In the big data era, voluminous datasets are routinely acquired, stored and analyzed with the aim to inform biomedical discoveries and validate hypotheses. No doubt, data volume and diversity have dramatically increased by the advent of new technologies and open data initiatives. Big data are used across the whole drug discovery pipeline from target identification and mechanism of action to identification of novel leads and drug candidates. Such methods are depicted and discussed, with the aim to provide a general view of computational tools and databases available. We feel that big data leveraging needs to be cost-effective and focus on personalized medicine. For this, we propose the interplay of information technologies and (chemo)informatic tools on the basis of their synergy.

G protein-coupled receptors (GPCRs) are involved in numerous physiological processes and are the most frequent targets of approved drugs. The explosion in the number of new 3D molecular structures of GPCRs (3D-GPCRome) during the last decade has greatly advanced the mechanistic understanding and drug design opportunities for this protein family. Molecular dynamics (MD) simulations have become a widely established technique to explore the conformational landscape of proteins at an atomic level. However, the analysis and visualization of MD simulations require efficient storage resources and specialized software. Here we present GPCRmd (http://gpcrmd.org/), an online platform that incorporates web-based visualization capabilities as well as a comprehensive and user-friendly analysis toolbox that allows scientists from different disciplines to visualize, analyse and share GPCR MD data.GPCRmd originates from a community-driven effort to create the first open, interactive, and standardized database of GPCR MD simulations.However, static high-resolution structures provide little information on the intrinsic 71 flexibility of GPCRs, a key aspect to fully understand their function. Important advances 72

Peptides and proteins are attractive initial leads for the rational design of bioactive molecules. Several natural cyclic peptides have recently emerged as templates for drug design due to their resistance to chemical or enzymatic hydrolysis and high selectivity to receptors. The development of practical protocols that mimic the power of nature's strategies remains paramount for the advancement of novel peptide-based drugs. The de novo design of peptide mimetics (nonpeptide molecules or cyclic peptides) for the synthesis of linear or cyclic peptides has enhanced the progress of therapeutics and diverse areas of science and technology. In the case of metabolically unstable peptide ligands, the rational design and synthesis of cyclic peptide analogues has turned into an alternative approach for improved biological activity.

Derangement of cellular immunity is central in the pathophysiology of multiple sclerosis (MS) and is often manifested by abnormal cytokine production. We investigated cytokine secretion in peripheral blood mononuclear cells (PBMC) of 18 MS patients and 15 controls and correlated cytokine polarization with the nature of antigenic stimulus. We synthesized two novel citrullinated peptides, linear [Cit(91), Ala(96), Cit(97)]MBP(87-99) and cyclo(87-99)[Cit(91), Ala(96), Cit(97)]MBP(87-99) that resulted from citrullination of 91,97 Arg residues in antagonists, linear [Arg(91), Ala(96)]MBP(87-99) and cyclo(87-99)[Arg(91), Ala(96)]MBP(87-99) peptides. PBMC from MS patients and controls were cultured with citrullinated peptides, and both peptides caused a Th1 polarization in all MS patients studied. In contrast, culture with noncitrullinated MBP peptides resulted in heterogeneous cytokine secretion that differed between individual patients. Thus, citrullination of self-antigens may potentially trigger disease in susceptible individuals. This finding may open new avenues in drug design of new substances that inhibit citrullination and arrest epitope spreading and worsening of MS.