Lead hopping using SVM and 3D pharmacophore fingerprints

The combination of 3D pharmacophore fingerprints and the support vector machine classification algorithm has been used to generate robust models that are able to classify compounds as active or inactive in a number of G-protein-coupled receptor assays. The models have been tested against progressively more challenging validation sets where steps are taken to ensure that compounds in the validation set are chemically and structurally distinct from the training set. In the most challenging example, we simulate a lead-hopping experiment by excluding an entire class of compounds (defined by a core substructure) from the training set. The left-out active compounds comprised approximately 40% of the actives. The model trained on the remaining compounds is able to recall 75% of the actives from the "new" lead series while correctly classifying >99% of the 5000 inactives included in the validation set.     

Fingerprint directed scaffold hopping for identification of CCR2 antagonists

Chemokine receptors have evolved as attractive targets for disease conditions which arise due to immunomodulation involving host-defense mechanisms. CCR2, a chemokine receptor, is targeted for diseases like arthritis, multiple sclerosis, vascular disease, obesity, and type 2 diabetes. This study provides a new strategy of a ligand based technique which exploits fingerprint led fragment features in conjunction with structure-guided design for identifying new scaffolds for CCR2. A fragment based mining (FBM) technique was employed on a chemical database to identify novel scaffold hops. The hits were subjected to 3-point pharmacophore fingerprint procedures with Tanimoto similarity metric to compare pharmacophoric fingerprints. The final 66 hits generated by these exercises were predicted by the validated HQSAR model, and the top predicted were suggested as probable scaffolds for CCR2 antagonism. The identified scaffolds were validated through molecular docking studies. The ligands were docked by providing receptor flexibility in the extra cellular domain (1 and 3), N terminal domain, and in the transmembrane (TM1 & TM7) helix region with IFD approach. Some of the scaffolds showed H-bonding potential which was not explored by the data set molecules. All identified scaffolds highlighted a key hydrogen bonding interaction with Thr292 as supported by mutational studies. The observed pi stacking interaction with Tyr188 in data set molecules was also produced by the new scaffolds. Taking the advantage of receptor flexibility the scaffolds explored the hydrophobic binding cleft between helix 1 and 7 occupied by residues Leu44, Leu45, Leu48 and Ile300, Ile303, Ile304, respectively. Two of the identified molecules have promising outcomes and can be considered as novel scaffolds for CCR2 binding.     

MED-SuMoLig: a new ligand-based screening tool for efficient scaffold hopping

The identification of small molecules with selective bioactivity, whether intended as potential therapeutics or as tools for experimental research, is central to progress in medicine and in the life sciences. To facilitate such study, we have developed a ligand-based program well-suited for effective screening of large compound collections. This package, MED-SuMoLig, combines a SMARTS-driven substructure search aiming at 3D pharmacophore profiling and computation of the local atomic density of the compared molecules. The screening utility was then investigated using 52 diverse active molecules (against CDK2, Factor Xa, HIV-1 protease, neuraminidase, ribonuclease A, and thymidine kinase) merged to a library of about 40,000 putative inactive (druglike) compounds. In all cases, the program recovered more than half of the actives in the top 3% of the screened library. We also compared the performance of MED-SuMoLig with that of ChemMine or of ROCS and found that MED-SuMoLig outperformed both methods for CDK2 and Factor Xa in terms of enrichment rates or performed equally well for the other targets.     

2D conformationally sampled pharmacophore: a ligand-based pharmacophore to differentiate delta opioid agonists from antagonists

Pharmacophores are widely used for rational drug design and include those based on receptor binding sites or on known ligands. To date, ligand-based pharmacophores have typically used one or a small number of conformers of known receptor ligands. However, this method does not take into account the inherent dynamic nature of molecules, which sample a wide range of conformations, any of which could be the bound form. In the present study, molecular dynamics (MD) simulations were used as a means to sample the conformational space of ligands to include all accessible conformers at room temperature in the development of a pharmacophore. On the basis of these conformers, probability distributions of selected distances and angles in a series of delta specific opioid ligands were obtained and correlated with agonist versus antagonist activities. Individually, the distributions did not allow for unique agonist and antagonist pharmacophores to be identified. However, by extending the conformational analysis to two dimensions, a 2D conformationally sampled pharmacophore (CSP) for distinguishing delta receptor agonists and antagonists was developed. Application of this model to the compound DPI2505 suggests that it may have agonist activity. It is anticipated that the CSP method, which does not require alignment of compounds during pharmacophore development, will be a useful tool for obtaining structure-function relationships of ligands particularly in systems where the receptor 3D structure is not known.     

Systematic assessment of scaffold distances in ChEMBL: prioritization of compound data sets for scaffold hopping analysis in virtual screening

The evaluation of the scaffold hopping potential of computational methods is of high relevance for virtual screening. For benchmark calculations, classes of known active compounds are utilized. Ideally, such classes should have a well-defined content of structurally diverse scaffolds. However, in reported benchmark investigations, the choice of activity classes is often difficult to rationalize. To provide a compendium of well-characterized test cases for the assessment of scaffold hopping potential, structural distances between scaffolds were systematically calculated for compound classes available in the ChEMBL database. Nearly seven million scaffold pairs were evaluated. On the basis of the global scaffold distance distribution, a threshold value for large scaffold distances was determined. Compound data sets were ranked based on the proportion of scaffold pairs with large distances they contained, taking additional criteria into account that are relevant for virtual screening. A set of 50 activity classes is provided that represent attractive test cases for scaffold hopping analysis and benchmark calculations.     

Computer-aided molecular modeling of a D2-agonist dopamine pharmacophore

Summary Using computer-aided molecular modeling techniques to analyze models recently proposed for the receptor binding sites of dopaminergic agonists, we superimposed the chemical structures of various compounds that mimic the pharmacological behavior of dopamine, as well as inactive enantiomers, on a postulated three-dimensional frame of reference. We analyzed the vector directionalities of the lone pairs of the nitrogen common to these molecules, and the acidic hydrogen of phenols (in aminoindanes, aminotetralins, apomorphines,p-phenol-piperazines, octahydrobenzo(g)quinolines, octahydrobenzo(f)quinolines, and benzazepines) or of nitrogen (in ergoline-type compounds and related structures). This model, when expressed as distances from that of the reference compound pergolide, correlates with the dopaminergic binding affinity observed in compounds previously reported to act on the dopaminergic system in the central nervous system (CNS). The regression analysis of log K_D with respect to the distances of the vectors of the acidic hydrogen support the hypothesis that these compounds bind to the receptor as donors in hydrogen bond formation.     

Jolkinolide D pharmacophore: synthesis and reaction with biomolecules

To obtain information on the chemical modification of biomolecules with jolkinolide D, a bioactive diterpenoid of plant origin, jolkinolide D pharmacophore was synthesized, and its reactivity toward amino acids, nucleosides, and DNA was investigated.     

A pharmacophore model for dopamine D4 receptor antagonists

A pharmacophore model for dopamine D₄ antagonists has been developed on the basis of a previously reported dopamine D₂ model. By using exhaustive conformational analyses (MM3^* force field and the GB/SA hydration model) and least-squares molecular superimposition studies, a set of eighteen structurally diverse high affinity D₄ antagonists have successfully been accommodated in the D₄ pharmacophore model. Enantioselectivities may be rationalized by conformational energies required for the enantiomers to adopt their proposed bioactive conformations. The pharmacophore models for antagonists at the D₄ and D₂ receptor subtypes have been compared in order to get insight into molecular properties of importance for D₂/D₄ receptor selectivity. It is concluded that the bioactive conformations of antagonists at the two receptor subtypes are essentially identical. Receptor essential volumes previously identified for the D₂ receptor are shown to be present also in the D₄ receptor. In addition, a novel receptor essential volume in the D₄ receptor, not present in the D₂ receptor, has been identified. This feature may be exploited for the design of D₄ selective antagonists. However, it is concluded that the major determinant for D₂/D₄ selectivity is the nature of the interactions between the receptor and aromatic ring systems. The effects of the electronic properties of these ring systems on the affinities for the two receptor subtypes differ substantially.     

Discovery of potential M2 channel inhibitors based on the amantadine scaffold via virtual screening and pharmacophore modeling

The M2 channel protein on the influenza A virus membrane has become the main target of the anti-flu drugs amantadine and rimantadine. The structure of the M2 channel proteins of the H3N2 (PDB code 2RLF) and 2009-H1N1 (Genbank accession number GQ385383) viruses may help researchers to solve the drug-resistant problem of these two adamantane-based drugs and develop more powerful new drugs against influenza A virus. In the present study, we searched for new M2 channel inhibitors through a combination of different computational methodologies, including virtual screening with docking and pharmacophore modeling. Virtual screening was performed to calculate the free energies of binding between receptor M2 channel proteins and 200 new designed ligands. After that, pharmacophore analysis was used to identify the important M2 protein-inhibitor interactions and common features of top binding compounds with M2 channel proteins. Finally, the two most potential compounds were determined as novel leads to inhibit M2 channel proteins in both H3N2 and 2009-H1N1 influenza A virus.     

Sodium 4-amino-5-hydroxy-7-sulfonaphthalene-2-sulfonate an efficient ligand for click reaction in water: Synthesis of 1,2,3-triazole pharmacophore linked-quinazolinone scaffold

Water soluble sodium 4-amino-5-hydroxy-7-sulfonaphthalene-2-sulfonate ligand was used successfully for the preparation of 1,2,3-triazoles pharmacophore linked-quinazolinone scaffold. The reaction of ethyl 4-oxo-3,4-dihydroquinazoline-2-carboxylate and related amide compounds with propargyl bromide afforded ethyl 4-oxo-3-(prop-2-yn-1-yl)-3,4-dihydroquinazoline-2-carboxylate and its amide derivatives. The reaction of propargylated compounds with azides catalyzed by copper (II) salt, in the presence of Sodium 4-amino-5-hydroxy-7-sulfonaphthalene-2-sulfonate as a ligand in water produced novel 1,2,3-triazole pharmacophore linked-quinazolinone-4-one scaffold with high-to-excellent yields. The ligand assisted in the click reaction and reduced loading of copper salt to 2 mol%. Simplicity, short reaction times, use of water as green solvent, and low catalyst loading are the main advantages of this procedure.     

Toward the identification of a reliable 3D QSAR pharmacophore model for the CCK2 receptor antagonism

The present study describes application of computational approaches to identify a validated and reliable 3D QSAR pharmacophore model for the CCK-2R antagonism through integrated ligand and structure based studies using anthranilic sulfonamide and 1,3,4-benzotriazepine based CCK-2R antagonists. The best hypothesis consisted five features viz. two aliphatic hydrophobic, one aromatic hydrophobic, one H-bond acceptor, and one ring aromatic feature with an excellent correlation for 34 training set (r2(training) = 0.83) and 58 test set compounds (r2(test) = 0.74). This model was validated through F-test and docking studies at the active site of the plausible CCK-2R where the 99% significance and well corroboration with the pharmacophore model respectively describes the model's reliability. The model also predicts well to other known clinically effective CCK-2R antagonists. Therefore, the developed model may useful in finding new scaffolds that may aid in design and develop new chemical entities (NCEs) as potent CCK-2R antagonists before their synthesis.     

Structural unit analysis identifies lead series and facilitates scaffold hopping in combinatorial chemistry

Combinatorial chemistry and high-throughput screening technologies produce huge amounts of data on a regular basis. Sieving through these libraries of compounds and their associated assay data to identify appropriate series for follow-up is a daunting task, which has created a need for computational techniques that can find coherent islands of structure-activity relationships in this sea. Structural unit analysis (SUA) examines an entire data set so as to identify the molecular substructures or fragments that distinguish compounds with high activity from those with average activity. The algorithm is iterative and follows set heuristics in order to generate the structural units. It produces graphs that represent a set of units, which become SUA rules. Finding all of the input structures that match these graphs generates clusters. The Apriori algorithm for association rule mining is adapted to explore all of the combinations of structural units that define useful series. User-defined constraints are applied toward series selection and the refinement of rules. The significance of a series is determined by applying statistical methods appropriate to each data set. Application to the NCI-H23 (DTP Human Tumor Cell Line Screen) database serves to illustrate the process by which structural series are identified. An application of the method to scaffold hopping is then discussed in connection with proprietary screening data from a lead optimization project directed toward the treatment of respiratory tract infections at Bayer Healthcare. SUA was able to successfully identify promising alternative core structures in addition to identifying compounds with above-average activity and selectivity.     

Unsupervised 3D ring template searching as an ideas generator for scaffold hopping: use of the LAMDA, RigFit, and field-based similarity search (FBSS) methods

Crystal structures taken from the Cambridge Structural Database were used to build a ring scaffold database containing 19 050 3D structures, with each such scaffold then being used to generate a centroid connecting path (CCP) representation. The CCP is a novel object that connects ring centroids, ring linker atoms, and other important points on the connection path between ring centroids. Unsupervised searching in the scaffold and CCP data sets was carried out using the atom-based LAMDA and RigFit search methods and the field-based similarity search method. The performance of these methods was tested with three different ring scaffold queries. These searches demonstrated that unsupervised 3D scaffold searching methods can find not only the types of ring systems that might be retrieved in carefully defined pharmacophore searches (supervised approach) but also additional, structurally diverse ring systems that could form the starting point for lead discovery programs or other scaffold-hopping applications. Not only are the methods effective but some are sufficiently rapid to permit scaffold searching in large chemical databases on a routine basis.     

Keto-coumarin scaffold for photoinitiators for 3D printing and photocomposites

The purposes of this paper are moving toward (a) the development of a new series of photoinitiators (PIs) which are based on the keto-coumarin (KC) core, (b) the introduction of light-emitting diodes (LEDs) as inexpensive and safe sources of irradiation, (c) the study of the photochemical mechanisms through which the new PIs react using different techniques such as Fourier transform infrared, UV–visible or fluorescence spectroscopy, and so on, (d) the use of such compounds (presenting good reactivity and excellent photopolymerization initiating abilities) for two specific and high added value applications: 3D printing (@405 nm) and preparation of thick glass fiber photocomposites with excellent depth of cure, and finally (e) the comparison of the performance of these KC derivatives versus other synthesized coumarin derivatives. In this study, six well-designed KC derivatives ( KC-C , KC-D , KC-E , KC-F , KC-G , and KC-H ) are examined as high-performance visible-light PIs for the cationic polymerization of epoxides as well as the free-radical polymerization of acrylates upon irradiation with LED@405 nm. Excellent polymerization rates are obtained using two different approaches: a photo-oxidation process in combination with an iodonium (Iod) salt and a photo-reduction process when associated with an amine (N-phenylglycine or ethyl 4-(dimethylamino)benzoate). High final reactive conversions were obtained. A full picture of the involved photochemical mechanisms is provided.     

Combining 4D pharmacophore generation and multidimensional QSAR: modeling ligand binding to the bradykinin B2 receptor

We recently reported the development of two receptor-modeling concepts (software Quasar and Raptor) based on multidimensional quantitative structure-activity relationships (QSAR) and allowing for the explicit simulation of induced fit. As the identification of the bioactive configuration of ligand molecules in such studies is all but unambiguous, each compound may be represented by an ensemble of different conformations, orientations, stereoisomers, and protonation states, leading to a 4D data set. In this account, we present a novel technology (software Symposar) allowed to automatically generate a 4D pharmacophore as input for multidimensional QSAR. Symposar aligns ligands utilizing fuzzylike 2D-subfeature mapping and, subsequently, a Monte Carlo search on a 3D similarity grid. The two-step concept (4D pharmacophore generation and quantification of ligand binding by multidimensional QSAR) was applied to 186 compounds binding to the bradykinin B2 receptor. The prediction of their binding affinity by means of the Quasar and Raptor technologies allowed for consensus scoring and generated topologically and quantitatively consistent receptor models. These converged at a cross-validated r2 of 0.752 and 0.815 and yielded a predictive r2 of 0.784 and 0.853 for a test set (for Quasar and Raptor, respectively).     

Forging of nicotine for the effective management of diabetic wounds: A hybrid of scaffold hopping and molecular dynamics simulation approaches

Diabetic wound (DW) is a huge threat to the health care community and is always challenging to treat. The main biochemical culprits in DW recalcitrance are elevated inflammatory mediators, proteases, cell proliferation and migration suppressors, anti-angiogenic factors, and bacterial infections. In this scenario, using a scaffold to target important factors at each stage of pathogenesis can accelerate the healing process. Many shreds of evidence disclosed the role of nicotine scaffold in handling inflammation, infection, proliferation, migration, and angiogenesis. All these factors made us forge nicotine by employing a scaffold hopping approach. The hops were then subjected to molecular docking and binding free energy calculations against Matrix metallopeptidase 9, Glycogen synthase kinase 3 beta, Tumor necrosis factor alpha, MurC and ParE enzymes. Gratifyingly, molecule H1 was found to possess significant inhibitory activity against the selected receptors as evidenced by their high negative glide score and binding energy. Furthermore, 100 ns of molecular dynamics simulation studies (MD) was performed for the five H1/4XCT, H1/5F95, H1/2AZ5, H1/4C13 and H1/4MOT complexes to get insight into the binding modes and stability. The MD results showed significant stability as evidenced by the low conformational changes of the H1 with the chosen receptors. Hence, H1 might be a druggable candidate in the therapeutic management of DW. However, further research is strongly recommended to advance the drug into the therapeutic pipeline.     

Derivation of a 3D pharmacophore model for the angiotensin-II site one receptor

Summary A systematic search has been used to derive a hypothesis for the receptor-bound conformation of A-II antagonists at the AT₁ receptor. The validity of the pharmacophore hypothesis has been tested using CoMFA, which included 50 diverse A-II antagonists, spanning four orders of magnitude in activity. The resulting cross-validated R² of 0.64 (conventional R² of 0.76) is indicative of a good predictive model of activity, and has been used to estimate potency for a variety of non-peptidyl antagonists. The structural model for the non-peptide has been compared with respect to the natural substrate, A-II, by generating peptide to non-peptide overlays.