Cryptic pocket formation underlies allosteric modulator selectivity at muscarinic GPCRs.

Allosteric modulators are highly desirable as drugs, particularly for G-protein-coupled receptor (GPCR) targets, because allosteric drugs can achieve selectivity between closely related receptors. The mechanisms by which allosteric modulators achieve selectivity remain elusive, however, particularly given recent structures that reveal similar allosteric binding sites across receptors. Here we show that positive allosteric modulators (PAMs) of the M1 muscarinic acetylcholine receptor (mAChR) achieve exquisite selectivity by occupying a dynamic pocket absent in existing crystal structures. This cryptic pocket forms far more frequently in molecular dynamics simulations of the M1 mAChR than in those of other mAChRs. These observations reconcile mutagenesis data that previously appeared contradictory. Further mutagenesis experiments validate our prediction that preventing cryptic pocket opening decreases the affinity of M1-selective PAMs. Our findings suggest opportunities for the design of subtype-specific drugs exploiting cryptic pockets that open in certain receptors but not in other receptors with nearly identical static structures.

Novel peptide probes to assess the tensional state of fibronectin fibers in cancer.

Transformations of extracellular matrix (ECM) accompany pathological tissue changes, yet how cell-ECM crosstalk drives these processes remains unknown as adequate tools to probe forces or mechanical strains in tissues are lacking. Here, we introduce a new nanoprobe to assess the mechanical strain of fibronectin (Fn) fibers in tissue, based on the bacterial Fn-binding peptide FnBPA5. FnBPA5 exhibits nM binding affinity to relaxed, but not stretched Fn fibers and is shown to exhibit strain-sensitive ECM binding in cell culture in a comparison with an established Fn-FRET probe. Staining of tumor tissue cryosections shows large regions of relaxed Fn fibers and injection of radiolabeled 111In-FnBPA5 in a prostate cancer mouse model reveals specific accumulation of 111In-FnBPA5 in tumor with prolonged retention compared to other organs. The herein presented approach enables to investigate how Fn fiber strain at the tissue level impacts cell signaling and pathological progression in different diseases.

Revealing Atomic-Level Mechanisms of Protein Allostery with Molecular Dynamics Simulations.

Molecular dynamics (MD) simulations have become a powerful and popular method for the study of protein allostery, the widespread phenomenon in which a stimulus at one site on a protein influences the properties of another site on the protein. By capturing the motions of a protein's constituent atoms, simulations can enable the discovery of allosteric binding sites and the determination of the mechanistic basis for allostery. These results can provide a foundation for applications including rational drug design and protein engineering. Here, we provide an introduction to the investigation of protein allostery using molecular dynamics simulation. We emphasize the importance of designing simulations that include appropriate perturbations to the molecular system, such as the addition or removal of ligands or the application of mechanical force. We also demonstrate how the bidirectional nature of allostery-the fact that the two sites involved influence one another in a symmetrical manner-can facilitate such investigations. Through a series of case studies, we illustrate how these concepts have been used to reveal the structural basis for allostery in several proteins and protein complexes of biological and pharmaceutical interest.

Multidomain Assembler (MDA) Generates Models of Large Multidomain Proteins.

Homology modeling predicts protein structures using known structures of related proteins as templates. We developed MULTIDOMAIN ASSEMBLER (MDA) to address the special problems that arise when modeling proteins with large numbers of domains, such as fibronectin with 30 domains, as well as cases with hundreds of templates. These problems include how to spatially arrange nonoverlapping template structures, and how to get the best template coverage when some sequence regions have hundreds of available structures while other regions have a few distant homologs. MDA automates the tasks of template searching, visualization, and selection followed by multidomain model generation, and is part of the widely used molecular graphics package UCSF CHIMERA (University of California, San Francisco). We demonstrate applications and discuss MDA's benefits and limitations.

A guide to the visual analysis and communication of biomolecular structural data.

Biologists regularly face an increasingly difficult task - to effectively communicate bigger and more complex structural data using an ever-expanding suite of visualization tools. Whether presenting results to peers or educating an outreach audience, a scientist can achieve maximal impact with minimal production time by systematically identifying an audience's needs, planning solutions from a variety of visual communication techniques and then applying the most appropriate software tools. A guide to available resources that range from software tools to professional illustrators can help researchers to generate better figures and presentations tailored to any audience's needs, and enable artistically inclined scientists to create captivating outreach imagery.

Engineering mechanosensitive multivalent receptor-ligand interactions: why the nanolinker regions of bacterial adhesins matter.

Inspired by bacterial adhesins, we present a promising strategy of how to engineer peptides to probe various mechanical strains of extracellular matrix fibers. Functional sequence alignment of bacterial adhesins reveals that the bacterial linkers connecting the multivalent binding motifs recognizing fibronectin show considerable heterogeneity in length. Their length regulates the tunable affinities for fibronectin fibrils when stretched into different mechanical strain states. This platform has potential applications in probing extracellular matrix fiber strains in tissues.

Probing the Structure and Dynamics of Proteins by Combining Molecular Dynamics Simulations and Experimental NMR Data.

NMR experiments provide detailed structural information about biological macromolecules in solution. However, the amount of information obtained is usually much less than the number of degrees of freedom of the macromolecule. Moreover, the relationships between experimental observables and structural information, such as interatomic distances or dihedral angle values, may be multiple-valued and may rely on empirical parameters and approximations. The extraction of structural information from experimental data is further complicated by the time- and ensemble-averaged nature of NMR observables. Combining NMR data with molecular dynamics simulations can elucidate and alleviate some of these problems, as well as allow inconsistencies in the NMR data to be identified. Here, we use a number of examples from our work to highlight the power of molecular dynamics simulations in providing a structural interpretation of solution NMR data.

Stretching fibronectin fibres disrupts binding of bacterial adhesins by physically destroying an epitope.

Although soluble inhibitors are frequently used to block cell binding to the extracellular matrix (ECM), mechanical stretching of a protein fibre alone can physically destroy a cell-binding site. Here, we show using binding assays and steered molecular dynamics that mechanical tension along fibronectin (Fn) fibres causes a structural mismatch between Fn-binding proteins from Streptococcus dysgalactiae and Staphylococcus aureus. Both adhesins target a multimodular site on Fn that is switched to low affinity by stretching the intermodular distances on Fn. Heparin reduces binding but does not eliminate mechanosensitivity. These adhesins might thus preferentially bind to sites at which ECM fibres are cleaved, such as wounds or inflamed tissues. The mechanical switch described here operates differently from the catch bond mechanism that Escherichia coli uses to adhere to surfaces under fluid flow. Demonstrating the existence of a mechanosensitive cell-binding site provides a new perspective on how the mechanobiology of ECM might regulate bacterial and cell-binding events, virulence and the course of infection.

Epirubicin exhibits potent anti-tumor activity in an animal model of malignant glioma when administered via controlled-release polymers.

Epirubicin (EPI) has strong cytotoxic activity that makes it a potential candidate for the treatment of malignant gliomas. To minimize toxicity and increase CNS penetration, EPI was incorporated into biodegradable polymers, and its in vitro and in vivo properties were studied. 9L, F98, C6, U251, and EMT-6 cell lines were treated with EPI in vitro and cell viability was measured. Toxicity of EPI/polycarboxyphenoxypropane-sebacic-acid (pCPP:SA) polymers was tested in vivo using F344 rats intracranially implanted with EPI polymers (2-50% by weight). The efficacy of 50% EPI:pCPP:SA polymers was determined in F344 rats intracranially challenged with 9L and treated either simultaneously or 5 days after tumor implantation. The efficacy of 50% EPI:pCCP:SA polymers administered on Day 5 in combination with oral TMZ was determined in rats intracranially challenged with 9L gliosarcoma. EPI was cytotoxic in all cell lines used in vitro. Intracranial implantation of the EPI polymers in rats generated neither local nor systemic toxicity. Animals receiving intracranial EPI on Day 5 had 50% long-term survivors (LTS), which was superior to local EPI delivered on Day 0 (LTS = 12.5%). Animals receiving intracranial EPI in combination with oral TMZ had 75% LTS whereas no other group had LTS. In those EPI treated animals that died before the controls there was evidence of intracranial hemorrhage. Systemic epirubicin resulted in high toxicity levels and early deaths in all the experiments. EPI polymers, alone or in combination with oral TMZ, is an effective therapeutic modality against experimental 9L gliosarcoma.

Automated fiber tracking of human brain white matter using diffusion tensor imaging.

Reconstruction of white matter tracts based on diffusion tensor imaging (DTI) is currently widely used in clinical research. This reconstruction allows us to identify coordinates of specific white matter tracts and to investigate their anatomy. Fiber reconstruction, however, relies on manual identification of anatomical landmarks of a tract of interest, which is based on subjective judgment and thus a potential source of experimental variability. Here, an automated tract reconstruction approach is introduced. A set of reference regions of interest (rROIs) known to select a tract of interest was marked in our DTI brain atlas. The atlas was then linearly transformed to each subject, and the rROI set was transferred to the subject for tract reconstruction. Agreement between the automated and manual approaches was measured for 11 tracts in 10 healthy volunteers and found to be excellent (kappa>0.8) and remained high up to 4-5 mm of the linear transformation errors. As a first example, the automated approach was applied to brain tumor patients and strategies to cope with severe anatomical abnormalities are discussed.