Discovery of new PKN2 inhibitory chemotypes via QSAR-guided selection of docking-based pharmacophores.

Serine/threonine-protein kinase N2 (PKN2) plays an important role in cell cycle progression, cell migration, cell adhesion and transcription activation signaling processes. In cancer, however, it plays important roles in tumor cell migration, invasion and apoptosis. PKN2 inhibitors have been shown to be promising in treating cancer. This prompted us to model this interesting target using our QSAR-guided selection of docking-based pharmacophores approach where numerous pharmacophores are extracted from docked ligand poses and allowed to compete within the context of QSAR. The optimal pharmacophore was sterically-refined, validated by receiver operating characteristic (ROC) curve analysis and used as virtual search query to screen the National Cancer Institute (NCI) database for new promising anti-PKN2 leads of novel chemotypes. Three low micromolar hits were identified with IC50 values ranging between 9.9 and 18.6 µM. Pharmacological assays showed promising cytotoxic properties for active hits in MTT and wound healing assays against MCF-7 and PANC-1 cancer cells.

Pharmacophoric analogs of sotorasib-entrapped KRAS G12C in its inactive GDP-bound conformation: covalent docking and molecular dynamics investigations.

For decades, KRAS G12C was considered an undruggable target. However, in recent times, a covalent inhibitor known as sotorasib was discovered and approved for the treatment of patients with KRAS G12C-driven cancers. Ever since the discovery of this drug, several preclinical efforts have focused on identifying novel therapeutic candidates that could act as covalent binders of KRAS G12C. Despite these intensive efforts, only a few KRAS G12C inhibitors have entered clinical trials. Hence, this highlights the need to develop effective drug candidates that could be used in the treatment of KRAS G12C-driven cancers. Herein, we embarked on a virtual screening campaign that involves the identification of pharmacophores of sotorasib that could act as covalent arsenals against the KRAS G12C target. To our knowledge, this is the first computational study that involves the compilation of sotorasib pharmacophores from an online chemical database against KRAS G12C. After this library of chemical entities was compiled, we conducted a covalent docking-based virtual screening that revealed three promising drug candidates (CID_146235944, CID_160070181, and CID_140956845) binding covalently to the crucial nucleophilic side chain of Cys12 and interact with the residues that form the cryptic allosteric pocket of KRAS G12C in its inactive GDP-bound conformation. Subsequently, ADMET profiling portrayed the covalent inhibitors as lead-like candidates, while 100 ns molecular dynamics was used to substantiate their stability. Although our overall computational study has shown the promising potential of the lead-like candidates in impeding oncogenic RAS signaling, more experimental efforts are needed to validate and establish their preclinical relevance. Implication of KRAS G12C in cancer and computational approach towards impeding the KRAS G12C RAS signaling.

Structural determinants of sphingosine-1-phosphate receptor selectivity.

Fingolimod, the prodrug of fingolimod-1-phosphate (F1P), was the first sphingosine-1-phosphate receptor (S1PR) modulator approved for multiple sclerosis. F1P unselectively targets all five S1PR subtypes. While agonism (functional antagonism via receptor internalization) at S1PR1 leads to the desired immune modulatory effects, agonism at S1PR3 is associated with cardiac adverse effects. This motivated the development of S1PR3 -sparing compounds and led to a second generation of S1PR1,5 -selective ligands like siponimod and ozanimod. Our method combines molecular dynamics simulations and three-dimensional pharmacophores (dynophores) and enables the elucidation of S1PR subtype-specific binding site characteristics, visualizing also subtle differences in receptor-ligand interactions. F1P and the endogenous ligand sphingosine-1-phosphate bind to the orthosteric pocket of all S1PRs, but show different binding mode dynamics, uncovering potential starting points for the development of subtype-specific ligands. Our study contributes to the mechanistic understanding of the selectivity profile of approved drugs like ozanimod and siponimod and pharmaceutical tool compounds like CYM5541.

Combining the Classification and Pharmacophore Approaches to Understand Homogeneous Olfactory Perceptions at Peripheral Level: Focus on Two Aroma Mixtures.

The mechanisms involved in the homogeneous perception of odorant mixtures remain largely unknown. With the aim of enhancing knowledge about blending and masking mixture perceptions, we focused on structure-odor relationships by combining the classification and pharmacophore approaches. We built a dataset of about 5000 molecules and their related odors and reduced the multidimensional space defined by 1014 fingerprints representing the structures to a tridimensional 3D space using uniform manifold approximation and projection (UMAP). The self-organizing map (SOM) classification was then performed using the 3D coordinates in the UMAP space that defined specific clusters. We explored the allocating in these clusters of the components of two aroma mixtures: a blended mixture (red cordial (RC) mixture, 6 molecules) and a masking binary mixture (isoamyl acetate/whiskey-lactone [IA/WL]). Focusing on clusters containing the components of the mixtures, we looked at the odor notes carried by the molecules belonging to these clusters and also at their structural features by pharmacophore modeling (PHASE). The obtained pharmacophore models suggest that WL and IA could have a common binding site(s) at the peripheral level, but that would be excluded for the components of RC. In vitro experiments will soon be carried out to assess these hypotheses.

Fragment hopping protocol for the design of small-molecule protein-protein interaction inhibitors.

Fragment-based ligand discovery (FBLD) is one of the most successful approaches to designing small-molecule protein-protein interaction (PPI) inhibitors. The incorporation of computational tools to FBLD allows the exploration of chemical space in a time- and cost-efficient manner. Herein, a computational protocol for the development of small-molecule PPI inhibitors using fragment hopping, a fragment-based de novo design approach, is described and a case study is presented to illustrate the efficiency of this protocol. Fragment hopping facilitates the design of PPI inhibitors from scratch solely based on key binding features in the PPI complex structure. This approach is an open system that enables the inclusion of different state-of-the-art programs and softwares to improve its performances.

Antibacterial Effects of Flavonoids and Their Structure-Activity Relationship Study: A Comparative Interpretation.

According to the latest report released by the World Health Organization, bacterial resistance to well-known and widely available antibacterial drugs has become a significant and severe global health concern and a grim challenge to tackle in order to cure infections associated with multidrug-resistant pathogenic microorganisms efficiently. Consequently, various strategies have been orchestrated to cure the severe complications related to multidrug-resistant bacteria effectively. Some approaches involved the retardation of biofilm formation and multidrug-resistance pumps in bacteria as well as the discovery of new antimicrobial agents demonstrating different mechanisms of action. In this regard, natural products namely alkaloids, terpenoids, steroids, anthraquinone, flavonoids, saponins, tannins, etc., have been suggested to tackle the multidrug-resistant bacterial strains owing to their versatile pharmacological effects. Amongst these, flavonoids, also known as polyphenolic compounds, have been widely evaluated for their antibacterial property due to their tendency to retard the growth of a wide range of pathogenic microorganisms, including multidrug-resistant bacteria. The hydroxylation of C5, C7, C3', and C4'; and geranylation or prenylation at C6 have been extensively studied to increase bacterial inhibition of flavonoids. On the other hand, methoxylation at C3' and C5 has been reported to decrease flavonoids' antibacterial action. Hence, the latest information on the antibacterial activity of flavonoids is summarized in this review, with particular attention to the structure-activity relationship of this broad class of natural compounds to discover safe and potent antibacterial agents as natural products.

Human Estrogen Receptor Alpha Antagonists, Part 3: 3-D Pharmacophore and 3-D QSAR Guided Brefeldin A Hit-to-Lead Optimization toward New Breast Cancer Suppressants.

The estrogen receptor α (ERα) is an important biological target mediating 17ß-estradiol driven breast cancer (BC) development. Aiming to develop innovative drugs against BC, either wild-type or mutated ligand-ERα complexes were used as source data to build structure-based 3-D pharmacophore and 3-D QSAR models, afterward used as tools for the virtual screening of National Cancer Institute datasets and hit-to-lead optimization. The procedure identified Brefeldin A (BFA) as hit, then structurally optimized toward twelve new derivatives whose anticancer activity was confirmed both in vitro and in vivo. Compounds as SERMs showed picomolar to low nanomolar potencies against ERα and were then investigated as antiproliferative agents against BC cell lines, as stimulators of p53 expression, as well as BC cell cycle arrest agents. Most active leads were finally profiled upon administration to female Wistar rats with pre-induced BC, after which 3DPQ-12, 3DPQ-3, 3DPQ-9, 3DPQ-4, 3DPQ-2, and 3DPQ-1 represent potential candidates for BC therapy.

Identification of Some Promising Heterocycles Useful in Treatment of Allergic Rhinitis: Virtual Screening, Pharmacophore Mapping, Molecular Docking, and Molecular Dynamics.

Rhinitis is an allergic disease that causes troubles and restlessness for patients. In this research work we will focus on finding promising organic molecules with potential ability to target histamine receptor with no sedative side effect. Phalazines and their isosteres, pyrimidines and pyridines have been reported to target H1 receptors, for this reason we have searched for library of these basic scaffolds, this library which has 184 organic molecules will be subjected for further explorations through computer aided drug design techniques. Swiss ADMET will be used to gather these compounds in clusters. Cluster with low potential to penetrate BBB is selected for virtual screening through pharmacophore model. Then molecular docking that revealed the stability of the complex formed between the investigated molecules and H1 receptor. ADMET profile showed three compounds (XVIII), (XX), and (XXI) with no toxicity on liver and no effect on CYP2D6, these three compounds were subjected to molecular dynamic simulations and compound (XVIII) showed the most stable complex with the target protein (H1). Finally, we can say this work helped us to find new compounds with promising potential to target H1 without ability to penetrate BBB, so they can be used as useful candidates in treatment of rhinitis and deserve to be subjected for preclinical and clinical investigations. Supplementary Information: The online version contains supplementary material available at 10.1134/S1068162022330019.

Estimating the accuracy of pharmacophore-based detection of cognate receptor-ligand pairs in the immunoglobulin superfamily.

Secreted and membrane-bound members of the immunoglobulin superfamily (IgSF) encompass a large, diverse array of proteins that play central roles in immune response and neural development, and are implicated in diseases ranging from cancer to rheumatoid arthritis. Despite the potential biomedical benefits of understanding IgSF:IgSF cognate receptor-ligand interactions, relatively little about them is known at a molecular level, and experimentally probing all possible receptor-ligand pairs is prohibitively costly. The Protein Ligand Interface Design (ProtLID) algorithm is a computational pharmacophore-based approach to identify cognate receptor-ligand pairs that was recently validated in a pilot study on a small set of IgSF complexes. Although ProtLID has shown a success rate of 61% at identifying at least one cognate ligand for a given receptor, it currently lacks any form of confidence measure that can prioritize individual receptor-ligand predictions to pursue experimentally. In this study, we expanded the application of ProtLID to cover all IgSF complexes with available structural data. In addition, we introduced an approach to estimate the confidence of predictions made by ProtLID based on a statistical analysis of how the ProtLID-constructed pharmacophore matches the structures of candidate ligands. The confidence score combines the physicochemical compatibility, spatial consistency, and mathematical skewness of the distribution of matches throughout a set of candidate ligands. Our results suggest that a subset of cases meeting stringent confidence criteria will always have at least one successful receptor-ligand prediction.

De Novo Design of Selective Quadruplex-Duplex Junction Ligands and Structural Characterisation of Their Binding Mode: Targeting the G4 Hot-Spot.

Targeting the interface between DNA quadruplex and duplex regions by small molecules holds significant promise in both therapeutics and nanotechnology. Herein, a new pharmacophore is reported, which selectively binds with high affinity to quadruplex-duplex junctions, while presenting a poorer affinity for G-quadruplex or duplex DNA alone. Ligands complying with the reported pharmacophore exhibit a significant affinity and selectivity for quadruplex-duplex junctions, including the one observed in the HIV-1 LTR-III sequence. The structure of the complex between a quadruplex-duplex junction with a ligand of this family has been determined by NMR methods. According to these data, the remarkable selectivity of this structural motif for quadruplex-duplex junctions is achieved through an unprecedented interaction mode so far unexploited in medicinal and biological chemistry: the insertion of a benzylic ammonium moiety into the centre of the partially exposed G-tetrad at the interface with the duplex. Further decoration of the described scaffolds with additional fragments opens up the road to the development of selective ligands for G-quadruplex-forming regions of the genome.

Structural exploration of multifunctional monoamine oxidase B inhibitors as potential drug candidates against Alzheimer's disease.

AD is one of the most typical neurodegenerative disorders that suffer many seniors worldwide. Recently, MAO inhibitors have received increasing attention not only for their roles involved in monoamine neurotransmitters metabolism and oxidative stress but also for their additional neuroprotective and neurorescue effects against AD. The curiosity in MAO inhibitors is reviving, and novel MAO-B inhibitors recently developed with ancillary activities (e.g., Aß aggregation and AChE inhibition, anti-ROS and chelating activities) have been proposed as multitarget drugs foreshadowing a positive outlook for the treatment of AD. The current review describes the recent development of the design, synthesis, and screening of multifunctional ligands based on MAO-B inhibition for AD therapy. Structure-activity relationships and rational design strategies of the synthetic or natural product derivatives (chalcones, coumarins, chromones, and homoisoflavonoids) are discussed.

Mechanistic and Predictive QSAR Analysis of Diverse Molecules to Capture Salient and Hidden Pharmacophores for Anti-Thrombotic Activity.

Thrombosis is a life-threatening disease with a high mortality rate in many countries. Even though anti-thrombotic drugs are available, their serious side effects compel the search for safer drugs. In search of a safer anti-thrombotic drug, Quantitative Structure-Activity Relationship (QSAR) could be useful to identify crucial pharmacophoric features. The present work is based on a larger data set comprising 1121 diverse compounds to develop a QSAR model having a balance of acceptable predictive ability (Predictive QSAR) and mechanistic interpretation (Mechanistic QSAR). The developed six parametric model fulfils the recommended values for internal and external validation along with Y-randomization parameters such as R2tr = 0.831, Q2LMO = 0.828, R2ex = 0.783. The present analysis reveals that anti-thrombotic activity is found to be correlated with concealed structural traits such as positively charged ring carbon atoms, specific combination of aromatic Nitrogen and sp2-hybridized carbon atoms, etc. Thus, the model captured reported as well as novel pharmacophoric features. The results of QSAR analysis are further vindicated by reported crystal structures of compounds with factor Xa. The analysis led to the identification of useful novel pharmacophoric features, which could be used for future optimization of lead compounds.

Predicting Potential Endocrine Disrupting Chemicals Binding to Estrogen Receptor α (ERα) Using a Pipeline Combining Structure-Based and Ligand-Based in Silico Methods.

The estrogen receptors α (ERα) are transcription factors involved in several physiological processes belonging to the nuclear receptors (NRs) protein family. Besides the endogenous ligands, several other chemicals are able to bind to those receptors. Among them are endocrine disrupting chemicals (EDCs) that can trigger toxicological pathways. Many studies have focused on predicting EDCs based on their ability to bind NRs; mainly, estrogen receptors (ER), thyroid hormones receptors (TR), androgen receptors (AR), glucocorticoid receptors (GR), and peroxisome proliferator-activated receptors gamma (PPARγ). In this work, we suggest a pipeline designed for the prediction of ERα binding activity. The flagged compounds can be further explored using experimental techniques to assess their potential to be EDCs. The pipeline is a combination of structure based (docking and pharmacophore models) and ligand based (pharmacophore models) methods. The models have been constructed using the Environmental Protection Agency (EPA) data encompassing a large number of structurally diverse compounds. A validation step was then achieved using two external databases: the NR-DBIND (Nuclear Receptors DataBase Including Negative Data) and the EADB (Estrogenic Activity DataBase). Different combination protocols were explored. Results showed that the combination of models performed better than each model taken individually. The consensus protocol that reached values of 0.81 and 0.54 for sensitivity and specificity, respectively, was the best suited for our toxicological study. Insights and recommendations were drawn to alleviate the screening quality of other projects focusing on ERα binding predictions.

A brief overview on recent advances in spiro[chromane-2,4'-piperidine]-4(3H)-one-functionalized compounds in medicinal chemistry research.

The spiro[chromane-2,4'-piperidine]-4(3H)-one is an important pharmacophore. It is a structural component in many drugs, drug candidates (or lead compounds) and various biochemical reagents. This review demonstrated an impressive progress in syntheses of spiro[chromane-2,4'-piperidine]-4(3H)-one-derived compoundsin the recent years and focuses on features of their biological relevance's. The prospects for the development of new biologically active substances containing a spiro[chromane-2,4'-piperidine]-4(3H)-one pharmacophore are analyzed and briefly discussed in terms of its structure, reaction, mechanism, scope and potential utility.

Combining carbonic anhydrase and thioredoxin reductase inhibitory motifs within a single molecule dramatically increases its cytotoxicity.

A hypothesis that simultaneous targeting cancer-related carbonic anhydrase hCA IX and hCA XII isoforms (whose overexpression is a cancer cell's defence mechanism against hypoxia) along with thioredoxin reductase (overexpressed in cancers as a defence against oxidative stress) may lead to synergistic antiproliferative effects was confirmed by testing combinations of the two inhibitor classes against pancreatic cancer cells (PANC-1). Combining both pharmacophoric motifs within one molecule led to a sharp increase of cytotoxicity. This preliminary observation sets the ground for a fundamentally new approach to anticancer agent design.

Discovery of Novel Hsp90 C-Terminal Inhibitors Using 3D-Pharmacophores Derived from Molecular Dynamics Simulations.

Hsp90 C-terminal domain (CTD) inhibitors are promising novel agents for cancer treatment, as they do not induce the heat shock response associated with Hsp90 N-terminal inhibitors. One challenge associated with CTD inhibitors is the lack of a co-crystallized complex, requiring the use of predicted allosteric apo pocket, limiting structure-based (SB) design approaches. To address this, a unique approach that enables the derivation and analysis of interactions between ligands and proteins from molecular dynamics (MD) trajectories was used to derive pharmacophore models for virtual screening (VS) and identify suitable binding sites for SB design. Furthermore, ligand-based (LB) pharmacophores were developed using a set of CTD inhibitors to compare VS performance with the MD derived models. Virtual hits identified by VS with both SB and LB models were tested for antiproliferative activity. Compounds 9 and 11 displayed antiproliferative activities in MCF-7 and Hep G2 cancer cell lines. Compound 11 inhibited Hsp90-dependent refolding of denatured luciferase and induced the degradation of Hsp90 clients without the concomitant induction of Hsp70 levels. Furthermore, compound 11 offers a unique scaffold that is promising for the further synthetic optimization and development of molecules needed for the evaluation of the Hsp90 CTD as a target for the development of anticancer drugs.

Medicinal Chemistry Targeting Mitochondria: From New Vehicles and Pharmacophore Groups to Old Drugs with Mitochondrial Activity.

Interest in tumor cell mitochondria as a pharmacological target has been rekindled in recent years. This attention is due in part to new publications documenting heterogenous characteristics of solid tumors, including anoxic and hypoxic zones that foster cellular populations with differentiating metabolic characteristics. These populations include tumor-initiating or cancer stem cells, which have a strong capacity to adapt to reduced oxygen availability, switching rapidly between glycolysis and oxidative phosphorylation as sources of energy and metabolites. Additionally, this cell subpopulation shows high chemo- and radioresistance and a high capacity for tumor repopulation. Interestingly, it has been shown that inhibiting mitochondrial function in tumor cells affects glycolysis pathways, cell bioenergy, and cell viability. Therefore, mitochondrial inhibition may be a viable strategy for eradicating cancer stem cells. In this context, medicinal chemistry research over the last decade has synthesized and characterized "vehicles" capable of transporting novel or existing pharmacophores to mitochondrial tumor cells, based on mechanisms that exploit the physicochemical properties of the vehicles and the inherent properties of the mitochondria. The pharmacophores, some of which have been isolated from plants and others, which were synthesized in the lab, are diverse in chemical nature. Some of these molecules are active, while others are prodrugs that have been evaluated alone or linked to mitochondria-targeted agents. Finally, researchers have recently described drugs with well-proven safety and efficacy that may exert a mitochondria-specific inhibitory effect in tumor cells through noncanonical mechanisms. The effectiveness of these molecules may be improved by linking them to mitochondrial carrier molecules. These promising pharmacological agents should be evaluated alone and in combination with classic chemotherapeutic drugs in clinical studies.

Synthesis and Cytotoxic Activity of New Vindoline Derivatives Coupled to Natural and Synthetic Pharmacophores.

New Vinca alkaloid derivatives were synthesized to improve the biological activity of the natural alkaloid vindoline. To this end, experiments were performed to link vindoline with various structural units, such as amino acids, a 1,2,3-triazole derivative, morpholine, piperazine and N-methylpiperazine. The structure of the new compounds was characterized by NMR spectroscopy and mass spectrometry (MS). Several compounds exhibited in vitro antiproliferative activity against human gynecological cancer cell lines with IC50 values in the low micromolar concentration range.

Probabilistic Approach for Virtual Screening Based on Multiple Pharmacophores.

Pharmacophore modeling is usually considered as a special type of virtual screening without probabilistic nature. Correspondence of at least one conformation of a molecule to pharmacophore is considered as evidence of its bioactivity. We show that pharmacophores can be treated as one-class machine learning models, and the probability the reflecting model's confidence can be assigned to a pharmacophore on the basis of their precision of active compounds identification on a calibration set. Two schemes (Max and Mean) of probability calculation for consensus prediction based on individual pharmacophore models were proposed. Both approaches to some extent correspond to commonly used consensus approaches like the common hit approach or the one based on a logical OR operation uniting hit lists of individual models. Unlike some known approaches, the proposed ones can rank compounds retrieved by multiple models. These approaches were benchmarked on multiple ChEMBL datasets used for ligand-based pharmacophore modeling and externally validated on corresponding DUD-E datasets. The influence of complexity of pharmacophores and their performance on a calibration set on results of virtual screening was analyzed. It was shown that Max and Mean approaches have superior early enrichment to the commonly used approaches. Thus, a well-performing, easy-to-implement, and probabilistic alternative to existing approaches for pharmacophore-based virtual screening was proposed.

Metabolic-Hydroxy and Carboxy Functionalization of Alkyl Moieties in Drug Molecules: Prediction of Structure Influence and Pharmacologic Activity.

Alkyl moieties-open chain or cyclic, linear, or branched-are common in drug molecules. The hydrophobicity of alkyl moieties in drug molecules is modified by metabolic hydroxy functionalization via free-radical intermediates to give primary, secondary, or tertiary alcohols depending on the class of the substrate carbon. The hydroxymethyl groups resulting from the functionalization of methyl groups are mostly oxidized further to carboxyl groups to give carboxy metabolites. As observed from the surveyed cases in this review, hydroxy functionalization leads to loss, attenuation, or retention of pharmacologic activity with respect to the parent drug. On the other hand, carboxy functionalization leads to a loss of activity with the exception of only a few cases in which activity is retained. The exceptions are those groups in which the carboxy functionalization occurs at a position distant from a well-defined primary pharmacophore. Some hydroxy metabolites, which are equiactive with their parent drugs, have been developed into ester prodrugs while carboxy metabolites, which are equiactive to their parent drugs, have been developed into drugs as per se. In this review, we present and discuss the above state of affairs for a variety of drug classes, using selected drug members to show the effect on pharmacologic activity as well as dependence of the metabolic change on drug molecular structure. The review provides a basis for informed predictions of (i) structural features required for metabolic hydroxy and carboxy functionalization of alkyl moieties in existing or planned small drug molecules, and (ii) pharmacologic activity of the metabolites resulting from hydroxy and/or carboxy functionalization of alkyl moieties.