Discovery of a new potent inhibitor of mushroom tyrosinase (Agaricus bisporus) containing 4-(4-hydroxyphenyl)piperazin-1-yl moiety

Exploring Structural Requirements for Sigma-1 Receptor Linear Ligands: Experimental and Computational Approaches

Sigma-1 receptor (S1R) is involved in a large array of biological functions due to its ability to interact with various proteins and ion channels. Crystal structures of human S1R revealed the trimeric organization for which each protomer comprises the ligand binding pocket. This study applied a multistep computational procedure to develop a pharmacophore model obtained from molecular dynamics simulations of available cocrystal structures of well-known S1R ligands. Apart from the well-established positive ionizable and hydrophobic features, the obtained model included an additional specific hydrophobic feature and different excluded volumes, thus increasing the selectivity of the model as well as a more detailed determination of the distance between two essential features. The obtained pharmacophore model passed the validation test by receiver operating characteristic (ROC) curve analysis of active and inactive S1R ligands. Finally, the pharmacophoric performance was experimentally investigated through the synthesis and binding assay of new 4-phenylpiperazine-based compounds. The most active new ligand 2-(3-methyl-1-piperidyl)-1-(4-phenylpiperazin-1-yl)ethanone (3) showed an S1R affinity close to the reference compound haloperidol (Ki values of 4.8 and 2.6 nM, respectively). The proposed pharmacophore model can represent a useful tool to design and discover new potent S1R ligands.

Computational methods to analyze and predict the binding mode of inhibitors targeting both human and mushroom tyrosinase

Tyrosinase, a copper-containing enzyme critical in melanin biosynthesis, is a key drug target for hyperpigmentation and melanoma in humans. Testing the inhibitory effects of compounds using tyrosinase from Agaricus bisporus (AbTYR) has been a common practice to identify potential therapeutics from synthetic and natural sources. However, structural diversity among human tyrosinase (hTYR) and AbTYR presents a challenge in developing drugs that are therapeutically effective. In this study, we combined retrospective and computational analyses with experimental data to provide insights into the development of new inhibitors targeting both hTYR and AbTYR. We observed contrasting effects of Thiamidol™ and our 4-(4-hydroxyphenyl)piperazin-1-yl-derivative (6) on both enzymes; based on this finding, we aimed to investigate their binding modes in hTYR and AbTYR to identify residues that significantly improve affinity. All the information led to the discovery of compound [4-(4-hydroxyphenyl)piperazin-1-yl](2-methoxyphenyl)methanone (MehT-3, 7), which showed comparable activity on AbTYR (IC50 = 3.52 μM) and hTYR (IC50 = 5.4 μM). Based on these achievements we propose the exploitation of our computational results to provide relevant structural information for the development of newer dual-targeting molecules, which could be preliminarily tested on AbTYR as a rapid and inexpensive screening procedure before being tested on hTYR.

Discovery and computational studies of piperidine/piperazine-based compounds endowed with sigma receptor affinity

Herein, we describe our efforts to identify sigma receptor 1 (S1R) ligands through a screening campaign on our in-house collection of piperidine/piperazine-based compounds. Our investigations led to the discovery of the potent compound 2-[4-(benzyl)-1-piperidin-1-yl]-1-4-(4-phenylpiperazin-1-yl)ethanone (1) with high affinity toward S1R (Ki value of 3.2 nM) that was comparable to reference compound haloperidol (Ki value of 2.5 nM). Functional assay revealed that compound 1 acted as S1R agonist. To decipher the binding mode of this promising S1R ligand as a starting point for further structure-based optimization, we analysed the docking pose by using a S1R-structure derived from cocrystal structures of potent ligands in complex with target protein. The computational study was enriched with molecular dynamic simulations that revealed the crucial amino acid residues that interacted with the most interesting compound 1.

Synthesis, In Silico Studies, and Antioxidant and Tyrosinase Inhibitory Potential of 2-(Substituted Phenyl) Thiazolidine-4-Carboxamide Derivatives

Heterocyclic nuclei have shown a wide variety of biological activities, highlighting their importance in drug discovery. Derivatives of 2,4-subsituted thiazolidine have a structural similarity with the substrates of tyrosinase enzymes. Hence, they can be used as an inhibitor to compete against tyrosine in the biosynthesis of melanin. This study is focused on design, synthesis, biological activities, and in silico studies of thiazolidine derivatives substituted at positions 2 and 4. The synthesized compounds were evaluated to determine the antioxidant activity and tyrosine inhibitory potential using mushroom tyrosinase. The most potent tyrosinase enzyme inhibitor was compound 3c having IC₅₀ value 16.5 ± 0.37 µM, whereas compound 3d showed maximum antioxidant activity in a DPPH free radical scavenging assay (IC₅₀ = 18.17 µg/mL). Molecular docking studies were conducted using mushroom tyrosinase (PDB ID: 2Y9X) to analyze binding affinities and binding interactions of the protein-ligand complex. Docking results indicated that hydrogen bonds and hydrophobic interactions were mainly involved in the ligand and protein complex. The highest binding affinity was found to be -8.4 Kcal/mol. These results suggest that thiazolidine-4-carboxamide derivatives could serve as lead molecules for development of novel potential tyrosinase inhibitors.

Heterocyclic Compounds as Synthetic Tyrosinase Inhibitors: Recent Advances

Tyrosinase is a copper-containing enzyme which is widely distributed in nature (e.g., bacteria, mammals, fungi) and involved in two consecutive steps of melanin biosynthesis. In humans, an excessive production of melanin can determine hyperpigmentation disorders as well as neurodegenerative processes in Parkinson's disease. The development of molecules able to inhibit the high activity of the enzyme remain a current topic in medicinal chemistry, because the inhibitors reported so far present several side effects. Heterocycle-bearing molecules are largely diffuse in this sense. Due to their importance as biologically active compounds, we decided to report a comprehensive review of synthetic tyrosinase inhibitors possessing heterocyclic moieties reported within the last five years. For the reader's convenience, we classified them as inhibitors of mushroom tyrosinase (Agaricus bisporus) and human tyrosinase.

In silico and in vitro studies of novel derivatives of tyrosol and raspberry ketone as the mushroom tyrosinase inhibitors

Tyrosinase is the key enzyme for melanin biosynthesis. Overproduction and deposition of this pigment cause different problems in various industries including agriculture and food. Finding safe tyrosinase inhibitors thus attracts great research interest. The goal of this study is evaluation of inhibitory potencies of some novel synthetic derivatives of tyrosol and raspberry ketone on diphenolase activity of mushroom tyrosinase. The ligands inhibited enzyme activity and compound 4-(2-(4-(hydroxymethyl)-2-methyl-1,3-dioxolan-2-yl)ethyl)phenol (1d) exhibited the most inhibitory potency (77% inhibition, IC₅₀ = 0.32 µmol L^-1) via the mixed inhibition mode. This compound was also safe according to the results of in vitro analyses. The enzyme-ligands interactions were theoretically and experimentally investigated using molecular docking and fluorescence quenching approaches, respectively. Modes of quenching and related parameters were also determined and molecular docking data showed that the ligands bind to important sites of the enzyme. These compounds, especially 1d, can be suggested as efficient candidates for further investigations.

Leveraging the 3-Chloro-4-fluorophenyl Motif to Identify Inhibitors of Tyrosinase from Agaricus bisporus

Tyrosinase (EC 1.14.18.1) is implicated in melanin production in various organisms. There is a growing body of evidence suggesting that the overproduction of melanin might be related to several skin pigmentation disorders as well as neurodegenerative processes in Parkinson's disease. Based on this consideration, the development of tyrosinase inhibitors represents a new challenge to identify new agents in pharmaceutical and cosmetic applications. With the goal of identifying tyrosinase inhibitors from a synthetic source, we employed a cheap and facile preliminary assay using tyrosinase from Agaricus bisporus (AbTYR). We have previously demonstrated that the 4-fluorobenzyl moiety might be effective in interactions with the catalytic site of AbTYR; moreover, the additional chlorine atom exerted beneficial effects in enhancing inhibitory activity. Therefore, we planned the synthesis of new small compounds in which we incorporated the 3-chloro-4-fluorophenyl fragment into distinct chemotypes that revealed the ability to establish profitable contact with the AbTYR catalytic site. Our results confirmed that the presence of this fragment is an important structural feature to improve the AbTYR inhibition in these new chemotypes as well. Furthermore, docking analysis supported the best activity of the selected studied compounds, possessing higher potency when compared with reference compounds.

Ensemble of structure and ligand-based classification models for hERG liability profiling

Drug-induced cardiotoxicity represents one of the most critical safety concerns in the early stages of drug development. The blockade of the human ether-à-go-go-related potassium channel (hERG) is the most frequent cause of cardiotoxicity, as it is associated to long QT syndrome which can lead to fatal arrhythmias. Therefore, assessing hERG liability of new drugs candidates is crucial to avoid undesired cardiotoxic effects. In this scenario, computational approaches have emerged as useful tools for the development of predictive models able to identify potential hERG blockers. In the last years, several efforts have been addressed to generate ligand-based (LB) models due to the lack of experimental structural information about hERG channel. However, these methods rely on the structural features of the molecules used to generate the model and often fail in correctly predicting new chemical scaffolds. Recently, the 3D structure of hERG channel has been experimentally solved enabling the use of structure-based (SB) strategies which may overcome the limitations of the LB approaches. In this study, we compared the performances achieved by both LB and SB classifiers for hERG-related cardiotoxicity developed by using Random Forest algorithm and employing a training set containing 12789 hERG binders. The SB models were trained on a set of scoring functions computed by docking and rescoring calculations, while the LB classifiers were built on a set of physicochemical descriptors and fingerprints. Furthermore, models combining the LB and SB features were developed as well. All the generated models were internally validated by ten-fold cross-validation on the TS and further verified on an external test set. The former revealed that the best performance was achieved by the LB model, while the model combining the LB and the SB attributes displayed the best results when applied on the external test set highlighting the usefulness of the integration of LB and SB features in correctly predicting unseen molecules. Overall, our predictive models showed satisfactory performances providing new useful tools to filter out potential cardiotoxic drug candidates in the early phase of drug discovery.

Investigation on Hydrazonobenzenesulfonamides as Human Carbonic Anhydrase I, II, IX and XII Inhibitors

A small series of hydrazonobenzenesulfonamides was designed, synthesized and studied for their human carbonic anhydrase (hCA) inhibitory activity. The synthesized compounds were evaluated against hCA I, II, IX and XII isoforms using acetazolamide (AAZ) as the standard inhibitor. Various hydrazonosulfonamide derivatives showed inhibitory activity at low nanomolar levels with selectivity against the cytosolic hCA II isoform, as well as the transmembrane, tumor-associated enzymes hCA IX and XII. The most potent and selective hydrazones 8, 9, 10, 11, 19 and 24 were docked into isoforms I, II, IX and XII to better understand their activity and selectivity for the different CA isoforms.

Design, Synthesis, and in Vitro Evaluation of 4-(4-Hydroxyphenyl)piperazine-Based Compounds Targeting Tyrosinase

Melanin biosynthesis is enzymatically regulated by tyrosinase (TYR, EC 1.14.18.1), which is efficiently inhibited by natural and synthetic phenols, demonstrating potential therapeutic application for the treatment of several human diseases. Herein we report the inhibitory effects of a series of (4-(4-hydroxyphenyl)piperazin-1-yl)arylmethanone derivatives, that were designed, synthesised and assayed against TYR from Agaricus bisporus (AbTYR). The best inhibitory activity was predominantly found for compounds bearing selected hydrophobic ortho-substituents on the aroyl moiety (IC50 values in the range of 1.5-4.6 μM). They proved to be more potent than the reference compound kojic acid (IC50 =17.8 μM) and displayed competitive mechanism of inhibition of diphenolase activity of AbTYR. Docking simulation predicted their binding mode into the catalytic cavities of AbTYR and the modelled human TYR. In addition, these compounds displayed antioxidant activity combined with no cytotoxicity in MTT tests. Notably, the best inhibitor affected tyrosinase activity in α-MSH-stimulated B16F10 cells, thus demonstrating anti-melanogenic activity.

Prediction and validation of host-pathogen interactions by a versatile inference approach using Aspergillus fumigatus as a case study

Biological networks are characterized by diverse interactions and dynamics in time and space. Many regulatory modules operate in parallel and are interconnected with each other. Some pathways are functionally known and annotated accordingly, e.g., endocytosis, migration, or cytoskeletal rearrangement. However, many interactions are not so well characterized. For reconstructing the biological complexity in cellular networks, we combine here existing experimentally confirmed and analyzed interactions with a protein-interaction inference framework using as basis experimentally confirmed interactions from other organisms. Prediction scoring includes sequence similarity, evolutionary conservation of interactions, the coexistence of interactions in the same pathway, orthology as well as structure similarity to rank and compare inferred interactions. We exemplify our inference method by studying host-pathogen interactions during infection of Mus musculus (phagolysosomes in alveolar macrophages) with Aspergillus fumigatus (conidia, airborne, asexual spores). Three of nine predicted critical host-pathogen interactions could even be confirmed by direct experiments. Moreover, we suggest drugs that manipulate the host-pathogen interaction.

Evaluation of 4-(4-Fluorobenzyl)piperazin-1-yl]-Based Compounds as Competitive Tyrosinase Inhibitors Endowed with Antimelanogenic Effects

There is a considerable attention for the development of inhibitors of tyrosinase (TYR) as therapeutic strategy for the treatment of hyperpigmentation disorders in humans. Continuing in our efforts to identify TYR inhibitors, we describe the design, synthesis and pharmacophore exploration of new small molecules structurally characterized by the presence of the 4-fluorobenzylpiperazine moiety as key pharmacophoric feature for the inhibition of TYR from Agaricus bisporus (AbTYR). Our investigations resulted in the discovery of the competitive inhibitor [4-(4-fluorobenzyl)piperazin-1-yl]-(3-chloro-2-nitro-phenyl)methanone 26 (IC50 =0.18 μM) that proved to be ∼100-fold more active than reference compound kojic acid (IC50 =17.76 μM). Notably, compound 26 exerted antimelanogenic effect on B16F10 cells in absence of cytotoxicity. Docking analysis suggested its binding mode into AbTYR and into modelled human TYR.

Recent advances in the design and discovery of synthetic tyrosinase inhibitors

Tyrosinase is a copper-containing metalloenzyme that is responsible for the rate-limiting catalytic step in the melanin biosynthesis and enzymatic browning. As a promising target, tyrosinase inhibitors can be used as skin whitening agents and food preservatives, thus having broad potential in the fields of food, cosmetics, agriculture and medicine. From 2015 to 2020, numerous synthetic inhibitors of tyrosinase have been developed to overcome the challenges of low efficacy and side effects. This review summarizes the enzyme structure and biological functions of tyrosinase and demonstrates the recent advances of synthetic tyrosinase inhibitors from the perspective of medicinal chemistry, providing a better understanding of the catalytic mechanisms and more effective tyrosinase inhibitors.

SAR and QSAR research on tyrosinase inhibitors using machine learning methods

Tyrosinase is a key rate-limiting enzyme in the process of melanin synthesis, which is closely related to human pigmentation disorders. Tyrosinase inhibitors can down-regulate tyrosinase to effectively reduce melanin synthesis. In this work, we conducted structure-activity relationship (SAR) study on 1097 diverse mushroom tyrosinase inhibitors. We applied five kinds of machine learning methods to develop 15 classification models. Model 5B built by fully connected neural networks and ECFP4 fingerprints achieved the highest prediction accuracy of 91.36% and Matthews correlation coefficient (MCC) of 0.81 on the test set. The applicability domains (AD) of classification models were defined by d S T D - P R O method. Moreover, we clustered the 1097 inhibitors into eight subsets by K-Means to figure out inhibitors' structural features. In addition, 10 quantitative structure-activity relationship (QSAR) models were constructed by four machine learning methods based on 813 inhibitors. Model 6 J, the best QSAR model, was developed by fully connected neural networks with 50 RDKit descriptors. It resulted in a coefficient of determination (r ²) of 0.770 and a root mean squared error (RMSE) of 0.482 on the test set. The AD of Model 6 J was visualized by Williams plot. The models built in this study can be obtained from the authors.