The Most Common Functional Groups in Bioactive Molecules and How Their Popularity Has Evolved over Time

Deep generative design with 3D pharmacophoric constraints

Generative models have increasingly been proposed as a solution to the molecular design problem. However, it has proved challenging to control the design process or incorporate prior knowledge, limiting their practical use in drug discovery. In particular, generative methods have made limited use of three-dimensional (3D) structural information even though this is critical to binding. This work describes a method to incorporate such information and demonstrates the benefit of doing so. We combine an existing graph-based deep generative model, DeLinker, with a convolutional neural network to utilise physically-meaningful 3D representations of molecules and target pharmacophores. We apply our model, DEVELOP, to both linker and R-group design, demonstrating its suitability for both hit-to-lead and lead optimisation. The 3D pharmacophoric information results in improved generation and allows greater control of the design process. In multiple large-scale evaluations, we show that including 3D pharmacophoric constraints results in substantial improvements in the quality of generated molecules. On a challenging test set derived from PDBbind, our model improves the proportion of generated molecules with high 3D similarity to the original molecule by over 300%. In addition, DEVELOP recovers 10× more of the original molecules compared to the baseline DeLinker method. Our approach is general-purpose, readily modifiable to alternate 3D representations, and can be incorporated into other generative frameworks. Code is available at https://github.com/oxpig/DEVELOP.

Visible light-driven conjunctive olefination

Carboxylic acids and aldehydes are ubiquitous in chemistry and are native functionalities in many bioactive molecules and natural products. As such, a general cross-coupling process that involves these partners would open new avenues to achieve molecular diversity. Here we report a visible-light-mediated and transition metal-free conjunctive olefination that uses an alkene 'linchpin' with a defined geometry to cross-couple complex molecular scaffolds that contain carboxylic acids and aldehydes. The chemistry merges two cornerstones of organic synthesis-namely, the Wittig reaction and photoredox catalysis-in a catalytic cycle that couples a radical addition process with the redox generation of a phosphonium ylide. The methodology allows the rapid structural diversification of bioactive molecules and natural products in a native form, with a high functional group tolerance, and also forges a new alkene functional group with a programmable E-Z stereochemistry.

FraGAT: a fragment-oriented multi-scale graph attention model for molecular property prediction

MOTIVATION

Molecular property prediction is a hot topic in recent years. Existing graph-based models ignore the hierarchical structures of molecules. According to the knowledge of chemistry and pharmacy, the functional groups of molecules are closely related to its physio-chemical properties and binding affinities. So, it should be helpful to represent molecular graphs by fragments that contain functional groups for molecular property prediction.

RESULTS

In this article, to boost the performance of molecule property prediction, we first propose a definition of molecule graph fragments that may be or contain functional groups, which are relevant to molecular properties, then develop a fragment-oriented multi-scale graph attention network for molecular property prediction, which is called FraGAT. Experiments on several widely used benchmarks are conducted to evaluate FraGAT. Experimental results show that FraGAT achieves state-of-the-art predictive performance in most cases. Furthermore, our case studies show that when the fragments used to represent the molecule graphs contain functional groups, the model can make better predictions. This conforms to our expectation and demonstrates the interpretability of the proposed model.

AVAILABILITY AND IMPLEMENTATION

The code and data underlying this work are available in GitHub, at https://github.com/ZiqiaoZhang/FraGAT.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Thiourea Organocatalysts as Emerging Chiral Pollutants: En Route to Porphyrin-Based (Chir)Optical Sensing

Environmental pollution with chiral organic compounds is an emerging problem requiring innovative sensing methods. Amino-functionalized thioureas, such as 2-(dimethylamino)cyclohexyl-(3,5-bis(trifluoromethyl)phenyl)thiourea (Takemoto’s catalyst), are widely used organocatalysts with virtually unknown environmental safety data. Ecotoxicity studies based on the Vibrio fischeri luminescence inhibition test reveal significant toxicity of Takemoto’s catalyst (EC50 = 7.9 mg/L) and its NH2-substituted analog (EC50 = 7.2–7.4 mg/L). The observed toxic effect was pronounced by the influence of the trifluoromethyl moiety. En route to the porphyrin-based chemosensing of Takemoto-type thioureas, their supramolecular binding to a series of zinc porphyrins was studied with UV-Vis and circular dichroism (CD) spectroscopy, computational analysis and single crystal X-ray diffraction. The association constant values generally increased with the increasing electron-withdrawing properties of the porphyrins and electron-donating ability of the thioureas, a result of the predominant Zn⋯N cation–dipole (Lewis acid–base) interaction. The binding event induced a CD signal in the Soret band region of the porphyrin hosts—a crucial property for chirality sensing of Takemoto-type thioureas.

Can an Intermediate Rate of Nitrogen Inversion Affect Drug Efficacy?

Nitrogen-inversion rates and diffusion coefficients were measured using 1H NMR for 14 drug-like molecules. The slow nitrogen-inversion rates interconverting the enantiomers of these molecules lay within a postulated intermediate range in terms of their ability to bind to proteins bounded by diffusion constraints, potentially affecting the availability, hence efficacy, of these compounds if they were utilized as drugs. The postulated intermediate range is based on a capture-volume concept, whereby the nitrogen inversion during the time a ligand takes to pass through a volume surrounding the protein binding site, as calculated by the diffusion rate, determines if it will influence ligand binding to the protein. In the systems examined here, the measured nitrogen-inversion rates and the times required to traverse the capture volume differed by a few orders of magnitude. Potentially more consequential are intermediate nitrogen-inversion rates in epimeric cases—since the energies of the interconverting species are unequal, a heavy bias against the eutomer might occur. The implications of an intermediate nitrogen-inversion rate are significant for in silico drug design, drug efficacy, molecular modeling of drug–protein binding, pharmacokinetics, drug enantiomer evaluation, etc. Due consideration of the process should thus be taken into account for drug development directions and in vitro evaluation.

Ti-Catalyzed and -Mediated Oxidative Amination Reactions

Titanium is an attractive metal for catalytic reaction development: it is earth-abundant, inexpensive, and generally nontoxic. However-like most early transition metals-catalytic redox reactions with Ti are difficult because of the stability of the high-valent Ti^IV state. Understanding the fundamental mechanisms behind Ti redox processes is key for making progress toward potential catalytic applications. This Account details recent progress in Ti-catalyzed (and -mediated) oxidative amination reactions that proceed through formally Ti^II/Ti^IV catalytic cycles.This class of reactions is built on our initial discovery of Ti-catalyzed [2 + 2 + 1] pyrrole synthesis from alkynes and azobenzene, where detailed mechanistic studies have revealed important factors that allow for catalytic turnover despite the inherent difficulty of Ti redox. Two important conclusions from mechanistic studies are that (1) low-valent Ti intermediates in catalysis can be stabilized through coordination of π-acceptor substrates or products, where they can act as "redox-noninnocent" ligands through metal-to-ligand π back-donation, and (2) reductive elimination processes with Ti proceed through π-type electrocyclic (or pericyclic) reaction mechanisms rather than direct σ-bond coupling.The key reactive species in Ti-catalyzed oxidative amination reactions are Ti imidos (Ti≡NR), which can be generated from either aryl diazenes (RN═NR) or organic azides (RN₃). These Ti imidos can then undergo [2 + 2] cycloadditions with alkynes, resulting in intermediates that can be coupled to an array of other unsaturated functional groups, including alkynes, alkenes, nitriles, and nitrosos. This basic reactivity pattern has been extended into a broad range of catalytic and stoichiometric oxidative multicomponent coupling reactions of alkynes and other reactive small molecules, leading to multicomponent syntheses of various heterocycles and aminated building blocks.For example, catalytic oxidative coupling of Ti imidos with two different alkynes leads to pyrroles, while stoichiometric oxidative coupling with alkynes and nitriles leads to pyrazoles. These heterocycle syntheses often yield substitution patterns that are complementary to those of classical condensation routes and provide access to new electron-rich, highly substituted heteroaromatic scaffolds. Furthermore, catalytic oxidative alkyne carboamination reactions can be accomplished via reaction of Ti imidos with alkynes and alkenes, yielding α,β-unsaturated imine or cyclopropylimine building blocks. New catalytic and stoichiometric oxidative amination methods such as alkyne α-diimination, isocyanide imination, and ring-opening oxidative amination of strained alkenes are continuously emerging as a result of better mechanistic understanding of Ti redox catalysis.Ultimately, these Ti-catalyzed and -mediated oxidative amination methods demonstrate the importance of examining often-overlooked elements like the early transition metals through the lens of modern catalysis: rather than a lack of utility, these elements frequently have undiscovered potential for new transformations with orthogonal or complementary selectivity to their late transition metal counterparts.

Synthesis and Bio-evaluation of 2-Alkyl Substituted Fluorinated Genistein Analogues Against Breast Cancer

BACKGROUND

Breast cancer is the leading cause of cancer death in women. The current methods of chemotherapy for breast cancer generally have strong adverse reactions and drug resistance. Therefore, the discovery of novel anti-breast cancer lead compounds is urgently needed.

OBJECTIVE

Design and synthesize a series of 2-alkyl substituted fluorinated genistein analogues and evaluate their anti-breast cancer activity.

METHODS

Target compounds were obtained in a multistep reaction synthesis. The anti-tumor activity of compounds I-1~I-35 were evaluated with MCF-7, MDA-MB-231, MDA-MB-435, and MCF-10A cell lines in vitro, with tamoxifen as the positive control. Molecular docking was used to study the interaction between the synthesized compounds and PI3K-gamma.

RESULTS

A series of 2-alkyl substituted fluorinated genistein analogues were designed, synthesized and screened for their bioactivity. Most of the compounds displayed better selectivity toward breast cancer cell lines as compared with tamoxifen. Among these analogues, I-2, I-3, I-4, I-9, I-15 and I-17 have the strongest selective inhibition of breast cancer cells. Compounds I-10, I-13, I-15, I-17 and I-33 were found to have significant inhibitory effects on breast cancer cells. Molecular docking studies have shown that these compounds may act as PI3Kγ inhibitors and may further exhibit anti-breast cancer effects.

CONCLUSION

Most of the newly synthesized compounds could highly selectively inhibit breast cancer cell lines. The experimental results indicate that the synthesized analogs may also have obvious selective inhibitory effects on other malignant proliferation cancer cells.

Nickel-Catalyzed Deaminative Cyanation: Nitriles and One-Carbon Homologation from Alkyl Amines

A nickel-catalyzed deaminative cyanation of Katritzky pyridinium salts has been developed. When it is coupled with formation of the pyridinium salt from primary amines, this method enables alkyl amines to be converted to alkyl nitriles. A less toxic cyanide reagent, Zn(CN)₂, is utilized, and diverse functional groups and heterocycles are tolerated. The method also enables a one-carbon homologation of alkyl amines via reduction of the nitrile products, in addition to many other potential transformations of the versatile nitrile group.

Enzymkatalysierte späte Modifizierungen: Besser spät als nie

Die Enzymkatalyse gewinnt zunehmend an Bedeutung in der Synthesechemie. Die durch Bioinformatik und Enzym‐Engineering stetig wachsende Zahl von Biokatalysatoren eröffnet eine große Vielfalt selektiver Reaktionen. Insbesondere für späte Funktionalisierungsreaktionen ist die Biokatalyse ein geeignetes Werkzeug, das oftmals der konventionellen De‐novo‐Synthese überlegen ist. Enzyme haben sich als nützlich erwiesen, um funktionelle Gruppen direkt in komplexe Molekülgerüste einzuführen sowie für die rasche Diversifizierung von Substanzbibliotheken. Biokatalytische Oxyfunktionalisierungen, Halogenierungen, Methylierungen, Reduktionen und Amidierungen sind von besonderem Interesse, da diese Strukturmotive häufig in Pharmazeutika vertreten sind. Dieser Aufsatz gibt einen Überblick über die Stärken und Schwächen der enzymkatalysierten späten Modifizierungen durch native und optimierte Enzyme in der Synthesechemie. Ebenso werden wichtige Beispiele in der Wirkstoffentwicklung hervorgehoben.

Enzymatic Late-Stage Modifications: Better Late Than Never

Enzyme catalysis is gaining increasing importance in synthetic chemistry. Nowadays, the growing number of biocatalysts accessible by means of bioinformatics and enzyme engineering opens up an immense variety of selective reactions. Biocatalysis especially provides excellent opportunities for late-stage modification often superior to conventional de novo synthesis. Enzymes have proven to be useful for direct introduction of functional groups into complex scaffolds, as well as for rapid diversification of compound libraries. Particularly important and highly topical are enzyme-catalysed oxyfunctionalisations, halogenations, methylations, reductions, and amide bond formations due to the high prevalence of these motifs in pharmaceuticals. This Review gives an overview of the strengths and limitations of enzymatic late-stage modifications using native and engineered enzymes in synthesis while focusing on important examples in drug development.

Decatungstate-Catalyzed C(sp3)-H Sulfinylation: Rapid Access to Diverse Organosulfur Functionality

Here we report the direct conversion of strong, aliphatic C(sp3)-H bonds into the corresponding alkyl sulfinic acids via decatungstate photocatalysis. This transformation has been applied to a diverse range of C(sp3)-rich scaffolds, including natural products and approved pharmaceuticals, providing efficient access to complex sulfur-containing products. To demonstrate the broad potential of this methodology for the divergent synthesis of pharmaceutically relevant molecules, procedures for the diversification of the sulfinic acid products into a range of medicinally relevant functional groups have been developed.

R-group replacement database for medicinal chemistry

Aim:

Generation of an R-group replacement system for compound optimization in medicinal chemistry.

Materials & methods:

From bioactive compounds, analogue series (ASs) were systematically extracted and from these ASs, all R-groups were isolated and further analyzed.

Exemplary results & data:

From more than 17,000 ASs, more than 50,000 unique R-groups were isolated. For the 500 most frequently used R-groups, preferred replacements were identified and organized in hierarchies. All original data and an R-group replacement database are made available in an open access deposition.

Limitations & next steps:

The searchable database has no limitations and can easily be modified using the source data we provide. The next step will be applying this R-group resource in practical medicinal chemistry projects as decision support.

To optimize the biological activity of small molecules in medicinal chemistry, series of analogues are generated by introducing substituents (R-groups) at different positions. The choice of R-groups largely depends on the experience of individual chemists. We have computationally isolated a large number of R-groups from currently available analogue series. Frequently used R-groups and their preferred replacements were identified and organized in a searchable database for medicinal chemists to aid in R-group selection.

Automated Generation of Novel Fragments Using Screening Data, a Dual SMILES Autoencoder, Transfer Learning and Syntax Correction

Fragment-based hit identification (FBHI) allows proportionately greater coverage of chemical space using fewer molecules than traditional high-throughput screening approaches. However, effectively exploiting this advantage is highly dependent on the library design. Solubility, stability, chemical complexity, chemical/shape diversity, and synthetic tractability for fragment elaboration are all critical aspects, and molecule design remains a time-consuming task for computational and medicinal chemists. Artificial neural networks have attracted considerable attention in automated de novo design applications and could also prove useful for fragment library design. Chemical autoencoders are neural networks consisting of encoder and decoder parts, which respectively compress and decompress molecular representations. The decoder is applied to samples drawn from the space of compressed representations to generate novel molecules that can be scored for properties of interest. Here, we report an autoencoder model using a recurrent neural network architecture, which was trained using 486,565 fragments curated from commercial sources, to simultaneously reconstruct both SMILES and chemical fingerprints. To explore its utility in fragment design, we applied transfer learning to the fingerprint decoder layers to train a classifier using 66 frequent hitter fragments identified from our screening campaigns. Using a particle swarm optimization sampling approach, we compare the performance of this "dual" model to an architecture encoding SMILES only. The dual model produced valid SMILES with improved features, considering a range of properties including aromatic ring counts, heavy atom count, synthetic accessibility, and a new fragment complexity score we term Feature Complexity (FeCo). Additionally, we demonstrate that generative performance is further enhanced by use of a simple syntax-correction procedure during training, in which invalid and undesirable SMILES are spiked into the training set. Finally, we used the syntax-corrected model to generate a library of novel candidate privileged fragments.

Comparative Study of Deep Generative Models on Chemical Space Coverage

In recent years, deep molecular generative models have emerged as promising methods for de novo molecular design. Thanks to the rapid advance of deep learning techniques, deep learning architectures such as recurrent neural networks, variational autoencoders, and adversarial networks have been successfully employed for constructing generative models. Recently, quite a few metrics have been proposed to evaluate these deep generative models. However, many of these metrics cannot evaluate the chemical space coverage of sampled molecules. This work presents a novel and complementary metric for evaluating deep molecular generative models. The metric is based on the chemical space coverage of a reference dataset-GDB-13. The performance of seven different molecular generative models was compared by calculating what fraction of the structures, ring systems, and functional groups could be reproduced from the largely unseen reference set when using only a small fraction of GDB-13 for training. The results show that the performance of the generative models studied varies significantly using the benchmark metrics introduced herein, such that the generalization capabilities of the generative models can be clearly differentiated. In addition, the coverages of GDB-13 ring systems and functional groups were compared between the models. Our study provides a useful new metric that can be used for evaluating and comparing generative models.

Rapid and Mild Lactamization Using Highly Electrophilic Triphosgene in a Microflow Reactor

Lactams are cyclic amides that are indispensable as drugs and as drug candidates. Conventional lactamization includes acid-mediated and coupling-agent-mediated approaches that suffer from narrow substrate scope, much waste, and/or high cost. Inexpensive, less-wasteful approaches mediated by highly electrophilic reagents are attractive, but there is an imminent risk of side reactions. Herein, a methods using highly electrophilic triphosgene in a microflow reactor that accomplishes rapid (0.5-10 s), mild, inexpensive, and less-wasteful lactamization are described. Methods A and B, which use N-methylmorpholine and N-methylimidazole, respectively, were developed. Various lactams and a cyclic peptide containing acid- and/or heat-labile functional groups were synthesized in good to high yields without the need for tedious purification. Undesired reactions were successfully suppressed, and the risk of handling triphosgene was minimized by the use of microflow technology.

What's in a Name? Drug Nomenclature and Medicinal Chemistry Trends using INN Publications

The World Health Organization assigns international nonproprietary names (INN), also known as common names, to compounds upon request from drug developers. Structures of INNs are publicly available and represent a source, albeit underused, to understand trends in drug research and development. Here, we explain how a common drug name is composed and analyze chemical entities from 2000 to 2021. In the analysis, we describe some changes that intertwine chemical structure, newer therapeutic targets (e.g., kinases), including a significant increase in the use of fluorine and of heterocycles, and some other evolutionary modifications, such as the progressive increase in molecular weight. Alongside these, small signs of change can be spotted, such as the rise in spirocyclic scaffolds and small rings and the emergence of unconventional structural moieties that might forecast the future to come.

Chalcones reverse the anxiety and convulsive behavior of adult zebrafish

In the treatment of anxiety and seizures, drugs of the benzodiazepine (BZD) class are used, which act on the Central Nervous System (CNS) through the neurotransmitter gamma-aminobutyric acid (GABA). Flavonoids modulate GABAA receptors. The aim of this study was to evaluate the anxiolytic and anticonvulsant effects of synthetic chalcones and their mechanisms of action via the GABAergic system, using adult zebrafish (ZFa). The animals were treated with chalcones (4.0 or 20 or 40 mg/kg; 20 µL; i.p) and submitted to the open field and 96 h toxicity test. Chalcones that cause locomotor alteration were evaluated in the light and dark anxiolytic test. The same doses of chalcones were evaluated in the anticonvulsant test. The lowest effective dose was chosen to assess the possible involvement in the GABAA receptor by blocking the flumazenil (fmz) antagonist. No chalcone was toxic and altered ZFa's locomotion. All chalcones had anxiolytic and anticonvulsant effects, mainly chalcones 1, where all doses showed effects in both tests. These effects were blocked by Fmz (antagonist GABAA), where it shows evidence of the performance of these activities of the GABA system. Therefore, this study demonstrated in relation to structure-activity, that the position of the substituents is important in the intensity of activities and that the absence of toxicity and the action of these compounds in the CNS, shows the pharmacological potential of these molecules, and, therefore, the insights are designed for the development of new drugs.

The role of reversible and irreversible covalent chemistry in targeted protein degradation

Proteolysis-targeting chimeras (PROTACs) that degrade disease-causing proteins by hijacking the endogenous ubiquitin-proteasome system have emerged as an exciting and transformative technology in both chemical biology and drug discovery. Currently, the majority of PROTACs use reversible non-covalent ligands for both the target protein of interest (POI) and E3 ligase. In this review, we explore the burgeoning role of reversible and irreversible covalent chemistry in targeted protein degradation. We highlight the key advantages of targeted covalent inhibitors, whether as the target POI or E3 ligase ligand, such as their ability to enhance the selectivity of PROTACs, enable access to more of the "undruggable" proteome and expand the repertoire of recruited E3 ligases.

Chemoselective Amide-Forming Ligation Between Acylsilanes and Hydroxylamines Under Aqueous Conditions

We report the facile amide-forming ligation of acylsilanes with hydroxylamines (ASHA ligation) under aqueous conditions. The ligation is fast, chemoselective, mild, high-yielding and displays excellent functional-group tolerance. Late-stage modifications of an array of marketed drugs, peptides, natural products, and biologically active compounds showcase the robustness and functional-group tolerance of the reaction. The key to the success of the reaction could be the possible formation of the strong Si-O bond via a Brook-type rearrangement. Given its simplicity and efficiency, this ligation has the potential to unfold new applications in the areas of medicinal chemistry and chemical biology.

One-Pot Synthesis of 3-Substituted 4H-Quinolizin-4-ones via Alkyne Substrate Control Strategy

Three-substituted 4H-quinolizin-4-ones were obtained via a facile method with good selectivity and high efficiency. On the basis of alkyne substrate control, the mild and cost-efficient reaction has a broad substrate scope (20 examples, up to 93% yield) and is also easy to scale up. Active sites on the products allow for further modifications. The alkyne substrate control strategy could be further extended to achieve more complex three-substituted 4H-quinolizin-4-one skeletons.

Overview of the SAMPL6 pKa challenge: evaluating small molecule microscopic and macroscopic pKa predictions

The prediction of acid dissociation constants (pKa) is a prerequisite for predicting many other properties of a small molecule, such as its protein-ligand binding affinity, distribution coefficient (log D), membrane permeability, and solubility. The prediction of each of these properties requires knowledge of the relevant protonation states and solution free energy penalties of each state. The SAMPL6 pKa Challenge was the first time that a separate challenge was conducted for evaluating pKa predictions as part of the Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) exercises. This challenge was motivated by significant inaccuracies observed in prior physical property prediction challenges, such as the SAMPL5 log D Challenge, caused by protonation state and pKa prediction issues. The goal of the pKa challenge was to assess the performance of contemporary pKa prediction methods for drug-like molecules. The challenge set was composed of 24 small molecules that resembled fragments of kinase inhibitors, a number of which were multiprotic. Eleven research groups contributed blind predictions for a total of 37 pKa distinct prediction methods. In addition to blinded submissions, four widely used pKa prediction methods were included in the analysis as reference methods. Collecting both microscopic and macroscopic pKa predictions allowed in-depth evaluation of pKa prediction performance. This article highlights deficiencies of typical pKa prediction evaluation approaches when the distinction between microscopic and macroscopic pKas is ignored; in particular, we suggest more stringent evaluation criteria for microscopic and macroscopic pKa predictions guided by the available experimental data. Top-performing submissions for macroscopic pKa predictions achieved RMSE of 0.7-1.0 pKa units and included both quantum chemical and empirical approaches, where the total number of extra or missing macroscopic pKas predicted by these submissions were fewer than 8 for 24 molecules. A large number of submissions had RMSE spanning 1-3 pKa units. Molecules with sulfur-containing heterocycles or iodo and bromo groups were less accurately predicted on average considering all methods evaluated. For a subset of molecules, we utilized experimentally-determined microstates based on NMR to evaluate the dominant tautomer predictions for each macroscopic state. Prediction of dominant tautomers was a major source of error for microscopic pKa predictions, especially errors in charged tautomers. The degree of inaccuracy in pKa predictions observed in this challenge is detrimental to the protein-ligand binding affinity predictions due to errors in dominant protonation state predictions and the calculation of free energy corrections for multiple protonation states. Underestimation of ligand pKa by 1 unit can lead to errors in binding free energy errors up to 1.2 kcal/mol. The SAMPL6 pKa Challenge demonstrated the need for improving pKa prediction methods for drug-like molecules, especially for challenging moieties and multiprotic molecules.

The Playbooks of Medicinal Chemistry Design Moves

Large databases of biologically relevant molecules, such as ChEMBL, SureChEMBL, or compound collections of pharmaceutical or agrochemical companies, are invaluable sources of medicinal chemistry information, albeit implicit. We developed a modified matched molecular pair approach to systematically and exhaustively extract the transformations in these databases and distill them into snippets of explicit design knowledge that are easily interpretable and directly applicable. The resulting "playbooks of medicinal chemistry design moves" capture the collective pharmaceutical and agrochemical research expertise across multiple chemists, companies, targets, and projects. They can be queried in an automated fashion for systematic prospective design and compound generation. The ChEMBL playbook and an application to exploit it are available at https://github.com/mahendra-awale/medchem_moves.

Global Assessment of Substituents on the Basis of Analogue Series

While bioisosteric replacements have been extensively investigated, comprehensive analyses of R-/functional groups have thus far been rare in medicinal chemistry. We introduce a new analysis concept for the exploration of chemical substituent space that is based upon bioactive analogue series as a source. From ∼24,000 analogue series, more than 19,000 substituents were isolated that were differently distributed. A subset of ∼400 substituent fragments occurred most frequently in different structural contexts. These substituents contained well-known R-groups as well as novel structures. Substitution site-specific replacement and network analysis revealed that chemically similar substituents preferentially occurred at given sites and identified intuitive substitution pathways that can be explored for compound design. Taken together, the results of our analysis provide new insights into substituent space and identify preferred substituents on the basis of analogue series. As a part of our study, all the data reported are made freely available.

Groundbreaking Anticancer Activity of Highly Diversified Oxadiazole Scaffolds

Nowadays, an increasing number of heterocyclic-based drugs found application in medicinal chemistry and, in particular, as anticancer agents. In this context, oxadiazoles—five-membered aromatic rings—emerged for their interesting biological properties. Modification of oxadiazole scaffolds represents a valid strategy to increase their anticancer activity, especially on 1,2,4 and 1,3,4 regioisomers. In the last years, an increasing number of oxadiazole derivatives, with remarkable cytotoxicity for several tumor lines, were identified. Structural modifications, that ensure higher cytotoxicity towards malignant cells, represent a solid starting point in the development of novel oxadiazole-based drugs. To increase the specificity of this strategy, outstanding oxadiazole scaffolds have been designed to selectively interact with biological targets, including enzymes, globular proteins, and nucleic acids, showing more promising antitumor effects. In the present work, we aim to provide a comprehensive overview of the anticancer activity of these heterocycles, describing their effect on different targets and highlighting how their structural versatility has been exploited to modulate their biological properties.