Corrigendum: Computer-assisted quantification of motile and invasive capabilities of cancer cells.

This corrects the article DOI: 10.1038/srep15338.

Native Electrospray Ionization Mass Spectrometry Reveals Multiple Facets of Aptamer-Ligand Interactions: From Mechanism to Binding Constants.

Aptamers are oligonucleotide receptors obtained through an iterative selection process from random-sequence libraries. Though many aptamers for a broad range of targets with high affinity and selectivity have been generated, a lack of high-resolution structural data and the limitations of currently available biophysical tools greatly impede understanding of the mechanisms of aptamer-ligand interactions. Here we demonstrate that an approach based on native electrospray ionization mass spectrometry (ESI-MS) can be successfully applied to characterize aptamer-ligand complexes in all details.

Rational Design of Membrane-Pore-Forming Peptides.

Specific interactions of peptides with lipid membranes are essential for cellular communication and constitute a central aspect of the innate host defense against pathogens. A computational method for generating innovative membrane-pore-forming peptides inspired by natural templates is presented. Peptide representation in terms of sequence- and topology-dependent hydrophobic moments is introduced.

Computer-assisted quantification of motile and invasive capabilities of cancer cells.

High-throughput analysis of cancer cell dissemination and its control by extrinsic and intrinsic cellular factors is hampered by the lack of adequate and efficient analytical tools for quantifying cell motility. Oncology research would greatly benefit from such a methodology that allows to rapidly determine the motile behaviour of cancer cells under different environmental conditions, including inside three-dimensional matrices. We combined automated microscopy imaging of two- and three-dimensional cell cultures with computational image analysis into a single assay platform for studying cell dissemination in high-throughput.

Piloting the membranolytic activities of peptides with a self-organizing map.

Antimicrobial peptides (AMPs) show remarkable selectivity toward lipid membranes and possess promising antibiotic potential. Their modes of action are diverse and not fully understood, and innovative peptide design strategies are needed to generate AMPs with improved properties. We present a de novo peptide design approach that resulted in new AMPs possessing low-nanomolar membranolytic activities.

Inhibiting HtrA protease by addressing a computationally predicted allosteric ligand binding site.

is associated with inflammatory diseases and can cause gastric cancer and mucosa-associated lymphoma. One of the bacterium's key proteins is high temperature requirement A (HtrA) protein, an extracellular serine protease that cleaves E-cadherin of gastric epithelial cells, which leads to loss of cell-cell adhesion. Inhibition of HtrA may constitute an intervention strategy against infection.

Deorphaning pyrrolopyrazines as potent multi-target antimalarial agents.

The discovery of pyrrolopyrazines as potent antimalarial agents is presented, with the most effective compounds exhibiting EC50 values in the low nanomolar range against asexual blood stages of Plasmodium falciparum in human red blood cells, and Plasmodium berghei liver schizonts, with negligible HepG2 cytotoxicity. Their potential mode of action is uncovered by predicting macromolecular targets through avant-garde computer modeling. The consensus prediction method suggested a functional resemblance between ligand binding sites in non-homologous target proteins, linking the observed parasite elimination to IspD, an enzyme from the non-mevalonate pathway of isoprenoid biosynthesis, and multi-kinase inhibition.

Aminothiazole-featured pirinixic acid derivatives as dual 5-lipoxygenase and microsomal prostaglandin E2 synthase-1 inhibitors with improved potency and efficiency in vivo.

Dual inhibition of microsomal prostaglandin E2 synthase-1 (mPGES-1) and 5-lipoxygenase (5-LO) is currently pursued as potential pharmacological strategy for treatment of inflammation and cancer. Here we present a series of 26 novel 2-aminothiazole-featured pirinixic acid derivatives as dual 5-LO/mPGES-1 inhibitors with improved potency (exemplified by compound 16 (2-[(4-chloro-6-{[4-(naphthalen-2-yl)-1,3-thiazol-2-yl]amino}pyrimidin-2-yl)sulfanyl]octanoic acid) with IC50 = 0.3 and 0.

Exhaustive proteome mining for functional MHC-I ligands.

We present the development and application of a new machine-learning approach to exhaustively and reliably identify major histocompatibility complex class I (MHC-I) ligands among all 20(8) octapeptides and in genome-derived proteomes of Mus musculus , influenza A H3N8, and vesicular stomatitis virus (VSV). Focusing on murine H-2K(b), we identified potent octapeptides exhibiting direct MHC-I binding and stabilization on the surface of TAP-deficient RMA-S cells. Computationally identified VSV-derived peptides induced CD8(+) T-cell proliferation after VSV-infection of mice.

Scrutinizing MHC-I binding peptides and their limits of variation.

Designed peptides that bind to major histocompatibility protein I (MHC-I) allomorphs bear the promise of representing epitopes that stimulate a desired immune response. A rigorous bioinformatical exploration of sequence patterns hidden in peptides that bind to the mouse MHC-I allomorph H-2K(b) is presented. We exemplify and validate these motif findings by systematically dissecting the epitope SIINFEKL and analyzing the resulting fragments for their binding potential to H-2K(b) in a thermal denaturation assay.

Computational Resources for MHC Ligand Identification.

Advances in the high-throughput determination of functional modulators of major histocompatibility complex (MHC) and improved computational predictions of MHC ligands have rendered the rational design of immunomodulatory peptides feasible. Proteome-derived peptides and 'reverse vaccinology' by computational means will play a driving role in future vaccine design. Here we review the molecular mechanisms of the MHC mediated immune response, present the computational approaches that have emerged in this area of biotechnology, and provide an overview of publicly available computational resources for predicting and designing new peptidic MHC ligands.

Adaptive peptide design.

Computer algorithms help in the identification and optimization of peptides with desired structure and function. We provide an overview of the current focus of our research group in this field, highlighting innovative methods for peptide representation and de novo peptide generation. Our evolutionary molecular design cycle contains structure-activity relationship modeling by machine-learning methods, virtual peptide generation, activity prediction, peptide syntheses, as well as biophysical and biochemical activity determination.

Virtual screening for compounds that mimic protein-protein interface epitopes.

Modulation of protein-protein interactions (PPI) has emerged as a new concept in rational drug design. Here, we present a computational protocol for identifying potential PPI inhibitors. Relevant regions of interfaces (epitopes) are predicted for three-dimensional protein models and serve as queries for virtual compound screening.