MOTIVATION: Antibodies are an important class of biological drugs, but with limitations, such as inadequate pharmacokinetics, adverse immunogenicity and high production costs. Synthetic peptides for the desired target represent an important alternative to antibodies. However, no computational tool exists to guide the design of these peptides. RESULTS: To identify the interacting residues in a given antibody-antigen (Ab-Ag) interface we used Interface Interacting Residue (I2R), a selection method based on computed molecular interactions. The aggregation of all the molecular interactions between epitope and paratope residues allowed us to transform the 3D Ab-Ag complex structures into interface graphs. Based on these data and the probability of molecular interaction we developed EPI-Peptide Designer tool that uses predicted paratope residues for an epitope of interest to generate targeted peptide ligand libraries. EPI-Peptide Designer successfully predicted 301 peptides able to bind to LiD1 target protein (65% of the experimentally tested peptides), an enrichment of 22% compared to randomly generated peptides. This tool should enable the development of a new generation of synthetic interacting peptides that could be very useful in the biosensor, diagnostic and therapeutic fields. AVAILABILITY AND IMPLEMENTATION: All software developed in this work are available at http://www.biocomp.icb.ufmg.br/biocomp/ CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: Synthetic biology studies how to design and construct biological systems with functions that do not exist in nature. Biochemical networks, although easier to control, have been used less frequently than genetic networks as a base to build a synthetic system. To date, no clear engineering principles exist to design such cell-free biochemical networks. RESULTS: We describe a methodology for the construction of synthetic biochemical networks based on three main steps: design, simulation and experimental validation. We developed BioNetCAD to help users to go through these steps. BioNetCAD allows designing abstract networks that can be implemented thanks to CompuBioTicDB, a database of parts for synthetic biology. BioNetCAD enables also simulations with the HSim software and the classical Ordinary Differential Equations (ODE). We demonstrate with a case study that BioNetCAD can rationalize and reduce further experimental validation during the construction of a biochemical network. AVAILABILITY AND IMPLEMENTATION: BioNetCAD is freely available at http://www.sysdiag.cnrs.fr/BioNetCAD. It is implemented in Java and supported on MS Windows. CompuBioTicDB is freely accessible at http://compubiotic.sysdiag.cnrs.fr/.