The Molecular Organization of Human cGMP Specific Phosphodiesterase 6 (PDE6): Structural Implications of Somatic Mutations in Cancer and Retinitis Pigmentosa

Identification of selective inhibitors for phosphodiesterase 5A using e-pharmacophore modelling and large-scale virtual screening-based structure guided drug discovery approaches

The inhibition of Phosphodiesterase 5A (PDEA5) has the potential to modulate pulmonary arterial hypertension and cardiovascular diseases. Exploring the cross-reactivity of clinically available PDE5A therapeutics with PDE6A is intriguing in order to develop highly selective PDE5A compounds in cardiovascular arena. In the current study, we leveraged e-pharmacophore based screening and molecular dynamics (MD) simulation to discover more selective PDE5A inhibitors as compared to the PDE6A catalytic domain. e-Pharmacophore based mapping of the CoCoCo database (7 million compounds: ∼ 150,000,000 conformers), followed by Glide docking, MM-GBSA, and protein-inhibitor interaction analysis, revealed 1536427, 4832637 and 6788240 as stable, tight binders of PDE5A instead of PDE6A. These compounds adhere to Lipinski Rule of Five (RO5) and ADME/Tox criteria. MD simulations analysis showed that 1536427 stays stable and tightly binds to catalytic (Q-region) core of PDE5A catalytic domain as compared to sildenafil. Pronounced inward motions of the hydrophobic (H-region) and Lid region indicate the closure of PDE5A-1536427 complex, whereas this region in PDE6A-1536427 is more open. Significant differences in the interactions, stability, and dynamics of 1536427 were observed in the catalytic domain of PDE6A, demonstrating less specificity for PDE6A in comparison to PDE5A. After lead optimization and therapeutic interventions, this proposed lead may emerge as a promising PDE5A selective inhibitor.Communicated by Ramaswamy H. Sarma.

Importance of Autoimmune Responses in Progression of Retinal Degeneration Initiated by Gene Mutations

Inherited retinal diseases (IRDs) are clinically and genetically heterogeneous rare disorders associated with retinal dysfunction and death of retinal photoreceptor cells, leading to blindness. Among the most frequent and severe forms of those retinopathies is retinitis pigmentosa (RP) that affects 1:4,000 individuals worldwide. The genes that have been implicated in RP are associated with the proteins present in photoreceptor cells or retinal pigment epithelium (RPE). Asymmetric presentation or sudden progression in retinal disease suggests that a gene mutation alone might not be responsible for retinal degeneration. Immune responses could directly target the retina or be site effect of immunity as a bystander deterioration. Autoantibodies against retinal autoantigens have been found in RP, which led to a hypothesis that autoimmunity could be responsible for the progression of photoreceptor cell death initiated by a genetic mutation. The other contributory factor to retinal degeneration is inflammation that activates the innate immune mechanisms, such as complement. If autoimmune responses contribute to the progression of retinopathy, this could have an implication on treatment, such as gene replacement therapy. In this review, we provide a perspective on the current role of autoimmunity/immunity in RP pathophysiology.

COSMIC Cancer Gene Census 3D database: understanding the impacts of mutations on cancer targets

Mutations in hallmark genes are believed to be the main drivers of cancer progression. These mutations are reported in the Catalogue of Somatic Mutations in Cancer (COSMIC). Structural appreciation of where these mutations appear, in protein-protein interfaces, active sites or deoxyribonucleic acid (DNA) interfaces, and predicting the impacts of these mutations using a variety of computational tools are crucial for successful drug discovery and development. Currently, there are 723 genes presented in the COSMIC Cancer Gene Census. Due to the complexity of the gene products, structures of only 87 genes have been solved experimentally with structural coverage between 90% and 100%. Here, we present a comprehensive, user-friendly, web interface (https://cancer-3d.com/) of 714 modelled cancer-related genes, including homo-oligomers, hetero-oligomers, transmembrane proteins and complexes with DNA, ribonucleic acid, ligands and co-factors. Using SDM and mCSM software, we have predicted the impacts of reported mutations on protein stability, protein-protein interfaces affinity and protein-nucleic acid complexes affinity. Furthermore, we also predicted intrinsically disordered regions using DISOPRED3.

Current Modulation of Guanylate Cyclase Pathway Activity-Mechanism and Clinical Implications

For years, guanylate cyclase seemed to be homogenic and tissue nonspecific enzyme; however, in the last few years, in light of preclinical and clinical trials, it became an interesting target for pharmacological intervention. There are several possible options leading to an increase in cyclic guanosine monophosphate concentrations. The first one is related to the uses of analogues of natriuretic peptides. The second is related to increasing levels of natriuretic peptides by the inhibition of degradation. The third leads to an increase in cyclic guanosine monophosphate concentration by the inhibition of its degradation by the inhibition of phosphodiesterase type 5. The last option involves increasing the concentration of cyclic guanosine monophosphate by the additional direct activation of soluble guanylate cyclase. Treatment based on the modulation of guanylate cyclase function is one of the most promising technologies in pharmacology. Pharmacological intervention is stable, effective and safe. Especially interesting is the role of stimulators and activators of soluble guanylate cyclase, which are able to increase the enzymatic activity to generate cyclic guanosine monophosphate independently of nitric oxide. Moreover, most of these agents are effective in chronic treatment in heart failure patients and pulmonary hypertension, and have potential to be a first line option.

Untangling Dual-Targeting Therapeutic Mechanism of Epidermal Growth Factor Receptor (EGFR) Based on Reversed Allosteric Communication

Dual-targeting therapeutics by coadministration of allosteric and orthosteric drugs is drawing increased attention as a revolutionary strategy for overcoming the drug-resistance problems. It was further observed that the occupation of orthosteric sites by therapeutics agents has the potential to enhance allosteric ligand binding, which leads to improved potency of allosteric drugs. Epidermal growth factor receptor (EGFR), as one of the most critical anti-cancer targets belonging to the receptor tyrosine kinase family, represents a quintessential example. It was revealed that osimertinib, an ATP-competitive covalent EGFR inhibitor, remarkably enhanced the affinity of a recently developed allosteric inhibitor JBJ-04-125-02 for EGFRL858R/T790M. Here, we utilized extensive large-scale molecular dynamics simulations and the reversed allosteric communication to untangle the detailed molecular underpinning, in which occupation of osimertinib at the orthosteric site altered the overall conformational ensemble of EGFR mutant and reshaped the allosteric site via long-distance signaling. A unique intermediate state resembling the active conformation was identified, which was further stabilized by osimertinib loading. Based on the allosteric communication pathway, we predicted a novel allosteric site positioned around K867, E868, H893, and K960 within the intermediate state. Its correlation with the orthosteric site was validated by both structural and energetic analysis, and its low sequence conservation indicated the potential for selective targeting across the human kinome. Together, these findings not only provided a mechanistic basis for future clinical application of the dual-targeting therapeutics, but also explored an innovative perception of allosteric inhibition of tyrosine kinase signaling.

The PDE-Opathies: Diverse Phenotypes Produced by a Functionally Related Multigene Family

The phosphodiesterase (PDE)-opathies, an expanding set of disorders caused by germline mutations in cyclic nucleotide PDEs, present an intriguing paradox. The enzymes encoded by the PDE family all hydrolyze cAMP and/or cGMP, but mutations in different family members produce very divergent phenotypes. Three interacting factors have been shown recently to contribute to this phenotypic diversity: (i) the 21 genes encode over 80 different isoforms, using alternative mRNA splicing and related mechanisms; (ii) the various isoforms have different regulatory mechanisms, mediated by their unique amino-terminal regulatory domains; (iii) the isoforms differ widely in their pattern of tissue expression. These mechanisms explain why many PDE-opathies are gain-of-function mutations and how they exemplify uniqueness and redundancy within a multigene family.

A recursive molecular docking coupled with energy-based pose-rescoring and MD simulations to identify hsGC βH-NOX allosteric modulators for cardiovascular dysfunctions

Modulating the activity of human soluble guanylate cyclase (hsGC) through allosteric regulation of the βH-NOX domain has been considered as an immediate treatment for cardiovascular disorder (CVDs). Currently available βH-NOX domain-specific agonists including cinaciguat are unable to deal with the conundrum raised due to oxidative stress in the case of CVDs and their associated comorbidities. Therefore, the idea of investigating novel compounds for allosteric regulation of hsGC activation has been rekindled to circumvent CVDs. Current study aims to identify novel βH-NOX domain-specific compounds that can selectively turn on sGC functions by modulating the conformational dynamics of the target protein. Through a comprehensive computational drug-discovery approach, we first executed a target-based performance assessment of multiple docking (PLANTS, QVina, LeDock, Vinardo, Smina) scoring functions based on multiple performance metrices. QVina showed the highest capability of selecting true-positive ligands over false positives thus, used to screen 4.8 million ZINC15 compounds against βH-NOX domain. The docked ligands were further probed in terms of contact footprint and pose reassessment through clustering analysis and PLANTS docking, respectively. Subsequently, energy-based AMBER rescoring of top 100 low-energy complexes, per-residue energy decomposition analysis, and ADME-Tox analysis yielded the top three compounds i.e. ZINC000098973660, ZINC001354120371, and ZINC000096022607. The impact of three selected ligands on the internal structural dynamics of the βH-NOX domain was also investigated through molecular dynamics simulations. The study revealed potential electrostatic interactions for better conformational dialogue between βH-NOX domain and allosteric ligands that are critical for the activation of hsGC as compared to the reference compound.

Suppression of cGMP-Dependent Photoreceptor Cytotoxicity With Mycophenolate Is Neuroprotective in Murine Models of Retinitis Pigmentosa

Purpose

To determine the effect of mycophenolate mofetil (MMF) on retinal degeneration on two mouse models of retinitis pigmentosa.

Methods

Intraperitoneal injections of MMF were administered daily in rd10 and c57 mice starting at postoperative day 12 (P12) and rd1 mice starting at P8. The effect of MMF was assessed with optical coherence tomography, immunohistochemistry, electroretinography, and OptoMotry. Whole retinal cyclic guanosine monophosphate (cGMP) and mycophenolic acid levels were quantified with mass spectrometry. Photoreceptor cGMP cytotoxicity was evaluated with cell counts of cGMP immunostaining.

Results

MMF treatment significantly delays the onset of retinal degeneration and cGMP-dependent photoreceptor cytotoxicity in rd10 and rd1 mice, albeit a more modest effect in the latter. In rd10 mice, treatment with MMF showed robust preservation of the photoreceptors up to P22 with associated suppression of cGMP immunostaining and microglial activation; The neuroprotective effect diminished after P22, but outer retinal thickness was still significantly thicker by P35 and OptoMotry response was significantly better up to P60. Whereas cGMP immunostaining of the photoreceptors were present in rd10 and rd1 mice, hyperphysiological whole retinal cGMP levels were observed only in rd1 mice.

Conclusions

Early treatment with MMF confers potent neuroprotection in two animal models of RP by suppressing the cGMP-dependent common pathway for photoreceptor cell death. The neuroprotective effect of MMF on cGMP-dependent cytotoxicity occurs independently of the presence of hyperphysiological whole retinal cGMP levels. Thus our data suggest that MMF may be an important new class of neuroprotective agent that could be useful in the treatment of patients with RP.

Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine

Protein stability predictions are becoming essential in medicine to develop novel immunotherapeutic agents and for drug discovery. Despite the large number of computational approaches for predicting the protein stability upon mutation, there are still critical unsolved problems: 1) the limited number of thermodynamic measurements for proteins provided by current databases; 2) the large intrinsic variability of ΔΔG values due to different experimental conditions; 3) biases in the development of predictive methods caused by ignoring the anti-symmetry of ΔΔG values between mutant and native protein forms; 4) over-optimistic prediction performance, due to sequence similarity between proteins used in training and test datasets. Here, we review these issues, highlighting new challenges required to improve current tools and to achieve more reliable predictions. In addition, we provide a perspective of how these methods will be beneficial for designing novel precision medicine approaches for several genetic disorders caused by mutations, such as cancer and neurodegenerative diseases.

A novel mutation in PDE6B in Spanish Water Dogs with early-onset progressive retinal atrophy

OBJECTIVE

To identify the underlying mutation in a recently identified early-onset progressive retinal atrophy (PRA) in the Spanish Water Dog (SWD) breed.

ANIMAL STUDIED

Eighteen SWDs were used in this study. Six SWDs diagnosed with PRA and 12 phenotypically normal SWDs.

PROCEDURES

An exclusion analysis using an established microsatellite panel to screen PRA candidate genes was combined with whole genome sequencing of two affected SWD siblings and two phenotypically normal SWDs (a sibling and the dam).

RESULTS

A 6-bp deletion was identified in exon 19 of PDE6B removing two highly conserved amino acids from the enzymatic domain of the PDE6B protein (c.2218-2223del; p.Phe740_Phe741del). This segregated with the disease status in the small study pedigree.

CONCLUSIONS

Identification of this novel PDE6B mutation adds to the already described PDE6B mutations responsible for PRA in the Irish Setter, Sloughi, and American Staffordshire Terrier dog breeds. A DNA-based test was designed to allow breeders to genotype their animals and make informed breeding decisions in the effort to eradicate PRA from the SWD breed.

Exploring the structural basis of conformational heterogeneity and autoinhibition of human cGMP-specific protein kinase Iα through computational modelling and molecular dynamics simulations

Protein kinase Iα (PKGIα) is a pivotal cyclic guanosine monophosphate (cGMP) signalling protein. Major steps related to the structural plasticity of PKGIα have been inferred but the structural aspects of the auto-inhibition and multidomain tertiary organization of human PKGIα in active and inactive form are not clear. Here we combine computational comparative modelling, protein-protein docking and molecular dynamics (MD) simulations to investigate structural details of the repressed state of the catalytic domain of PKGIα. Exploration of the potential inhibitory conformation of the auto-inhibitory domain (AI) within the catalytic cleft reveals that the pseudo-substrate motif binds with residues of the glycine rich loop and substrate-binding lobe. Dynamic changes as a result of coupling of the catalytic and AI domains are also investigated. The three-dimensional homodimeric models of PKGIα in the active and inactive state indicate that PKGIα in its inactive-state attains a compact globular structure where cyclic nucleotide binding (CNB-A/B) domains are buried, whereas the catalytic domains are inaccessible with their substrate-binding pockets facing the N-terminal of CNB-A. Contrary to this, the active-state model of PKGIα shows an extended conformation where CNB-A/B domains are slightly rearranged and the catalytic domains of homodimer flanking the C-terminal with their substrate binding lobes free to entrap downstream proteins. These findings are consistent with previously reported static images of the multidomain organization of PKGIα. Structural insights pertaining to the conformational heterogeneity and auto-inhibition of PKGIα provided in this study may help to understand the dynamics-driven effective regulation of PKGIα.

Probing the Structural Dynamics of the Catalytic Domain of Human Soluble Guanylate Cyclase

In the nitric oxide (NO) signaling pathway, human soluble guanylate cyclase (hsGC) synthesizes cyclic guanosine monophosphate (cGMP); responsible for the regulation of cGMP-specific protein kinases (PKGs) and phosphodiesterases (PDEs). The crystal structure of the inactive hsGC cyclase dimer is known, but there is still a lack of information regarding the substrate-specific internal motions that are essential for the catalytic mechanism of the hsGC. In the current study, the hsGC cyclase heterodimer complexed with guanosine triphosphate (GTP) and cGMP was subjected to molecular dynamics simulations, to investigate the conformational dynamics that have functional implications on the catalytic activity of hsGC. Results revealed that in the GTP-bound complex of the hsGC heterodimer, helix 1 of subunit α (α:h1) moves slightly inwards and comes close to helix 4 of subunit β (β:h4). This conformational change brings loop 2 of subunit β (β:L2) closer to helix 2 of subunit α (α:h2). Likewise, loop 2 of subunit α (α:L2) comes closer to helix 2 of subunit β (β:h2). These structural events stabilize and lock GTP within the closed pocket for cyclization. In the cGMP-bound complex, α:L2 detaches from β:h2 and establishes interactions with β:L2, which results in the loss of global structure compactness. Furthermore, with the release of pyrophosphate, the interaction between α:h1 and β:L2 weakens, abolishing the tight packing of the binding pocket. This study discusses the conformational changes induced by the binding of GTP and cGMP to the hsGC catalytic domain, valuable in designing new therapeutic strategies for the treatment of cardiovascular diseases.

Prediction of impacts of mutations on protein structure and interactions: SDM, a statistical approach, and mCSM, using machine learning

Next-generation sequencing methods have not only allowed an understanding of genome sequence variation during the evolution of organisms but have also provided invaluable information about genetic variants in inherited disease and the emergence of resistance to drugs in cancers and infectious disease. A challenge is to distinguish mutations that are drivers of disease or drug resistance, from passengers that are neutral or even selectively advantageous to the organism. This requires an understanding of impacts of missense mutations in gene expression and regulation, and on the disruption of protein function by modulating protein stability or disturbing interactions with proteins, nucleic acids, small molecule ligands, and other biological molecules. Experimental approaches to understanding differences between wild-type and mutant proteins are most accurate but are also time-consuming and costly. Computational tools used to predict the impacts of mutations can provide useful information more quickly. Here, we focus on two widely used structure-based approaches, originally developed in the Blundell lab: site-directed mutator (SDM), a statistical approach to analyze amino acid substitutions, and mutation cutoff scanning matrix (mCSM), which uses graph-based signatures to represent the wild-type structural environment and machine learning to predict the effect of mutations on protein stability. Here, we describe DUET that uses machine learning to combine the two approaches. We discuss briefly the development of mCSM for understanding the impacts of mutations on interfaces with other proteins, nucleic acids, and ligands, and we exemplify the wide application of these approaches to understand human genetic disorders and drug resistance mutations relevant to cancer and mycobacterial infections. STATEMENT FOR A BROADER AUDIENCE: Genetic or somatic changes in genes can lead to mutations in human proteins, which give rise to genetic disorders or cancer, or to genes of pathogens leading to drug resistance. Computer software described here, using statistical approaches or machine learning, uses the information from genome sequencing of humans and pathogens, together with experimental or modeled 3D structures of gene products, the proteins, to predict impacts of mutations in genetic disease, cancer and drug resistance.

The molecular architecture of photoreceptor phosphodiesterase 6 (PDE6) with activated G protein elucidates the mechanism of visual excitation

Photoreceptor phosphodiesterase 6 (PDE6) is the central effector of the visual excitation pathway in both rod and cone photoreceptors, and PDE6 mutations that alter PDE6 structure or regulation can result in several human retinal diseases. The rod PDE6 holoenzyme consists of two catalytic subunits (Pαβ) whose activity is suppressed in the dark by binding of two inhibitory γ-subunits (Pγ). Upon photoactivation of rhodopsin, the heterotrimeric G protein (transducin) is activated, resulting in binding of the activated transducin α-subunit (Gt_α) to PDE6, displacement of Pγ from the PDE6 active site, and enzyme activation. Although the biochemistry of this pathway is understood, a lack of detailed structural information about the PDE6 activation mechanism hampers efforts to develop therapeutic interventions for managing PDE6-associated retinal diseases. To address this gap, here we used a cross-linking MS-based approach to create a model of the entire interaction surface of Pγ with the regulatory and catalytic domains of Pαβ in its nonactivated state. Following reconstitution of PDE6 and activated Gt_α with liposomes and identification of cross-links between Gt_α and PDE6 subunits, we determined that the PDE6-Gt_α protein complex consists of two Gt_α-binding sites per holoenzyme. Each Gt_α interacts with the catalytic domains of both catalytic subunits and induces major changes in the interaction sites of the Pγ subunit with the catalytic subunits. These results provide the first structural model for the activated state of the transducin-PDE6 complex during visual excitation, enhancing our understanding of the molecular etiology of inherited retinal diseases.

Allosteric Regulation of Rod Photoreceptor Phosphodiesterase 6 (PDE6) Elucidated by Chemical Cross-Linking and Quantitative Mass Spectrometry

Photoreceptor phosphodiesterase (PDE6) is the central effector enzyme in the visual excitation pathway in rod and cone photoreceptors. Its tight regulation is essential for the speed, sensitivity, recovery, and adaptation of visual signaling. The rod PDE6 holoenzyme (Pαβγ₂) is composed of a catalytic heterodimer (Pαβ) that binds two inhibitory γ subunits. Each of the two catalytic subunits (Pα and Pβ) contains a catalytic domain responsible for cGMP hydrolysis and two tandem GAF domains, one of which binds cGMP noncatalytically. Unlike related GAF-containing PDEs where cGMP binding allosterically activates catalysis, the physiological significance of cGMP binding to the GAF domains of PDE6 is unknown. To elucidate the structural determinants of PDE6 allosteric regulators, we biochemically characterized PDE6 complexes in various allosteric states (Pαβ, Pαβ-cGMP, Pαβγ₂, and Pαβγ₂-cGMP) with a quantitative cross-linking/mass spectrometry approach. We employed a normalization strategy to dissect the cross-linking reactivity of individual residues in order to assess the spatial cross-linking propensity of detected pairs. In addition to identifying cross-linked pairs that undergo conformational changes upon ligand binding, we observed an asymmetric binding of the inhibitory γ-subunit and the noncatalytic cGMP to the GAFa domains of rod PDE6, as well as a stable open conformation of Pαβ catalytic dimer in different allosteric states. These results advance our understanding of the exquisite regulatory control of the lifetime of rod PDE6 activation/deactivation during visual signaling, as well as providing a structural basis for interpreting how mutations in rod PDE6 subunits can lead to retinal diseases.