA inhibitors (CAIs) such as methazolamide prevent amyloid-β-peptide (Aβ)-induced overproduction of reactive oxygen species (ROS) and mitochondrial dysfunction. MAO-B is also implicated in ROS production, cholinergic system disruption, and amyloid plaque formation. In this work, we combined a reversible MAO-B inhibitor of the coumarin and chromone type with benzenesulfonamide fragments as highly effective CAIs. A hit-to-lead optimization led to a significant set of derivatives showing potent low nanomolar inhibition of the target brain CAs (KIs in the range of 0.1-90.0 nM) and MAO-B (IC50 in the range of 6.7-32.6 nM). Computational studies were conducted to elucidate the structure-activity relationship and predict ADMET properties. The most effective multitarget compounds totally prevented Aβ-related toxicity, reverted ROS formation, and restored the mitochondrial functionality in an SH-SY5Y cell model surpassing the efficacy of single-target drugs.

Dual Targeting of PTP1B and Aldose Reductase with Marine Drug Phosphoeleganin: A Promising Strategy for Treatment of Type 2 Diabetes

An in-depth study on the inhibitory mechanism on protein tyrosine phosphatase 1B (PTP1B) and aldose reductase (AR) enzymes, including analysis of the insulin signalling pathway, of phosphoeleganin, a marine-derived phosphorylated polyketide, was achieved. Phosphoeleganin was demonstrated to inhibit both enzymes, acting respectively as a pure non-competitive inhibitor of PTP1B and a mixed-type inhibitor of AR. In addition, in silico docking analyses to evaluate the interaction mode of phosphoeleganin with both enzymes were performed. Interestingly, this study showed that phosphoeleganin is the first example of a dual inhibitor polyketide extracted from a marine invertebrate, and it could be used as a versatile scaffold structure for the synthesis of new designed multiple ligands.

Comprehensive review for anticancer hybridized multitargeting HDAC inhibitors

Despite the encouraging clinical progress of chemotherapeutic agents in cancer treatment, innovation and development of new effective anticancer candidates still represents a challenging endeavor. With 15 million death every year in 2030 according to the estimates, cancer has increased rising of an alarm as a real crisis for public health and health systems worldwide. Therefore, scientist began to introduce innovative solutions to control the cancer global health problem. One of the promising strategies in this issue is the multitarget or smart hybrids having two or more pharmacophores targeting cancer. These rationalized hybrid molecules have gained great interests in cancer treatment as they are capable to simultaneously inhibit more than cancer pathway or target without drug-drug interactions and with less side effects. A prime important example of these hybrids, the HDAC hybrid inhibitors or referred as multitargeting HDAC inhibitors. The ability of HDAC inhibitors to synergistically improve the efficacy of other anti-cancer drugs and moreover, the ease of HDAC inhibitors cap group modification prompt many medicinal chemists to innovate and develop new generation of HDAC hybrid inhibitors. Notably, and during this short period, there are four HDAC inhibitor hybrids have entered different phases of clinical trials for treatment of different types of blood and solid tumors, namely; CUDC-101, CUDC-907, Tinostamustine, and Domatinostat. This review shed light on the most recent hybrids of HDACIs with one or more other cancer target pharmacophore. The designed multitarget hybrids include topoisomerase inhibitors, kinase inhibitors, nitric oxide releasers, antiandrogens, FLT3 and JAC-2 inhibitors, PDE5-inhibitors, NAMPT-inhibitors, Protease inhibitors, BRD4-inhibitors and other targets. This review may help researchers in development and discovery of new horizons in cancer treatment.

Aldose reductase and protein tyrosine phosphatase 1B inhibitors as a promising therapeutic approach for diabetes mellitus

Diabetes mellitus is a metabolic disease characterized by high blood glucose levels and usually associated with several chronic pathologies. Aldose reductase and protein tyrosine phosphatase 1B enzymes have identified as two novel molecular targets associated with the onset and progression of type II diabetes and related comorbidities. Although many inhibitors against these enzymes have already found in the field of diabetic mellitus, the research for discovering more effective and selective agents with optimal pharmacokinetic properties continues. In addition, dual inhibition of these target proteins has proved as a promising therapeutic approach. A variety of diverse scaffolds are presented in this review for the future design of potent and selective inhibitors of aldose reductase and protein tyrosine phosphatase 1B based on the most important structural features of both enzymes. The discovery of novel dual aldose reductase and protein tyrosine phosphatase 1B inhibitors could be effective therapeutic molecules for the treatment of insulin-resistant type II diabetes mellitus. The methods used comprise a literature survey and X-ray crystal structures derived from Protein Databank (PDB). Despite the available therapeutic options for type II diabetes mellitus, the inhibitors of aldose reductase and protein tyrosine phosphatase 1B could be two promising approaches for the effective treatment of hyperglycemia and diabetes-associated pathologies. Due to the poor pharmacokinetic profile and low in vivo efficacy of existing inhibitors of both targets, the research turned to more selective and cell-permeable agents as well as multi-target molecules.

Multi-Target Drugs Against Metabolic Disorders

BACKGROUND

Metabolic disorders are a major cause of illness and death worldwide. Metabolism is the process by which the body makes energy from proteins, carbohydrates, and fats; chemically breaking these down in the digestive system towards sugars and acids which constitute the human body's fuel for immediate use, or to store in body tissues, such as the liver, muscles, and body fat.

OBJECTIVE

The efficiency of treatments for multifactor diseases has not been proved. It is accepted that to manage multifactor diseases, simultaneous modulation of multiple targets is required leading to the development of new strategies for discovery and development of drugs against metabolic disorders.

METHODS

In silico studies are increasingly being applied by researchers due to reductions in time and costs for new prototype synthesis; obtaining substances that present better therapeutic profiles.

DISCUSSION

In the present work, in addition to discussing multi-target drug discovery and the contributions of in silico studies to rational bioactive planning against metabolic disorders such as diabetes and obesity, we review various in silico study contributions to the fight against human metabolic pathologies.

CONCLUSION

In this review, we have presented various studies involved in the treatment of metabolic disorders; attempting to obtain hybrid molecules with pharmacological activity against various targets and expanding biological activity by using different mechanisms of action to treat a single pathology.

Ligand-based Modeling for the Prediction of Pharmacophore Features for Multi-targeted Inhibition of the Arachidonic Acid Cascade

The single-target drugs against the arachidonic acid inflammatory pathway are associated with serious side effects, hence, as a first step towards multi-target drugs, we have studied the pharmacophoric features common to the inhibitors of 5-lipoxygenase-activating protein (FLAP), microsomal prostaglandin E-synthase 1 (mPGES-1) and leukotriene A4 hydrolase (LTA4H). FLAP and mPGES-1 shared subfamily-specific positions (SSPs) and four mPGES-1 inhibitors binding to them mapped onto the pharmacophore derived from FLAP inhibitors (Ph-FLAP). The reactions of mPGES-1 and LTA4H had high structural similarity. The pharmacophore derived from two substrate mimic inhibitors of LTA4H (Ph-LTA4H) also mapped onto three mPGES-1 inhibitors. Screening of in-house database for Ph-FLAP and Ph-LTA4H identified one compound, C1. It inhibited the production of the mPGES-1 product, prostaglandin E2 (PGE2) by 97.8±1.6 % at 50 μM in HeLa cells and can be a starting point for designing molecules inhibiting all three targets simultaneously.

Multiple target-centric strategy to tame inflammation

Single-target inhibition is an unsatisfactory therapeutic option to treat multifactorial pathologies, brought into limelight 'paradox of inflammation' beside dearth of innovation, rationalizes a shift toward 'multiple-target' design concept in anti-inflammatory research field. To improvise, two platform strategies, drugs mixture or multitarget drugs, are plausible. Dual cyclooxygenase/lipoxygenase inhibitor 'licofelone' developed after the backfire of rofecoxib due to safety concerns has fetched first light of triumph of the latter strategy. As hitting multiple targets in restraint is perhaps more viable strategy rather than single target, this review, outlines the most germane multiple target agents of synthetic and natural origin placing clear advantage in favors of multitarget strategy as real therapeutic solution for inflammation.

Use of machine learning approaches for novel drug discovery

INTRODUCTION

The use of computational tools in the early stages of drug development has increased in recent decades. Machine learning (ML) approaches have been of special interest, since they can be applied in several steps of the drug discovery methodology, such as prediction of target structure, prediction of biological activity of new ligands through model construction, discovery or optimization of hits, and construction of models that predict the pharmacokinetic and toxicological (ADMET) profile of compounds.

AREAS COVERED

This article presents an overview on some applications of ML techniques in drug design. These techniques can be employed in ligand-based drug design (LBDD) and structure-based drug design (SBDD) studies, such as similarity searches, construction of classification and/or prediction models of biological activity, prediction of secondary structures and binding sites docking and virtual screening.

EXPERT OPINION

Successful cases have been reported in the literature, demonstrating the efficiency of ML techniques combined with traditional approaches to study medicinal chemistry problems. Some ML techniques used in drug design are: support vector machine, random forest, decision trees and artificial neural networks. Currently, an important application of ML techniques is related to the calculation of scoring functions used in docking and virtual screening assays from a consensus, combining traditional and ML techniques in order to improve the prediction of binding sites and docking solutions.

Screening of multi-targeted natural compounds for receptor tyrosine kinases inhibitors and biological evaluation on cancer cell lines, in silico and in vitro

Receptors for growth factors encompass within the superfamily of receptor tyrosine kinases and are known to regulate numerous biological processes including cellular growth, proliferation, metabolism, survival, cell differentiation and apoptosis. These receptors have recently caught the attention of the researchers as an attractive target to combat cancer owing to the evidence suggesting their over-expression in cancer cells. Therefore, we studied receptor-based molecular docking of IR (PDB; 3ETA), IGF1R (PDB; 1K3A), EGFR (PDB; 1M17), VEGFIR (PDB; 3HNG), and VEGFIIR (PDB; 2OH4) against natural compounds. Further, in vitro investigation of the biological effect of lead molecules in an array of cancer cell lines was done. All selected natural compounds were docked with the X-ray crystal structure of selected protein by employing GLIDE (Grid-based Ligand Docking with Energetics) Maestro 9.6. InterBioScreen natural compounds docked with each selected protein molecules by using GLIDE high throughput virtual screening. On the basis of Gscore, we select 20 compounds along with 68 anticancer compounds for GLIDE extra precision molecular docking. It was discovered in this study that compound epigallocatechin gallate (EGCG) yielded magnificent Gscore with IGF1R (PDB; 1K3A) and VEGFIIR (PDB; 2OH4), and protein-ligand interactions are chart out. Effect of EGCG on biological activity such as mRNA expression of selected protein, cell proliferation, oxidative stress, and cell migration was reported after the 48 h treatments in cancer cell lines. The RT-PCR densitometric bands analysis showed that compound EGCG reduced the mRNA expression of IGF1R, VEGFIIR, and mTOR at 80 μM concentration. Moreover, EGCG significantly reduced cell proliferation and ROS generation after 48 h treatments. Our result also indicated a reduction in the potential for cell migration that might show in vivo anti-metastasis activity of EGCG.

Design, synthesis and biological evaluation of colchicine derivatives as novel tubulin and histone deacetylase dual inhibitors

A new class of colchicine derivatives were designed and synthesized as tubulin-HDAC dual inhibitors. Biological evaluations of these hybrids included the inhibitory activity of HDAC, tubulin polymerization analysis, in vitro cell cycle analysis in HCT-116 cells and cytotoxicity against different cancer cell lines. Hybrid 6d behaved as potent HDAC-tubulin dual inhibitor and showed comparable cytotoxicity with colchicine. Compound 11a exhibited powerful tubulin inhibitory activity, moderate anti-HDAC activity and the most potent cytotoxicity (IC50 = 2-105 nM).

Multitarget inhibitors derived from crosstalk mechanism involving VEGFR2

Seven VEGFR small-molecule inhibitors have been approved by the US FDA as anticancer drugs, which confirms the therapeutic value of angiogenesis inhibitors. However, much more evidence indicates that VEGFR inhibition alone is usually not sufficient to block the tumor progress. The potential of some agents targeting VEGFR owes partially to the simultaneous inhibition of additional targets in other signaling pathways. In this review, the crosstalk between VEGFR2 and the additional targets in other signaling pathways, such as EGFR, MET, FGFR, PDGFR, c-Kit, Raf, PI3K and HDAC, and the synergistic effects derived from multitarget activities against these crosstalks are discussed. We also briefly describe the multitarget inhibitors in clinical trials or reported in the literature and patents under the different multitarget categories involving VEGFR2.

Design, synthesis and biological evaluation of 4′-demethyl-4-deoxypodophyllotoxin derivatives as novel tubulin and histone deacetylase dual inhibitors

In this study, we have designed and synthesized a class of 4′-demethyl-4-deoxypodophyllotoxin derivatives as tubulin–HDAC dual inhibitors.

Inferring multi-target QSAR models with taxonomy-based multi-task learning

BACKGROUND

A plethora of studies indicate that the development of multi-target drugs is beneficial for complex diseases like cancer. Accurate QSAR models for each of the desired targets assist the optimization of a lead candidate by the prediction of affinity profiles. Often, the targets of a multi-target drug are sufficiently similar such that, in principle, knowledge can be transferred between the QSAR models to improve the model accuracy. In this study, we present two different multi-task algorithms from the field of transfer learning that can exploit the similarity between several targets to transfer knowledge between the target specific QSAR models.

RESULTS

We evaluated the two methods on simulated data and a data set of 112 human kinases assembled from the public database ChEMBL. The relatedness between the kinase targets was derived from the taxonomy of the humane kinome. The experiments show that multi-task learning increases the performance compared to training separate models on both types of data given a sufficient similarity between the tasks. On the kinase data, the best multi-task approach improved the mean squared error of the QSAR models of 58 kinase targets.

CONCLUSIONS

Multi-task learning is a valuable approach for inferring multi-target QSAR models for lead optimization. The application of multi-task learning is most beneficial if knowledge can be transferred from a similar task with a lot of in-domain knowledge to a task with little in-domain knowledge. Furthermore, the benefit increases with a decreasing overlap between the chemical space spanned by the tasks.