Intramolecular Hydrogen Bond Expectations in Medicinal Chemistry

Design strategies centered on intramolecular hydrogen bonds are sometime used in drug discovery, but their general applicability has not been addressed beyond scattered examples or circumstantial evidence. A total of 1053 matched molecular pairs where only one of the two molecules is able to form an intramolecular hydrogen bond via monatomic transformations have been identified across the ChEMBL database. These pairs were used to investigate the effect of intramolecular hydrogen bonds on biological activity. While cases of extreme, conflicting variation of effect emerge, the mean biological activity difference for a pair is close to zero and does not exceed ±0.5 log biological activity for over 50% of the analyzed sample

Exploiting Structural Information in Patent Specifications for Key Compound Prediction

Patent specifications are one of many information sources needed to progress drug discovery projects. Understanding compound prior art and novelty checking, validation of biological assays, and identification of new starting points for chemical explorations are a few areas where patent analysis is an important component. Cheminformatics methods can be used to facilitate the identification of so-called key compounds in patent specifications. Such methods, relying on structural information extracted from documents by expert curation or text mining, can complement or in some cases replace the traditional manual approach of searching for clues in the text. This paper describes and compares three different methods for the automatic prediction of key compounds in patent specifications using structural information alone. For this data set, the cluster seed analysis described by Hattori et al. (Hattori, K.; Wakabayashi, H.; Tamaki, K. Predicting key example compounds in competitors' patent applications using structural information alone. <i>J. Chem. Inf. Model.</i> <b>2008</b>, <i>48</i>, 135–142) is superior in terms of prediction accuracy with 26 out of 48 drugs (54%) correctly predicted from their corresponding patents. Nevertheless, the two new methods, based on frequency of R-groups (FOG) and maximum common substructure (MCS) similarity measures, show significant advantages due to their inherent ability to visualize relevant structural features. The results of the FOG method can be enhanced by manual selection of the scaffolds used in the analysis. Finally, a successful example of applying FOG analysis for designing potent ATP-competitive AXL kinase inhibitors with improved properties is described

Binding Mode and Induced Fit Predictions for Prospective Computational Drug Design

Computer-aided drug design plays an important role in medicinal chemistry to obtain insights into molecular mechanisms and to prioritize design strategies. Although significant improvement has been made in structure based design, it still remains a key challenge to accurately model and predict induced fit mechanisms. Most of the current available techniques either do not provide sufficient protein conformational sampling or are too computationally demanding to fit an industrial setting. The current study presents a systematic and exhaustive investigation of predicting binding modes for a range of systems using PELE (Protein Energy Landscape Exploration), an efficient and fast protein–ligand sampling algorithm. The systems analyzed (cytochrome P, kinase, protease, and nuclear hormone receptor) exhibit different complexities of ligand induced fit mechanisms and protein dynamics. The results are compared with results from classical molecular dynamics simulations and (induced fit) docking. This study shows that ligand induced side chain rearrangements and smaller to medium backbone movements are captured well in PELE. Large secondary structure rearrangements, however, remain challenging for all employed techniques. Relevant binding modes (ligand heavy atom RMSD < 1.0 Å) can be obtained by the PELE method within a few hours of simulation, positioning PELE as a tool applicable for rapid drug design cycles

New Hits as Antagonists of GPR103 Identified by HTS

Preclinical data indicate that GPR103 receptor and its endogenous neuropeptides QRFP26 and QRFP43 are involved in appetite regulation. A high throughput screening (HTS) for small molecule GPR103 antagonists was performed with the clinical goal to target weight management by modulation of appetite. A high hit rate from the HTS and initial low confirmation with respect to functional versus affinity data challenged us to revise the established screening cascade. To secure high quality data while increasing throughput, the binding assay was optimized on quality to run at single concentration. This strategy enabled evaluation of a larger fraction of chemical clusters and singletons delivering 17 new compound classes for GPR103 antagonism. Representative compounds from three clusters are presented. One of the identified clusters was further investigated, and an initial structure–activity relationship study is reported. The most potent compound identified had a pIC₅₀ of 7.9 with an improved ligand lipophilic efficiency

Theoretical Studies of Chemical Reactivity of Metabolically Activated Forms of Aromatic Amines toward DNA

The metabolism of aromatic and heteroaromatic amines (ArNH₂) results in nitrenium ions (ArNH⁺) that modify nucleobases of DNA, primarily deoxyguanosine (dG), by forming dG-C8 adducts. The activated amine nitrogen in ArNH⁺ reacts with the C8 of dG, which gives rise to mutations in DNA. For the most mutagenic ArNH₂, including the majority of known genotoxic carcinogens, the stability of ArNH⁺ is of intermediate magnitude. To understand the origin of this observation as well as the specificity of reactions of ArNH⁺ with guanines in DNA, we investigated the chemical reactivity of the metabolically activated forms of ArNH₂, that is, ArNHOH and ArNHOAc, toward 9-methylguanine by DFT calculations. The chemical reactivity of these forms is determined by the rate constants of two consecutive reactions leading to cationic guanine intermediates. The formation of ArNH⁺ accelerates with resonance stabilization of ArNH⁺, whereas the formed ArNH⁺ reacts with guanine derivatives with the constant diffusion-limited rate until the reaction slows down when ArNH⁺ is about 20 kcal/mol more stable than PhNH⁺. At this point, ArNHOH and ArNHOAc show maximum reactivity. The lowest activation energy of the reaction of ArNH⁺ with 9-methylguanine corresponds to the charge-transfer π-stacked transition state (π-TS) that leads to the direct formation of the C8 intermediate. The predicted activation barriers of this reaction match the observed absolute rate constants for a number of ArNH⁺. We demonstrate that the mutagenic potency of ArNH₂ correlates with the rate of formation and the chemical reactivity of the metabolically activated forms toward the C8 atom of dG. On the basis of geometric consideration of the π-TS complex made of genotoxic compounds with long aromatic systems, we propose that precovalent intercalation in DNA is not an essential step in the genotoxicity pathway of ArNH₂. The mechanism-based reasoning suggests rational design strategies to avoid genotoxicity of ArNH₂ primarily by preventing N-hydroxylation of ArNH₂

The deubiquitinase USP7 uses a distinct ubiquitin-like domain to deubiquitinate NF-kB subunits

The transcription factor NF-kB is a master regulator of the innate immune response and plays a central role in inflammatory diseases by mediating the expression of pro-inflammatory cytokines.Ubiquitination-triggered proteasomal degradation of DNA-bound NF-kB strongly limits the expression of its target genes. Conversely, USP7 (deubiquitinase ubiquitin-specific peptidase7) opposes the activities of E3ligases,stabilizes DNAbound NF-kB, and thereby promotes NF-kB–mediated transcription. Using gene expression and synthetic peptide arrays on membrane support and overlay analyses, we found here that inhibiting USP7 increases NF-kB ubiquitination and degradation, prevents Toll-like receptor–induced pro-inflammatory cytokine expression, and represents an effective strategy for controlling inflammation. However, the broad regulatory roles of USP7 in cell death pathways, chromatin, and DNA damage responses limit the use of catalytic inhibitors of USP7 as anti inflammatory agents. To this end,we identified nNF-kB–binding site in USP7, ubiquitin-like domain 2, that selectively mediates interactions of USP7 with NF-kB subunits but is dispensable for interactions with other proteins. Moreover, we found that the amino acids 757LDEL760 in USP7 critically contribute to the interaction with the p65 subunit of NF-ŒB. Our findings support the notion that USP7 activity could be potentially targeted in a substrate-selective manner through the development of noncatalytic inhibitors of this deubiquitinase to abrogate NF-kB activity

Inter-annotator agreement (F-score) without ambiguity resolution.

<p>Inter-annotator agreement (F-score) without ambiguity resolution.</p

Annotated Chemical Patent Corpus: A Gold Standard for Text Mining - Figure 1

<p>Example patent text with pre-annotations as shown by the Brat annotation tool.</p

Number of annotated terms and unique terms in the harmonized set and in the full patent set of the gold standard corpus after disambiguation.

<p>Number of annotated terms and unique terms in the harmonized set and in the full patent set of the gold standard corpus after disambiguation.</p

Target class distribution of the 8,066 patents from which the final set was drawn.

<p>Target class distribution of the 8,066 patents from which the final set was drawn.</p