Non-Canonical Allostery in Cyclic Nucleotide Dependent Kinases

The cAMP- and cGMP-dependent protein kinases (PKA and PKG) are canonically activated by the corresponding cyclic nucleotides. However, both systems are also sensitive to a wide range of non-canonical allosteric effectors, such as reactive oxygen species, which induce the formation of regulatory inter- and intra-molecular disulfide bridges, and disease-related mutations (DRMs). Here, we present a combined analysis of representative non-canonical allosteric effectors for PKA and PKG, and we identify common molecular mechanisms underlying non-canonical allostery in these kinases, from shifts in dynamical regulatory equilibria to modulation of inter-protomer interactions. In addition, mutations may also drive oligomerization beyond dimerization, and possibly phase transitions, causing loss of kinase inhibitory function and amplifying the allosteric effects of DRMs. Hence non-canonical allosteric stimuli often result in constitutive kinase activation underlying either physiological control of downstream signaling pathways or pathological outcomes, from aortic aneurisms to cancer predisposition. Overall, PKA and PKG emerge as “pan-sensors” going well beyond canonical cyclic nucleotide activation, revealing their versatile roles as central signaling hubs.     

Folding Steps in the Fibrillation of Functional Amyloid: Denaturant Sensitivity Reveals Common Features in Nucleation and Elongation

Functional bacterial amyloids (FuBA) are intrinsically disordered proteins (IDPs) which rapidly and efficiently aggregate, forming extremely stable fibrils. The conversion from IDP to amyloid is evolutionarily optimized and likely couples folding to association. Many FuBA contain several imperfect repeat sequences which contribute to the stability of mature FuBA fibrils. Aggregation can be considered an intermolecular extension of the process of intramolecular protein folding which has traditionally been studied using chemical denaturants. Here we employ denaturants to investigate folding steps during fibrillation of CsgA and FapC. We quantify protein compactification (i.e. the extent of burial of otherwise exposed surface area upon association of proteins) during different stages of fibrillation based on the dependence of fibrillation rate constants on the denaturant concentration (m-values) determined from fibrillation curves. For both proteins, urea mainly affects nucleation and elongation (not fragmentation), consistent with the fact that these steps involve both intra- and intermolecular association. The two steps have similar m-values, indicating that activation steps in nucleation and elongation involve the same level of folding. Surprisingly, deletion of two or three repeats from FapC leads to larger m-values (i.e. higher compactification) during the activation step of fibril growth. This observation is extended by SAXS analysis of the fibrils which indicates that weakening of the amyloidogenic core caused by repeat deletions causes a larger portion of normally unstructured regions of the protein to be included into the amyloid backbone. We conclude that the sensitivity of fibrillation to denaturants can provide useful insight into molecular mechanisms of aggregation.     

Explaining and Predicting Allostery with Allosteric Database and Modern Analytical Techniques

Allostery is a phenomenon that the protein activity is regulated when a non-functional site on it is bounded. This phenomenon is important in life process and disease therapy. However, it is difficult to study allostery due to the lack of knowledge. Facing this demand, we have created Allosteric Database (ASD) 10 years before to collect numerous kinds of allosteric data. In this review, we will introduce the 4 categories of data in ASD. For each category, we further reviewed how researchers applied ASD data to conduct studies. We focused on their research topics, analytical methods and conclusions. Several discoveries of new drug targets and allosteric modulators driven by ASD are also summarized. We hope this review could inspire researchers with new utilities of ASD data.     

Allostery and Missense Mutations as Intermittently Linked Promising Aspects of Modern Computational Drug Discovery

Drug research and development is a multidisciplinary field with its own successes. Yet, given the complexity of the process, it also faces challenges over the long development stages and even includes those that develop once a drug is marketed, i.e. drug toxicity and drug resistance. Better success can be achieved via well designed criteria in the early drug development stages. Here, we introduce the concepts of allostery and missense mutations, and argue that incorporation of these two intermittently linked biological phenomena into the early computational drug discovery stages would help to reduce the attrition risk in later stages of the process. We discuss the individual or in concert mechanisms of actions of mutations in allostery. Design of allosteric drugs is challenging compared to orthosteric drugs, yet they have been gaining popularity in recent years as alternative systems for the therapeutic regulation of proteins with an action-at-a-distance mode and non-invasive mechanisms. We propose an easy-to-apply computational allosteric drug discovery protocol which considers the mutation effect, and detail it with three case studies focusing on (1) analysis of effect of an allosteric mutation related to isoniazid drug resistance in tuberculosis; (2) identification of a cryptic pocket in the presence of an allosteric mutation of falcipain-2 as a malarial drug target; and (3) deciphering the effects of SARS-CoV-2 evolutionary mutations on a potential allosteric modulator with changes to allosteric communication paths.     

Modeling Innate Antiviral Immunity in Physiological Context

An effective innate antiviral response is critical for the mitigation of severe disease and host survival following infection. In vivo, the innate antiviral response is triggered by cells that detect the invading pathogen and then communicate through autocrine and paracrine signaling to stimulate the expression of genes that inhibit viral replication, curtail cell proliferation, or modulate the immune response. In other words, the innate antiviral response is complex and dynamic. Notably, in the laboratory, culturing viruses and assaying viral life cycles frequently utilizes cells that are derived from tissues other than those that support viral replication during natural infection, while the study of viral pathogenesis often employs animal models. In recapitulating the human antiviral response, it is important to consider that variation in the expression and function of innate immune sensors and antiviral effectors exists across species, cell types, and cell differentiation states, as well as when cells are placed in different contexts. Thus, to gain novel insight into the dynamics of the host response and how specific sensors and effectors impact infection kinetics by a particular virus, the model system must be selected carefully. In this review, we briefly introduce key signaling pathways involved in the innate antiviral response and highlight how these differ between systems. We then review the application of tissue-engineered or 3D models for studying the antiviral response, and suggest how these in vitro culture systems could be further utilized to assay physiologically-relevant host responses and reveal novel insight into virus-host interactions.     

Microsecond Dynamics During the Binding-induced Folding of an Intrinsically Disordered Protein

Tau is an intrinsically disordered protein implicated in many neurodegenerative diseases. The repeat domain fragment of tau, tau-K18, is known to undergo a disorder to order transition in the presence of lipid micelles and vesicles, in which helices form in each of the repeat domains. Here, the mechanism of helical structure formation, induced by a phospholipid mimetic, sodium dodecyl sulfate (SDS) at sub-micellar concentrations, has been studied using multiple biophysical probes. A study of the conformational dynamics of the disordered state, using photoinduced electron transfer coupled to fluorescence correlation spectroscopy (PET-FCS) has indicated the presence of an intermediate state, I, in equilibrium with the unfolded state, U. The cooperative binding of the ligand (L), SDS, to I has been shown to induce the formation of a compact, helical intermediate (IL₅) within the dead time (∼37 µs) of a continuous flow mixer. Quantitative analysis of the PET-FCS data and the ensemble microsecond kinetic data, suggests that the mechanism of induction of helical structure can be described by a U ↔ I ↔ IL₅ ↔ FL₅ mechanism, in which the final helical state, FL₅, forms from IL₅ with a time constant of 50–200 µs. Finally, it has been shown that the helical conformation is an aggregation-competent state that can directly form amyloid fibrils.     

Validation of an Allosteric Binding Site of Src Kinase Identified by Unbiased Ligand Binding Simulations

Allostery plays a primary role in regulating protein activity, making it an important mechanism in human disease and drug discovery. Identifying allosteric regulatory sites to explore their biological significance and therapeutic potential is invaluable to drug discovery; however, identification remains a challenge. Allosteric sites are often “cryptic” without clear geometric or chemical features. Since allosteric regulatory sites are often less conserved in protein kinases than the orthosteric ATP binding site, allosteric ligands are commonly more specific than ATP competitive inhibitors. We present a generalizable computational protocol to predict allosteric ligand binding sites based on unbiased ligand binding simulation trajectories. We demonstrate the feasibility of this protocol by revisiting our previously published ligand binding simulations using the first identified viral proto-oncogene, Src kinase, as a model system. The binding paths for kinase inhibitor PP1 uncovered three metastable intermediate states before binding the high-affinity ATP-binding pocket, revealing two previously known allosteric sites and one novel site. Herein, we validate the novel site using a combination of virtual screening and experimental assays to identify a V-type allosteric small-molecule inhibitor that targets this novel site with specificity for Src over closely related kinases. This study provides a proof-of-concept for employing unbiased ligand binding simulations to identify cryptic allosteric binding sites and is widely applicable to other protein–ligand systems.     

Heteroarylamide smoothened inhibitors: Discovery of N-[2,4-dimethyl-5-(1-methylimidazol-4-yl)phenyl]-4-(2-pyridylmethoxy)benzamide (AZD8542) and N-[5-(1H-imidazol-2-yl)-2,4-dimethyl-phenyl]-4-(2- pyridylmethoxy)benzamide (AZD7254)

Aberrant hedgehog (Hh) pathway signaling is implicated in multiple cancer types and targeting the Smoothened (SMO) receptor, a key protein of the Hh pathway, has proven effective in treating metastasized basal cell carcinoma. Our lead optimization effort focused on a series of heteroarylamides. We observed that a methyl substitution ortho to the heteroaryl groups on an aniline core significantly improved the potency of this series of compounds. These findings predated the availability of SMO crystal structure in 2013. Here we retrospectively applied quantum mechanics calculations to demonstrate the o-Me substitution favors the bioactive conformation by inducing a dihedral twist between the heteroaryl rings and the core aniline. The o-Me also makes favorable hydrophobic interactions with key residue side chains in the binding pocket. From this effort, two compounds (AZD8542 and AZD7254) showed excellent pharmacokinetics across multiple preclinical species and demonstrated in vivo activity in abrogating the Hh paracrine pathway as well as anti- tumor effects.     

Choosing Optimal Microcarcinoma Patients for Active Surveillance Study (Compass): Effectiveness Evaluation of a Preoperative Clinical Framework

ObjectiveActive surveillance (AS) is a management alternative for patients with low-risk papillary thyroid microcarcinoma (PTMC). To decide the best candidates for AS, clinicians can use a framework to classify PTMC patients as ideal, appropriate, or inappropriate. This study aimed to explore the correlation between the framework categories and surgical pathology.MethodsThis multicenter retrospective study was conducted between 2014 and 2016. We included 1997 patients who underwent thyroid surgery for the first time due to suspected PTMC and were confirmed as PTMC by postoperative pathology. The consistency of modified preoperative risk stratification and the pathologic condition were evaluated using a consistency ratio and the Kappa coefficient. Stratified analysis was also performed to test consistency in different age groups.ResultsBased on the decision-making framework, 558 (27.9%) patients could receive AS while 810 (40.6%) patients did not require immediate surgery according to the actual postoperative pathology. The sensitivity, false-positive rate, specificity, false-negative rate, and consistency rate were 82.39%, 56.91%, 43.09%, 17.61%, and 66.45%, respectively. The Kappa value was 0.268. Stratified analysis showed that the sensitivity was 87.7% among patients aged 18 to 59 years. In the group aged ≥60 years, the specificity was up to 87.5%, but the sensitivity was low.ConclusionThe results of the modified risk-stratified clinical decision-making framework did not have a high consistency with the postoperative results. However, the framework showed a good effect in selecting patients for immediate surgery in the younger group and patients for AS in the older group.     

Ecological analysis and environmental niche modelling of Dactylorhiza hatagirea (D. Don) Soo: A conservation approach for critically endangered medicinal orchid

The natural populations of Dactylorhiza hatagirea have been greatly affected due to incessant exploitation. As such, studies on its population attributes together with habitat suitability and environmental factors affecting its distribution are needed to be undertaken for its conservation in nature. Present study aimed at accessing an impact of anthropogenic pressure on population structure and locate suitable habitats for the conservation of this critically endangered orchid. Considerable changes in the phytosociological attributes were observed on account of the changing magnitude and extent of anthropogenic threat in their natural abode. The distribution pattern of species indicated that more than 90% of the populations exhibit substantially aggregated spatial distribution. Maximum Entropy (MaxEnt) distribution modelling algorithm was used to predict suitable habitat and potential area for its cultivation and reintroduction. Twenty-seven occurrence records, nineteen bioclimatic variables, altitude, and slope were used. MaxEnt map output gave the habitat suitability for this species and predicted its distribution in the North-Western Himalayas of India for approximately 616 km². Jackknifing indicated that maximum temperature of warmest month, annual mean temperature, mean temperature of the driest quarter, and mean temperature of the wettest quarter were the governing factors for its distribution and hence, presented a higher gain with respect to other variables. According to permutation importance, precipitation seasonality and mean temperature of wettest quarter shows the prominent impact on the habitat distribution. Results of AUC (area under curve) were statistically significant (0.940) and the line of predicted omission falls very close to an omission on training samples, validating a better run of the model. Response curves revealed a probable increase in the occurrence of D. hatagirea with an increase in mean temperature of the wettest quarter and maximum temperature of the warmest month contributed more than 50% to predicted habitat suitability. Direct field observations concurrent with predicted habitat suitability and google-earth images represent greater model thresholds for successful inception of the species. Together, the study proposes that the species can be conserved in or near its present-day natural habitats and is equally effective in determining the possible habitats for its cultivation and reintroduction.     

Linker DNA Length is a Key to Tri-nucleosome Folding

The folding of a nucleosome array has long been one of the fundamental and unsolved problems in chromatin biology. In this study, we address how nucleosome array folding depends on the length of linker DNA. We performed molecular dynamics simulations of a tri-nucleosome, a minimal model of chromatin folding, with various linker lengths (LLs) ranging from 20 to 40 base pairs (bps). We found that the tri-nucleosome folding strongly depends on LLs, and classified the structure ensemble into five classes, named from trinuc-1 to trinuc-5. As a function of LL, the different classes appear, on average, every 2 bps with a period of 10 bps, and are characterized by distinct inter-nucleosome interactions. The trinuc-1 conformation corresponds to LL ~ 10n, where n is an integer, and is stabilized by the tight packing between the first and the third nucleosomes, consistent with a zigzag fiber form. Structures of the other four classes are more diverse and distributed continuously in the space of possible configurations. Histone-DNA electrostatic interactions in the tri-nucleosome are further analyzed.     

Single-Molecule Force Spectroscopy of Membrane Protein Folding

Single-molecule force spectroscopy is a unique method that can probe the structural changes of single proteins at a high spatiotemporal resolution while mechanically manipulating them over a wide force range. Here, we review the current understanding of membrane protein folding learned by using the force spectroscopy approach. Membrane protein folding in lipid bilayers is one of the most complex biological processes in which diverse lipid molecules and chaperone proteins are intricately involved. The approach of single protein forced unfolding in lipid bilayers has produced important findings and insights into membrane protein folding. This review provides an overview of the forced unfolding approach, including recent achievements and technical advances. Progress in the methods can reveal more interesting cases of membrane protein folding and clarify general mechanisms and principles.     

Competitive Microtubule Binding of PEX14 Coordinates Peroxisomal Protein Import and Motility

Human PEX14 plays a dual role as docking protein in peroxisomal protein import and as peroxisomal anchor for microtubules (MT), which relates to peroxisome motility. For docking, the conserved N-terminal domain of PEX14 (PEX14-NTD) binds amphipathic alpha-helical ligands, typically comprising one or two aromatic residues, of which human PEX5 possesses eight. Here, we show that the PEX14-NTD also binds to microtubular filaments in vitro with a dissociation constant in nanomolar range. PEX14 interacts with two motifs in the C-terminal region of human ß-tubulin. At least one of the binding motifs is in spatial proximity to the binding site of microtubules (MT) for kinesin. Both PEX14 and kinesin can bind to MT simultaneously. Notably, binding of PEX14 to tubulin can be prevented by its association with PEX5. The data suggest that PEX5 competes peroxisome anchoring to MT by occupying the ß-tubulin-binding site of PEX14. The competitive correlation of matrix protein import and motility may facilitate the homogeneous dispersion of peroxisomes in mammalian cells.     

The PCDDB (Protein Circular Dichroism Data Bank): A Bioinformatics Resource for Protein Characterisations and Methods Development

The Protein Circular Dichroism Data Bank (PCDDB) [https://pcddb.cryst.bbk.ac.uk] is an established resource for the biological, biophysical, chemical, bioinformatics, and molecular biology communities. It is a freely-accessible repository of validated protein circular dichroism (CD) spectra and associated sample and metadata, with entries having links to other bioinformatics resources including, amongst others, structure (PDB), AlphaFold, and sequence (UniProt) databases, as well as to published papers which produced the data and cite the database entries. It includes primary (unprocessed) and final (processed) spectral data, which are available in both text and pictorial formats, as well as detailed sample and validation information produced for each of the entries. Recently the metadata content associated with each of the entries, as well as the number and structural breadth of the protein components included, have been expanded. The PCDDB includes data on both wild-type and mutant proteins, and because CD studies primarily examine proteins in solution, it also contains examples of the effects of different environments on their structures, plus thermal unfolding/folding series. Methods for both sequence and spectral comparisons are included.The data included in the PCDDB complement results from crystal, cryo-electron microscopy, NMR spectroscopy, bioinformatics characterisations and classifications, and other structural information available for the proteins via links to other databases. The entries in the PCDDB have been used for the development of new analytical methodologies, for interpreting spectral and other biophysical data, and for providing insight into structures and functions of individual soluble and membrane proteins and protein complexes.