KNeMAP: a network mapping approach for knowledge-driven comparison of transcriptomic profiles.

Motivation: Transcriptomic data can be used to describe the mechanism of action (MOA) of a chemical compound. However, omics data tend to be complex and prone to noise, making the comparison of different datasets challenging. Often, transcriptomic profiles are compared at the level of individual gene expression values, or sets of differentially expressed genes.

Exploring cooperative molecular contacts using a PostgreSQL database system.

Cooperative molecular contacts play an important role in protein structure and ligand binding. Here, we constructed a PostgreSQL database that stores structural information in the form of atomic environments and allows flexible mining of molecular contacts. Taking the Ser-His-Asp/Glu catalytic triad as a first test case, we demonstrate that the presence of a carboxylate oxygen atom in the vicinity of a His is associated with shorter Ser-OH.

Analysis of Biologics Molecular Descriptors towards Predictive Modelling for Protein Drug Development Using Time-Gated Raman Spectroscopy.

Pharmaceutical proteins, compared to small molecular weight drugs, are relatively fragile molecules, thus necessitating monitoring protein unfolding and aggregation during production and post-marketing. Currently, many analytical techniques take offline measurements, which cannot directly assess protein folding during production and unfolding during processing and storage. In addition, several orthogonal techniques are needed during production and market surveillance.

AICAR and compound C negatively modulate HCC-induced primary human hepatic stellate cell activation in vitro.

Tumor stroma and microenvironment have been shown to affect hepatocellular carcinoma (HCC) growth, with activated hepatic stellate cells (HSC) as a major contributor in this process. Recent evidence suggests that the energy sensor adenosine monophosphate-activated kinase (AMPK) may mediate a series of essential processes during carcinogenesis and HCC progression. Here, we investigated the effect of different HCC cell lines with known or mutations on primary human HSC activation, proliferation, and AMPK activation.

Binding Site Interactions of Modulators of Breast Cancer Resistance Protein, Multidrug Resistance-Associated Protein 2, and P-Glycoprotein Activity.

ATP-binding cassette (ABC)-transporters protect tissues by pumping their substrates out of the cells in many physiological barriers, such as the blood-brain barrier, intestine, liver, and kidney. These substrates include various endogenous metabolites, but, in addition, ABC transporters recognize a wide range of compounds, therefore affecting the disposition and elimination of clinically used drugs and their metabolites. Although numerous ABC-transporter inhibitors are known, the underlying mechanism of inhibition is not well characterized.

Tamoxifen mechanically deactivates hepatic stellate cells via the G protein-coupled estrogen receptor.

Tamoxifen has been used for many years to target estrogen receptor signalling in breast cancer cells. Tamoxifen is also an agonist of the G protein-coupled estrogen receptor (GPER), a GPCR ubiquitously expressed in tissues that mediates the acute response to estrogens. Here we report that tamoxifen promotes mechanical quiescence in hepatic stellate cells (HSCs), stromal fibroblast-like cells whose activation triggers and perpetuates liver fibrosis in hepatocellular carcinomas.

Predictive classification models and targets identification for betulin derivatives as Leishmania donovani inhibitors.

Betulin derivatives have been proven effective in vitro against Leishmania donovani amastigotes, which cause visceral leishmaniasis. Identifying the molecular targets and molecular mechanisms underlying their action is a currently an unmet challenge. In the present study, we tackle this problem using computational methods to establish properties essential for activity as well as to screen betulin derivatives against potential targets.

Adenosine analogs bearing phosphate isosteres as human MDO1 ligands.

The human O-acetyl-ADP-ribose deacetylase MDO1 is a mono-ADP-ribosylhydrolase involved in the reversal of post-translational modifications. Until now MDO1 has been poorly characterized, partly since no ligand is known besides adenosine nucleotides. Here, we synthesized thirteen compounds retaining the adenosine moiety and bearing bioisosteric replacements of the phosphate at the ribose 5'-oxygen.

Structural Isosteres of Phosphate Groups in the Protein Data Bank.

We developed a computational workflow to mine the Protein Data Bank for isosteric replacements that exist in different binding site environments but have not necessarily been identified and exploited in compound design. Taking phosphate groups as examples, the workflow was used to construct 157 data sets, each composed of a reference protein complexed with AMP, ADP, ATP, or pyrophosphate as well other ligands. Phosphate binding sites appear to have a high hydration content and large size, resulting in U-shaped bioactive conformations recurrently found across unrelated protein families.

A structure-activity relationship study of ABCC2 inhibitors.

Multidrug resistance associated protein 2 (MRP2/ABCC2) is a membrane transport protein that can potentially affect the disposition of many substrate drugs and their metabolites. Recently, we studied the interaction of a library of 432 compounds with ABCC2, and the structure-activity relationship (SAR) of a subset of 64 compounds divided into four scaffolds (Wissel, G. et al.

Predictive Modeling of Ocular Pharmacokinetics and Adverse Effects.

Treatment of ocular disorders is a challenge due to the difficulty of delivering drugs to the target tissues within the eye at sufficient concentrations to produce a therapeutic effect. The cornea and the blood-retinal barrier, comprising of the retinal pigment epithelium and the retinal capillaries, are the main barriers for delivering drugs to treat diseases in the anterior and posterior parts of the eye, respectively. The eye has a rich blood supply and relatively small mass, and drugs can distribute from the systemic blood circulation to the choroid through the fenestrated choroidal blood vessels, but further permeation into the eye is limited by the blood-retinal barrier.

IDAAPM: integrated database of ADMET and adverse effects of predictive modeling based on FDA approved drug data.

Background: The disposition of a pharmaceutical compound within an organism, i.e. its Absorption, Distribution, Metabolism, Excretion, Toxicity (ADMET) properties and adverse effects, critically affects late stage failure of drug candidates and has led to the withdrawal of approved drugs.

Exploring the structure-activity relationships of ABCC2 modulators using a screening approach.

ABCC2 is a transporter with key influence on liver and kidney pharmacokinetics. In order to explore the structure-activity relationships of compounds that modulate ABCC2, and by doing so gain insights into drug-drug interactions, we screened a library of 432 compounds for modulators of radiolabeled β-estradiol 17-(β-d-glucuronide) (EG) and fluorescent 5(6)-carboxy-2',7'-dichlorofluorescein transport (CDCF) in membrane vesicles. Following the primary screen at 80μM, dose-response curves were used to investigate in detail 86 compounds, identifying 16 low μM inhibitors and providing data about the structure-activity relationships in four series containing 19, 24, 10, and eight analogues.

Integrated in vitro-in silico screening strategy for the discovery of antibacterial compounds.

Multidrug-resistant bacterial infections are an increasing source of healthcare problems, and the research for new antibiotics is currently unable to respond to this challenge. In this work, we present a screening strategy that integrates cell-based high-throughput screening (HTS) with in silico analogue search for antimicrobial small-molecule drug discovery. We performed an HTS on a diverse chemical library by using an assay based on a bioluminescent Escherichia coli K-12 (pTetLux1) strain.

SVM classification and CoMSIA modeling of UGT1A6 interacting molecules.

The human UDP-glucuronosyltransferase 1A6 (UGT1A6) plays important roles in elimination of many xenobiotics, including drugs. We have experimentally assessed inhibitory properties of 46 compounds toward UGT1A6 catalyzing the glucuronidation of 1-naphthol and built models for predicting compounds interactions with the enzyme. The tested compounds were divided into a training set (n = 31; evaluated by 10-fold cross-validation) and an external test set (n = 15), both of which yielded similar accuracies (80-81%) and Matthews correlation coefficients (0.

Applying linear and non-linear methods for parallel prediction of volume of distribution and fraction of unbound drug.

Volume of distribution and fraction unbound are two key parameters in pharmacokinetics. The fraction unbound describes the portion of free drug in plasma that may extravasate, while volume of distribution describes the tissue access and binding of a drug. Reliable in silico predictions of these pharmacokinetic parameters would benefit the early stages of drug discovery, as experimental measuring is not feasible for screening purposes.

Retrospective molecular docking study of WY-25105 ligand to β-secretase and bias of the three-dimensional structure flexibility.

β-Secretase (BACE) is a very promising target in the search for a treatment for Alzheimer's disease using a protein-ligand inhibition approach. Given the many published X-ray structures of BACE protein, structure-based drug design has been used extensively to support new inhibitor discovery programs. Due to the high flexibility and large catalytic site of this protein, sampling of the huge conformational space of the binding site is the big challenge to overcome and is the main limitation of the most widely used docking programs.

Recent trends and applications in 3D virtual screening.

Virtual screening (VS) is becoming an increasingly important approach for identifying and selecting biologically active molecules against specific pharmaceutically relevant targets. Compared to conventional high throughput screening techniques, in silico screening is fast and inexpensive, and is increasing in popularity in early-stage drug discovery endeavours. This paper reviews and discusses recent trends and developments in three-dimensional (3D) receptor-based and ligand-based VS methodologies.

Comparison of three preprocessing filters efficiency in virtual screening: identification of new putative LXRbeta regulators as a test case.

In silico screening methodologies are widely recognized as efficient approaches in early steps of drug discovery. However, in the virtual high-throughput screening (VHTS) context, where hit compounds are searched among millions of candidates, three-dimensional comparison techniques and knowledge discovery from databases should offer a better efficiency to finding novel drug leads than those of computationally expensive molecular dockings. Therefore, the present study aims at developing a filtering methodology to efficiently eliminate unsuitable compounds in VHTS process.

Multiple-step virtual screening using VSM-G: overview and validation of fast geometrical matching enrichment.

Numerous methods are available for use as part of a virtual screening strategy but, as yet, no single method is able to guarantee both a level of confidence comparable to experimental screening and a level of computing efficiency that could drastically cut the costs of early phase drug discovery campaigns. Here, we present VSM-G (virtual screening manager for computational grids), a virtual screening platform that combines several structure-based drug design tools. VSM-G aims to be as user-friendly as possible while retaining enough flexibility to accommodate other in silico techniques as they are developed.