PhosY-secretome profiling combined with kinase-substrate interaction screening defines active c-Src-driven extracellular signaling.

c-Src tyrosine kinase is a renowned key intracellular signaling molecule and a potential target for cancer therapy. Secreted c-Src is a recent observation, but how it contributes to extracellular phosphorylation remains elusive. Using a series of domain deletion mutants, we show that the N-proximal region of c-Src is essential for its secretion. The tissue inhibitor of metalloproteinases 2 (TIMP2) is an extracellular substrate of c-Src. Limited proteolysis-coupled mass spectrometry and mutagenesis studies verify that the Src homology 3 (SH3) domain of c-Src and the P31VHP34 motif of TIMP2 are critical for their interaction. Comparative phosphoproteomic analyses identify an enrichment of PxxP motifs in phosY-containing secretomes from c-Src-expressing cells with cancer-promoting roles. Inhibition of extracellular c-Src using custom SH3-targeting antibodies disrupt kinase-substrate complexes and inhibit cancer cell proliferation. These findings point toward an intricate role for c-Src in generating phosphosecretomes, which will likely influence cell-cell communication, particularly in c-Src-overexpressing cancers.

Integrating Protein Interaction Surface Prediction with a Fragment-Based Drug Design: Automatic Design of New Leads with Fragments on Energy Surfaces.

Protein-protein interactions (PPIs) have emerged in the past years as significant pharmacological targets in the development of new therapeutics due to their key roles in determining pathological pathways. Herein, we present fragments on energy surfaces, a simple and general design strategy that integrates the analysis of the dynamic and energetic signatures of proteins to unveil the substructures involved in PPIs, with docking, selection, and combination of drug-like fragments to generate new PPI inhibitor candidates. Specifically, structural representatives of the target protein are used as inputs for the blind physics-based prediction of potential protein interaction surfaces using the matrix of low coupling energy decomposition method. The predicted interaction surfaces are subdivided into overlapping windows that are used as templates to direct the docking and combination of fragments representative of moieties typically found in active drugs. This protocol is then applied and validated using structurally diverse, important PPI targets as test systems. We demonstrate that our approach facilitates the exploration of the molecular diversity space of potential ligands, with no requirement of prior information on the location and properties of interaction surfaces or on the structures of potential lead compounds. Importantly, the hit molecules that emerge from our ab initio design share high chemical similarity with experimentally tested active PPI inhibitors. We propose that the protocol we describe here represents a valuable means of generating initial leads against difficult targets for further development and refinement.

Protein Allostery and Ligand Design: Computational Design Meets Experiments to Discover Novel Chemical Probes.

Herein we examine the determinants of the allosteric inhibition of the mitochondrial chaperone TRAP1 by a small molecule ligand. The knowledge generated is harnessed into the design of novel derivatives with interesting biological properties. TRAP1 is a member of the Hsp90 family of proteins, which work through sequential steps of ATP processing coupled to client-protein remodeling. Isoform selective inhibition of TRAP1 can provide novel information on the biomolecular mechanisms of molecular chaperones, as well as new insights into the development of small molecules with therapeutic potential. Our analysis of the interactions between an active first-generation allosteric ligand and TRAP1 shows how the small molecule induces long-range perturbations that influence the attainment of reactive poses in the active site. At the same time, the dynamic adaptation of the allosteric binding pocket to the presence of the first-generation compound sets the stage for the design of a set of second-generation ligands: the characterization of the formation/disappearance of pockets around the allosteric site that is used to guide optimize the ligands' fit for the allosteric site and improve inhibitory activities. The effects of the newly designed molecules are validated experimentally in vitro and in vivo. We discuss the implications of our approach as a promising strategy towards understanding the molecular determinants of allosteric regulation in chemical and molecular biology, and towards speeding up the design of allosteric small molecule modulators.

New perspectives in cancer drug development: computational advances with an eye to design.

Computational chemistry has come of age in drug discovery. Indeed, most pharmaceutical development programs rely on computer-based data and results at some point. Herein, we discuss recent applications of advanced simulation techniques to difficult challenges in drug discovery. These entail the characterization of allosteric mechanisms and the identification of allosteric sites or cryptic pockets determined by protein motions, which are not immediately evident in the experimental structure of the target; the study of ligand binding mechanisms and their kinetic profiles; and the evaluation of drug-target affinities. We analyze different approaches to tackle challenging and emerging biological targets. Finally, we discuss the possible perspectives of future application of computation in drug discovery.