Fourteen (hetero-)(arylidene)arylhydrazide derivatives (ABH1–ABH14) were synthesized, and their inhibitory activities against monoamine oxidases (MAOs) and acetylcholinesterase (AChE) were evaluated. Compound ABH5 most potently inhibited MAO-B with an IC50 value of 0.025 ± 0.0019 μM; ABH2 and ABH3 exhibited high IC50 values as well. Most of the compounds weakly inhibited MAO-A, except ABH5 (IC50 = 3.31 ± 0.41 μM). Among the active compounds, ABH2 showed the highest selectivity index (SI) of 174 for MAO-B, followed by ABH5 (SI = 132). ABH3 and ABH5 effectively inhibited AChE with IC50 values of 15.7 ± 6.52 and 16.5 ± 7.29 μM, respectively, whereas the other compounds were weak inhibitors of AChE. ABH5 was shown to be a reversible competitive inhibitor for MAO-A and MAO-B with Ki values of 0.96 ± 0.19 and 0.024 ± 0.0077 μM, respectively, suggesting that this molecule can be considered as an interesting candidate for further development as a multitarget inhibitor relating to neurodegenerative disorders.

Rheumatoid arthritis (RA) is a chronic autoimmune disease, which is compared to “immortal cancer” in industry. Currently, SYK, BTK, and JAK are the three major targets of protein tyrosine kinase for this disease. According to existing research, marketed and research drugs for RA are mostly based on single target, which limits their efficacy. Therefore, designing multitarget or dual-target inhibitors provide new insights for the treatment of RA regarding of the specific association between SYK, BTK, and JAK from two signal transduction pathways. In this study, machine learning (XGBoost, SVM) and deep learning (DNN) models were combined for the first time to build a powerful integrated model for SYK, BTK, and JAK. The predictive power of the integrated model was proved to be superior to that of a single classifier. In order to accurately assess the generalization ability of the integrated model, comprehensive similarity analysis was performed on the training and the test set, and the prediction accuracy of the integrated model was specifically analyzed under different similarity thresholds. External validation was conducted using single-target and dual-target inhibitors, respectively. Results showed that our model not only obtained a high recall rate (97%) in single-target prediction, but also achieved a favorable yield (54.4%) in dual-target prediction. Furthermore, by clustering dual-target inhibitors, the prediction performance of model in various classes were proved, evaluating the applicability domain of the model in the dual-target drug screening. In summary, the integrated model proposed is promising to screen dual-target inhibitors of SYK/JAK or BTK/JAK as RA drugs, which is beneficial for the clinical treatment of rheumatoid arthritis.

This is the final issue of ACS Combinatorial Science. I write these words with a profound sense of gratitude to the many authors and reviewers who have contributed to its pages, to our Editorial Advisory Board members who have provided wise counsel, and to the small but mighty group of associate editors and staff who have made the journal a joy to put together. I also write with both sadness and confidence at the literal and figurative turning of the page that the journal’s closing represents. Volume 1 of the Journal of Combinatorial Chemistry appeared on Jan. 12, 1999, under the direction of Founding Editor-in-Chief Anthony W. Czarnik. Tony was involved in the combi-chem revolution from its earliest days, when the idea of making and testing libraries of potential small-molecule drugs was new, and the nascent field was dominated by concerns about how parallel synthesis could be done and how compounds could be adequately characterized. New instruments for parallel reactions and purifications were all the rage, new ideas for molecular tagging or bead sorting were eagerly traded at meetings, and companies were founded and folded at a dizzying pace. But the heart of the Journal of Combinatorial Chemistry was always the chemistry: good reactions discovered and optimized for the synthesis of potentially useful molecular structures. The potential power of the field, at least to those moving into it, was obvious. For the most part, I shall not cite particular papers here, for fear of leaving out countless worthy contributions. But, for me, a 1996 review(1) by Wayne Guida and colleagues was critical to my appreciation of the subject. It posed the startling hypothesis that the potential size of the ultimate library of drug-like molecules was essentially infinite, estimated at up to 1063 distinct structures. This suggested that there must be a very large number of chemical answers to every question in any field that relied on molecular structure and properties. How to find some of those answers became a motivating concern for a substantial number of investigators, and the field of combinatorial chemistry was born. I succeeded Dr. Czarnik as Editor-in-Chief in late 2010, understanding that the field of drug discovery had undergone a revolution with the rollout of the first monoclonal antibody blockbuster, Humira (adalimumab). Antibodies are made by combinatorial synthesis and screening, whether by the immune system or by the laboratory investigator using techniques such as phage display. In appreciation of this, and a parallel understanding that the properties of polymeric materials and other systems of interacting molecular components were being developed by new methods of synthesis and analysis, the ACS agreed to change the name of the journal to ACS Combinatorial Science. As we wrote then, “The name change signals an expansion of the journal’s scope to include combinatorial and evolutionary approaches to problems in biology, molecular biology, materials science, and catalysis development, in addition to the journal’s traditional focus on synthetic chemistry methods and high-throughput drug discovery.” And we were off on a very interesting ride. ACS Combinatorial Science was the first and only ACS journal to be devoted to a way of doing science, rather than to a specific field of knowledge or application. It was perhaps, therefore, destined to be transient, since methods change. It is now undeniable that combinatorial approaches are woven deeply into the fabric of modern therapeutic development. Few companies pursuing a new small-molecule drug would think twice about making a candidate library to probe structure–activity relationships in a scaffold family, and every biotech startup, or academic laboratory in chemical biology for that matter, has at its fingertips powerful tools for generating and testing biomolecular libraries of immense size. The fields that use solid-state and polymeric materials, from photoelectronics to hydrogels to nanotechnology, now have at their disposal well-accepted methods of making and testing candidates of varying composition. New analytical methods have always been a vital part of combinatorial exploration, and these are now widely distributed and ever improving. Thus, at least the initial development of combinatorial molecular science and technology may be considered complete. Its impact has been profound, and its methods will continue to shape our world and help answer society’s most critical challenges. New chemistry will always infuse library synthesis and materials development. Biomolecular evolution will continue to grow in power and sophistication. And new excitement in such areas as machine learning and DNA-encoded libraries will continue to appear. I will look for all of these in the pages of other journals that cover an enormous range of subjects. And I commend all of you readers of this journal to many happy interactions in the combinatorial enterprise that is research itself and to the insights and discoveries that emerge from them. Views expressed in this editorial are those of the author and not necessarily the views of the ACS. This article references 1 other publications.

Combinatorial synthesis and high-throughput characterization of a Ni–Ti–Co thin film materials library are reported for exploration of reversible martensitic transformation. The library was prepared by magnetron co-sputtering, annealed in vacuum at 500 °C without atmospheric exposure, and evaluated for shape memory behavior as an indicator of transformation. Composition, structure, and transformation behavior of the 177 pads in the library were characterized using high-throughput wavelength dispersive spectroscopy (WDS), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and four-point probe temperature-dependent resistance (R(T)) measurements. A new, expanded composition space having phase transformation with low thermal hysteresis and Co > 10 at. % is found. Unsupervised machine learning methods of hierarchical clustering were employed to streamline data processing of the large XRD and XPS data sets. Through cluster analysis of XRD data, we identified and mapped the constituent structural phases. Composition–structure–property maps for the ternary system are made to correlate the functional properties to the local microstructure and composition of the Ni–Ti–Co thin film library.

In combinatorial chemical approaches, optimizing the composition and arrangement of building blocks toward a particular function has been done using a number of methods, including high throughput molecular screening, molecular evolution, and computational prescreening. Here, a different approach is considered that uses sparse measurements of library molecules as the input to a machine learning algorithm which generates a comprehensive, quantitative relationship between covalent molecular structure and function that can then be used to predict the function of any molecule in the possible combinatorial space. To test the feasibility of the approach, a defined combinatorial chemical space consisting of ∼1012 possible linear combinations of 16 different amino acids was used. The binding of a very sparse, but nearly random, sampling of this amino acid sequence space to 9 different protein targets is measured and used to generate a general relationship between peptide sequence and binding for each target. Surprisingly, measuring as little as a few hundred to a few thousand of the ∼1012 possible molecules provides sufficient training to be highly predictive of the binding of the remaining molecules in the combinatorial space. Furthermore, measuring only amino acid sequences that bind weakly to a target allows the accurate prediction of which sequences will bind 10–100 times more strongly. Thus, the molecular recognition information contained in a tiny fraction of molecules in this combinatorial space is sufficient to characterize any set of molecules randomly selected from the entire space, a fact that potentially has significant implications for the design of new chemical function using combinatorial chemical libraries.

Mutagenesis of surface-exposed residues, or “resurfacing”, is a protein engineering strategy that can be utilized to disrupt antibody recognition or modulate the capacity of a protein to elicit antibody responses. We apply resurfacing to engineer Dengue virus envelope protein domain III (DENV DIII) antigens with the goal of focusing humoral recognition on epitopes of interest by selective ablation of irrelevant and undesired epitopes. Cross-reactive but non-neutralizing antibodies have the potential to enhance Dengue virus (DENV) infection by a process called antibody-dependent enhancement, thought to be associated with severe secondary heterotypic infection. Thus, a focus on epitopes associated with broadly neutralizing antibodies is important both for understanding human antibody responses against DENV and for the development of a successful DENV vaccine. To engineer DENV DIII antigens focusing on the AG strand epitope associated with broadly neutralizing antibody responses, we generated yeast surface display libraries of DENV2 DIII where the AB loop (associated with cross-reactive but non-neutralizing antibody responses) and FG loop (associated with serotype-specific antibody responses) were mutagenized to allow for all possible amino acid substitutions. Loop variants that maintained the AG strand epitope and simultaneously disrupted the AB and FG loop epitopes exhibited high and diverse mutational loads that were amenable to loop exchange and transplantation into a DENV4 DIII background. Thus, several loop variants fulfill this antigenicity criteria regardless of serotype context. The resulting resurfaced DIII antigens may be utilized as AG strand epitope-focusing probes or immunogen candidates.

Ugi four-component reactions (U-4CRs) are widely recognized as being highly efficient for the synthesis of pseudopeptides. However, the products of these reactions are not so interesting as drug candidates because they are not conformationally restricted enough for a potent interaction with biological targets. One possible way to overcome this problem is to replace amine and oxo components in the U-4CRs with cyclic imines in so-called Joullié−Ugi three-component reactions (JU-3CRs). This approach provides a robust single-step route to peptide moieties connected to N-heterocyclic motifs that are found as core skeletons in many natural products and pharmaceutical compounds. JU-3CRs also provide much better diastereoselectivity than their four-component analogues. We survey here the redesign of many synthetic routes for the efficient preparation of a wide variety of three-, five-, six-, and seven-membered heterocyclic compounds connected to the peptide backbone. Additionally, in the Ugi reactions based on the cyclic imines, α-acidic isocyanides, or azides can be replaced with normal isocyanides or acids, respectively, leading to the synthesis of N-heterocycles attached to oxazoles or tetrazoles, which are of great pharmaceutical significance. This Review includes all research articles related to Ugi reactions based on the cyclic imines to the year 2020 and will be useful to chemists in designing novel synthetic routes for the synthesis of individual and combinatorial libraries of natural products and drug-like compounds.

For improved cost-effectiveness and temperature-stability, a ready to use lateral flow assay (LFA) is developed in this work for detecting inflammation/infection biomarker C-reactive protein (CRP) in human patient samples on the basis of aptamers. In prescreening investigations, an aptamer with CRP affinity was immobilized on microarray chips in forward and sandwich formats to optimize assay conditions. We suggest these microarray techniques as a resource-sparing and fast-screening instrument for evaluation of various conditions. The capability of the aptamer to detect CRP was shown. Optimized assay conditions were consequently transferred to the LFA-platform. Here we could demonstrate for the first time an aptamer-based LFA for the detection of CRP in human patient samples in pathologically relevant concentrations. The cutoff for CRP detection is set at 10 mg/L, providing a distinctive “yes” (≥10 mg/L CRP) or “no” (<10 mg/L CRP) answer for the patient. The resulting aptamer-based LFA is promising with regard to its application as point-of-care testing (POCT) for efficient monitoring, especially of patients affected by frequent infections or inflammations.

Electromanipulation and electrical characterization of cancerous cells is becoming a topic of high interest as the results reported to date demonstrate a good differentiation among various types of cells from an electrical viewpoint. Dielectrophoresis and broadband dielectric spectroscopy are complementary tools for sorting, identification, and characterization of malignant cells and were successfully used on both primary tumor cells and culture cells as well. However, the literature is presenting a plethora of studies with respect to electrical evaluation of these type of cells, and this review is reporting a collection of information regarding the functioning principles of different types of dielectrophoresis setups, theory of cancer cell polarization, and electrical investigation (including here the polarization mechanisms). The interpretation of electrical characteristics against frequency is discussed with respect to interfacial/Maxwell–Wagner polarization and the parasitic influence of electrode polarization. Moreover, the electrical equivalent circuits specific to biological cells polarizations are discussed for a good understanding of the cells’ morphology influence. The review also focuses on advantages of specific low-conductivity buffers employed currently for improving the efficiency of dielectrophoresis and provides a set of synthesized data from the literature highlighting clear differentiation between the crossover frequencies of different cancerous cells.

Peptide macrocyclization is typically associated with the development of higher affinity and more protease stable protein ligands, and, as such, is an important tool in peptide drug discovery. Yet, within the context of a diverse library, does cyclization give inherent advantages over linear peptides? Here, we used mRNA display to create a peptide library of diverse ring sizes and topologies (monocyclic, bicyclic, and linear). Several rounds of in vitro selection against streptavidin were performed and the winning peptide sequences were analyzed for their binding affinities and overall topologies. The effect of adding a protease challenge on the enrichment of various peptides was also investigated. Taken together, the selection output yields insights about the relative abundance of binders of various topologies within a structurally diverse library.

Research data management is a major necessity for the digital transformation in material science. Material science is multifaceted and experimental data, especially, is highly diverse. We demonstrate an adjustable approach to a group level data management based on a customizable document management software. Our solution is to continuously transform data management workflows from generalized to specialized data management. We start up fast with a relatively unregulated base setting and adapt continuously over the period of use to transform more and more data procedures into specialized data management workflows. By continuous adaptation and integration of analysis workflows and metadata schemes, the amount and the quality of the data improves. As an example of this process, in a period of 36 months, data on over 1800 samples, mainly materials libraries with hundreds of individual samples, were collected. The research data management system now contains over 1700 deposition processes and more than 4000 characterization documents. From initially mainly user-defined data input, an increased number of specialized data processing workflows was developed allowing the collection of more specialized, quality-assured data sets.

The power of ribosomes has increasingly been harnessed for the synthesis and selection of molecular libraries. Technologies, such as phage display, yeast display, and mRNA display, effectively couple genotype to phenotype for the molecular evolution of high affinity epitopes for many therapeutic targets. Genetic code expansion is central to the success of these technologies, allowing researchers to surpass the intrinsic capabilities of the ribosome and access new, genetically encoded materials for these selections. Here, we review techniques for the chemical expansion of genetically encoded libraries, their abilities and limits, and opportunities for further development. Importantly, we also discuss methods and metrics used to assess the efficiency of modification and library diversity with these new techniques.

A novel magnetic metal–organic framework (Fe3O4@[email protected]) has been prepared and characterized by spectroscopic, microscopic, and magnetic techniques. This magnetically separable catalyst exhibited high catalytic activity for nitrile hydration and the ability to reduce isothiocyanates, isocyanates, and isocyanides with excellent activity and selectivity without any additional reducing agent.

A MoS2-supported-calix[4]arene (MoS2-CA4) nanocatalyst was used for efficient synthesis of 2,4,5-trisubstituted imidazole derivatives from 1-(4-nitrophenyl)-2-(4-(trifluoromethyl)phenyl)ethane-1,2-dione, aldehydes and ammonium acetate under solvent-free conditions. Reusability of the catalyst up to five cycles without any significant loss in the yields of the product is the unique feature of this heterogeneous solid catalysis. Furthermore, the noteworthy highlights of this method are safe reaction profiles, broad substrate scope, excellent yields, economical, solvent-free, and simple workup conditions. All synthesized compounds were evaluated for their in vitro antitubercular (TB) activity against Mycobacterium tuberculosis (Mtb) H37Rv. Among the screened compounds 3c, 3d, 3f, 3m, and 3r had MIC values of 2.15, 2.78, 5.75, 1.36, and 0.75 μM, respectively, and exhibited more potency than the reference drugs pyrazinamide (MIC: 3.12 μM), ciprofloxacin (MIC: 4.73 μM), and ethambutol (7.61 μM). Besides, potent compounds (3c, 3d, 3f, 3m, and 3r) have been tested for inhibition of MabA (β-ketoacyl-ACP reductase) enzyme and cytotoxic activity against mammalian Vero cell line. A molecular docking study was carried out on the MabA (PDB ID: 1UZN) enzyme to predict the interactions of the synthesized compounds. The results of the in vitro anti-TB activity and docking study showed that synthesized compounds have a strong anti-TB activity and can be adapted and produced more effectively as a lead compound.

Nucleic acid aptamers are single-stranded oligonucleotides that may be evolved for affinity and specificity for their targets and can be easily produced, regenerated, and stabilized. In this study, we adapted Ni-NTA (nickle-charged nitrilotriacetic acid) affinity-chromatography in the development of single-stranded DNA aptamers against N-cadherin protein by systematic evolution of ligands by exponential enrichment (SELEX). After ten rounds of selection, two aptamers, designated NS13 and NC23, were selected, which showed low dissociation constants of 93 and 174 nM, respectively. The 5′-carboxyfluorescein-labeled NS13 was used for the sensitive detection of N-cadherin protein by the enzyme-linked oligonucleotide assay (ELONA) method.

The preparation of natural product-inspired nucleoside analogs using solution-phase parallel synthesis is described. The key intermediates containing alkyne and N-protected amino moieties were developed to allow for further skeleton and substituent diversity using click chemistry and urea or amide bond formation. Rapid purification was accomplished using solid-phase extraction. The obtained library comprised 80 molecules incorporating two diversity positions and one chiral center, each of which was efficiently prepared in good purity and acceptable overall yield. A bacterial morphology study was also performed.

We established a system for simultaneous measurements of photoelectrochemical (PEC) reaction and photoabsorption in a semiconductor photoelectrode. This system uses a photoacoustic technique and photoelectrodes with a film-thickness gradient that was prepared by electrophoretic deposition of tungsten(VI) oxide particles while pulling up a substrate. The system enabled high-throughput determination of optimum film thickness, and the results showed that irradiation direction has a significant influence on PEC performance for a photoelectrode with a thick film. Furthermore, the mechanism of enhancement of PEC performance by postnecking treatment was discussed.

Circulating tumor cells (CTCs) carry reliable clinical information for the diagnosis and treatment of cancer that is a malignant disease with a high mortality rate. However, the amount of CTCs in the blood is quite low. To obtain credible clinical information, an efficient method of extracting CTCs is necessary. Microfluidic technology has proven its effectiveness on CTCs separation in recent years. Here, we present a comprehensive review of CTC sorting methods based on microfluidics. Specifically, we introduce four different microfluidic sorting methods of CTCs and compare their advantages and disadvantages. Finally, we summarize the analysis of CTCs based on microfluidics and present a prospective view of future research.

Active metabolites from natural sources are the predominant molecular targets in numerous biological studies owing to their appropriate compatibility with biological systems and desirable selective toxicities. Thus, their potential for therapeutic development could span a broad scope of disease areas, including pathological and neurological dysfunctions. Cardiac glycosides are a unique class of specialized metabolites that have been extensively applied as therapeutic agents for the treatment of numerous heart conditions, and more recently, they have also been explored as probable antitumor agents. They are a class of naturally derived compounds that bind to and inhibit Na+/K+-ATPase. This study presents cardiac glycosides and their analogues with highlights on their applications, challenges, and prospects as lead compounds for cancer treatment.

A new coronavirus (CoV) caused a pandemic named COVID-19, which has become a global health care emergency in the present time. The virus is referred to as SARS-CoV-2 (severe acute respiratory syndrome-coronavirus-2) and has a genome similar (∼82%) to that of the previously known SARS-CoV (SARS coronavirus). An attractive therapeutic target for CoVs is the main protease (Mpro) or 3-chymotrypsin-like cysteine protease (3CLpro), as this enzyme plays a key role in polyprotein processing and is active in a dimeric form. Further, Mpro is highly conserved among various CoVs, and a mutation in Mpro is often lethal to the virus. Thus, drugs targeting the Mpro enzyme significantly reduce the risk of mutation-mediated drug resistance and display broad-spectrum antiviral activity. The combinatorial design of peptide-based inhibitors targeting the dimerization of SARS-CoV Mpro represents a potential therapeutic strategy. In this regard, we have compiled the literature reports highlighting the effect of mutations and N-terminal deletion of residues of SARS-CoV Mpro on its dimerization and, thus, catalytic activity. We believe that the present review will stimulate research in this less explored yet quite significant area. The effect of the COVID-19 epidemic and the possibility of future CoV outbreaks strongly emphasize the urgent need for the design and development of potent antiviral agents against CoV infections.