Proof-of-Concept in Developing a 45% Drug Loaded Amorphous Nanoparticle Formulation

Amorphous solid dispersion (ASD) is an enabling approach utilized to deliver poorly soluble compounds. ASDs can spontaneously generate drug-rich amorphous nanoparticles upon dissolution, which can act as a reservoir for maintaining supersaturation during oral absorption. But, conventional ASDs are often limited in drug loadings to < 20 %. For indications where the dose is high, this can translate into a significant pill burden. The aim of this research was to develop a high drug loading (DL) amorphous nanoparticle (ANP) formulation that can release the drug-rich nanoparticles into solution upon contact with aqueous environment. Nanoparticles were directly engineered using solvent/anti-solvent precipitation. The obtained nanoparticle suspension was then concentrated followed by solidification to a re-dispersible amorphous dosage form using spray drying or lyophilization. The impact of process variables was studied using dynamic light scattering (DLS), scanning electron microscopy (SEM), high performance liquid chromatography (HPLC), nuclear magnetic resonance (NMR) and differential scanning calorimetry (DSC). It was observed that spray drying led to a non-re-dispersible formulation. Sucrose and trehalose containing lyocakes resulted in re-dispersible formulations. The trehalose containing lyocakes, in a dog study, gave comparable performance to the reference tablet in the fasted state but lower area under the curve (AUC) in fed state.

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.

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.

ChemBead Enabled High-Throughput Cross-Electrophile Coupling Reveals a New Complementary Ligand

High-throughput experimentation (HTE) methods are central to modern medicinal chemistry. While many HTE approaches to C-N and Csp2 -Csp2 bonds are available, options for Csp2 -Csp3 bonds are limited. We report here how the adaptation of nickel-catalyzed cross-electrophile coupling of aryl bromides with alkyl halides to HTE is enabled by AbbVie ChemBeads technology. By using this approach, we were able to quickly map out the reactivity space at a global level with a challenging array of 3×222 micromolar reactions. The observed hit rate (56 %) is competitive with other often-used HTE reactions and the results are scalable. A key to this level of success was the finding that bipyridine 6-carboxamidine (BpyCam), a ligand that had not previously been shown to be optimal in any reaction, is as general as the best-known ligands with complementary reactivity. Such "cryptic" catalysts may be common and modern HTE methods should facilitate the process of finding these catalysts.

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.

Exploring pH Dependent Host/Guest Binding Affinities

When the electrostatic environment surrounding binding partners changes between unbound and bound states, the net uptake or release of a proton is possible by either binding partner. This process is pH-dependent in that the free energy required to uptake or release the proton varies with pH. This pH-dependence is typically not considered in conventional free energy methods where the use of fixed protonation states is the norm. In the present paper, we apply a simple two-step approach to calculate the pH-dependent binding free energy of a model cucubit[7]uril host/guest system. By use of λ-dynamics with an enhanced sampling protocol, adaptive landscape flattening, pK_a shifts and reference binding free energies upon complexation were determined. This information enables the construction of pH-dependent binding profiles that accurately capture the pK_a shifts and reproduce binding free energies at the different pH conditions that were observed experimentally. Our calculations illustrate a general framework for computing pH-dependent binding free energies but also point to some issues in modeling the molecular charge distributions within this series of molecules with CGenFF. However, by introducing some minor charge modifications to the CGenFF force field, we saw significant improvement in accuracy of the calculated pK_a shifts.

In Silico Prediction of Intestinal Permeability by Hierarchical Support Vector Regression

The vast majority of marketed drugs are orally administrated. As such, drug absorption is one of the important drug metabolism and pharmacokinetics parameters that should be assessed in the process of drug discovery and development. A nonlinear quantitative structure-activity relationship (QSAR) model was constructed in this investigation using the novel machine learning-based hierarchical support vector regression (HSVR) scheme to render the extremely complicated relationships between descriptors and intestinal permeability that can take place through various passive diffusion and carrier-mediated active transport routes. The predictions by HSVR were found to be in good agreement with the observed values for the molecules in the training set (n = 53, r² = 0.93, q CV 2 = 0.84, RMSE = 0.17, s = 0.08), test set (n = 13, q² = 0.75-0.89, RMSE = 0.26, s = 0.14), and even outlier set (n = 8, q² = 0.78-0.92, RMSE = 0.19, s = 0.09). The built HSVR model consistently met the most stringent criteria when subjected to various statistical assessments. A mock test also assured the predictivity of HSVR. Consequently, this HSVR model can be adopted to facilitate drug discovery and development.

Machine learning meets pK a

We present a small molecule pK a prediction tool entirely written in Python. It predicts the macroscopic pK a value and is trained on a literature compilation of monoprotic compounds. Different machine learning models were tested and random forest performed best given a five-fold cross-validation (mean absolute error=0.682, root mean squared error=1.032, correlation coefficient r 2 =0.82). We test our model on two external validation sets, where our model performs comparable to Marvin and is better than a recently published open source model. Our Python tool and all data is freely available at https://github.com/czodrowskilab/Machine-learning-meets-pKa.

Machine learning meets pK a

We present a small molecule pK a prediction tool entirely written in Python. It predicts the macroscopic pK a value and is trained on a literature compilation of monoprotic compounds. Different machine learning models were tested and random forest performed best given a five-fold cross-validation (mean absolute error=0.682, root mean squared error=1.032, correlation coefficient r 2 =0.82). We test our model on two external validation sets, where our model performs comparable to Marvin and is better than a recently published open source model. Our Python tool and all data is freely available at https://github.com/czodrowskilab/Machine-learning-meets-pKa.

Intermolecular alkene difunctionalizations for the synthesis of saturated heterocycles

Saturated heterocycles are important structural motifs in a range of pharmaceuticals and agrochemicals. As a result of their importance, syntheses of these molecules have been extensively investigated. Despite the progress in this area, the most adopted strategies are still often characterized with inefficiency or relying on functionalizations with specialized precursors and pre-existing cores. This review highlights a dynamic synthetic strategy for the direct synthesis of saturated heterocycles from intermolecular alkene difunctionalizations. These coupling processes are highly modular, and therefore, offer perhaps the most convenient means to prepare diverse heterocyclic structures in compound libraries for bioactivity evoluations.

Impact of Physicochemical Properties on Dose and Hepatotoxicity of Oral Drugs

A database containing maximum daily doses of 1841 marketed oral drugs was used to examine the influence of physicochemical properties on dose and hepatotoxicity (drug induced liver injury, DILI). Drugs in the highest ∼20% dose range had significantly reduced mean lipophilicity and molecular weight, increased fractional surface area, increased % of acids, and decreased % of bases versus drugs in the lower ∼60% dose range. Drugs in the ∼20-40% dose range had intermediate mean properties, similar to the mean values for the full drug set. Drugs that are both large and highly lipophilic almost invariably do not have doses in the upper ∼20% range. The results show that oral druglike physicochemical properties are different according to these dose ranges, and this is consistent with maintenance of acceptable safety profiles as efficacious exposure increases. Verified DILI annotations from a compilation of >1000 approved drugs (Chen, M.; et al. Drug Discov. Today, 2016, 21, 648 ) were used. The drugs classified as "No DILI" ( n = 163) had significantly lower dose and lipophilicity, and higher Fsp3 (fraction of carbon atoms that are sp³ hybridized) versus the "Most DILI" ( n = 163) drugs. The percentages of acids were reduced and bases increased in the "No DILI" versus the "Most DILI" groups. Drugs classified as "Less DILI" or "Ambiguous DILI" had intermediate mean values of dose, lipophilicity, Fsp3, and % acids and bases. The impact of lipophilicity and Fsp3 on DILI increases in the upper 20% versus the lower 80% dose range, and a simple decision tree model predicted "No DILI" versus "Most DILI" outcomes with 82% accuracy. The model correctly classified 19 of 22 drugs (86%) that failed in development due to human hepatotoxicity. Because many oral drugs lacking DILI annotations are predicted to be "Most DILI", the model is best used preclinically in conjunction with experimental DILI mitigation.

Enantioselective Synthesis of α-(Hetero)aryl Piperidines through Asymmetric Hydrogenation of Pyridinium Salts and Its Mechanistic Insights

Enantioselective synthesis of α-aryl and α-heteroaryl piperidines is reported. The key step is an iridium-catalyzed asymmetric hydrogenation of substituted N-benzylpyridinium salts. High levels of enantioselectivity up to 99.3:0.7 er were obtained for a range of α-heteroaryl piperidines. DFT calculations support an outersphere dissociative mechanism for the pyridinium reduction. Notably, initial protonation of the final enamine intermediate determines the stereochemical outcome of the transformation rather than hydride reduction of the resultant iminium intermediate.

Ligand efficiency metrics in drug discovery: the pros and cons from a practical perspective

INTRODUCTION

Ligand efficiency metrics are almost universally accepted as a valuable indicator of compound quality and an aid to reduce attrition. Areas covered: In this review, the authors describe ligand efficiency metrics giving a balanced overview on their merits and points of weakness in order to enable the readers to gain an informed opinion. Relevant theoretical breakthroughs and drug-like properties are also illustrated. Several recent exemplary case studies are discussed in order to illustrate the main fields of application of ligand efficiency metrics. Expert opinion: As a medicinal chemist guide, ligand efficiency metrics perform in a context- and chemotype-dependent manner; thus, they should not be used as a magic box. Since the 'big bang' of efficiency metrics occurred more or less ten years ago and the average time to develop a new drug is over the same period, the next few years will give a clearer outlook on the increased rate of success, if any, gained by means of these new intriguing tools.

Enantioselective Iridium-Catalyzed Allylic Cyclizations

A method for the enantioselective synthesis of carbo- and heterocyclic ring systems enabled through the combination of Lewis acid activation and iridium-catalyzed allylic substitution is described. The reaction proceeds with branched, allylic alcohols and carbon nucleophiles as well as heteronucleophiles to give a diverse set of ring systems in good yields and with high enantioselectivities. The utility of the method is highlighted by the asymmetric syntheses of erythrococcamides A and B.

Amine promiscuity and toxicology analysis

Drug discovery programs often face challenges to obtain sufficient duration of action of the drug (i.e. seek longer half-lives). If the pharmacodynamic response is driven by free plasma concentration of the drug then extending the plasma drug concentration is a valid approach. Half-life is dependent on the volume of distribution, which in turn can be dependent upon the ionization state of the molecule. Basic compounds tend to have a higher volume of distribution leading to longer half-lives. However, it has been shown that bases may also have higher promiscuity. In this work, we describe an analysis of in vitro pharmacological profiling and toxicology data investigating the role of primary, secondary, and tertiary amines in imparting promiscuity and thus off-target toxicity. Primary amines are found to be less promiscuous in in vitro assays and have improved profiles in in vivo toxicology studies compared to secondary and tertiary amines.

Molecular inflation, attrition and the rule of five

Physicochemical properties underlie all aspects of drug action and are critical for solubility, permeability and successful formulation. Specific physicochemical properties shown to be relevant to oral drugs are size, lipophilicity, ionisation, hydrogen bonding, polarity, aromaticity and shape. The rule of 5 (Ro5) and subsequent studies have raised awareness of the importance of compound quality amongst bioactive molecules. Lipophilicity, probably the most important physical property of oral drugs, has on average changed little over time in oral drugs, until increases in drugs published after 1990. In contrast other molecular properties such as average size have increased significantly. Factors influencing property inflation include the targets pursued, where antivirals frequently violate the Ro5, risk/benefit considerations, and variable drug discovery practices. The compounds published in patents from the pharmaceutical industry are on average larger, more lipophilic and less complex than marketed oral drugs. The variation between individual companies' patented compounds is due to different practices and not to the targets pursued. Overall, there is demonstrable physical property attrition in moving from patents to candidate drugs to marketed drugs. The pharmaceutical industry's recent poor productivity has been due, in part, to progression of molecules that are unable to unambiguously test clinical efficacy, and attrition can therefore be improved by ensuring candidate drug quality is 'fit for purpose.' The combined ligand efficiency (LE) and lipophilic ligand efficiency (LLE) values of many marketed drugs are optimised relative to other molecules acting at the same target. Application of LLE in optimisation can help identify improved leads, even with challenging targets that seem to require lipophilic ligands. Because of their targets, some projects may need to pursue 'beyond Ro5' physicochemical space; such projects will require non-standard lead generation and optimisation and should not dominate in a well-balanced portfolio. Compound quality is controllable by lead selection and optimisation and should not be a cause of clinical failure.

Profiling the estimated plasma concentrations of 215 marketed oral drugs

The human pharmacokinetic parameters of 215 marketed oral drugs have been collated and their estimated plasma concentrations (following repeat dosing) profiled against time using a one-compartment model.

Gold-catalyzed cyclization and cycloisomerization of yne-tethered ynamide: the significance of a masked enol-equivalent of an amide

This perspective briefly describes the conceptual manifestation of a Brønsted acid promoted Au-catalyzed cyclization of yne-tethered ynamides for the construction of novel N-heterocycles. A hetero-atom assisted intramolecular 6-endo-dig cyclization of a transient ketene N,O-acetal (a masked enol-ether of an amide), generated from an ambivalent ynamide through the attack of p-TsOH, with a Au-activated yne-motif creates dihydropyridinones and benzo[f]dihydroisoquinolones. The Au(I)-catalyzed cycloisomerization of an alkyne-tethered ketene N,N-acetal to manufacture unusual cyclobutene-fused azepine scaffolds is also highlighted.

Syntheses and in Vitro Antiplasmodial Activity of Aminoalkylated Chalcones and Analogues

A series of readily synthesized and inexpensive aminoalkylated chalcones and diarylpropane analogues (1-55) were synthesized and tested against chloroquinone-sensitive (D10 and NF54) and -resistant (Dd2 and K1) strains of Plasmodium falciparum. Hydrogenation of the enone to a diarylpropane moiety increased antiplasmodial bioactivity significantly. The influence of the structure of the amine moiety, A-ring substituents, propyl vs ethyl linker, and chloride salt formation on further enhancing antiplasmodial activity was investigated. Several compounds have IC₅₀ values similar to or better than chloroquine (CQ). The most active compound (26) had an IC₅₀ value of 0.01 μM. No signs of resistance were detected, as can be expected from compounds with structures unrelated to CQ and other currently used antimalarial drugs. Toxicity tests (in vitro CHO cell assay) gave high SI indices.

Catalytic Synthesis of N-Unprotected Piperazines, Morpholines, and Thiomorpholines from Aldehydes and SnAP Reagents

Commercially available SnAP (stannyl amine protocol) reagents allow the transformation of aldehydes and ketones into a variety of N-unprotected heterocycles. By identifying new ligands and reaction conditions, a robust catalytic variant that expands the substrate scope to previously inaccessible heteroaromatic substrates and new substitution patterns was realized. It also establishes the basis for a catalytic enantioselective process through the use of chiral ligands.

Molecular Property Design: Does Everyone Get It?

The principles of molecular property optimization in drug design have been understood for decades, yet much drug discovery activity today is conducted at the periphery of historical druglike property space. Lead optimization trajectories aimed at reducing physicochemical risk, assisted by ligand efficiency metrics, could help to reduce clinical attrition rates.

Analysis of Physicochemical Properties for Drugs of Natural Origin

The impact of time, therapy area, and route of administration on 13 physicochemical properties calculated for 664 drugs developed from a natural prototype was investigated. The mean values for the majority of properties sampled over five periods from pre-1900 to 2013 were found to change in a statistically significant manner. In contrast, lipophilicity and aromatic ring count remained relatively constant, suggesting that these parameters are the most important for successful prosecution of a natural product drug discovery program if the route of administration is not focused exclusively on oral availability. An examination by therapy area revealed that anti-infective agents had the most differences in physicochemical property profiles compared with other areas, particularly with respect to lipophilicity. However, when this group was removed, the variation between the mean values for lipophilicity and aromatic ring count across the remaining therapy areas was again found not to change in a meaningful manner, further highlighting the importance of these two parameters. The vast majority of drugs with a natural progenitor were formulated for either oral and/or injectable administration. Injectables were, on average, larger and more polar than drugs developed for oral, topical, and inhalation routes.

Discovery of a potent, orally available dual CysLT₁ and CysLT₂ antagonist with dicarboxylic acid

A potent, orally available dual CysLT₁ and CysLT₂ receptor antagonist with a dicarboxylic acid is described. 4-(3-(Carboxymethyl)-4-{(E)-2-[4-(4-phenoxybutoxy)phenyl]vinyl}-1H-indol-1-yl)butanoic acid (15: ONO-4310321, IC₅₀: CysLT₁=13nM, CysLT₂=25 nM) showed excellent pharmacokinetic profiles (%Frat=100) compared with our previously reported compound 1 (%Frat=1.5). In addition, we describe a new rule for dicarboxylic acid derivatives to show good oral bioavailability (%Frat⩾40) in rats (HBDs: ⩽2, ClogP: >6.5 and TPSA: <100). Especially, reduction of only one hydrogen-bond donor (HBDs) showed dramatically improved oral bioavailability. This small change of HBDs in dicarboxylic acid derivatives is generally a very effective modification.

Protocols utilizing constant pH molecular dynamics to compute pH-dependent binding free energies

In protein–ligand binding, the electrostatic environments of the two binding partners may vary significantly in bound and unbound states, which may lead to protonation changes upon binding. In cases where ligand binding results in a net uptake or release of protons, the free energy of binding is pH-dependent. Nevertheless, conventional free energy calculations and molecular docking protocols typically do not rigorously account for changes in protonation that may occur upon ligand binding. To address these shortcomings, we present a simple methodology based on Wyman’s binding polynomial formalism to account for the pH dependence of binding free energies and demonstrate its use on cucurbit[7]uril (CB[7]) host–guest systems. Using constant pH molecular dynamics and a reference binding free energy that is taken either from experiment or from thermodynamic integration computations, the pH-dependent binding free energy is determined. This computational protocol accurately captures the large pK_a shifts observed experimentally upon CB[7]:guest association and reproduces experimental binding free energies at different levels of pH. We show that incorrect assignment of fixed protonation states in free energy computations can give errors of >2 kcal/mol in these host–guest systems. Use of the methods presented here avoids such errors, thus suggesting their utility in computing proton-linked binding free energies for protein–ligand complexes.

Synthesis of diverse nitrogen-enriched heterocyclic scaffolds using a suite of tunable one-pot multicomponent reactions

Five elegant and switchable three-component reactions which enable access to a new series of nitrogen-containing heterocycles are reported. A novel one-step addition of an isocyanide to a hydrazine derived Schiff base affords unique six-membered pyridotriazine scaffolds (A and E). With slight modification of reaction conditions and replacement of the nucleophilic isocyanide moiety with different electrophiles (i.e., isocyanates, isothiocyanates, cyclic anhydrides, and acyl chlorides) five-membered triazolopyridine scaffolds (B, D, F, G) are generated in a single step. Furthermore, the use of phenyl hydrazine enables access to dihydroindazole-carboxamides, devoid of a bridge-head nitrogen (C). All protocols are robust and tolerate a diverse collection of reactants, and as such, it is expected that the new scaffolds and associated chemistry will garner high interest from medicinal chemists involved in either file enhancement or specific target-related drug discovery campaigns.

The Influence of Bioisosteres in Drug Design: Tactical Applications to Address Developability Problems

The application of bioisosteres in drug discovery is a well-established design concept that has demonstrated utility as an approach to solving a range of problems that affect candidate optimization, progression, and durability. In this chapter, the application of isosteric substitution is explored in a fashion that focuses on the development of practical solutions to problems that are encountered in typical optimization campaigns. The role of bioisosteres to affect intrinsic potency and selectivity, influence conformation, solve problems associated with drug developability, including P-glycoprotein recognition, modulating basicity, solubility, and lipophilicity, and to address issues associated with metabolism and toxicity is used as the underlying theme to capture a spectrum of creative applications of structural emulation in the design of drug candidates.

Benzonitrile Oxide Cycloadditions with Exocyclic Methylene Benzothiazepine Dioxides

N-substituted 5-methylene-2,3,4,5-tetrahydrobenzo[f][1,2]thiazepine 1,1-dioxides underwent 1,3-dipolar cycloaddition with benzonitrile oxide, generated in situ, to give isoxazoline spiro adducts. The cycloadditions were completely regioselective to give the hitherto unreported 3,4-dihydro-2H,4′H-spiro[benzo[f][1,2]thiazepine-5,5′-isoxazole] 1,1-dioxide cycloadduct. Where the N-substituent on the sulfonamide cycloaddition precursor was a 2-substituted arene, the resulting atropisomerism along the N-aryl bond led to facial selectivity in the cycloaddition reaction, with greater than 90 % diastereoselectivity.

On the Relationship between Molecular Hit Rates in High-Throughput Screening and Molecular Descriptors

High-throughput screening (HTS) is widely used in the pharmaceutical industry to identify novel chemical starting points for drug discovery projects. The current study focuses on the relationship between molecular hit rate in recent in-house HTS and four common molecular descriptors: lipophilicity (ClogP), size (heavy atom count, HEV), fraction of sp3-hybridized carbons (Fsp3), and fraction of molecular framework ( fMF). The molecular hit rate is defined as the fraction of times the molecule has been assigned as active in the HTS campaigns where it has been screened. Beta-binomial statistical models were built to model the molecular hit rate as a function of these descriptors. The advantage of the beta-binomial statistical models is that the correlation between the descriptors is taken into account. Higher degree polynomial terms of the descriptors were also added into the beta-binomial statistic model to improve the model quality. The relative influence of different molecular descriptors on molecular hit rate has been estimated, taking into account that the descriptors are correlated to each other through applying beta-binomial statistical modeling. The results show that ClogP has the largest influence on the molecular hit rate, followed by Fsp3 and HEV. fMF has only a minor influence besides its correlation with the other molecular descriptors.