Novel coumarin-based tyrosinase inhibitors discovered by OECD principles-validated QSAR approach from an enlarged, balanced database

Computational studies of tyrosinase inhibitors

Computational studies have significantly advanced the understanding of tyrosinase (TYR) function, mechanism, and inhibition, accelerating the development of more effective and selective inhibitors. This chapter provides an overview of in silico studies on TYR inhibitors, emphasizing key inhibitory chemotypes and the main residues involved in ligand-target interactions. The chapter discusses tools applied in the context of TYR inhibitor development, e.g., structure-based virtual screening, molecular docking, artificial intelligence, and machine learning algorithms.

Naturally-Occurring Tyrosinase Inhibitors Classified by Enzyme Kinetics and Copper Chelation

Currently, there are three major assaying methods used to validate in vitro whitening activity from natural products: methods using mushroom tyrosinase, human tyrosinase, and dopachrome tautomerase (or tyrosinase-related protein-2, TRP-2). Whitening agent development consists of two ways, melanin synthesis inhibition in melanocytes and downregulation of melanocyte stimulation. For melanin levels, the melanocyte cell line has been used to examine melanin synthesis with the expression levels of TRP-1 and TRP-2. The proliferation of epidermal surfaced cells and melanocytes is stimulated by cellular signaling receptors, factors, or mediators including endothelin-1, α-melanocyte-stimulating hormone, nitric oxide, histamine, paired box 3, microphthalmia-associated transcription factor, pyrimidine dimer, ceramide, stem cell factors, melanocortin-1 receptor, and cAMP. In addition, the promoter region of melanin synthetic genes including tyrosinase is upregulated by melanocyte-specific transcription factors. Thus, the inhibition of growth and melanin synthesis in gene expression levels represents a whitening research method that serves as an alternative to tyrosinase inhibition. Many researchers have recently presented the bioactivity-guided fractionation, discovery, purification, and identification of whitening agents. Melanogenesis inhibition can be obtained using three different methods: tyrosinase inhibition, copper chelation, and melanin-related protein downregulation. There are currently four different types of inhibitors characterized based on their enzyme inhibition mechanisms: competitive, uncompetitive, competitive/uncompetitive mixed-type, and noncompetitive inhibitors. Reversible inhibitor types act as suicide substrates, where traditional inhibitors are classified as inactivators and reversible inhibitors based on the molecule-recognizing properties of the enzyme. In a minor role, transcription factors can also be downregulated by inhibitors. Currently, the active site copper iron-binding inhibitors such as kojic acid and chalcone exhibit tyrosinase inhibitory activity. Because the tyrosinase catalysis site structure is important for the mechanism determination of tyrosinase inhibitors, understanding the enzyme recognition and inhibitory mechanism of inhibitors is essential for the new development of tyrosinase inhibitors. The present review intends to classify current natural products identified by means of enzyme kinetics and copper chelation to exhibit tyrosinase enzyme inhibition.

Do AutoML-Based QSAR Models Fulfill OECD Principles for Regulatory Assessment? A 5-HT1A Receptor Case

The drug discovery and development process requires a lot of time, financial, and workforce resources. Any reduction in these burdens might benefit all stakeholders in the healthcare domain, including patients, government, and companies. One of the critical stages in drug discovery is a selection of molecular structures with a strong affinity to a particular molecular target. The possible solution is the development of predictive models and their application in the screening process, but due to the complexity of the problem, simple and statistical models might not be sufficient for practical application. The manuscript presents the best-in-class predictive model for the serotonin 1A receptor affinity and its validation according to the Organization for Economic Co-operation and Development guidelines for regulatory purposes. The model was developed based on a database with close to 9500 molecules by using an automatic machine learning tool (AutoML). The model selection was conducted based on the Akaike information criterion value and 10-fold cross-validation routine, and later good predictive ability was confirmed with an additional external validation dataset with over 700 molecules. Moreover, the multi-start technique was applied to test if an automatic model development procedure results in reliable results.

Design, Synthesis, In Vitro, and In silico Evaluation of N-phenylacetamide-oxindole-thiosemicarbazide hybrids as New Potential Tyrosinase Inhibitors

A novel series of N-phenylacetamide-oxindole-thiosemicarbazide hybrids were synthesized and evaluated for their tyrosinase inhibitory activity. According to tyrosinase inhibition results, all the synthesized compounds showed high tyrosinase inhibitory activity with IC50 values ranging from 0.8 to 3.88 µM in comparison to positive control kojic acid with IC50 value of 36.32 µM. Among tested compounds, analog 7o, containing the 2-methyl-4-nitrophenyl on N-phenylacetamide moiety displayed superior tyrosinase inhibition. This compound was around 45-fold more potent than kojic acid. The kinetic analysis of compound 7o demonstrated that this compound is a competitive inhibitor against tyrosinase. Docking study of this compound demonstrated that compound 7o interacted with critical histidine residues within tyrosinase active site.

Alignment-Free Antimicrobial Peptide Predictors: Improving Performance by a Thorough Analysis of the Largest Available Data Set

In the last two decades, a large number of machine-learning-based predictors for the activities of antimicrobial peptides (AMPs) have been proposed. These predictors differ from one another in the learning method and in the training and testing data sets used. Unfortunately, the training data sets present several drawbacks, such as a low representativeness regarding the experimentally validated AMP space, and duplicated peptide sequences between negative and positive data sets. These limitations give a low confidence to most of the approaches to be used in prospective studies. To address these weaknesses, we propose novel modeling and assessing data sets from the largest experimentally validated nonredundant peptide data set reported to date. From these novel data sets, alignment-free quantitative sequence-activity models (AF-QSAMs) based on Random Forest are created to identify general AMPs and their antibacterial, antifungal, antiparasitic, and antiviral functional types. An applicability domain analysis is carried out to determine the reliability of the predictions obtained, which, to the best of our knowledge, is performed for the first time for AMP recognition. A benchmarking is undertaken between the models proposed and several models from the literature that are freely available in 13 programs (ClassAMP, iAMP-2L, ADAM, MLAMP, AMPScanner v2.0, AntiFP, AMPfun, PEPred-suite, AxPEP, CAMPR3, iAMPpred, APIN, and Meta-iAVP). The models proposed are those with the best performance in all of the endpoints modeled, while most of the methods from the literature have weak-to-random predictive agreements. The models proposed are also assessed through Y-scrambling and repeated k-fold cross-validation tests, demonstrating that the outcomes obtained by them are not given by chance. Three chemometric analyses also confirmed the relevance of the peptides descriptors used in the modeling. Therefore, it can be concluded that the models built by fixing the drawbacks existing in the literature contribute to identifying antibacterial, antifungal, antiparasitic, and antiviral peptides with high effectivity and reliability. Models are freely available via the AMPDiscover tool at https://biocom-ampdiscover.cicese.mx/.

A comprehensive review on tyrosinase inhibitors

Tyrosinase is a multi-copper enzyme which is widely distributed in different organisms and plays an important role in the melanogenesis and enzymatic browning. Therefore, its inhibitors can be attractive in cosmetics and medicinal industries as depigmentation agents and also in food and agriculture industries as antibrowning compounds. For this purpose, many natural, semi-synthetic and synthetic inhibitors have been developed by different screening methods to date. This review has focused on the tyrosinase inhibitors discovered from all sources and biochemically characterised in the last four decades.

The Modern Use of an Ancient Plant: Exploring the Antioxidant and Nutraceutical Potential of the Maltese Mushroom (Cynomorium Coccineum L.)

In the continuous scientific search for new safe and effective drugs, there has recently been a rediscovery of natural substances as a potential reservoir of innovative therapeutic solutions for human health, with the prospect of integrating with and sometimes replacing conventional drugs. Cynomorium coccineum subsp. coccineum is a holoparasitic plant well known in ethnopharmacology, although its current use as a curative remedy is reported only in some ethnic groups of North Africa and the Arabian Peninsula. Often known as ‘Maltese mushroom’ due to its unique appearance and the absence of chlorophyll, C. coccineum is present in almost all of the Mediterranean Basin. It is only recently that a few research groups have begun to look for confirmation of some of its traditional uses to highlight previously unknown biological activities. Here, we review the recent scientific findings on the plant’s phytochemistry and the most significant descriptions of some of its antioxidant and biological activities (antimicrobial, anticancer, pro-erectile, and anti-tyrosinase enzyme) both in vivo and in vitro. Some of these may be promising from the perspective of food and cosmetic formulations. The purpose of this review is to provide an initial impetus to those who, in the foreseeable future, will want to increase the knowledge and possible applications of this plant full of history, charm, and mystery.

Fragment-based in silico modeling of multi-target inhibitors against breast cancer-related proteins

Breast cancer is the most frequent cancer reported in women, being responsible for hundreds of thousands of deaths. Chemotherapy has proven to be effective against this malignant neoplasm depending on different biological factors such as the histopathology, grade, and stage, among others. However, breast cancer cells have become resistant to current chemotherapeutic regimens, urging the discovery of new anti-breast cancer drugs. Computational approaches have the potential to offer promising alternatives to accelerate the search for potent and versatile anti-breast cancer agents. In the present work, we introduce the first multitasking (mtk) computational model devoted to the in silico fragment-based design of new molecules with high inhibitory activity against 19 different proteins involved in breast cancer. The mtk-computational model was created from a dataset formed by 24,285 cases, and it exhibited accuracy around 93% in both training and prediction (test) sets. Several molecular fragments were extracted from the molecules present in the dataset, and their quantitative contributions to the inhibitory activities against all the proteins under study were calculated. The combined use of the fragment contributions and the physicochemical interpretations of the different molecular descriptors in the mtk-computational model allowed the design of eight new molecular entities not reported in our dataset. These molecules were predicted as potent multi-target inhibitors against all the proteins, and they exhibited a desirable druglikeness according to the Lipinski's rule of five and its variants.

Structure-Activity Relationship Study of Hydroxycoumarins and Mushroom Tyrosinase

The structure-activity relationships of four hydroxycoumarins, two with the hydroxyl group on the aromatic ring of the molecule and two with the hydroxyl group replacing hydrogen of the pyrone ring, and their interactions with mushroom tyrosinase were studied. These compounds displayed different behaviors upon action of the enzyme. The two compounds, ar-hydroxylated 6-hydroxycoumarin and 7-hydroxycoumarin, were both weak substrates of the enzyme. Interestingly, in both cases, the product of the catalysis was the 6,7-hydroxycoumarin, although 5,6- and 7,8-isomers could also theoretically be formed. Additionally, both were able to reduce the formation of dopachrome when tyrosinase acted on its typical substrate, L-tyrosine. Although none of the compounds that contained a hydroxyl group on the pyrone ring were substrates of tyrosinase, the 3-hydroxycoumarin was a potent inhibitor of the enzyme, and the 4-hydroxycoumarin was not an inhibitor. These results were compared with those obtained by in silico molecular docking predictions to obtain potentially useful information for the synthesis of new coumarin-based inhibitors that resemble the structure of the 3-hydroxycoumarin.

Design and discovery of tyrosinase inhibitors based on a coumarin scaffold

A novel series of 3-aryl and 3-heteroarylcoumarins displaying tyrosinase inhibitory activity.

Fragment-based optimization of small molecule CXCL12 inhibitors for antagonizing the CXCL12/CXCR4 interaction

The chemokine CXCL12 and its G protein-coupled receptor (GPCR) CXCR4 are high-priority clinical targets because of their involvement in metastatic cancers (also implicated in autoimmune disease and cardiovascular disease). Because chemokines interact with two distinct sites to bind and activate their receptors, both the GPCRs and chemokines are potential targets for small molecule inhibition. A number of chemokines have been validated as targets for drug development, but virtually all drug discovery efforts focus on the GPCRs. However, all CXCR4 receptor antagonists with the exception of MSX-122 have failed in clinical trials due to unmanageable toxicities, emphasizing the need for alternative strategies to interfere with CXCL12/CXCR4-guided metastatic homing. Although targeting the relatively featureless surface of CXCL12 was presumed to be challenging, focusing efforts at the sulfotyrosine (sY) binding pockets proved successful for procuring initial hits. Using a hybrid structure-based in silico/NMR screening strategy, we recently identified a ligand that occludes the receptor recognition site. From this initial hit, we designed a small fragment library containing only nine tetrazole derivatives using a fragment-based and bioisostere approach to target the sY binding sites of CXCL12. Compound binding modes and affinities were studied by 2D NMR spectroscopy, X-ray crystallography, molecular docking and cell-based functional assays. Our results demonstrate that the sY binding sites are conducive to the development of high affinity inhibitors with better ligand efficiency (LE) than typical protein-protein interaction inhibitors (LE ≤ 0.24). Our novel tetrazole-based fragment 18 was identified to bind the sY21 site with a K(d) of 24 μM (LE = 0.30). Optimization of 18 yielded compound 25 which specifically inhibits CXCL12-induced migration with an improvement in potency over the initial hit 9. The fragment from this library that exhibited the highest affinity and ligand efficiency (11: K(d) = 13 μM, LE = 0.33) may serve as a starting point for development of inhibitors targeting the sY12 site.

Isolation and characterization of polyphenol oxidase from Sardinian poisonous and non-poisonous chemotypes of Ferula communis (L.)

Ferula communis (L.), a plant belonging to Apiaceae, is widely present in Sardinia, Italy. Currently, interest in F. communis focuses on the presence of two chemotypes in the wild. One chemotype is poisonous to animals, whereas the other chemotype is non-poisonous. Polyphenol oxidase (PPO) has been extracted and partially purified from the two chemotypes of F. communis. The biochemical characterization of the enzymes showed significant differences. In particular, while the two PPOs were not able to use 6- and 7-hydroxycoumarin as substrates, they showed distinct specificity for 6,7- and 7,8-dihydroxycoumarin. Significant differences in the enzyme behavior towards common PPO inhibitors were also observed. In addition, activation energy and activation energy for denaturation were determined, showing significant differences between FP-PPO and FNP-PPO, particularly for denaturation kinetics. The possible roles of the two PPOs in determining differences in composition and toxicity of the two F. communis chemotypes are also discussed.

Classification models for safe drug molecules

Frequent failure of drug candidates during development stages remains the major deterrent for an early introduction of new drug molecules. The drug toxicity is the major cause of expensive late-stage development failures. An early identification/optimization of the most favorable molecule will naturally save considerable cost, time, human efforts and minimize animal sacrifice. (Quantitative) Structure Activity Relationships [(Q)SARs] represent statistically derived predictive models correlating biological activity (including desirable therapeutic effect and undesirable side effects) of chemicals (drugs/toxicants/environmental pollutants) with molecular descriptors and/or properties. (Q)SAR models which categorize the available data into two or more groups/classes are known as classification models. Numerous techniques of diverse nature are being presently employed for development of classification models. Though there is an increasing use of classification models for prediction of either biological activity or toxicity, the future trend will naturally be towards the development of classification models capable of simultaneous prediction of biological activity, toxicity, and pharmacokinetic parameters so as to accelerate development of bioavailable safe drug molecules.

Urgent call for reconsideration of chronic kidney disease

Circulating toxins namely: free radicals, cytokines and metabolic products induce glomerular endothelial dysfunction, hemodynamic maladjustment and chronic ischemic state;this leads to tubulointerstitial fibrosis in chronic kidney disease (CKD). Altered vascular homeostasis observed in late stage CKD revealed defective angiogenesis and impaired nitric oxide production explaining therapeutic resistance to vasodilator treatment in late stage CKD. Under current practice, CKD patients are diagnosed and treated at a rather late stage due to the lack of sensitivity of the diagnostic markers available. This suggests the need for an alternative therapeutic strategy implementing the therapeutic approach at an early stage. This view is supported by the normal or mildly impaired vascular homeostasis observed in early stage CKD. Treatment at this early stage can potentially enhance renal perfusion, correct the renal ischemic state and restore renal function. Thus, this alternative therapeutic approach would effectively prevent end-stage renal disease.