Exploring biology with small organic molecules

High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage

In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

Effects of local and systemic treatment with human natural killer-1 mimetic peptide (HNK-1) after ventral root avulsion and reimplantation in mice

Background

Spinal ventral root injuries generate significant motoneuron degeneration, which hinders full functional recovery. The poor prognosis of functional recovery can be attributed to the use or combination of different therapeutic approaches. Several molecules have been screened as potential treatments in combination with surgical reimplantation of the avulsed roots, the gold standard approach for such injuries. Among the studied molecules, human natural killer-1 (HNK-1) stands out as it is related to the stimulation of motor axon outgrowth. Therefore, we aimed to comparatively investigate the effects of local administration of an HNK-1 mimetic peptide (mp-HNK-1) and systemic treatment with ursolic acid (UA), another HNK-1 mimetic, after ventral root avulsion and reimplantation with heterologous fibrin biopolymer (HFB).

Methods

Female mice of the isogenic strain C57BL/6JUnib were divided into five experimental groups: Avulsion, Reimplantation, mp-HNK-1 (in situ), and UA (systemic treatment). Mice were evaluated 2 and 12 weeks after surgery. Functional assessment was performed every four days using the Catwalk platform. Neuronal survival was analyzed by cytochemistry, and glial reactions and synaptic coverage were evaluated by immunofluorescence.

Results

Treatment with UA elicited long-term neuroprotection, accompanied by a decrease in microglial reactions, and reactive astrogliosis. The neuroprotective effects of UA were preceded by increased glutamatergic and GABAergic inputs in the ventral spinal cord two weeks after injury. However, a single application of mp-HNK-1 had no significant effects. Functional analysis showed that UA treatment led to an improvement in motor and sensory recovery.

Conclusion

Overall, the results indicate that UA is neuroprotective, acting on glial cells and synaptic maintenance, and the combination of these findings led to a better functional recovery.

A multi-signal mitochondria-targeted fluorescent probe for simultaneously distinguishing biothiols and realtime visualizing its metabolism in cancer cells and tumor models

Biothiols and its metabolite SO2 derivatives play vital roles in various physiological processes. Although a few probes have been designed for monitoring the metabolism of biothiols, developing multi-signal fluorescent probes with practicability for simultaneously distinguishing biothiols (GSH, Cys and Hcy) and real-time visualizing SO2 derivatives is an enormous challenge. To better visualize biothiols metabolism in vitro and vivo, we developed a novel multi-signal NIR fluorescent probe (probe 2) with mitochondria-targeted for distinguishing biothiols and its metabolism, based on an ICT-PET synergetic mechanism. Probe 2 with dual recognition sites distinguishing detected Cys/Hcy (Red-Green), GSH (Green) and SO32- (Blue) via three channels. First probe 2 distinguished Cys and GSH to estimate main biothiols in living cells through the ratio changes of two well-defined emission bands (Red-Green), and then imaged its metabolite SO2 with ratiometric fluorescence (Red-Blue), eliminating the interference by different biothiols. Notably, probe 2 exhibits satisfactory sensitivity (detection limit: 0.21, 0.13, 0.14 and 3.06 μM for Cys, Hcy, GSH and SO32-, respectively), high selectivity, reliability at physiological pH, and rapid fluorescence response (within 10 min). Given these advantages, probe 2 has been successfully applied to the real-time monitor GSH metabolic process in MCF-7 cells and biothiols metabolism in breast cancer, suggesting biothiols metabolic changes might be a diagnostic indicator during cancer treatment. So probe 2 is a convenient and efficient tool for understanding the physiological functions of biothiols and its metabolism.

Exploring Scoring Function Space: Developing Computational Models for Drug Discovery

BACKGROUND

The idea of scoring function space established a systems-level approach to address the development of models to predict the affinity of drug molecules by those interested in drug discovery.

OBJECTIVE

Our goal here is to review the concept of scoring function space and how to explore it to develop machine learning models to address protein-ligand binding affinity.

METHODS

We searched the articles available in PubMed related to the scoring function space. We also utilized crystallographic structures found in the protein data bank (PDB) to represent the protein space.

RESULTS

The application of systems-level approaches to address receptor-drug interactions allows us to have a holistic view of the process of drug discovery. The scoring function space adds flexibility to the process since it makes it possible to see drug discovery as a relationship involving mathematical spaces.

CONCLUSION

The application of the concept of scoring function space has provided us with an integrated view of drug discovery methods. This concept is useful during drug discovery, where we see the process as a computational search of the scoring function space to find an adequate model to predict receptor-drug binding affinity.

On-DNA hydroalkylation of N-vinyl heterocycles via photoinduced EDA-complex activation

The emergence of DNA-encoded library (DEL) technology has provided a considerable advantage to the pharmaceutical industry in the pursuit of discovering novel therapeutic candidates for their drug development initiatives. This combinatorial technique not only offers a more economical, spatially efficient, and time-saving alternative to the existing ligand discovery methods, but also enables the exploration of additional chemical space by utilizing novel DNA-compatible synthetic transformations to leverage multifunctional building blocks from readily available substructures. In this report, a decarboxylative-based hydroalkylation of DNA-conjugated N-vinyl heterocycles enabled by single-electron transfer (SET) and subsequent hydrogen atom transfer through electron-donor/electron-acceptor (EDA) complex activation is detailed. The simplicity and robustness of this method permits inclusion of a broad array of alkyl radical precursors and DNA-tethered nitrogenous heterocyles to generate medicinally relevant substituted heterocycles with pendant functional groups. Moreover, a successful telescoped route provides the opportunity to access a broad range of intricate structural scaffolds by employing basic carboxylic acid feedstocks.

Parallel Synthesis of Piperazine Tethered Thiazole Compounds with Antiplasmodial Activity

Thiazole and piperazine are two important heterocyclic rings that play a prominent role in nature and have a broad range of applications in agricultural and medicinal chemistry. Herein, we report the parallel synthesis of a library of diverse piperazine-tethered thiazole compounds. The reaction of piperazine with newly generated 4-chloromethyl-2-amino thiazoles led to the desired piperazine thiazole compounds with high purities and good overall yields. Using a variety of commercially available carboxylic acids, the parallel synthesis of a variety of disubstituted 4-(piperazin-1-ylmethyl)thiazol-2-amine derivatives is described. the screening of the compounds led to the identification of antiplasmodial compounds that exhibited interesting antimalarial activity, primarily against the Plasmodium falciparum chloroquine-resistant Dd2 strain. The hit compound 2291-61 demonstrated an antiplasmodial EC50 of 102 nM in the chloroquine-resistant Dd2 strain and a selectivity of over 140.

QMrebind: incorporating quantum mechanical force field reparameterization at the ligand binding site for improved drug-target kinetics through milestoning simulations

Understanding the interaction of ligands with biomolecules is an integral component of drug discovery and development. Challenges for computing thermodynamic and kinetic quantities for pharmaceutically relevant receptor-ligand complexes include the size and flexibility of the ligands, large-scale conformational rearrangements of the receptor, accurate force field parameters, simulation efficiency, and sufficient sampling associated with rare events. Our recently developed multiscale milestoning simulation approach, SEEKR2 (Simulation Enabled Estimation of Kinetic Rates v.2), has demonstrated success in predicting unbinding (koff) kinetics by employing molecular dynamics (MD) simulations in regions closer to the binding site. The MD region is further subdivided into smaller Voronoi tessellations to improve the simulation efficiency and parallelization. To date, all MD simulations are run using general molecular mechanics (MM) force fields. The accuracy of calculations can be further improved by incorporating quantum mechanical (QM) methods into generating system-specific force fields through reparameterizing ligand partial charges in the bound state. The force field reparameterization process modifies the potential energy landscape of the bimolecular complex, enabling a more accurate representation of the intermolecular interactions and polarization effects at the bound state. We present QMrebind (Quantum Mechanical force field reparameterization at the receptor-ligand binding site), an ORCA-based software that facilitates reparameterizing the potential energy function within the phase space representing the bound state in a receptor-ligand complex. With SEEKR2 koff estimates and experimentally determined kinetic rates, we compare and interpret the receptor-ligand unbinding kinetics obtained using the newly reparameterized force fields for model host-guest systems and HSP90-inhibitor complexes. This method provides an opportunity to achieve higher accuracy in predicting receptor-ligand koff rate constants.

Sunlight-directed fluorophore-switch in photosynthesis of cyanine subcellular organelle markers for bio-imaging

The photoconvertible fluorophore synthesis enables the light controlled imaging channels switch for accurate tracking the quantity and localization of intracellular biomolecules in chemical biology. Herein, we repurposed the photochemistry of Fischer's base and developed a sunlight-directed fluorophore-switch strategy for high-efficiency trimethine cyanine (Cy3.5/Cy3) synthesis. The unexpected sunlight-directed photoconversion of Fischer's base proceeds in conventional solvents and accelerates in chloroform via photo-oxidation and hydrogen atom transfer without using extra additives, and the heterogenous dimerization mechanism was proposed and confirmed by isolation of the reactive intermediates. The reliable strategy is employed in the photosynthesis of commercially available cytomembrane marker (DiI) and other cyanine based organelle markers with appreciable yields. Sunlight-controlled fluorophore-switch of subcellular organelle markers in living cells validated the feasibility of our strategy with cell-tolerant character. Moreover, remote control synthesis of Cy3.5 in vivo directed via sunlight further demonstrated the extended application of our strategy. Therefore, this sunlight-directed strategy will facilitate exploitation of cyanine-based probes with switched fluorescence imaging channels and further enable precise description of the dynamic variations in living cells with minimal autofluorescence and cellular disturbance.

Self-supervised learning with chemistry-aware fragmentation for effective molecular property prediction

Molecular property prediction (MPP) is a crucial and fundamental task for AI-aided drug discovery (AIDD). Recent studies have shown great promise of applying self-supervised learning (SSL) to producing molecular representations to cope with the widely-concerned data scarcity problem in AIDD. As some specific substructures of molecules play important roles in determining molecular properties, molecular representations learned by deep learning models are expected to attach more importance to such substructures implicitly or explicitly to achieve better predictive performance. However, few SSL pre-trained models for MPP in the literature have ever focused on such substructures. To challenge this situation, this paper presents a Chemistry-Aware Fragmentation for Effective MPP (CAFE-MPP in short) under the self-supervised contrastive learning framework. First, a novel fragment-based molecular graph (FMG) is designed to represent the topological relationship between chemistry-aware substructures that constitute a molecule. Then, with well-designed hard negative pairs, a is pre-trained on fragment-level by contrastive learning to extract representations for the nodes in FMGs. Finally, a Graphormer model is leveraged to produce molecular representations for MPP based on the embeddings of fragments. Experiments on 11 benchmark datasets show that the proposed CAFE-MPP method achieves state-of-the-art performance on 7 of the 11 datasets and the second-best performance on 3 datasets, compared with six remarkable self-supervised methods. Further investigations also demonstrate that CAFE-MPP can learn to embed molecules into representations implicitly containing the information of fragments highly correlated to molecular properties, and can alleviate the over-smoothing problem of graph neural networks.

Upconverting Nanoparticle-Based Photoactive Probes for Highly Efficient Labeling and Isolation of Target Proteins

Photoaffinity labeling (PAL) has blossomed into a powerful and versatile tool for capture and identification of biomolecular targets. However, low labeling efficiency for specific targets such as lectins, the tedious process for protein purification, inevitable cellular photodamage, and less tissue penetration of UV light are significant challenges. Herein, we reported a near-infrared (NIR) light-driven photoaffinity labeling approach using upconverting nanoparticle (UCNP)-based photoactive probes, which were constructed by assembling photoactive groups and ligands onto NaYF4:Yb,Tm nanoparticles. The novel probes were easily prepared and functionalized, and the labeled proteins can be isolated and purified through simple centrifugation and washing. The advantages of this approach were demonstrated by labeling and isolation of peanut agglutinin (PNA), asialoglycoprotein receptor (ASGPR), and human carbonic anhydrase II (hCAII) from mixed proteins or cell lysates with good selectivity and efficiency, especially for PNA and ASGPR, two lectins that showed low binding affinity to their ligands. More importantly, successful labeling of PNA through pork tissues and ASGPR in mice strongly proved the good tissue penetrating capacity of NIR light and the application potential of UCNP-based photoactive probes for protein labeling in vivo. Biosafety of this approach was experimentally validated by enzyme, cell, and animal work, and we demonstrated that NIR light caused minimal photodamage to enzyme activity compared to UV light, and the UCNP-based photoactive probe presents good biosafety both in vitro and in vivo. We believe that this novel PAL approach will provide a promising tool for study of ligand-protein interactions and identification of biomolecular targets.

CRISPR/Cas-Based Techniques for Live-Cell Imaging and Bioanalysis

CRISPR/Cas systems have found widespread applications in gene editing due to their high accuracy, high programmability, ease of use, and affordability. Benefiting from the cleavage properties (trans- or cis-) of Cas enzymes, the scope of CRISPR/Cas systems has expanded beyond gene editing and they have been utilized in various fields, particularly in live-cell imaging and bioanalysis. In this review, we summarize some fundamental working mechanisms and concepts of the CRISPR/Cas systems, describe the recent advances and design principles of CRISPR/Cas mediated techniques employed in live-cell imaging and bioanalysis, highlight the main applications in the imaging and biosensing of a wide range of molecular targets, and discuss the challenges and prospects of CRISPR/Cas systems in live-cell imaging and biosensing. By illustrating the imaging and bio-sensing processes, we hope this review will guide the best use of the CRISPR/Cas in imaging and quantifying biological and clinical elements and inspire new ideas for better tool design in live-cell imaging and bioanalysis.

An interrupted Corey-Chaykovsky reaction of designed azaarenium salts: synthesis of complex polycyclic spiro- and fused cyclopropanoids

Simultaneous dearomatizing spirannulation of pyridinium salts is still in its infancy. Here, we present an organized skeletal remodeling of designed pyridinium salts by utilizing an interrupted Corey-Chaykovsky reaction to access unprecedented and structurally intriguing molecular architectures such as the vicinal bis-spirocyclic indanones and spirannulated benzocycloheptanones. This hybrid strategy rationally merges the nucleophilic features of sulfur ylides with the electrophilic pyridinium salts to achieve the regio- and stereoselective synthesis of new classes of cyclopropanoids. The plausible mechanistic pathways were derived from experimental results and control experiments.

Chemoproteomics Reveals the Pan-HER Kinase Inhibitor Neratinib To Target an Arabidopsis Epoxide Hydrolase Related to Phytohormone Signaling

Plant phytohormone pathways are regulated by an intricate network of signaling components and modulators, many of which still remain unknown. Here, we report a forward chemical genetics approach for the identification of functional SA agonists in Arabidopsis thaliana that revealed Neratinib (Ner), a covalent pan-HER kinase inhibitor drug in humans, as a modulator of SA signaling. Instead of a protein kinase, chemoproteomics unveiled that Ner covalently modifies a surface-exposed cysteine residue of Arabidopsis epoxide hydrolase isoform 7 (AtEH7), thereby triggering its allosteric inhibition. Physiologically, the Ner application induces jasmonate metabolism in an AtEH7-dependent manner as an early response. In addition, it modulates PATHOGENESIS RELATED 1 (PR1) expression as a hallmark of SA signaling activation as a later effect. AtEH7, however, is not the exclusive target for this physiological readout induced by Ner. Although the underlying molecular mechanisms of AtEH7-dependent modulation of jasmonate signaling and Ner-induced PR1-dependent activation of SA signaling and thus defense response regulation remain unknown, our present work illustrates the powerful combination of forward chemical genetics and chemical proteomics for identifying novel phytohormone signaling modulatory factors. It also suggests that marginally explored metabolic enzymes such as epoxide hydrolases may have further physiological roles in modulating signaling.

Acid/Base-Steered Cascade Cyclization: An Efficient One-Pot Access to Diverse Isobenzofuranone and Isoindolobenzoxazinone Derivatives

We herein report the acid/base-steered two distinct reaction pathways of 2-acylbenzoic acids with isatoic anhydrides. In the presence of Na₂CO₃, the cascade process consists of the cyclization of 2-acetylbenzoic acid and nucleophilic ring-opening reaction of isatoic anhydride to furnish isobenzofuranone derivatives with high efficiency. However, p-toluenesulfonic acid can promote the product isobenzofuranones to undergo sequential intramolecular rearrangment, nucleophilic addition and cyclization reaction to produce diverse isoindolobenzoxazinones in good yields. The synthetic utility of this method was further demonstrated by the gram-scale preparation of the desired products and the facile transformations of the resulting products.

Development and photo-properties and intracellular behavior of visible-light-responsive molecule localizing to organelles of living cell

Visible-light-responsive azobenzene derivative in which a functional group having cell membrane permeability and a fluorophore were bonded was synthesized. This compound localized to the hydrophobic part in the lipid membrane of the liposome, and when the light corresponding to the transition absorption of azobenzene was irradiated, morphological change of the liposome was observed. When this compound was loaded into living cells, this molecule localized to the lysosome and when irradiated with light of the same wavelength caused cell death. These observed changes are thought to be due to photoisomerization of azobenzene derivatives.

Graphical abstract

Investigation of d-Amino Acid-Based Surfactants and Nanocomposites with Gold and Silica Nanoparticles as against Multidrug-Resistant Bacteria Agents

d-amino acid-based surfactants (d-AASs) were synthesized and their antimicrobial activity was evaluated. N-α-lauroyl-d-arginine ethyl ester hydrochloride (d-LAE), d-proline dodecyl ester (d-PD), and d-alanine dodecyl ester (d-AD) were found to have antibacterial activity against both Gram-positive and -negative bacteria, but less efficacy against Gram-negative bacteria. For these reasons, combining antimicrobial agents with nanoparticles is a promising technique for improving their antibacterial properties to eliminate drug-resistant pathogens. d-LAE coated on gold (AuNP) and silica (SiNP) nanoparticles has more efficient antibacterial activity than that of d-LAE alone. However, unlike d-LAE, d-PD has enhanced antibacterial activity upon being coated on AuNP. The antibacterial d-AASs and their nanocomposites with nanoparticles were synthesized in an environmentally friendly manner and are expected to be valuable new antimicrobial agents against multidrug-resistant (MDR) pathogens.

Serotonergic drugs modulate the phase behavior of complex lipid bilayers

Serotonin is an endogenous neurotransmitter involved in both physiological and pathophysiological processes. Traditionally, serotonin acts as a ligand for G protein-coupled receptors (GPCRs) leading to subsequent cell signaling. However, serotonin can also bind to lipid membranes with high affinity and modulate the phase behavior in 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC)/N-palmitoyl-D-erythro-sphingosylphosphorylcholine (PSM)/cholesterol model membranes mimicking the outer leaflet of the plasma membrane. Here, we investigated if serotonergic drugs containing the pharmacophore from serotonin would also modulate phase behavior in lipid membranes in a similar fashion. We used ²H NMR spectroscopy to explore the phase behavior of POPC/PSM/cholesterol (4/4/2 molar ratio) mixtures in the presence of the serotonergic drugs aripiprazole, BRL-54443, BW-723C86, and CP-135807 at a lipid to drug molar ratio of 10:1. POPC and PSM were perdeuterated in the palmitoyl chain, respectively, and prepared in individual samples. Numerical lineshape simulations of the ²H NMR spectra were used to calculate the order parameter profiles and projected lengths of the saturated acyl chains. All serotonergic drugs induce two components in ²H NMR spectra, indicating that they increased the hydrophobic mismatch between the thickness of the coexisting lipid phases leading to larger domain sizes, relatively similarly to serotonin. AFM force indentation and Raman spectral studies, which interrogate membrane mechanical properties, also indicate changes in membrane order in the presence of these drugs. These findings highlight how serotonergic drugs alter membrane phase behavior and could modulate both target and other membrane proteins, possibly explaining the side effects observed for serotonergic and other clinically relevant drugs.

Expanding the Repertoire of Low-Molecular-Weight Pentafluorosulfanyl-Substituted Scaffolds

The pentafluorosulfanyl (-SF5 ) functional group is of increasing interest as a bioisostere in medicinal chemistry. A library of SF5 -containing compounds, including amide, isoxazole, and oxindole derivatives, was synthesised using a range of solution-based and solventless methods, including microwave and ball-mill techniques. The library was tested against targets including human dihydroorotate dehydrogenase (HDHODH). A subsequent focused approach led to synthesis of analogues of the clinically used disease modifying anti-rheumatic drugs (DMARDs), Teriflunomide and Leflunomide, considered for potential COVID-19 use, where SF5 bioisostere deployment led to improved inhibition of HDHODH compared with the parent drugs. The results demonstrate the utility of the SF5 group in medicinal chemistry.

Atomic level and structural understanding of natural ligands inhibiting Helicobacter pylori peptide deformylase through ligand and receptor based screening, SIFT, molecular dynamics and DFT - a structural computational approach

Helicobacter pylori is a Gram-negative microaerophilic gastric pathogen, responsible for the cause of peptic ulcer around half of the global population. Although several antibiotics and combination therapies have been employed for H. pylori-related gastric ulcer and cancer regiments, identifying potent inhibitors for specific targets of this bacterium will help assessing better treatment periodicity and methods to eradicate H. pylori. Herein, 1,000,000 natural compounds were virtually screened against Helicobacter pylori Peptide deformylase (HpPDF). Pharmacophore hypotheses were created using ligand and receptor-based pharmacophore modeling of GLIDE. Stringent HTVS and IFD docking protocol of GLIDE predicted leads with stable intermolecular bonds and scores. Molecular dynamics simulation of HpPDF was carried out for 100 ns using GROMACS. Hits ZINC00225109 and ZINC44896875 came up with a glide score of -9.967 kcal/mol and -12.114 kcal/mol whereas; reference compound actinonin produced a glide score of -9.730 kcal/mol. Binding energy values of these hits revealed the involvement of significant Van der Waals and Coulomb forces and the deduction of lipophilic forces that portray the deep hydrophobic residues in the S1pocket of H. pylori. The DFT analysis established the electron density-based features of the molecules and observed that the results correlate with intermolecular docking interactions. Analysis of the MD trajectories revealed the crucial residues involved in HpPDF - ligand binding and the conformational changes in the receptor. We have identified and deciphered the crucial features necessary for the potent ligand binding at catalytic site of HpPDF. The resulting ZINC natural compound hits from the study could be further employed for potent drug development.Communicated by Ramaswamy H. Sarma.

Potential Antiviral Action of Alkaloids

Viral infections and outbreaks have become a major concern and are one of the main causes of morbidity and mortality worldwide. The development of successful antiviral therapeutics and vaccines remains a daunting challenge. The discovery of novel antiviral agents is a public health emergency, and extraordinary efforts are underway globally to identify safe and effective treatments for different viral diseases. Alkaloids are natural phytochemicals known for their biological activities, many of which have been intensively studied for their broad-spectrum of antiviral activities against different DNA and RNA viruses. The purpose of this review was to summarize the evidence supporting the efficacy of the antiviral activity of plant alkaloids at half-maximum effective concentration (EC50) or half-maximum inhibitory concentration (IC50) below 10 μM and describe the molecular sites most often targeted by natural alkaloids acting against different virus families. This review highlights that considering the devastating effects of virus pandemics on humans, plants, and animals, the development of high efficiency and low-toxicity antiviral drugs targeting these viruses need to be developed. Furthermore, it summarizes the current research status of alkaloids as the source of antiviral drug development, their structural characteristics, and antiviral targets. Overall, the influence of alkaloids at the molecular level suggests a high degree of specificity which means they could serve as potent and safe antiviral agents waiting for evaluation and exploitation.

Modern Approaches in the Discovery and Development of Plant-Based Natural Products and Their Analogues as Potential Therapeutic Agents

Natural products represents an important source of new lead compounds in drug discovery research. Several drugs currently used as therapeutic agents have been developed from natural sources; plant sources are specifically important. In the past few decades, pharmaceutical companies demonstrated insignificant attention towards natural product drug discovery, mainly due to its intrinsic complexity. Recently, technological advancements greatly helped to address the challenges and resulted in the revived scientific interest in drug discovery from natural sources. This review provides a comprehensive overview of various approaches used in the selection, authentication, extraction/isolation, biological screening, and analogue development through the application of modern drug-development principles of plant-based natural products. Main focus is given to the bioactivity-guided fractionation approach along with associated challenges and major advancements. A brief outline of historical development in natural product drug discovery and a snapshot of the prominent natural drugs developed in the last few decades are also presented. The researcher’s opinions indicated that an integrated interdisciplinary approach utilizing technological advances is necessary for the successful development of natural products. These involve the application of efficient selection method, well-designed extraction/isolation procedure, advanced structure elucidation techniques, and bioassays with a high-throughput capacity to establish druggability and patentability of phyto-compounds. A number of modern approaches including molecular modeling, virtual screening, natural product library, and database mining are being used for improving natural product drug discovery research. Renewed scientific interest and recent research trends in natural product drug discovery clearly indicated that natural products will play important role in the future development of new therapeutic drugs and it is also anticipated that efficient application of new approaches will further improve the drug discovery campaign.

Organoids in image-based phenotypic chemical screens

Image-based phenotypic screening relies on the extraction of multivariate information from cells cultured under a large variety of conditions. Technical advances in high-throughput microscopy enable screening in increasingly complex and biologically relevant model systems. To this end, organoids hold great potential for high-content screening because they recapitulate many aspects of parent tissues and can be derived from patient material. However, screening is substantially more difficult in organoids than in classical cell lines from both technical and analytical standpoints. In this review, we present an overview of studies employing organoids for screening applications. We discuss the promises and challenges of small-molecule treatments in organoids and give practical advice on designing, running, and analyzing high-content organoid-based phenotypic screens.

Exploring and mapping chemical space with molecular assembly trees

The rule-based search of chemical space can generate an almost infinite number of molecules, but exploration of known molecules as a function of the minimum number of steps needed to build up the target graphs promises to uncover new motifs and transformations. Assembly theory is an approach to compare the intrinsic complexity and properties of molecules by the minimum number of steps needed to build up the target graphs. Here, we apply this approach to prebiotic chemistry, gene sequences, plasticizers, and opiates. This allows us to explore molecules connected to the assembly tree, rather than the entire space of molecules possible. Last, by developing a reassembly method, based on assembly trees, we found that in the case of the opiates, a new set of drug candidates could be generated that would not be accessible via conventional fragment-based drug design, thereby demonstrating how this approach might find application in drug discovery.

Photoredox-mediated hydroalkylation and hydroarylation of functionalized olefins for DNA-encoded library synthesis

DNA-encoded library (DEL) technology features a time- and cost-effective interrogation format for the discovery of therapeutic candidates in the pharmaceutical industry. To develop DEL platforms, the implementation of water-compatible transformations that facilitate the incorporation of multifunctional building blocks (BBs) with high C(sp3) carbon counts is integral for success. In this report, a decarboxylative-based hydroalkylation of DNA-conjugated trifluoromethyl-substituted alkenes enabled by single-electron transfer (SET) and subsequent hydrogen atom termination through electron donor-acceptor (EDA) complex activation is detailed. In a further photoredox-catalyzed hydroarylation protocol, the coupling of functionalized, electronically unbiased olefins is achieved under air and within minutes of blue light irradiation through the intermediacy of reactive (hetero)aryl radical species with full retention of the DNA tag integrity. Notably, these processes operate under mild reaction conditions, furnishing complex structural scaffolds with a high density of pendant functional groups.

Cellular model system to dissect the isoform-selectivity of Akt inhibitors

The protein kinase Akt plays a pivotal role in cellular processes. However, its isoforms' distinct functions have not been resolved to date, mainly due to the lack of suitable biochemical and cellular tools. Against this background, we present the development of an isoform-dependent Ba/F3 model system to translate biochemical results on isoform specificity to the cellular level. Our cellular model system complemented by protein X-ray crystallography and structure-based ligand design results in covalent-allosteric Akt inhibitors with unique selectivity profiles. In a first proof-of-concept, the developed molecules allow studies on isoform-selective effects of Akt inhibition in cancer cells. Thus, this study will pave the way to resolve isoform-selective roles in health and disease and foster the development of next-generation therapeutics with superior on-target properties.

Computational Prediction of Binding Affinity for CDK2-ligand Complexes. A Protein Target for Cancer Drug Discovery

BACKGROUND

CDK2 participates in the control of eukaryotic cell-cycle progression. Due to the great interest in CDK2 for drug development and the relative easiness in crystallizing this enzyme, we have over 400 structural studies focused on this protein target. This structural data is the basis for the development of computational models to estimate CDK2-ligand binding affinity.

OBJECTIVE

This work focuses on the recent developments in the application of supervised machine learning modeling to develop scoring functions to predict the binding affinity of CDK2.

METHOD

We employed the structures available at the protein data bank and the ligand information accessed from the BindingDB, Binding MOAD, and PDBbind to evaluate the predictive performance of machine learning techniques combined with physical modeling used to calculate binding affinity. We compared this hybrid methodology with classical scoring functions available in docking programs.

RESULTS

Our comparative analysis of previously published models indicated that a model created using a combination of a mass-spring system and cross-validated Elastic Net to predict the binding affinity of CDK2-inhibitor complexes outperformed classical scoring functions available in AutoDock4 and AutoDock Vina.

CONCLUSION

All studies reviewed here suggest that targeted machine learning models are superior to classical scoring functions to calculate binding affinities. Specifically for CDK2, we see that the combination of physical modeling with supervised machine learning techniques exhibits improved predictive performance to calculate the protein-ligand binding affinity. These results find theoretical support in the application of the concept of scoring function space.

Flexible nanocellulose-based SERS substrates for fast analysis of hazardous materials by spiral scanning

Surface-enhanced Raman scattering (SERS) has proven to be a valuable tool for assessing harmful chemicals in various substances, including water, soil, and foods. However, a fast measurement system is required for multiplexed detection to extend the range of its applications. The rotating scanning stage of the SERS substrate is considered to be a promising approach to achieving a fast measurement system. This paper reports a facile measurement system by using a flexible nanocellulose-based SERS substrate and a spiral scanning system, which rotates the cylinder sample holder and moves the stage. A flexible nanocellulose-based SERS substrate deposited with Au nanoparticles is suitable for the spiral scanning system, which requires SERS substrates to be highly flexible and durable. The well-known toxic fungicide, thiram, was tested by this system. The results revealed that the nanocellulose-based SERS substrate is well-fitted with a spiral scanning system and that the signal data from a large area substrate can be obtained within 30 s. It is noteworthy that the error of spiral scanning measurements is smaller than that of multi-spot sampling. This work provides a powerful tool for Raman spectroscopic analysis, which requires quantitative and fast testing. Furthermore, various flexible SERS substrates can be utilized in this system for toxic materials detection.

A novel sodium-fluorescent crystal

In this work, a novel sodium-fluorescent crystal (Na-FS) was synthesized from 4-dimethylaminobenzoic acid and sodium hydroxide by one-pot hydrothermal method. The structure and conformation of Na-FS were confirmed by single-crystal X-ray diffraction and scanning electron microscope, and the optical properties were studied by fluorescence spectrometer. The results showed that: Na-FS was a triclinic crystal, space group was P-1, cell parameters a, b and c were 10.5113(3), 15.9198(5) and 15.9560(5) Å, respectively, and the number of independent atoms Z in a structure cell was two. Additionally, Na-FS has a blue fluorescence emission (around 360 nm under excited at the range of 230-300 nm) with great photostability and photobleaching resistance, and the quantum yield of Na-FS is 30.58%.

Developments in Photoredox-Mediated Alkylation for DNA-Encoded Libraries

Recently, DNA-encoded library (DEL) technology has emerged as an innovative screening modality for the rapid discovery of therapeutic candidates in pharmaceutical settings. This platform enables a cost-effective, time-efficient, and large-scale assembly and interrogation of billions of small organic ligands against a biological target in a single experiment. An outstanding challenge in DEL synthesis is the necessity for water-compatible transformations under ambient conditions. To access uncharted chemical space, the adoption of photoredox catalysis in DELs, including Ni-catalyzed manifolds and radical/polar crossover reactions, has enabled the construction of novel structural scaffolds through regulated odd-electron intermediates. Herein, a critical discussion of the validation of photoredox-mediated alkylation in DEL environments is presented. Current synthetic gaps are highlighted and opportunities for further development are speculated upon.

Application of Machine Learning Techniques to Predict Binding Affinity for Drug Targets: A Study of Cyclin-Dependent Kinase 2

BACKGROUND

The elucidation of the structure of cyclin-dependent kinase 2 (CDK2) made it possible to develop targeted scoring functions for virtual screening aimed to identify new inhibitors for this enzyme. CDK2 is a protein target for the development of drugs intended to modulate cellcycle progression and control. Such drugs have potential anticancer activities.

OBJECTIVE

Our goal here is to review recent applications of machine learning methods to predict ligand- binding affinity for protein targets. To assess the predictive performance of classical scoring functions and targeted scoring functions, we focused our analysis on CDK2 structures.

METHODS

We have experimental structural data for hundreds of binary complexes of CDK2 with different ligands, many of them with inhibition constant information. We investigate here computational methods to calculate the binding affinity of CDK2 through classical scoring functions and machine- learning models.

RESULTS

Analysis of the predictive performance of classical scoring functions available in docking programs such as Molegro Virtual Docker, AutoDock4, and Autodock Vina indicated that these methods failed to predict binding affinity with significant correlation with experimental data. Targeted scoring functions developed through supervised machine learning techniques showed a significant correlation with experimental data.

CONCLUSION

Here, we described the application of supervised machine learning techniques to generate a scoring function to predict binding affinity. Machine learning models showed superior predictive performance when compared with classical scoring functions. Analysis of the computational models obtained through machine learning could capture essential structural features responsible for binding affinity against CDK2.

Biological small-molecule assays using gradient-based microfluidics

Studying the potency of small-molecules on eukaryotic and prokaryotic cells using conventional biological settings requires time-consuming procedures and large volumes of expensive small-molecules. Microfluidics could significantly expedite these assays by enabling operation in high-throughput and (semi)automated modes. Here, we introduce a microfluidics platform based on multi-volume microchamber arrays that can produce a wide range of small-molecule concentrations with a desired gradient-based profile for rapid and precise biological testing within a single device with minimal hands-on time. The concept behind this device is based on introducing the same amount of a small-molecule into microchambers of different volumes to spontaneously generate a gradient concentration profile via diffusion. This design enables to obtain an unprecedented concentration range (e.g., three orders of magnitude) that can be easily adjusted, allowing us to pinpoint the precise effect of small-molecules on pre-loaded prokaryotic and eukaryotic cells. We also propose a comprehensive relationship for determining the loading time (the only required parameter for implementing this platform) in order to study the effects of any small-molecule on a biological species in a desired test. We demonstrate the versatility of this microfluidics platform by conducting two small-molecule assays-antimicrobial resistance and sugar-phosphate toxicity for both eukaryotic and prokaryotic biological systems.

Surface-enhanced Raman scattering-active AuNR array cellulose films for multi-hazard detection

In this study, we report a surface-enhanced Raman scattering (SERS)-active array film, which is based on regenerated cellulose hydrogels and gold nanorods (AuNRs), by combining a silicon rubber mask with a vacuum filtration method. This strategy enables the direct AuNR array formation on hydrogel surface with a precisely controlled number density. Moreover, the control of interparticle nanogap has been realized by the spatial deformation of hydrogels. A decrease in gaps between AuNRs deposited on hydrogels can result in SERS enhancement because 3D porous hydrogel structures turned into 2D closely packed hydrogel films during drying. In our experiments, SERS sensor arrays show excellent SERS activity to detect rhodamine 6 G and thiram down to 10 pM and 100 fM with competitive enhancement factors of 3.9 × 10⁸ and 9.5 × 10⁹, respectively. Importantly, the resultant SERS-active arrays with nine sensor units can efficiently detect nine different analytes on a single substrates at a time. Moreover, we demonstrate that physical bending has little effect on the SERS activity of flexible AuNR array hydrogel films, which indicates the high reproducibility of SERS measurement. This SERS array film has great potential to simultaneously detect multiple hazards for the practical application of SERS analysis.

Bond reactivity indices approach analysis of the [2+2] cycloaddition of jatrophane skeleton diterpenoids from Euphorbia gaditana Coss to tetracyclic gaditanone

The reaction mechanism of the intramolecular [2 + 2] cycloaddition from a jatrophane precursor to the gaditanane skeleton, an unprecedented 5/6/4/6-fused tetracyclic ring framework recently isolated from Euphorbia spp., was studied using the bond reactivity indices approach. Furthermore, six diterpenoids, including three undescribed jatrophanes isolated from E. gaditana Coss, were described. The structures of these compounds were deduced by a combination of 2D NMR spectroscopy and ECD data analysis.

Serotonin Alters the Phase Equilibrium of a Ternary Mixture of Phospholipids and Cholesterol

Unsaturated and saturated phospholipids tend to laterally segregate, especially in the presence of cholesterol. Small molecules such as neurotransmitters, toxins, drugs etc. possibly modulate this lateral segregation. The small aromatic neurotransmitter serotonin (5-HT) has been found to bind to membranes. We studied the lipid structure and packing of a ternary membrane mixture consisting of palmitoyl-oleoyl-phosphatidylcholine, palmitoyl-sphingomyelin, and cholesterol at a molar ratio of 4/4/2 in the absence and in the presence of 5-HT, using a combination of solid-state 2H NMR, atomic force microscopy, and atomistic molecular dynamics (MD) simulations. Both NMR and MD report formation of a liquid ordered (L o ) and a liquid disordered (L d ) phase coexistence with small domains. Lipid exchange between the domains was fast such that single component 2H NMR spectra are detected over a wide temperature range. A drastic restructuring of the domains was induced when 5-HT is added to the membranes at a 9 mol% concentration relative to the lipids. 2H NMR spectra of all components of the mixture showed two prominent contributions indicative of molecules of the same kind residing both in the disordered and the ordered phase. Compared to the data in the absence of 5-HT, the lipid chain order in the disordered phase was further decreased in the presence of 5-HT. Likewise, addition of serotonin increased lipid chain order within the ordered phase. These characteristic lipid chain order changes were confirmed by MD simulations. The 5-HT-induced larger difference in lipid chain order results in more pronounced differences in the hydrophobic thickness of the individual membrane domains. The correspondingly enlarged hydrophobic mismatch between ordered and disordered phases is assumed to increase the line tension at the domain boundary, which drives the system into formation of larger size domains. These results not only demonstrate that small membrane binding molecules such as neurotransmitters have a profound impact on essential membrane properties. It also suggests a mechanism by which the interaction of small molecules with membranes can influence the function of membrane proteins and non-cognate receptors. Altered membrane properties may modify lateral sorting of membrane protein, membrane protein conformation, and thus influence their function as suspected for neurotransmitters, local anesthetics, and other small drug molecules.

Mechanisms of Action for Small Molecules Revealed by Structural Biology in Drug Discovery

Small-molecule drugs are organic compounds affecting molecular pathways by targeting important proteins. These compounds have a low molecular weight, making them penetrate cells easily. Small-molecule drugs can be developed from leads derived from rational drug design or isolated from natural resources. A target-based drug discovery project usually includes target identification, target validation, hit identification, hit to lead and lead optimization. Understanding molecular interactions between small molecules and their targets is critical in drug discovery. Although many biophysical and biochemical methods are able to elucidate molecular interactions of small molecules with their targets, structural biology is the most powerful tool to determine the mechanisms of action for both targets and the developed compounds. Herein, we reviewed the application of structural biology to investigate binding modes of orthosteric and allosteric inhibitors. It is exemplified that structural biology provides a clear view of the binding modes of protease inhibitors and phosphatase inhibitors. We also demonstrate that structural biology provides insights into the function of a target and identifies a druggable site for rational drug design.

Label-free fluorescence detection of protein–ligand interactions based on binding-induced enzymatic cleavage protection

Label-free fluorescence monitoring protein–ligand interaction based on binding induced enzymatic cleavage protection.

Water-triggered union of multi-component reactions towards the synthesis of a 4H-chromene hybrid scaffold

An unprecedented union of multi-component reactions to construct pyrazole- and pyranopyrazole-adorned 4H-chromene from simple reactants in water at ambient temperature is reported. This innovative tactic has integrated two distinct four-component reactions (4CRs) that occur transiently to form four new heterocycles via ten covalent bonds in a single step.

A union of multi-component reactions to construct pyrazole- and pyranopyrazole-adorned 4H-chromene from simple reactants in water at RT is reported. 2 distinct four-component reactions occur transiently to form 4 new heterocycles via 10 covalent bonds in a single step.

R-BIND: An Interactive Database for Exploring and Developing RNA-Targeted Chemical Probes

While the opportunities available for targeting RNA with small molecules have been widely appreciated, the challenges associated with achieving specific RNA recognition in biological systems have hindered progress and prevented many researchers from entering the field. To facilitate the discovery of RNA-targeted chemical probes and their subsequent applications, we curated the RNA-targeted BIoactive ligaNd Database (R-BIND). This collection contains an array of information on reported chemical probes that target non-rRNA and have biological activity, and analysis has led to the discovery of RNA-privileged properties. Herein, we developed an online platform to make this information freely available to the community, offering search options, a suite of tools for probe development, and an updated R-BIND data set with detailed experimental information for each probe. We repeated the previous cheminformatics analysis on the updated R-BIND list and found that the distinguishing physicochemical, structural, and spatial properties remained unchanged, despite an almost 50% increase in the database size. Further, we developed several user-friendly tools, including queries based on cheminformatic parameters, experimental details, functional groups, and substructures. In addition, a nearest neighbor algorithm can assess the similarity of user-uploaded molecules to R-BIND ligands. These tools and resources can be used to design small molecule libraries, optimize lead ligands, or select targets, probes, assays, and control experiments. Chemical probes are critical to the study and discovery of novel functions for RNA, and we expect this resource to greatly assist researchers in exploring and developing successful RNA-targeted probes.

Covalent-Allosteric Inhibitors to Achieve Akt Isoform-Selectivity

Isoforms of protein kinase Akt are involved in essential processes including cell proliferation, survival, and metabolism. However, their individual roles in health and disease have not been thoroughly evaluated. Thus, there is an urgent need for perturbation studies, preferably mediated by highly selective bioactive small molecules. Herein, we present a structure‐guided approach for the design of structurally diverse and pharmacologically beneficial covalent‐allosteric modifiers, which enabled an investigation of the isoform‐specific preferences and the important residues within the allosteric site of the different isoforms. The biochemical, cellular, and structural evaluations revealed interactions responsible for the selective binding profiles. The isoform‐selective covalent‐allosteric Akt inhibitors that emerged from this approach showed a conclusive structure–activity relationship and broke ground in the development of selective probes to delineate the isoform‐specific functions of Akt kinases.

Rapid construction of tetrahydropyridine scaffolds via formal imino Diels-Alder reactions of Schiff bases and Nazarov reagents

Described is a one-flask, two-step method for the synthesis of highly functionalized piperidines. The process involves formal [4 + 2] cycloadditions of Schiff bases and Nazarov reagents, followed by facile elaborations of the initial cycloadducts. Notably, these aza-annulations are facilitated by protic solvents and proceed smoothly under ambient conditions, without other additives. The synthetic utility of this annulation protocol is further showcased through a concise, convergent synthesis of (±)-tetrabenazine.

Phenotype-based discovery of a HeLa-specific cytotoxic molecule that downregulates HPV-mediated signaling pathways via oxidative damage

Selective bioactive compounds have emerged as major players in chemical biology for their potential in disrupting diverse biological pathways with minimal adverse effects. Using phenotypic screening, we identified an anti-cancer agent, SB2001, with a highly specific cytotoxicity toward HeLa human cervical cancer cells. The subsequent mechanistic study revealed that SB2001 induced apoptotic cell death through restoring p53 function and suppressed the human papillomavirus (HPV)-mediated oncoprotein signaling pathway via oxidative damage in HeLa cells. SB2001 also selectively induced HeLa-specific tumor regression without any adverse effects in an in vivo tumor xenograft model, demonstrating its potential as a promising chemical probe.

A simple and sensitive detection of small molecule-protein interactions based on terminal protection-mediated exponential strand displacement amplification

We herein describe a simple and sensitive strategy to detect a small molecule-protein interaction based on terminal protection-mediated exponential strand displacement amplification (eSDA). In principle, the small molecule linked to a DNA probe protects the DNA probe against the exonuclease I-catalyzed degradation after its binding to the corresponding target protein. The protected DNA probe then serves as a template to promote eSDA. Consequently, a large number of duplexes are produced, which leads to a high fluorescence from a double-stranded DNA specific fluorescent dye, SYBR Green I. As a model system to prove this sensing strategy, the interaction between biotin and streptavidin (SA), which is known to be the strongest among the non-covalent biological interactions, was selected and its analytical performance was thoroughly investigated. As a result, SA was sensitively detected with the limit of detection of 16 pM. In addition, the practical applicability of this method was successfully demonstrated by reliably determining the SA in human serum.