Use of 3D Properties to Characterize Beyond Rule-of-5 Property Space for Passive Permeation

Learning Joint 2-D and 3-D Graph Diffusion Models for Complete Molecule Generation

Designing new molecules is essential for drug discovery and material science. Recently, deep generative models that aim to model molecule distribution have made promising progress in narrowing down the chemical research space and generating high-fidelity molecules. However, current generative models only focus on modeling 2-D bonding graphs or 3-D geometries, which are two complementary descriptors for molecules. The lack of ability to jointly model them limits the improvement of generation quality and further downstream applications. In this article, we propose a joint 2-D and 3-D graph diffusion model (JODO) that generates geometric graphs representing complete molecules with atom types, formal charges, bond information, and 3-D coordinates. To capture the correlation between 2-D molecular graphs and 3-D geometries in the diffusion process, we develop a diffusion graph transformer (DGT) to parameterize the data prediction model that recovers the original data from noisy data. The DGT uses a relational attention mechanism that enhances the interaction between node and edge representations. This mechanism operates concurrently with the propagation and update of scalar attributes and geometric vectors. Our model can also be extended for inverse molecular design targeting single or multiple quantum properties. In our comprehensive evaluation pipeline for unconditional joint generation, the experimental results show that JODO remarkably outperforms the baselines on the QM9 and GEOM-Drugs datasets. Furthermore, our model excels in few-step fast sampling, as well as in inverse molecule design and molecular graph generation. Our code is provided in https://github.com/GRAPH-0/JODO.

Improving the Accuracy of Permeability Data to Gain Predictive Power: Assessing Sources of Variability in Assays Using Cell Monolayers

The ability to predict the rate of permeation of new compounds across biological membranes is of high importance for their success as drugs, as it determines their efficacy, pharmacokinetics, and safety profile. In vitro permeability assays using Caco-2 monolayers are commonly employed to assess permeability across the intestinal epithelium, with an extensive number of apparent permeability coefficient (Papp) values available in the literature and a significant fraction collected in databases. The compilation of these Papp values for large datasets allows for the application of artificial intelligence tools for establishing quantitative structure-permeability relationships (QSPRs) to predict the permeability of new compounds from their structural properties. One of the main challenges that hinders the development of accurate predictions is the existence of multiple Papp values for the same compound, mostly caused by differences in the experimental protocols employed. This review addresses the magnitude of the variability within and between laboratories to interpret its impact on QSPR modelling, systematically and quantitatively assessing the most common sources of variability. This review emphasizes the importance of compiling consistent Papp data and suggests strategies that may be used to obtain such data, contributing to the establishment of robust QSPRs with enhanced predictive power.

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.

Exploring the chemical space of orally bioavailable PROTACs

A principal challenge in the discovery of proteolysis targeting chimeras (PROTACs) as oral medications is their bioavailability. To facilitate drug design, it is therefore essential to identify the chemical space where orally bioavailable PROTACs are more likely to be situated. To this aim, we extracted structure-bioavailability insights from published data using traditional 2D descriptors, thereby shedding light on their potential and limitations as drug design tools. Subsequently, we describe cutting-edge experimental, computational and hybrid design strategies based on 3D descriptors, which show promise for enhancing the probability of discovering PROTACs with high oral bioavailability.

Design Principles for Balancing Lipophilicity and Permeability in beyond Rule of 5 Space

An ab initio conformational analysis of oral beyond Rule of 5 (bRo5) drugs was complemented with measured permeability and logP(octanol) to derive design principles conferring oral bioavailability. 3D polar surface area (PSA) thresholds for oral bRo5 drugs coincided with those reported for Ro5 space. The majority of oral bRo5 drugs exceeded the Ro5 logP threshold of 5, reflecting a bias for permeability. Above 500 Da molecular weight (MW), oral drugs and highly permeable Novartis compounds occupy a narrow polarity range (topological or TPSA/MW) of 0.1-0.3 Å2 /Da, whose upper half coincides with the lower 90 percentiles of the Novartis logP set. This TPSA/MW range and 3D PSA below 100 Å2 define the "Rule of ~1 /₅" for balancing lipophilicity and permeability. Neutral TPSA, defined as TPSA minus 3D PSA occurs independent of conformation, intramolecular hydrogen bonds (IMHB) and MW, suggesting it is an intrinsic molecular property. Neutral TPSA increased in the lead optimization (LO) campaigns of three first in class de novo designed bRo5 drugs and may be a useful design parameter in bRo5 space.

Multi_CycGT: A Deep Learning-Based Multimodal Model for Predicting the Membrane Permeability of Cyclic Peptides

Cyclic peptides are gaining attention for their strong binding affinity, low toxicity, and ability to target "undruggable" proteins; however, their therapeutic potential against intracellular targets is constrained by their limited membrane permeability, and researchers need much time and money to test this property in the laboratory. Herein, we propose an innovative multimodal model called Multi_CycGT, which combines a graph convolutional network (GCN) and a transformer to extract one- and two-dimensional features for predicting cyclic peptide permeability. The extensive benchmarking experiments show that our Multi_CycGT model can attain state-of-the-art performance, with an average accuracy of 0.8206 and an area under the curve of 0.8650, and demonstrates satisfactory generalization ability on several external data sets. To the best of our knowledge, it is the first deep learning-based attempt to predict the membrane permeability of cyclic peptides, which is beneficial in accelerating the design of cyclic peptide active drugs in medicinal chemistry and chemical biology applications.

Molecular chameleons in drug discovery

Molecular chameleons possess a flexibility that allows them to dynamically shield or expose polar functionalities in response to the properties of the environment. Although the concept of molecular chameleons was introduced already in 1970, interest in them has grown considerably since the 2010s, when drug discovery has focused to an increased extent on new chemical modalities. Such modalities include cyclic peptides, macrocycles and proteolysis-targeting chimeras, all of which reside in a chemical space far from that of traditional small-molecule drugs. Both cell permeability and aqueous solubility are required for the oral absorption of drugs. Engineering these properties, and potent target binding, into the larger new modalities is a more daunting task than for traditional small-molecule drugs. The ability of chameleons to adapt to different environments may be essential for success. In this Review, we provide both general and theoretical insights into the realm of molecular chameleons. We discuss why chameleons have come into fashion and provide a do-it-yourself toolbox for their design; we then provide a glimpse of how advanced in silico methods can support molecular chameleon design.

Addressing Challenges of Macrocyclic Conformational Sampling in Polar and Apolar Solvents: Lessons for Chameleonicity

We evaluated a workflow to reliably sample the conformational space of a set of 47 peptidic macrocycles. Starting from SMILES strings, we use accelerated molecular dynamics simulations to overcome high energy barriers, in particular, the cis-trans isomerization of peptide bonds. We find that our approach performs very well in polar solvents like water and dimethyl sulfoxide. Interestingly, the protonation state of a secondary amine in the ring only slightly influences the conformational ensembles of our test systems. For several of the macrocycles, determining the conformational distribution in chloroform turns out to be considerably more challenging. Especially, the choice of partial charges crucially influences the ensembles in chloroform. We address these challenges by modifying initial structures and the choice of partial charges. Our results suggest that special care has to be taken to understand the configurational distribution in apolar solvents, which is a key step toward a reliable prediction of membrane permeation of macrocycles and their chameleonic properties.

How a few help all: cooperative crossing of lipid membranes by COSAN anions

Experimental results show that the presence of a concentration gradient of certain nano-ions (most notably cobaltabisdicarbollide ([o-COSAN]- anions), induce a current across intact artificial phospholipid bilayers in spite of the high Born free energy estimated for these ions. The mechanism underlying this observed translocation of nano-anions across membranes has yet to be determined. Here we show, using molecular dynamics simulations, that the permeation of [o-COSAN]- anions across a lipid bilayer proceeds in a cooperative manner. Single nano-ions can enter the bilayer but permeation is hampered by a free energy barrier of about 8kBT. The interaction between these nano-ions inside a leaflet induces a flip-flop translocation mechanism with the formation of transient, elongated structure inside the membrane. This cooperative flip-flop allows an efficient distribution of [o-COSAN]- anions in both leaflets of the bilayer. These results suggest the existence of a new mechanism for permeation of nano-ions across lipid membranes, relevant for those that have the appropriate self-assembly character.

Proapoptotic effects of halogenated bis-phenylthiourea derivatives in cancer cells

New halogenated thiourea derivatives were synthesized via the reaction of substituted phenylisothiocyanates with aromatic amines. Their cytotoxic activity was examined in in vitro studies against solid tumors (SW480, SW620, PC3), a hematological malignance (K-562), and normal keratinocytes (HaCaT). Most of the compounds were more effective against SW480 (1a, 3a, 3b, 5j), K-562 (2b, 3a, 4a), or PC3 (5d) cells than cisplatin, with favorable selectivity. Their anticancer mechanisms were studied by Annexin V-fluorescein-5-isothiocyanate apoptosis, caspase-3/caspase-7 assessment, cell cycle analysis, interleukin-6 (IL-6) release inhibition, and reactive oxygen species (ROS) generation assay. Thioureas 1a, 2b, 3a, and 4a were the most potent activators of early apoptosis in K-562 cells, and substances 1a, 3b, 5j triggered late-apoptosis or necrosis in SW480 cells. This proapoptotic effect was proved by the significant increase of caspase-3/caspase-7 activation. Cell cycle analysis revealed that derivatives 1a, 3a, 5j increased the number of SW480 and K-562 cells in the sub-G1 and/or G0/G1 phases, and one evoked cycle arrest at the G2 phase. The most potent thioureas inhibited IL-6 cytokine secretion from PC3 cells and both colon cancer cell lines. Apoptosis-inducing compounds also increased ROS production in all tumor cell cultures, which may enhance their anticancer properties.

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.

Conformational Sampling Deciphers the Chameleonic Properties of a VHL-Based Degrader

Chameleonicity (the capacity of a molecule to adapt its conformations to the environment) may help to identify orally bioavailable drugs in the beyond-Rule-of-5 chemical space. Computational methods to predict the chameleonic behaviour of degraders have not yet been reported and the identification of molecular chameleons still relies on experimental evidence. Therefore, there is a need to tune predictions with experimental data. Here, we employ PROTAC-1 (a passively cell-permeable degrader), for which NMR and physicochemical data prove the chameleonic behaviour, to benchmark the capacity of two conformational sampling algorithms and selection schemes. To characterize the conformational ensembles in both polar and nonpolar environments, we compute three molecular properties proven to be essential for cell permeability: conformer shape (radius of gyration), polarity (3D PSA), and the number of intramolecular hydrogen bonds. Energetic criteria were also considered. Infographics monitored the simultaneous variation of those properties in computed and NMR conformers. Overall, we provide key points for tuning conformational sampling tools to reproduce PROTAC-1 chameleonicity according to NMR evidence. This study is expected to improve the design of PROTAC drugs and the development of computational sustainable strategies to exploit the potential of new modalities in drug discovery.

Permeability of New Antifungal Fluconazole Derivatives through a Lipophilic Membrane: Experiment and Modeling

Relationships between the structures of molecules and their properties form the basis of modern chemistry and lay the foundation for structure-based drug design. Being the main two determinants of bioavailability, solubility and permeability of drugs are widely investigated experimentally and predicted from physicochemical parameters and structural descriptors. In the present study, we measure the passive diffusion permeability of a series of new fluconazole derivatives with triazole and thiazolo-pyrimidine moieties connected by different linker bridges through the PermeaPad barrier-a relatively new biomimetic lipophilic membrane that has been increasingly used in recent years. The permeability coefficients of new derivatives are shown to be dependent both on the structure of the linker fragment and on the substituent in the phenyl ring of the thiazolo-pyrimidine moiety. The impact of the compound ionization state on the permeability is revealed. Reliable correlations of the permeability with the antifungal activity and distribution coefficient are found. In addition, the solubility-diffusion approach is shown to be able to successfully predict the permeability of the studied derivatives. The obtained results can be considered another step in the development of permeability databases and design of schemes for in vitro permeability prediction.

ADMET profiling and molecular docking of potential antimicrobial peptides previously isolated from African catfish, Clarias gariepinus

Amidst rising cases of antimicrobial resistance, antimicrobial peptides (AMPs) are regarded as a promising alternative to traditional antibiotics. Even so, poor pharmacokinetic profiles of certain AMPs impede their utility necessitating, a careful assessment of potential AMPs' absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties during novel lead exploration. Accordingly, the present study utilized ADMET scores to profile seven previously isolated African catfish antimicrobial peptides (ACAPs). After profiling, the peptides were docked against approved bacterial protein targets to gain insight into their possible mode of action. Promising ACAPs were then chemically synthesized, and their antibacterial activity was validated in vitro utilizing the broth dilution method. All seven examined antimicrobial peptides passed the ADMET screening, with two (ACAP-IV and ACAP-V) exhibiting the best ADMET profile scores. The ACAP-V had a higher average binding energy (-8.47 kcal/mol) and average global energy (-70.78 kcal/mol) compared to ACAP-IV (-7.60 kcal/mol and -57.53 kcal/mol), with the potential to penetrate and disrupt bacterial cell membrane (PDB Id: 2w6d). Conversely, ACAP-IV peptide had higher antibacterial activity against E. coli and S. aureus (Minimum Inhibitory Concentration, 520.7 ± 104.3 μg/ml and 1666.7 ± 416.7 μg/ml, respectively) compared to ACAP-V. Collectively, the two antimicrobial peptides (ACAP-IV and ACAP-V) are potential novel leads for the food, cosmetic and pharmaceutical industries. Future research is recommended to optimize the expression of such peptides in biological systems for extended evaluation.

Membrane Permeating Macrocycles: Design Guidelines from Machine Learning

The ability to predict cell-permeable candidate molecules has great potential to assist drug discovery projects. Large molecules that lie beyond the Rule of Five (bRo5) are increasingly important as drug candidates and tool molecules for chemical biology. However, such large molecules usually do not cross cell membranes and cannot access intracellular targets or be developed as orally bioavailable drugs. Here, we describe a random forest (RF) machine learning model for the prediction of passive membrane permeation rates developed using a set of over 1000 bRo5 macrocyclic compounds. The model is based on easily calculated chemical features/descriptors as independent variables. Our random forest (RF) model substantially outperforms a multiple linear regression model based on the same features and achieves better performance metrics than previously reported models using the same underlying data. These features include: (1) polar surface area in water, (2) the octanol-water partitioning coefficient, (3) the number of hydrogen-bond donors, (4) the sum of the topological distances between nitrogen atoms, (5) the sum of the topological distances between nitrogen and oxygen atoms, and (6) the multiple molecular path count of order 2. The last three features represent molecular flexibility, the ability of the molecule to adopt different conformations in the aqueous and membrane interior phases, and the molecular "chameleonicity." Guided by the model, we propose design guidelines for membrane-permeating macrocycles. It is anticipated that this model will be useful in guiding the design of large, bioactive molecules for medicinal chemistry and chemical biology applications.

Linker-Dependent Folding Rationalizes PROTAC Cell Permeability

Proteolysis-targeting chimeras (PROTACs) must be cell permeable to reach their target proteins. This is challenging as the bivalent structure of PROTACs puts them in chemical space at, or beyond, the outer limits of oral druggable space. We used NMR spectroscopy and molecular dynamics (MD) simulations independently to gain insights into the origin of the differences in cell permeability displayed by three flexible cereblon PROTACs having closely related structures. Both methods revealed that the propensity of the PROTACs to adopt folded conformations with a low solvent-accessible 3D polar surface area in an apolar environment is correlated to high cell permeability. The chemical nature and the flexibility of the linker were essential for the PROTACs to populate folded conformations stabilized by intramolecular hydrogen bonds, π-π interactions, and van der Waals interactions. We conclude that MD simulations may be used for the prospective ranking of cell permeability in the design of cereblon PROTACs.

Trends in small molecule drug properties: A developability molecule assessment perspective

Developability molecule assessment is a key interfacial capability across the biopharmaceutical industry, screening and staging molecules discovered by medicinal chemists for successful chemistry manufacturing controls (CMC) development and launch. The breadth of responsibility and expertise such teams possess puts them in a unique position to understand the impact of the physicochemical properties of a drug during its initial discovery and subsequent development. However, most of the publications describing trends in physicochemical properties are written from a medicinal chemistry perspective with the aim to identify molecules with better ADMET profiles that are either lead-like or drug-like, failing to describe the impact these properties have on CMC development. To systematically uncover knowledge obtained from recent trends in physicochemical properties and the corresponding impact on CMC development, a comprehensive analysis was conducted on molecules in the drug repurposing hub dataset. The only physicochemical property that seems to have been preserved in FDA-approved oral molecules over the decades (1900-2020) is a constant H-bond donor count, highlighting the importance this property has on cell permeability and lattice energy. Pharmaceutical attrition analysis suggests that partition-distribution coefficient, H-bond acceptors, polar surface area and the fraction of sp³ carbons are properties that are associated with compound attrition. Looking at pharmaceutical attrition asynchronously with the temporal analysis of FDA-approved oral molecules highlights the opposing trends, risks and diminishing effects some of these physiochemical properties (cLogP, cLogD and Fsp3) have on describing compound attrition during the past decade. Trellising the dataset by target class suggests that certain formulation and drug delivery strategies can be anticipated or put into place based on target class of a molecule. For example, molecules binding to nuclear hormone receptors are amenable to lipid-based drug delivery systems with proven commercial success. Although the poor solubility of kinase inhibitors is a combination of hydrophobicity (due to aromaticity) required to bind to its target and high lattice energy (melting point), they are a challenging target class to formulate. The influence of drug targets on physicochemical properties and the temporal nature of these properties is highlighted when comparing molecules in the drug repurposing dataset to those developed at Amgen. An improved understanding of the impact of molecular properties on performance attributes can accelerate decisions and facilitate risk assessments during candidate selection and development.

Refinement of Computational Access to Molecular Physicochemical Properties: From Ro5 to bRo5

There is a need of computational tools to rank bRo5 drug candidates in the very early phases of drug discovery when chemical matter is unavailable. In this study, we selected three compounds: (a) a Ro5 drug (Pomalidomide), (b) a bRo5 orally available drug (Saquinavir), and (c) a polar PROTAC (CMP 98) to focus on computational access to physicochemical properties. To provide a benchmark, the three compounds were first experimentally characterized for their lipophilicity, polarity, IMHBs, and chameleonicity. To reproduce the experimental information content, we generated conformer ensembles with conformational sampling and molecular dynamics in both water and nonpolar solvents. Then we calculated Rgyr, 3D PSA, and IMHB number. An innovative pool of strategies for data analysis was then provided. Overall, we report a contribution to close the gap between experimental and computational methods for characterizing bRo5 physicochemical properties.

PepSeA: Peptide Sequence Alignment and Visualization Tools to Enable Lead Optimization

Therapeutic peptides offer potential advantages over small molecules in terms of selectivity, affinity, and their ability to target "undruggable" proteins that are associated with a wide range of pathologies. Despite their importance, current molecular design capabilities that inform medicinal chemistry decisions on peptide programs are limited. More specifically, there are unmet needs for structure-activity relationship (SAR) analysis and visualization of linear, cyclic, and cross-linked peptides containing non-natural motifs, which are widely used in drug discovery. To bridge this gap, we developed PepSeA (Peptide Sequence Alignment and Visualization), an open-source, freely available package of sequence-based tools (https://github.com/Merck/PepSeA). PepSeA enables multiple sequence alignment of non-natural amino acids and enhanced visualization with the hierarchical editing language for macromolecules (HELM). Via stepwise SAR analysis of a ChEMBL peptide data set, we demonstrate the utility of PepSeA to accelerate decision making in lead optimization campaigns in pharmaceutical setting. PepSeA represents an initial attempt to expand cheminformatics capabilities for therapeutic peptides and to enable rapid and more efficient design-make-test cycles.

Prediction of Chameleonic Efficiency

Chameleonic properties, i. e., the capacity of a molecule to hide polarity in non-polar environments and expose it in water, help achieving sufficient permeability and solubility for drug molecules with high MW. We present models of experimental measures of polarity for a set of 24 FDA approved drugs (MW 405-1113) and one PROTAC (MW 1034). Conformational ensembles in aqueous and non-polar environments were generated using molecular dynamics. A linear regression model that predicts chromatographic apparent polarity (EPSA) with a mean unsigned error of 10 Ų was derived based on separate terms for donor, acceptor, and total molecular SASA. A good correlation (R² =0.92) with an experimental measure of hydrogen bond donor potential, Δlog P_oct-tol , was found for the mean hydrogen bond donor SASA of the conformational ensemble scaled with Abraham's A hydrogen bond acidity. Two quantitative measures of chameleonic behaviour, the chameleonic efficiency indices, are introduced. We envision that the methods presented herein will be useful to triage designed molecules and prioritize those with the best chance of achieving acceptable permeability and solubility.

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.

Permeability prediction in the beyond-Rule-of 5 chemical space: Focus on cyclic hexapeptides

Cyclic peptides (CPs) are gaining more and more relevance in drug discovery. Since one of their main drawbacks is poor permeability, the discovery of new orally available CP drugs requires computational tools that predict CP permeability in very early drug discovery. In this study we used a literature dataset of 62 cyclic hexapeptides to evaluate the performances of a number of in silico tools based on different computational theory to model and rationalize PAMPA and Caco-2 permeability values. In particular, we submitted the dataset to a) online calculators, b) QSPR strategies, c) a physics-based tool, d) a mixed approach and e) a kinetic method. This latter is an emergent strategy in which a few relevant conformations retrieved from a set of molecular dynamics (MD) simulations by the Markov State Model (MSM) are used to establish the compounds permeability. Both free and commercial software were used. Results were compared with a model based on experimental physicochemical descriptors. All the computational approaches but online calculators performed quite well and show that lipophilicity and not polarity is the main determinant of the investigated event. A second major outcome of the study is that the impact of flexibility on the permeability of the considered dataset cannot be unambiguously assessed. Finally, our comparative analysis, which also included not common applied strategies, allowed a sound evaluation of the pros and cons of the applied computational approaches.

Structure, solubility, and permeability relationships in a diverse middle molecule library

To develop methodology to predict the potential druggability of middle molecules, we examined the structure, solubility, and permeability relationships of a diverse library (HKDL ver.1) consisting of 510 molecules (359 natural product derivatives, 76 non-natural products, 46 natural products, and 29 non-natural product derivatives). The library included peptides, depsipeptides, macrolides, and lignans, and 476 of the 510 compounds had a molecular weight in the range of 500-2000 Da. The solubility and passive diffusion velocity of the middle molecules were assessed using the parallel artificial membrane permeability assay (PAMPA). Quantitative values of solubility of 471 molecules and passive diffusion velocity of 287 molecules were obtained, and their correlations with the structural features of the molecules were examined. Based on the results, we propose a method to predict the passive diffusion characteristics of middle molecules from their three-dimensional structural features.

Rifampicin as an example of beyond-rule-of-5 compound: Ionization beyond water and lipophilicity beyond octanol/water

Ionization and lipophilicity in early drug discovery are commonly characterized in water and octanol/water, respectively and thus do not consider the non-polar features of the biomembrane core. This is particularly limiting for bRo5 compounds which may adapt their properties (e.g. ionization and lipophilicity) to the environment. In this paper we used experimental methods to characterize rifampicin for its ionization properties in various water/cosolvent mixtures and in pure MeCN and its lipophilicity in octanol/water and toluene/water systems. Moreover, we also measured log k'80 PLRP-S, a chromatographic index of lipophilicity in non-polar media. Results show that the existence domain of neutral rifampicin is limited compared to the zwitterion, but the lipophilic cationic species is extremely relevant in non-polar environments.

Solution Conformations Shed Light on PROTAC Cell Permeability

Proteolysis targeting chimeras (PROTACs) induce intracellular degradation of target proteins. Their bifunctional structure puts degraders in a chemical space where ADME properties often complicate drug discovery. Herein we provide the first structural insight into PROTAC cell permeability obtained by NMR studies of a VHL-based PROTAC (1), which is cell permeable despite having a high molecular weight and polarity and a large number of rotatable bonds. We found that 1 populates elongated and polar conformations in solutions that mimic extra- and intracellular compartments. Conformations were folded and had a smaller polar surface area in chloroform, mimicking a cell membrane interior. Formation of intramolecular and nonclassical hydrogen bonds, π–π interactions, and shielding of amide groups from solvent all facilitate cell permeability by minimization of size and polarity. We conclude that molecular chameleonicity appears to be of major importance for 1 to enter into target cells.

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.

Membrane Permeability in Cyclic Peptides is Modulated by Core Conformations

Cyclic peptides have the potential to bind to challenging targets, which are undruggable with small molecules, but their application is limited by low membrane permeability. Here, using a series of cyclic pentapeptides, we showed that established physicochemical criteria of permeable peptides are heavily violated. We revealed that a dominant core conformation, stabilized by amides' shielding pattern, could guide the design of novel compounds. As a result, counter-intuitive strategies, such as incorporation of polar residues, can be beneficial for permeability. We further find that core globularity is a promising descriptor, which can extend the capability of standard predictive models.

Development and Regulatory Challenges for Peptide Therapeutics

There has been an increased interest in and activity for the use of peptide therapeutics to treat a variety of human diseases. The number of peptide drugs entering clinical development and the market has increased significantly over the past decade despite inherent challenges of peptide therapeutic discovery, development, and patient-friendly delivery. Disparities in interpretation and application of existing regulatory guidances to innovative synthetic and conjugated peptide assets have resulted in challenges for both regulators and sponsors. The Symposium on Development and Regulatory Challenges for Peptide Therapeutics at the 40th Annual Meeting of the American College of Toxicology held in November of 2019 focused on the following specific topics: (1) peptide therapeutic progress and future directions, and approaches to discover, optimize, assess, and deliver combination peptide therapeutics for treatment of diseases; (2) toxicological considerations to advance peptide drug-device combination products for efficient development and optimal patient benefit and adherence; (3) industry and regulatory perspectives on the regulation of synthetic and conjugated peptide products, including exploration of regulatory classifications, interpretations, and application of the existing guidances International Council for Harmonisation (ICH) M3(R2) and ICH S6(R1) in determining nonclinical study recommendations; and (4) presentation of the 2016 Health and Environmental Sciences Institute's Genetic Toxicology Technical Committee working group assessment of genotoxicity testing requirements. Perspectives were shared from industry and regulatory scientists working in the peptide therapeutics field followed by an open forum panel discussion to discuss questions drafted for the peptide therapeutics scientific community, which will be discussed in more detail.

Structural Similarities between Some Common Fluorophores Used in Biology, Marketed Drugs, Endogenous Metabolites, and Natural Products

It is known that at least some fluorophores can act as 'surrogate' substrates for solute carriers (SLCs) involved in pharmaceutical drug uptake, and this promiscuity is taken to reflect at least a certain structural similarity. As part of a comprehensive study seeking the 'natural' substrates of 'orphan' transporters that also serve to take up pharmaceutical drugs into cells, we have noted that many drugs bear structural similarities to natural products. A cursory inspection of common fluorophores indicates that they too are surprisingly 'drug-like', and they also enter at least some cells. Some are also known to be substrates of efflux transporters. Consequently, we sought to assess the structural similarity of common fluorophores to marketed drugs, endogenous mammalian metabolites, and natural products. We used a set of some 150 fluorophores along with standard fingerprinting methods and the Tanimoto similarity metric. Results: The great majority of fluorophores tested exhibited significant similarity (Tanimoto similarity > 0.75) to at least one drug, as judged via descriptor properties (especially their aromaticity, for identifiable reasons that we explain), by molecular fingerprints, by visual inspection, and via the "quantitative estimate of drug likeness" technique. It is concluded that this set of fluorophores does overlap with a significant part of both the drug space and natural products space. Consequently, fluorophores do indeed offer a much wider opportunity than had possibly been realised to be used as surrogate uptake molecules in the competitive or trans-stimulation assay of membrane transporter activities.

Predicting the Permeability of Macrocycles from Conformational Sampling - Limitations of Molecular Flexibility

Macrocycles constitute superior ligands for targets that have flat binding sites but often require long synthetic routes, emphasizing the need for property prediction prior to synthesis. We have investigated the scope and limitations of machine learning classification models and of regression models for predicting the cell permeability of a set of denovo-designed, drug-like macrocycles. 2D-Based classification models, which are fast to calculate, discriminated between macrocycles that had low-medium and high permeability and may be used as virtual filters in early drug discovery projects. Importantly, stereo- and regioisomer were correctly classified. QSPR studies of two small sets of comparator drugs suggested that use of 3D descriptors, calculated from biologically relevant conformations, would allow development of more precise regression models for late phase drug projects. However, a 3D permeability model could only be developed for a rigid series of macrocycles. Comparison of NMR based conformational analysis with in silico conformational sampling indicated that this shortcoming originates from the inability of the molecular mechanics force field to identify the relevant conformations for flexible macrocycles. We speculate that a Kier flexibility index of ≤10 constitutes a current upper limit for reasonably accurate 3D prediction of macrocycle cell permeability.

Clearance prediction for Amgen molecules against Extended Clearance Classification System (ECCS) and future directions

Early prediction of elimination pathways for new chemical entities can have a profound impact on drug discovery programs. The recently proposed Extended Clearance Classification System (ECCS) is a step in the right direction, providing a framework to help identify the major elimination pathway of a drug. A list of 42 Amgen small molecules was evaluated against the ECCS framework to assess its performance in retrospectively predicting their major elimination pathway. Here, we present a critical analysis of the chemical space defined by the ECCS framework with the aim of identifying its applicability and constraints. This evaluation highlights the critical need for periodic review and revision of ECCS, given that target constraints are moving molecules away from the traditional 'drug-like' physicochemical space.

Machine learning-guided discovery and design of non-hemolytic peptides

Reducing hurdles to clinical trials without compromising the therapeutic promises of peptide candidates becomes an essential step in peptide-based drug design. Machine-learning models are cost-effective and time-saving strategies used to predict biological activities from primary sequences. Their limitations lie in the diversity of peptide sequences and biological information within these models. Additional outlier detection methods are needed to set the boundaries for reliable predictions; the applicability domain. Antimicrobial peptides (AMPs) constitute an extensive library of peptides offering promising avenues against antibiotic-resistant infections. Most AMPs present in clinical trials are administrated topically due to their hemolytic toxicity. Here we developed machine learning models and outlier detection methods that ensure robust predictions for the discovery of AMPs and the design of novel peptides with reduced hemolytic activity. Our best models, gradient boosting classifiers, predicted the hemolytic nature from any peptide sequence with 95–97% accuracy. Nearly 70% of AMPs were predicted as hemolytic peptides. Applying multivariate outlier detection models, we found that 273 AMPs (~ 9%) could not be predicted reliably. Our combined approach led to the discovery of 34 high-confidence non-hemolytic natural AMPs, the de novo design of 507 non-hemolytic peptides, and the guidelines for non-hemolytic peptide design.

Degraders early developability assessment: face-to-face with molecular properties

Pharmaceutical scientists have huge expectations from heterobifunctional small molecule degraders to treat diseases with an unmet medical need. However, degraders are large and flexible and pose significant challenges in terms of cellular uptake and bioavailability. An efficient property-based design is therefore required to discover new oral degrader medicines. Here, we show the non‑transferability to degraders of in silico tools routinely implemented in small molecule drug discovery programs; and provide ionization, lipophilicity, polarity and chameleonicity data for a series of seven degraders. We also reveal that permeability can be modeled by Δlog k_W^IAM - an experimental polarity descriptor. Overall, the paper is a proof-of-concept that shows to discover new oral degrader drugs ad hoc property-based design strategies are required.

Structure-Permeability Relationship of Semipeptidic Macrocycles-Understanding and Optimizing Passive Permeability and Efflux Ratio

We herein report the first thorough analysis of the structure-permeability relationship of semipeptidic macrocycles. In total, 47 macrocycles were synthesized using a hybrid solid-phase/solution strategy, and then their passive and cellular permeability was assessed using the parallel artificial membrane permeability assay (PAMPA) and Caco-2 assay, respectively. The results indicate that semipeptidic macrocycles generally possess high passive permeability based on the PAMPA, yet their cellular permeability is governed by efflux, as reported in the Caco-2 assay. Structural variations led to tractable structure-permeability and structure-efflux relationships, wherein the linker length, stereoinversion, N-methylation, and peptoids site-specifically impact the permeability and efflux. Extensive nuclear magnetic resonance, molecular dynamics, and ensemble-based three-dimensional polar surface area (3D-PSA) studies showed that ensemble-based 3D-PSA is a good predictor of passive permeability.

Facts, Patterns, and Principles in Drug Discovery: Appraising the Rule of 5 with Measured Physicochemical Data

The rule of 5 was designed to estimate the likelihood of poor absorption or permeation, noting the impact of poor solubility. This Perspective explores the impact of various physicochemical descriptors and contemporary lipophilicity measurements on permeability and solubility, showing that the distribution coefficient log D_7.4 (rather than log P) is the most impactful parameter. Molecular weight, almost invariably the defining characteristic of "beyond the rule of 5" compounds, has little impact on solubility when log D_7.4 measurements and aromaticity are considered. Predicting permeation is more complex, given passive and carrier transport mechanisms; however, notable patterns of behavior are apparent, giving insight even "beyond the rule of 5". Recommended best practices should involve using the facts (measurements) and the patterns they reveal to establish informative principles rather than fastidious rules.

Updating the portfolio of physicochemical descriptors related to permeability in the beyond the rule of 5 chemical space

Beyond rule of 5 (bRo5) molecules are attracting significant interest in modern drug discovery mostly because many novel targets require large and more flexible structures. The main aim of this paper is the identification of ad hoc bRo5 physicochemical descriptors of ionization, lipophilicity, polarity and chameleonicity and their measurement. We used different methods to collect ionization (pK_a measures and log k'80 PLRP-S trends), lipophilicity (in octanol/water, in apolar systems and in biomimetic environments), polarity (Δlog P_oct-tol, EPSA and Δlog K_W^IAM) and chameleonicity (ChameLogD) descriptors for 26 bRo5 drugs. A second aim was to check the relationship between physicochemical descriptors and permeability for a subset of compounds for which solid permeability values are reported in the literature. Results showed that the physicochemical profile in the bRo5 chemical space is often experimentally accessible, albeit more tools are required to overcome limitations of individual methods. For the investigated compounds, permeability is governed by Δlog P_oct-tol and preliminary data support that chameleonicity could also have an impact.

Permeability of Cyclic Peptide Macrocycles and Cyclotides and Their Potential as Therapeutics

Macrocycles have emerged as a viable approach for the modulation of tough targets in drug discovery. In this Innovations article we discuss recent progress toward the design of cell permeable and orally bioavailable peptide macrocycles and cyclotides and provide a perspective for their potential as therapeutics. We highlight design concepts that may be broadly relevant to drug discovery efforts beyond the rule of five.

Experimental lipophilicity for beyond Rule of 5 compounds

Aim: To set up a chromatographic strategy for the determination of log P for beyond Rule of 5 (bRo5) drugs. Materials & methods: Capacity factors measured by reverse phase-HPLC. Balance of intermolecular interactions governing systems assessed by partial least squares regression (PLSR) coupled with block relevance anaysis (PLSR-BR) and multiblock PLSR (MBPLSR). Determination of virtual log P obtained through conformational sampling. Results: log k′60 is highly correlated with log P for a dataset of 36 Ro5 compliant compounds (R2 = 0.93, Q2 = 0.90). We refer to the value generated via this method as BRlogP. The balance of intermolecular forces controlling BRlogP and log P are very similar. The ElogPs measured for the bRo5 dataset are significantly higher than corresponding BRlogP. Conclusion: The combination of BRlogP and ElogP provides an experimental lipophilicity range for bRo5 compounds.

Application of biomimetic HPLC to estimate in vivo behavior of early drug discovery compounds

Characterizing the properties of large numbers of compounds and estimating their potential absorption, distribution, metabolism and elimination properties are important early stages in the process of drug discovery and help to reduce later stage attrition. The chromatographic separation principles using stationary phases that contain proteins and phospholipids are more suitable for compound characterization and estimation of the pharmacokinetic properties than the traditional octanol/water partition coefficient. This technology, when standardized, enables the prediction of in vivo behavior and the selection of compounds with the best potential, thus reducing the number of animal experiments. Chromatography may be involved more widely in the future to measure kinetic aspects of compounds’ binding to proteins and receptors which would enable designing compounds that require a lower frequency of doses and have more predictable pharmacokinetic profiles.

Conformation and Permeability: Cyclic Hexapeptide Diastereomers

Conformational ensembles of eight cyclic hexapeptide diastereomers in explicit cyclohexane, chloroform, and water were analyzed by multicanonical molecular dynamics (McMD) simulations. Free-energy landscapes (FELs) for each compound and solvent were obtained from the molecular shapes and principal component analysis at T = 300 K; detailed analysis of the conformational ensembles and flexibility of the FELs revealed that permeable compounds have different structural profiles even for a single stereoisomeric change. The average solvent-accessible surface area (SASA) in cyclohexane showed excellent correlation with the cell permeability, whereas this correlation was weaker in chloroform. The average SASA in water correlated with the aqueous solubility. The average polar surface area did not correlate with cell permeability in these solvents. A possible strategy for designing permeable cyclic peptides from FELs obtained from McMD simulations is proposed.

Metabolites of n-Butylparaben and iso-Butylparaben Exhibit Estrogenic Properties in MCF-7 and T47D Human Breast Cancer Cell Lines

Two oxidized metabolites of n-butylparaben (BuP) and iso-butylparaben (IsoBuP) discovered in human urine samples exhibit structural similarity to endogenous estrogens. We hypothesized that these metabolites bind to the human estrogen receptor (ER) and promote estrogen signaling. We tested this using models of ER-mediated cellular proliferation. The estrogenic properties of 3-hydroxy n-butyl 4-hydroxybenzoate (3OH) and 2-hydroxy iso-butyl 4-hydroxybenzoate (2OH) were determined using the ER-positive, estrogen-dependent human breast cancer cell lines MCF-7, and T47D. The 3OH metabolite induced cellular proliferation with EC50 of 8.2 µM in MCF-7 cells. The EC50 for 3OH in T47D cells could not be reached. The 2OH metabolite induced proliferation with EC50 of 2.2 µM and 43.0 µM in MCF-7 and T47D cells, respectively. The EC50 for the parental IsoBuP and BuP was 0.30 and 1.2 µM in MCF-7 cells, respectively. The expression of a pro-proliferative, estrogen-inducible gene (GREB1) was induced by these compounds and blocked by co-administration of an ER antagonist (ICI 182, 780), confirming the ER-dependence of these effects. The metabolites promoted significant ER-dependent transcriptional activity of an ERE-luciferase reporter construct at 10 and 20 µM for 2OH and 10 µM for 3OH. Computational docking studies showed that the paraben compounds exhibited the potential for favorable ligand-binding domain interactions with human ERα in a manner similar to known x-ray crystal structures of 17ß-estradiol in complex with ERα. We conclude that the hydroxylated metabolites of BuP and IsoBuP are weak estrogens and should be considered as additional components of potential endocrine disrupting effects upon paraben exposure.

Preferential Equilibrium Partitioning of Positively Charged Tryptophan into Phosphatidylcholine Bilayer Membranes

The interactions between small molecules and lipid bilayers play a critical role in the function of cellular membranes. Understanding how a small molecule interacts with the lipid bilayer differently based on its charge reveals primordial mechanisms of transport across membranes and assists in the design of drug molecules that can penetrate cells. We have previously reported that tryptophan permeated through a phosphatidylcholine lipid bilayer membrane at a faster rate when it was positively charged (Trp+) than when negatively charged (Trp-), which corresponded to a lower potential of mean force (PMF) barrier determined through simulations. In this report, we demonstrate that Trp+ partitions into the lipid bilayer membrane to a greater degree than Trp- by interacting with the ester linkage of a phosphatidylcholine lipid, where it is stabilized by the electron withdrawing glycerol functional group. These results are in agreement with tryptophan's known role as an anchor for transmembrane proteins, though the tendency for binding of a positively charged tryptophan is surprising. We discuss the implications of our results on the mechanisms of unassisted permeation and penetration of small molecules within and across lipid bilayer membranes based on molecular charge, shape, and molecular interactions within the bilayer structure.

Design Principles for Intestinal Permeability of Cyclic Peptides

One of the most exciting facets of cyclic peptides is that they have the potential to be orally bioavailable, despite having physical properties well beyond the traditional "Rule-of-5" chemistry space (Lipinski et al., Adv Drug Deliv Rev. 23(1): 3-25, 1997). An important component of meeting this challenge is to design cyclic peptides with good intestinal permeability. Here we discuss the design principles for intestinal permeability that have been developed in recent year. These principles can be subdivided into three regimes: physical property guidelines, design strategies for the macrocyclic ring, and design strategies for side chains. The most important overall aims are to minimize solvent-exposed polarity while keeping size, flexibility, and lipophilicity within favorable ranges, thereby allowing peptide chemists to achieve intestinal permeability in addition to other important properties for their compounds, such as solubility and binding affinity. Here we describe a variety of design strategies that have been developed to help peptide chemists in this endeavor.

Conformational Sampling of Macrocyclic Drugs in Different Environments: Can We Find the Relevant Conformations?

Conformational flexibility is a major determinant of the properties of macrocycles and other drugs in beyond rule of 5 (bRo5) space. Prediction of conformations is essential for design of drugs in this space, and we have evaluated three tools for conformational sampling of a set of 10 bRo5 drugs and clinical candidates in polar and apolar environments. The distance-geometry based OMEGA was found to yield ensembles spanning larger structure and property spaces than the ensembles obtained by MOE-LowModeMD (MOE) and MacroModel (MC). Both MC and OMEGA but not MOE generated different ensembles for polar and apolar environments. All three conformational search methods generated conformers similar to the crystal structure conformers for 9 of the 10 compounds, with OMEGA performing somewhat better than MOE and MC. MOE and OMEGA found all six conformers of roxithromycin that were identified by NMR in aqueous solutions, whereas only OMEGA sampled the three conformers observed in chloroform. We suggest that characterization of conformers using molecular descriptors, e.g., the radius of gyration and polar surface area, is preferred to energy- or root-mean-square deviation-based methods for selection of biologically relevant conformers in drug discovery in bRo5 space.

Impact of Dynamically Exposed Polarity on Permeability and Solubility of Chameleonic Drugs Beyond the Rule of 5

Conformational flexibility has been proposed to significantly affect drug properties outside rule-of-5 (Ro5) chemical space. Here, we investigated the influence of dynamically exposed polarity on cell permeability and aqueous solubility for a structurally diverse set of drugs and clinical candidates far beyond the Ro5, all of which populated multiple distinct conformations as revealed by X-ray crystallography. Efflux-inhibited (passive) Caco-2 cell permeability correlated strongly with the compounds' minimum solvent-accessible 3D polar surface areas (PSA), whereas aqueous solubility depended less on the specific 3D conformation. Inspection of the crystal structures highlighted flexibly linked aromatic side chains and dynamically forming intramolecular hydrogen bonds as particularly effective in providing "chameleonic" properties that allow compounds to display both high cell permeability and aqueous solubility. These structural features, in combination with permeability predictions based on the correlation to solvent-accessible 3D PSA, should inspire drug design in the challenging chemical space far beyond the Ro5.