Improving the hit-to-lead process: data-driven assessment of drug-like and lead-like screening hits

Copper-mediated cyclization of thiosemicarbazones leading to 1,3,4-thiadiazoles: Structural elucidation, DFT calculations, in vitro biological evaluation and in silico evaluation studies

Cancer's global impact necessitates innovative and less toxic treatments. Thiosemicarbazones (TSCs), adaptable metal chelators, offer such potential. In this study, we have synthesized N (4)-substituted heterocyclic TSCs from syringaldehyde (TSL1, TSL2), and also report the unexpected copper-mediated cyclization of the TSCs to form thiadiazoles (TSL3, TSL4), expanding research avenues. This work includes extensive characterization and studies such as DNA/protein binding, molecular docking, and theoretical analyses to demonstrate the potential of the as-prepared TSCs and thiadiazoles against different cancer cells. The DFT results depict that the thiadiazoles exhibit greater structural stability and reduced reactivity compared to the corresponding TSCs. The docking results suggest superior EGFR inhibition for TSL3 with a binding constant value of - 6.99 Kcal/mol. According to molecular dynamics studies, the TSL3-EGFR complex exhibits a lower average RMSD (1.39 nm) as compared to the TSL1-EGFR complex (3.29 nm) suggesting that both the thiadiazole and thiosemicarbazone examined here can be good inhibitors of EGFR protein, also that TSL3 can inhibit EGFR better than TSL1. ADME analysis indicates drug-likeness and oral availability of the thiadiazole-based drugs. The DNA binding experiment through absorption and emission spectroscopy discovered that TSL3 is more active towards DNA which is quantitatively calculated with a Kb value of 4.74 × 106 M-1, Kq value of 4.04 × 104 M-1and Kapp value of 5 × 106 M-1. Furthermore, the BSA binding studies carried out with fluorescence spectroscopy showed that TSL3 shows better binding capacity (1.64 × 105 M-1) with BSA protein. All the compounds show significant cytotoxicity against A459-lung, MCF-7-breast, and HepG2-liver cancer cell lines; TSL3 exhibits the best cytotoxicity, albeit less effective than cisplatin. Thiadiazoles demonstrate greater cytotoxicity than the TSCs. Overall, the promise of TSCs and thiadiazoles in cancer research is highlighted by this study. Furthermore, it unveils unexpected copper-mediated cyclization of the TSCs to thiadiazoles.

MicroCycle: An Integrated and Automated Platform to Accelerate Drug Discovery

We herein describe the development and application of a modular technology platform which incorporates recent advances in plate-based microscale chemistry, automated purification, in situ quantification, and robotic liquid handling to enable rapid access to high-quality chemical matter already formatted for assays. In using microscale chemistry and thus consuming minimal chemical matter, the platform is not only efficient but also follows green chemistry principles. By reorienting existing high-throughput assay technology, the platform can generate a full package of relevant data on each set of compounds in every learning cycle. The multiparameter exploration of chemical and property space is hereby driven by active learning models. The enhanced compound optimization process is generating knowledge for drug discovery projects in a time frame never before possible.

Structure-based design, and development of amidinyl, amidoximyl and hydroxamic acid based organic molecules as novel antimalarial drug candidates

Malaria remains a significant global health concern causing numerous fatalities and the emergence of antimalarial drug resistance highlights the urgent need for novel therapeutic options with innovative mechanisms of action and targets. This study aimed to design potential inhibitors of Plasmodium falciparum 6-pyruvoyltetrahydropterin synthase (PfPTPS), synthesize them, and experimentally validate their efficacy as antimalarial agents. A structure-based approach was employed to design a series of novel derivatives, including amidinyl, amidoximyl and hydroxamic acid analogs (1c, 1d, 2b, and 3b), with a focus on their ability to bind to the Zn2+ present in the active site of PfPTPS. The syntheses of these compounds were accomplished through various multi-step synthetic pathways and their structural identities were confirmed using 1H and 13C NMR spectra, mass spectra, and elemental analysis. The compounds were screened for their antiplasmodial activity against the NF54 strain of P. falciparum and in vitro cytotoxicity testing was performed using L-6 cells. The in vivo acute toxicity of the compounds was evaluated in mice. Docking studies of the compounds with the 3D structure of PfPTPS revealed their strong binding affinities, with compound 3b exhibiting notable metal-acceptor interaction with the Zn2+ in the protein binding pocket thereby positioning it as a lead compound for PfPTPS inhibition. The in vitro antiplasmodial studies revealed moderate efficacies against the Pf NF54 strain, particularly compounds 1d and 3b which displayed IC50 < 0.2 μM. No significant cytotoxicity was noted on the L-6 rat cell line. Moreover, in vivo studies suggested that compound 3b exhibited both safety and efficacy in treating rodent malaria. The identified lead compound in this study represents a possible candidate for antimalarial drug development and can be further explored in the search for alternative antifolate drugs to combat the malaria menace.

Discovery of IRAK4 Inhibitors (Zabedosertib) and

Interleukin-1 receptor-associated kinase 4 (IRAK4) plays a critical role in innate inflammatory processes. Here, we describe the discovery of two clinical candidate IRAK4 inhibitors, BAY1834845 (zabedosertib) and BAY1830839, starting from a high-throughput screening hit derived from Bayer's compound library. By exploiting binding site features distinct to IRAK4 using an in-house docking model, liabilities of the original hit could surprisingly be overcome to confer both candidates with a unique combination of good potency and selectivity. Favorable DMPK profiles and activity in animal inflammation models led to the selection of these two compounds for clinical development in patients.

Hit-to-lead optimization of a 2-aminobenzimidazole series as new candidates for chagas disease

Chagas disease is a neglected tropical disease caused by Trypanosoma cruzi. Because current treatments present several limitations, including long duration, variable efficacy and serious side effects, there is an urgent need to explore new antitrypanosomal drugs. The present study describes the hit-to-lead optimization of a 2-aminobenzimidazole hit 1 identified through in vitro phenotypic screening of a chemical library against intracellular Trypanosoma cruzi amastigotes, which focused on optimizing potency, selectivity, microsomal stability and lipophilicity. Multiparametric Structure-Activity Relationships were investigated using a set of 277 derivatives. Although the physicochemical and biological properties of the initial hits were improved, a combination of low kinetic solubility and in vitro cytotoxicity against mammalian cells prevented progression of the best compounds to an efficacy study using a mouse model of Chagas disease.

Synthesis, Design, and Structure-Activity Relationship of a Benzenesulfonylpiperazine Series Against Trypanosoma Cruzi

Chagas disease is a neglected tropical disease, endemic in Latin America and caused by  the protozoan parasite Trypanosoma cruzi . Available treatments show low cure efficacy during the chronic phase of the disease and cause a series of side effects, reinforcing the need to develop new drugs against Chagas disease. In this work, we describe the optimization of a trypanocidal hit compound recently reported in phenotypic HTS studies against Trypanosoma cruzi . A hit-to-lead process was initiated and a structure-activity relationship against Trypanosoma cruzi was obtained after the synthesis and biological evaluation of 22 new benzenesulfonylpiperazine derivatives. From this SAR study, we identified three compounds with a promising predicted ADMET profile and potency comparable to the reference drug benznidazole, which are candidates for further development towards therapies for Chagas disease.

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.

Drug Discovery for Mycobacterium tuberculosis Using Structure-Based Computer-Aided Drug Design Approach

Developing new, more effective antibiotics against resistant Mycobacterium tuberculosis that inhibit its essential proteins is an appealing strategy for combating the global tuberculosis (TB) epidemic. Finding a compound that can target a particular cavity in a protein and interrupt its enzymatic activity is the crucial objective of drug design and discovery. Such a compound is then subjected to different tests, including clinical trials, to study its effectiveness against the pathogen in the host. In recent times, new techniques, which involve computational and analytical methods, enhanced the chances of drug development, as opposed to traditional drug design methods, which are laborious and time-consuming. The computational techniques in drug design have been improved with a new generation of software used to develop and optimize active compounds that can be used in future chemotherapeutic development to combat global tuberculosis resistance. This review provides an overview of the evolution of tuberculosis resistance, existing drug management, and the design of new anti-tuberculosis drugs developed based on the contributions of computational techniques. Also, we show an appraisal of available software and databases on computational drug design with an insight into the application of this software and databases in the development of anti-tubercular drugs. The review features a perspective involving machine learning, artificial intelligence, quantum computing, and CRISPR combination with available computational techniques as a prospective pathway to design new anti-tubercular drugs to combat resistant tuberculosis.

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.

Cheminformatic Characterization of Natural Antimicrobial Products for the Development of New Lead Compounds

The growing antimicrobial resistance (AMR) of pathogenic organisms to currently prescribed drugs has resulted in the failure to treat various infections caused by these superbugs. Therefore, to keep pace with the increasing drug resistance, there is a pressing need for novel antimicrobial agents, especially from non-conventional sources. Several natural products (NPs) have been shown to display promising in vitro activities against multidrug-resistant pathogens. Still, only a few of these compounds have been studied as prospective drug candidates. This may be due to the expensive and time-consuming process of conducting important studies on these compounds. The present review focuses on applying cheminformatics strategies to characterize, prioritize, and optimize NPs to develop new lead compounds against antimicrobial resistance pathogens. Moreover, case studies where these strategies have been used to identify potential drug candidates, including a few selected open-access tools commonly used for these studies, are briefly outlined.

Discovery of a first-in-class inhibitor of sulfide:quinone oxidoreductase that protects against adverse cardiac remodeling and heart failure

AIMS

Hydrogen sulfide (H2S) is a potent signaling molecule that activates diverse cardioprotective pathways by posttranslational modification (persulfidation) of cysteine residues in upstream protein targets. Heart failure patients with reduced ejection fraction (HFrEF) exhibit low levels of H2S. Sulfide: quinone oxidoreductase (SQOR) catalyzes the first irreversible step in the metabolism of H2S and plays a key role in regulating H2S-mediated signaling. Our aim here was to discover a first-in-class inhibitor of human SQOR and evaluate its cardioprotective effect in an animal model of HFrEF.

METHODS AND RESULTS

We identified a potent inhibitor of human SQOR (STI1, IC50 = 29 nM) by high-throughput screening of a small-molecule library, followed by focused medicinal chemistry optimization and structure-based design. STI1 is a competitive inhibitor that binds with high selectivity to the coenzyme Q-binding pocket in SQOR. STI1 exhibited very low cytotoxicity and attenuated the hypertrophic response of neonatal rat ventricular cardiomyocytes and H9c2 cells induced by neurohormonal stressors. A mouse HFrEF model was produced by transverse aortic constriction (TAC). Treatment of TAC mice with STI1 mitigated the development of cardiomegaly, pulmonary congestion, dilatation of the left ventricle, and cardiac fibrosis and decreased the pressure gradient across the aortic constriction. Moreover, STI1 dramatically improved survival, preserved cardiac function, and prevented the progression to HFrEF by impeding the transition from compensated to decompensated left ventricle hypertrophy.

CONCLUSION

We demonstrate that the coenzyme Q-binding pocket in human SQOR is a druggable target and establish proof of concept for the potential of SQOR inhibitors to provide a novel therapeutic approach for the treatment of HFrEF.

TRANSLATIONAL PERSPECTIVE

In HFrEF there is a compelling need for new drugs that mitigate the pathological remodeling induced by injury and improve patient survival. This study identifies SQOR-inhibiting drugs as a promising first-in-class therapy for HFrEF patients. Due to the well-established protective properties of H2S-induced signaling in renal physiology and disease, this novel class of heart failure therapeutics may also address the large unmet need of therapies for approximately 50% of heart failure patients that have coexisting chronic renal dysfunction.

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.

Radioligand and computational insight in structure - Activity relationship of saccharin derivatives being ipsapirone and revospirone analogues

Schizophrenia and depression are diseases that significantly impede human functioning in society. Current antidepressant drugs are not fully effective. According to literature data, the effect on D₂R or 5-HT_1AR can effectively reduce the symptoms of depression or schizophrenia. Recent research hypothetized that the synergism of both of these receptors can improve the effectiveness of therapy. Ipsapirone, a representative of long-chain arylpiperazines, is a known 5-HT_1AR ligand that has antidepressant effect. This compound has no affinity for the D₂R. Bearing in mind, we decided to design ligands with improved affinity to D₂R and confirmed that in some cases elongation of the carbon linker or arylpiperazine exchange may have beneficial influence on the binding to D2R and 5-HT1AR. Four groups of ligands being ipsapirone analogues with butyl, pentyl, hexyl and stiffened xylene chains were designed. All compounds were obtained in solvent-free reactions supported by a microwave irradiation with an efficiency mainly above 60%. All ligands containing 1-(2-pyrimidinyl)piperazine exhibited high affinity to 5-HT_1AR. In this case, chemical modifications within the chain did not affect the affinity to D₂R. In the case of ligands containing 1-phenylpiperazine, 1-(3-trifluoromethylphenyl)piperazine, 1-(1-naphthyl)piperazine, and 1-(4-chlorophenyl)piperazine, elongation of carbon linker increases of affinity to D₂R. For ligands containing 1- (2-pyridyl) piperazine, and 1-(2,3-dichlorophenyl)piperazine, we observed an opposite effect. For ligands containing 1-phenylpiperazine, 1-(2-methoxyphenyl)piperazine and 1-(2-pyridyl)piperazine, chain elongation had no effect on 5-HT_1AR binding. In turn of ligands containing 1-(3-trifluoromethylphenyl)piperazine and 1- (2,3-dichlorophenyl)piperazine, we observed that elongation of carbon linker has a positive influence to 5-HT_1AR. Molecular modelling was used to support the SAR study.

Actives from MMV Open Access Boxes? A suggested way forward

It is estimated that more than 1 billion people across the world are affected by a neglected tropical disease (NTD) that requires medical intervention. These diseases tend to afflict people in areas with high rates of poverty and cost economies billions of dollars every year. Collaborative drug discovery efforts are required to reduce the burden of these diseases in endemic regions. The release of “Open Access Boxes” is an initiative launched by Medicines for Malaria Venture (MMV) in collaboration with its partners to catalyze new drug discovery in neglected diseases. These boxes are mainly requested by biology researchers across the globe who may not otherwise have access to compounds to screen nor knowledge of the workflow that needs to be followed after identification of actives from their screening campaigns. Here, we present guidelines on how to move such actives beyond the hit identification stage, to help in capacity strengthening and enable a greater impact of the initiative.

Synthesis of novel tris-chalcones and determination of their inhibition profiles against some metabolic enzymes

In this study, we report the synthesis of novel tris-chalcones and testing of human carbonic anhydrase I, and II isoenzymes (hCA I, and hCA II), acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and α-glycosidase (α-Gly) inhibitors for the development of novel chalcone structures towards for treatment of some diseases. The compounds demonstrated K_i values between 13.6 ± 1.1 and 50.0 ± 17.1 nM on hCA I, 9.9 ± 0.8 and 39.5 ± 15.1 nM on hCA II, 3.1 ± 0.2 and 20.1 ± 1.9 nM on AChE, 4.9 ± 0.4 and 14.7 ± 5.2 nM on BChE and 3.9 ± 0.2 and 22.4 ± 10.7 nM on α-Gly enzymes. The results revealed that novel tris-chalcones can have promising drug potential for glaucoma, leukaemia, epilepsy; Alzheimer's disease that was associated with the high enzymatic activity of hCA I, hCA II, AChE, and BChE enzymes.

The influence of calculated physicochemical properties of compounds on their ADMET profiles

We analyzed the influence of calculated physicochemical properties of more than 20,000 compounds on their P-gp and BCRP mediated efflux, microsomal stability, hERG inhibition, and plasma protein binding. Our goal was to provide guidance for designing compounds with desired pharmacokinetic profiles. Our analysis showed that compounds with ClogP less than 3 and molecular weight less than 400 will have high microsomal stability and low plasma protein binding. Compounds with logD less than 2.2 and/or basic pKa larger than 5.3 are likely to be BCRP substrates and compounds with basic pKa less than 5.2 and/or acidic pKa less than 13.4 are less likely to inhibit hERG. Based on these results, compounds with MW < 400, ClogP < 3, basic pKa < 5.2 and acidic pKa < 13.4 are likely to have good bioavailability and low hERG inhibition.

Role of the lysyl oxidase enzyme family in cardiac function and disease

Heart diseases are a major cause of morbidity and mortality world-wide. Lysyl oxidase (LOX) and related LOX-like (LOXL) isoforms play a vital role in remodelling the extracellular matrix (ECM). The LOX family controls ECM formation by cross-linking collagen and elastin chains. LOX/LOXL proteins are copper-dependent amine oxidases that catalyse the oxidation of lysine, causing cross-linking between the lysine moieties of lysine-rich proteins. Dynamic changes in LOX and LOXL protein-expression occur in a variety of cardiac pathologies; these changes are believed to be central to the associated tissue-fibrosis. An awareness of the potential pathophysiological importance of LOX has led to the evaluation of interventions that target LOX/LOXL proteins for heart-disease therapy. The purposes of this review article are: (i) to summarize the basic biochemistry and enzyme function of LOX and LOXL proteins; (ii) to consider their tissue and species distribution; and (iii) to review the results of experimental studies of the roles of LOX and LOXL proteins in heart disease, addressing involvement in the mechanisms, pathophysiology and therapeutic responses based on observations in patient samples and relevant animal models. Therapeutic targeting of LOX family enzymes has shown promising results in animal models, but small-molecule approaches have been limited by non-specificity and off-target effects. Biological approaches show potential promise but are in their infancy. While there is strong evidence for LOX-family protein participation in heart failure, myocardial infarction, cardiac hypertrophy, dilated cardiomyopathy, atrial fibrillation and hypertension, as well as potential interest as therapeutic targets, the precise involvement of LOX-family proteins in heart disease requires further investigation.

Bayer's in silico ADMET platform: a journey of machine learning over the past two decades

Over the past two decades, an in silico absorption, distribution, metabolism, and excretion (ADMET) platform has been created at Bayer Pharma with the goal to generate models for a variety of pharmacokinetic and physicochemical endpoints in early drug discovery. These tools are accessible to all scientists within the company and can be a useful in assisting with the selection and design of novel leads, as well as the process of lead optimization. Here. we discuss the development of machine-learning (ML) approaches with special emphasis on data, descriptors, and algorithms. We show that high company internal data quality and tailored descriptors, as well as a thorough understanding of the experimental endpoints, are essential to the utility of our models. We discuss the recent impact of deep neural networks and show selected application examples.

Hepatic Transporter Alterations by Nuclear Receptor Agonist T0901317 in Sandwich-Cultured Human Hepatocytes: Proteomic Analysis and PBPK Modeling to Evaluate Drug-Drug Interaction Risk

In vitro approaches for predicting drug-drug interactions (DDIs) caused by alterations in transporter protein regulation are not well established. However, reports of transporter regulation via nuclear receptor (NR) modulation by drugs are increasing. This study examined alterations in transporter protein levels in sandwich-cultured human hepatocytes (SCHH; n = 3 donors) measured by liquid chromatography-tandem mass spectrometry-based proteomic analysis after treatment with N-[4-(1,1,1,3,3,3-hexafluoro-2-hydroxypropan-2-yl)phenyl]-N-(2,2,2-trifluoroethyl)benzenesulfonamide (T0901317), the first described synthetic liver X receptor agonist. T0901317 treatment (10 μM, 48 hours) decreased the levels of organic cation transporter (OCT) 1 (0.22-, 0.43-, and 0.71-fold of control) and organic anion transporter (OAT) 2 (0.38-, 0.38-, and 0.53-fold of control) and increased multidrug resistance protein (MDR) 1 (1.37-, 1.48-, and 1.59-fold of control). The induction of NR downstream gene expression supports the hypothesis that T0901317 off-target effects on farnesoid X receptor and pregnane X receptor activation are responsible for the unexpected changes in OCT1, OAT2, and MDR1. Uptake of the OCT1 substrate metformin in SCHH was decreased by T0901317 treatment. Effects of decreased OCT1 levels on metformin were simulated using a physiologically-based pharmacokinetic (PBPK) model. Simulations showed a clear decrease in metformin hepatic exposure resulting in a decreased pharmacodynamic effect. This DDI would not be predicted by the modest changes in simulated metformin plasma concentrations. Altogether, the current study demonstrated that an approach combining SCHH, proteomic analysis, and PBPK modeling is useful for revealing tissue concentration-based DDIs caused by unexpected regulation of hepatic transporters by NR modulators. SIGNIFICANCE STATEMENT: This study utilized an approach combining sandwich-cultured human hepatocytes, proteomic analysis, and physiologically based pharmacokinetic modeling to evaluate alterations in pharmacokinetics (PK) and pharmacodynamics (PD) caused by transporter regulation by nuclear receptor modulators. The importance of this approach from a mechanistic and clinically relevant perspective is that it can reveal drug-drug interactions (DDIs) caused by unexpected regulation of hepatic transporters and enable prediction of altered PK and PD changes, especially for tissue concentration-based DDIs.

Marine Alkaloids with Anti-Inflammatory Activity: Current Knowledge and Future Perspectives

Alkaloids are nitrogenous compounds with various biological activities. Alkaloids with anti-inflammatory activity are commonly found in terrestrial plants, but there are few records of the identification and characterization of the activity of these compounds in marine organisms such as fungi, bacteria, sponges, ascidians, and cnidarians. Seaweed are a source of several already elucidated bioactive compounds, but few studies have described and characterized the activity of seaweed alkaloids with anti-inflammatory properties. In this review, we have gathered the current knowledge about marine alkaloids with anti-inflammatory activity and suggest future perspectives for the study and bioprospecting of these compounds.

Design, synthesis and biological evaluation of novel 2-(5-aryl-1H-imidazol-1-yl) derivatives as potential inhibitors of the HIV-1 Vpu and host BST-2 protein interaction

Novel ethyl 2-(5-aryl-1H-imidazol-1-yl)-acetates 17 and propionates 18, together with their acetic acid 19 and acetohydrazide 20 derivatives, were designed and synthesized using TosMIC chemistry. Biological evaluation of these newly synthesized scaffolds in the HIV-1 Vpu- Host BST-2 ELISA assay identified seven hits (17a, 17b, 17c, 17g, 18a, 20f and 20g) with greater than 50% inhibitory activity. These hits were validated in the HIV-1 Vpu- Host BST-2 AlphaScreen™ and six of the seven compounds were found to have comparable percentage inhibitory activities to those of the ELISA assay. Compounds 17b and 20g, with consistent percentage inhibitory activities across the two assays, had IC₅₀ values of 11.6 ± 1.1 μM and 17.6 ± 0.9 μM in a dose response AlphaScreen™ assay. In a cell-based HIV-1 antiviral assay, compound 17b exhibited an EC₅₀ = 6.3 ± 0.7 μM at non-toxic concentrations (CC₅₀ = 184.5 ± 0.8 μM), whereas compound 20g displayed antiviral activity roughly equivalent to its toxicity (CC₅₀ = 159.5 ± 0.9 μM). This data suggests that compound 17b, active in both cell-based and biochemical assays, provides a good starting point for the design of possible lead compounds for prevention of HIV-1 Vpu and host BST-2 protein binding in new anti-HIV therapeutics.

Multi-Target Drugs Against Metabolic Disorders

BACKGROUND

Metabolic disorders are a major cause of illness and death worldwide. Metabolism is the process by which the body makes energy from proteins, carbohydrates, and fats; chemically breaking these down in the digestive system towards sugars and acids which constitute the human body's fuel for immediate use, or to store in body tissues, such as the liver, muscles, and body fat.

OBJECTIVE

The efficiency of treatments for multifactor diseases has not been proved. It is accepted that to manage multifactor diseases, simultaneous modulation of multiple targets is required leading to the development of new strategies for discovery and development of drugs against metabolic disorders.

METHODS

In silico studies are increasingly being applied by researchers due to reductions in time and costs for new prototype synthesis; obtaining substances that present better therapeutic profiles.

DISCUSSION

In the present work, in addition to discussing multi-target drug discovery and the contributions of in silico studies to rational bioactive planning against metabolic disorders such as diabetes and obesity, we review various in silico study contributions to the fight against human metabolic pathologies.

CONCLUSION

In this review, we have presented various studies involved in the treatment of metabolic disorders; attempting to obtain hybrid molecules with pharmacological activity against various targets and expanding biological activity by using different mechanisms of action to treat a single pathology.

A Structure-Based Drug Discovery Paradigm

Structure-based drug design is becoming an essential tool for faster and more cost-efficient lead discovery relative to the traditional method. Genomic, proteomic, and structural studies have provided hundreds of new targets and opportunities for future drug discovery. This situation poses a major problem: the necessity to handle the “big data” generated by combinatorial chemistry. Artificial intelligence (AI) and deep learning play a pivotal role in the analysis and systemization of larger data sets by statistical machine learning methods. Advanced AI-based sophisticated machine learning tools have a significant impact on the drug discovery process including medicinal chemistry. In this review, we focus on the currently available methods and algorithms for structure-based drug design including virtual screening and de novo drug design, with a special emphasis on AI- and deep-learning-based methods used for drug discovery.

The compromise of virtual screening and its impact on drug discovery

Introduction: Docking and structure-based virtual screening (VS) have been standard approaches in structure-based design for over two decades. However, our understanding of the limitations, potential, and strength of these techniques has enhanced, raising expectations. Areas covered: Based on a survey of reports in the past five years, we assess whether VS: (1) predicts binding poses in agreement with crystallographic data (when available); (2) is a superior screening tool, as often claimed; (3) is successful in identifying chemical scaffolds that can be starting points for subsequent lead optimization cycles. Data shows that knowledge of the target and its chemotypes in postprocessing lead to viable hits in early drug discovery endeavors. Expert opinion: VS is capable of accurate placements in the pocket for the most part, but does not consistently score screening collections accurately. What matters is capitalization on available resources to get closer to a viable lead or optimizable series. Integration of approaches, subjective hit selection guided by knowledge of the receptor or endogenous ligand, libraries driven by experimental guides, validation studies to identify the best docking/scoring that reproduces experimental findings, constraints regarding receptor-ligand interactions, thoroughly designed methodologies, and predefined cutoff scoring criteria strengthen VS's position in pharmaceutical research.

All that glitters is not gold: Panning cytotoxic natural products and derivatives with a fused tricyclic backbone by the estimation of their leadlikeness for cancer treatment

Tricyclic compounds call the attention because of their pharmacological properties, and are considered a preferred platform for the development of drugs. Especially, in cancer treatment, these planar compounds are known for their ability to stack with DNA base pairs, acting as intercalators. In this sense, natural products (NPs) are a prodigal source of polycyclic compounds, comprising classes, such as carbolines, anthraquinones and xanthones. However, most of these compounds lack suitable physico-chemical properties, compatible to oral bioaviability. In this perspective, this paper aims to overview the role of tricyclic cores in the development of cytotoxic compounds, focusing on the leadlikeness estimation of the most prominent NP classes and their synthetic derivatives.

The CSD Drug Subset: The Changing Chemistry and Crystallography of Small Molecule Pharmaceuticals

We report the generation and statistical analysis of the CSD drug subset: a subset of the Cambridge Structural Database (CSD) consisting of every published small-molecule crystal structure containing an approved drug molecule. By making use of InChI matching, a CSD Python API workflow to link CSD entries to the online database Drugbank.ca has been produced. This has resulted in a subset of 8632 crystal structures, representing all published solid forms of 785 unique drug molecules. We hope that this new resource will lead to improvements in targeted cheminformatics and statistical model building in a pharmaceutical setting. In addition to this, as part of the Advanced Digital Design of Pharmaceutical Therapeutics collaboration between academia and industry, we have been given the unique opportunity to run comparative analysis on the internal crystal structure databases of AstraZeneca and Pfizer, alongside comparison to the CSD as a whole.

An approach towards enhancement of a screening library: The Next Generation Library Initiative (NGLI) at Bayer - against all odds?

Pharmaceutical companies often refer to 'screening their library' when performing high-throughput screening (HTS) on a corporate compound collection to identify lead structures for small-molecule drug discovery programs. Characteristics of such a library, including the size, chemical space covered, and physicochemical properties, often determine the success of a screening campaign. Therefore, strategies to maintain and enhance the overall quality of screening collections are crucial to stay competitive and to cope with the 'novelty erosion' that is observed gradually. The Next Generation Library Initiative (NGLI), the enhancement of Bayer's HTS collection by 500000 newly designed compounds within 5 years, is addressing exactly this challenge. Here, we describe this collaborative project, which involves all internal medicinal chemists in a crowd-sourcing approach, as well as selected external partners, to reach this ambitious goal.

Scaffold-Hopping from Synthetic Drugs by Holistic Molecular Representation

The discovery of novel ligand chemotypes allows to explore uncharted regions in chemical space, thereby potentially improving synthetic accessibility, potency, and the drug-likeness of molecules. Here, we demonstrate the scaffold-hopping ability of the new Weighted Holistic Atom Localization and Entity Shape (WHALES) molecular descriptors compared to seven state-of-the-art molecular representations on 30,000 compounds and 182 biological targets. In a prospective application, we apply WHALES to the discovery of novel retinoid X receptor (RXR) modulators. WHALES descriptors identified four agonists with innovative molecular scaffolds, populating uncharted regions of the chemical space. One of the agonists, possessing a rare non-acidic chemotype, revealed high selectivity on 12 nuclear receptors and comparable efficacy as bexarotene on induction of ATP-binding cassette transporter A1, angiopoietin like protein 4 and apolipoprotein E. The outcome of this research supports WHALES as an innovative tool to explore novel regions of the chemical space and to detect novel bioactive chemotypes by straightforward similarity searching.

ADME studies and preliminary safety pharmacology of LDT5, a lead compound for the treatment of benign prostatic hyperplasia

This study aimed to estimate the absorption, distribution, metabolism and excretion (ADME) properties and safety of LDT5, a lead compound for oral treatment of benign prostatic hyperplasia that has previously been characterized as a multi-target antagonist of α_1A-, α_1D-adrenoceptors and 5-HT_1A receptors. The preclinical characterization of this compound comprised the evaluation of its in vitro properties, including plasma, microsomal and hepatocytes stability, cytochrome P450 metabolism and inhibition, plasma protein binding, and permeability using MDCK-MDR1 cells. De-risking and preliminary safety pharmacology assays were performed through screening of 44 off-target receptors and in vivo tests in mice (rota-rod and single dose toxicity). LDT5 is stable in rat and human plasma, human liver microsomes and hepatocytes, but unstable in rat liver microsomes and hepatocytes (half-life of 11 min). LDT5 is highly permeable across the MDCK-MDR1 monolayer (P_app ∼32×10^-6 cm/s), indicating good intestinal absorption and putative brain penetration. LDT5 is not extensively protein-bound and is a substrate of human CYP2D6 and CYP2C19 but not of CYP3A4 (half-life >60 min), and did not significantly influence the activities of any of the human cytochrome P450 isoforms screened. LDT5 was considered safe albeit new studies are necessary to rule out putative central adverse effects through D₂, 5-HT_1A and 5-HT_2B receptors, after chronic use. This work highlights the drug-likeness properties of LDT5 and supports its further preclinical development.

Approaches for discovering novel bioactive small molecules targeting autophagy

INTRODUCTION

In recent years, development of novel bioactive small molecules targeting autophagy has been implicated for autophagy-related disease treatment. Screening new small molecules regulating autophagy allows for the discovery of novel autophagy machinery and therapeutic agents. Areas covered: Two major screening methods for novel autophagy modulators are introduced in this review, namely target based screening and phenotype based screening. With increasing attention focused on chemical compound libraries, coupled with the development of new assay systems, this review attempts to provide an efficient strategy to explore autophagy biology and discover small molecules for the treatment of autophagy-related diseases. Expert opinion: Adopting an appropriate autophagy screening strategy is important for developing small molecules capable of treating neurodegenerative diseases and cancers. Phenotype based screening and target based screening were both used for developing effective small molecules. However, each of these methods has many pros and cons. An efficient approach is suggested to screen for novel lead compounds targeting autophagy, which could provide new hits with better efficiency and rapidity.

Combination of amino acid/dipeptide with ligustrazine-betulinic acid as antitumor agents

The lead compound TBA, 3β-Hydroxy-lup-20(29)-ene-28-oic acid-3, 5, 6-trimethylpyrazin-2-methyl ester, which exhibited promising antitumor activity and induced tumor cell apoptosis in various cancer cell lines, had previously been reported. Moreover, reports have revealed that the introduction of amino acid to betulinic acid could improve selective cytotoxicity as well as water solubility. Thus, a series of novel TBA amino acid and dipeptide derivatives were designed, synthesized and screened for selective cytotoxic activity against five cancer cell lines (HepG2, HT-29, Hela, BCG-823 and A549) and the not malignant cell line MDCK by standard MTT assay. Most of the tested TBA-amino acid and dipeptide analogues showed stronger anti-proliferative activity against all tested tumor cell lines than TBA. Among them, BA-25 exhibited the greatest cytotoxic activity on tumor cell lines (mean IC₅₀ = 2.31 ± 0.78 μM), that was twofold than the positive drug cisplatin (DDP), while it showed lower cytotoxicity on MDCK cell line than DDP. Further cell apoptosis analyses indicated BA-25-induced apoptosis was associated with loss of mitochondrial membrane potential and increase of intracellular free Ca²⁺ concentration.

From Type I to Type II: Design, Synthesis, and Characterization of Potent Pyrazin-2-ones as DFG-Out Inhibitors of PDGFRβ

Reversible protein kinase inhibitors that bind in the ATP cleft can be classified as type I or type II binders. Of these, type I inhibitors address the active form, whereas type II inhibitors typically lock the kinase in an inactive form. At the molecular level, the conformation of the flexible activation loop holding the key DFG motif controls access to the ATP site, thereby determining an active or inactive kinase state. Accordingly, type I and type II kinase inhibitors bind to so-called DFG-in or DFG-out conformations, respectively. Based on our former study on highly selective platelet-derived growth factor receptor β (PDGFRβ) pyrazin-2-one type I inhibitors, we expanded this scaffold toward the deep pocket, yielding the highly potent and effective type II inhibitor 5 (4-[(4-methylpiperazin-1-yl)methyl]-N-[3-[[6-oxo-5-(3,4,5-trimethoxyphenyl)-1H-pyrazin-3-yl]methyl]phenyl]benzamide). In vitro characterization, including selectivity panel data from activity-based assays (300 kinases) and affinity-based assays (97 kinases) of these PDGFRβ type I (1; 5-(4-hydroxy-3-methoxy-phenyl)-3-(3,4,5-trimethoxyphenyl)-1H-pyrazin-2-one) and II (5) inhibitors showing the same pyrazin-2-one chemotype are compared. Implications are discussed regarding the data for selectivity and efficacy of type I and type II ligands.

Latest Advances Towards Ras Inhibition: A Medicinal Chemistry Perspective

Owing to their high occurrence rate across many human cancers and their lack of druggability so far, mutant forms of the signaling protein Ras are currently among the most attractive (and elusive) oncology targets. This strong appeal explains the sustained effort in the field, and the ensuing progress has rekindled optimism regarding the discovery of Ras inhibitors. In this Minireview, we discuss the most recent advances towards irreversible inhibitors, and highlight approaches to inhibitors of Ras-effector interactions that have been overshadowed by the current focus on direct Ras inhibition. At the same time, we provide a critical assessment from a medicinal chemistry perspective.

New agents for the treatment of drug-resistant Mycobacterium tuberculosis

Inadequate dosing and incomplete treatment regimens, coupled with the ability of the tuberculosis bacilli to cause latent infections that are tolerant of currently used drugs, have fueled the rise of multidrug-resistant tuberculosis (MDR-TB). Treatment of MDR-TB infections is a major clinical challenge that has few viable or effective solutions; therefore patients face a poor prognosis and years of treatment. This review focuses on emerging drug classes that have the potential for treating MDR-TB and highlights their particular strengths as leads including their mode of action, in vivo efficacy, and key medicinal chemistry properties. Examples include the newly approved drugs bedaquiline and delaminid, and other agents in clinical and late preclinical development pipeline for the treatment of MDR-TB. Herein, we discuss the challenges to developing drugs to treat tuberculosis and how the field has adapted to these difficulties, with an emphasis on drug discovery approaches that might produce more effective agents and treatment regimens.

Low potency toxins reveal dense interaction networks in metabolism

BACKGROUND

The chemicals of metabolism are constructed of a small set of atoms and bonds. This may be because chemical structures outside the chemical space in which life operates are incompatible with biochemistry, or because mechanisms to make or utilize such excluded structures has not evolved. In this paper I address the extent to which biochemistry is restricted to a small fraction of the chemical space of possible chemicals, a restricted subset that I call Biochemical Space. I explore evidence that this restriction is at least in part due to selection again specific structures, and suggest a mechanism by which this occurs.

RESULTS

Chemicals that contain structures that our outside Biochemical Space (UnBiological groups) are more likely to be toxic to a wide range of organisms, even though they have no specifically toxic groups and no obvious mechanism of toxicity. This correlation of UnBiological with toxicity is stronger for low potency (millimolar) toxins. I relate this to the observation that most chemicals interact with many biological structures at low millimolar toxicity. I hypothesise that life has to select its components not only to have a specific set of functions but also to avoid interactions with all the other components of life that might degrade their function.

CONCLUSIONS

The chemistry of life has to form a dense, self-consistent network of chemical structures, and cannot easily be arbitrarily extended. The toxicity of arbitrary chemicals is a reflection of the disruption to that network occasioned by trying to insert a chemical into it without also selecting all the other components to tolerate that chemical. This suggests new ways to test for the toxicity of chemicals, and that engineering organisms to make high concentrations of materials such as chemical precursors or fuels may require more substantial engineering than just of the synthetic pathways involved.

Kinase profiling in early stage drug discovery: sorting things out

Protein kinases represent one of the largest superfamilies of drugable targets and a major research area for both the pharmaceutical industry and academic groups. This has resulted in the emergence of numerous screening technologies and services dedicated to kinase profiling. In spite of this plentiful offering, the field is not without its own pitfalls, as the profusion of reported conditions and data can ultimately complicate interpretation of project results. Here, we discuss how kinase profiling was used in our early stage drug discovery efforts, from the perspective of a smaller biotech relying largely on assay outsourcing.

Advances in computationally modeling human oral bioavailability

Although significant progress has been made in experimental high throughput screening (HTS) of ADME (absorption, distribution, metabolism, excretion) and pharmacokinetic properties, the ADME and Toxicity (ADME-Tox) in silico modeling is still indispensable in drug discovery as it can guide us to wisely select drug candidates prior to expensive ADME screenings and clinical trials. Compared to other ADME-Tox properties, human oral bioavailability (HOBA) is particularly important but extremely difficult to predict. In this paper, the advances in human oral bioavailability modeling will be reviewed. Moreover, our deep insight on how to construct more accurate and reliable HOBA QSAR and classification models will also discussed.

The application of in silico drug-likeness predictions in pharmaceutical research

The concept of drug-likeness, established from the analyses of the physiochemical properties or/and structural features of existing small organic drugs or/and drug candidates, has been widely used to filter out compounds with undesirable properties, especially poor ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiles. Here, we summarize various approaches for drug-likeness evaluations, including simple rules/filters based on molecular properties/structures and quantitative prediction models based on sophisticated machine learning methods, and provide a comprehensive review of recent advances in this field. Moreover, the strengths and weaknesses of these approaches are briefly outlined. Finally, the drug-likeness analyses of natural products and traditional Chinese medicines (TCM) are discussed.

A 'rule of 0.5' for the metabolite-likeness of approved pharmaceutical drugs

We exploit the recent availability of a community reconstruction of the human metabolic network ('Recon2') to study how close in structural terms are marketed drugs to the nearest known metabolite(s) that Recon2 contains. While other encodings using different kinds of chemical fingerprints give greater differences, we find using the 166 Public MDL Molecular Access (MACCS) keys that 90 % of marketed drugs have a Tanimoto similarity of more than 0.5 to the (structurally) 'nearest' human metabolite. This suggests a 'rule of 0.5' mnemonic for assessing the metabolite-like properties that characterise successful, marketed drugs. Multiobjective clustering leads to a similar conclusion, while artificial (synthetic) structures are seen to be less human-metabolite-like. This 'rule of 0.5' may have considerable predictive value in chemical biology and drug discovery, and may represent a powerful filter for decision making processes.

Discovery of novel bacterial elongation condensing enzyme inhibitors by virtual screening

The elongation condensing enzymes in the bacterial fatty acid biosynthesis pathway represent desirable targets for the design of novel, broad-spectrum antimicrobial agents. A series of substituted benzoxazolinones was identified in this study as a novel class of elongation condensing enzyme (FabB and FabF) inhibitors using a two-step virtual screening approach. Structure activity relationships were developed around the benzoxazolinone scaffold showing that N-substituted benzoxazolinones were most active. The benzoxazolinone scaffold has high chemical tractability making this chemotype suitable for further development of bacterial fatty acid synthesis inhibitors.

Data-driven medicinal chemistry in the era of big data

Science, and the way we undertake research, is changing. The increasing rate of data generation across all scientific disciplines is providing incredible opportunities for data-driven research, with the potential to transform our current practices. The exploitation of so-called 'big data' will enable us to undertake research projects never previously possible but should also stimulate a re-evaluation of all our data practices. Data-driven medicinal chemistry approaches have the potential to improve decision making in drug discovery projects, providing that all researchers embrace the role of 'data scientist' and uncover the meaningful relationships and patterns in available data.