Why Some Targets Benefit from beyond Rule of Five Drugs

Identification of readily available pseudo-natural products

Pseudo-natural products (PNPs) combine fragments derived from NPs in ways that are not found in nature, and may lead to the discovery of novel chemotypes for unexpected targets or the identification of unprecedented bioactivities. PNPs have increasingly been explored in recent drug discovery programs, and are strongly enriched in clinical compounds. We describe how a large number of structurally different PNPs can be accessed readily and without the need to execute labor- and time intensive synthesis programs. We employed an improved version of the previously reported natural product fragment combination (NPFC) tool to analyze the full library of 3.5 M synthetic small molecules and screening libraries from Enamine for PNP content, assessed the spatial complexity of Enamine-PNPs using the recently developed normalized spatial score (nSPS) and evaluated the bioactivity of a selected subset of Enamine-PNPs in the unbiased morphological cell painting assay. A major fraction (32%; 1.1 million compounds) of the Enamine library are PNPs which contain a significant number of compounds with unexpected and probably new bioactivity.

Targeted protein degradation in CNS disorders: a promising route to novel therapeutics?

Targeted protein degradation (TPD) is a rapidly expanding field, with various PROTACs (proteolysis-targeting chimeras) in clinical trials and molecular glues such as immunomodulatory imide drugs (IMiDs) already well established in the treatment of certain blood cancers. Many current approaches are focused on oncology targets, leaving numerous potential applications underexplored. Targeting proteins for degradation offers a novel therapeutic route for targets whose inhibition remains challenging, such as protein aggregates in neurodegenerative diseases. This mini review focuses on the prospect of utilizing TPD for neurodegenerative disease targets, particularly PROTAC and molecular glue formats and opportunities for novel CNS E3 ligases. Some key challenges of utilizing such modalities including molecular design of degrader molecules, drug delivery and blood brain barrier penetrance will be discussed.

Process Mass Intensity (PMI): A Holistic Analysis of Current Peptide Manufacturing Processes Informs Sustainability in Peptide Synthesis

Small molecule therapeutics represent the majority of the FDA-approved drugs. Yet, many attractive targets are poorly tractable by small molecules, generating a need for new therapeutic modalities. Due to their biocompatibility profile and structural versatility, peptide-based therapeutics are a possible solution. Additionally, in the past two decades, advances in peptide design, delivery, formulation, and devices have occurred, making therapeutic peptides an attractive modality. However, peptide manufacturing is often limited to solid-phase peptide synthesis (SPPS), liquid phase peptide synthesis (LPPS), and to a lesser extent hybrid SPPS/LPPS, with SPPS emerging as a predominant platform technology for peptide synthesis. SPPS involves the use of excess solvents and reagents which negatively impact the environment, thus highlighting the need for newer technologies to reduce the environmental footprint. Herein, fourteen American Chemical Society Green Chemistry Institute Pharmaceutical Roundtable (ACS GCIPR) member companies with peptide-based therapeutics in their portfolio have compiled Process Mass Intensity (PMI) metrics to help inform the sustainability efforts in peptide synthesis. This includes PMI assessment on 40 synthetic peptide processes at various development stages in pharma, classified according to the development phase. This is the most comprehensive assessment of synthetic peptide environmental metrics to date. The synthetic peptide manufacturing process was divided into stages (synthesis, purification, isolation) to determine their respective PMI. On average, solid-phase peptide synthesis (SPPS) (PMI ≈ 13,000) does not compare favorably with other modalities such as small molecules (PMI median 168-308) and biopharmaceuticals (PMI ≈ 8300). Thus, the high PMI for peptide synthesis warrants more environmentally friendly processes in peptide manufacturing.

Expanding FTMap for Fragment-Based Identification of Pharmacophore Regions in Ligand Binding Sites

The knowledge of ligand binding hot spots and of the important interactions within such hot spots is crucial for the design of lead compounds in the early stages of structure-based drug discovery. The computational solvent mapping server FTMap can reliably identify binding hot spots as consensus clusters, free energy minima that bind a variety of organic probe molecules. However, in its current implementation, FTMap provides limited information on regions within the hot spots that tend to interact with specific pharmacophoric features of potential ligands. E-FTMap is a new server that expands on the original FTMap protocol. E-FTMap uses 119 organic probes, rather than the 16 in the original FTMap, to exhaustively map binding sites, and identifies pharmacophore features as atomic consensus sites where similar chemical groups bind. We validate E-FTMap against a set of 109 experimentally derived structures of fragment-lead pairs, finding that highly ranked pharmacophore features overlap with the corresponding atoms in both fragments and lead compounds. Additionally, comparisons of mapping results to ensembles of bound ligands reveal that pharmacophores generated with E-FTMap tend to sample highly conserved protein-ligand interactions. E-FTMap is available as a web server at https://eftmap.bu.edu.

Investigating the effect of polymerase inhibitors on cellular proliferation: Computational studies, cytotoxicity, CDK1 inhibitory potential, and LC-MS/MS cancer cell entrapment assays

Directly acting antivirals (DAAs) are a breakthrough in the treatment of HCV. There are controversial reports on their tendency to induce hepatocellular carcinoma (HCC) in HCV patients. Numerous reports have concluded that the HCC is attributed to patient-related factors while others are inclined to attribute this as a DAA side-effect. This study aims to investigate the effect of polymerase inhibitor DAAs, especially daclatasivir (DLT) on cellular proliferation as compared to ribavirin (RBV). The interaction of DAAs with variable cell-cycle proteins was studied in silico. The binding affinities to multiple cellular targets were investigated and the molecular dynamics were assessed. The in vitro effect of the selected candidate DLT on cancer cell proliferation was determined and the CDK1 inhibitory potential in was evaluated. Finally, the cellular entrapment of the selected candidates was assessed by an in-house developed and validated LC-MS/MS method. The results indicated that polymerase inhibitor antiviral agents, especially DLT, may exert an anti-proliferative potential against variable cancer cell lines. The results showed that the effect may be achieved via potential interaction with the multiple cellular targets, including the CDK1, resulting in halting of the cellular proliferation. DLT exhibited a remarkable cell permeability in the liver cancer cell line which permits adequate interaction with the cellular targets. In conclusion, the results reveal that the polymerase inhibitor (DLT) may have an anti-proliferative potential against liver cancer cells. These results may pose DLT as a therapeutic choice for patients suffering from HCV and are liable to HCC development.

Prodrugs as empowering tools in drug discovery and development: recent strategic applications of drug delivery solutions to mitigate challenges associated with lead compounds and drug candidates

The delivery of a drug to a specific organ or tissue at an efficacious concentration is the pharmacokinetic (PK) hallmark of promoting effective pharmacological action at a target site with an acceptable safety profile. Sub-optimal pharmaceutical or ADME profiles of drug candidates, which can often be a function of inherently poor physicochemical properties, pose significant challenges to drug discovery and development teams and may contribute to high compound attrition rates. Medicinal chemists have exploited prodrugs as an informed strategy to productively enhance the profiles of new chemical entities by optimizing the physicochemical, biopharmaceutical, and pharmacokinetic properties as well as selectively delivering a molecule to the site of action as a means of addressing a range of limitations. While discovery scientists have traditionally employed prodrugs to improve solubility and membrane permeability, the growing sophistication of prodrug technologies has enabled a significant expansion of their scope and applications as an empowering tool to mitigate a broad range of drug delivery challenges. Prodrugs have emerged as successful solutions to resolve non-linear exposure, inadequate exposure to support toxicological studies, pH-dependent absorption, high pill burden, formulation challenges, lack of feasibility of developing solid and liquid dosage forms, first-pass metabolism, high dosing frequency translating to reduced patient compliance and poor site-specific drug delivery. During the period 2012-2022, the US Food and Drug Administration (FDA) approved 50 prodrugs, which amounts to 13% of approved small molecule drugs, reflecting both the importance and success of implementing prodrug approaches in the pursuit of developing safe and effective drugs to address unmet medical needs.

Evaluating physiochemical properties of FDA-approved orally administered drugs

INTRODUCTION

Analyses of orally administered FDA-approved drugs from 1990 to 1993 enabled the identification of a set of physiochemical properties known as Lipinski's Rule of Five (Ro5). The original Ro5 and extended versions still remain the reference criteria for drug development programs. Since many bioactive compounds do not conform to the Ro5, we validated the relevance of and adherence to these rulesets in a contemporary cohort of FDA-approved drugs.

AREAS COVERED

The authors noted that a significant proportion of FDA-approved orally administered parent compounds from 2011 to 2022 deviate from the original Ro5 criteria (~38%) or the Ro5 with extensions (~53%). They then evaluated if a contemporary Ro5 criteria (cRo5) could be devised to better predict oral bioavailability. Furthermore, they discuss many case studies showcasing the need for and benefit of increasing the size of certain compounds and cover several evolving strategies for improving oral bioavailability.

EXPERT OPINION

Despite many revisions to the Ro5, the authors find that no single proposed physiochemical rule has universal concordance with absolute oral bioavailability. Innovations in drug delivery and formulation have dramatically expanded the range of physicochemical properties and the chemical diversity for oral administration.

Screening of potential inhibitors of Leishmania major N-myristoyltransferase from Azadirachta indica phytochemicals for leishmaniasis drug discovery by molecular docking, molecular dynamics simulation and density functional theory methods

Leishmaniasis is one of the most neglected parasitic diseases worldwide. The toxicity of current drugs used for its treatment is a major obstacle to their effectiveness, necessitating the discovery and development of new therapeutic agents for better disease control. In Leishmania parasites, N-Myristoyltransferase (NMT) has been identified as a promising target for drug development. Thus, exploring well-known medicinal plants such as Azadirachta indica and their phytochemicals can offer a diverse range of treatment options, potentially leading to disease prevention and control. To assess the therapeutic potential of these compounds, their ADMET prediction and drug-likeness properties were analyzed. The top 4 compounds were selected which had better and significantly low binding energy than the reference molecule QMI. Based on the binding energy score of the top compounds, the results show that Isonimocinolide has the highest binding affinity (-9.8 kcal/mol). In addition, a 100 ns MD simulation of the four best compounds showed that Isonimocinolide and Nimbolide have good stability with LmNMT. These compounds were then subjected to MMPBSA (last 30 ns) calculation to analyze protein-ligand stability and dynamic behavior. Nimbolide and Meldenin showed lowest binding free energy i.e. -84.301 kJ/mol and -91.937 kJ/mol respectively. DFT was employed to calculate the HOMO-LUMO energy gap, global reactivity parameters, and molecular electrostatic potential of all hit molecules. The promising results obtained from MD simulations and MMPBSA analyses provide compelling evidence for the potential use of these compounds in future drug development efforts for the treatment of leishmaniasis.Communicated by Ramaswamy H. Sarma.

Beyond Rule-of-five: Permeability Assessment of Semipeptidic Macrocycles

Compounds beyond the rule-of-five are generating interest as they expand the molecular toolbox for modulating targets previously considered "undruggable". Macrocyclic peptides are an efficient class of molecules for modulating protein-protein interactions. However, predicting their permeability is difficult as they differ from small molecules. Although constrained by macrocyclization, they generally retain some conformational flexibility associated with an enhanced ability to cross biological membranes. In this study, we investigated the relationship between the structure of semi-peptidic macrocycles and their membrane permeability through structural modifications. Based on a scaffold of four amino acids and a linker, we synthesized 56 macrocycles incorporating modifications in either stereochemistry, N-methylation, or lipophilicity and assessed their passive permeability using the parallel artificial membrane permeability assay (PAMPA). Our results show that some semi-peptidic macrocycles have adequate passive permeability even with properties outside the Lipinski rule of five. We found that N-methylation in position 2 and the addition of lipophilic groups to the side chain of tyrosine led to an improvement in permeability with a decrease in tPSA and 3D-PSA. This enhancement could be attributed to the shielding effect of the lipophilic group on some regions of the macrocycle, which in turn, facilitates a favorable macrocycle conformation for permeability, suggesting some degree of chameleonic behavior.

Chromenopyrazole-Peptide Conjugates as Small-Molecule Based Inhibitors Disrupting the Protein-RNA Interaction of LIN28-let-7

Targeting the protein-RNA interaction of LIN28 and let-7 is a promising strategy for the development of novel anticancer therapeutics. However, a limited number of small-molecule inhibitors disrupting the LIN28-let-7 interaction with potent efficacy are available. Herein, we developed a novel LIN28-inhibiting strategy by targeting selective hotspot amino acids at the LIN28-let-7 binding interface with small-molecule-based bifunctional conjugates. Starting from reported small-molecule LIN28 inhibitors, we identified a feasible linker-attachment position after performing a structure-activity relationship exploration based on the LIN28-targeting chromenopyrazoles. In parallel, a virtual alanine scan identified hotspot residues at the protein-RNA binding interface, based on which we designed a set of peptides to enhance the interaction with the identified hotspot residues. Conjugation of the tailor-designed peptides with linker-attached chromenopyrazoles yielded a series of bifunctional small-molecule-peptide conjugates, represented by compound 83 (PH-223), as a new LIN28-targeting chemical modality. Our result demonstrated an unexplored rational design approach using bifunctional conjugates to target protein-RNA interactions.

Chamelogk: A Chromatographic Chameleonicity Quantifier to Design Orally Bioavailable Beyond-Rule-of-5 Drugs

New chemical modalities in drug discovery include molecules belonging to the bRo5 chemical space. Because of their complex and flexible structure, bRo5 compounds often suffer from a poor solubility/permeability profile. Chameleonicity describes the capacity of a molecule to adapt to the environment through conformational changes; the design of molecular chameleons is a medicinal chemistry strategy simultaneously optimizing solubility and permeability. A default method to quantify chameleonicity in early drug discovery is still missing. Here we introduce Chamelogk, an automated, fast, and cheap chromatographic descriptor of chameleonicity. Moreover, we report measurements for 55 Ro5 and bRo5 compounds and validate our method with literature data. Then, selected case studies (macrocycles, nonmacrocyclic compounds, and PROTACs) are used to illustrate the application of Chamelogk in combination with lipophilicity (BRlogD) and polarity (Δ log kwIAM) descriptors. Overall, we show how Chamelogk deserves being included in property-based drug discovery strategies to design oral bioavailable bRo5 compounds.

Today's drug discovery and the shadow of the rule of 5

INTRODUCTION

The rule of 5 developed by Lipinski et al., a landmark and prescient piece of scholarship, focused the minds of drug hunters by systematically characterizing the physical make-up of drug molecules for the first time, noting many sub-optimal compounds identified by high-throughput screening practices. Its profound influence on thinking and practices, whilst providing benefit, perhaps etched the guidelines too strongly in the minds of some drug hunters who applied the bounds too literally without understanding the implications of the underlying statistics.

AREAS COVERED

This opinion is based on recent key developments that take thinking, measurements, and standards beyond those first set out, particularly the influences of molecular weight and the understanding, measurement, and calculation of lipophilicity.

EXPERT OPINION

Techniques and technologies for physicochemical estimations set new standards. It is timely to celebrate the significance and influence of the rule of 5, whilst taking thinking to new levels with better characterizations. The shadow of the rule of 5 may be long, but it is not dark, as new measurements, predictions and principles emerge as guiding lights in the design and prioritization of higher-quality molecules redefining the meaning of beyond the rule of 5.

T52 attenuates oncogenic STAT3 signaling and suppresses osteosarcoma

BACKGROUND

T52 is a steroidal saponin extracted from the traditional Chinese herb Rohdea fargesii (Baill.), and it is reported to possess strong anti-proliferative capabilities in human pharyngeal carcinoma cell lines. However, whether T52 has anti-osteosarcoma properties, and its potential mechanism is remains unknown.

PURPOSE

To examine the outcome and underlying mechanism of T52 in osteosarcomas (OS).

METHODS/STUDY DESIGNS

The physiological roles of T52 in OS cells were examined using CCK-8, colony formation (CF), EdU staining, cell cycle/apoptosis and cell migration/invasion assays. The relevant T52 targets against OS were assessed via bioinformatics prediction, and the binding sites were analyzed by molecular docking. Western blot analysis was carried out to examine the levels of factors associated with apoptosis, cell cycle, and STAT3 signaling pathway activation.

RESULTS

T52 markedly diminished the proliferation, migration, and invasion of OS cells, and promoted G2/M arrest and apoptosis in a dose-dependent fashion (DDF) in vitro. Mechanistically, molecular docking predicted that T52 stably associated with STAT3 Src homology 2 (SH2) domain residues. Western blot revealed that T52 suppressed the STAT3 signaling pathway, as well as the expression of the downstream targets, such as, Bcl-2, Cyclin D1, and c-Myc. In addition, the anti-OS property of T52 were partially reversed by STAT3 reactivation, which confirmed that STAT3 signaling is critical for regulating the anti-OS property of T52.

CONCLUSION

We firstly demonstrated that T52 possessed strong anti-osteosarcoma property in vitro, which was brought on by the inhibition of the STAT3 signaling pathway. Our findings provided pharmacological support for treating OS with T52.

Relevance of the Trillion-Sized Chemical Space "eXplore" as a Source for Drug Discovery

Within the past two decades, virtual combinatorial compound collections, so-called chemical spaces, became an important molecule source for pharmaceutical research all over the world. The emergence of compound vendor chemical spaces with rapidly growing numbers of molecules raises questions about their application suitability and the quality of the content. Here, we examine the composition of the recently published and, so far, biggest chemical space, "eXplore", which comprises approximately 2.8 trillion virtual product molecules. The utility of eXplore to retrieve interesting chemistry around approved drugs and common Bemis Murcko scaffolds has been assessed with several methods (FTrees, SpaceLight, SpaceMACS). Further, the overlap between several vendor chemical spaces and a physicochemical property distribution analysis has been performed. Despite the straightforward chemical reactions underlying its setup, eXplore is demonstrated to provide relevant and, most importantly, easily accessible molecules for drug discovery campaigns.

Inhibitors of the Oncogenic PA2G4-MYCN Protein-Protein Interface

MYCN is a major oncogenic driver for neuroblastoma tumorigenesis, yet there are no direct MYCN inhibitors. We have previously identified PA2G4 as a direct protein-binding partner of MYCN and drive neuroblastoma tumorigenesis. A small molecule known to bind PA2G4, WS6, significantly decreased tumorigenicity in TH-MYCN neuroblastoma mice, along with the inhibition of PA2G4 and MYCN interactions. Here, we identified a number of novel WS6 analogues, with 80% structural similarity, and used surface plasmon resonance assays to determine their binding affinity. Analogues #5333 and #5338 showed direct binding towards human recombinant PA2G4. Importantly, #5333 and #5338 demonstrated a 70-fold lower toxicity for normal human myofibroblasts compared to WS6. Structure-activity relationship analysis showed that a 2,3 dimethylphenol was the most suitable substituent at the R1 position. Replacing the trifluoromethyl group on the phenyl ring at the R2 position, with a bromine or hydrogen atom, increased the difference between efficacy against neuroblastoma cells and normal myofibroblast toxicity. The WS6 analogues inhibited neuroblastoma cell phenotype in vitro, in part through effects on apoptosis, while their anti-cancer effects required both PA2G4 and MYCN expression. Collectively, chemical inhibition of PA2G4-MYCN binding by WS6 analogues represents a first-in-class drug discovery which may have implications for other MYCN-driven cancers.

Trust Your Gut: Strategies and Tactics for Intestinally Restricted Drugs

Non-absorbable small-molecule drugs targeted to the gut represent an alternative approach to safe, non-systemic therapeutics. Such drugs remain confined to the gastrointestinal tract upon oral dosing by virtue of their limited passive permeability, increasing the local concentration at the site of action while minimizing exposure elsewhere in the body. Herein we review the latest advances in the field of gut-restricted therapeutics, highlighting the different strategies and tactics that medicinal chemists have employed in pursuit of drugs with minimal intestinal absorption.

Fragment-based drug discovery supports drugging 'undruggable' protein-protein interactions

Protein-protein interactions (PPIs) have important roles in various cellular processes, but are commonly described as 'undruggable' therapeutic targets due to their large, flat, featureless interfaces. Fragment-based drug discovery (FBDD) has achieved great success in modulating PPIs, with more than ten compounds in clinical trials. Here, we highlight the progress of FBDD in modulating PPIs for therapeutic development. Targeting hot spots that have essential roles in both fragment binding and PPIs provides a shortcut for the development of PPI modulators via FBDD. We highlight successful cases of cracking the 'undruggable' problems of PPIs using fragment-based approaches. We also introduce new technologies and future trends. Thus, we hope that this review will provide useful guidance for drug discovery targeting PPIs.

Going Viral: An Investigation into the Chameleonic Behaviour of Antiviral Compounds

The ability to adjust conformations in response to the polarity of the environment, i.e. molecular chameleonicity, is considered to be important for conferring both high aqueous solubility and high cell permeability to drugs in chemical space beyond Lipinski's rule of 5. We determined the conformational ensembles populated by the antiviral drugs asunaprevir, simeprevir, atazanavir and daclatasvir in polar (DMSO-d₆ ) and non-polar (chloroform) environments with NMR spectroscopy. Daclatasvir was fairly rigid, whereas the first three showed large flexibility in both environments, that translated into major differences in solvent accessible 3D polar surface area within each conformational ensemble. No significant differences in size and polar surface area were observed between the DMSO-d₆ and chloroform ensembles of these three drugs. We propose that such flexible compounds are characterized as "partial molecular chameleons" and hypothesize that their ability to adopt conformations with low polar surface area contributes to their membrane permeability and oral absorption.

Trends in oral small-molecule drug discovery and product development based on product launches before and after the Rule of Five

In 1997, the 'Rule of Five' (Ro5) suggested physicochemical limitations for orally administered drugs, based on the analysis of chemical libraries from the early 1990s. In this review, we report on the trends in oral drug product development by analyzing products launched between 1994 and 1997 and between 2013 and 2019. Our analysis confirmed that most new oral drugs are within the Ro5 descriptors; however, the number of new drug products of drugs with molecular weight (MW) and calculated partition coefficient (clogP) beyond the Ro5 has slightly increased. Analysis revealed that there is no single scientific or technological reason for this trend, but that it likely results from incremental advances are being made in molecular biology, target diversity, drug design, medicinal chemistry, predictive modeling, drug metabolism and pharmacokinetics, and drug delivery.

In silico Structure Prediction, Molecular Docking, and Dynamic Simulation of Plasmodium falciparum AP2-I Transcription Factor

Plasmodium falciparum Apicomplexan Apetala 2 Invasion (PfAP2-I) transcription factor (TF) is a protein that regulates the expression of a subset of gene families involved in P. falciparum red blood cell (RBC) invasion. Inhibiting PfAP2-I TF with small molecules represents a potential new antimalarial therapeutic target to combat drug resistance, which this study aims to achieve. The 3D model structure of PfAP2-I was predicted ab initio using ROBETTA prediction tool and was validated using Save server 6.0 and MolProbity. Computed Atlas of Surface Topography of proteins (CASTp) 3.0 was used to predict the active sites of the PfAP2-I modeled structure. Pharmacophore modeling of the control ligand and PfAP2-I modeled structure was carried out using the Pharmit server to obtain several compounds used for molecular docking analysis. Molecular docking and postdocking studies were conducted using AutoDock vina and Discovery studio. The designed ligands' toxicity predictions and in silico drug-likeness were performed using the SwissADME predictor and OSIRIS Property Explorer. The modeled protein structure from the ROBETTA showed a validation result of 96.827 for ERRAT, 90.2% of the amino acid residues in the most favored region for the Ramachandran plot, and MolProbity score of 1.30 in the 98th percentile. Five (5) best hit compounds from molecular docking analysis were selected based on their binding affinity (between -8.9 and -11.7 Kcal/mol) to the active site of PfAP2-I and were considered for postdocking studies. For the absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties, compound MCULE-7146940834 had the highest drug score (0.63) and drug-likeness (6.76). MCULE-7146940834 maintained a stable conformation within the flexible protein's active site during simulation. The good, estimated binding energies, drug-likeness, drug score, and molecular dynamics simulation interaction observed for MCULE-7146940834 against PfAP2-I show that MCULE-7146940834 can be considered a lead candidate for PfAP2-I inhibition. Experimental validations should be carried out to ascertain the efficacy of these predicted best hit compounds.

Computer aided drug design in the development of proteolysis targeting chimeras

Proteolysis targeting chimeras represent a class of drug molecules with a number of attractive properties, most notably a potential to work for targets that, so far, have been in-accessible for conventional small molecule inhibitors. Due to their different mechanism of action, and physico-chemical properties, many of the methods that have been designed and applied for computer aided design of traditional small molecule drugs are not applicable for proteolysis targeting chimeras. Here we review recent developments in this field focusing on three aspects: de-novo linker-design, estimation of absorption for beyond-rule-of-5 compounds, and the generation and ranking of ternary complex structures. In spite of this field still being young, we find that a good number of models and algorithms are available, with the potential to assist the design of such compounds in-silico, and accelerate applied pharmaceutical research.

Physicochemical QSAR analysis of hERG inhibition revisited: towards a quantitative potency prediction

In an earlier study (Didziapetris R & Lanevskij K (2016). J Comput Aided Mol Des. 30:1175-1188) we collected a database of publicly available hERG inhibition data for almost 6700 drug-like molecules and built a probabilistic Gradient Boosting classifier with a minimal set of physicochemical descriptors (log P, pK_a, molecular size and topology parameters). This approach favored interpretability over statistical performance but still achieved an overall classification accuracy of 75%. In the current follow-up work we expanded the database (provided in Supplementary Information) to almost 9400 molecules and performed temporal validation of the model on a set of novel chemicals from recently published lead optimization projects. Validation results showed almost no performance degradation compared to the original study. Additionally, we rebuilt the model using AFT (Accelerated Failure Time) learning objective in XGBoost, which accepts both quantitative and censored data often reported in protein inhibition studies. The new model achieved a similar level of accuracy of discerning hERG blockers from non-blockers at 10 µM threshold, which can be conceived as close to the performance ceiling for methods aiming to describe only non-specific ligand interactions with hERG. Yet, this model outputs quantitative potency values (IC₅₀) and is not tied to a particular classification cut-off. pIC₅₀ from patch-clamp measurements can be predicted with R² ≈ 0.4 and MAE < 0.5, which enables ligand ranking according to their expected potency levels. The employed approach can be valuable for quantitative modeling of various ADME and drug safety endpoints with a high prevalence of censored data.

Development of Macrocyclic PRMT5-Adaptor Protein Interaction Inhibitors

The PRMT5-MEP50 methyltransferase is a major target for anticancer drug discovery, and modulators of its interactions with different regulatory proteins are in high demand because they modulate PRMT5 substrate selectivity. We describe a strategy for the development of a PRMT5/adaptor protein PPI inhibitor, which includes the design and synthesis of macrocyclic peptides based on the motif for the interaction of PRMT5 with its adaptor protein RioK1. After the initial exploration of different macrocycle sizes and cyclization linkages, analysis of a peptide library identified hot spots for the variation of the amino acid structure. The incorporation of nonproteinogenic amino acids into the macrocyclic peptide led to a potent cyclic PRMT5 binding peptide (K_i = 66 nM), which selectively inhibits the interaction of PRMT5 with the adaptor proteins RioK1 and pICln (IC₅₀ = 654 nM) but not with the alternative adaptor protein MEP50. The inhibitor is a promising tool for further biological investigation of this intriguing protein interface.

The use of machine learning modeling, virtual screening, molecular docking, and molecular dynamics simulations to identify potential VEGFR2 kinase inhibitors

Targeting the signaling pathway of the Vascular endothelial growth factor receptor-2 is a promising approach that has drawn attention in the quest to develop novel anti-cancer drugs and cardiovascular disease treatments. We construct a screening pipeline using machine learning classification integrated with similarity checks of approved drugs to find new inhibitors. The statistical metrics reveal that the random forest approach has slightly better performance. By further similarity screening against several approved drugs, two candidates are selected. Analysis of absorption, distribution, metabolism, excretion, and toxicity, along with molecular docking and dynamics are performed for the two candidates with regorafenib as a reference. The binding energies of molecule1, molecule2, and regorafenib are - 89.1, - 95.3, and - 87.4 (kJ/mol), respectively which suggest candidate compounds have strong binding to the target. Meanwhile, the median lethal dose and maximum tolerated dose for regorafenib, molecule1, and molecule2 are predicted to be 800, 1600, and 393 mg/kg, and 0.257, 0.527, and 0.428 log mg/kg/day, respectively. Also, the inhibitory activity of these compounds is predicted to be 7.23 and 7.31, which is comparable with the activity of pazopanib and sorafenib drugs. In light of these findings, the two compounds could be further investigated as potential candidates for anti-angiogenesis therapy.

On drug discovery against infectious diseases and academic medicinal chemistry contributions

This perspective is an attempt to document the problems that medicinal chemists are facing in drug discovery. It is also trying to identify relevant/possible, research areas in which academics can have an impact and should thus be the subject of grant calls. Accordingly, it describes how hit discovery happens, how compounds to be screened are selected from available chemicals and the possible reasons for the recurrent paucity of useful/exploitable results reported. This is followed by the successful hit to lead stories leading to recent and original antibacterials which are, or about to be, used in human medicine. Then, illustrated considerations and suggestions are made on the possible inputs of academic medicinal chemists. This starts with the observation that discovering a “good” hit in the course of a screening campaign still rely on a lot of luck – which is within the reach of academics –, that the hit to lead process requires a lot of chemistry and that if public–private partnerships can be important throughout these stages, they are absolute requirements for clinical trials. Concerning suggestions to improve the current hit success rate, one academic input in organic chemistry would be to identify new and pertinent chemical space, design synthetic accesses to reach these and prepare the corresponding chemical libraries. Concerning hit to lead programs on a given target, if no new hits are available, previously reported leads along with new structural data can be pertinent starting points to design, prepare and assay original analogues. In conclusion, this text is an actual plea illustrating that, in many countries, academic research in medicinal chemistry should be more funded, especially in the therapeutic area neglected by the industry. At the least, such funds would provide the intensive to secure series of hopefully relevant chemical entities which appears to often lack when considering the results of academic as well as industrial screening campaigns.

Mapping the binding sites of challenging drug targets

An increasing number of medically important proteins are challenging drug targets because their binding sites are too shallow or too polar, are cryptic and thus not detectable without a bound ligand or located in a protein-protein interface. While such proteins may not bind druglike small molecules with sufficiently high affinity, they are frequently druggable using novel therapeutic modalities. The need for such modalities can be determined by experimental or computational fragment based methods. Computational mapping by mixed solvent molecular dynamics simulations or the FTMap server can be used to determine binding hot spots. The strength and location of the hot spots provide very useful information for selecting potentially successful approaches to drug discovery.

An Efficient Modern Strategy to Screen Drug Candidates Targeting RdRp of SARS-CoV-2 With Potentially High Selectivity and Specificity

Desired drug candidates should have both a high potential binding chance and high specificity. Recently, many drug screening strategies have been developed to screen compounds with high possible binding chances or high binding affinity. However, there is still no good solution to detect whether those selected compounds possess high specificity. Here, we developed a reverse DFCNN (Dense Fully Connected Neural Network) and a reverse docking protocol to check a given compound’s ability to bind diversified targets and estimate its specificity with homemade formulas. We used the RNA-dependent RNA polymerase (RdRp) target as a proof-of-concept example to identify drug candidates with high selectivity and high specificity. We first used a previously developed hybrid screening method to find drug candidates from an 8888-size compound database. The hybrid screening method takes advantage of the deep learning-based method, traditional molecular docking, molecular dynamics simulation, and binding free energy calculated by metadynamics, which should be powerful in selecting high binding affinity candidates. Also, we integrated the reverse DFCNN and reversed docking against a diversified 102 proteins to the pipeline for assessing the specificity of those selected candidates, and finally got compounds that have both predicted selectivity and specificity. Among the eight selected candidates, Platycodin D and Tubeimoside III were confirmed to effectively inhibit SARS-CoV-2 replication in vitro with EC₅₀ values of 619.5 and 265.5 nM, respectively. Our study discovered that Tubeimoside III could inhibit SARS-CoV-2 replication potently for the first time. Furthermore, the underlying mechanisms of Platycodin D and Tubeimoside III inhibiting SARS-CoV-2 are highly possible by blocking the RdRp cavity according to our screening procedure. In addition, the careful analysis predicted common critical residues involved in the binding with active inhibitors Platycodin D and Tubeimoside III, Azithromycin, and Pralatrexate, which hopefully promote the development of non-covalent binding inhibitors against RdRp.

Discovery of a Novel Src Homology-2 Domain Containing Protein Tyrosine Phosphatase-2 (SHP2) and Cyclin-Dependent Kinase 4 (CDK4) Dual Inhibitor for the Treatment of Triple-Negative Breast Cancer

The treatment of triple-negative breast cancer (TNBC) remains a huge clinical challenge and dual-targeted small-molecule drugs might provide new therapeutic options for this type of breast cancer. In this work, we discovered a series of SHP2 and CDK4 dual inhibitors through a fused pharmacophore strategy and structural optimization. Notably, lead compound 10 with excellent SHP2 (IC₅₀ = 4.3 nM) and CDK4 (IC₅₀ = 18.2 nM) inhibitory activities effectively induced G0/G1 arrest to prevent the proliferation of TNBC cell lines. Furthermore, compound 10 showed great in vivo pharmacokinetic properties (F = 45.8%) and exerted significant antitumor efficacy in the EMT6 syngeneic mouse model. Western blotting and immunohistochemical analysis confirmed that 10 effectively targeted on both SHP2 and CDK4 and activated the immune response in tumors. These results indicate that lead compound 10, as the first SHP2 and CDK4 dual inhibitor, merits further development for treating TNBC.

DDPD 1.0: a manually curated and standardized database of digital properties of approved drugs for drug-likeness evaluation and drug development

Drug-likeness is a vital consideration when selecting compounds in the early stage of drug discovery. A series of drug-like properties are needed to predict the drug-likeness of a given compound and provide useful guidelines to increase the likelihood of converting lead compounds into drugs. Experimental physicochemical properties, pharmacokinetic/toxicokinetic properties and maximum dosages of approved small-molecule drugs from multiple text-based unstructured data resources have been manually assembled, curated, further digitized and processed into structured data, which are deposited in the Database of Digital Properties of approved Drugs (DDPD). DDPD 1.0 contains 30 212 drug property entries, including 2250 approved drugs and 32 properties, in a standardized value/unit format. Moreover, two analysis tools are provided to examine the drug-likeness features of given molecules based on the collected property data of approved drugs. Additionally, three case studies are presented to demonstrate how users can utilize the database. We believe that this database will be a valuable resource for the drug discovery and development field.

Database URL: http://www.inbirg.com/ddpd

Current trends of benzothiazoles in drug discovery: a patent review (2015-2020)

INTRODUCTION

Benzothiazole is a bicyclic ring system composed of thiazole and benzene rings. It is present as an important pharmacophore in many marketed drugs. The notable potential of benzothiazoles as therapeutic agent for different target diseases has prompted a growing interest in benzothiazole-based drug development in recent years.

AREAS COVERED

This review of 55 benzothiazole-related patents, filed from 2015 to 2020, covers a wide range of pharmacological activities. These patents were collated from Google Patents and Lens search engines. The inventions were categorized and discussed based on their respective group of target diseases, including metabolic diseases, cancer, inflammation, neurodegeneration, viral diseases, bacterial infections, fibrosis and thrombosis.

EXPERT OPINION

Benzothiazole has shown to be a scaffold with great pharmacological importance and thus, serves as a building block for the development of derivatives having high therapeutic activity. Benzothiazole derivatives were patented for a range of therapeutic applications, with a special focus on cancer research. Several compounds have the potential to progress into the market, given that they exert both selectivity and in vivo efficacy. Others require a more thorough study to obtain adequate information on the compounds.

In silico evidence of beauvericin antiviral activity against SARS-CoV-2

Background

Scientists are still battling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for the coronavirus 2019 (COVID-19) pandemic so human lives can be saved worldwide. Secondary fungal metabolites are of intense interest due to their broad range of pharmaceutical properties. Beauvericin (BEA) is a secondary metabolite produced by the fungus Beauveria bassiana. Although promising anti-viral activity has previously been reported for BEA, studies investigating its therapeutic potential are limited.

Methods

The objective of this study was to assess the potential usage of BEA as an anti-viral molecule via protein–protein docking approaches using MolSoft.

Results

In-silico results revealed relatively favorable binding energies for BEA to different viral proteins implicated in the vital life stages of this virus. Of particular interest is the capability of BEA to dock to both the main coronavirus protease (Pockets A and B) and spike proteins. These results were validated by molecular dynamic simulation (Gromacs). Several parameters, such as root-mean-square deviation/fluctuation, the radius of gyration, H-bonding, and free binding energy were analyzed. Computational analyses revealed that interaction of BEA with the main protease pockets in addition to the spike glycoprotein remained stable.

Conclusion

Altogether, our results suggest that BEA might be considered as a potential competitive and allosteric agonist inhibitor with therapeutic options for treating COVID-19 pending in vitro and in vivo validation.

Analysis of the uncharted, druglike property space by self-organizing maps

Physicochemical properties are fundamental to predict the pharmacokinetic and pharmacodynamic behavior of drug candidates. Easily calculated descriptors such as molecular weight and logP have been found to correlate with the success rate of clinical trials. These properties have been previously shown to highlight a sweet-spot in the chemical space associated with favorable pharmacokinetics, which is superior against other regions during hit identification and optimization. In this study, we applied self-organizing maps (SOMs) trained on sixteen calculated properties of a subset of known drugs for the analysis of commercially available compound databases, as well as public biological and chemical databases frequently used for drug discovery. Interestingly, several regions of the property space have been identified that are highly overrepresented by commercially available chemical libraries, while we found almost completely unoccupied regions of the maps (commercially neglected chemical space resembling the properties of known drugs). Moreover, these underrepresented portions of the chemical space are compatible with most rigorous property filters applied by the pharma industry in medicinal chemistry optimization programs. Our results suggest that SOMs may be directly utilized in the strategy of library design for drug discovery to sample previously unexplored parts of the chemical space to aim at yet-undruggable targets.

Analysis of physicochemical properties of protein-protein interaction modulators suggests stronger alignment with the "rule of five"

Despite the important roles played by protein-protein interactions (PPIs) in disease, they have been long considered as 'undruggable'. However, recent advances have suggested that PPIs are druggable but may not follow conventional rules of 'drug ability'. Here we explore which physicochemical parameters are essential for a PPI modulator to be a clinical drug by analysing the physicochemical properties of small-molecule PPI modulators in the market, in clinical trials, and published. Our analysis reveals that those compounds currently on the market have a larger range of values for most of the physicochemical parameters, whereas those in clinical trials fit much more stringently to standard drug-like parameters. This observation was particularly true for molecular weight, clog P and topological polar surface area, where aside from a few outliers, most of the compounds in clinical trials fit within standard drug-like parameters. This implies that the newer PPI modulators are more drug-like than those currently on the market, suggesting that designing new PPI-specific screening libraries should remain within standard drug-like parameters in order to obtain a clinical candidate. Taken together, our analysis has important implications for designing future drug discovery campaigns aimed at targeting PPIs.

Emerging therapeutic opportunities for integrin inhibitors

Integrins are cell adhesion and signalling proteins crucial to a wide range of biological functions. Effective marketed treatments have successfully targeted integrins αIIbβ3, α4β7/α4β1 and αLβ2 for cardiovascular diseases, inflammatory bowel disease/multiple sclerosis and dry eye disease, respectively. Yet, clinical development of others, notably within the RGD-binding subfamily of αv integrins, including αvβ3, have faced significant challenges in the fields of cancer, ophthalmology and osteoporosis. New inhibitors of the related integrins αvβ6 and αvβ1 have recently come to the fore and are being investigated clinically for the treatment of fibrotic diseases, including idiopathic pulmonary fibrosis and nonalcoholic steatohepatitis. The design of integrin drugs may now be at a turning point, with opportunities to learn from previous clinical trials, to explore new modalities and to incorporate new findings in pharmacological and structural biology. This Review intertwines research from biological, clinical and medicinal chemistry disciplines to discuss historical and current RGD-binding integrin drug discovery, with an emphasis on small-molecule inhibitors of the αv integrins.

Integrins are key signalling molecules that are present on the surface of subsets of cells and are therefore good potential therapeutic targets. In this Review, Hatley and colleagues discuss the development of integrin inhibitors, particularly the challenges in developing inhibitors for integrins that contain an αv-subunit, and suggest how these challenges could be addressed.

Myxobacterial depsipeptide chondramides interrupt SARS-CoV-2 entry by targeting its broad, cell tropic spike protein

The severity of the COVID-19 pandemic has necessitated the search for drugs against SARS-CoV-2. In this study, we explored via in silico approaches myxobacterial secondary metabolites against various receptor-binding regions of SARS-CoV-2 spike which are responsible in recognition and attachment to host cell receptors mechanisms, namely ACE2, GRP78, and NRP1. In general, cyclic depsipeptide chondramides conferred high affinities toward the spike RBD, showing strong binding to the known viral hot spots Arg403, Gln493 and Gln498 and better selectivity compared to most host cell receptors studied. Among them, chondramide C3 (1) exhibited a binding energy which remained relatively constant when docked against most of the spike variants. Chondramide C (2) on the other hand exhibited strong affinity against spike variants identified in the United Kingdom (N501Y), South Africa (N501Y, E484K, K417N) and Brazil (N501Y, E484K, K417T). Chondramide C6 (9) showed highest BE towards GRP78 RBD. Molecular dynamics simulations were also performed for chondramides 1 and 2 against SARS-CoV-2 spike RBD of the Wuhan wild-type and the South African variant, respectively, where resulting complexes demonstrated dynamic stability within a 120-ns simulation time. Protein-protein binding experiments using HADDOCK illustrated weaker binding affinity for complexed chondramide ligands in the RBD against the studied host cell receptors. The chondramide derivatives in general possessed favorable pharmacokinetic properties, highlighting their potential as prototypic anti-COVID-19 drugs limiting viral attachment and possibly minimizing viral infection.Communicated by Ramaswamy H. Sarma.

Assessing the binding properties of CASP14 targets and models

An important question is how well the models submitted to CASP retain the properties of target structures. We investigate several properties related to binding. First we explore the binding of small molecules as probes, and count the number of interactions between each residue and such probes, resulting in a binding fingerprint. The similarity between two fingerprints, one for the X-ray structure and the other for a model, is determined by calculating their correlation coefficient. The fingerprint similarity weakly correlates with global measures of accuracy, and GDT_TS higher than 80 is a necessary but not sufficient condition for the conservation of surface binding properties. The advantage of this approach is that it can be carried out without information on potential ligands and their binding sites. The latter information was available for a few targets, and we explored whether the CASP14 models can be used to predict binding sites and to dock small ligands. Finally, we tested the ability of models to reproduce protein-protein interactions by docking both the X-ray structures and the models to their interaction partners in complexes. The analysis showed that in CASP14 the quality of individual domain models is approaching that offered by X-ray crystallography, and hence such models can be successfully used for the identification of binding and regulatory sites, as well as for assembling obligatory protein-protein complexes. Success of ligand docking, however, often depends on fine details of the binding interface, and thus may require accounting for conformational changes by simulation methods.

On the design of lead-like DNA-encoded chemical libraries

DNA-encoded libraries (DELs) are becoming an established technology for finding ligands for protein targets. We have abstracted and analysed libraries from the literature to assess the synthesis strategy, selections of reactions and monomers and their propensity to reveal hits. DELs have led to hit compounds across a range of diverse protein classes. The range of reactions and monomers utilised has been relatively limited and the hits are often higher in molecular weight than might be considered ideal. Considerations for future library designs with reference to chemical diversity and lead-like properties are discussed.

Ensemble completeness in conformer sampling: the case of small macrocycles

In this study we compare the three algorithms for the generation of conformer ensembles Biovia BEST, Schrödinger Prime macrocycle sampling (PMM) and Conformator (CONF) form the University of Hamburg, with ensembles derived for exhaustive molecular dynamics simulations applied to a dataset of 7 small macrocycles in two charge states and three solvents. Ensemble completeness is a prerequisite to allow for the selection of relevant diverse conformers for many applications in computational chemistry. We apply conformation maps using principal component analysis based on ring torsions. Our major finding critical for all applications of conformer ensembles in any computational study is that maps derived from MD with explicit solvent are significantly distinct between macrocycles, charge states and solvents, whereas the maps for post-optimized conformers using implicit solvent models from all generator algorithms are very similar independent of the solvent. We apply three metrics for the quantification of the relative covered ensemble space, namely cluster overlap, variance statistics, and a novel metric, Mahalanobis distance, showing that post-optimized MD ensembles cover a significantly larger conformational space than the generator ensembles, with the ranking PMM > BEST >> CONF. Furthermore, we find that the distributions of 3D polar surface areas are very similar for all macrocycles independent of charge state and solvent, except for the smaller and more strained compound 7, and that there is also no obvious correlation between 3D PSA and intramolecular hydrogen bond count distributions.

Design and Synthesis of Simplified Polyketide Analogs: New Modalities beyond the Rule of 5

Natural products provide important lead structures for development of pharmaceutical agents or present attractive tools for medicinal chemistry. However, structurally complex and thus less accessible metabolites defying conventional drug-like properties, as expressed by Pfizer's rule of five, have received less attention as medicinal leads. Traditionally, research focus has been on realizing total syntheses rather than developing more readily available analogs to resolve the critical supply issue. However, very recent studies with complex myxobacterial polyketides have demonstrated that considerable structural simplification may be realized with retention of biological potencies. The context, underlying rationale and importance of tailored synthetic strategies of three such case studies are presented, which may inspire further related activities and may eventually help exploiting the largely untapped biological potential of complex metabolites in general.

Small molecule approaches to treat autoimmune and inflammatory diseases (Part III): Targeting cytokines and cytokine receptor complexes

Chronic and dysregulated cytokine signaling plays an important role in the pathogenic development of many autoimmune and inflammatory diseases. Despite intrinsic challenges in the disruption of interactions between cytokines and cytokine receptors, many first-in-class small-molecule inhibitors have been discovered over the past few years. The third part of the digest series presents recent progress in identifying such inhibitors and highlights the application of novel research tools in the fields of structural biology, computational analysis, screening methods, biophysical/biochemical assays and medicinal chemistry strategy.

Global Analysis of Models for Predicting Human Absorption: QSAR, In Vitro, and Preclinical Models

Models intended to predict intestinal absorption are an essential part of the drug development process. Although many models exist for capturing intestinal absorption, many questions still exist around the applicability of these models to drug types like "beyond rule of 5" (bRo5) and low absorption compounds. This presents a challenge as current models have not been rigorously tested to understand intestinal absorption. Here, we assembled a large, structurally diverse dataset of ∼1000 compounds with known in vitro, preclinical, and human permeability and/or absorption data. In silico (quantitative structure-activity relationship), in vitro (Caco-2), and in vivo (rat) models were statistically evaluated for predictive performance against this human intestinal absorption dataset. We expect this evaluation to serve as a resource for DMPK scientists and medicinal/computational chemists to increase their understanding of permeability and absorption model utility and applications for academia and industry.

Target-Based Evaluation of "Drug-Like" Properties and Ligand Efficiencies

Physicochemical descriptors commonly used to define "drug-likeness" and ligand efficiency measures are assessed for their ability to differentiate marketed drugs from compounds reported to bind to their efficacious target or targets. Using ChEMBL version 26, a data set of 643 drugs acting on 271 targets was assembled, comprising 1104 drug-target pairs having ≥100 published compounds per target. Taking into account changes in their physicochemical properties over time, drugs are analyzed according to their target class, therapy area, and route of administration. Recent drugs, approved in 2010-2020, display no overall differences in molecular weight, lipophilicity, hydrogen bonding, or polar surface area from their target comparator compounds. Drugs are differentiated from target comparators by higher potency, ligand efficiency (LE), lipophilic ligand efficiency (LLE), and lower carboaromaticity. Overall, 96% of drugs have LE or LLE values, or both, greater than the median values of their target comparator compounds.

Discovery of Surfactins as Inhibitors of MicroRNA Processing Using Cat-ELCCA

MicroRNAs (miRNAs) are a family of small noncoding RNAs that regulate gene expression. Due to their important activity in the fine-tuning of protein translation, abnormal expression of miRNAs has been linked to many human diseases, making the targeting of miRNAs attractive as a novel therapeutic strategy. Accordingly, researchers have been heavily engaged in the discovery of small molecule modulators of miRNAs. With an interest in the identification of new chemical space for targeting miRNAs, we developed a high-throughput screening (HTS) technology, catalytic enzyme-linked click chemistry assay (cat-ELCCA), aimed at the discovery of small molecule ligands for pre-miR-21, a miRNA that is frequently overexpressed in human cancers. From our HTS campaign, we found that natural products, a source of many impactful human medicines, may be a promising source of potential pre-miR-21-selective maturation inhibitors. Herein we describe our first efforts in natural product inhibitor discovery leading to the identification of a depsipeptide class of natural products as RNA-binding inhibitors of Dicer-mediated miRNA processing.

Cell Permeability of Isomeric Macrocycles: Predictions and NMR Studies

Conformation-dependent 3D descriptors have been shown to provide better predictions of the physicochemical properties of macrocycles than 2D descriptors. However, the computational identification of relevant conformations for macrocycles is nontrivial. Herein, we report that the Caco-2 cell permeability difference between a pair of diastereomeric macrocycles correlated with their solvent accessible 3D polar surface area and radius of gyration. The descriptors were calculated from the macrocycles’ solution-phase conformational ensembles and independently from ensembles obtained by conformational sampling. Calculation of the two descriptors for three other stereo- and regioisomeric macrocycles also allowed the correct ranking of their cell permeability. Methods for conformational sampling may thus allow ranking of passive permeability for moderately flexible macrocycles, thereby contributing to the prioritization of macrocycles for synthesis in lead optimization.

A Decade of FDA-Approved Drugs (2010-2019): Trends and Future Directions

A total of 378 novel drugs and 27 biosimilars approved by the U.S. Food and Drug Administration (FDA) between 2010 and 2019 were evaluated according to approval numbers by year, therapeutic areas, modalities, route of administration, first-in-class designation, approval times, and expedited review categories. From this review, oncology remains the top therapy area (25%), followed by infection (15%) and central nervous system disorders (11%). Regulatory incentives have been effective as evidenced by an increase in orphan drugs as well as antibacterial drugs approved under the GAIN act. Clinical development times may be increasing, perhaps as a result of the increase in orphan drug indications. Small molecules continue to mostly adhere to "Rule of 5" (Ro5) parameters, but innovation in new modalities is rapidly progressing with approvals for antisense oligonucleotides (ASO), small-interfering RNA (siRNAs), and antibody-directed conjugates (ADCs). Finally, novel targets and scientific breakthroughs that address areas of unmet clinical need are discussed in detail.

Antioxidant-Rich Woodfordia fruticosa Leaf Extract Alleviates Depressive-Like Behaviors and Impede Hyperglycemia

Dhaiphul (Woodfordia fruticosa) is a frequently demanded plant in South-East Asian regions for its diverse medicinal values. This study was proposed to examine antioxidant, antidiabetic, and antidepressant potentials of methanol extract of W. fruticosa leaves (MEWF) and its derived n-hexane (NHFMEWF) and ethyl acetate (EAFMEWF) fractions through in vitro, in vivo, and computational models. Among test samples, MEWF and EAFMEWF contained the highest phenolic content and showed maximal antioxidant activity in DPPH radical scavenging and ferric reducing power assays. In comparison, NHFMEWF possessed maximum flavonoid content and a significantly potent α-amylase inhibitory profile comparable with positive control acarbose. In animal models of depression (forced swimming and tail suspension test), EAFMEWF and NHFMEWF demonstrated a dose-dependent antidepressant-like effect; explicitly, the depressive-like behaviors significantly declined in EAFMEWF-treated dosing groups in contrast to the control group. In the computational analysis, previously isolated flavonoid compounds from Dhaiphul leaves manifested potent binding affinity against several key therapeutic target proteins of diabetes and depressive disorders including α-amylase, serotonin transporter, dopamine transporter, and neuronal nitric oxide synthase with varying pharmacokinetics and toxicity profiles. This research's outcomes may provide potential dietary supplements for mitigating hyperglycemia, cellular toxicity, and depressive disorder.

Structure Based Design of Bicyclic Peptide Inhibitors of RbAp48

The scaffolding protein RbAp48 is part of several epigenetic regulation complexes and is overexpressed in a variety of cancers. In order to develop tool compounds for the study of RbAp48 function, we have developed peptide inhibitors targeting the protein-protein interaction interface between RbAp48 and the scaffold protein MTA1. Based on a MTA1-derived linear peptide with low micromolar affinity and informed by crystallographic analysis, a bicyclic peptide was developed that inhibits the RbAp48/MTA1 interaction with a very low nanomolar KD value of 8.56 nM, and which showed appreciable stability against cellular proteases. Design included exchange of a polar amide cyclization strategy to hydrophobic aromatic linkers enabling mono- and bicyclization by means of cysteine alkylation, which improved affinity by direct interaction of the linkers with a hydrophobic residue on RbAp48. Our results demonstrate that stepwise evolution of a structure-based design is a suitable strategy for inhibitor development targeting PPIs.

Steering New Drug Discovery Campaigns: Permeability, Solubility, and Physicochemical Properties in the bRo5 Chemical Space

An increasing number of drug discovery programs concern compounds in the beyond rule of 5 (bRo5) chemical space, such as cyclic peptides, macrocycles, and degraders. Recent results show that common paradigms of property-based drug design need revision to be applied to larger and more flexible compounds. A virtual event entitled "Solubility, permeability and physico-chemical properties in the bRo5 chemical space" was organized to provide preliminary guidance on how to make the discovery of oral drugs in the bRo5 space more effective. The four speakers emphasized the importance of the bRo5 space as a source of new oral drugs and provided examples of experimental and computational methods specifically tailored for design and optimization in this chemical space.