Automated selection of compounds with physicochemical properties to maximize bioavailability and druglikeness

In silico evaluation of binding interaction and ADME study of new 1,3-diazetidin-2-one derivatives with high antiproliferative activity

A series of eight novels' 1,3-diazetidin-2-ones have been proposed to assess their potential activities. They are intended to examine antiproliferative effects through inhibition of epidermal growth factor receptor (EGFR) expression. These eight compounds strongly interact with the EGFR protein, responsible for the activity. As part of a present study, these compounds were docked to the crystal structure of the EGFR (Protein Data Bank code: 1 M17) to determine their binding affinity at the active site. Based on computer predictions, two compounds were demonstrated high scores of 80.80 and 85.89. After analyzing ADME properties, these compounds were found to have significant potential for binding. Consequently, the abilities of gefitinib, erlotinib, imatinib, and sorafenib were selected for comparison as controls. Computational methods were performed to predict the critical disposition of eight novels' 1,3-diazetidin-2-one derivatives to the EGFR. Moreover, a docking technique employing the Genetic Optimization for Ligand Docking program was conducted. Compounds 2 and 7 demonstrate a high docking peace-wise scoring function (PLP) fitness of 85.89 and 80.80, respectively. They fulfilled the Lipinski's rule, topological descriptors, and fingerprints of drug-like molecular structure keys. These compounds can be used as lead compounds to develop novel antiproliferative agents. The outcome of applying this study is novel series of 1,3-diazetidin-2-one compounds as new analogs were designed and evaluated for their antiproliferative activity with a higher potency profile and binding affinity within the active sites of EGFR.

In silico identification of a β2-adrenoceptor allosteric site that selectively augments canonical β2AR-Gs signaling and function

Activation of β₂-adrenoceptors (β₂ARs) causes airway smooth muscle (ASM) relaxation and bronchodilation, and β₂AR agonists (β-agonists) are front-line treatments for asthma and other obstructive lung diseases. However, the therapeutic efficacy of β-agonists is limited by agonist-induced β₂AR desensitization and noncanonical β₂AR signaling involving β-arrestin that is shown to promote asthma pathophysiology. Accordingly, we undertook the identification of an allosteric site on β₂AR that could modulate the activity of β-agonists to overcome these limitations. We employed the site identification by ligand competitive saturation (SILCS) computational method to comprehensively map the entire 3D structure of in silico-generated β₂AR intermediate conformations and identified a putative allosteric binding site. Subsequent database screening using SILCS identified drug-like molecules with the potential to bind to the site. Experimental assays in HEK293 cells (expressing recombinant wild-type human β₂AR) and human ASM cells (expressing endogenous β₂AR) identified positive and negative allosteric modulators (PAMs and NAMs) of β₂AR as assessed by regulation of β-agonist-stimulation of cyclic AMP generation. PAMs/NAMs had no effect on β-agonist-induced recruitment of β-arrestin to β₂AR- or β-agonist-induced loss of cell surface expression in HEK293 cells expressing β₂AR. Mutagenesis analysis of β₂AR confirmed the SILCS identified site based on mutants of amino acids R131, Y219, and F282. Finally, functional studies revealed augmentation of β-agonist-induced relaxation of contracted human ASM cells and bronchodilation of contracted airways. These findings identify a allosteric binding site on the β₂AR, whose activation selectively augments β-agonist-induced Gs signaling, and increases relaxation of ASM cells, the principal therapeutic effect of β-agonists.

Identification of a Potent Human Trace Amine-Associated Receptor 1 Antagonist

Human trace amine-associated receptor subtype 1 (hTAAR1) is a G protein-coupled receptor that has therapeutic potential for multiple diseases, including schizophrenia, drug addiction, and Parkinson's disease (PD). Although several potent agonists have been identified and have shown positive results in various clinical trials for schizophrenia, the discovery of potent hTAAR1 antagonists remains elusive. Herein, we report the results of structure-activity relationship studies that have led to the discovery of a potent hTAAR1 antagonist (RTI-7470-44, 34). RTI-7470-44 exhibited an IC₅₀ of 8.4 nM in an in vitro cAMP functional assay, a K_i of 0.3 nM in a radioligand binding assay, and showed species selectivity for hTAAR1 over the rat and mouse orthologues. RTI-7470-44 displayed good blood-brain barrier permeability, moderate metabolic stability, and a favorable preliminary off-target profile. Finally, RTI-7470-44 increased the spontaneous firing rate of mouse VTA dopaminergic neurons and blocked the effects of the known TAAR1 agonist RO5166017. Collectively, this work provides a promising hTAAR1 antagonist probe that can be used to study TAAR1 pharmacology and the potential therapeutic role in hypodopaminergic diseases such as PD.

In Silico Resources of Drug-Likeness as a Mirror: What Are We Lacking in Pesticide-Likeness?

Unfavorable bioavailability is an important aspect underlying the failure of drug candidates. Computational approaches for evaluating drug-likeness can minimize these risks. Over the past decades, computational approaches for evaluating drug-likeness have sped up the process of drug development and were also quickly derived to pesticide-likeness. As a result of many critical differences between drugs and pesticides, many kinds of methods for drug-likeness cannot be used for pesticide-likeness. Therefore, it is crucial to comprehensively compare and analyze the differences between drug-likeness and pesticide-likeness, which may provide a basis for solving the problems encountered during the evaluation of pesticide-likeness. Here, we systematically collected the recent advances of drug-likeness and pesticide-likeness and compared their characteristics. We also evaluated the current lack of studies on pesticide-likeness, the molecular descriptors and parameters adopted, the pesticide-likeness model on pesticide target organisms, and comprehensive analysis tools. This work may guide researchers to use appropriate methods for developing pesticide-likeness models. It may also aid non-specialists to understand some important concepts in drug-likeness and pesticide-likeness.

Lipophilicity, Pharmacokinetic Properties, and Molecular Docking Study on SARS-CoV-2 Target for Betulin Triazole Derivatives with Attached 1,4-Quinone

A key parameter in the design of new active compounds is lipophilicity, which influences the solubility and permeability through membranes. Lipophilicity affects the pharmacodynamic and toxicological profiles of compounds. These parameters can be determined experimentally or by using different calculation methods. The aim of the research was to determine the lipophilicity of betulin triazole derivatives with attached 1,4-quinone using thin layer chromatography in a reverse phase system and a computer program to calculate its theoretical model. The physiochemical and pharmacokinetic properties were also determined by computer programs. For all obtained parameters, the similarity analysis and multilinear regression were determined. The analyses showed that there is a relationship between structure and properties under study. The molecular docking study showed that betulin triazole derivatives with attached 1,4-quinone could inhibit selected SARS-CoV-2 proteins. The MLR regression showed that there is a correlation between affinity scoring values (ΔG) and the physicochemical properties of the tested compounds.

Progress toward B-Cell Lymphoma 6 BTB Domain Inhibitors for the Treatment of Diffuse Large B-Cell Lymphoma and Beyond

B-cell lymphoma 6 (BCL6) is a master regulator of germinal center formation that produce antibody-secreting plasma cells and memory B-cells for sustained immune responses. The BTB domain of BCL6 (BCL6^BTB) forms a homodimer that mediates transcriptional repression by recruiting its corepressor proteins to form a biologically functional transcriptional complex. The protein-protein interaction (PPI) between the BCL6^BTB and its corepressors has emerged as a therapeutic target for the treatment of DLBCL and a number of other human cancers. This Perspective provides an overview of recent advances in the development of BCL6^BTB inhibitors from reversible inhibitors, irreversible inhibitors, to BCL6 degraders. Inhibitor design and medicinal chemistry strategies for the development of novel compounds will be provided. The binding mode of new inhibitors to BCL6^BTB are highlighted. Also, the in vitro and in vivo assays used for the evaluation of new compounds will be discussed.

Small molecules inhibitors of the heterogeneous ribonuclear protein A18 (hnRNP A18): a regulator of protein translation and an immune checkpoint

We have identified chemical probes that simultaneously inhibit cancer cell progression and an immune checkpoint. Using the computational Site Identification by Ligand Competitive Saturation (SILCS) technology, structural biology and cell-based assays, we identify small molecules that directly and selectively bind to the RNA Recognition Motif (RRM) of hnRNP A18, a regulator of protein translation in cancer cells. hnRNP A18 recognizes a specific RNA signature motif in the 3′UTR of transcripts associated with cancer cell progression (Trx, VEGF, RPA) and, as shown here, a tumor immune checkpoint (CTLA-4). Post-transcriptional regulation of immune checkpoints is a potential therapeutic strategy that remains to be exploited. The probes target hnRNP A18 RRM in vitro and in cells as evaluated by cellular target engagement. As single agents, the probes specifically disrupt hnRNP A18–RNA interactions, downregulate Trx and CTLA-4 protein levels and inhibit proliferation of several cancer cell lines without affecting the viability of normal epithelial cells. These first-in-class chemical probes will greatly facilitate the elucidation of the underexplored biological function of RNA Binding Proteins (RBPs) in cancer cells, including their effects on proliferation and immune checkpoint activation.

HerbiPAD: a free web platform to comprehensively analyze constitutive property and herbicide-likeness to estimate chemical bioavailability

BACKGROUND

Herbicides, as efficient weed control measures, play a crucial role in ensuring food security. The emergence of herbicide-resistant weeds has negatively affected food security and promoted the demand for new and improved herbicides. The balance between bioavailability and the potency of a compound is one of the most pressing challenges in the development of novel ideal herbicides. Herbicide-likeness analysis is crucial for the evaluation of this balance and thus may help to address this issue. Many herbicide-likeness analysis methods have been developed to screen potential novel lead compounds. However, there remains a lack of user-friendly and integrated tools to comprehensively evaluate herbicide-likeness.

RESULTS

Herbicide-likeness of compounds was assessed through integrated analysis incorporating the physicochemical properties of commercial herbicides, a qualitative rule, and three quantitative scoring functions developed for evaluating herbicide-likeness. HerbiPAD (http://agroda.gzu.edu.cn:9999/ccb/database/HerbiPAD/) is a free web platform integrated with the collected database and scoring model. This platform contains 542 approved herbicides and > 29 000 physicochemical descriptors. The accuracy of HerbiPAD in distinguishing known herbicides from nonherbicides was 84.2%. In the case study, HerbiPAD evaluated 60 new compounds from seven different herbicide targets, and the accuracy of predicting better bioavailability was 83.3%.

CONCLUSIONS

HerbiPAD was designed to quickly and efficiently evaluate herbicide-likeness by integrating qualitative and quantitative analyses. The simple and effective interpretation of the analysis interface may help noncomputational experts understand herbicide-likeness. © 2020 Society of Chemical Industry.

Recent advances in long-acting nanoformulations for delivery of antiretroviral drugs

In spite of introduction of combination antiretroviral therapy (cART) against human immunodeficiency virus (HIV) infection; inaccessibility and poor adherence to oral cART costs 10 in 100,000 death worldwide. Failure in adherence leads to viral rebound, emergence of drug resistance and anticipated HIV infection in high risk individuals. Various Long-acting antiretroviral (LA ARV) nanoformulations including nano-prodrug, solid drug nanoparticles (SDN), nanocrystals, aspherical nanoparticles, polymeric and lipidic nanoparticles have shown plasma/tissue drug concentration in the therapeutic range for several weeks during pre-clinical evaluation. LA ARV nanoformulations therefore have replaced cART as better alternative for the treatment of HIV infection. Cabenuva™ is recently approved by Health Canada containing LA cabotegravir+LA rilpivirine nanocrystals (ViiV healthcare) for once monthly administration by intramuscular route. The LA nanoformulation due to its nanosize insist on better stability, delivery to lymphatic, slow release into systemic circulation via lymphatic-circulatory system conjoint and secondary drug depot within infiltered immune cells at site of administration and systemic circulation in contrast to conventional drugs. However, the pharmacokinetic, biodistribution and efficacy of LA nanoformulations hinge onto physicochemical properties of the drugs and route of administration. Therefore, current review emphasizes on these contradistinctive factors that affects the reproducibility, safety, efficacy and toxicity of LA anti-HIV nanoformulations. Moreover, it expatiates on application of profuse nanoformulations for long-acting effect with promising preclinical discoveries and two clinical leads. To add on, utilization of physiology-based and mechanism-based pharmacokinetic modelling and in vivo animal models which could lead to enhanced safety and efficacy of LA ARV nanoformulations in humans have been included.

Identification of Thiourea-Based Inhibitors of the B-Cell Lymphoma 6 BTB Domain via NMR-Based Fragment Screening and Computer-Aided Drug Design

Protein-protein interactions (PPI) between the transcriptional repressor B-cell lymphoma 6 (BCL6) BTB domain (BCL6^BTB) and its corepressors have emerged as a promising target for anticancer therapeutics. However, identification of potent, drug-like inhibitors of BCL6^BTB has remained challenging. Using NMR-based screening of a library of fragment-like small molecules, we have identified a thiourea compound (7CC5) that binds to BCL6^BTB. From this hit, the application of computer-aided drug design (CADD), medicinal chemistry, NMR spectroscopy, and X-ray crystallography has yielded an inhibitor, 15f, that demonstrated over 100-fold improved potency for BCL6^BTB. This gain in potency was achieved by a unique binding mode that mimics the binding mode of the corepressor SMRT in the aromatic and the HDCH sites. The structure-activity relationship based on these new inhibitors will have a significant impact on the rational design of novel BCL6 inhibitors, facilitating the identification of therapeutics for the treatment of BCL6-dependent tumors.

Novel Noncatalytic Substrate-Selective p38α-Specific MAPK Inhibitors with Endothelial-Stabilizing and Anti-Inflammatory Activity

The p38 MAPK family is composed of four kinases of which p38α/MAPK14 is the major proinflammatory member. These kinases contribute to many inflammatory diseases, but the currently available p38 catalytic inhibitors (e.g., SB203580) are poorly effective and cause toxicity. We reasoned that the failure of catalytic p38 inhibitors may derive from their activity against noninflammatory p38 isoforms (e.g., p38β/MAPK11) and loss of all p38α-dependent responses, including anti-inflammatory, counterregulatory responses via mitogen- and stress-activated kinase (MSK) 1/2 and Smad3. We used computer-aided drug design to target small molecules to a pocket near the p38α glutamate-aspartate (ED) substrate-docking site rather than the catalytic site, the sequence of which had only modest homology among p38 isoforms. We identified a lead compound, UM101, that was at least as effective as SB203580 in stabilizing endothelial barrier function, reducing inflammation, and mitigating LPS-induced mouse lung injury. Differential scanning fluorimetry and saturation transfer difference-nuclear magnetic resonance demonstrated specific binding of UM101 to the computer-aided drug design-targeted pockets in p38α but not p38β. RNA sequencing analysis of TNF-α-stimulated gene expression revealed that UM101 inhibited only 28 of 61 SB203580-inhibited genes and 7 of 15 SB203580-inhibited transcription factors, but spared the anti-inflammatory MSK1/2 pathway. We provide proof of principle that small molecules that target the ED substrate-docking site may exert anti-inflammatory effects similar to the catalytic p38 inhibitors, but their isoform specificity and substrate selectivity may confer inherent advantages over catalytic inhibitors for treating inflammatory diseases.

Computer-Aided Drug Design Methods

Computational approaches are useful tools to interpret and guide experiments to expedite the antibiotic drug design process. Structure-based drug design (SBDD) and ligand-based drug design (LBDD) are the two general types of computer-aided drug design (CADD) approaches in existence. SBDD methods analyze macromolecular target 3-dimensional structural information, typically of proteins or RNA, to identify key sites and interactions that are important for their respective biological functions. Such information can then be utilized to design antibiotic drugs that can compete with essential interactions involving the target and thus interrupt the biological pathways essential for survival of the microorganism(s). LBDD methods focus on known antibiotic ligands for a target to establish a relationship between their physiochemical properties and antibiotic activities, referred to as a structure-activity relationship (SAR), information that can be used for optimization of known drugs or guide the design of new drugs with improved activity. In this chapter, standard CADD protocols for both SBDD and LBDD will be presented with a special focus on methodologies and targets routinely studied in our laboratory for antibiotic drug discoveries.

The Small Molecule IMR-1 Inhibits the Notch Transcriptional Activation Complex to Suppress Tumorigenesis

In many cancers, aberrant Notch activity has been demonstrated to play a role in the initiation and maintenance of the neoplastic phenotype and in cancer stem cells, which may allude to its additional involvement in metastasis and resistance to therapy. Therefore, Notch is an exceedingly attractive therapeutic target in cancer, but the full range of potential targets within the pathway has been underexplored. To date, there are no small-molecule inhibitors that directly target the intracellular Notch pathway or the assembly of the transcriptional activation complex. Here, we describe an in vitro assay that quantitatively measures the assembly of the Notch transcriptional complex on DNA. Integrating this approach with computer-aided drug design, we explored potential ligand-binding sites and screened for compounds that could disrupt the assembly of the Notch transcriptional activation complex. We identified a small-molecule inhibitor, termed Inhibitor of Mastermind Recruitment-1 (IMR-1), that disrupted the recruitment of Mastermind-like 1 to the Notch transcriptional activation complex on chromatin, thereby attenuating Notch target gene transcription. Furthermore, IMR-1 inhibited the growth of Notch-dependent cell lines and significantly abrogated the growth of patient-derived tumor xenografts. Taken together, our findings suggest that a novel class of Notch inhibitors targeting the transcriptional activation complex may represent a new paradigm for Notch-based anticancer therapeutics, warranting further preclinical characterization. Cancer Res; 76(12); 3593-603. ©2016 AACR.

A physicochemical descriptor-based scoring scheme for effective and rapid filtering of kinase-like chemical space

Background

The current chemical space of known small molecules is estimated to exceed 10⁶⁰ structures. Though the largest physical compound repositories contain only a few tens of millions of unique compounds, virtual screening of databases of this size is still difficult. In recent years, the application of physicochemical descriptor-based profiling, such as Lipinski's rule-of-five for drug-likeness and Oprea's criteria of lead-likeness, as early stage filters in drug discovery has gained widespread acceptance. In the current study, we outline a kinase-likeness scoring function based on known kinase inhibitors.

Results

The method employs a collection of 22,615 known kinase inhibitors from the ChEMBL database. A kinase-likeness score is computed using statistical analysis of nine key physicochemical descriptors for these inhibitors. Based on this score, the kinase-likeness of four publicly and commercially available databases, i.e., National Cancer Institute database (NCI), the Natural Products database (NPD), the National Institute of Health's Molecular Libraries Small Molecule Repository (MLSMR), and the World Drug Index (WDI) database, is analyzed. Three of these databases, i.e., NCI, NPD, and MLSMR are frequently used in the virtual screening of kinase inhibitors, while the fourth WDI database is for comparison since it covers a wide range of known chemical space. Based on the kinase-likeness score, a kinase-focused library is also developed and tested against three different kinase targets selected from three different branches of the human kinome tree.

Conclusions

Our proposed methodology is one of the first that explores how the narrow chemical space of kinase inhibitors and its relevant physicochemical information can be utilized to build kinase-focused libraries and prioritize pre-existing compound databases for screening. We have shown that focused libraries generated by filtering compounds using the kinase-likeness score have, on average, better docking scores than an equivalent number of randomly selected compounds. Beyond library design, our findings also impact the broader efforts to identify kinase inhibitors by screening pre-existing compound libraries. Currently, the NCI library is the most commonly used database for screening kinase inhibitors. Our research suggests that other libraries, such as MLSMR, are more kinase-like and should be given priority in kinase screenings.

Lipophilic hydroxytyrosol esters: fatty acid conjugates for potential topical administration

Hydroxytyrosol is a potent antioxidant natural molecule isolated from olive leaves and fruits. The presence of three hydroxy groups in its structure poses a limit for the topical application of this lead compound. A set of hydroxytyrosol conjugates with fatty acids at different molecular weights were synthesized under mild conditions. The topical delivery features of this new set of antioxidant molecules were evaluated as a function of their permeation profiles through the human stratum corneum and viable epidermis membranes. A dependence on their partition coefficients, their molecular weights, and their isometric configurations was then postulated. Encouraging results prompt further investigations on the polyfunctional role that hydroxytyrosol conjugates could have as agents in both anti-inflammatory and antioxidant therapies.