Correlations between sequence evolution and structural dynamics are of utmost importance in understanding the molecular mechanisms of function and their evolution. We have integrated Evol, a new package for fast and efficient comparative analysis of evolutionary patterns and conformational dynamics, into ProDy, a computational toolbox designed for inferring protein dynamics from experimental and theoretical data. Using information-theoretic approaches, Evol coanalyzes conservation and coevolution profiles extracted from multiple sequence alignments of protein families with their inferred dynamics.
Availability and implementation:
ProDy and Evol are open-source and freely available under MIT License from
Dual specificity phosphatase 6 (DUSP6) functions as a feedback attenuator of Fibroblast Growth Factor signaling during development. In vitro high throughput chemical screening attempts to discover DUSP6 inhibitors have yielded limited success. Yet, in vivo whole organism screens using zebrafish identified 1 (BCI) as an allosteric inhibitor of DUSP6. Here we designed and synthesized a panel of analogs to define structure-activity relationship (SAR) of DUSP6 inhibition. In vivo, high-content analysis in transgenic zebrafish coupled with cell-based chemical complementation assays identified structural features of the 1 pharmacophore that were essential for biological activity. In vitro assays of DUSP hyperactivation corroborated the results from in vivo and cellular SAR. The results reinforce the notion that DUSPs are druggable through allosteric mechanisms, and illustrate the utility of zebrafish as a model organism for in vivo SAR analyses.
Cognition Network Technology; FGF signaling; BCI; high-content screening; zebrafish
Mitochondria have emerged as the major regulatory platform responsible for coordination of numerous metabolic reactions as well as cell death processes, whereby the execution of intrinsic apoptosis includes the production of reactive oxygen species fueling oxidation of cardiolipin (CL) catalyzed by cytochrome (cyt) c. As this oxidation occurs within the peroxidase complex of cyt c with CL, the latter represents a promising target for the discovery and design of drugs with anti-apoptotic mechanism of action. In this work, we designed and synthesized a new group of mitochondria-targeted imidazole-substituted analogues of stearic acid TPP-n-ISA with different positions of the attached imidazole group on the fatty acid (n=6, 8, 10, 13 and 14). By using a combination of absorption spectroscopy and EPR protocols (continuous wave electron paramagnetic resonance, and electron spin echo envelope modulation) we demonstrated that TPP-n-ISA indeed were able to potently suppress CL induced structural re-arrangements in cyt c paving the way to its peroxidase competence. TPP-n-ISA analogues preserved the low spin hexa-coordinated heme iron state in cyt c/CL complexes whereby TPP-6-ISA displayed a significantly more effective preservation pattern than TPP-14-ISA. Elucidation of these intermolecular stabilization mechanisms of cyt c identified TPP-6-ISA as an effective inhibitor of the peroxidase function of cyt c/CL complexes with a significant anti-apoptotic potential realized in mouse embryonic cells exposed to ionizing irradiation. These experimental findings were detailed and supported by all atom molecular dynamics simulations. Based on the experimental data and computations predictions, we identified TPP-6-ISA as a candidate drug with optimized anti-apoptotic potency.
All-atom molecular dynamics simulation; Cardiolipin peroxidation; Cytochrome c; Electron paramagnetic resonance; Imidazole-substituted stearic acid; Mitochondria targeting; Peroxidase inhibitors; Reactive intermediates
Although the process of drug development requires efficacy and toxicity testing in animals prior to human testing, animal models have limited ability to accurately predict human responses to xenobiotics and other insults. Societal pressures are also focusing on reduction of and, ultimately, replacement of animal testing. However, a variety of in vitro models, explored over the last decade, have not been powerful enough to replace animal models. New initiatives sponsored by several US federal agencies seek to address this problem by funding the development of physiologically relevant human organ models on microscopic chips. The eventual goal is to simulate a human-on-a-chip, by interconnecting the organ models, thereby replacing animal testing in drug discovery and development. As part of this initiative, we aim to build a three-dimensional human liver chip that mimics the acinus, the smallest functional unit of the liver, including its oxygen gradient. Our liver-on-a-chip platform will deliver a microfluidic three-dimensional co-culture environment with stable synthetic and enzymatic function for at least 4 weeks. Sentinel cells that contain fluorescent biosensors will be integrated into the chip to provide multiplexed, real-time readouts of key liver functions and pathology. We are also developing a database to manage experimental data and harness external information to interpret the multimodal data and create a predictive platform.
The liver is a heterogeneous organ with many vital functions, including metabolism of pharmaceutical drugs and is highly susceptible to injury from these substances. The etiology of drug induced liver disease is still debated although generally regarded as a continuum between an activated immune response and hepatocyte metabolic dysfunction, most often resulting from an intermediate reactive metabolite. This debate stems from the fact that current animal and in vitro models provide limited physiologically relevant information and their shortcomings have resulted in ‘silent’ hepatotoxic drugs being introduced into clinical trials, garnering huge financial losses for drug companies through withdrawals and late stage clinical failures. As we advance our understanding into the molecular processes leading to liver injury, it is increasingly clear that a) the pathologic lesion is not only due to liver parenchyma but is also due to the interactions between the hepatocytes and the resident liver immune cells, stellate cells and endothelial cells; and, b) animal models do not reflect the human cell interactions. Therefore, a predictive human, in vitro model must address the interactions between the major human liver cell types and measure key determinants of injury such as the dosage and metabolism of the drug, the stress response, cholestatic effect, and the immune and fibrotic response. In this mini-review, we first discuss the current state of macro-scale in vitro liver culture systems with examples that have been commercialized. We then introduce the paradigm of microfluidic culture systems that aim to mimic the liver with physiologically relevant dimensions, cellular structure, perfusion and mass transport by taking advantage of micro and nanofabrication technologies. We review the most prominent liver-on-a-chip platforms in terms of their physiological relevance and drug response. We conclude with a commentary on other critical advances such as the deployment of fluorescence-based biosensors to identify relevant toxicity pathways, as well as computational models to create a predictive tool.
Drug Induced Liver Injury; Liver on chip; Hepatotoxicity; High Content Screening; Predictive Modeling
Catalytic loop motions facilitate substrate recognition and binding in many enzymes. While these motions appear to be highly flexible, their functional significance suggests that structure-encoded preferences may play a role in selecting particular mechanisms of motions. We performed an extensive study on a set of enzymes to assess whether the collective/global dynamics, as predicted by elastic network models (ENMs), facilitates or even defines the local motions undergone by functional loops. Our dataset includes a total of 117 crystal structures for ten enzymes of different sizes and oligomerization states. Each enzyme contains a specific functional/catalytic loop (10–21 residues long) that closes over the active site during catalysis. Principal component analysis (PCA) of the available crystal structures (including apo and ligand-bound forms) for each enzyme revealed the dominant conformational changes taking place in these loops upon substrate binding. These experimentally observed loop reconfigurations are shown to be predominantly driven by energetically favored modes of motion intrinsically accessible to the enzyme in the absence of its substrate. The analysis suggests that robust global modes cooperatively defined by the overall enzyme architecture also entail local components that assist in suitable opening/closure of the catalytic loop over the active site.
Protein loops have critical roles in ligand binding and catalysis. An unresolved issue in this context is the extent to which the intrinsic dynamics of proteins predispose loops to perform their molecular function. In this work, we (i) critically examine the structural changes undergone by functional/catalytic loops based on a set of enzyme crystal structures in the presence/absence of a ligand, and (ii) examine to what extent those motions are correlated with, or driven by, the global modes that are predictable using simplified, physics-based models. Using a dataset of 117 structures for ten enzymes of different sizes and oligomerization states, we show that the collective modes defined by the protein topology favor loop rearrangements in reasonable agreement with those experimentally observed upon activation. These results suggest that simple but robust motions encoded by the entire architecture, not the local binding site only, assist in binding of the ligand, positioning of the catalytic loop, and/or sequestration of the catalytic site, which in turn, enable efficient catalysis.
PUMA (p53 upregulated modulator of apoptosis) is a Bcl-2 homology 3 (BH3)-only Bcl-2 family member and a key mediator of apoptosis induced by a wide variety of stimuli. PUMA is particularly important in initiating radiation-induced apoptosis and damage in the gastrointestinal and hematopoietic systems. Unlike most BH3-only proteins, PUMA neutralizes all five known antiapoptotic Bcl-2 members through high affinity interactions with its BH3 domain to initiate mitochondria-dependent cell death. Using structural data on the conserved interactions of PUMA with Bcl-2-like proteins, we developed a pharmacophore model that mimics these interactions. In silico screening of the ZINC 8.0 database with this pharmacophore model yielded 142 compounds that could potentially disrupt these interactions. Thirteen structurally diverse compounds with favorable in silico ADME/Toxicity profiles have been retrieved from this set. Extensive testing of these compounds using cell-based and cell-free systems identified lead compounds that confer considerable protection against PUMA-dependent and radiation-induced apoptosis, and inhibit the interaction between PUMA and Bcl-xL.
Inhibition of PUMA-induced apoptosis; Bcl-2 protein family; BH3 domain; protein-protein interactions; pharmacophore modeling; druggability; virtual screening of libraries of small compounds
Summary: We developed a Python package, ProDy, for structure-based analysis of protein dynamics. ProDy allows for quantitative characterization of structural variations in heterogeneous datasets of structures experimentally resolved for a given biomolecular system, and for comparison of these variations with the theoretically predicted equilibrium dynamics. Datasets include structural ensembles for a given family or subfamily of proteins, their mutants and sequence homologues, in the presence/absence of their substrates, ligands or inhibitors. Numerous helper functions enable comparative analysis of experimental and theoretical data, and visualization of the principal changes in conformations that are accessible in different functional states. ProDy application programming interface (API) has been designed so that users can easily extend the software and implement new methods.
Availability: ProDy is open source and freely available under GNU General Public License from http://www.csb.pitt.edu/ProDy/.
Contact: firstname.lastname@example.org; email@example.com
The dual specificity phosphatase 6 (Dusp6) functions as a feedback regulator of fibroblast growth factor (FGF) signaling to limit the activity of extracellular signal regulated kinase (ERK) 1 and 2. We have identified a small molecule inhibitor of Dusp6, (E)-2-benzylidene-3-(cyclohexylamino)-2,3-dihydro-1H-inden-1-one (BCI), using a transgenic zebrafish chemical screen. BCI treatment blocked Dusp6 activity and enhanced FGF target gene expression in zebrafish embryos. Docking simulations predicted an allosteric binding site for BCI within the phosphatase domain. In vitro studies supported a model that BCI inhibits Dusp6 catalytic activation by ERK2 substrate binding. A temporal role for Dusp6 in restricting cardiac progenitors and controlling heart organ size was uncovered with BCI treatment at varying developmental stages. This study highlights the power of in vivo zebrafish chemical screens to identify novel compounds targeting Dusp6, a component of the FGF signaling pathway that has eluded traditional high-throughput in vitro screens.
Druggability assessment of a target protein has emerged
years as an important concept in hit-to-lead optimization. A reliable
and physically relevant measure of druggability would allow informed
decisions on the risk of investing in a particular target. Here, we
define “druggability” as a quantitative estimate of
binding sites and affinities for a potential drug acting on a specific
protein target. In the present study, we describe a new methodology
that successfully predicts the druggability and maximal binding affinity
for a series of challenging targets, including those that function
through allosteric mechanisms. Two distinguishing features of the
methodology are (i) simulation of the binding dynamics of a diversity
of probe molecules selected on the basis of an analysis of approved
drugs and (ii) identification of druggable sites and estimation of
corresponding binding affinities on the basis of an evaluation of
the geometry and energetics of bound probe clusters. The use of the
methodology for a variety of targets such as murine double mutant-2,
protein tyrosine phosphatase 1B (PTP1B), lymphocyte function-associated
antigen 1, vertebrate kinesin-5 (Eg5), and p38 mitogen-activated protein
kinase provides examples for which the method correctly captures the
location and binding affinities of known drugs. It also provides insights
into novel druggable sites and the target’s structural changes
that would accommodate, if not promote and stabilize, drug binding.
Notably, the ability to identify high affinity spots even in challenging
cases such as PTP1B or Eg5 shows promise as a rational tool for assessing
the druggability of protein targets and identifying allosteric or
novel sites for drug binding.
Dual-specificity phosphatases (DSPs) are important, but poorly understood, cell signaling enzymes that remove phosphate groups from tyrosine and serine/threonine residues on their substrate. Deregulation of DSPs has been implicated in cancer, obesity, diabetes, inflammation, and Alzheimer’s disease. Due to their biological and biomedical significance, DSPs have increasingly become the subject of drug discovery high-throughput screening (HTS) and focused compound library development efforts. Progress in identifying selective and potent DSP inhibitors has, however, been restricted by the lack of sufficient structural data on inhibitor-bound DSPs. The shallow, almost flat, substrate binding sites in DSPs have been a major factor in hampering the rational design and the experimental development of active site inhibitors. Recent experimental and virtual HTS studies, as well as advances in molecular modeling, provide new insights into the potential mechanisms for substrate recognition and binding by this important class of enzymes. We present herein an overview of the progress, along with a brief description of applications to two types of DSPs: Cdc25 and MAP kinase phosphatase (MKP) family members. In particular, we focus on combined computational and experimental efforts for designing Cdc25B and MKP-1 inhibitors and understanding their mechanisms of interactions with their target proteins. These studies emphasize the utility of developing computational models and methods that meet the two major challenges currently faced in structure-based in silico design of lead compounds: the conformational flexibility of the target protein and the entropic contribution to the selection and stabilization of particular bound conformers.
Dual-specificity phosphatases; computer-aided drug discovery; high throughput screening; structure-based virtual screening; molecular docking; intrinsic dynamics; focused library design.