Rational Design of Small 3D Gold Clusters

Abstract  

We designed a series of small 3D gold clusters using a four-atomic tetrahedron with a four center–two electron (4c–2e) bond inside as a building block. The follow-up results of the unbiased global minimum searches proved that indeed the designed 3D structures containing small tetrahedral building blocks with a 4c–2e bond inside are either global minimum structures or low-lying isomers. We believe that the proposed way of building 3D clusters could be used for rational design of other 3D gold clusters.     

Computer-assisted combinatorial design of bicyclic thymidine analogs as inhibitors of <Emphasis Type="Italic">Mycobacterium tuberculosis</Emphasis> thymidine monophosphate kinase

Abstract  

Thymidine monophosphate kinase (TMPK_mt) is an essential enzyme for nucleotide metabolism in Mycobacterium tuberculosis, and thus an attractive target for novel antituberculosis agents. In this work, we have explored the chemical space around the 2′,3′-bicyclic thymidine nucleus by designing and in silico screening of a virtual focused library selected via structure based methods to identify more potent analogs endowed with favorable ADME-related properties. In all the library members we have exchanged the ribose ring of the template with a cyclopentane moiety that is less prone to enzymatic degradation. In addition, we have replaced the six-membered 2′,3′-ring by a number of five-membered and six-membered heterocyclic rings containing alternative proton donor and acceptor groups, to exploit the interaction with the carboxylate groups of Asp9 and Asp163 as well as with several cationic residues present in the vicinity of the TMPK_mt binding site. The three-dimensional structure of the TMPK_mt complexed with 5-hydroxymethyl-dUMP, an analog of dTMP, was employed to develop a QSAR model, to parameterize a scoring function specific for the TMPK_mt target and to select analogues which display the highest predicted binding to the target. As a result, we identified a small highly focused combinatorial subset of bicyclic thymidine analogues as virtual hits that are predicted to inhibit the mycobacterial TMPK in the submicromolar concentration range and to display favorable ADME-related properties.     

Fast 3D shape screening of large chemical databases through alignment-recycling

Background  

Large chemical databases require fast, efficient, and simple ways of looking for similar structures. Although such tasks are now fairly well resolved for graph-based similarity queries, they remain an issue for 3D approaches, particularly for those based on 3D shape overlays. Inspired by a recent technique developed to compare molecular shapes, we designed a hybrid methodology, alignment-recycling, that enables efficient retrieval and alignment of structures with similar 3D shapes.     

Visualisation and subsets of the chemical universe database GDB-13 for virtual screening

Abstract  

The chemical universe database GDB-13, which enumerates 977 million organic molecules up to 13 atoms of C, N, O, S and Cl following simple chemical stability and synthetic feasibility rules, represents a vast reservoir for new fragments. GDB-13 was classified using the MQN-system discussed in the preceding paper for the analysis of PubChem fragments. Two hundred and fifty-five subsets of GDB-13 were generated by the combinatorial use of eight restrictive criteria, including fragment-like (“rule of three”) and scaffold-like (no acyclic carbon atoms) filters. Virtual screening for analogs of 15 commercial drugs of 13 non-hydrogen atoms or less shows that retrieving MQN-neighbors of a query molecule from GDB-13 or its subsets provides on average a 38-fold enrichment in structural analogs (Daylight-type substructure fingerprint Tanimoto T _SF > 0.7), and a 75-fold enrichment in shape-similar analogs (ROCS TanimotoCombo score > 1.4). An MQN-searchable version of GDB-13 is provided at .     

Is it time for biocatalysis in fragment-based drug discovery?

The use of biocatalysts for fragment-based drug discovery has yet to be fully investigated, despite the promise enzymes hold for the synthesis of poly-functional, non-protected small molecules. Here we analyze products of the biocatalysis literature to demonstrate the potential for not only fragment generation, but also the enzyme-mediated elaboration of these fragments. Our analysis demonstrates that biocatalytic products can readily populate 3D chemical space, offering diverse catalytic approaches to help generate new, bioactive molecules.

This perspective discusses how biocatalysis could play an important role in the future fragment-based drug discovery.     

Structure-guided fragment-based<Emphasis Type="Italic"> in silico</Emphasis> drug design of dengue protease inhibitors

An in silico fragment-based drug design approach was devised and applied towards the identification of small molecule inhibitors of the dengue virus (DENV) NS2B-NS3 protease. Currently, no DENV protease co-crystal structure with bound inhibitor and fully formed substrate binding site is available. Therefore a homology model of DENV NS2B-NS3 protease was generated employing a multiple template spatial restraints method and used for structure-based design. A library of molecular fragments was derived from the ZINC screening database with help of the retrosynthetic combinatorial analysis procedure (RECAP). 150,000 molecular fragments were docked to the DENV protease homology model and the docking poses were rescored using a target-specific scoring function. High scoring fragments were assembled to small molecule candidates by an implicit linking cascade. The cascade included substructure searching and structural filters focusing on interactions with the S1 and S2 pockets of the protease. The chemical space adjacent to the promising candidates was further explored by neighborhood searching. A total of 23 compounds were tested experimentally and two compounds were discovered to inhibit dengue protease (IC₅₀ = 7.7 μM and 37.9 μM, respectively) and the related West Nile virus protease (IC₅₀ = 6.3 μM and 39.0 μM, respectively). This study demonstrates the successful application of a structure-guided fragment-based in silico drug design approach for dengue protease inhibitors providing straightforward hit generation using a combination of homology modeling, fragment docking, chemical similarity and structural filters.     

DOVIS 2.0: an efficient and easy to use parallel virtual screening tool based on AutoDock 4.0

Background  

Small-molecule docking is an important tool in studying receptor-ligand interactions and in identifying potential drug candidates. Previously, we developed a software tool (DOVIS) to perform large-scale virtual screening of small molecules in parallel on Linux clusters, using AutoDock 3.05 as the docking engine. DOVIS enables the seamless screening of millions of compounds on high-performance computing platforms. In this paper, we report significant advances in the software implementation of DOVIS 2.0, including enhanced screening capability, improved file system efficiency, and extended usability.     

Pharmacophore generation,atom-based 3D-QSAR and molecular dynamics simulation analyses of pyridine-3-carboxamide-6-yl-urea analogues as potential gyrase B inhibitors

DNA gyrase subunit B (GyrB) is an attractive drug target for the development of antibacterial agents with therapeutic potential. In the present study, computational studies based on pharmacophore modelling, atom-based QSAR, molecular docking, free binding energy calculation and dynamics simulation were performed on a series of pyridine-3-carboxamide-6-yl-urea derivatives. A pharmacophore model using 49 molecules revealed structural and chemical features necessary for these molecules to inhibit GyrB. The best fitted model AADDR.13 was generated with a coefficient of determination (r²) of 0.918. This model was validated using test set molecules and had a good r² of 0.78. 3D contour maps generated by the 3D atom-based QSAR revealed the key structural features responsible for the GyrB inhibitory activity. Extra precision molecular docking showed hydrogen bond interactions with key amino acid residues of ATP-binding pocket, important for inhibitor binding. Further, binding free energy was calculated by the MM-GBSA rescoring approach to validate the binding affinity. A 10 ns MD simulation of inhibitor #47 showed the stability of the predicted binding conformations. We identified 10 virtual hits by in silico high-throughput screening. A few new molecules were also designed as potent GyrB inhibitors. The information obtained from these methodologies may be helpful to design novel inhibitors of GyrB.     

Covalent attachment of the plant natural product naringenin to small glass and ceramic beads

Background  

Natural products have numerous medicinal applications and play important roles in the biology of the organisms that accumulate them. Few methods are currently available for identifying proteins that bind to small molecules, therefore the discovery of cellular targets for natural products with pharmacological activity continues to pose a significant challenge in drug validation. Similarly, the identification of enzymes that participate in the biosynthesis or modification of natural products remains a formidable bottleneck for metabolic engineering. Flavonoids are one large group of natural products with a diverse number of functions in plants and in human health. The coupling of flavonoids to small ceramic and glass beads provides a first step in the development of high-throughput, solid-support base approaches to screen complex libraries to identify proteins that bind natural products.     

Reaction between benzyllithium and 2-ethylpyridine: chiral crystals of a 1-(2-pyridyl)ethyllithium complex versus formation of lithium 4-benzyl-2-ethyl-1,4-dihydropyridinide

Abstract  

The reaction between benzyllithium and prochiral 2-ethylpyridine in tetrahydrofuran has been studied. In the presence of N,N,N′,N′′,N′′-pentamethyldiethylenetriamine (PMDTA), it was found that 1-(2-pyridyl)ethyllithium was formed as a PMDTA complex. This complex is mononuclear, with lithium coordinated to the pyridyl nitrogen atom only; there are no short lithium–carbon distances and the structure approaches that of an enamide rather than a carbanion. The complex undergoes spontaneous resolution and forms chiral crystals with two molecules in the asymmetric unit; the two molecules have different configurations at the chirogenic pyridyl nitrogen atoms but share the same chiral conformation of the chelate ring systems. Reaction between benzyllithium and 2-ethylpyridine in tetrahydrofuran in the absence of PMDTA was found to give a high proportion of lithium 4-benzyl-2-ethyl-1,4-dihydropyridinide, and crystals of a dinuclear complex displaying tetrahydrofuran ligands and co-crystallised n-hexane molecules were isolated.     

Investigation of the chaperone function of the small heat shock protein — AgsA

Background  

A small heat shock protein AgsA was originally isolated from Salmonella enterica serovar Typhimurium. We previously demonstrated that AgsA was an effective chaperone that could reduce the amount of heat-aggregated proteins in an Escherichia coli rpoH mutant. AgsA appeared to promote survival at lethal temperatures by cooperating with other chaperones in vivo. To investigate the aggregation prevention mechanisms of AgsA, we constructed N- or C-terminal truncated mutants and compared their properties with wild type AgsA.     

Tubulin is a molecular target of the Wnt-activating chemical probe

Background

In drug discovery research, cell-based phenotypic screening is an essential method for obtaining potential drug candidates. Revealing the mechanism of action is a key step on the path to drug discovery. However, elucidating the target molecules of hit compounds from phenotypic screening campaigns remains a difficult and troublesome process. Simple and efficient methods for identifying the target molecules are essential.

Results

2-Amino-4-(3,4-(methylenedioxy)benzylamino)-6-(3-methoxyphenyl)pyrimidine (AMBMP) was identified as a senescence inducer from a phenotypic screening campaign. The compound is widely used as a Wnt agonist, although its target molecules remain to be clarified. To identify its target proteins, we compared a series of cellular assay results for the compound with our pathway profiling database. The database comprises the activities of compounds from simple assays of cellular reporter genes and cellular proliferations. In this database, compounds were classified on the basis of statistical analysis of their activities, which corresponded to a mechanism of action by the representative compounds. In addition, the mechanisms of action of the compounds of interest could be predicted using the database. Based on our database analysis, the compound was anticipated to be a tubulin disruptor, which was subsequently confirmed by its inhibitory activity of tubulin polymerization.

Conclusion

These results demonstrate that tubulin is identified for the first time as a target molecule of the Wnt-activating small molecule and that this might have misled the conclusions of some previous studies. Moreover, the present study also emphasizes that our pathway profiling database is a simple and potent tool for revealing the mechanisms of action of hit compounds obtained from phenotypic screenings and off targets of chemical probes.

     

Automated extraction of chemical structure information from digital raster images

Background  

To search for chemical structures in research articles, diagrams or text representing molecules need to be translated to a standard chemical file format compatible with cheminformatic search engines. Nevertheless, chemical information contained in research articles is often referenced as analog diagrams of chemical structures embedded in digital raster images. To automate analog-to-digital conversion of chemical structure diagrams in scientific research articles, several software systems have been developed. But their algorithmic performance and utility in cheminformatic research have not been investigated.     

A graph representation of molecular ensembles for polymer property prediction

Synthetic polymers are versatile and widely used materials. Similar to small organic molecules, a large chemical space of such materials is hypothetically accessible. Computational property prediction and virtual screening can accelerate polymer design by prioritizing candidates expected to have favorable properties. However, in contrast to organic molecules, polymers are often not well-defined single structures but an ensemble of similar molecules, which poses unique challenges to traditional chemical representations and machine learning approaches. Here, we introduce a graph representation of molecular ensembles and an associated graph neural network architecture that is tailored to polymer property prediction. We demonstrate that this approach captures critical features of polymeric materials, like chain architecture, monomer stoichiometry, and degree of polymerization, and achieves superior accuracy to off-the-shelf cheminformatics methodologies. While doing so, we built a dataset of simulated electron affinity and ionization potential values for >40k polymers with varying monomer composition, stoichiometry, and chain architecture, which may be used in the development of other tailored machine learning approaches. The dataset and machine learning models presented in this work pave the path toward new classes of algorithms for polymer informatics and, more broadly, introduce a framework for the modeling of molecular ensembles.

A graph representation that captures critical features of polymeric materials and an associated graph neural network achieve superior accuracy to off-the-shelf cheminformatics methodologies.     

Ab initio and DFT conformational study on nitrosamine (H<Subscript>2</Subscript>N–N=O) and <Emphasis Type="Italic">N</Emphasis>-Nitrosodimethylamine [(CH<Subscript>3</Subscript>)<Subscript>2</Subscript>N–N=O]

Abstract  

Ab initio and DFT calculations have been performed to characterize some ground state structures of the title molecules. Relative energies, rotational barriers, NBO charges, and dipole moments (μ) have been calculated and analyzed. It has been confirmed that only highly correlated methods (e.g., CCSD) are able to yield the non-planar structure as a minimum, for the H₂NNO molecule. On the other hand, all computational levels here employed are able to yield a planar C₂NNO frame for the (CH₃)₂NNO as a minimum. Important correlations between atomic charges and bond distances are discussed. Replacement of H by methyl group increases the rotational barrier and μ values by at least 3 kcal/mol and 0.4 D, respectively. The largest μ values are obtained for the structures in which the nitrogen lone pair is parallel to the NO group π system, and are consistent with a larger contribution of a dipolar resonance structure.     

The in silico identification of small molecules for protein-protein interaction inhibition in AKAP-Lbc–RhoA signaling complex

The rational design of small molecules that mimic key residues at the interface of interacting proteins can be a successful approach to target certain biological signaling cascades causing pathophysiological outcome. The A-Kinase Anchoring Protein, i.e. AKAP-Lbc, catalyses nucleotide exchange on RhoA and is involved in cardiac repolarization. The oncogenic AKAP-Lbc induces the RhoA GTPase hyperactivity and aberrantly amplifies the signaling pathway leading to hypertrophic cardiomyocytes. We took advantage of the AKAP-Lbc–RhoA complex crystal structure to design in silico small molecules predicted to inhibit the associated pathological signaling cascade. We adopted the strategies of pharmacophore building, virtual screening and molecular docking to identify the small molecules capable to target AKAP-Lbc and RhoA interactions. The pharmacophore model based virtual screening unveils two lead compounds from the TIMBAL database of small molecules modulating the targeted protein-protein interactions. The molecular docking analysis revealed the lead compounds’ potentialities to establish the essential chemical interactions with the key interactive residues of the complex. These features provided a road map for designing additional potent chemical derivatives and fragments of the original lead compounds to perturb the AKAP-Lbc and RhoA interactions. Experimental validations may elucidate the therapeutic potential of these lead chemical scaffolds to deal with aberrant AKAP-Lbc signaling based cardiac hypertrophy.     

An informatics search for the low-molecular weight chromium-binding peptide

Background  

The amino acid composition of a low molecular weight chromium binding peptide (LMWCr), isolated from bovine liver, is reportedly E:G:C:D::4:2:2:2, though its sequence has not been discovered. There is some controversy surrounding the exact biochemical forms and the action of Cr(III) in biological systems; the topic has been the subject of many experimental reports and continues to be investigated. Clarification of Cr-protein interactions will further understanding Cr(III) biochemistry and provide a basis for novel therapies based on metallocomplexes or small molecules.     

The evolution of farnesoid X,vitamin D,and pregnane X receptors: insights from the green-spotted pufferfish (<Emphasis Type="Italic">Tetraodon nigriviridis</Emphasis>) and other non-mammalian species

Background  

The farnesoid X receptor (FXR), pregnane X receptor (PXR), and vitamin D receptor (VDR) are three closely related nuclear hormone receptors in the NR1H and 1I subfamilies that share the property of being activated by bile salts. Bile salts vary significantly in structure across vertebrate species, suggesting that receptors binding these molecules may show adaptive evolutionary changes in response. We have previously shown that FXRs from the sea lamprey (Petromyzon marinus) and zebrafish (Danio rerio) are activated by planar bile alcohols found in these two species. In this report, we characterize FXR, PXR, and VDR from the green-spotted pufferfish (Tetraodon nigriviridis), an actinopterygian fish that unlike the zebrafish has a bile salt profile similar to humans. We utilize homology modelling, docking, and pharmacophore studies to understand the structural features of the Tetraodon receptors.