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

Recent Advances on Small-Molecule Inhibitors of Lipocalin-like Proteins

Lipid transfer proteins (LTPs) are crucial players in nonvesicular lipid trafficking. LTPs sharing a lipocalin lipid transfer domain (lipocalin-like proteins) have a wide range of biological functions, such as regulating immune responses and cell proliferation, differentiation, and death as well as participating in the pathogenesis of inflammatory, metabolic, and neurological disorders and cancer. Therefore, the development of small-molecule inhibitors targeting these LTPs is important and has potential clinical applications. Herein, we summarize the structure and function of lipocalin-like proteins, mainly including retinol-binding proteins, lipocalins, and fatty acid-binding proteins and discuss the recent advances on small-molecule inhibitors for these protein families and their applications in disease treatment. The findings of our Perspective can provide guidance for the development of inhibitors of these LTPs and highlight the challenges that might be faced during the procedures.

Optimization of 4-amino-pyridazin-3(2H)-one as a valid core scaffold for FABP4 inhibitors

Current clinical research suggests that fatty acid-binding protein 4 inhibitors (FABP4is), which are of biological and therapeutic interest, may show potential in treating cancer and other illnesses. We sought to uncover new structures through the optimization of the previously reported 4-amino and 4-ureido pyridazinone-based series of FABP4is as part of a larger research effort to create more potent FABP4 inhibitors. This led to the identification of 14e as the most potent analog with IC50  = 1.57 μM, which is lower than the IC50 of the positive control. Advanced modeling investigations and in silico absorption, distribution, metabolism, and excretion - toxicity calculations suggested that 14e represents a potential candidate for in vivo studies such as FABP4i.

Steered Molecular Dynamics Simulations Study on FABP4 Inhibitors

Ordinary small molecule de novo drug design is time-consuming and expensive. Recently, computational tools were employed and proved their efficacy in accelerating the overall drug design process. Molecular dynamics (MD) simulations and a derivative of MD, steered molecular dynamics (SMD), turned out to be promising rational drug design tools. In this paper, we report the first application of SMD to evaluate the binding properties of small molecules toward FABP4, considering our recent interest in inhibiting fatty acid binding protein 4 (FABP4). FABP4 inhibitors (FABP4is) are small molecules of therapeutic interest, and ongoing clinical studies indicate that they are promising for treating cancer and other diseases such as metabolic syndrome and diabetes.

Profiling the Structural determinants of pyrrolidine derivative as gelatinases (MMP-2 and MMP-9) inhibitors using in silico approaches

Quantitative structure activity relationship (QSAR) studies on pyrrolidine derivatives have been established using CoMFA, CoMSIA, and Hologram QSAR analysis to estimate the values (pIC₅₀) of gelatinase inhibitors. When the CoMFA cross-validation value, Q², was 0.625, the training set coefficient of determination, R² was 0.981. In CoMSIA, Q² was 0.749 and R² was 0.988. In the HQSAR, Q² was 0.84 and R² was 0.946. Visualization of these models was performed by contour maps showing favorable and unfavorable regions for activity, while visualization of HQSAR model was performed by a colored atomic contribution graph. Based on the results obtained of external validation, the CoMSIA model was statistically more significant and robust and was selected as the best model to predict new, more active inhibitors. To study the modes of interactions of the predicted compounds in the active site of MMP-2 and MMP-9, a simulation of molecular docking was realized. A combined study of MD simulations and calculation of free binding energy, were also carried out to validate the results obtained on the best predicted and most active compound in dataset and the compound NNGH as control compound. The results confirm the molecular docking results and indicate that the predicted ligands were stable in the binding site of MMP-2 and MMP-9.

Designing of new tetrahydro-β-carboline-based ABCG2 inhibitors using 3D-QSAR, molecular docking, and DFT tools

Human ATP-binding cassette superfamily G member 2 (ABCG2) protein is a member of the ABC transporter family, which is responsible for multidrug resistance (MDR) in cancerous cells. MDR reduces the effectiveness of chemotherapy in breast cancer, which is one of the leading causes of death in women globally. MDR in cancer cells is one of the immediate signs of progression of resistance; thus, various anticancer drugs can be designed. To reduce MDR, we utilized the tetrahydro-β-carboline (THβC) compound library. We accomplished a three-dimensional quantitative structure-activity relationship (3D-QSAR), scaffold hopping to design a new library of compounds of THβC, and further molecular docking, induced-fit docking (IFD), molecular mechanics energies combined with generalized born and surface area continuum solvation (MM-GBSA), drug-like features, ADMET properties, and density functional theory (DFT) studies were performed. From these studies, the best 3D-QSAR model (r2 = 0.99, q2 = 0.92) was found, and the necessity of electrostatic, steric, and hydrophobic field effects were determined that could modulate bioactivity. Moreover, based on electrostatic, steric, and hydrophobic field notations, new THβC derivatives (3409) were designed. These findings might provide new insight for researchers to perform in vitro and in vivo studies for better antagonists against MDR in treating breast cancer.Communicated by Ramaswamy H. Sarma.

Genipin Attenuates Diabetic Cognitive Impairment by Reducing Lipid Accumulation and Promoting Mitochondrial Fusion via FABP4/Mfn1 Signaling in Microglia

The present study was conducted to evaluate the effect of genipin (GEN) on the microglia of diabetic cognitive impairment and explore its potential mechanism. Diabetic mice were induced by STZ/HFD, while GEN was intragastrically and intraventricularly treated. The human microglia cell HMC3 was induced by LPS/HG/PA. As a result, GEN attenuated diabetic symptoms and diabetic cognitive impairment-related behavior in novel object recognition, Morris water maze and passive avoidance tests. GEN inhibited M1 microglia polarization, lipid accumulation, oxidative stress and promoted mitochondrial fusion via FABP4/Mfn1. FABP4 overexpression, Mfn1 overexpression, selective FABP4 inhibitor BMS, and Mfn1 SiRNA were employed for investigating the mechanism. The inhibitory effect of GEN on ROS may be associated with NOX2 signaling and the translocation of p47phox/p67phox to the cell membrane. With the ROS scavenger NAC, it was proved that ROS participated in GEN-mediated inflammation and lipid accumulation. GEN inhibited the phosphorylation and nucleus translocation of NF-κB. GEN inhibited the ubiquitination of Mfn1, which was mediated by the E3 ligase Hrd1. GEN also enhanced microglia phagocytosis. Molecular docking predicted that GEN may interact with FABP4 by hydrogen bond at the S53 and R78 residues. In conclusion, GEN attenuated diabetic cognitive impairment by inhibiting inflammation, lipid accumulation and promoting mitochondrial fusion via FABP4/Mfn1 signaling.

Ligand Growing Experiments Suggested 4-amino and 4-ureido pyridazin-3(2H)-one as Novel Scaffold for FABP4 Inhibition

Fatty acid binding protein (FABP4) inhibitors are of synthetic and therapeutic interest and ongoing clinical studies indicate that they may be a promise for the treatment of cancer, as well as other diseases. As part of a broader research effort to develop more effective FABP4 inhibitors, we sought to identify new structures through a two-step computing assisted molecular design based on the established scaffold of a co-crystallized ligand. Novel and potent FABP4 inhibitors have been developed using this approach and herein we report the synthesis, biological evaluation and molecular docking of the 4-amino and 4-ureido pyridazinone-based series.

Fatty acid-binding protein 4 in kidney diseases: From mechanisms to clinics

Considerable evidence indicated the relationship between fatty acid-binding protein 4 (FABP4) and kidney diseases. FABP4, a small molecular lipid chaperone, is identified to regulate fatty acid oxidation, inflammation, apoptosis, endoplasmic reticulum stress and macrophage-to-myofibroblast transition in kidney diseases. Many studies have shown that circulating FABP4 level is related to proteinuria, renal function decline, cardiovascular complications of end-stage renal disease and even the prognosis of kidney transplanted patients. Notably, pharmacological or genetic inhibition of FABP4 attenuated renal injury in the various experimental models of kidney diseases, making it promising to develop potential therapeutic strategies targeting FABP4 in kidney diseases. In this study, we updated and reviewed the mechanisms and clinical significance of FABP4 in kidney diseases.

Adipocyte fatty acid binding protein 4 (FABP4) inhibitors. An update from 2017 to early 2022

The fatty acid binding protein 4 (FABP4) is a protein predominantly expressed in macrophages and adipose tissue, where it regulates fatty acids storage and lipolysis and is an essential mediator of inflammation. Small molecule inhibitors of FABP4 have attracted interest following the recent publications of beneficial pharmacological effects of these compounds for the treatment of metabolic syndrome and, more recently, for other pathologies. Since the synthesis of the BMS309403, one of the first selective and effective FABP4 inhibitors, hundreds of other inhibitors have been synthesized (i.e., derivatives of niacin, quinoxaline, aryl-quinoline, bicyclic pyridine, urea, aromatic compounds and other novel heterocyclic compounds). This review updates the recently reported (2017 to early 2022) molecules as adipocyte fatty acid binding protein 4 inhibitors.

Artificial Intelligence Technologies for COVID-19 De Novo Drug Design

The recent covid crisis has provided important lessons for academia and industry regarding digital reorganization. Among the fascinating lessons from these times is the huge potential of data analytics and artificial intelligence. The crisis exponentially accelerated the adoption of analytics and artificial intelligence, and this momentum is predicted to continue into the 2020s and beyond. Drug development is a costly and time-consuming business, and only a minority of approved drugs generate returns exceeding the research and development costs. As a result, there is a huge drive to make drug discovery cheaper and faster. With modern algorithms and hardware, it is not too surprising that the new technologies of artificial intelligence and other computational simulation tools can help drug developers. In only two years of covid research, many novel molecules have been designed/identified using artificial intelligence methods with astonishing results in terms of time and effectiveness. This paper reviews the most significant research on artificial intelligence in de novo drug design for COVID-19 pharmaceutical research.

Structural derivatization strategies of natural phenols by semi-synthesis and total-synthesis

Structural derivatization of natural products has been a continuing and irreplaceable source of novel drug leads. Natural phenols are a broad category of natural products with wide pharmacological activity and have offered plenty of clinical drugs. However, the structural complexity and wide variety of natural phenols leads to the difficulty of structural derivatization. Skeleton analysis indicated most types of natural phenols can be structured by the combination and extension of three common fragments containing phenol, phenylpropanoid and benzoyl. Based on these fragments, the derivatization strategies of natural phenols were unified and comprehensively analyzed in this review. In addition to classical methods, advanced strategies with high selectivity, efficiency and practicality were emphasized. Total synthesis strategies of typical fragments such as stilbenes, chalcones and flavonoids were also covered and analyzed as the supplementary for supporting the diversity-oriented derivatization of natural phenols.

Synthesis and inverse virtual screening of new bi-cyclic structures towards cancer-relevant cellular targets

We report here synthetic approaches to access new classes of small molecules based on three heterocyclic scaffolds, i.e. 3,7-dihydropyrimido[4,5-d]pyridazine-4,8-dione, 1,8-naphthyridin-4(1H)-one and 4H-pyrido[1,2-a]pyrimidin-4-one. The bi-cyclic structure 3,7-dihydropyrimido[4,5-d]pyridazine-4,8-dione is a new heterocycle, described here for the first time. In silico methodologies of inverse virtual screening have been used to preliminary analyse the molecules, in order to explore their potential as hits for chemical biology investigations. Our computational study has been conducted with 43 synthetically accessible small molecules towards 31 cellular proteins involved in cancer pathogenesis. Binding energies were quantified using molecular docking calculations, allowing to define the relative affinities of the ligands for the cellular targets. Through this methodology, 16 proteins displayed effective interactions with distinct small molecules within the matrix. In addition, 23 ligands have demonstrated high affinity for at least one cellular protein, using as reference the co-crystallised ligand in the X-ray structure. The evaluation of ADME and drug score for selected hits also highlights that these new molecular series can serve as sources of lead candidates for further structure optimisation and biological studies.

Synthesis and in vitro evaluation of chlorogenic acid amides as potential hypoglycemic agents and their synergistic effect with acarbose

Type 2 Diabetes mellitus is a chronic disease considered one of the most severe global health emergencies. Chlorogenic acid (1) has been shown to delay intestinal glucose absorption by inhibiting the activity of α-glucosidase (α-Glu) and α-amylase (α-Amy). In the present work, eleven chlorogenic acid amides have been synthesized and evaluated for their antioxidant properties (as DPPH and ORAC) and inhibition activity towards the two enzymes and, with the aim to obtain dual-action antidiabetic agents. The two most promising hypoglycemic compounds, bearing a tertiary amine function on an alkyl chain (8) and a benzothiazole scaffold (11), showed IC₅₀ values lower than that of (1) (45.5 µM α-Glu; 105.2 µM α-Amy). Amides 8 and 11 were by far more potent α-Glu inhibitors than the antidiabetic drug acarbose (IC₅₀ = 268.4 µM) and about twice less active toward α-Amy than acarbose (IC₅₀ = 34.4 µM). Kinetics experiments on amides 8 and 11 indicated these compounds as mixed-type inhibitors of α-Glu with K'_i values of 13.3 and 6.3 µM, respectively. The amylase inhibition occurred with a competitive mechanism in the presence of 8 (K_i = 79.7 µM) and with a mixed-type mechanism with 11 (K_i = 19.1 µM; K'_i = 93.6 µM). Molecular docking analyses supported these results, highlighting the presence of additional binding sites in both enzymes. Fluorescence experiments confirmed the grater affinity of amides 8 and 11 towards the two enzymes respect to (1). Moreover, a significant enhancement in acarbose efficacy was observed when inhibition assays were performed adding acarbose and amide 11. The above outcomes pinpointed the benzothiazole-based amide 11 as a promising candidate for further studies on type 2 diabetes treatment, both alone or combined with acarbose.

Four-Step Domino Reaction Enables Fully Controlled Non-Statistical Synthesis of Hexaarylbenzene with Six Different Aryl Groups*

Hexaarylbenzene (HAB) derivatives are versatile aromatic systems playing a significant role as chromophores, liquid crystalline materials, molecular receptors, molecular-scale devices, organic light-emitting diodes and candidates for organic electronics. Statistical synthesis of simple symmetrical HABs is known via cyclotrimerization or Diels-Alder reactions. By contrast, the synthesis of more complex, asymmetrical systems, and without involvement of statistical steps, remains an unsolved problem. Here we present a generally applicable synthetic strategy to access asymmetrical HAB via an atom-economical and high-yielding metal-free four-step domino reaction using nitrostyrenes and α,α-dicyanoolefins as easily available starting materials. Resulting domino product-functionalized triarylbenzene (TAB)-can be used as a key starting compound to furnish asymmetrically substituted hexaarylbenzenes in high overall yield and without involvement of statistical steps. This straightforward domino process represents a distinct approach to create diverse and still unexplored HAB scaffolds, containing six different aromatic rings around central benzene core.

Discovery of Novel Acetamide-Based Heme Oxygenase-1 Inhibitors with Potent In Vitro Antiproliferative Activity

Heme oxygenase-1 (HO-1) promotes heme catabolism exercising cytoprotective roles in normal and cancer cells. Herein, we report the design, synthesis, molecular modeling, and biological evaluation of novel HO-1 inhibitors. Specifically, an amide linker in the central spacer and an imidazole were fixed, and the hydrophobic moiety required by the pharmacophore was largely modified. In many tumors, overexpression of HO-1 correlates with poor prognosis and chemoresistance, suggesting the inhibition of HO-1 as a possible antitumor strategy. Accordingly, compounds 7i and 7l-p emerged for their potency against HO-1 and were investigated for their anticancer activity against prostate (DU145), lung (A549), and glioblastoma (U87MG, A172) cancer cells. The selected compounds showed the best activity toward U87MG cells. Compound 7l was further investigated for its in-cell enzymatic HO-1 activity, expression levels, and effects on cell invasion and vascular endothelial growth factor (VEGF) extracellular release. The obtained data suggest that 7l can reduce cell invasivity acting through modulation of HO-1 expression.

Machine learning vs. field 3D-QSAR models for serotonin 2A receptor psychoactive substances identification

Serotonergic psychedelics, substances exerting their effects primarily through the serotonin 2A receptor (5HT2AR), continue to comprise a substantial portion of reported new psychoactive substances (NPS). In this paper five quantitative structure-activity relationship (QSAR) models for predicting the affinity of 5-HT2AR ligands have been developed. The resulting models, exploiting the accessibility of the QSAR equations, generate a useful tool for the investigation and identification of unclassified molecules. The models have been built using a set of 375 molecules using Forge software, and the quality was confirmed by statistical analysis, resulting in effective tools with respect to their predictive and descriptive capabilities. The best performing algorithm among the machine learning approaches and the classical field 3D-QSAR model were then combined to produce a consensus model and were exploited, together with a pharmacophorefilter, to explore the 5-HT2AR activity of 523 105 natural products, to classify a set of recently reported 5-HT2AR NPS and to design new potential active molecules. The findings of this study should facilitate the identification and classification of emerging 5-HT2AR ligands including NPS.

Effects of the histone acetylase inhibitor C646 on growth and differentiation of adipose-derived stem cells

As an important histone acetylase, the transcriptional coactivator P300/CBP affects target gene expression and plays a role in the maintenance of stem cell characteristics and differentiation potential. In this study, we explored the action of a highly effective selective histone acetylase inhibitor, C646, on goat adipose-derived stem cells (gADSCs), and investigated the impact of histone acetylation on the growth characteristics and the differentiation potential of ADSCs. We found that C646 blocked the cell proliferation, arrested the cell cycle, and triggered apoptosis. Notably, immunocytochemistry and western blot analyses showed that the acetylation level of histone H3K9 was increased. Moreover, although real-time quantitative PCR and western blot confirmed that P300 expression was inhibited under these conditions, the expression level of two other histone acetylases, TIP60 and PCAF, was significantly increased. Furthermore, C646 clearly promoted the differentiation of gADSCs into adipocytes and had an impact on their differentiation into neuronal cells. This study provides new insights into the epigenetic regulation of stem cell differentiation and may represent an experimental basis for the comprehension of stem cell characteristics and function. Furthermore, it is of great relevance for the application of adult stem cells to somatic cell cloning, which may improve the efficiency of large livestock cloning and foster the production of transgenic animals.

An Integrated Pharmacophore/Docking/3D-QSAR Approach to Screening a Large Library of Products in Search of Future Botulinum Neurotoxin A Inhibitors

Botulinum toxins are neurotoxins produced by Clostridium botulinum. This toxin can be lethal for humans as a cause of botulism; however, in small doses, the same toxin is used to treat different conditions. Even if the therapeutic doses are effective and safe, the adverse reactions could be local and could unmask a subclinical impairment of neuromuscular transmissions. There are not many cases of adverse events in the literature; however, it is possible that sometimes they do not occur as they are transient and, if they do occur, there is no possibility of a cure other than to wait for the pharmacological effect to end. Inhibition of botulinum neurotoxin type A (BoNT/A) effects is a strategy for treating botulism as it can provide an effective post-exposure remedy. In this paper, 13,592,287 compounds were screened through a pharmacophore filter, a 3D-QSAR model, and a virtual screening; then, the compounds with the best affinity were selected. Molecular dynamics simulation studies on the first four compounds predicted to be the most active were conducted to verify that the poses foreseen by the docking were stable. This approach allowed us to identify compounds with a calculated inhibitory activity in the range of 316–500 nM.

Repurposing strategies on pyridazinone-based series by pharmacophore- and structure-driven screening

We report here in silico repurposing studies on 52 new pyridazinone-based small-molecules through inverse virtual screening (iVS) methodologies. These analogues were originally designed as formyl peptide receptor (FPR) ligands. As it is sometimes the case in drug discovery programmes, subsequent biological screening demonstrated the inefficacy of the molecules in binding FPRs, failing in the identification of new hits. Through a focussed drug-repurposing approach we have defined a variety of potential targets that are suitable to interact with this library of pyridazinone-based analogues. A two-step approach has been conducted for computational analysis. Specifically, the molecules were initially processed through a pharmacophore-based screening. Secondly, the resulting features of binding were investigated by docking studies and following molecular dynamic simulations, in order to univocally confirm "pyridazinone-based ligand-target protein" interactions. Our findings propose aspartate aminotransferase as the most favourable repurposed target for this small-molecule series, worth of additional medicinal chemistry investigations in the field.

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.

Identification of new dual FABP4/5 inhibitors based on a naphthalene-1-sulfonamide FABP4 inhibitor

Fatty acid binding protein 4 (FABP4) and fatty acid binding protein 5 (FABP5) are mainly expressed in adipocytes and/or macrophages and play essential roles in energy metabolism and inflammation. When FABP4 function is diminished, FABP5 expression is highly increased possibly as a functional compensation. Dual FABP4/5 inhibitors are expected to provide beneficial synergistic effect on treating diabetes, atherosclerosis, and inflammation-related diseases. Starting from our previously reported selective FABP4 inhibitor 8, structural biology information was used to modulate the selectivity profile and to design potent dual FABP4/5 inhibitors with good selectivity against FABP3. Two compounds A16 and B8 were identified to show inhibitory activities against both FABP4/5 and good selectivity over FABP3, which could also reduce the level of forskolin-stimulated lipolysis in mature 3T3-L1 adipocytes. Compared with compound 8, these two compounds exhibited better anti-inflammatory effects in lipopolysaccharide-stimulated RAW264.7 murine macrophages, with decreased levels of pro-inflammatory cytokines TNFα and MCP-1 and apparently inhibited IKK/NF-κB pathway.

Virtual identification of novel peroxisome proliferator-activated receptor (PPAR) α/δ dual antagonist by 3D-QSAR, molecule docking, and molecule dynamics simulation

The therapeutic potential of PPARs antagonists extends beyond diabetes. PPARs antagonists represent a new drug class that holds promise as a broadly applicable therapeutic approach for cancer treatment. Thus, there is a strong need to develop a rational design strategy for creating PPARs antagonists. In this study, three-dimensional quantitative structure-activity relationship (3D-QSAR) models of PPARα receptor (CoMFA-1, q ² = 0.636, r ² = 0.953; CoMSIA-1, q ² = 0.779, r ² = 0.999) and PPARδ receptor (CoMFA-2, q ² = 0.624, r ² = 0.906; CoMSIA-2, q ² = 0.627, r ² = 0.959) were successfully constructed using 35 triazolone ring derivatives. Contour map analysis revealed that the electrostatic and hydrophobic fields played vital roles in the bioactivity of dual antagonists. Molecular docking studies suggested that the hydrogen bonding, electrostatic and hydrophobic interactions all influenced the binding of receptor-ligand complex. Based on the information obtained above, we designed a series of compounds. The docking results were mutually validated with 3D-QSAR results. Three-dimensional-QSAR and absorption, distribution, metabolism, excretion and toxicity (ADMET) predictions indicated that 19 newly designed compounds possessed excellent biological activity and physicochemical properties. In summary, this research could provide theoretical guidance for the structural optimization of novel PPARα and δ dual antagonists. Communicated by Ramaswamy H. Sarma.

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.

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.

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.

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).