A computer-based prediction platform for the reaction of ozone with organic compounds in aqueous solution: kinetics and mechanisms.

Ozonation of secondary wastewater effluents can reduce the discharge of micropollutants by transforming their chemical structures. Therefore, a better understanding of the formation of transformation products during ozonation is important. In this study, a computer-based prediction platform for the kinetics and mechanisms of the reactions of ozone with organic compounds was developed to enable in silico predictions of transformation products. With the developed prediction platform, reaction kinetics expressed as second-order rate constants for the reactions of ozone with selected organic compounds (kO3, M-1 s-1) can be predicted based on an adapted kO3 prediction model from a previous study (Lee et al., Environ. Sci. Technol., 2015, 49, 9925-9935) (average model error of about a factor of 6 for 14 compound classes with 284 model compounds). Ozone reaction mechanisms reported in the literature have been reviewed and, using chemoinformatics tools, encoded into about 340 individual reaction rules that can be generally applied to predict the transformation products of micropollutants. Predictions for kO3 and/or transformation products were overall consistent with the experimental data for three micropollutants used as validation compounds (e.g., carbamazepine, tramadol, and triclosan). However, limitations of the current kO3 prediction platform were also identified: ambiguous assignment of the n-th highest occupied molecular orbital energy (EHOMO-n) to the reactive sites, potential errors associated with the use of a gas-phase geometry, and a poor kO3 prediction for certain compounds (cetirizine). Therefore, the current prediction tool should not be considered as a substitute for experimental studies and experimental data are still required in the future to obtain a more robust prediction model. Nonetheless, the developed prediction platform, made available as a stand-alone graphical user interface (GUI) application, will provide useful information about aqueous ozone chemistry to various groups of end-users such as environmental chemists, engineers, or toxicologists.

Rapid mass spectrometric conversion of tissue biopsy samples into permanent quantitative digital proteome maps.

Clinical specimens are each inherently unique, limited and nonrenewable. Small samples such as tissue biopsies are often completely consumed after a limited number of analyses. Here we present a method that enables fast and reproducible conversion of a small amount of tissue (approximating the quantity obtained by a biopsy) into a single, permanent digital file representing the mass spectrometry (MS)-measurable proteome of the sample. The method combines pressure cycling technology (PCT) and sequential window acquisition of all theoretical fragment ion spectra (SWATH)-MS. The resulting proteome maps can be analyzed, re-analyzed, compared and mined in silico to detect and quantify specific proteins across multiple samples. We used this method to process and convert 18 biopsy samples from nine patients with renal cell carcinoma into SWATH-MS fragment ion maps. From these proteome maps we detected and quantified more than 2,000 proteins with a high degree of reproducibility across all samples. The measured proteins clearly distinguished tumorous kidney tissues from healthy tissues and differentiated distinct histomorphological kidney cancer subtypes.

Quantitative variability of 342 plasma proteins in a human twin population.

The degree and the origins of quantitative variability of most human plasma proteins are largely unknown. Because the twin study design provides a natural opportunity to estimate the relative contribution of heritability and environment to different traits in human population, we applied here the highly accurate and reproducible SWATH mass spectrometry technique to quantify 1,904 peptides defining 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2-7 years, and proportioned the observed total quantitative variability to its root causes, genes, and environmental and longitudinal factors. The data indicate that different proteins show vastly different patterns of abundance variability among humans and that genetic control and longitudinal variation affect protein levels and biological processes to different degrees. The data further strongly suggest that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors. Moreover, we identified 13 cis-SNPs significantly influencing the level of specific plasma proteins. These results therefore have immediate implications for the effective design of blood-based biomarker studies.

OMA and OPA--software-supported mass spectra analysis of native and modified nucleic acids.

The platform-independent software package consisting of the oligonucleotide mass assembler (OMA) and the oligonucleotide peak analyzer (OPA) was created to support the analysis of oligonucleotide mass spectra. It calculates all theoretically possible fragments of a given input sequence and annotates it to an experimental spectrum, thus, saving a large amount of manual processing time. The software performs analysis of precursor and product ion spectra of oligonucleotides and their analogues comprising user-defined modifications of the backbone, the nucleobases, or the sugar moiety, as well as adducts with metal ions or drugs. The ability to expand the library of building blocks and to implement individual structural variations makes it extremely useful for supporting the analysis of therapeutically active compounds. The functionality of the software tool is demonstrated on the examples of a platinated double-stranded oligonucleotide and a modified RNA sequence. Experiments also reveal the unique dissociation behavior of platinated higher-order DNA structures.

Visualization and virtual screening of the chemical universe database GDB-17.

The chemical universe database GDB-17 contains 166.4 billion molecules of up to 17 atoms of C, N, O, S, and halogens obeying rules for chemical stability, synthetic feasibility, and medicinal chemistry. GDB-17 was analyzed using 42 integer value descriptors of molecular structure which we term "Molecular Quantum Numbers" (MQN). Principal component analysis and representation of the (PC1, PC2)-plane provided a graphical overview of the GDB-17 chemical space. Rapid ligand-based virtual screening (LBVS) of GDB-17 using the city-block distance CBD(MQN) as a similarity search measure was enabled by a hashed MQN-fingerprint. LBVS of the entire GDB-17 and of selected subsets identified shape similar, scaffold hopping analogs (ROCS > 1.6 and T(SF) < 0.5) of 15 drugs. Over 97% of these analogs occurred within CBD(MQN) ≤ 12 from each drug, a constraint which might help focus advanced virtual screening. An MQN-searchable 50 million subset of GDB-17 is publicly available at www.gdb.unibe.ch .

Enumeration of 166 billion organic small molecules in the chemical universe database GDB-17.

Drug molecules consist of a few tens of atoms connected by covalent bonds. How many such molecules are possible in total and what is their structure? This question is of pressing interest in medicinal chemistry to help solve the problems of drug potency, selectivity, and toxicity and reduce attrition rates by pointing to new molecular series. To better define the unknown chemical space, we have enumerated 166.4 billion molecules of up to 17 atoms of C, N, O, S, and halogens forming the chemical universe database GDB-17, covering a size range containing many drugs and typical for lead compounds. GDB-17 contains millions of isomers of known drugs, including analogs with high shape similarity to the parent drug. Compared to known molecules in PubChem, GDB-17 molecules are much richer in nonaromatic heterocycles, quaternary centers, and stereoisomers, densely populate the third dimension in shape space, and represent many more scaffold types.

Discovery of α7-nicotinic receptor ligands by virtual screening of the chemical universe database GDB-13.

The chemical universe database GDB-13 enumerates 977 million organic molecules up to 13 atoms of C, N, O, Cl, and S that are virtually possible following simple rules for chemical stability and synthetic feasibility. Analogs of nicotine were identified in GDB-13 using the city-block distance in MQN-space (CBD(MQN)) as a similarity measure, combined with a restriction eliminating problematic structural elements. The search was carried out with a Web browser available at www.gdb.unibe.ch . This virtual screening procedure selected 31 504 analogs of nicotine from GDB-13, from which 48 were known nicotinic ligands reported in Chembl. An additional 60 virtual screening hits were purchased and tested for modulation of the acetylcholine signal at the human α7 nAChR expressed in Xenopus oocytes, which led to the identification of three previously unknown inhibitors. These experiments demonstrate for the first time the use of GDB-13 for ligand discovery.

Visualisation of the chemical space of fragments, lead-like and drug-like molecules in PubChem.

The 4.5 million organic molecules with up to 20 non-hydrogen atoms in PubChem were analyzed using the MQN-system, which consists in 42 integer value descriptors of molecular structure. The 42-dimensional MQN-space was visualised by principal component analysis and representation of the (PC1, PC2), (PC1, PC3) and (PC2, PC3) planes. The molecules were organized according to ring count (PC1, 38% of variance), the molecular size (PC2, 25% of variance), and the H-bond acceptor count (PC3, 12% of variance). Compounds following Lipinski's bioavailability, Oprea's lead-likeness and Congreve's fragment-likeness criteria formed separated groups in MQN-space visible in the (PC2, PC3) plane. MQN-similarity searches of the 4.5 million molecules (see the browser available at www.gdb.unibe.ch ) gave significant enrichment factors for recovering groups of fragment-sized bioactive compounds related to ten different biological targets taken from Chembl, allowing lead-hopping relationships not seen with substructure fingerprint similarity searches. The diversity of different compound series was analyzed by MQN-distance histograms.

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

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 www.gdb.unibe.ch .

Exploring the chemical space of known and unknown organic small molecules at www.gdb.unibe.ch.

Organic small molecules are of particular interest for medicinal chemistry since they comprise many biologically active compounds which are potential drugs. To understand this vast chemical space, we are enumerating all possible organic molecules to create the chemical universe database GDB, which currently comprises 977 million molecules up to 13 atoms of C, N, O, Cl and S. Furthermore, we have established a simple classification method for organic molecules in form of the MQN (molecular quantum numbers) system, which is an equivalent of the periodic system of the elements. Despite its simplicity the 42 dimensional MQN system is surprisingly relevant with respect to bioactivity, as evidenced by the fact that groups of biosimilar compounds form close groups in MQN space. The MQN space of the known organic molecules in PubChem and of the unknown molecules in the Chemical Universe Database GDB-13 can be searched interactively using browser tools freely accessible at www.gdb.unibe.ch.

A searchable map of PubChem.

The database PubChem was classified using 42 integer value descriptors of molecular structure, here called molecular quantum numbers (MQNs), which count atoms and bond types, polar groups, and topological features. Principal component analysis of the MQN data set shows that PubChem compounds occupy a partially filled elliptical cone in the (PC1,PC2,PC3) space whose axis is the first principal component PC1 (65% variability) representing molecular size, and the ellipse axes are PC2 (18% variability, representing structural flexibility) and PC3 (7% variability, representing polarity). A visual overview of PubChem is provided by color-coded representations of the (PC2,PC3) plane. The MQNs form a scalar fingerprint which can be used to measure the similarity between pairs of molecules and enable ligand-based virtual screening, as illustrated for the enrichment of bioactives from the DUD data set from PubChem. An MQN-annotated version of PubChem with an MQN-similarity search tool is available at www.gdb.unibe.ch .

Identification of selective norbornane-type aspartate analogue inhibitors of the glutamate transporter 1 (GLT-1) from the chemical universe generated database (GDB).

A variety of conformationally constrained aspartate and glutamate analogues inhibit the glutamate transporter 1 (GLT-1, also known as EAAT2). To expand the search for such analogues, a virtual library of aliphatic aspartate and glutamate analogues was generated starting from the chemical universe database GDB-11, which contains 26.4 million possible molecules up to 11 atoms of C, N, O, F, resulting in 101026 aspartate analogues and 151285 glutamate analogues. Virtual screening was realized by high-throughput docking to the glutamate binding site of the glutamate transporter homologue from Pyrococcus horikoshii (PDB code: 1XFH ) using Autodock. Norbornane-type aspartate analogues were selected from the top-scoring virtual hits and synthesized. Testing and optimization led to the identification of (1R*,2R*,3S*,4R*,6R*)-2-amino-6-phenethyl-bicyclo[2.2.1]heptane-2,3-dicarboxylic acid as a new inhibitor of GLT-1 with IC(50) = 1.4 µM against GLT-1 and no inhibition of the related transporter EAAC1. The systematic diversification of known ligands by enumeration with help of GDB followed by virtual screening, synthesis, and testing as exemplified here provides a general strategy for drug discovery.

970 million druglike small molecules for virtual screening in the chemical universe database GDB-13.

GDB-13 enumerates small organic molecules containing up to 13 atoms of C, N, O, S, and Cl following simple chemical stability and synthetic feasibility rules. With 977,468,314 structures, GDB-13 is the largest publicly available small organic molecule database to date.