Hyphenated 3D-QSAR statistical model-scaffold hopping analysis for the identification of potentially potent and selective sigma-2 receptor ligands

Integrated computational approaches for identification of potent pyrazole-based glycogen synthase kinase-3β (GSK-3β) inhibitors: 3D-QSAR, virtual screening, docking, MM/GBSA, EC, MD simulation studies

Glycogen synthase kinase-3β (GSK-3β) has emerged as a crucial target due to its substantial contribution in various cellular processes. Dysfunctional GSK-3β activity can lead to ion channel disturbances, sustain abnormal excitability, and contribute to the pathogenesis of epilepsy and other GSK-3β-related disorders. A set of 82 pyrazole analogs was utilized to study its structural features using a three-dimensional quantitative structure-activity relationship (3D-QSAR), virtual screening, molecular docking, and molecular dynamics. The QSAR model, validated using internal and external methods, demonstrated robustness with a high correlation coefficient r2training = 0.99, cross-validation coefficient q2 = 0.79, r2test = 0.69, and r2external = 0.74. The "Average of Actives" in the Activity Atlas model identified 17 molecules as active. Subsequent pharmacophore-based virtual screening of 17 actives yielded 70 compounds, which were selected as the prediction set to determine the potential GSK-3β inhibitors. Docking studies pinpointed compound P66 as the promising lead compound, with a docking score of - 10.555 kcal/mol. These findings were further supported by electrostatic potential (ESP), electrostatic complementarity (EC), and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) analyses. Furthermore, a 500 ns molecular dynamics (MD) simulation confirmed the structural and conformational stability of the lead complex throughout the simulation period. As a result, this study suggests that compound P66 holds the potential to be a potent lead candidate for the inhibition of GSK-3β, offering a novel therapeutic approach for GSK-3β related disorders, including epilepsy.

Scaffold hopping approaches for dual-target antitumor drug discovery: opportunities and challenges

INTRODUCTION

Scaffold hopping has emerged as a practical tactic to enrich the synthetic bank of small molecule antitumor agents. Specifically, it enables the chemist to refine the lead compound's pharmacodynamic, pharmacokinetic, and physiochemical properties. Scaffold hopping opens up fresh molecular territory beyond established patented chemical domains.

AREA COVERED

The authors present the scaffold hopping-based drug design strategies for dual inhibitory antitumor structural templates in this review. Minor modifications, structure rigidification and simplification (ring-closing and opening), and complete structural overhauls were the strategies employed by the medicinal chemist to generate a library of bifunctional inhibitors. In addition, the review presents an overview of the computational methods of scaffold hopping (software and programs) and organopalladium catalysis leveraged for the synthesis of templates designed via scaffold hopping.

EXPERT OPINION

The medicinal chemist has demonstrated remarkable prowess in furnishing dual inhibitory antitumor chemical architectures. Scaffold hopping-based drug design strategies have yielded a plethora of pharmacodynamically superior dual modulatory antitumor agents. An integrated approach involving computational advancements, synthetic methodology advancements, and conventional drug design strategies is required to increase the number of scaffold-hopping-assisted drug discovery campaigns.

The Benzoxazole Heterocycle: A Comprehensive Review of the Most Recent Medicinal Chemistry Developments of Antiproliferative, Brain-Penetrant, and Anti-inflammatory Agents

The benzoxazole is one of the most widely exploited heterocycles in drug discovery. Natural occurring and synthetic benzoxazoles show a broad range of biological activities. Many benzoxazoles are available for treating several diseases, and, to date, a few are in clinical trials. Moreover, an ever-increasing number of benzoxazole derivatives are under investigation in the early drug discovery phase and as potential hit or lead compounds. This perspective is an attempt to thoroughly review the rational design, the structure-activity relationship, and the biological activity of the most notable benzoxazoles developed during the past 5 years (period 2019-to date) in cancers, neurological disorders, and inflammation. We also briefly overviewed each target and its role in the disease. The huge amount of work examined suggests the great potential of the scaffold and the high interest of the scientific community in novel biologically active compounds containing the benzoxazole core.

Exploring the potential of FDA approved anti-diabetic drugs for repurposing against COVID-19: a core combination of multiple computational strategies and integrated artificial intelligence

The latest variant of coronavirus is omicron. The World Health Organization (WHO) designated variation 'B.1.1.529' named omicron as a variant of concern (VOC) on 26 November 2021. By September 2020, it will have infected over 16 million patients and killed over 600,000 people over the world. This very infectious viral illness still poses a danger to world health; it has also become the greatest problem the world is facing and become the main area of research. The development of vaccines is insufficient to stop their spread and serious effects. Despite several reputable pharmaceutical firms claiming to have developed a cure for COVID-19. For that purpose, the field-based 3D-QSAR model has been used to analyze a series of anti-diabetic drugs to repurpose them against COVID-19. The LOO verified partial least square (PLS) model generates satisfactory q2 (0.4) and r2 (0.5) values. By using this model 10 compounds were screened out of 55 FDA approved anti-diabetic drugs (built-up library). Additionally, these substances were examined using molecular docking screening and ADMET. Finally, the drugs L8, and L23 were discovered to be the lead drugs. Density functional theory at the B3LYP/6-311G* technique was used to examine structural geometries, electronic characteristics, and molecular electrostatic potential (MEP). This work will greatly assist in the detection and development of leads for early drug development to control COVID-19.Communicated by Ramaswamy H. Sarma.

3D-QSAR and ADMET studies of morpholino-pyrimidine inhibitors of DprE1 from Mycobacterium tuberculosis

DprE1 is involved in the synthesis of Mycobacterium tuberculosis cell wall and is a potent drug target for Tuberculosis (TB) treatment. The structure and dynamics of the loops L-I and L-II flanking the inhibitor binding site was studied using molecular dynamics (MD) simulation and MMPBSA in Amber v18. Docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) of 55 Morpholino-pyrimidine (MP) inhibitors was carried out using Autodock v1.2.0 and Forge v10. ADMET analysis was done using SwissADME and pkCSM. All MP inhibitors docked in the DprE1 binding pocket, making contacts with L-II residues. MD studies showed that L-I and L-II unfold in the absence of the inhibitor but fold stably structure with reduced protein motions in the presence of MP-38, the highest affinity inhibitor. This was confirmed by k-means clustering and secondary structure analysis. L-II residues, L317, F320 and R325 contributed most towards the MMPBSA binding free energy of MP-38. A robust field-based 3D-QSAR model showed values of r2train = 0.982, r2test = 0.702 and q2 = 0.516. The MP inhibitor field points were broadly divided into negative electrostatics near the A, B rings and hydrophobic electrostatics near the D, E rings. Addition of negative groups at methanone position and ring B as well as addition of hydrophobic and bulky groups at ring E will improve activity. Highly active compounds 47, 49 and 50 of MP series exhibited highly favourable drug-like properties. SAR and ADMET insights attained from this model will help in the development of active DprE1 inhibitors in future.Communicated by Ramaswamy H. Sarma.

3D-QSAR assisted identification of selective CYP1B1 inhibitors: an effective bioisosteric replacement/molecular docking/electrostatic complementarity analysis

Cytochrome P450-1B1 is a majorly overexpressed drug-metabolizing enzyme in tumors and is responsible for inactivation and subsequent resistance to a variety of anti-cancer drugs, i.e., docetaxel, tamoxifen, and cisplatin. In the present study, a 3D quantitative structure-activity relationship (3D-QSAR) model has been constructed for the identification, design, and optimization of novel CYP1B1 inhibitors. The model has been built using a set of 148 selective CYP1B1 inhibitors. The developed model was evaluated based on certain statistical parameters including q2 and r2 which showed the acceptable predictive and descriptive capability of the generated model. The developed 3D-QSAR model assisted in understanding the key molecular fields which were firmly related to the selective CYP1B1 inhibition. A theoretic approach for the generation of new lead compounds with optimized CYP1B1 receptor affinity has been performed utilizing bioisosteric replacement analysis. These generated molecules were subjected to a developed 3D-QSAR model to predict the inhibitory activity potentials. Furthermore, these compounds were scrutinized through the activity atlas model, molecular docking, electrostatic complementarity, molecular dynamics, and waterswap analysis. The final hits might act as selective CYP1B1 inhibitors which could address the issue of resistance. This 3D-QSAR includes several chemically diverse selective CYP1B1 receptor ligands and well accounts for the individual ligand's inhibition affinities. These features of the developed 3D-QSAR model will ensure future prospective applications of the model to speed up the identification of new potent and selective CYP1B1 receptor ligands.

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.

Computational Chemistry for the Identification of Lead Compounds for Radiotracer Development

The use of computer-aided drug design (CADD) for the identification of lead compounds in radiotracer development is steadily increasing. Traditional CADD methods, such as structure-based and ligand-based virtual screening and optimization, have been successfully utilized in many drug discovery programs and are highlighted throughout this review. First, we discuss the use of virtual screening for hit identification at the beginning of drug discovery programs. This is followed by an analysis of how the hits derived from virtual screening can be filtered and culled to highly probable candidates to test in in vitro assays. We then illustrate how CADD can be used to optimize the potency of experimentally validated hit compounds from virtual screening for use in positron emission tomography (PET). Finally, we conclude with a survey of the newest techniques in CADD employing machine learning (ML).

A potent estrogen receptor and microtubule specific purine-benzothiazole-based fluorescent molecular probe induces apoptotic death of breast cancer cells

Breast cancer is the most common malignancy in women and is a heterogeneous disease at molecular level. Early detection and specificity are the key prerequisite for the treatment of this deadly cancer. To address these issues attention on the breast cancer specific receptor protein(s) is the most realistic option. Herein estrogen (E) and progesterone (Pg) receptors(R) were considered to design fluorescent molecular probes with possible therapeutic option. We adopted QSAR technique to design a library of benzothiazole-purine hybrid molecules. Molecular docking offers us three screened molecules as most potential. Among these molecules one abbreviated as “CPIB” showed blue fluorescence and detected ER positive cancer cells at 1 nM concentration. At elevated concentration, CPIB induces apoptotic deaths of same cancer cells through targeting intracellular microtubules without affecting normal cells or ER negative cells. CPIB is one of its kind with two-in-one potential of “Detection and Destroy” ability targeting ER positive breast cancer cells.

From Far West to East: Joining the Molecular Architecture of Imidazole-like Ligands in HO-1 Complexes

HO-1 overexpression has been reported in several cases/types of human malignancies. Unfortunately, poor clinical outcomes are reported in most of these cases, and the inhibition of HO-1 is considered a valuable and proven anticancer approach. To identify novel hit compounds suitable as HO-1 inhibitors, we report here a fragment-based approach where ligand joining experiments were used. The two most important parts of the classical structure of the HO-1 inhibitors were used as a starting point, and 1000 novel compounds were generated and then virtually evaluated by structure and ligand-based approaches. The joining experiments led us to a novel series of indole-based compounds. A synthetic pathway for eight selected molecules was designed, and the compounds were synthesized. The biological activity revealed that some molecules reach the micromolar activity, whereas molecule 4d inhibits the HO-1 with an IC₅₀ of 1.03 μM. This study suggested that our joining approach was successful, and a novel hit compound was generated. These results are ongoing for further development.

Growing the molecular architecture of imidazole-like ligands in HO-1 complexes

Up-regulation of HO-1 had been frequently reported in different cases and types of human malignancies. Since poor clinical outcomes are reported in these cases, this enzyme's inhibition is considered a valuable and proven anticancer approach. To identify novel HO-1 inhibitors suitable for drug development, we report a structure-guided fragment-based approach to identify new lead compounds. Different parts of the selected molecules were analyzed, and the different series of novel compounds were virtually evaluated. The growing experiments of the classical HO-1 inhibitors structure led us to different hit-compounds. A synthetic pathway for six selected molecules was designed, and the compounds were synthesized. The biological activity revealed that molecules 10 and 12 inhibit the HO-1 activity with an IC₅₀ of 1.01 and 0.90 μM, respectively. This study suggested that our growing approach was successful, and these results are ongoing for further development.

Computational Drug Repurposing Resources and Approaches for Discovering Novel Antifungal Drugs against Candida albicans N-Myristoyl Transferase

Candida albicans is a yeast that is an opportunistic fungal pathogen and also identified as ubiquitous polymorphic species that is mainly linked with major fungal infections in humans, particularly in the immunocompromised patients including transplant recipients, chemotherapy patients, HIV-infected patients as well as in low-birth-weight infants. Systemic Candida infections have a high mortality rate of around 29 to 76%. For reducing its infection, limited drugs are existing such as caspofungin, fluconazole, terbinafine, and amphotericin B, etc. which contain unlikable side effects and also toxic. This review intends to utilize advanced bioinformatics technologies such as Molecular docking, Scaffold hopping, Virtual screening, Pharmacophore modeling, Molecular dynamics (MD) simulation for the development of potentially new drug candidates with a drug-repurpose approach against Candida albicans within a limited time frame and also cost reductive.

Small Molecules Selectively Targeting Sigma-1 Receptor for the Treatment of Neurological Diseases

The sigma-1 (σ1) receptor, an enigmatic protein originally classified as an opioid receptor subtype, is now understood to possess unique structural and functional features of its own and play critical roles to widely impact signaling transduction by interacting with receptors, ion channels, lipids, and kinases. The σ1 receptor is implicated in modulating learning, memory, emotion, sensory systems, neuronal development, and cognition and accordingly is now an actively pursued drug target for various neurological and neuropsychiatric disorders. Evaluation of the five selective σ1 receptor drug candidates (pridopidine, ANAVEX2-73, SA4503, S1RA, and T-817MA) that have entered clinical trials has shown that reaching clinical approval remains an evasive and important goal. This review provides up-to-date information on the selective targeting of σ1 receptors, including their history, function, reported crystal structures, and roles in neurological diseases, as well as a useful collation of new chemical entities as σ1 selective orthosteric ligands or allosteric modulators.

Synthesis, Cytotoxicity Evaluation, and Computational Insights of Novel 1,4-Diazepane-Based Sigma Ligands

Among several potential applications, sigma receptor ligands can be used as antipsychotics, antiamnesics, and against other neurodegenerative disorders as well as neuroprotective agents. We present herein a new series of diazepane-containing derivatives as σR ligands obtained by a conformational expansion approach of our previously synthesized piperidine-based compounds. The best results were reached by benzofurane 2c, 3c and quinoline 2d, 3d-substituted diazepane derivatives, which showed the highest σR affinity. The cytotoxic activities of synthesized compounds were evaluated against two cancer cell lines, and the results indicated that none of the compounds induced significant toxicity in these cells. We also evaluated the antioxidant activity by radical scavenging capacity of our best compounds on ABTS and H₂O₂. The results obtained reveal that our new derivatives possess an excellent antioxidant profile and could be protective for the cells. Overall, the benzofurane derivative 2c due to its strong interaction with the active site of the receptor, as confirmed by molecular dynamic simulations, emerged as the optimum compound with high σ1R affinity, low cytotoxicity, and a potent antioxidant activity.

Refined pharmacophore features for virtual screening of human thromboxane A2 receptor antagonists

For a long time, the structural basis of TXA2 receptor is limited due to the lack of crystal structure information, till the release of the crystal structure of TXA2 receptor, which deepens our understanding about ligand recognition and selectivity mechanisms of this physiologically important receptor. In this research, we report the successful implementation in the discovery of an optimal pharmacophore model of human TXA2 receptor antagonists through virtual screening. Structure-based pharmacophore models were generated based on two crystal structures of human TXA2 receptor (PDB entry 6IIU and 6IIV). Docking simulation revealed interaction modes of the virtual screening hits against TXA2 receptor, which was validated through molecular dynamics simulation and binding free energy calculation. ADMET properties were also analyzed to evaluate the toxicity and physio-chemical characteristics of the hits. The research would provide valuable insight into the binding mechanisms of TXA2 receptor antagonists and thus be helpful for designing novel antagonists.

Repurposing of FDA-Approved Drugs for Treating Iatrogenic Botulism: A Paired 3D-QSAR/Docking Approach†

Botulinum neurotoxin (BoNT) is widely used for the treatment of spasticity, focal dystonia, chronic migraine, facial hemispasm, and facial aesthetic treatments. Generally, treatment with botulinum toxin is a safe procedure when conducted by clinicians with expertise, and local side effects are rare and transient. However, occasionally adverse effects can occur due to the spread of the drug to nontargeted muscles and organs, producing dry mouth, fatigue, and flu-like symptoms, up to signs of systemic botulism, which appears to be more frequent in children treated for spasticity than in adults. In silico 3D-QSAR and molecular docking studies were performed to build a structure-based model on selected potent known botulinum neurotoxin type A inhibitors; this was used to screen the US Food and Drug Administration (FDA) database. Thirty molecules were identified as possible light-chain BoNT/A inhibitors. In this study, we applied a well-established ligand- and structure-based methodology for the identification of hit compounds among a database of FDA-approved drugs. The identification of budesonide, protirelin, and ciclesonide followed by other compounds can be considered a starting point for investigations of selected compounds that could bypass much of the time and costs involved in the drug approval process.

Computational Tools in the Discovery of FABP4 Ligands: A Statistical and Molecular Modeling Approach

Small molecule inhibitors of adipocyte fatty-acid binding protein 4 (FABP4) have received interest following the recent publication of their pharmacologically beneficial effects. Recently, it was revealed that FABP4 is an attractive molecular target for the treatment of type 2 diabetes, other metabolic diseases, and some type of cancers. In past years, hundreds of effective FABP4 inhibitors have been synthesized and discovered, but, unfortunately, none have reached the clinical research phase. The field of computer-aided drug design seems to be promising and useful for the identification of FABP4 inhibitors; hence, different structure- and ligand-based computational approaches have been used for their identification. In this paper, we searched for new potentially active FABP4 ligands in the Marine Natural Products (MNP) database. We retrieved 14,492 compounds from this database and filtered through them with a statistical and computational filter. Seven compounds were suggested by our methodology to possess a potential inhibitory activity upon FABP4 in the range of 97–331 nM. ADMET property prediction was performed to validate the hypothesis of the interaction with the intended target and to assess the drug-likeness of these derivatives. From these analyses, three molecules that are excellent candidates for becoming new drugs were found.

Structure-Based Approach for the Prediction of Mu-opioid Binding Affinity of Unclassified Designer Fentanyl-Like Molecules

Three quantitative structure-activity relationship (QSAR) models for predicting the affinity of mu-opioid receptor (μOR) ligands have been developed. The resulted models, exploiting the accessibility of the QSAR modeling, generate a useful tool for the investigation and identification of unclassified fentanyl-like structures. The models have been built using a set of 115 molecules using Forge as a software, and the quality was confirmed by statistical analysis, resulting in being effective for their predictive and descriptive capabilities. The three different approaches were then combined to produce a consensus model and were exploited to explore the chemical landscape of 3000 fentanyl-like structures, generated by a theoretical scaffold-hopping approach. The findings of this study should facilitate the identification and classification of new μOR ligands with fentanyl-like structures.

Synthesis, in vitro and in vivo characterization of new benzoxazole and benzothiazole-based sigma receptor ligands

A new set of 5-chlorobenzoxazole- and 5-chlorobenzothiazole-based derivatives containing the azepane ring as a basic moiety was designed, synthesized and evaluated through binding assays to measure their affinity and selectivity towards σ₁ and σ₂ receptors. Compounds 19, 22 and 24, with a four units spacer between the bicyclic scaffold and the azepane ring, showed nanomolar affinity towards both receptor subtype and the best K_i values (K_i σ₁ = 1.27, 2.30, and 0.78 and K_i σ₂ = 7.9, 3.8, and 7.61 nM, respectively). Evaluation of cytotoxic and apoptotic effects in MCF-7 human cancer cells was useful to assess σ₂ receptor activity, while an in vivo mice model of inflammatory pain allowed to analyze σ₁ receptor pharmacological properties. In vitro and in vivo results suggested that compound 19 is a σ₁/σ₂ agonist, compound 24 a σ₁ antagonist/σ₂ agonist, whereas compound 22 might act as σ₁ antagonist/σ₂ partial agonist. Due to their pharmacological profile, a potential therapeutic application in cancer of aforesaid novel σ₁/σ₂ receptor ligands, especially 22 and 24, is proposed.

Discovery of novel coumarin derivatives as potent and orally bioavailable BRD4 inhibitors based on scaffold hopping

The bromodomain and extra-terminal (BET) bromodomains, particularly BRD4, have been identified as promising therapeutic targets in the treatment of many human disorders such as cancer, inflammation, obesity, and cardiovascular disease. Recently, the discovery of novel BRD4 inhibitors has garnered substantial interest. Starting from scaffold hopping of the reported compound dihydroquinazolinone (PFI-1), a series of coumarin derivatives were designed and synthesised as a new chemotype of BRD4 inhibitors. Interestingly, the representative compounds 13 exhibited potent BRD4 binding affinity and cell proliferation inhibitory activity, and especially displayed a favourable PK profile with high oral bioavailability (F = 49.38%) and metabolic stability (T_1/2 = 4.2 h), meaningfully making it as a promising lead compound for further drug development.

3D-QSAR, Docking, ADME/Tox studies on Flavone analogs reveal anticancer activity through Tankyrase inhibition

Flavones are known as an inhibitor of tankyrase, a potential drug target of cancer. We here expedited the use of different computational approaches and presented a fast, easy, cost-effective and high throughput screening method to identify flavones analogs as potential tankyrase inhibitors. For this, we developed a field point based (3D-QSAR) quantitative structure-activity relationship model. The developed model showed acceptable predictive and descriptive capability as represented by standard statistical parameters r² (0.89) and q² (0.67). This model may help to explain SAR data and illustrated the key descriptors which were firmly related with the anticancer activity. Using the QSAR model a dataset of 8000 flavonoids were evaluated to classify the bioactivity, which resulted in the identification of 1480 compounds with the IC₅₀ value of less than 5 µM. Further, these compounds were scrutinized through molecular docking and ADMET risk assessment. Total of 25 compounds identified which further analyzed for drug-likeness, oral bioavailability, synthetic accessibility, lead-likeness, and alerts for PAINS & Brenk. Besides, metabolites of screened compounds were also analyzed for pharmacokinetics compliance. Finally, compounds F2, F3, F8, F11, F13, F20, F21 and F25 with predicted activity (IC₅₀) of 1.59, 1, 0.62, 0.79, 3.98, 0.79, 0.63 and 0.64, respectively were find as top hit leads. This study is offering the first example of a computationally-driven tool for prioritization and discovery of novel flavone scaffold for tankyrase receptor affinity with high therapeutic windows.

Fourfold Filtered Statistical/Computational Approach for the Identification of Imidazole Compounds as HO-1 Inhibitors from Natural Products

Over-regulation of Heme oxygenase 1 (HO-1) has been recently identified in many types of human cancer, and in these cases, poor clinical outcomes are normally reported. Indeed, the inhibition of HO-1 is being considered as an anticancer approach. Imidazole scaffold is normally present in most of the classical HO-1 inhibitors and seems indispensable to the inhibitory activity due to its strong interaction with the Fe(II) of the heme group. In this paper, we searched for new potentially HO-1 inhibitors among three different databases: Marine Natural Products (MNP), ZINC Natural Products (ZNP) and Super Natural II (SN2). 484,527 compounds were retrieved from the databases and filtered through four statistical/computational filters (2D descriptors, 2D-QSAR pharmacophoric model, 3D-QSAR pharmacophoric model, and docking). Different imidazole-based compounds were suggested by our methodology to be potentially active in inhibiting the HO-1, and the results have been rationalized by the bioactivity of the filtered molecules reported in the literature.

Progress in the development of selective heme oxygenase-1 inhibitors and their potential therapeutic application

Heme oxygenases (HOs) are a family of enzymes involved in the selective catabolism of free circulating heme. While HO-2 is constitutively expressed, HO-1 is strongly overexpressed under stressful stimuli (e.g., oxidative stress). Under these conditions, HO-1 exerts its strong cytoprotective activities and plays a crucial role in stimulating cell survival by removing the pro-oxidant heme and by producing carbon monoxide and biliverdin (promptly reduced to bilirubin). Unfortunately, the broad spectrum of HO-1 cytoprotective effects has been well experimentally documented both in normal and tumor cells, where the enzyme can be overexpressed, making it an exciting target in the management of some type of tumors. Development of non-competitive HO-1 inhibitors dates back in 2002 with the discovery of Azalanstat. Since then, many efforts have been devoted to the identification of selective HO-1 and HO-2 inhibitors and to unravel the molecular determinants responsible for selectivity. Molecular modeling studies supported the identification of chemical features involved in the recognition and inhibition of these enzymes. Herein, medicinal chemistry aspects and in silico studies related to the development of HO inhibitors will be discussed. The purpose of this review is to highlight recent advances in the development of new selective HO-1 and HO-2 inhibitors and covers the last six years (2013-2018).

Morphing of Ibogaine: A Successful Attempt into the Search for Sigma-2 Receptor Ligands

Ibogaine is a psychoactive indole alkaloid with high affinity for several targets including the σ₂ receptor. Indeed, extensive data support the involvement of the σ₂ receptor in neurological disorders, including Alzheimer’s disease, schizophrenia, alcohol abuse and pain. Due to its serious side effects which prevent ibogaine from potential clinical applications, novel ibogaine derivatives endowed with improved σ₂ receptor affinity may be particularly beneficial. With the purpose to facilitate the investigation of iboga alkaloid derivatives which may serve as templates for the design of selective σ₂ receptor ligands, here we report a deconstruction study on the ibogaine tricyclic moiety and a successive scaffold-hopping of the indole counterpart. A 3D-QSAR model has been applied to predict the σ₂ pK_i values of the new compounds, whereas a molecular docking study conducted upon the σ₂ receptor built by homology modeling was used to further validate the best-scored molecules. We eventually evaluated pinoline, a carboline derivative, for σ₂ receptor affinity through radioligand binding assay and the results confirmed the predicted high µM range of affinity and good selectivity. The obtained results could be helpful in the drug design process of new ibogaine simplified analogs with improved σ₂ receptor binding capabilities.

A Pseudouridine Isoxazolidinyl Nucleoside Analogue Structural Analysis: A Morphological Approach

An in silico study has been conducted upon (3′RS,5′SR)-5-[2′-benzyl-5′-hydroxymethyl-1′,2′-isoxazolidin-3′-yl]uracil through a molecular dynamics/docking approach that highlights its potential inhibitory activity upon the wild-type pseudouridine 5′-monophosphate glycosidase. The crystal structure of this compound has been solved by means of X-ray single crystal diffraction and the data inferred were used to predict its crystal morphology. These data were compared with optical microscopy images and confirmed the validity of the computed models. This robust approach, already used for several other different compounds, provides a fast and reliable tool to standardize a crystallization method in order to get similar and good quality crystals. As different crystal shapes could be associated with different polymorphic forms, this method could be considered a fast and cheap screening to choose among different and coexistent polymorphic forms. Furthermore, a match with the original crystal structure of pseudouridine 5′-monophosphate is provided.

FABP4 inhibitors 3D-QSAR model and isosteric replacement of BMS309403 datasets

The data have been obtained from FABP4 inhibitor molecules previously published. The 120 compounds were used to build a 3D-QSAR model. The development of the QSAR model has been undertaken with the use of Forge software using the PM3 optimized structure and the experimental IC₅₀ of each compound. The QSAR model was also employed to predict the activity of 3000 new isosteric derivatives of BMS309403. The isosteric replacement was also validated by the synthesis and the biological screening of three new compounds reported in the related research article “3D-QSAR assisted identification of FABP4 inhibitors: An effective scaffold hopping analysis/QSAR evaluation” (Floresta et al., 2019).

3D-QSAR assisted identification of FABP4 inhibitors: An effective scaffold hopping analysis/QSAR evaluation

Following on the recent publication of pharmacologically relevant effects, small molecule inhibitors of adipocyte fatty-acid binding protein 4 (FABP4) have attracted high interest. FABP4 is mainly expressed in macrophages and adipose tissue, where it regulates fatty acid storage and lipolysis, being also an important mediator of inflammation. In this regard, FABP4 recently demonstrated an interesting molecular target for the treatment of type 2 diabetes, other metabolic diseases and some type of cancers. In the past years, hundreds of effective FABP4 inhibitors have been synthesized. In this paper, a quantitative structure-activity relationship (QSAR) model has been produced, in order to predict the bioactivity of FABP4 inhibitors. The methodology has been combined with a scaffold-hopping approach, allowing to identify three new molecules that act as effective inhibitors of this protein. These molecules, synthesized and tested for their FABP4 inhibitor activity, showed IC₅₀ values between 3.70 and 5.59 μM, with a high level of agreement with the predicted values.

A Structure- and Ligand-Based Virtual Screening of a Database of "Small" Marine Natural Products for the Identification of "Blue" Sigma-2 Receptor Ligands

Sigma receptors are a fascinating receptor protein class whose ligands are actually under clinical evaluation for the modulation of opioid analgesia and their use as positron emission tomography radiotracers. In particular, peculiar biological and therapeutic functions are associated with the sigma-2 (σ₂) receptor. The σ₂ receptor ligands determine tumor cell death through apoptotic and non-apoptotic pathways, and the overexpression of σ₂ receptors in several tumor cell lines has been well documented, with significantly higher levels in proliferating tumor cells compared to quiescent ones. This acknowledged feature has found practical application in the development of cancer cell tracers and for ligand-targeting therapy. In this context, the development of new ligands that target the σ₂ receptors is beneficial for those diseases in which this protein is involved. In this paper, we conducted a search of new potential σ₂ receptor ligands among a database of 1517 “small” marine natural products constructed by the union of the Seaweed Metabolite and the Chemical Entities of Biological Interest (ChEBI) Databases. The structures were passed through two filters that were constituted by our developed two-dimensional (2D) and three-dimensional Quantitative Structure-Activity Relationship (3D-QSAR) statistical models, and successively docked upon a σ₂ receptor homology model that we built according to the FASTA sequence of the σ₂/TMEM97 (SGMR2_HUMAN) receptor.

Discovery of High-Affinity Cannabinoid Receptors Ligands through a 3D-QSAR Ushered by Scaffold-Hopping Analysis

Two 3D quantitative structure–activity relationships (3D-QSAR) models for predicting Cannabinoid receptor 1 and 2 (CB₁ and CB₂) ligands have been produced by way of creating a practical tool for the drug-design and optimization of CB₁ and CB₂ ligands. A set of 312 molecules have been used to build the model for the CB₁ receptor, and a set of 187 molecules for the CB₂ receptor. All of the molecules were recovered from the literature among those possessing measured K_i values, and Forge was used as software. The present model shows high and robust predictive potential, confirmed by the quality of the statistical analysis, and an adequate descriptive capability. A visual understanding of the hydrophobic, electrostatic, and shaping features highlighting the principal interactions for the CB₁ and CB₂ ligands was achieved with the construction of 3D maps. The predictive capabilities of the model were then used for a scaffold-hopping study of two selected compounds, with the generation of a library of new compounds with high affinity for the two receptors. Herein, we report two new 3D-QSAR models that comprehend a large number of chemically different CB₁ and CB₂ ligands and well account for the individual ligand affinities. These features will facilitate the recognition of new potent and selective molecules for CB₁ and CB₂ receptors.

Development of new HO-1 inhibitors by a thorough scaffold-hopping analysis

HO-1 inhibition is considered a valuable anticancer approach. In fact, up-regulation of HO-1 had been repeatedly reported in many types of human malignancies, and in these clinical cases, poor outcomes are reported. To identify novel HO-1 inhibitors suitable for drug development, a scaffold-hopping strategy calculation was utilized to design novel derivatives. Different parts of the selected molecule were analyzed and the different series of novel compounds were virtually evaluated. The calculation for the linker moiety of the classical HO-1 inhibitors structure led us to compounds 5 and 6. A synthetic pathway for the two molecules was designed and the compounds were synthesized. The biological activity revealed an HO-1 inhibition of 0.9 and 54 μM for molecules 5 and 6 respectively. This study suggested that our scaffold-hopping approach was successful and these results are ongoing for further development.

Design, synthesis and pharmacological evaluation of N4,N6-disubstituted pyrimidine-4,6-diamine derivatives as potent EGFR inhibitors in non-small cell lung cancer

A novel series of 4, 6-disubstituted pyrimidines derivatives were designed, synthesized, and evaluated as epidermal growth factor receptor (EGFR) inhibitors for non-small cell lung cancer(NSCLC). 4, 6-disubstituted pyrimidines as core structure was utilized to substitute the lead structure AZD3759 of the quinazoline basic skeleton via an approach involving scaffold hopping. It was found that compound Yfq07 exhibited the best inhibitory effect compared with AZD3759 in vitro and in vivo: Yfq07 exhibited a competitive ATP inhibitory effect, multiple target effects, and further featured a stronger activity against H3255, A431, HCC827, PC-9 and H1975 compared to AZD3759. Moreover, a stronger pro-apoptotic effect, inhibition of cell G2/M phase on A431, H3255, HCC827 and H1975 could also be observed. In this study, the ultimate goal was changing the core structure to improve other epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) properties while retaining the overall potency. Yfq07 was further explored as an effective 4, 6-pyrimidine anticancer agent for the treatment of human NSCLC.

Novel Structural Insight into Inhibitors of Heme Oxygenase-1 (HO-1) by New Imidazole-Based Compounds: Biochemical and In Vitro Anticancer Activity Evaluation

In this paper, the design, synthesis, and molecular modeling of a new azole-based HO-1 inhibitors was reported, using compound 1 as a lead compound, in which an imidazole moiety is linked to a hydrophobic group by means of an ethanolic spacer. The tested compounds showed a good inhibitor activity and possessed IC₅₀ values in the micromolar range. These results were obtained by targeting the hydrophobic western region. Molecular modeling studies confirmed a consolidated binding mode in which the nitrogen of the imidazolyl moiety coordinated the heme ferrous iron, meanwhile the hydrophobic groups were located in the western region of HO-1 binding pocket. Moreover, the new compounds were screened for in silico ADME-Tox properties to predict drug-like behavior with convincing results. Finally, the in vitro antitumor activity profile of compound 1 was investigated in different cancer cell lines and nanomicellar formulation was synthesized with the aim of improving compound's 1 water solubility. Finally, compound 1 was tested in melanoma cells in combination with doxorubicin showing interesting synergic activity.

Synthesis, evaluation and CoMFA/CoMSIA study of nitrofuranyl methyl N-heterocycles as novel antitubercular agents

A series of novel nitrofuranyl methyl N-heterocycles based on the structure of IIIM-MCD-211 were designed and synthesized. Compounds 6d, 8b and 12a show excellent activity against MTB H37Rv strain (MIC: 0.031-0.062 μg/mL) roughly comparable to INH and IIIM-MCD-211. In addition, a three-dimensional quantitative structure-activity relationship (3D-QSAR) study was performed on the above mentioned chemical series employing comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) techniques. The developed CoMFA and CoMSIA models display high external predictability (r²_pred of 0.954 and 0.935, respectively) and good statistical robustness. More importantly, the newly designed compounds 16a and 16b (MIC: <0.016 μg/mL) based on the two models, as expected, were found to be more active than 12a and IIIM-MCD-21. Design and synthesis of more potent nitrofuranyl methyl N-heterocycles as anti-TB agents are currently in progress.