Novel chemical space exploration via natural products

Type of Tetrahydronaphthalene-Fused 1,5-Dipoles and Their Application in Polycyclic Compounds Synthesis

Palladium-catalyzed dipolar cycloaddition reactions represent an efficient strategy for the construction of cyclic compounds, with the development of novel dipolar precursors being a key focus. In this study, a new type of dipolar precursor was synthesized through the assembly of the vinylethylene carbonate unit and the tetrahydronaphthalene skeleton. This dipolar precursor can undergo [3 + 2], [5 + 4], and [5 + 2] cycloaddition reactions, leading to the construction of tetrahydronaphthalene-fused oxazolidin-2-ones, 1,5-oxazonines, and tetrahydrooxepines. In general, all of these reactions exhibited good reaction efficiency and functional group tolerance.

Probing the molecular mechanisms of α-synuclein inhibitors unveils promising natural candidates through machine-learning QSAR, pharmacophore modeling, and molecular dynamics simulations

Parkinson's disease is characterized by a multifactorial nature that is linked to different pathways. Among them, the abnormal deposition and accumulation of α-synuclein fibrils is considered a neuropathological hallmark of Parkinson's disease. Several synthetic and natural compounds have been tested for their potency to inhibit the aggregation of α-synuclein. However, the molecular mechanisms responsible for the potency of these drugs to further rationalize their development and optimization are yet to be determined. To enhance our understanding of the structural requirements necessary for modulating the aggregation of α-synuclein fibrils, we retrieved a large dataset of α-synuclein inhibitors with their reported potency from the ChEMBL database to explore their chemical space and to generate QSAR models for predicting new bioactive compounds. The best performing QSAR model was applied to the LOTUS natural products database to screen for potential α-synuclein inhibitors followed by a pharmacophore design using the representative compounds sampled from each cluster in the ChEMBL dataset. Five natural products were retained after molecular docking studies displaying a binding affinity of - 6.0 kcal/mol or lower. ADMET analysis revealed satisfactory properties and predicted that all the compounds can cross the blood-brain barrier and reach their target. Finally, molecular dynamics simulations demonstrated the superior stability of LTS0078917 compared to the clinical candidate, Anle138b. We found that LTS0078917 shows promise in stabilizing the α-synuclein monomer by specifically binding to its hairpin-like coil within the N-terminal region. Our dynamic analysis of the inhibitor-monomer complex revealed a tendency towards a more compact conformation, potentially reducing the likelihood of adopting an elongated structure that favors the formation and aggregation of pathological oligomers. These findings offer valuable insights for the development of novel α-synuclein inhibitors derived from natural sources.

Discovery of Anti-SARS-CoV-2 Nsp9 Binders from Natural Products by a Native Mass Spectrometry Approach

The search for effective antiviral agents against SARS-CoV-2 remains a critical global endeavor. In this study, we focused on the viral nucleocapsid protein Nsp9, which is a key player in viral RNA replication and an attractive drug target. Employing a two-pronged approach, an in-house natural product library was screened using native mass spectrometry to identify compounds capable of binding to Nsp9. From the initial screening, apart from the previously reported hit oridonin (protein binding ratio of 0.56 in the initial screening, Kd = 7.2 ± 1.0 μM), we have identified a second Nsp9-interacting compound, the diterpenoid ryanodine, with a protein binding ratio of 0.3 and a Kd of 48.05 ± 5.03 μM. To gain deeper insights into the binding interactions and to explore potential structural requirements, the collision-induced affinity selection mass spectrometry (CIAS-MS) approach allowed us to identify six known oridonin analogues produced by the plant Rabdosia rubescens, each with varying affinities to Nsp9. Native MS validation of their individual binding activities to Nsp9 revealed that all analogues exhibited reduced affinity compared to oridonin. Structural-activity relationship analysis highlighted key functional groups, including 1-OH, 6-OH, 7-OH, and the enone moiety, which are crucial for Nsp9 binding. Combined data from our native mass spectrometry and CIAS-MS approaches provide valuable insights into the molecular interactions between Nsp9 and these compounds.

Challenges in natural product-based drug discovery assisted with in silico-based methods

The application of traditional medicine by humans for the treatment of ailments as well as improving the quality of life far outdates recorded history. To date, a significant percentage of humans, especially those living in developing/underprivileged communities still rely on traditional medicine for primary healthcare needs. In silico-based methods have been shown to play a pivotal role in modern pharmaceutical drug discovery processes. The application of these methods in identifying natural product (NP)-based hits has been successful. This is very much observed in many research set-ups that use rationally in silico-based methods in combination with experimental validation techniques. The combination has rendered the use of in silico-based approaches even more popular and successful in the investigation of NPs. However, identifying and proposing novel NP-based hits for experimental validation comes with several challenges such as the availability of compounds by suppliers, the huge task of separating pure compounds from complex mixtures, the quantity of samples available from the natural source to be tested, not to mention the potential ecological impact if the natural source is exhausted. Because most peer-reviewed publications are biased towards "positive results", these challenges are generally not discussed in publications. In this review, we highlight and discuss these challenges. The idea is to give interested scientists in this field of research an idea of what they can come across or should be expecting as well as prompting them on how to avoid or fix these issues.

Codeine dysregulates ribosome biogenesis in Escherichia coli with DNA double-strand breaks to chart path to new classes of antibiotics

Aim

A bacterial genetics-guided approach was utilized for the discovery of new compounds affecting bacterial genome stability.

Materials & methods

Fungal extracts and fractions were tested for genome instability-mediated antibacterial activity. Interaction assays and RT-qPCR were used to identify compounds that boost the activity of sub-minimum inhibitory concentration streptomycin and obtain insights on the molecular mechanisms of the primary hit compound, respectively.

Results

Several extracts and fractions caused bacterial genome instability. Codeine, in synergy with streptomycin, regulates double-strand break (DSB) repair and causes bacterial ribosome dysfunction in the absence of DSBs, and dysregulation of ribosome biogenesis in a DSB-dependent manner.

Conclusion

This study demonstrates a potential viable strategy that we are exploring for the discovery of new chemical entities with activities against Escherichia coli and other bacterial pathogens.

Navigating bioactivity space in anti-tubercular drug discovery through the deployment of advanced machine learning models and cheminformatics tools: a molecular modeling based retrospective study

Mycobacterium tuberculosis is the bacterial strain that causes tuberculosis (TB). However, multidrug-resistant and extensively drug-resistant tuberculosis are significant obstacles to effective treatment. As a result, novel therapies against various strains of M. tuberculosis have been developed. Drug development is a lengthy procedure that includes identifying target protein and isolation, preclinical testing of the drug, and various phases of a clinical trial, etc., can take decades for a molecule to reach the market. Computational approaches such as QSAR, molecular docking techniques, and pharmacophore modeling have aided drug development. In this review article, we have discussed the various techniques in tuberculosis drug discovery by briefly introducing them and their importance. Also, the different databases, methods, approaches, and software used in conducting QSAR, pharmacophore modeling, and molecular docking have been discussed. The other targets targeted by these techniques in tuberculosis drug discovery have also been discussed, with important molecules discovered using these computational approaches. This review article also presents the list of drugs in a clinical trial for tuberculosis found drugs. Finally, we concluded with the challenges and future perspectives of these techniques in drug discovery.

Computer-aided drug design approaches applied to screen natural product's structural analogs targeting arginase in Leishmania spp

Introduction: Leishmaniasis is a disease with high mortality rates and approximately 1.5 million new cases each year. Despite the new approaches and advances to fight the disease, there are no effective therapies. Methods: Hence, this study aims to screen for natural products' structural analogs as new drug candidates against leishmaniasis. We applied Computer-aided drug design (CADD) approaches, such as virtual screening, molecular docking, molecular dynamics simulation, molecular mechanics-generalized Born surface area (MM-GBSA) binding free estimation, and free energy perturbation (FEP) aiming to select structural analogs from natural products that have shown anti-leishmanial and anti-arginase activities and that could bind selectively against the Leishmania arginase enzyme. Results: The compounds 2H-1-benzopyran, 3,4-dihydro-2-(2-methylphenyl)-(9CI), echioidinin, and malvidin showed good results against arginase targets from three parasite species and negative results for potential toxicities. The echioidinin and malvidin ligands generated interactions in the active center at pH 2.0 conditions by MM-GBSA and FEP methods. Conclusions: This work suggests the potential anti-leishmanial activity of the compounds and thus can be further in vitro and in vivo experimentally validated.

Bioactive Natural Product Discovery via Deuterium Adduct Bioactivity Screening

The discovery of bioactive natural products lies at the forefront of human medicine. The continued discovery of these molecules is imperative in the fight against infection and disease. While natural products have historically dominated the drug market, discovery in recent years has slowed significantly, partly due to limitations in current discovery methodologies. This work demonstrates a new workflow, deuterium adduct bioactivity screening (DABS), which pairs untargeted isotope labeling with whole cell binding assays for bioactive natural product discovery. DABS was validated and led to the discovery of a new isoprenyl guanidine alkaloid, zillamycin, which showed anti-cancer and anti-microbial activities. DABS thus represents a new workflow to accelerate discovery of natural products with a wide range of bioactive potentials.

Total Synthesis of Kopsone

A total synthesis of kopsone was achieved, featuring stereoselective preparation of an acyclic aldehyde having a protected hydroxylamine moiety via Ireland-Claisen rearrangement and intramolecular cycloaddition of an eight-membered cyclic nitrone to form the 2-azabicyclo[3.3.1]nonane skeleton.

Assessment of the antidiabetic potential of extract and novel phytoniosomes formulation of Tradescantia pallida leaves in the alloxan-induced diabetic mouse model

Diabetes inflicts health and economic burdens on communities and the present antidiabetic therapies have several drawbacks. Tradescantia pallida leaves have been used as a food colorant and food preservative; however, to our knowledge antidiabetic potential of the leaves of T. pallida has not been explored yet. The current study aimed to investigate the antidiabetic potential of T. pallida leaves extract and its comparison with the novel nisosome formulation of the extract. The leaves extract and phytoniosomes of T. pallida in doses of 15, 25 and 50 mg/kg were used to assess the oral glucose loaded, and alloxan-induced diabetic mice models. The biological parameters evaluated were; change in body weight, blood biochemistry, relative organ to body weight ratio and histopathology of the liver, pancreas and kidney. Results revealed that the extract 50 mg/kg and phytoniosomes 25 and 50 mg/kg remarkably reduced the blood glucose level in all hyperglycemic mice by possibly inhibiting α-amylase and α-glucosidase production. Body weight and blood biochemical parameters were considerably improved in phytoniosomes 50 mg/kg treated group. The relative body weight was similar to those of healthy mice in extract 50 mg/kg, phytoniosomes 25 mg/kg, and phytoniosomes 50 mg/kg treated groups. Histopathology showed the regeneration of cells in the CHN50 treated group. Hyphenated chromatographic analysis revealed potent metabolites, which confirmed the antidiabetic potential of the extract by inhibiting α-amylase and α-glucosidase using in silico analysis. The present data suggested that phytoniosomes have shown better antidiabetic potential than crude extract of these leaves.

Scaffold Hybrid of the Natural Product Tanshinone I with Piperidine for the Discovery of a Potent NLRP3 Inflammasome Inhibitor

Natural products provide inspiration and have proven to be the most valuable source for drug discovery. Herein, we report a scaffold hybrid strategy of Tanshinone I for the discovery of NLRP3 inflammasome inhibitors. 36 compounds were designed and synthesized, and the cheminformatic analyses showed that these compounds occupy a unique chemical space. The biological evaluation identified compounds 5j, 12a, and 12d as NLRP3 inflammasome inhibitors with significant potency, selectivity, and drug-likeness. Mechanistic studies revealed that these Tanshinone I derivatives could inhibit the degradation of the protein NLRP3 and block the oligomerization of NLRP3-induced apoptosis-associated speck-like proteins, thus inhibiting NLRP3 inflammasome activation. In addition, the water solubility, in vitro metabolic stability, and oral bioavailability of these compounds were also greatly improved compared to Tanshinone I. Therefore, this protocol provides a new structural evolution of Tanshinone I and a new class of potent NLRP3 inflammasome inhibitors.

Recent ring distortion reactions for diversifying complex natural products

Covering: 2013-2022.Chemical diversification of natural products is an efficient way to generate natural product-like compounds for modern drug discovery programs. Utilizing ring-distortion reactions for diversifying natural products would directly alter the core ring systems of small molecules and lead to the production of structurally complex and diverse compounds for high-throughput screening. We review the ring distortion reactions recently used in complexity-to-diversity (CtD) and pseudo natural products (pseudo-NPs) strategies for diversifying complex natural products. The core ring structures of natural products are altered via ring expansion, ring cleavage, ring edge-fusion, ring spiro-fusion, ring rearrangement, and ring contraction. These reactions can rapidly provide natural product-like collections with properties suitable for a wide variety of biological and medicinal applications. The challenges and limitations of current ring distortion reactions are critically assessed, and avenues for future improvements of this rapidly expanding field are discussed. We also provide a toolbox for chemists for the application of ring distortion reactions to access natural product-like molecules.

Thiol Reactivity of N-Aryl α-Methylene-γ-lactams: Influence of the Guaianolide Structure

The α-methylene-γ-lactam offers promise as a complementary warhead for the development of targeted covalent inhibitors. However, an understanding of the factors governing its electrophilic reactivity is needed to promote the development of lead compounds utilizing this motif. Herein we synthesize a series of N-aryl-substituted α-methylene-γ-lactams installed within the framework of a bioactive guaianolide analog. To determine the effects of the guaianolide structure on the electrophilic reactivity, these compounds were reacted with glutathione under biomimetic conditions, and the rate constants were measured. A linear free-energy relationship was observed with the Hammett parameter of the N-aryl group within the cis- or trans-annulated isomeric series of compounds. However, the trans-annulated compounds exhibited a ca. 10-fold increase in reactivity relative to both the cis-annulated compounds and the corresponding N-arylated 3-methylene-2-pyrrolidinones. Density functional theory calculations revealed that the reactivity of the trans-annulated stereoisomers is promoted by the partial release of the ring strain of the fused seven-membered ring in the thio-Michael addition transition state.

Natural products for infectious microbes and diseases: an overview of sources, compounds, and chemical diversities

As coronavirus disease 2019 (COVID-19) threatens human health globally, infectious disorders have become one of the most challenging problem for the medical community. Natural products (NP) have been a prolific source of antimicrobial agents with widely divergent structures and a range vast biological activities. A dataset comprising 618 articles, including 646 NP-based compounds from 672 species of natural sources with biological activities against 21 infectious pathogens from five categories, was assembled through manual selection of published articles. These data were used to identify 268 NP-based compounds classified into ten groups, which were used for network pharmacology analysis to capture the most promising lead-compounds such as agelasine D, dicumarol, dihydroartemisinin and pyridomycin. The distribution of maximum Tanimoto scores indicated that compounds which inhibited parasites exhibited low diversity, whereas the chemistries inhibiting bacteria, fungi, and viruses showed more structural diversity. A total of 331 species of medicinal plants with compounds exhibiting antimicrobial activities were selected to classify the family sources. The family Asteraceae possesses various compounds against C. neoformans, the family Anacardiaceae has compounds against Salmonella typhi, the family Cucurbitacea against the human immunodeficiency virus (HIV), and the family Ancistrocladaceae against Plasmodium. This review summarizes currently available data on NP-based antimicrobials against refractory infections to provide information for further discovery of drugs and synthetic strategies for anti-infectious agents.

Natural product drug discovery in the artificial intelligence era

Natural products (NPs) are primarily recognized as privileged structures to interact with protein drug targets. Their unique characteristics and structural diversity continue to marvel scientists for developing NP-inspired medicines, even though the pharmaceutical industry has largely given up. High-performance computer hardware, extensive storage, accessible software and affordable online education have democratized the use of artificial intelligence (AI) in many sectors and research areas. The last decades have introduced natural language processing and machine learning algorithms, two subfields of AI, to tackle NP drug discovery challenges and open up opportunities. In this article, we review and discuss the rational applications of AI approaches developed to assist in discovering bioactive NPs and capturing the molecular "patterns" of these privileged structures for combinatorial design or target selectivity.

Tilianin: A Potential Natural Lead Molecule for New Drug Design and Development for the Treatment of Cardiovascular Disorders

Cardiovascular disorders (CVDs) are the leading risk factor for death worldwide, and research into the processes and treatment regimens has received a lot of attention. Tilianin is a flavonoid glycoside that can be found in a wide range of medicinal plants and is most commonly obtained from Dracocephalum moldavica. Due to its extensive range of biological actions, it has become a well-known molecule in recent years. In particular, numerous studies have shown that tilianin has cardioprotective properties against CVDs. Hence, this review summarises tilianin’s preclinical research in CVDs, as well as its mechanism of action and opportunities in future drug development. The physicochemical and drug-likeness properties, as well as the toxicity profile, were also highlighted. Tilianin can be a natural lead molecule in the therapy of CVDs such as coronary heart disease, angina pectoris, hypertension, and myocardial ischemia, according to scientific evidence. Free radical scavenging, inflammation control, mitochondrial function regulation, and related signalling pathways are all thought to play a role in tilianin’s cardioprotective actions. Finally, we discuss tilianin-derived compounds, as well as the limitations and opportunities of using tilianin as a lead molecule in drug development for CVDs. Overall, the scientific evidence presented in this review supports that tilianin and its derivatives could be used as a lead molecule in CVD drug development initiatives.

Diversity and Chemical Library Networks of Large Data Sets

The quantification of chemical diversity has many applications in drug discovery, organic chemistry, food, and natural product chemistry, to name a few. As the size of the chemical space is expanding rapidly, it is imperative to develop efficient methods to quantify the diversity of large and ultralarge chemical libraries and visualize their mutual relationships in chemical space. Herein, we show an application of our recently introduced extended similarity indices to measure the fingerprint-based diversity of 19 chemical libraries typically used in drug discovery and natural products research with over 18 million compounds. Based on this concept, we introduce the Chemical Library Networks (CLNs) as a general and efficient framework to represent visually the chemical space of large chemical libraries providing a global perspective of the relation between the libraries. For the 19 compound libraries explored in this work, it was found that the (extended) Tanimoto index offers the best description of extended similarity in combination with RDKit fingerprints. CLNs are general and can be explored with any structure representation and similarity coefficient for large chemical libraries.

Qualitative and Quantitative Comparison of Liquid–Liquid Phase Extraction Using Ethyl Acetate and Liquid–Solid Phase Extraction Using Poly-Benzyl-Resin for Natural Products

A key step in the process of isolating microbial natural products is the preparation of an extract from a culture. This step determines which molecules will be available for detection in the subsequent chemical and biological analysis of a biodiscovery pipeline. In the present study we wanted to document potential differences in performance between liquid–liquid extraction using ethyl acetate and liquid–solid extraction using a poly-benzyl-resin. For the comparison of the two extraction protocols, we spiked a culture of Flavobacterium sp. with a diverse selection of natural products of microbial and plant origin to investigate whether the methods were comparable with respect to selectivity. We also investigated the efficiency of the two extraction methods quantitatively, using water spiked with a selection of natural products, and studied the quantitative effect of different pH levels of the aqueous solutions on the extraction yields of the two methods. The same compounds were extracted by the two methods, but the solid-phase extract contained more media components compared with the liquid-phase extract. Quantitatively, the two extraction methods varied in their recovery rates. We conclude that practical aspects could be more important when selecting one of the extraction protocols, as their efficiencies in extracting specific compounds were quite similar.

Investigating Fungi-Derived Bioactive Molecules as Inhibitor of the SARS Coronavirus Papain Like Protease: Computational Based Study

Due to the rapid growth of the COVID-19 pandemic and its outcomes, developing a remedy to fight the predicament is critical. So far, it has infected more than 214,468,601 million people and caused the death of 4,470,969 million people according to the August 27, 2021, World Health Organization's (WHO) report. Several studies have been published on both computational and wet-lab approaches to develop antivirals for COVID-19, although there has been no success yet. However, the wet-lab approach is laborious, expensive, and time-consuming, and computational techniques have screened the activity of bioactive compounds from different sources with less effort and cost. For this investigation, we screened the binding affinity of fungi-derived bioactive molecules toward the SARS coronavirus papain-like protease (PLpro) by using computational approaches. Studies showed that protease inhibitors can be very effective in controlling virus-induced infections. Additionally, fungi represent a vast source of bioactive molecules, which could be potentially used for antiviral therapy. Fifty fungi-derived bioactive compounds were investigated concerning SARS-CoV-2 PLpro by using Auto Dock 4.2.1, Gromacs 2018. 2, ADMET, Swiss-ADME, FAF-Drugs 4.023, pKCSM, and UCLA-DOE server. From the list of the screened bioactive compounds, Dihydroaltersolanol C, Anthraquinone, Nigbeauvin A, and Catechin were selected with the Auto-Dock results of -8.68, -7.52, -10.46, and -10.58 Kcal/mol, respectively, based on their binding affinity compared to the reference drug. We presented the drug likeliness, toxicity, carcinogenicity, and mutagenicity of all compounds using ADMET analysis. They interacted with the amino acid residues, Gly163, Trp106, Ser111, Asp164, and Cys270, through hydrogen bonds. The root-mean-square deviation (RMSD), root-mean-square fluctuations (RMSF), solvent-accessible surface area (SASA), and radius of gyration (Rg) values revealed a stable interaction. From the overall analyses, we can conclude that Dihydroaltersolanol C, Anthraquinone, Nigbeauvin A, and Catechin are classified as promising candidates for PLpro, thus potentially useful in developing a medicine for COVID-19.

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.

The Transporter-Mediated Cellular Uptake and Efflux of Pharmaceutical Drugs and Biotechnology Products: How and Why Phospholipid Bilayer Transport Is Negligible in Real Biomembranes

Over the years, my colleagues and I have come to realise that the likelihood of pharmaceutical drugs being able to diffuse through whatever unhindered phospholipid bilayer may exist in intact biological membranes in vivo is vanishingly low. This is because (i) most real biomembranes are mostly protein, not lipid, (ii) unlike purely lipid bilayers that can form transient aqueous channels, the high concentrations of proteins serve to stop such activity, (iii) natural evolution long ago selected against transport methods that just let any undesirable products enter a cell, (iv) transporters have now been identified for all kinds of molecules (even water) that were once thought not to require them, (v) many experiments show a massive variation in the uptake of drugs between different cells, tissues, and organisms, that cannot be explained if lipid bilayer transport is significant or if efflux were the only differentiator, and (vi) many experiments that manipulate the expression level of individual transporters as an independent variable demonstrate their role in drug and nutrient uptake (including in cytotoxicity or adverse drug reactions). This makes such transporters valuable both as a means of targeting drugs (not least anti-infectives) to selected cells or tissues and also as drug targets. The same considerations apply to the exploitation of substrate uptake and product efflux transporters in biotechnology. We are also beginning to recognise that transporters are more promiscuous, and antiporter activity is much more widespread, than had been realised, and that such processes are adaptive (i.e., were selected by natural evolution). The purpose of the present review is to summarise the above, and to rehearse and update readers on recent developments. These developments lead us to retain and indeed to strengthen our contention that for transmembrane pharmaceutical drug transport "phospholipid bilayer transport is negligible".

Nature-derived hit, lead, and drug-like small molecules: Current status and future aspects against key target proteins of Coronaviruses

BACKGROUND

COVID-19 pandemic, the most unprecedented event of the year 2020, has brought millions of scientists worldwide in a single platform to fight against it. Though several drugs are now in the clinical trial, few vaccines available on the market already but the lack of an effect of those is making the situation worse.

AIM OF THE STUDY

In this review, we demonstrated comprehensive data of natural antiviral products showing activities against different proteins of Human Coronaviruses (HCoV) that are responsible for its pathogenesis. Furthermore, we categorized the compounds into the hit, lead, and drug based on the IC50/EC50 value, drug-likeness, and lead-likeness test to portray their potentiality to be a drug. We also demonstrated the present status of our screened antiviral compounds with respect to clinical trials and reported the lead compounds that can be promoted to clinical trial against COVID-19.

METHODS

A systematic search strategy was employed focusing on Natural Products (NPs) with proven activity (in vitro, in vivo, or in silico) against human coronaviruses, in general, and data were gathered from databases like PubMed, Web of Science, Google Scholar, SciVerse, and Scopus. Information regarding clinical trials retrieved from the Clinical Trial database.

RESULTS

Total "245" natural compounds were identified initially from the literature study. Among them, Glycyrrhizin, Caffeic acid, Curcumin is in phase 3, and Tetrandrine, Cyclosporine, Tacrolimus, Everolimus are in phase 4 clinical trial. Except for Glycyrrhizin, all compounds showed activity against COVID-19.

CONCLUSIONS

In summary, our demonstrated specific small molecules with lead and drug-like capabilities clarified their position in the drug discovery pipeline and proposed their future research against COVID-19.

Recent update on nano-phytopharmaceuticals in the management of diabetes

Due to changed lifestyle and other reasons, diabetes has become one of the common metabolic disorder of the globe. Numerous therapeutic options are available, which controls the plasma glucose levels. However, most of the drugs are associated with some undesired side effects. Owing to the side effects and enhanced understanding of the phytochemicals, an inclination toward herbal medicine is seen in the population. These herbal products are also associated with concerns like poor aqueous solubility, compromised permeation, and a low degree of bioavailability. So, the emergence of nanotechnology in the herbal medicine is required to nullify the associated concerns of conventional antidiabetic drugs. The present review aims to compile the literature available for the nano-interventions pertinent to herbal products for diabetes management.

Exploring the chemical space of protein-protein interaction inhibitors through machine learning

Although protein-protein interactions (PPIs) have emerged as the basis of potential new therapeutic approaches, targeting intracellular PPIs with small molecule inhibitors is conventionally considered highly challenging. Driven by increasing research efforts, success rates have increased significantly in recent years. In this study, we analyze the physicochemical properties of 9351 non-redundant inhibitors present in the iPPI-DB and TIMBAL databases to define a computational model for active compounds acting against PPI targets. Principle component analysis (PCA) and k-means clustering were used to identify plausible PPI targets in regions of interest in the active group in the chemical space between active and inactive iPPI compounds. Notably, the uniquely defined active group exhibited distinct differences in activity compared with other active compounds. These results demonstrate that active compounds with regions of interest in the chemical space may be expected to provide insights into potential PPI inhibitors for particular protein targets.

NP Navigator: A New Look at the Natural Product Chemical Space

Natural products (NPs), being evolutionary selected over millions of years to bind to biological macromolecules, remained an important source of inspiration for medicinal chemists even after the advent of efficient drug discovery technologies such as combinatorial chemistry and high-throughput screening. Thus, there is a strong demand for efficient and user-friendly computational tools that allow to analyze large libraries of NPs. In this context, we introduce NP Navigator - a freely available intuitive online tool for visualization and navigation through the chemical space of NPs and NP-like molecules. It is based on the hierarchical ensemble of generative topographic maps, featuring NPs from the COlleCtion of Open NatUral producTs (COCONUT), bioactive compounds from ChEMBL and commercially available molecules from ZINC. NP Navigator allows to efficiently analyze different aspects of NPs - chemotype distribution, physicochemical properties, biological activity and commercial availability of NPs. The latter concerns not only purchasable NPs but also their close analogs that can be considered as synthetic mimetics of NPs or pseudo-NPs.

Cheminformatic Profiling and Hit Prioritization of Natural Products with Activities against Methicillin-Resistant Staphylococcus aureus (MRSA)

Several natural products (NPs) have displayed varying in vitro activities against methicillin-resistant Staphylococcus aureus (MRSA). However, few of these compounds have not been developed into potential antimicrobial drug candidates. This may be due to the high cost and tedious and time-consuming process of conducting the necessary preclinical tests on these compounds. In this study, cheminformatic profiling was performed on 111 anti-MRSA NPs (AMNPs), using a few orally administered conventional drugs for MRSA (CDs) as reference, to identify compounds with prospects to become drug candidates. This was followed by prioritizing these hits and identifying the liabilities among the AMNPs for possible optimization. Cheminformatic profiling revealed that most of the AMNPs were within the required drug-like region of the investigated properties. For example, more than 76% of the AMNPs showed compliance with the Lipinski, Veber, and Egan predictive rules for oral absorption and permeability. About 34% of the AMNPs showed the prospect to penetrate the blood–brain barrier (BBB), an advantage over the CDs, which are generally non-permeant of BBB. The analysis of toxicity revealed that 59% of the AMNPs might have negligible or no toxicity risks. Structure–activity relationship (SAR) analysis revealed chemical groups that may be determinants of the reported bioactivity of the compounds. A hit prioritization strategy using a novel “desirability scoring function” was able to identify AMNPs with the desired drug-likeness. Hit optimization strategies implemented on AMNPs with poor desirability scores led to the design of two compounds with improved desirability scores.

Thermal proteome profiling reveals GPX4 as the target of the autophagy inducer conophylline

Conophylline (CNP) is a vinca alkaloid extracted from the Tabernaemontana divaricata plant. It has been reported that CNP induces autophagy in a mammalian target of rapamycin (mTOR)-independent manner, thereby inhibits protein aggregation. However, the mode of action of CNP in inducing autophagy remains unknown. In this study, we identified glutathione peroxidase 4 (GPX4) as a CNP-binding protein by using thermal proteome profiling (TPP). The technique exploits changes in the thermal stability of proteins resulting from ligand interaction, which is capable of identifying compound-binding proteins without chemical modification. GPX4, an antioxidant protein that uses reduced glutathione as a cofactor, directly catalyzes the reduction of hydrogen peroxide, organic hydroperoxides, and lipid peroxides. GPX4 suppresses lipid peroxide accumulation, thus plays a key role in protecting cells from oxidative damage. We found that treatment with CNP caused accumulation of lipid reactive oxygen species (ROS) in cultured cells. Furthermore, similarly with CNP treatment, GPX4 deficiency caused accumulation of lipid ROS and induced autophagy. These findings indicate that GPX4 is a direct target of CNP involved in autophagy induction. Significance Statement In the present study, we identified glutathione peroxidase 4 (GPX4) as a binding protein of conophylline (CNP) by using thermal proteome profiling (TPP).We showed that CNP treatment, similarly with the inhibition of GPX4, induced lipid ROS accumulation and autophagy. The present findings suggest that GPX4 is the CNP target protein involved in autophagy induction. Furthermore, these results indicates that TPP is a useful technique for determining the mechanism of natural compounds.

Protein druggability assessment for natural products using in silico simulation: A case study with estrogen receptor and the flavonoid genistein

Traditional herbal medicine (THM) comprises a vast number of natural compounds. Most of them are metabolized into different structures after administration, which makes the clarification of THM's mode of action more complicated. To evaluate the biological activities of those components and metabolites, in silico simulation technology is helpful. We focused on mixed-solvent molecular dynamics (MD) simulation for druggability assessment of natural products. Mixed-solvent MD is an in silico simulation method for the exploration of ligand-binding sites on target proteins, which uses water and an organic molecule mixture. The selection of organic small molecules is an important factor for predicting the characteristics of natural products. In this study, we used the known crystal structure of estrogen receptors with genistein as a test case and explored fragments reflecting the characteristics of natural products. We found that structures with a 4-pyrone structure are more often included in the natural products database compared with the DrugBank database, and we selectively detected the known-binding sites of estrogen receptor α and β. The results indicate that the 4-pyrone structure might be promising for predicting the protein druggability of flavonoids. Additionally, mixed-solvent MD simulation discriminates the selectivity of genistein between estrogen receptor β and α, indicating that the simulation can be evaluated using indices that differ from those of traditional ligand docking. Although this approach is still in its early stages, it has the potential to provide valuable information for understanding the diverse biological activities of natural products.

FragNet, a Contrastive Learning-Based Transformer Model for Clustering, Interpreting, Visualizing, and Navigating Chemical Space

The question of molecular similarity is core in cheminformatics and is usually assessed via a pairwise comparison based on vectors of properties or molecular fingerprints. We recently exploited variational autoencoders to embed 6M molecules in a chemical space, such that their (Euclidean) distance within the latent space so formed could be assessed within the framework of the entire molecular set. However, the standard objective function used did not seek to manipulate the latent space so as to cluster the molecules based on any perceived similarity. Using a set of some 160,000 molecules of biological relevance, we here bring together three modern elements of deep learning to create a novel and disentangled latent space, viz transformers, contrastive learning, and an embedded autoencoder. The effective dimensionality of the latent space was varied such that clear separation of individual types of molecules could be observed within individual dimensions of the latent space. The capacity of the network was such that many dimensions were not populated at all. As before, we assessed the utility of the representation by comparing clozapine with its near neighbors, and we also did the same for various antibiotics related to flucloxacillin. Transformers, especially when as here coupled with contrastive learning, effectively provide one-shot learning and lead to a successful and disentangled representation of molecular latent spaces that at once uses the entire training set in their construction while allowing "similar" molecules to cluster together in an effective and interpretable way.

Synthesis of Morpholine-Based Analogues of (-)-Zampanolide and Their Biological Activity

We describe the convergent synthesis of three prototypical examples of a new class of analogues of the complex, cytotoxic marine macrolide (-)-zampanolide that incorporate an embedded N-substituted morpholine moiety in place of the natural tetrahydropyran ring. The final construction of the macrolactone core was based on a high-yielding intramolecular HWE olefination, while the hemiaminal-linked side chain was elaborated through a stereoselective, BINAL-H-mediated addition of (Z,E)-sorbamide to a macrocyclic aldehyde precursor. The synthesis of the common functionalized morpholine building block involved two consecutive epoxide openings with tosylamide and the product of the first opening reaction, respectively, as nucleophiles. Of the three morpholino-zampanolides investigated, the N-acetyl and the N-benzoyl derivatives both exhibited nanomolar antiproliferative activity, thus being essentially equipotent with the natural product. In contrast, the activity of the N-tosyl derivative was significantly reduced.

Ethnobotany and the Role of Plant Natural Products in Antibiotic Drug Discovery

The crisis of antibiotic resistance necessitates creative and innovative approaches, from chemical identification and analysis to the assessment of bioactivity. Plant natural products (NPs) represent a promising source of antibacterial lead compounds that could help fill the drug discovery pipeline in response to the growing antibiotic resistance crisis. The major strength of plant NPs lies in their rich and unique chemodiversity, their worldwide distribution and ease of access, their various antibacterial modes of action, and the proven clinical effectiveness of plant extracts from which they are isolated. While many studies have tried to summarize NPs with antibacterial activities, a comprehensive review with rigorous selection criteria has never been performed. In this work, the literature from 2012 to 2019 was systematically reviewed to highlight plant-derived compounds with antibacterial activity by focusing on their growth inhibitory activity. A total of 459 compounds are included in this Review, of which 50.8% are phenolic derivatives, 26.6% are terpenoids, 5.7% are alkaloids, and 17% are classified as other metabolites. A selection of 183 compounds is further discussed regarding their antibacterial activity, biosynthesis, structure-activity relationship, mechanism of action, and potential as antibiotics. Emerging trends in the field of antibacterial drug discovery from plants are also discussed. This Review brings to the forefront key findings on the antibacterial potential of plant NPs for consideration in future antibiotic discovery and development efforts.

The Ascidian-Derived Metabolites with Antimicrobial Properties

Among the sub-phylum of Tunicate, ascidians represent the most abundant class of marine invertebrates, with 3000 species by heterogeneous habitat, that is, from shallow water to deep sea, already reported. The chemistry of these sessile filter-feeding organisms is an attractive reservoir of varied and peculiar bioactive compounds. Most secondary metabolites isolated from ascidians stand out for their potential as putative therapeutic agents in the treatment of several illnesses like microbial infections. In this review, we present and discuss the antibacterial activity shown by the main groups of ascidian-derived products, such as sulfur-containing compounds, meroterpenes, alkaloids, peptides, furanones, and their derivatives. Moreover, the direct evidence of a symbiotic association between marine ascidians and microorganisms shed light on the real producers of many extremely potent marine natural compounds. Hence, we also report the antibacterial potential, joined to antifungal and antiviral activity, of metabolites isolated from ascidian-associate microorganisms by culture-dependent methods.

Remarkable Potential of Zerumbone to Generate a Library with Six Natural Product-like Skeletons by Natural Material-Related Diversity-Oriented Synthesis

Diversity-oriented synthesis (DOS) is an effective strategy for the quick creation of diverse and high three-dimensional compounds from simple starting materials. The selection of a starting material is the key to constructing useful, chemically diverse compound libraries for the development of new drugs. Here, we report a novel, general, and facile strategy for the creation of diverse compounds with high structural diversity from readily available natural products, such as zerumbone, as the synthetic starting material. Zerumbone is the major component of the essential oil from wild ginger, Zingiber zerumbet Smith. It is noteworthy that zerumbone has a powerful latent reactivity, partly because of its three double bonds, two conjugated and one isolated, and a double conjugated carbonyl group in an 11-membered ring structure. In fact, zerumbone has been shown to be a successful example of natural material-related DOS (NMRDOS). We will report that zerumbone can be converted in one chemical step from four zerumbone derivatives into rare and markedly different scaffolds by transannulation.

An enumeration of natural products from microbial, marine and terrestrial sources

The discovery of a new drug is a multidisciplinary and very costly task. One of the major steps is the identification of a lead compound, i.e. a compound with a certain degree of potency and that can be chemically modified to improve its activity, metabolic properties, and pharmacokinetics profiles. Terrestrial sources (plants and fungi), microbes and marine organisms are abundant resources for the discovery of new structurally diverse and biologically active compounds. In this chapter, an attempt has been made to quantify the numbers of known published chemical structures (available in chemical databases) from natural sources. Emphasis has been laid on the number of unique compounds, the most abundant compound classes and the distribution of compounds in terrestrial and marine habitats. It was observed, from the recent investigations, that ~500,000 known natural products (NPs) exist in the literature. About 70 % of all NPs come from plants, terpenoids being the most represented compound class (except in bacteria, where amino acids, peptides, and polyketides are the most abundant compound classes). About 2,000 NPs have been co-crystallized in PDB structures.

Synthetic biology based construction of biological activity-related library of fungal decalin-containing diterpenoid pyrones

A synthetic biology method based on heterologous biosynthesis coupled with genome mining is a promising approach for increasing the opportunities to rationally access natural product with novel structures and biological activities through total biosynthesis and combinatorial biosynthesis. Here, we demonstrate the advantage of the synthetic biology method to explore biological activity-related chemical space through the comprehensive heterologous biosynthesis of fungal decalin-containing diterpenoid pyrones (DDPs). Genome mining reveals putative DDP biosynthetic gene clusters distributed in five fungal genera. In addition, we design extended DDP pathways by combinatorial biosynthesis. In total, ten DDP pathways, including five native pathways, four extended pathways and one shunt pathway, are heterologously reconstituted in a genetically tractable heterologous host, Aspergillus oryzae, resulting in the production of 22 DDPs, including 15 new analogues. We also demonstrate the advantage of expanding the diversity of DDPs to probe various bioactive molecules through a wide range of biological evaluations.

Combining genome mining and heterologous expression in a genetically tractable host can lead to bioactive natural products discovery and production. Here, the authors employ this strategy for new decalin-containing diterpenoid pyrenes production by expressing native, extended, and shunt pathways in Aspergillus oryzae.

Unraveling Plant Natural Chemical Diversity for Drug Discovery Purposes

The screening and testing of extracts against a variety of pharmacological targets in order to benefit from the immense natural chemical diversity is a concern in many laboratories worldwide. And several successes have been recorded in finding new actives in natural products, some of which have become new drugs or new sources of inspiration for drugs. But in view of the vast amount of research on the subject, it is surprising that not more drug candidates were found. In our view, it is fundamental to reflect upon the approaches of such drug discovery programs and the technical processes that are used, along with their inherent difficulties and biases. Based on an extensive survey of recent publications, we discuss the origin and the variety of natural chemical diversity as well as the strategies to having the potential to embrace this diversity. It seemed to us that some of the difficulties of the area could be related with the technical approaches that are used, so the present review begins with synthetizing some of the more used discovery strategies, exemplifying some key points, in order to address some of their limitations. It appears that one of the challenges of natural product-based drug discovery programs should be an easier access to renewable sources of plant-derived products. Maximizing the use of the data together with the exploration of chemical diversity while working on reasonable supply of natural product-based entities could be a way to answer this challenge. We suggested alternative ways to access and explore part of this chemical diversity with in vitro cultures. We also reinforced how important it was organizing and making available this worldwide knowledge in an "inventory" of natural products and their sources. And finally, we focused on strategies based on synthetic biology and syntheses that allow reaching industrial scale supply. Approaches based on the opportunities lying in untapped natural plant chemical diversity are also considered.

Diversity-Oriented Library Synthesis from Steviol and Isosteviol-Derived Scaffolds

The readily available natural product stevioside provides a unique diterpene core structure that can be explored for small molecule library development by diversity-oriented synthesis and functional group transformations. Validation arrays were prepared from steviol, isosteviol, and related analogues, derived from stevioside, to produce over 90 compounds. These compounds were submitted to the NIH Molecular Libraries Small Molecule Repository for screening in the Molecular Libraries Screening Center Network. Micromolar hits were identified in multiple high-throughput assays for several library members. A cheminformatics analysis of the compounds was performed that verified the expected diversity and complexity of this set of compounds. The screening results indicate that scaffolds-derived natural products can provide screening hits against multiple target proteins.

Striking essential oil: tapping into a largely unexplored source for drug discovery

Essential oils (EOs) have been used therapeutically for centuries. In recent decades, randomized controlled (clinical) trials have supported efficacy in specific therapeutic indications for a few of them. Some EOs, their components or derivatives thereof have been approved as drugs. Nevertheless, they are still considered products that are mainly used in complementary and alternative medicine. EO components occupy a special niche in chemical space, that offers unique opportunities based on their unusual physicochemical properties, because they are typically volatile and hydrophobic. Here we evaluate selected physicochemical parameters, used in conventional drug discovery, of EO components present in a range of commercially available EOs. We show that, contrary to generally held belief, most EO components meet current-day requirements of medicinal chemistry for good drug candidates. Moreover, they also offer attractive opportunities for lead optimization or even fragment-based drug discovery. Because their therapeutic potential is still under-scrutinized, we propose that this be explored more vigorously with present-day methods.

ChEMBL-Likeness Score and Database GDBChEMBL

The generated database GDB17 enumerates 166.4 billion molecules up to 17 atoms of C, N, O, S and halogens following simple rules of chemical stability and synthetic feasibility. However, most molecules in GDB17 are too complex to be considered for chemical synthesis. To address this limitation, we report GDBChEMBL as a subset of GDB17 featuring 10 million molecules selected according to a ChEMBL-likeness score (CLscore) calculated from the frequency of occurrence of circular substructures in ChEMBL, followed by uniform sampling across molecular size, stereocenters and heteroatoms. Compared to the previously reported subsets FDB17 and GDBMedChem selected from GDB17 by fragment-likeness, respectively, medicinal chemistry criteria, our new subset features molecules with higher synthetic accessibility and possibly bioactivity yet retains a broad and continuous coverage of chemical space typical of the entire GDB17. GDBChEMBL is accessible at http://gdb.unibe.ch for download and for browsing using an interactive chemical space map at http://faerun.gdb.tools.

Clostrindolin is an antimycobacterial pyrone alkaloid from Clostridium beijerinckii

Anaerobic bacteria represent an underexplored source of bioactive natural products with unusual structural features. Here we report the isolation and structure elucidation of an antimycobacterial natural product, clostroindolin, produced by Clostridium beijerinckii. Furthermore, we provide first insights into structure activity relationships, which might guide the development of novel antibiotics against mycobacteria.

Evolving Antibiotics against Resistance: a Potential Platform for Natural Product Development?

To avoid an antibiotic resistance crisis, we need to develop antibiotics at a pace that matches the rate of evolution of resistance. However, the complex functions performed by antibiotics-combining, e.g., penetration of membranes, counteraction of resistance mechanisms, and interaction with molecular targets-have proven hard to achieve with current methods for drug development, including target-based screening and rational design. Here, we argue that we can meet the evolution of resistance in the clinic with evolution of antibiotics in the laboratory. On the basis of the results of experimental evolution studies of microbes in general and antibiotic production in Actinobacteria in particular, we propose methodology for evolving antibiotics to circumvent mechanisms of resistance. This exploits the ability of evolution to find solutions to complex problems without a need for design. We review evolutionary theory critical to this approach and argue that it is feasible and has important advantages over current methods for antibiotic discovery.

Fragment-based screening with natural products for novel anti-parasitic disease drug discovery

Introduction: Fragment-based drug discovery can identify relatively simple compounds with low binding affinity due to fewer binding interactions with protein targets. FBDD reduces the library size and provides simpler starting points for subsequent chemical optimization of initial hits. A much greater proportion of chemical space can be sampled in fragment-based screening compared to larger molecules with typical molecular weights (MWs) of 250-500 g mol-1 used in high-throughput screening (HTS) libraries. Areas covered: The authors cover the role of natural products in fragment-based drug discovery against parasitic disease targets. They review the approaches to develop fragment-based libraries either using natural products or natural product-like compounds. The authors present approaches to fragment-based drug discovery against parasitic diseases and compare these libraries with the 3D attributes of natural products. Expert opinion: To effectively use the three-dimensional properties and the chemical diversity of natural products in fragment-based drug discovery against parasitic diseases, there needs to be a mind-shift. Library design, in the medicinal chemistry area, has acknowledged that escaping flat-land is very important to increase the chances of clinical success. Attempts to increase sp3 richness in fragment libraries are acknowledged. Sufficient low molecular weight natural products are known to create true natural product fragment libraries.

“Drug-likeness” properties of natural compounds

Our previous work was focused on the fundamental physical and chemical concepts behind “drug-likeness” and “natural product (NP)-likeness”. Herein, we discuss further details on the concepts of “drug-likeness”, “lead-likeness” and “NP-likeness”. The discussion will first focus on NPs as drugs, then a discussion of previous studies in which the complexities of the scaffolds and chemical space of naturally occurring compounds have been compared with synthetic, semisynthetic compounds and the Food and Drug Administration-approved drugs. This is followed by guiding principles for designing “drug-like” natural product libraries for lead compound discovery purposes. In addition, we present a tool for measuring “NP-likeness” of compounds and a brief presentation of machine-learning approaches. A binary quantitative structure–activity relationship for classifying drugs from nondrugs and natural compounds from nonnatural ones is also described. While the studies add to the plethora of recently published works on the “drug-likeness” of NPs, it no doubt increases our understanding of the physicochemical properties that make NPs fall within the ranges associated with “drug-like” molecules.

A general strategy for diversifying complex natural products to polycyclic scaffolds with medium-sized rings

The interrogation of complex biological pathways demands diverse small molecule tool compounds, which can often lead to important therapeutics for the treatment of human diseases. Since natural products are the most valuable source for the discovery of therapeutics, the derivatization of natural products has been extensively investigated to generate molecules for biological screenings. However, most previous approaches only modified a limited number of functional groups, which resulted in a limited number of skeleta. Here we show a general strategy for the preparation of a library of complex small molecules by combining state-of-the-art chemistry – the site-selective oxidation of C-H bonds - with reactions that expand rigid, small rings in polycyclic steroids to medium-sized rings. This library occupies a unique chemical space compared to selected diverse reference compounds. The diversification strategy developed herein for steroids can also be expanded to other types of natural products.

Derivatization of natural products is a powerful approach to generate new molecules for biological screenings. Here, the authors employ C-H oxidation and ring expansion methods for the preparation of a library of medium-sized ring skeleta, which occupy a unique chemical space based on chemoinformatic analysis.

Generation of a Small Library of Natural Products Designed to Cover Chemical Space Inexpensively

Natural products space includes at least 200,000 compounds and the structures of most of these compounds are available in digital format. Previous analyses showed (i) that although they were capable of taking up synthetic pharmaceutical drugs, such exogenous molecules were likely the chief ‘natural’ substrates in the evolution of the transporters used to gain cellular entry by pharmaceutical drugs, and (ii) that a relatively simple but rapid clustering algorithm could produce clusters from which individual elements might serve to form a representative library covering natural products space. This exploited the fact that the larger clusters were likely to be formed early in evolution (and hence to have been accompanied by suitable transporters), so that very small clusters, including singletons, could be ignored. In the latter work, we assumed that the molecule chosen might be that in the middle of the cluster. However, this ignored two other criteria, namely the commercial availability and the financial cost of the individual elements of these clusters. We here develop a small representative library in which we to seek to satisfy the somewhat competing criteria of coverage (‘representativeness’), availability and cost. It is intended that the library chosen might serve as a testbed of molecules that may or may not be substrates for known or orphan drug transporters. A supplementary spreadsheet provides details, and their availability via a particular supplier.

Medicinal Chemistry Aware Database GDBMedChem

The generated database GDB17 enumerates 166.4 billion possible molecules up to 17 atoms of C, N, O, S and halogens following simple chemical stability and synthetic feasibility rules, however medicinal chemistry criteria are not taken into account. Here we applied rules inspired by medicinal chemistry to exclude problematic functional groups and complex molecules from GDB17, and sampled the resulting subset uniformly across molecular size, stereochemistry and polarity to form GDBMedChem as a compact collection of 10 million small molecules. This collection has reduced complexity and better synthetic accessibility than the entire GDB17 but retains higher sp³ -carbon fraction and natural product likeness scores compared to known drugs. GDBMedChem molecules are more diverse and very different from known molecules in terms of substructures and represent an unprecedented source of diversity for drug design. GDBMedChem is available for 3D-visualization, similarity searching and for download at http://gdb.unibe.ch.