Prediction of Chameleonic Efficiency

Closing the Design-Make-Test-Analyze Loop: Interplay between Experiments and Predictions Drives PROTACs Bioavailability

The drug development landscape is expanding to include drug modalities such as PROteolysis-TArgeting Chimeras (PROTACs) and peptides, offering possibilities for previously intractable biological targets. However, with their size and chemical nature, they diverge from established frameworks for the prediction of oral bioavailability. This evolution to larger and more complex molecules necessitates new methodologies and prediction models to continuously expand on bioavailability guidelines. We describe the high-capacity adoption of two chromatographic physicochemical assays and their application for iterative compound optimization to achieve oral bioavailability. We further describe how these data underpin the continuous refinement of internal machine learning models, which guide compound synthesis decisions in the molecular design phase. Based on data for a set of 691 PROTACs, and two project examples, we confirm a sweet spot for oral bioavailability at log D values higher than the norm for small molecules and show how experimental data and prediction models synergize to effectively drive chemistry optimization.

Targeted protein degradation: advances in drug discovery and clinical practice

Targeted protein degradation (TPD) represents a revolutionary therapeutic strategy in disease management, providing a stark contrast to traditional therapeutic approaches like small molecule inhibitors that primarily focus on inhibiting protein function. This advanced technology capitalizes on the cell's intrinsic proteolytic systems, including the proteasome and lysosomal pathways, to selectively eliminate disease-causing proteins. TPD not only enhances the efficacy of treatments but also expands the scope of protein degradation applications. Despite its considerable potential, TPD faces challenges related to the properties of the drugs and their rational design. This review thoroughly explores the mechanisms and clinical advancements of TPD, from its initial conceptualization to practical implementation, with a particular focus on proteolysis-targeting chimeras and molecular glues. In addition, the review delves into emerging technologies and methodologies aimed at addressing these challenges and enhancing therapeutic efficacy. We also discuss the significant clinical trials and highlight the promising therapeutic outcomes associated with TPD drugs, illustrating their potential to transform the treatment landscape. Furthermore, the review considers the benefits of combining TPD with other therapies to enhance overall treatment effectiveness and overcome drug resistance. The future directions of TPD applications are also explored, presenting an optimistic perspective on further innovations. By offering a comprehensive overview of the current innovations and the challenges faced, this review assesses the transformative potential of TPD in revolutionizing drug development and disease management, setting the stage for a new era in medical therapy.

The Particle Drifting Effect: A Combined Function of Colloidal and Drug Properties

The particle drifting effect, where nanosized colloidal drug particles overcome the diffusional resistance of the aqueous boundary layer adjacent to the intestinal wall and increase drug absorption rates, is drawing increasing attention in pharmaceutical research. However, mechanistic understanding and accurate prediction of the particle drifting effect remain lacking. In this study, we systematically evaluated the extent of the particle drifting effect affected by drug and colloidal properties, including the size, number, and type of the moving species using biphasic diffusion experiments combined with computational fluid dynamics simulations and mass transport analyses. The results showed that the particle drifting effect is a sequential reaction of particle dissolution/dissociation in the diffusional boundary layer, followed by absorption of the free drug. Therefore, factors affecting the rate-limiting step, which can be either process or both under different circumstances, alter the particle drifting effect. Experimental results also agree with the theory that the particle dissolution rate is dependent on particle size, concentration, and drug solubility. In addition, rapid bile micelle dissociation and bile salt absorption facilitated drug absorption by the particle drifting effect. Our findings explain the highly dynamic nature of the particle drifting effect and will contribute to rational formulation development and better bioavailability prediction for formulations containing colloidal particles.

Computational methods and key considerations for in silico design of proteolysis targeting chimera (PROTACs)

Proteolysis-targeting chimeras (PROTACs), as heterobifunctional molecules, have garnered significant attention for their ability to target previously undruggable proteins. Due to the challenges in obtaining crystal structures of PROTAC molecules in the ternary complex, a plethora of computational tools have been developed to aid in PROTAC design. These computational tools can be broadly classified into artificial intelligence (AI)-based or non-AI-based methods. This review aims to provide a comprehensive overview of the latest computational methods for the PROTAC design process, covering both AI and non-AI approaches, from protein selection to ternary complex modeling and prediction. Key considerations for in silico PROTAC design are discussed, along with additional considerations for deploying AI-based models. These considerations are intended to guide subsequent model development in the PROTAC design process. Finally, future directions and recommendations are provided.

Highly Selective Drug-Derived Fluorescent Probes for the Cannabinoid Receptor Type 1 (CB1R)

The cannabinoid receptor type 1 (CB1R) is pivotal within the endocannabinoid system regulating various signaling cascades with effects in appetite regulation, pain perception, memory formation, and thermoregulation. Still, understanding of CB1R's cellular signaling, distribution, and expression dynamics is very fragmentary. Real-time visualization of CB1R is crucial for addressing these questions. Selective drug-like CB1R ligands with a defined pharmacological profile were investigated for the construction of CB1R fluorescent probes using a reverse design-approach. A modular design concept with a diethyl glycine-based building block as the centerpiece allowed for the straightforward synthesis of novel probe candidates. Validated by computational docking studies, radioligand binding, and cAMP assay, this systematic approach allowed for the identification of novel pyrrole-based CB1R fluorescent probes. Application in fluorescence-based target-engagement studies and live cell imaging exemplify the great versatility of the tailored CB1R probes for investigating CB1R localization, trafficking, pharmacology, and its pathological implications.

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.

Beyond Rule of Five and PROTACs in Modern Drug Discovery: Polarity Reducers, Chameleonicity, and the Evolving Physicochemical Landscape

Developing orally bioavailable drugs demands an understanding of absorption in early drug development. Traditional methods and physicochemical properties optimize absorption for rule of five (Ro5) compounds; beyond rule of five (bRo5) drugs necessitate advanced tools like the experimental measure of exposed polarity (EPSA) and the AbbVie multiparametric score (AB-MPS). Analyzing AB-MPS and EPSA against ∼1000 compounds with human absorption data and ∼10,000 AbbVie tool compounds (∼1000 proteolysis targeting chimeras or PROTACs, ∼7000 Ro5s, and ∼2000 bRo5s) revealed new patterns of physicochemical trends. We introduced a high-throughput "polarity reduction" descriptor: ETR, the EPSA-to-topological polar surface area (TPSA) ratio, highlights unique bRo5 and PROTAC subsets for specialized drug design strategies for effective absorption. Our methods and guidelines refine drug design by providing innovative in vitro approaches, enhancing physicochemical property optimization, and enabling accurate predictions of intestinal absorption in the complex bRo5 domain.

Oral Absorption of Middle-to-Large Molecules and Its Improvement, with a Focus on New Modality Drugs

To meet unmet medical needs, middle-to-large molecules, including peptides and oligonucleotides, have emerged as new therapeutic modalities. Owing to their middle-to-large molecular sizes, middle-to-large molecules are not suitable for oral absorption, but there are high expectations around orally bioavailable macromolecular drugs, since oral administration is the most convenient dosing route. Therefore, extensive efforts have been made to create bioavailable middle-to-large molecules or develop absorption enhancement technology, from which some successes have recently been reported. For example, Rybelsus® tablets and Mycapssa® capsules, both of which contain absorption enhancers, were approved as oral medications for type 2 diabetes and acromegaly, respectively. The oral administration of Rybelsus and Mycapssa exposes their pharmacologically active peptides with molecular weights greater than 1000, namely, semaglutide and octreotide, respectively, into systemic circulation. Although these two medications represent major achievements in the development of orally absorbable peptide formulations, the oral bioavailability of peptides after taking Rybelsus and Mycapssa is still only around 1%. In this article, we review the approaches and recent advances of orally bioavailable middle-to-large molecules and discuss challenges for improving their oral absorption.

Current advances and development strategies of orally bioavailable PROTACs

Proteolysis-targeting chimeras (PROTACs) have been an area of intensive research with the potential to extend drug space not target to traditional molecules. In the last half decade, we have witnessed several PROTACs initiated phase I/II/III clinical trials, which inspired us a lot. However, the structure of PROTACs beyond "rule of 5" resulted in developing PROTACs with acceptable oral pharmacokinetic (PK) properties remain one of the biggest bottleneck tasks. Many reports have demonstrated that it is possible to access orally bioavailable PROTACs through rational ligand and linker modifications. In this review, we systematically reviewed and highlighted the most recent advances in orally bioavailable PROTACs development, especially focused on the medicinal chemistry campaign of discovery process and in vivo oral PK properties. Moreover, the constructive strategies for developing oral PROTACs were proposed comprehensively. Collectively, we believe that the strategies summarized here may provide references for further development of oral PROTACs.

Energy-entropy multiscale cell correlation method to predict toluene-water log P in the SAMPL9 challenge

The energy-entropy multiscale cell correlation (EE-MCC) method is used to calculate toluene-water log P values of 16 drug molecules in the SAMPL9 physical properties challenge. EE-MCC calculates the free energy, energy and entropy from molecular dynamics (MD) simulations of the water and toluene solutions. Specifically, MCC evaluates entropy by partitioning the system into cells of correlated atoms at multiple length scales and further partitioning the local coordinates into energy wells, yielding vibrational and topographical terms from the energy-well sizes and probabilities. The log P values calculated by EE-MCC using three 200 ns MD simulations have a mean average error of 0.82 and standard error of the mean of 0.97 versus experiment, which is comparable with the best methods entered in SAMPL9. The main contribution to log P is from energy. Less polar drugs have more favourable energies of transfer. The entropy of transfer consists of increased solute vibrational and conformational terms in toluene due to weaker interactions, fewer solute positions in the larger-molecule solvent, reduced water vibrational entropy, negligible change in toluene vibrational entropy, and gains in solvent orientational entropy. The solvent entropy contributions here may be slightly underestimated because software limitations and statistical fluctuations meant that only the first shell could be included while averaged over the whole solution. Nonetheless, such issues will be addressed in future software to offer a general method to calculate entropy directly from MD simulation and to provide molecular understanding or guide system design.

Targeted Protein Degradation: Advances, Challenges, and Prospects for Computational Methods

The therapeutic approach of targeted protein degradation (TPD) is gaining momentum due to its potentially superior effects compared with protein inhibition. Recent advancements in the biotech and pharmaceutical sectors have led to the development of compounds that are currently in human trials, with some showing promising clinical results. However, the use of computational tools in TPD is still limited, as it has distinct characteristics compared with traditional computational drug design methods. TPD involves creating a ternary structure (protein-degrader-ligase) responsible for the biological function, such as ubiquitination and subsequent proteasomal degradation, which depends on the spatial orientation of the protein of interest (POI) relative to E2-loaded ubiquitin. Modeling this structure necessitates a unique blend of tools initially developed for small molecules (e.g., docking) and biologics (e.g., protein-protein interaction modeling). Additionally, degrader molecules, particularly heterobifunctional degraders, are generally larger than conventional small molecule drugs, leading to challenges in determining drug-like properties like solubility and permeability. Furthermore, the catalytic nature of TPD makes occupancy-based modeling insufficient. TPD consists of multiple interconnected yet distinct steps, such as POI binding, E3 ligase binding, ternary structure interactions, ubiquitination, and degradation, along with traditional small molecule properties. A comprehensive set of tools is needed to address the dynamic nature of the induced proximity ternary complex and its implications for ubiquitination. In this Perspective, we discuss the current state of computational tools for TPD. We start by describing the series of steps involved in the degradation process and the experimental methods used to characterize them. Then, we delve into a detailed analysis of the computational tools employed in TPD. We also present an integrative approach that has proven successful for degrader design and its impact on project decisions. Finally, we examine the future prospects of computational methods in TPD and the areas with the greatest potential for impact.

Prediction of toluene/water partition coefficients in the SAMPL9 blind challenge: assessment of machine learning and IEF-PCM/MST continuum solvation models

In recent years the use of partition systems other than the widely used biphasic n-octanol/water has received increased attention to gain insight into the molecular features that dictate the lipophilicity of compounds. Thus, the difference between n-octanol/water and toluene/water partition coefficients has proven to be a valuable descriptor to study the propensity of molecules to form intramolecular hydrogen bonds and exhibit chameleon-like properties that modulate solubility and permeability. In this context, this study reports the experimental toluene/water partition coefficients (log Ptol/w) for a series of 16 drugs that were selected as an external test set in the framework of the Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) blind challenge. This external set has been used by the computational community to calibrate their methods in the current edition (SAMPL9) of this contest. Furthermore, the study also investigates the performance of two computational strategies for the prediction of log Ptol/w. The first relies on the development of two machine learning (ML) models, which are built up by combining the selection of 11 molecular descriptors in conjunction with either the multiple linear regression (MLR) or the random forest regression (RFR) model to target a dataset of 252 experimental log Ptol/w values. The second consists of the parametrization of the IEF-PCM/MST continuum solvation model from B3LYP/6-31G(d) calculations to predict the solvation free energies of 163 compounds in toluene and benzene. The performance of the ML and IEF-PCM/MST models has been calibrated against external test sets, including the compounds that define the SAMPL9 log Ptol/w challenge. The results are used to discuss the merits and weaknesses of the two computational approaches.

A beginner's guide to current synthetic linker strategies towards VHL-recruiting PROTACs

Over the last two decades, proteolysis targeting chimeras (PROTACs) have been revolutionary in drug development rendering targeted protein degradation (TPD) as an emerging therapeutic modality. These heterobifunctional molecules are comprised of three units: a ligand for the protein of interest (POI), a ligand for an E3 ubiquitin ligase, and a linker that tethers the two motifs together. Von Hippel-Lindau (VHL) is one of the most widely employed E3 ligases in PROTACs development due to its prevalent expression across tissue types and well-characterised ligands. Linker composition and length has proven to play an important role in determining the physicochemical properties and spatial orientation of the POI-PROTAC-E3 ternary complex, thus influencing the bioactivity of degraders. Numerous articles and reports have been published showcasing the medicinal chemistry aspects of the linker design, but few have focused on the chemistry around tethering linkers to E3 ligase ligands. In this review, we focus on the current synthetic linker strategies employed in the assembly of VHL-recruiting PROTACs. We aim to cover a range of fundamental chemistries used to incorporate linkers of varying length, composition and functionality.

Trends in Molecular Properties, Bioavailability, and Permeability across the Bayer Compound Collection

For oral drugs, medicinal chemists aim to design compounds with high oral bioavailability, of which permeability is a key determinant. Taking advantage of >2000 compounds tested in rat bioavailability studies and >20,000 compounds tested in Caco2 assays at Bayer, we have examined the molecular properties governing bioavailability and permeability. In addition to classical parameters such as logD and molecular weight, we also investigated the relationship between calculated pK_a and permeability. We find that neutral compounds retain permeability up to a molecular weight limit of 700, while stronger acids and bases are restricted to weights of 400-500. We also investigate trends for common properties such as hydrogen bond donors and acceptors, polar surface area, aromatic ring count, and rotatable bonds, including compounds which exceed Lipinski's rule of five (Ro5). These property-structure relationships are combined to provide design guidelines for bioavailable drugs in both traditional and "beyond rule of 5" (bRo5) chemical space.

PROTAC degraders as chemical probes for studying target biology and target validation

Small molecule degraders such as PROTACs (PROteolysis TArgeting Chimeras) have emerged as new promising pharmacological modalities and the first PROTAC drug candidates are now studied clinically. The catalytic properties of PROTACs, acting as chemical degraders of a protein of interest (POI), represent an attractive new strategy for drug development. The development and characterization of PROTACs requires an array of additional assay systems that track the degradation pathway leading ultimately to degradation of the POI, identifying critical steps for PROTAC optimization. In addition to their exciting translational potential, PROTACs represent versatile chemical tools that considerably expanded our chemical biology toolbox and significantly enlarged the proteome that can be modulated by small molecules. Similar to conventional chemical probes, PROTACs used as chemical probes in target validation require comprehensive characterization. As a consequence, PROTAC-specific quality criteria should be defined by the chemical biology community. These criteria need to comprise additional or alternative parameters compared to those for conventional occupancy-driven chemical probes, such as the maximum level of target degradation (D_max), confirmation of a proteasome dependent degradation mechanism and, importantly, also kinetic parameters of POI degradation. The kinetic aspects are particularly relevant for PROTACs that harbor covalent binding moieties. Here, we review recent progress in the development of assay systems for PROTAC characterization and suggest a set of criteria for PROTACs as high quality chemical probes.

Structural Feature Analyzation Strategies toward Discovery of Orally Bioavailable PROTACs of Bruton's Tyrosine Kinase for the Treatment of Lymphoma

Bruton's tyrosine kinase proteolysis-targeting chimeras (BTK-PROTACs) have emerged as a promising approach to address the limitations of BTK inhibitors. However, conducting the rational discovery of orally bioavailable BTK-PROTACs presents significant challenges. In this study, dimensionality reduction analysis and model molecule validation were utilized to identify some key structural features for improving the oral absorption of BTK-PROTACs. The results were applied to optimize the newly discovered BTK-PROTACs B1 and B2. Compound C13 was discovered with improved oral bioavailability, high BTK degradation activity, and selectivity. It exhibited inhibitory effects against different hematologic cancer cells and attenuated the BTK-related signaling pathway. The oral administration of C13 effectively reduced BTK protein levels and suppressed tumor growth. This study led to the discovery of a new orally bioavailable BTK-PROTAC for the treatment of lymphoma, and we hope that the strategy will find wide utility.