Analyzing compound activity records and promiscuity degrees in light of publication statistics.

For the generation of contemporary databases of bioactive compounds, activity information is usually extracted from the scientific literature. However, when activity data are analyzed, source publications are typically no longer taken into consideration. Therefore, compound activity data selected from ChEMBL were traced back to thousands of original publications, activity records including compound, assay, and target information were systematically generated, and their distributions across the literature were determined.

Binding mode similarity measures for ranking of docking poses: a case study on the adenosine A2A receptor.

We report an investigation designed to explore alternative approaches for ranking of docking poses in the search for antagonists of the adenosine A2A receptor, an attractive target for structure-based virtual screening. Calculation of 3D similarity of docking poses to crystallographic ligand(s) as well as similarity of receptor-ligand interaction patterns was consistently superior to conventional scoring functions for prioritizing antagonists over decoys. Moreover, the use of crystallographic antagonists and agonists, a core fragment of an antagonist, and a model of an agonist placed into the binding site of an antagonist-bound form of the receptor resulted in a significant early enrichment of antagonists in compound rankings.

Evaluation of bisbenzamidines as inhibitors for matriptase-2.

The serine protease matriptase-2 has attracted much attention as a potential target for the treatment of iron overload diseases. In this study, a series of 27 symmetric, achiral bisbenzamidines was evaluated for inhibitory activity against human matriptase-2, against the closely related enzyme human matriptase, as well as against human thrombin, bovine factor Xa and human trypsin. The conformationally restricted piperazine derivative 19 and the oxamide-derived bisbenzamidine 1 were identified as the most potent inhibitors of this series for matriptase-2 and matriptase, respectively.

Phosphono Bisbenzguanidines as Irreversible Dipeptidomimetic Inhibitors and Activity-Based Probes of Matriptase-2.

Matriptase-2, a type II transmembrane serine protease, plays a key role in human iron homeostasis. Inhibition of matriptase-2 is considered as an attractive strategy for the treatment of iron-overload diseases, such as hemochromatosis and β-thalassemia. In the present study, synthetic routes to nine dipeptidomimetic inactivators were developed.

Activity-relevant similarity values for fingerprints and implications for similarity searching.

A largely unsolved problem in chemoinformatics is the issue of how calculated compound similarity relates to activity similarity, which is central to many applications. In general, activity relationships are predicted from calculated similarity values. However, there is no solid scientific foundation to bridge between calculated molecular and observed activity similarity.

Determining the Degree of Promiscuity of Extensively Assayed Compounds.

In the context of polypharmacology, an emerging concept in drug discovery, promiscuity is rationalized as the ability of compounds to specifically interact with multiple targets. Promiscuity of drugs and bioactive compounds has thus far been analyzed computationally on the basis of activity annotations, without taking assay frequencies or inactivity records into account. Most recent estimates have indicated that bioactive compounds interact on average with only one to two targets, whereas drugs interact with six or more.

Lessons learned from the design of chemical space networks and opportunities for new applications.

The concept of chemical space is of fundamental relevance in chemical informatics and computer-aided drug discovery. In a series of articles published in the Journal of Computer-Aided Molecular Design, principles of chemical space design were evaluated, molecular networks proposed as an alternative to conventional coordinate-based chemical reference spaces, and different types of chemical space networks (CSNs) constructed and analyzed. Central to the generation of CSNs was the way in which molecular similarity relationships were assessed and a primary focal point was the network-based representation of biologically relevant chemical space.

Three-Dimensional Similarity in Molecular Docking: Prioritizing Ligand Poses on the Basis of Experimental Binding Modes.

Molecular docking is the premier approach to structure-based virtual screening. While ligand posing is often successful, compound ranking using force field-based scoring functions remains difficult. Uncertainties associated with scoring often limit the ability to confidently identify new active compounds.

AnalogExplorer2 - Stereochemistry sensitive graphical analysis of large analog series.

AnalogExplorer is a computational methodology for the extraction and organization of series of structural analogs from compound data sets and their graphical analysis. The method is suitable for the analysis of large analog series originating from lead optimization programs. Herein we report AnalogExplorer2 designed to explicitly take stereochemical information during graphical analysis into account and describe a freely available deposition of the original AnalogExplorer program, AnalogExplorer2, and exemplary compound sets to illustrate their use.

On the evolving open peer review culture for chemical information science.

Compared to the traditional anonymous peer review process, open post-publication peer review provides additional opportunities -and challenges- for reviewers to judge scientific studies. In this editorial, we comment on the open peer review culture and provide some guidance for reviewers of manuscripts submitted to the Chemical Information Science channel of F1000Research.

One-pot synthesis of tetrazole-1,2,5,6-tetrahydronicotinonitriles and cholinesterase inhibition: Probing the plausible reaction mechanism via computational studies.

In the present study, one-pot synthesis of 1H-tetrazole linked 1,2,5,6-tetrahydronicotinonitriles under solvent-free conditions have been carried out in the presence of tetra-n-butyl ammonium fluoride trihydrated (TBAF) as catalyst and solvent. Computational studies have been conducted to elaborate two plausible mechanistic pathways of this one-pot reaction. Moreover, the synthesized compounds were screened for cholinesterases (acetylcholinesterase and butyrylcholinesterase) inhibition which are consider to be major malefactors of Alzheimer's disease (AD) to find lead compounds for further research in AD therapy.

Computational Exploration of Molecular Scaffolds in Medicinal Chemistry.

The scaffold concept is widely applied in medicinal chemistry. Scaffolds are mostly used to represent core structures of bioactive compounds. Although the scaffold concept has limitations and is often viewed differently from a chemical and computational perspective, it has provided a basis for systematic investigations of molecular cores and building blocks, going far beyond the consideration of individual compound series.

Assessing the Growth of Bioactive Compounds and Scaffolds over Time: Implications for Lead Discovery and Scaffold Hopping.

The increase in compounds with activity against five major therapeutic target families has been quantified on a time scale and investigated employing a compound-scaffold-cyclic skeleton (CSK) hierarchy. The analysis was designed to better understand possible reasons for target-dependent growth of bioactive compounds. There was strong correlation between compound and scaffold growth across all target families.

En Route to New Therapeutic Options for Iron Overload Diseases: Matriptase-2 as a Target for Kunitz-Type Inhibitors.

The cell-surface serine protease matriptase-2 is a critical stimulator of iron absorption by negatively regulating hepcidin, the key hormone of iron homeostasis. Thus, it has attracted much attention as a target in primary and secondary iron overload diseases. Here, we have characterised Kunitz-type inhibitors hepatocyte growth factor activator inhibitor 1 (HAI-1) and HAI-2 as powerful, slow-binding matriptase-2 inhibitors.

Design of chemical space networks on the basis of Tversky similarity.

Chemical space networks (CSNs) have been introduced as a coordinate-free representation of chemical space. In CSNs, nodes represent compounds and edges pairwise similarity relationships. These network representations are mostly used to navigate sections of biologically relevant chemical space.

Limiting the Number of Potential Binding Modes by Introducing Symmetry into Ligands: Structure-Based Design of Inhibitors for Trypsin-Like Serine Proteases.

In the absence of X-ray data, the exploration of compound binding modes continues to be a challenging task. For structure-based design, specific features of active sites in different targets play a major role in rationalizing ligand binding characteristics. For example, dibasic compounds have been reported as potent inhibitors of various trypsin-like serine proteases, the active sites of which contain several binding pockets that can be targeted by cationic moieties.

Berberine Reduces Neurotoxicity Related to Nonalcoholic Steatohepatitis in Rats.

Berberine is a plant alkaloid that has several pharmacological effects such as antioxidant, antilipidemic, and anti-inflammatory effects. Nonalcoholic steatohepatitis (NASH) triggers different aspects of disorders such as impaired endogenous lipid metabolism, hypercholesterolemia, oxidative stress, and neurotoxicity. In this study, we examined the mechanism by which NASH induces neurotoxicity and the protective effect of berberine against both NASH and its associated neurotoxicity.

Monitoring the Progression of Structure-Activity Relationship Information during Lead Optimization.

Lead optimization (LO) in medicinal chemistry is largely driven by hypotheses and depends on the ingenuity, experience, and intuition of medicinal chemists, focusing on the key question of which compound should be made next. It is essentially impossible to predict whether an LO project might ultimately be successful, and it is also very difficult to estimate when a sufficient number of compounds has been evaluated to judge the odds of a project. Given the subjective nature of LO decisions and the inherent optimism of project teams, very few attempts have been made to systematically evaluate project progression.

Design of chemical space networks using a Tanimoto similarity variant based upon maximum common substructures.

Chemical space networks (CSNs) have recently been introduced as an alternative to other coordinate-free and coordinate-based chemical space representations. In CSNs, nodes represent compounds and edges pairwise similarity relationships. In addition, nodes are annotated with compound property information such as biological activity.

Systematic Assessment of Molecular Selectivity at the Level of Targets, Bioactive Compounds, and Structural Analogues.

Through systematic mining of compound activity data, the target selectivity of bioactive compounds was systematically explored. The analysis was facilitated by applying, extending, and combining the concepts of target cliffs, selectivity cliffs, and matched molecular pairs. Selectivity relationships were explored at different levels including targets, individual bioactive compounds, and pairs of structural analogues.

Monitoring global growth of activity cliff information over time and assessing activity cliff frequencies and distributions.

Background: Activity cliffs (ACs) are formed by structurally analogous compounds with large potency variations. In medicinal chemistry, ACs are focal points of structure-activity relationship (SAR) analysis and typically studied on the basis of individual compound series.

Results: ACs have been investigated on a large scale by analyzing active compounds from medicinal chemistry sources covering current pharmaceutical targets.