Giorgio Saladino

Molecular Mechanism of SSR128129E, an Extracellularly Acting, Small-Molecule, Allosteric Inhibitor of FGF Receptor Signaling

The fibroblast growth factor (FGF)/fibroblast growth factor receptor (FGFR) signaling network plays an important role in cell growth, survival, differentiation, and angiogenesis. Deregulation of FGFR signaling can lead to cancer development. Here, we report an FGFR inhibitor, SSR128129E (SSR), that binds to the extracellular part of the receptor. SSR does not compete with FGF for binding to FGFR but inhibits FGF-induced signaling linked to FGFR internalization in an allosteric manner, as shown by crystallography studies, nuclear magnetic resonance, Fourier transform infrared spectroscopy, molecular dynamics simulations, free energy calculations, structure-activity relationship analysis, and FGFR mutagenesis. Overall, SSR is a small molecule allosteric inhibitor of FGF/FGFR signaling, acting via binding to the extracellular part of the FGFR.

Investigating Drug–Target Association and Dissociation Mechanisms Using Metadynamics-Based Algorithms

CONSPECTUS: This Account highlights recent advances and discusses major challenges in the field of drug-target recognition, binding, and unbinding studied using metadynamics-based approaches, with particular emphasis on their role in structure-based design. Computational chemistry has significantly contributed to drug design and optimization in an extremely broad range of areas, including prediction of target druggability and drug likeness, de novo design, fragment screening, ligand docking, estimation of binding affinity, and modulation of ADMET (absorption, distribution, metabolism, excretion, toxicity) properties. Computationally driven drug discovery must continuously adapt to keep pace with the evolving knowledge of the factors that modulate the pharmacological action of drugs. There is thus an urgent need for novel computational approaches that integrate the vast amount of complex information currently available for small (bio)organic compounds, biologically relevant targets and their complexes, while also accounting accurately for the thermodynamics and kinetics of drug-target association, the intrinsic dynamical behavior of biomolecular systems, and the complexity of protein-protein networks. Understanding the mechanism of drug binding to and unbinding from biological targets is fundamental for optimizing lead compounds and designing novel biologically active ones. One major challenge is the accurate description of the conformational complexity prior to and upon formation of drug-target complexes. Recently, enhanced sampling methods, including metadynamics and related approaches, have been successfully applied to investigate complex mechanisms of drugs binding to flexible targets. Metadynamics is a family of enhanced sampling techniques aimed at enhancing the rare events and reconstructing the underlying free energy landscape as a function of a set of order parameters, usually referred to as collective variables. Studies of drug binding mechanisms have predicted the most probable association and dissociation pathways and the related binding free energy profile. In addition, the availability of an efficient open-source implementation, running on cost-effective GPU (i.e., graphical processor unit) architectures, has considerably decreased the learning curve and the computational costs of the methods, and increased their adoption by the community. Here, we review the recent contributions of metadynamics and other enhanced sampling methods to the field of drug-target recognition and binding. We discuss how metadynamics has been used to search for transition states, to predict binding and unbinding paths, to treat conformational flexibility, and to compute free energy profiles. We highlight the importance of such predictions in drug discovery. Major challenges in the field and possible solutions will finally be discussed.

The Mechanism of Allosteric Coupling in Choline Kinase α1 Revealed by the Action of a Rationally Designed Inhibitor

Applying a CHOK hold: Combined experimental and computational studies of the binding mode of a rationally designed inhibitor of the dimeric choline kinase α1 (CHOKα1) explain the molecular mechanism of negative cooperativity (see scheme) and how the monomers are connected. The results give insight into how the symmetry of the dimer can be partially conserved despite a lack of conservation in the static crystal structures.

Towards a Molecular Understanding of the Link between Imatinib Resistance and Kinase Conformational Dynamics.

Due to its inhibition of the Abl kinase domain in the BCR-ABL fusion protein, imatinib is strikingly effective in the initial stage of chronic myeloid leukemia with more than 90% of the patients showing complete remission. However, as in the case of most targeted anti-cancer therapies, the emergence of drug resistance is a serious concern. Several drug-resistant mutations affecting the catalytic domain of Abl and other tyrosine kinases are now known. But, despite their importance and the adverse effect that they have on the prognosis of the cancer patients harboring them, the molecular mechanism of these mutations is still debated. Here by using long molecular dynamics simulations and large-scale free energy calculations complemented by in vitro mutagenesis and microcalorimetry experiments, we model the effect of several widespread drug-resistant mutations of Abl. By comparing the conformational free energy landscape of the mutants with those of the wild-type tyrosine kinases we clarify their mode of action. It involves significant and complex changes in the inactive-to-active dynamics and entropy/enthalpy balance of two functional elements: the activation-loop and the conserved DFG motif. What is more the T315I gatekeeper mutant has a significant impact on the binding mechanism itself and on the binding kinetics.

Assessing the Performance of Metadynamics and Path Variables in Predicting the Binding Free Energies of p38 Inhibitors

The accurate yet efficient evaluation of the free energy profiles of ligand-target association is a long sought goal in rational drug design. Methods that calculate the free energy along realistic association pathways, such as metadynamics, have been shown to provide reliable profiles, while accounting properly for solvation and target flexibility. However, these approaches usually require prohibitive computational resources and expert human intervention. Here, we show how multiple walkers metadynamics, when performed with optimal path collective variables (PCV), provides in a predetermined amount of computer time an accurate set of free energy profiles for a series of p38 inhibitors. The chosen test set, spanning a wide range of activity, is a challenging benchmark, both for computational methods and for human intuition, as the correct order for the binding affinity cannot be easily guessed. An excellent ranking of the ligands was obtained with minimal human assistance, an important step toward a fully automated pharmaceutical work-flow.

New insights in protein kinase conformational dynamics.

A significant portion of recent drug development efforts has been focused on protein kinases. More than a hundred different compounds are currently under clinical trials and nearly 30% of all the scientific articles in drug discovery are on protein kinase inhibitors. Protein kinases are very flexible targets and undergo significant conformational changes upon activation and during the catalytic cycle. This flexibility can be exploited in drug discovery. Some of the inactive states that emerge during the conformational changes are targeted by various inhibitors with a significant gain in selectivity. Here, we review the recent advances being made in understanding the details and the mechanism of these conformational changes thanks to the progress in molecular dynamics and free energy algorithms as well as to the availability of specialized computer hardware.

Conformational Selection and Induced Fit Mechanisms in the Binding of an Anticancer Drug to the c-Src Kinase.

Understanding the conformational changes associated with the binding of small ligands to their biological targets is a fascinating and meaningful question in chemistry, biology and drug discovery. One of the most studied and important is the so-called “DFG-flip” of tyrosine kinases. The conserved three amino-acid DFG motif undergoes an “in to out” movement resulting in a particular inactive conformation to which “type II” kinase inhibitors, such as the anti-cancer drug Imatinib, bind. Despite many studies, the details of this prototypical conformational change are still debated. Here we combine various NMR experiments and surface plasmon resonance with enhanced sampling molecular dynamics simulations to shed light into the conformational dynamics associated with the binding of Imatinib to the proto-oncogene c-Src. We find that both conformational selection and induced fit play a role in the binding mechanism, reconciling opposing views held in the literature. Moreover, an external binding pose and local unfolding (cracking) of the aG helix are observed.

An Allosteric Cross-Talk Between the Activation Loop and the ATP Binding Site Regulates the Activation of Src Kinase

Phosphorylation of the activation loop is a fundamental step in the activation of most protein kinases. In the case of the Src tyrosine kinase, a prototypical kinase due to its role in cancer and its historic importance, phosphorylation of tyrosine 416 in the activation loop is known to rigidify the structure and contribute to the switch from the inactive to a fully active form. However, whether or not phosphorylation is able per-se to induce a fully active conformation, that efficiently binds ATP and phosphorylates the substrate, is less clear. Here we employ a combination of solution NMR and enhanced-sampling molecular dynamics simulations to fully map the effects of phosphorylation and ATP/ADP cofactor loading on the conformational landscape of Src tyrosine kinase. We find that both phosphorylation and cofactor binding are needed to induce a fully active conformation. What is more, we find a complex interplay between the A-loop and the hinge motion where the phosphorylation of the activation-loop has a significant allosteric effect on the dynamics of the C-lobe.

Bridging the Gap between Folding Simulations and Experiments: The Case of the Villin Headpiece.

The increasing accuracy of molecular dynamics force fields parameters and the increasing resolution of experimental results allow one to carefully compare and complement in silico data with experimental observations. Here, we study the human villin headpiece C-terminal helical subdomain (HP35) with the recent highly optimized Amber99SB*-ILDN force field and compare the results with recent high resolution triplet-triplet energy transfer (TTET) experiments. The correct reproduction of the main structural features reveals a good agreement between experimental data and simulations.

A Simple Mechanism Underlying the Effect of Protecting Osmolytes on Protein Folding.

Osmolytes are small organic compounds that confer to the cell an enhanced adaptability to external conditions. Many osmolytes not only protect the cell from osmotic stress but also stabilize the native structure of proteins. While simplified models able to predict changes to protein stability are available, a general physicochemical explanation of the underlying microscopic mechanism is still missing. Here, we address this issue by performing very long all-atom MD simulations, free energy calculations, and experiments on a well-characterized mini-protein, the villin headpiece. Comparisons between the folding free energy landscapes in pure water and osmolyte solutions, together with experimental validation by means of circular dichroism, unfolding experiments, and NMR, led us to formulate a simple hypothesis for the protecting mechanism. Taken together, our results support a novel mechanistic explanation according to which the main driving force behind native state protection is a change in the solvent rotational diffusion.