Virtual Screening Strategy to Identify Retinoic Acid-Related Orphan Receptor γt Modulators.

Molecular docking is a key method used in virtual screening (VS) campaigns to identify small-molecule ligands for drug discovery targets. While docking provides a tangible way to understand and predict the protein-ligand complex formation, the docking algorithms are often unable to separate active ligands from inactive molecules in practical VS usage. Here, a novel docking and shape-focused pharmacophore VS protocol is demonstrated for facilitating effective hit discovery using retinoic acid receptor-related orphan receptor gamma t (RORγt) as a case study. RORγt is a prospective target for treating inflammatory diseases such as psoriasis and multiple sclerosis. First, a commercial molecular database was flexibly docked. Second, the alternative docking poses were rescored against the shape/electrostatic potential of negative image-based (NIB) models that mirror the target's binding cavity. The compositions of the NIB models were optimized via iterative trimming and benchmarking using a greedy search-driven algorithm or brute force NIB optimization. Third, a pharmacophore point-based filtering was performed to focus the hit identification on the known RORγt activity hotspots. Fourth, free energy binding affinity evaluation was performed on the remaining molecules. Finally, twenty-eight compounds were selected for in vitro testing and eight compounds were determined to be low µM range RORγt inhibitors, thereby showing that the introduced VS protocol generated an effective hit rate of ~29%.

Sdfconf: A Novel, Flexible, and Robust Molecular Data Management Tool.

Projects in chemo- and bioinformatics often consist of scattered data in various types and are difficult to access in a meaningful way for efficient data analysis. Data is usually too diverse to be even manipulated effectively. Sdfconf is data manipulation and analysis software to address this problem in a logical and robust manner. Other software commonly used for such tasks are either not designed with molecular and/or conformational data in mind or provide only a narrow set of tasks to be accomplished. Furthermore, many tools are only available within commercial software packages. Sdfconf is a flexible, robust, and free-of-charge tool for linking data from various sources for meaningful and efficient manipulation and analysis of molecule data sets. Sdfconf packages molecular structures and metadata into a complete ensemble, from which one can access both the whole data set and individual molecules and/or conformations. In this software note, we offer some practical examples of the utilization of sdfconf.

Optimization of Cavity-Based Negative Images to Boost Docking Enrichment in Virtual Screening.

Molecular docking is a key in silico method used routinely in modern drug discovery projects. Although docking provides high-quality ligand binding predictions, it regularly fails to separate the active compounds from the inactive ones. In negative image-based rescoring (R-NiB), the shape/electrostatic potential (ESP) of docking poses is compared to the negative image of the protein's ligand binding cavity. While R-NiB often improves the docking yield considerably, the cavity-based models do not reach their full potential without expert editing. Accordingly, a greedy search-driven methodology, brute force negative image-based optimization (BR-NiB), is presented for optimizing the models via iterative editing and benchmarking. Thorough and unbiased training, testing and stringent validation with a multitude of drug targets, and alternative docking software show that BR-NiB ensures excellent docking efficacy. BR-NiB can be considered as a new type of shape-focused pharmacophore modeling, where the optimized models contain only the most vital cavity information needed for effectively filtering docked actives from the inactive or decoy compounds. Finally, the BR-NiB code for performing the automated optimization is provided free-of-charge under MIT license via GitHub (https://github.com/jvlehtonen/brutenib) for boosting the success rates of docking-based virtual screening campaigns.

Rational design, optimization, and biological evaluation of novel α-Phosphonopropionic acids as covalent inhibitors of Rab geranylgeranyl transferase.

Rab geranylgeranyltransferase (GGTase-II, RGGT) catalyses the post-translational modification of eukaryotic Rab GTPases, proteins implicated in several pathologies, including cancer, diabetes, neurodegenerative, and infectious diseases. Thus, RGGT inhibitors are believed to be a potential platform for the development of drugs and tools for studying processes related to the abnormal activity of Rab GTPases. Here, a series of new α-phosphonocarboxylates have been prepared in the first attempt of rational design of covalent inhibitors of RGGT derived from non-covalent inhibitors. These compounds were equipped with electrophilic groups capable of binding cysteines, which are present in the catalytic cavity of RGGT. A few of these analogues have shown micromolar activity against RGGT, which correlated with their ability to inhibit the proliferation of the HeLa cancer cell line. The proposed mechanism of this inhibitory activity was rationalised by molecular docking and mass spectrometric measurements, supported by stability and reactivity studies.

Ligand-Enhanced Negative Images Optimized for Docking Rescoring.

Despite the pivotal role of molecular docking in modern drug discovery, the default docking scoring functions often fail to recognize active ligands in virtual screening campaigns. Negative image-based rescoring improves docking enrichment by comparing the shape/electrostatic potential (ESP) of the flexible docking poses against the target protein's inverted cavity volume. By optimizing these negative image-based (NIB) models using a greedy search, the docking rescoring yield can be improved massively and consistently. Here, a fundamental modification is implemented to this shape-focused pharmacophore modelling approach-actual ligand 3D coordinates are incorporated into the NIB models for the optimization. This hybrid approach, labelled as ligand-enhanced brute-force negative image-based optimization (LBR-NiB), takes the best from both worlds, i.e., the all-roundedness of the NIB models and the difficult to emulate atomic arrangements of actual protein-bound small-molecule ligands. Thorough benchmarking, focused on proinflammatory targets, shows that the LBR-NiB routinely improves the docking enrichment over prior iterations of the R-NiB methodology. This boost can be massive, if the added ligand information provides truly essential binding information that was lacking or completely missing from the cavity-based NIB model. On a practical level, the results indicate that the LBR-NiB typically works well when the added ligand 3D data originates from a high-quality source, such as X-ray crystallography, and, yet, the NIB model compositions can also sometimes be improved by fusing into them, for example, with flexibly docked solvent molecules. In short, the study demonstrates that the protein-bound ligands can be used to improve the shape/ESP features of the negative images for effective docking rescoring use in virtual screening.

Molecular docking and oxidation kinetics of 3-phenyl coumarin derivatives by human CYP2A13.

CYP2A13 enzyme is expressed in human extrahepatic tissues, while CYP2A6 is a hepatic enzyme. Reactions catalysed by CYP2A13 activate tobacco-specific nitrosamines and some other toxic xenobiotics in lungs.To compare oxidation characteristics and substrate-enzyme active site interactions in CYP2A13 vs CYP2A6, we evaluated CYP2A13 mediated oxidation characteristics of 23 coumarin derivatives and modelled their interactions at the enzyme active site.CYP2A13 did not oxidise six coumarin derivatives to corresponding fluorescent 7-hydroxycoumarins. The Km-values of the other coumarins varied 0.85-97 µM, Vmax-values of the oxidation reaction varied 0.25-60 min-1, and intrinsic clearance varied 26-6190 kL/min*mol CYP2A13). Km of 6-chloro-3-(3-hydroxyphenyl)-coumarin was 0.85 (0.55-1.15 95% confidence limit) µM and Vmax 0.25 (0.23-0.26) min-1, whereas Km of 6-hydroxy-3-(3-hydroxyphenyl)-coumarin was 10.9 (9.9-11.8) µM and Vmax 60 (58-63) min-1. Docking analyses demonstrated that 6-chloro or 6-methoxy and 3-(3-hydroxyphenyl) or 3-(4-trifluoromethylphenyl) substituents of coumarin increased affinity to CYP2A13, whereas 3-triazole or 3-(3-acetate phenyl) or 3-(4-acetate phenyl) substituents decreased it.The active site of CYP2A13 accepts more diversified types of coumarin substrates than the hepatic CYP2A6 enzyme. New sensitive and convenient profluorescent CYP2A13 substrates were identified, such as 6-chloro-3-(3-hydroxyphenyl)-coumarin having high affinity and 6-hydroxy-3-(3-hydroxyphenyl)-coumarin with high intrinsic clearance.

Coumarins as Tool Compounds to Aid the Discovery of Selective Function Modulators of Steroid Hormone Binding Proteins.

Steroid hormones play an essential role in a wide variety of actions in the body, such as in metabolism, inflammation, initiating and maintaining sexual differentiation and reproduction, immune functions, and stress response. Androgen, aromatase, and sulfatase pathway enzymes and nuclear receptors are responsible for steroid biosynthesis and sensing steroid hormones. Changes in steroid homeostasis are associated with many endocrine diseases. Thus, the discovery and development of novel drug candidates require a detailed understanding of the small molecule structure-activity relationship with enzymes and receptors participating in steroid hormone synthesis, signaling, and metabolism. Here, we show that simple coumarin derivatives can be employed to build cost-efficiently a set of molecules that derive essential features that enable easy discovery of selective and high-affinity molecules to target proteins. In addition, these compounds are also potent tool molecules to study the metabolism of any small molecule.

Getting Docking into Shape Using Negative Image-Based Rescoring.

The failure of default scoring functions to ensure virtual screening enrichment is a persistent problem for the molecular docking algorithms used in structure-based drug discovery. To remedy this problem, elaborate rescoring and postprocessing schemes have been developed with a varying degree of success, specificity, and cost. The negative image-based rescoring (R-NiB) has been shown to improve the flexible docking performance markedly with a variety of drug targets. The yield improvement is achieved by comparing the alternative docking poses against the negative image of the target protein's ligand-binding cavity. In other words, the shape and electrostatics of the binding pocket is directly used in the similarity comparison to rank the explicit docking poses. Here, the PANTHER/ShaEP-based R-NiB methodology is tested with six popular docking softwares, including GLIDE, PLANTS, GOLD, DOCK, AUTODOCK, and AUTODOCK VINA, using five validated benchmark sets. Overall, the results indicate that R-NiB outperforms the default docking scoring consistently and inexpensively, demonstrating that the methodology is ready for wide-scale virtual screening usage.

Development of new Coumarin-based profluorescent substrates for human cytochrome P450 enzymes.

Cytochrome P450 (CYP) enzymes constitute an essential xenobiotic metabolizing system that regulates the elimination of lipophilic compounds from the body. Convenient and affordable assays for CYP enzymes are important for assessing these metabolic pathways. In this study, 10 novel profluorescent coumarin derivatives with various substitutions at carbons 3, 6 and 7 were developed. Molecular modeling indicated that 3-phenylcoumarin offers an excellent scaffold for the development of selective substrate compounds for various human CYP forms, as they could be metabolized to fluorescent 7-hydroxycoumarin derivatives. Oxidation of profluorescent coumarin derivatives to fluorescent metabolites by 13 important human liver xenobiotic-metabolizing CYP forms was determined by enzyme kinetic assays. Four of the coumarin derivatives were converted to fluorescent metabolites by CYP1 family enzymes, with 6-methoxy-3-(4-trifluoromethylphenyl)coumarin being oxidized selectively by CYP1A2 in human liver microsomes. Another set of four compounds were metabolized by CYP2A6 and CYP1 enzymes. 7-Methoxy-3-(3-methoxyphenyl)coumarin was oxidized efficiently by CYP2C19 and CYP2D6 in a non-selective fashion. The advantages of the novel substrates were (1) an excellent signal-to-background ratio, (2) selectivity for CYP1 forms, and (3) convenient multiwell plate measurement, allowing for precise determination of potential inhibitors of important human hepatic forms CYP1A2, CYP2C19 and CYP2D6.

A Practical Perspective: The Effect of Ligand Conformers on the Negative Image-Based Screening.

Negative image-based (NIB) screening is a rigid molecular docking methodology that can also be employed in docking rescoring. During the NIB screening, a negative image is generated based on the target protein's ligand-binding cavity by inverting its shape and electrostatics. The resulting NIB model is a drug-like entity or pseudo-ligand that is compared directly against ligand 3D conformers, as is done with a template compound in the ligand-based screening. This cavity-based rigid docking has been demonstrated to work with genuine drug targets in both benchmark testing and drug candidate/lead discovery. Firstly, the study explores in-depth the applicability of different ligand 3D conformer generation software for acquiring the best NIB screening results using cyclooxygenase-2 (COX-2) as the example system. Secondly, the entire NIB workflow from the protein structure preparation, model build-up, and ligand conformer generation to the similarity comparison is performed for COX-2. Accordingly, hands-on instructions are provided on how to employ the NIB methodology from start to finish, both with the rigid docking and docking rescoring using noncommercial software. The practical aspects of the NIB methodology, especially the effect of ligand conformers, are discussed thoroughly, thus, making the methodology accessible for new users.

Molecular Docking-Based Design and Development of a Highly Selective Probe Substrate for UDP-glucuronosyltransferase 1A10.

Intestinal and hepatic glucuronidation by the UDP-glucuronosyltransferases (UGTs) greatly affect the bioavailability of phenolic compounds. UGT1A10 catalyzes glucuronidation reactions in the intestine, but not in the liver. Here, our aim was to develop selective, fluorescent substrates to easily elucidate UGT1A10 function. To this end, homology models were constructed and used to design new substrates, and subsequently, six novel C3-substituted (4-fluorophenyl, 4-hydroxyphenyl, 4-methoxyphenyl, 4-(dimethylamino)phenyl, 4-methylphenyl, or triazole) 7-hydroxycoumarin derivatives were synthesized from inexpensive starting materials. All tested compounds could be glucuronidated to nonfluorescent glucuronides by UGT1A10, four of them highly selectively by this enzyme. A new UGT1A10 mutant, 1A10-H210M, was prepared on the basis of the newly constructed model. Glucuronidation kinetics of the new compounds, in both wild-type and mutant UGT1A10 enzymes, revealed variable effects of the mutation. All six new C3-substituted 7-hydroxycoumarins were glucuronidated faster by human intestine than by liver microsomes, supporting the results obtained with recombinant UGTs. The most selective 4-(dimethylamino)phenyl and triazole C3-substituted 7-hydroxycoumarins could be very useful substrates in studying the function and expression of the human UGT1A10.

Blocking oestradiol synthesis pathways with potent and selective coumarin derivatives.

A comprehensive set of 3-phenylcoumarin analogues with polar substituents was synthesised for blocking oestradiol synthesis by 17-ß-hydroxysteroid dehydrogenase 1 (HSD1) in the latter part of the sulphatase pathway. Five analogues produced ≥62% HSD1 inhibition at 5 µM and, furthermore, three of them produced ≥68% inhibition at 1 µM. A docking-based structure-activity relationship analysis was done to determine the molecular basis of the inhibition and the cross-reactivity of the analogues was tested against oestrogen receptor, aromatase, cytochrome P450 1A2, and monoamine oxidases. Most of the analogues are only modestly active with 17-ß-hydroxysteroid dehydrogenase 2 - a requirement for lowering effective oestradiol levels in vivo. Moreover, the analysis led to the synthesis and discovery of 3-imidazolecoumarin as a potent aromatase inhibitor. In short, coumarin core can be tailored with specific ring and polar moiety substitutions to block either the sulphatase pathway or the aromatase pathway for treating breast cancer and endometriosis.

The Influence of Hydrogen Bonding on Sphingomyelin/Colipid Interactions in Bilayer Membranes.

The phospholipid acyl chain composition and order, the hydrogen bonding, and properties of the phospholipid headgroup all influence cholesterol/phospholipid interactions in hydrated bilayers. In this study, we examined the influence of hydrogen bonding on sphingomyelin (SM) colipid interactions in fluid uni- and multilamellar vesicles. We have compared the properties of oleoyl or palmitoyl SM with comparable dihydro-SMs, because the hydrogen bonding properties of SM and dihydro-SM differ. The association of cholestatrienol, a fluorescent cholesterol analog, with oleoyl sphingomyelin (OSM) was significantly stronger than its association with 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine, in bilayers with equal acyl chain order. The association of cholestatrienol with dihydro-OSM, which lacks a trans double bond in the sphingoid base, was even stronger than the association with OSM, suggesting an important role for hydrogen bonding in stabilizing sterol/SM interactions. Furthermore, with saturated SM in the presence of 15 mol % cholesterol, cholesterol association with fluid dihydro-palmitoyl SM bilayers was stronger than seen with palmitoyl SM under similar conditions. The different hydrogen bonding properties in OSM and dihydro-OSM bilayers also influenced the segregation of palmitoyl ceramide and dipalmitoylglycerol into an ordered phase. The ordered, palmitoyl ceramide-rich phase started to form above 2 mol % in the dihydro-OSM bilayers but only above 6 mol % in the OSM bilayers. The lateral segregation of dipalmitoylglycerol was also much more pronounced in dihydro-OSM bilayers than in OSM bilayers. The results show that hydrogen bonding is important for sterol/SM and ceramide/SM interactions, as well as for the lateral segregation of a diglyceride. A possible molecular explanation for the different hydrogen bonding in SM and dihydro-SM bilayers is presented and discussed.

Inhibitory effects and oxidation of 6-methylcoumarin, 7-methylcoumarin and 7-formylcoumarin via human CYP2A6 and its mouse and pig orthologous enzymes.

1. Information about the metabolism of compounds is essential in drug discovery and development, risk assessment of chemicals and further development of predictive methods. 2. In vitro and in silico methods were applied to evaluate the metabolic and inhibitory properties of 6-methylcoumarin, 7-methylcoumarin and 7-formylcoumarin with human CYP2A6, mouse CYP2A5 and pig CYP2A19. 3. 6-Methylcoumarin was oxidized to fluorescent 7-hydroxy-6-methylcoumarin by CYP2A6 (Km: 0.64-0.91 µM; Vmax: 0.81-0.89 min(-1)) and by CYP2A5 and CYP2A19. The reaction was almost completely inhibited at 10 µM 7-methylcoumarin in liver microsomes of human and mouse, but in pig only 40% inhibition was obtained with the anti-CYP2A5 antibody or with methoxsalen and pilocarpine. 7-Methylcoumarin was a mechanism-based inhibitor for CYP2A6, but not for the mouse and pig enzymes. 7-Formylcoumarin was a mechanism-based inhibitor for CYP2As of all species. 4. Docking and molecular dynamics simulations of 6-methylcoumarin and 7-methylcoumarin in the active sites of CYP2A6 and CYP2A5 demonstrated a favorable orientation of the 7-position of 6-methylcoumarin towards the heme moiety. Several orientations of 7-methylcoumarin were possible in CYP2A6 and CYP2A5. 5. These results indicate that the active site of CYP2A6 has unique interaction properties for ligands and differs in this respect from CYP2A5 and CYP2A19.

A novel structural unit in the N-terminal region of filamins.

Immunoglobulin-like (Ig) domains are a widely expanded superfamily that act as interaction motifs or as structural spacers in multidomain proteins. Vertebrate filamins (FLNs), which are multifunctional actin-binding proteins, consist of 24 Ig domains. We have recently discovered that in the C-terminal rod 2 region of FLN, Ig domains interact with each other forming functional domain pairs, where the interaction with signaling and transmembrane proteins is mechanically regulated by weak actomyosin contraction forces. Here, we investigated if there are similar inter-domain interactions around domain 4 in the N-terminal rod 1 region of FLN. Protein crystal structures revealed a new type of domain organization between domains 3, 4, and 5. In this module, domains 4 and 5 interact rather tightly, whereas domain 3 has a partially flexible interface with domain 4. NMR peptide titration experiments showed that within the three-domain module, domain 4 is capable for interaction with a peptide derived from platelet glycoprotein Ib. Crystal structures of FLN domains 4 and 5 in complex with the peptide revealed a typical ß sheet augmentation interaction observed for many FLN ligands. Domain 5 was found to stabilize domain 4, and this could provide a mechanism for the regulation of domain 4 interactions.

Ultrafast protein structure-based virtual screening with Panther.

Molecular docking is by far the most common method used in protein structure-based virtual screening. This paper presents Panther, a novel ultrafast multipurpose docking tool. In Panther, a simple shape-electrostatic model of the ligand-binding area of the protein is created by utilizing the protein crystal structure. The features of the possible ligands are then compared to the model by using a similarity search algorithm. On average, one ligand can be processed in a few minutes by using classical docking methods, whereas using Panther processing takes <1 s. The presented Panther protocol can be used in several applications, such as speeding up the early phases of drug discovery projects, reducing the number of failures in the clinical phase of the drug development process, and estimating the environmental toxicity of chemicals. Panther-code is available in our web pages (http://www.jyu.fi/panther) free of charge after registration.

Molecular mechanism of T-cell protein tyrosine phosphatase (TCPTP) activation by mitoxantrone.

T-cell protein tyrosine phosphatase (TCPTP) is a ubiquitously expressed non-receptor protein tyrosine phosphatase. It is involved in the negative regulation of many cellular signaling pathways. Thus, activation of TCPTP could have important therapeutic applications in diseases such as cancer and inflammation. We have previously shown that the α-cytoplasmic tail of integrin α1ß1 directly binds and activates TCPTP. In addition, we have identified in a large-scale high-throughput screen six small molecules that activate TCPTP. These small molecule activators include mitoxantrone and spermidine. In this study, we have investigated the molecular mechanism behind agonist-induced TCPTP activation. By combining several molecular modeling and biochemical techniques, we demonstrate that α1-peptide and mitoxantrone activate TCPTP via direct binding to the catalytic domain, whereas spermidine does not interact with the catalytic domain of TCPTP in vitro. Furthermore, we have identified a hydrophobic groove surrounded by negatively charged residues on the surface of TCPTP as a putative binding site for the α1-peptide and mitoxantrone. Importantly, these data have allowed us to identify a new molecule that binds to TCPTP, but interestingly cannot activate its phosphatase activity. Accordingly, we describe here mechanism of TCPTP activation by mitoxantrone, the cytoplasmic tail of α1-integrin, and a mitoxantrone-like molecule at the atomic level. These data provide invaluable insight into the development of novel TCPTP activators, and may facilitate the rational discovery of small-molecule cancer therapeutics.

2NH and 3OH are crucial structural requirements in sphingomyelin for sticholysin II binding and pore formation in bilayer membranes.

Sticholysin II (StnII) is a pore-forming toxin from the sea anemone Stichodactyla heliantus which belongs to the large actinoporin family. The toxin binds to sphingomyelin (SM) containing membranes, and shows high binding specificity for this lipid. In this study, we have examined the role of the hydrogen bonding groups of the SM long-chain base (i.e., the 2NH and the 3OH) for StnII recognition. We prepared methylated SM-analogs which had reduced hydrogen bonding capability from 2NH and 3OH. Both surface plasmon resonance experiments, and isothermal titration calorimetry measurements indicated that StnII failed to bind to bilayers containing methylated SM-analogs, whereas clear binding was seen to SM-containing bilayers. StnII also failed to induce calcein release (i.e., pore formation) from vesicles made to contain methylated SM-analogs, but readily induced calcein release from SM-containing vesicles. Molecular modeling of SM docked to the phosphocholine binding site of StnII indicated that the 2NH and 3OH groups were likely to form a hydrogen bond with Tyr135. In addition, it appeared that Tyr111 and Tyr136 could donate hydrogen bonds to phosphate oxygen, thus stabilizing SM binding to the toxin. We conclude that the interfacial hydrogen bonding properties of SM, in addition to the phosphocholine head group, are crucial for high-affinity SM/StnII-interaction.

L-arabinose/D-galactose 1-dehydrogenase of Rhizobium leguminosarum bv. trifolii characterised and applied for bioconversion of L-arabinose to L-arabonate with Saccharomyces cerevisiae.

Four potential dehydrogenases identified through literature and bioinformatic searches were tested for L-arabonate production from L-arabinose in the yeast Saccharomyces cerevisiae. The most efficient enzyme, annotated as a D-galactose 1-dehydrogenase from the pea root nodule bacterium Rhizobium leguminosarum bv. trifolii, was purified from S. cerevisiae as a homodimeric protein and characterised. We named the enzyme as a L-arabinose/D-galactose 1-dehydrogenase (EC 1.1.1.-), Rl AraDH. It belongs to the Gfo/Idh/MocA protein family, prefers NADP(+) but uses also NAD(+) as a cofactor, and showed highest catalytic efficiency (k cat/K m) towards L-arabinose, D-galactose and D-fucose. Based on nuclear magnetic resonance (NMR) and modelling studies, the enzyme prefers the α-pyranose form of L-arabinose, and the stable oxidation product detected is L-arabino-1,4-lactone which can, however, open slowly at neutral pH to a linear L-arabonate form. The pH optimum for the enzyme was pH 9, but use of a yeast-in-vivo-like buffer at pH 6.8 indicated that good catalytic efficiency could still be expected in vivo. Expression of the Rl AraDH dehydrogenase in S. cerevisiae, together with the galactose permease Gal2 for L-arabinose uptake, resulted in production of 18 g of L-arabonate per litre, at a rate of 248 mg of L-arabonate per litre per hour, with 86 % of the provided L-arabinose converted to L-arabonate. Expression of a lactonase-encoding gene from Caulobacter crescentus was not necessary for L-arabonate production in yeast.

Building shape-focused pharmacophore models for effective docking screening.

The performance of molecular docking can be improved by comparing the shape similarity of the flexibly sampled poses against the target proteins' inverted binding cavities. The effectiveness of these pseudo-ligands or negative image-based models in docking rescoring is boosted further by performing enrichment-driven optimization. Here, we introduce a novel shape-focused pharmacophore modeling algorithm O-LAP that generates a new class of cavity-filling models by clumping together overlapping atomic content via pairwise distance graph clustering. Top-ranked poses of flexibly docked active ligands were used as the modeling input and multiple alternative clustering settings were benchmark-tested thoroughly with five demanding drug targets using random training/test divisions. In docking rescoring, the O-LAP modeling typically improved massively on the default docking enrichment; furthermore, the results indicate that the clustered models work well in rigid docking. The C+ +/Qt5-based algorithm O-LAP is released under the GNU General Public License v3.0 via GitHub ( https://github.com/jvlehtonen/overlap-toolkit ). SCIENTIFIC CONTRIBUTION: This study introduces O-LAP, a C++/Qt5-based graph clustering software for generating new type of shape-focused pharmacophore models. In the O-LAP modeling, the target protein cavity is filled with flexibly docked active ligands, the overlapping ligand atoms are clustered, and the shape/electrostatic potential of the resulting model is compared against the flexibly sampled molecular docking poses. The O-LAP modeling is shown to ensure high enrichment in both docking rescoring and rigid docking based on comprehensive benchmark-testing.