Natural Enantiomers: Occurrence,Biogenesis and Biological Properties

The knowledge that natural products (NPs) are potent and selective modulators of important biomacromolecules (e.g., DNA and proteins) has inspired some of the world’s most successful pharmaceuticals and agrochemicals. Notwithstanding these successes and despite a growing number of reports on naturally occurring pairs of enantiomers, this area of NP science still remains largely unexplored, consistent with the adage “If you don’t seek, you don’t find”. Statistically, a rapidly growing number of enantiomeric NPs have been reported in the last several years. The current review provides a comprehensive overview of recent records on natural enantiomers, with the aim of advancing awareness and providing a better understanding of the chemical diversity and biogenetic context, as well as the biological properties and therapeutic (drug discovery) potential, of enantiomeric NPs.     

An Overview on Target-Based Drug Design against Kinetoplastid Protozoan Infections: Human African Trypanosomiasis,Chagas Disease and Leishmaniases

The protozoan diseases Human African Trypanosomiasis (HAT), Chagas disease (CD), and leishmaniases span worldwide and therefore their impact is a universal concern. The present regimen against kinetoplastid protozoan infections is poor and insufficient. Target-based design expands the horizon of drug design and development and offers novel chemical entities and potential drug candidates to the therapeutic arsenal against the aforementioned neglected diseases. In this review, we report the most promising targets of the main kinetoplastid parasites, as well as their corresponding inhibitors. This overview is part of the Special Issue, entitled “Advances of Medicinal Chemistry against Kinetoplastid Protozoa (Trypanosoma brucei, Trypanosoma cruzi and Leishmania spp.) Infections: Drug Design, Synthesis and Pharmacology”.     

Improving the Cellular Selectivity of a Membrane-Disrupting Antimicrobial Agent by Monomer Control and by Taming

Antimicrobial resistance represents a significant world-wide health threat that is looming. To meet this challenge, new classes of antimicrobial agents and the redesign of existing ones will be required. This review summarizes some of the studies that have been carried out in my own laboratories involving membrane-disrupting agents. A major discovery that we made, using a Triton X-100 as a prototypical membrane-disrupting molecule and cholesterol-rich liposomes as model systems, was that membrane disruption can occur by two distinct processes, depending on the state of aggregation of the attacking agent. Specifically, we found that monomers induced leakage, while attack by aggregates resulted in a catastrophic rupture of the membrane. This discovery led us to design of a series of derivatives of the clinically important antifungal agent, Amphotericin B, where we demonstrated the feasibility of separating antifungal from hemolytic activity by decreasing the molecule’s tendency to aggregate, i.e., by controlling its monomer concentration. Using an entirely different approach (i.e., a “taming” strategy), we found that by covalently attaching one or more facial amphiphiles (“floats”) to Amphotericin B, its aggregate forms were much less active in lysing red blood cells while maintaining high antifungal activity. The possibility of applying such “monomer control” and “taming” strategies to other membrane-disrupting antimicrobial agents is briefly discussed.     

Synthesis,Biological Evaluation,and Docking Studies of Antagonistic Hydroxylated Arecaidine Esters Targeting mAChRs

The muscarinic acetylcholine receptor family is a highly sought-after target in drug and molecular imaging discovery efforts aimed at neurological disorders. Hampered by the structural similarity of the five subtypes’ orthosteric binding pockets, these efforts largely failed to deliver subtype-selective ligands. Building on our recent successes with arecaidine-derived ligands targeting M₁, herein we report the synthesis of a related series of 11 hydroxylated arecaidine esters. Their physicochemical property profiles, expressed in terms of their computationally calculated CNS MPO scores and HPLC-logD values, point towards blood–brain barrier permeability. By means of a competitive radioligand binding assay, the binding affinity values towards each of the individual human mAChR subtypes hM₁–hM₅ were determined. The most promising compound of this series 17b was shown to have a binding constant towards hM₁ in the single-digit nanomolar region (5.5 nM). Similar to our previously reported arecaidine-derived esters, the entire series was shown to act as hM1R antagonists in a calcium flux assay. Overall, this study greatly expanded our understanding of this recurring scaffolds’ structure–activity relationship and will guide the development towards highly selective mAChRs ligands.     

In Silico Structure-Based Approach for Group Efficiency Estimation in Fragment-Based Drug Design Using Evaluation of Fragment Contributions

The notion of a contribution of a specific group in an organic molecule’s property and/or activity is both common in our thinking and is still not strictly correct due to the inherent non-additivity of free energy with respect to molecular fragments composing a molecule. The fragment- based drug discovery (FBDD) approach has proven to be fruitful in addressing the above notions. The main difficulty of the FBDD, however, is in its reliance on the low throughput and expensive experimental means of determining the fragment-sized molecules binding. In this article we propose a way to enhance the throughput and availability of the FBDD methods by judiciously using an in silico means of assessing the contribution to ligand-receptor binding energy of fragments of a molecule under question using a previously developed in silico Reverse Fragment Based Drug Discovery (R-FBDD) approach. It has been shown that the proposed structure-based drug discovery (SBDD) type of approach fills in the vacant niche among the existing in silico approaches, which mainly stem from the ligand-based drug discovery (LBDD) counterparts. In order to illustrate the applicability of the approach, our work retrospectively repeats the findings of the use case of an FBDD hit-to-lead project devoted to the experimentally based determination of additive group efficiency (GE)—an analog of ligand efficiency (LE) for a group in the molecule—using the Free-Wilson (FW) decomposition. It is shown that in using our in silico approach to evaluate fragment contributions of a ligand and to estimate GE one can arrive at similar decisions as those made using the experimentally determined activity-based FW decomposition. It is also shown that the approach is rather robust to the choice of the scoring function, provided the latter demonstrates a decent scoring power. We argue that the proposed approach of in silico assessment of GE has a wider applicability domain and expect that it will be widely applicable to enhance the net throughput of drug discovery based on the FBDD paradigm.     

Plant Secondary Metabolites Produced in Response to Abiotic Stresses Has Potential Application in Pharmaceutical Product Development

Plant secondary metabolites (PSMs) are vital for human health and constitute the skeletal framework of many pharmaceutical drugs. Indeed, more than 25% of the existing drugs belong to PSMs. One of the continuing challenges for drug discovery and pharmaceutical industries is gaining access to natural products, including medicinal plants. This bottleneck is heightened for endangered species prohibited for large sample collection, even if they show biological hits. While cultivating the pharmaceutically interesting plant species may be a solution, it is not always possible to grow the organism outside its natural habitat. Plants affected by abiotic stress present a potential alternative source for drug discovery. In order to overcome abiotic environmental stressors, plants may mount a defense response by producing a diversity of PSMs to avoid cells and tissue damage. Plants either synthesize new chemicals or increase the concentration (in most instances) of existing chemicals, including the prominent bioactive lead compounds morphine, camptothecin, catharanthine, epicatechin-3-gallate (EGCG), quercetin, resveratrol, and kaempferol. Most PSMs produced under various abiotic stress conditions are plant defense chemicals and are functionally anti-inflammatory and antioxidative. The major PSM groups are terpenoids, followed by alkaloids and phenolic compounds. We have searched the literature on plants affected by abiotic stress (primarily studied in the simulated growth conditions) and their PSMs (including pharmacological activities) from PubMed, Scopus, MEDLINE Ovid, Google Scholar, Databases, and journal websites. We used search keywords: “stress-affected plants,” “plant secondary metabolites, “abiotic stress,” “climatic influence,” “pharmacological activities,” “bioactive compounds,” “drug discovery,” and “medicinal plants” and retrieved published literature between 1973 to 2021. This review provides an overview of variation in bioactive phytochemical production in plants under various abiotic stress and their potential in the biodiscovery of therapeutic drugs. We excluded studies on the effects of biotic stress on PSMs.     

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.     

Novel Big Data-Driven Machine Learning Models for Drug Discovery Application

Most contemporary drug discovery projects start with a ‘hit discovery’ phase where small chemicals are identified that have the capacity to interact, in a chemical sense, with a protein target involved in a given disease. To assist and accelerate this initial drug discovery process, ’virtual docking calculations’ are routinely performed, where computational models of proteins and computational models of small chemicals are evaluated for their capacities to bind together. In cutting-edge, contemporary implementations of this process, several conformations of protein targets are independently assayed in parallel ‘ensemble docking’ calculations. Some of these protein conformations, a minority of them, will be capable of binding many chemicals, while other protein conformations, the majority of them, will not be able to do so. This fact that only some of the conformations accessible to a protein will be ’selected’ by chemicals is known as ’conformational selection’ process in biology. This work describes a machine learning approach to characterize and identify the properties of protein conformations that will be selected (i.e., bind to) chemicals, and classified as potential binding drug candidates, unlike the remaining non-binding drug candidate protein conformations. This work also addresses the class imbalance problem through advanced machine learning techniques that maximize the prediction rate of potential protein molecular conformations for the test case proteins ADORA2A (Adenosine A2a Receptor) and OPRK1 (Opioid Receptor Kappa 1), and subsequently reduces the failure rates and hastens the drug discovery process.     

Androstenedione (a Natural Steroid and a Drug Supplement): A Comprehensive Review of Its Consumption,Metabolism, Health Effects,and Toxicity with Sex Differences

Androstenedione is a steroidal hormone produced in male and female gonads, as well as in the adrenal glands, and it is known for its key role in the production of estrogen and testosterone. Androstenedione is also sold as an oral supplement, that is being utilized to increase testosterone levels. Simply known as “andro” by athletes, it is commonly touted as a natural alternative to anabolic steroids. By boosting testosterone levels, it is thought to be an enhancer for athletic performance, build body muscles, reduce fats, increase energy, maintain healthy RBCs, and increase sexual performance. Nevertheless, several of these effects are not yet scientifically proven. Though commonly used as a supplement for body building, it is listed among performance-enhancing drugs (PEDs) which is banned by the World Anti-Doping Agency, as well as the International Olympic Committee. This review focuses on the action mechanism behind androstenedione’s health effects, and further side effects including clinical features, populations at risk, pharmacokinetics, metabolism, and toxicokinetics. A review of androstenedione regulation in drug doping is also presented.     

New Promising Therapeutic Avenues of Curcumin in Brain Diseases

Curcumin, the dietary polyphenol isolated from Curcuma longa (turmeric), is commonly used as an herb and spice worldwide. Because of its bio-pharmacological effects curcumin is also called “spice of life”, in fact it is recognized that curcumin possesses important proprieties such as anti-oxidant, anti-inflammatory, anti-microbial, antiproliferative, anti-tumoral, and anti-aging. Neurodegenerative diseases such as Alzheimer’s Diseases, Parkinson’s Diseases, and Multiple Sclerosis are a group of diseases characterized by a progressive loss of brain structure and function due to neuronal death; at present there is no effective treatment to cure these diseases. The protective effect of curcumin against some neurodegenerative diseases has been proven by in vivo and in vitro studies. The current review highlights the latest findings on the neuroprotective effects of curcumin, its bioavailability, its mechanism of action and its possible application for the prevention or treatment of neurodegenerative disorders.     

“Texas-Sized” Molecular Boxes: From Chemistry to Applications

The design and synthesis of novel macrocyclic host molecules continues to attract attention because such species play important roles in supramolecular chemistry. However, the discovery of new classes of macrocycles presents a considerable challenge due to the need to embody by design effective molecular recognition features, as well as ideally the development of synthetic routes that permit further functionalization. In 2010, we reported a new class of macrocyclic hosts: a set of tetracationic imidazolium macrocycles, which we termed “Texas-sized” molecular boxes (TxSBs) in homage to Stoddart’s classic “blue box” (CBPQT⁴⁺). Compared with the rigid blue box, the first generation TxSB displayed considerably greater conformational flexibility and a relatively large central cavity, making it a good host for a variety of electron-rich guests. In this review, we provide a comprehensive summary of TxSB chemistry, detailing our recent progress in the area of anion-responsive supramolecular self-assembly and applications of the underlying chemistry to water purification, information storage, and controlled drug release. Our objective is to provide not only a review of the fundamental findings, but also to outline future research directions where TxSBs and their constructs may have a role to play.     

Secondary Metabolites of the Genus Amycolatopsis: Structures,Bioactivities and Biosynthesis

Actinomycetes are regarded as important sources for the generation of various bioactive secondary metabolites with rich chemical and bioactive diversities. Amycolatopsis falls under the rare actinomycete genus with the potential to produce antibiotics. In this review, all literatures were searched in the Web of Science, Google Scholar and PubMed up to March 2021. The keywords used in the search strategy were “Amycolatopsis”, “secondary metabolite”, “new or novel compound”, “bioactivity”, “biosynthetic pathway” and “derivatives”. The objective in this review is to summarize the chemical structures and biological activities of secondary metabolites from the genus Amycolatopsis. A total of 159 compounds derived from 8 known and 18 unidentified species are summarized in this paper. These secondary metabolites are mainly categorized into polyphenols, linear polyketides, macrolides, macrolactams, thiazolyl peptides, cyclic peptides, glycopeptides, amide and amino derivatives, glycoside derivatives, enediyne derivatives and sesquiterpenes. Meanwhile, they mainly showed unique antimicrobial, anti-cancer, antioxidant, anti-hyperglycemic, and enzyme inhibition activities. In addition, the biosynthetic pathways of several potent bioactive compounds and derivatives are included and the prospect of the chemical substances obtained from Amycolatopsis is also discussed to provide ideas for their implementation in the field of therapeutics and drug discovery.     

Molecular Modeling of Histamine Receptors—Recent Advances in Drug Discovery

The recent developments of fast reliable docking, virtual screening and other algorithms gave rise to discovery of many novel ligands of histamine receptors that could be used for treatment of allergic inflammatory disorders, central nervous system pathologies, pain, cancer and obesity. Furthermore, the pharmacological profiles of ligands clearly indicate that these receptors may be considered as targets not only for selective but also for multi-target drugs that could be used for treatment of complex disorders such as Alzheimer’s disease. Therefore, analysis of protein-ligand recognition in the binding site of histamine receptors and also other molecular targets has become a valuable tool in drug design toolkit. This review covers the period 2014–2020 in the field of theoretical investigations of histamine receptors mostly based on molecular modeling as well as the experimental characterization of novel ligands of these receptors.     

Deciphering the Interactions of Bioactive Compounds in Selected Traditional Medicinal Plants against Alzheimer’s Diseases via Pharmacophore Modeling,Auto-QSAR,and Molecular Docking Approaches

Neurodegenerative diseases, for example Alzheimer’s, are perceived as driven by hereditary, cellular, and multifaceted biochemical actions. Numerous plant products, for example flavonoids, are documented in studies for having the ability to pass the blood-brain barrier and moderate the development of such illnesses. Computer-aided drug design (CADD) has achieved importance in the drug discovery world; innovative developments in the aspects of structure identification and characterization, bio-computational science, and molecular biology have added to the preparation of new medications towards these ailments. In this study we evaluated nine flavonoid compounds identified from three medicinal plants, namely T. diversifolia, B. sapida, and I. gabonensis for their inhibitory role on acetylcholinesterase (AChE), butyrylcholinesterase (BChE) and monoamine oxidase (MAO) activity, using pharmacophore modeling, auto-QSAR prediction, and molecular studies, in comparison with standard drugs. The results indicated that the pharmacophore models produced from structures of AChE, BChE and MAO could identify the active compounds, with a recuperation rate of the actives found near 100% in the complete ranked decoy database. Moreso, the robustness of the virtual screening method was accessed by well-established methods including enrichment factor (EF), receiver operating characteristic curve (ROC), Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC), and area under accumulation curve (AUAC). Most notably, the compounds’ pIC₅₀ values were predicted by a machine learning-based model generated by the AutoQSAR algorithm. The generated model was validated to affirm its predictive model. The best models achieved for AChE, BChE and MAO were models kpls_radial_17 (R² = 0.86 and Q² = 0.73), pls_38 (R² = 0.77 and Q² = 0.72), kpls_desc_44 (R² = 0.81 and Q² = 0.81) and these externally validated models were utilized to predict the bioactivities of the lead compounds. The binding affinity results of the ligands against the three selected targets revealed that luteolin displayed the highest affinity score of −9.60 kcal/mol, closely followed by apigenin and ellagic acid with docking scores of −9.60 and −9.53 kcal/mol, respectively. The least binding affinity was attained by gallic acid (−6.30 kcal/mol). The docking scores of our standards were −10.40 and −7.93 kcal/mol for donepezil and galanthamine, respectively. The toxicity prediction revealed that none of the flavonoids presented toxicity and they all had good absorption parameters for the analyzed targets. Hence, these compounds can be considered as likely leads for drug improvement against the same.     

An Outline of the Latest Crystallographic Studies on Inhibitor-Enzyme Complexes for the Design and Development of New Therapeutics against Tuberculosis

The elucidation of the structure of enzymes and their complexes with ligands continues to provide invaluable insights for the development of drugs against many diseases, including bacterial infections. After nearly three decades since the World Health Organization’s (WHO) declaration of tuberculosis (TB) as a global health emergency, Mycobacterium tuberculosis (Mtb) continues to claim millions of lives, remaining among the leading causes of death worldwide. In the last years, several efforts have been devoted to shortening and improving treatment outcomes, and to overcoming the increasing resistance phenomenon. The structural elucidation of enzyme-ligand complexes is fundamental to identify hot-spots, define possible interaction sites, and elaborate strategies to develop optimized molecules with high affinity. This review offers a critical and comprehensive overview of the most recent structural information on traditional and emerging mycobacterial enzymatic targets. A selection of more than twenty enzymes is here discussed, with a special emphasis on the analysis of their binding sites, the definition of the structure–activity relationships (SARs) of their inhibitors, and the study of their main intermolecular interactions. This work corroborates the potential of structural studies, substantiating their relevance in future anti-mycobacterial drug discovery and development efforts.     

Downfalls of Chemical Probes Acting at the Kinase ATP-Site: CK2 as a Case Study

Protein kinases are a large class of enzymes with numerous biological roles and many have been implicated in a vast array of diseases, including cancer and the novel coronavirus infection COVID-19. Thus, the development of chemical probes to selectively target each kinase is of great interest. Inhibition of protein kinases with ATP-competitive inhibitors has historically been the most widely used method. However, due to the highly conserved structures of ATP-sites, the identification of truly selective chemical probes is challenging. In this review, we use the Ser/Thr kinase CK2 as an example to highlight the historical challenges in effective and selective chemical probe development, alongside recent advances in the field and alternative strategies aiming to overcome these problems. The methods utilised for CK2 can be applied to an array of protein kinases to aid in the discovery of chemical probes to further understand each kinase’s biology, with wide-reaching implications for drug development.     

Quantum algorithm for alchemical optimization in material design

The development of tailored materials for specific applications is an active field of research in chemistry, material science and drug discovery. The number of possible molecules obtainable from a set of atomic species grow exponentially with the size of the system, limiting the efficiency of classical sampling algorithms. On the other hand, quantum computers can provide an efficient solution to the sampling of the chemical compound space for the optimization of a given molecular property. In this work, we propose a quantum algorithm for addressing the material design problem with a favourable scaling. The core of this approach is the representation of the space of candidate structures as a linear superposition of all possible atomic compositions. The corresponding ‘alchemical’ Hamiltonian drives the optimization in both the atomic and electronic spaces leading to the selection of the best fitting molecule, which optimizes a given property of the system, e.g., the interaction with an external potential as in drug design. The quantum advantage resides in the efficient calculation of the electronic structure properties together with the sampling of the exponentially large chemical compound space. We demonstrate both in simulations and with IBM Quantum hardware the efficiency of our scheme and highlight the results in a few test cases. This preliminary study can serve as a basis for the development of further material design quantum algorithms for near-term quantum computers.

‘Alchemical’ quantum algorithm for the simultaneous optimisation of chemical composition and electronic structure for material design. By exploiting quantum mechanical principles this approach will boost drug discovery in the near future.     

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

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

From Combinations to Single-Molecule Polypharmacology—Cromolyn-Ibuprofen Conjugates for Alzheimer’s Disease

Despite Alzheimer’s disease (AD) incidence being projected to increase worldwide, the drugs currently on the market can only mitigate symptoms. Considering the failures of the classical paradigm “one target-one drug-one disease” in delivering effective medications for AD, polypharmacology appears to be a most viable therapeutic strategy. Polypharmacology can involve combinations of multiple drugs and/or single chemical entities modulating multiple targets. Taking inspiration from an ongoing clinical trial, this work aims to convert a promising cromolyn–ibuprofen drug combination into single-molecule “codrugs.” Such codrugs should be able to similarly modulate neuroinflammatory and amyloid pathways, while showing peculiar pros and cons. By exploiting a linking strategy, we designed and synthesized a small set of cromolyn–ibuprofen conjugates (4–6). Preliminary plasma stability and neurotoxicity assays allowed us to select diamide 5 and ethanolamide 6 as promising compounds for further studies. We investigated their immunomodulatory profile in immortalized microglia cells, in vitro anti-aggregating activity towards Aβ₄₂-amyloid self-aggregation, and their cellular neuroprotective effect against Aβ₄₂-induced neurotoxicity. The fact that 6 effectively reduced Aβ-induced neuronal death, prompted its investigation into an in vivo model. Notably, 6 was demonstrated to significantly increase the longevity of Aβ₄₂-expressing Drosophila and to improve fly locomotor performance.