Pharmacokinetics Profiler (PhaKinPro): Model Development, Validation, and Implementation as a Web Tool for Triaging Compounds with Undesired Pharmacokinetics Profiles.

Computational models that predict pharmacokinetic properties are critical to deprioritize drug candidates that emerge as hits in high-throughput screening campaigns. We collected, curated, and integrated a database of compounds tested in 12 major end points comprising over 10,000 unique molecules. We then employed these data to build and validate binary quantitative structure-activity relationship (QSAR) models. All trained models achieved a correct classification rate above 0.60 and a positive predictive value above 0.50. To illustrate their utility in drug discovery, we used these models to predict the pharmacokinetic properties for drugs in the NCATS Inxight Drugs database. In addition, we employed the developed models to predict the pharmacokinetic properties of all compounds in the DrugBank. All models described in this paper have been integrated and made publicly available via the PhaKinPro Web-portal that can be accessed at https://phakinpro.mml.unc.edu/.

An Improved Metric and Benchmark for Assessing the Performance of Virtual Screening Models.

Structure-based virtual screening (SBVS) is a key workflow in computational drug discovery. SBVS models are assessed by measuring the enrichment of known active molecules over decoys in retrospective screens. However, the standard formula for enrichment cannot estimate model performance on very large libraries. Additionally, current screening benchmarks cannot easily be used with machine learning (ML) models due to data leakage. We propose an improved formula for calculating VS enrichment and introduce the BayesBind benchmarking set composed of protein targets that are structurally dissimilar to those in the BigBind training set. We assess current models on this benchmark and find that none perform appreciably better than a KNN baseline. We publicly release the BayesBind benchmark at https://github.com/molecularmodelinglab/bigbind.

Discovery of a cell-active chikungunya virus nsP2 protease inhibitor using a covalent fragment-based screening approach.

Chikungunya virus (CHIKV) is a mosquito-borne alphavirus that has been responsible for numerous large-scale outbreaks in the last twenty years. Currently, there are no FDA-approved therapeutics for any alphavirus infection. CHIKV non-structural protein 2 (nsP2), which contains a cysteine protease domain, is essential for viral replication, making it an attractive target for a drug discovery campaign. Here, we optimized a CHIKV nsP2 protease (nsP2pro) biochemical assay for the screening of a 6,120-compound cysteine-directed covalent fragment library. Using a 50% inhibition threshold, we identified 153 hits (2.5% hit rate). In dose-response follow up, RA-0002034, a covalent fragment that contains a vinyl sulfone warhead, inhibited CHIKV nsP2pro with an IC 50 of 58 ± 17 nM, and further analysis with time-dependent inhibition studies yielded a k inact /K I of 6.4 × 10 3 M -1 s -1 . LC-MS/MS analysis determined that RA-0002034 covalently modified the catalytic cysteine in a site-specific manner. Additionally, RA-0002034 showed no significant off-target reactivity against a panel of cysteine proteases. In addition to the potent biochemical inhibition of CHIKV nsP2pro activity and exceptional selectivity, RA-0002034 was tested in cellular models of alphavirus infection and effectively inhibited viral replication of both CHIKV and related alphaviruses. This study highlights the discovery and characterization of the chemical probe RA-0002034 as a promising hit compound from covalent fragment-based screening for future development toward a CHIKV or pan-alphavirus therapeutic. Significance Statement: Chikungunya virus is one of the most prominent and widespread alphaviruses and has caused explosive outbreaks of arthritic disease. Currently, there are no FDA-approved drugs to treat disease caused by chikungunya virus or any other alphavirus-caused infection. Here, we report the discovery of a covalent small molecule inhibitor of chikungunya virus nsP2 protease activity and viral replication of four diverse alphaviruses. This finding highlights the utility of covalent fragment screening for inhibitor discovery and represents a starting point towards the development of alphavirus therapeutics targeting nsP2 protease.

Utilizing Low-Dimensional Molecular Embeddings for Rapid Chemical Similarity Search.

Nearest neighbor-based similarity searching is a common task in chemistry, with notable use cases in drug discovery. Yet, some of the most commonly used approaches for this task still leverage a brute-force approach. In practice this can be computationally costly and overly time-consuming, due in part to the sheer size of modern chemical databases. Previous computational advancements for this task have generally relied on improvements to hardware or dataset-specific tricks that lack generalizability. Approaches that leverage lower-complexity searching algorithms remain relatively underexplored. However, many of these algorithms are approximate solutions and/or struggle with typical high-dimensional chemical embeddings. Here we evaluate whether a combination of low-dimensional chemical embeddings and a k-d tree data structure can achieve fast nearest neighbor queries while maintaining performance on standard chemical similarity search benchmarks. We examine different dimensionality reductions of standard chemical embeddings as well as a learned, structurally-aware embedding-SmallSA-for this task. With this framework, searches on over one billion chemicals execute in less than a second on a single CPU core, five orders of magnitude faster than the brute-force approach. We also demonstrate that SmallSA achieves competitive performance on chemical similarity benchmarks.

Synthesis of 5-Benzylamino and 5-Alkylamino-Substituted Pyrimido[4,5-c]quinoline Derivatives as CSNK2A Inhibitors with Antiviral Activity.

A series of 5-benzylamine-substituted pyrimido[4,5-c]quinoline derivatives of the CSNK2A chemical probe SGC-CK2-2 were synthesized with the goal of improving kinase inhibitor cellular potency and antiviral phenotypic activity while maintaining aqueous solubility. Among the range of analogs, those bearing electron-withdrawing (4c and 4g) or donating (4f) substituents on the benzyl ring as well as introduction of non-aromatic groups such as the cyclohexylmethyl (4t) were shown to maintain CSNK2A activity. The CSNK2A activity was also retained with N-methylation of SGC-CK2-2, but α-methyl substitution of the benzyl substituent led to a 10-fold reduction in potency. CSNK2A inhibition potency was restored with indene-based compound 4af, with activity residing in the S-enantiomer (4ag). Analogs with the highest CSNK2A potency showed good activity for inhibition of Mouse Hepatitis Virus (MHV) replication. Conformational analysis indicated that analogs with the best CSNK2A inhibition (4t, 4ac, and 4af) exhibited smaller differences between their ground state conformation and their predicted binding pose. Analogs with reduced activity (4ad, 4ae, and 4ai) required more substantial conformational changes from their ground state within the CSNK2A protein pocket.

HIt Discovery using docking ENriched by GEnerative Modeling (HIDDEN GEM): A novel computational workflow for accelerated virtual screening of ultra-large chemical libraries.

Recent rapid expansion of make-on-demand, purchasable, chemical libraries comprising dozens of billions or even trillions of molecules has challenged the efficient application of traditional structure-based virtual screening methods that rely on molecular docking. We present a novel computational methodology termed HIDDEN GEM (HIt Discovery using Docking ENriched by GEnerative Modeling) that greatly accelerates virtual screening. This workflow uniquely integrates machine learning, generative chemistry, massive chemical similarity searching and molecular docking of small, selected libraries in the beginning and the end of the workflow. For each target, HIDDEN GEM nominates a small number of top-scoring virtual hits prioritized from ultra-large chemical libraries. We have benchmarked HIDDEN GEM by conducting virtual screening campaigns for 16 diverse protein targets using Enamine REAL Space library comprising 37 billion molecules. We show that HIDDEN GEM yields the highest enrichment factors as compared to state of the art accelerated virtual screening methods, while requiring the least computational resources. HIDDEN GEM can be executed with any docking software and employed by users with limited computational resources.

BigBind: Learning from Nonstructural Data for Structure-Based Virtual Screening.

Deep learning methods that predict protein-ligand binding have recently been used for structure-based virtual screening. Many such models have been trained using protein-ligand complexes with known crystal structures and activities from the PDBBind data set. However, because PDBbind only includes 20K complexes, models typically fail to generalize to new targets, and model performance is on par with models trained with only ligand information. Conversely, the ChEMBL database contains a wealth of chemical activity information but includes no information about binding poses. We introduce BigBind, a data set that maps ChEMBL activity data to proteins from the CrossDocked data set. BigBind comprises 583 K ligand activities and includes 3D structures of the protein binding pockets. Additionally, we augmented the data by adding an equal number of putative inactives for each target. Using this data, we developed Banana (basic neural network for binding affinity), a neural network-based model to classify active from inactive compounds, defined by a 10 µM cutoff. Our model achieved an AUC of 0.72 on BigBind's test set, while a ligand-only model achieved an AUC of 0.59. Furthermore, Banana achieved competitive performance on the LIT-PCBA benchmark (median EF1% 1.81) while running 16,000 times faster than molecular docking with Gnina. We suggest that Banana, as well as other models trained on this data set, will significantly improve the outcomes of prospective virtual screening tasks.

Enhancement of Polyacrylate Antiscalant Activity during Gypsum Deposit Formation with the Pretreatment of Aqueous Solutions with Spruce Wood Shavings.

Considerable efforts are made worldwide to reduce inorganic scale in reverse osmosis plants, boilers and heat exchangers, evaporators, industrial water systems, geothermal power plants and oilfield applications. These include the development of new environmentally friendly antiscalants and the improvement of conventional ones. The present report is dedicated to the unconventional application of spruce wood shavings in combination with polyacrylate (PAA-F1) in a model case of gypsum scale formation. The electrical conductivity of freshly prepared gypsum solutions with a saturation SI = 2.3 and a concentration of 0.05 mol·dm-3 was analyzed over time at 25°C. It is demonstrated that the small amounts of wood shavings (0.1% by mass) alone, after being in contact with CaCl2 and Na2SO4 stock solutions for 15 min, increase the induction time tind by 25 min relative to the blank experiment (tindblank). In the presence of PAA-F1 (0.1 mg·dm-3), the difference Δtind = tind - tindblank constitutes 110 min, whereas the sequential treatment of the stock solutions with the shavings followed by PAA-F1 injection gives Δtind = 205 min. The observed synergism is associated with the selective removal of colloidal Fe(OH)3solid and Al(OH)3solid nanoimpurities from the stock solutions via their sorption to the well-developed surface of wood. Wood shavings therefore represent a very promising and environmentally friendly material that can significantly improve the effectiveness of conventional antiscalants.

Accurate ligand-protein docking in CASP15 using the ClusPro LigTBM server.

In the ligand prediction category of CASP15, the challenge was to predict the positions and conformations of small molecules binding to proteins that were provided as amino acid sequences or as models generated by the AlphaFold2 program. For most targets, we used our template-based ligand docking program ClusPro ligTBM, also implemented as a public server available at https://ligtbm.cluspro.org/. Since many targets had multiple chains and a number of ligands, several templates, and some manual interventions were required. In a few cases, no templates were found, and we had to use direct docking using the Glide program. Nevertheless, ligTBM was shown to be a very useful tool, and by any ranking criteria, our group was ranked among the top five best-performing teams. In fact, all the best groups used template-based docking methods. Thus, it appears that the AlphaFold2-generated models, despite the high accuracy of the predicted backbone, have local differences from the x-ray structure that make the use of direct docking methods more challenging. The results of CASP15 confirm that this limitation can be frequently overcome by homology-based docking.

Mixed, nonclassical behavior in a classic allosteric protein.

Allostery is a major driver of biological processes requiring coordination. Thus, it is one of the most fundamental and remarkable phenomena in nature, and there is motivation to understand and manipulate it to a multitude of ends. Today, it is often described in terms of two phenomenological models proposed more than a half-century ago involving only T(tense) or R(relaxed) conformations. Here, methyl-based NMR provides extensive detail on a dynamic T to R switch in the classical dimeric allosteric protein, yeast chorismate mutase (CM), that occurs in the absence of substrate, but only with the activator bound. Switching of individual subunits is uncoupled based on direct observation of mixed TR states in the dimer. This unique finding excludes both classic models and solves the paradox of a coexisting hyperbolic binding curve and highly skewed substrate-free T-R equilibrium. Surprisingly, structures of the activator-bound and effector-free forms of CM appear the same by NMR, providing another example of the need to account for dynamic ensembles. The apo enzyme, which has a sigmoidal activity profile, is shown to switch, not to R, but to a related high-energy state. Thus, the conformational repertoire of CM does not just change as a matter of degree depending on the allosteric input, be it effector and/or substrate. Rather, the allosteric model appears to completely change in different contexts, which is only consistent with modern ensemble-based frameworks.

PLANTAIN: Diffusion-inspired Pose Score Minimization for Fast and Accurate Molecular Docking.

Molecular docking aims to predict the 3D pose of a small molecule in a protein binding site. Traditional docking methods predict ligand poses by minimizing a physics-inspired scoring function. Recently, a diffusion model has been proposed that iteratively refines a ligand pose. We combine these two approaches by training a pose scoring function in a diffusion-inspired manner. In our method, PLANTAIN, a neural network is used to develop a very fast pose scoring function. We parameterize a simple scoring function on the fly and use L-BFGS minimization to optimize an initially random ligand pose. Using rigorous benchmarking practices, we demonstrate that our method achieves state-of-the-art performance while running ten times faster than the next-best method. We release PLANTAIN publicly and hope that it improves the utility of virtual screening workflows.

Tyrosinase-Catalyzed Peptide Macrocyclization for mRNA Display.

mRNA display of macrocyclic peptides has proven itself to be a powerful technique to discover high-affinity ligands for a protein target. However, only a limited number of cyclization chemistries are known to be compatible with mRNA display. Tyrosinase is a copper-dependent oxidase that oxidizes tyrosine phenol to an electrophilic o-quinone, which is readily attacked by cysteine thiol. Here we show that peptides containing tyrosine and cysteine are rapidly cyclized upon tyrosinase treatment. Characterization of the cyclization reveals it to be widely applicable to multiple macrocycle sizes and scaffolds. We combine tyrosinase-mediated cyclization with mRNA display to discover new macrocyclic ligands targeting melanoma-associated antigen A4 (MAGE-A4). These macrocycles potently inhibit the MAGE-A4 binding axis with nanomolar IC50 values. Importantly, macrocyclic ligands show clear advantage over noncyclized analogues with ∼40-fold or greater decrease in IC50 values.

Fluorescent-Tagged Antiscalants-The New Materials for Scale Inhibition Mechanism Studies, Antiscalant Traceability and Antiscaling Efficacy Optimization during CaCO3 and CaSO4·2H2O Scale Formation.

Equipment scaling leads to reduced production efficiency in a wide range of industrial applications worldwide. Various antiscaling agents are currently commonly used to mitigate this problem. However, irrespective of their long and successful application in water treatment technologies, little is known about the mechanisms of scale inhibition, particularly the localization of scale inhibitors on scale deposits. The lack of such knowledge is a limiting factor in the development of applications for antiscalants. Meanwhile, fluorescent fragments integrated into scale inhibitor molecules have provided a successful solution to the problem. The focus of this study is, therefore, on the synthesis and investigation of a novel fluorescent antiscalant: (2-(6-morpholino-1,3-dioxo-1H-benzo[de]isoquinolin-2(3H)yl)ethylazanediyl)bis(methylenephosphonic acid) (ADMP-F) which is an analog of the commercial antiscalant: aminotris(methylenephosphonic acid) (ATMP). ADMP-F has been found to effectively control the precipitation of CaCO3 and CaSO4 in solution and is a promising tracer for organophosphonate scale inhibitors. ADMP-F was compared with two other fluorescent antiscalants-polyacrylate (PAA-F1) and bisphosphonate (HEDP-F)-and was found to be highly effective: PAA-F1 > ADMP-F >> HEDP-F (CaCO3) and PAA-F1 > ADMP-F > HEDP-F (CaSO4·2H2O). The visualization of the antiscalants on the deposits provides unique information on their location and reveals differences in the "antiscalant-deposit" interactions for scale inhibitors of different natures. For these reasons, a number of important refinements to the mechanisms of scale inhibition are proposed.

Mechanisms of Phototoxic Effects of Cationic Porphyrins on Human Cells In Vitro.

The toxic effects of four cationic porphyrins on various human cells were studied in vitro. It was found that, under dark conditions, porphyrins are almost nontoxic, while, under the action of light, the toxic effect was observed starting from nanomolar concentrations. At a concentration of 100 nM, porphyrins caused inhibition of metabolism in the MTT test in normal and cancer cells. Furthermore, low concentrations of porphyrins inhibited colony formation. The toxic effect was nonlinear; with increasing concentrations of various porphyrins, up to about 1 µM, the effect reached a plateau. In addition to the MTT test, this was repeated in experiments examining cell permeability to trypan blue, as well as survival after 24 h. The first visible manifestation of the toxic action of porphyrins is blebbing and swelling of cells. Against the background of this process, permeability to porphyrins and trypan blue appears. Subsequently, most cells (even mitotic cells) freeze in this swollen state for a long time (24 and even 48 h), remaining attached. Cellular morphology is mostly preserved. Thus, it is clear that the cells undergo mainly necrotic death. The hypothesis proposed is that the concentration dependence of membrane damage indicates a limited number of porphyrin targets on the membrane. These targets may be any ion channels, which should be considered in photodynamic therapy.

Harmonically mode-locked laser pulse accumulation in a self-resonating optical cavity.

Optical enhancement cavities enabling laser pulses to be coherently stacked in free space are used in several applications to enhance accessible optical power. In this study, we develop an optical cavity that accumulates harmonically mode-locked laser pulses with a self-resonating mechanism for X-ray sources based on laser-Compton scattering. In particular, a Fabry-Perot cavity composed of 99% reflectance mirrors maintained the optical resonance in a feedback-free fashion for more than half an hour and automatically resumed the accumulation even if the laser oscillation was suspended. In contrast to conventional optical enhancement cavity systems with a dedicated feedback controller, this characteristic is highly beneficial in practical applications, such as for laser-Compton scattering X-ray sources. Lastly, upscaling and adoption of the proposed system might improve the operability and equipment use of laser Compton-scattering X-ray sources.

Application and Visualization of Fluorescent-Tagged Antiscalants in Electrodialysis Processing of Aqueous Solutions Prone to Gypsum Scale Deposition.

Membrane scaling is a serious problem in electrodialysis. A widely used technique for controlling scale deposition in water treatment technologies is the application of antiscalants (AS). The present study reports on gypsum scale inhibition in electrodialysis cell by the two novel ASs: fluorescent-tagged bisphosphonate 1-hydroxy-7-(6-methoxy-1,3-dioxo-1Hbenzo[de]isoquinolin-2(3H)-yl)heptane-1,1-diyl-bis(phosphonic acid), HEDP-F and fluorescein-tagged polyacrylate, PAA-F2 (molecular mass 4000 Da) monitored by chronopotentiometry and fluorescent microscopy. It was found that cation-exchange membrane MK-40 scaling is sufficiently reduced by both ASs, used in 10-6 mol·dm-3 concentrations. PAA-F2 at these concentrations was found to be more efficient than HEDP-F. At the same time, PAA-F2 reveals gypsum crystals' habit modification, while HEDP-F does not noticeably affect the crystal form of the deposit. The strong auto-luminescence of MK-40 hampers visualization of both PAA-F2 and HEDP-F on the membrane surface. Nevertheless, PAA-F2 is proved to localize partly on the surface of gypsum crystals as a molecular adsorption layer, and to change their crystal habit. Crystal surface coverage by PAA-F2 appears to be nonuniform. Alternatively, HEDP-F localizes on the surface of a deposit tentatively in the form of [Ca-HEDP-F]. The proposed mechanisms of action are formulated and discussed. The application of antiscalants in electrodialysis for membrane scaling mitigation is demonstrated to be very promising.

Integrated approach to elucidate metal-implant related adverse outcome pathways.

Exogenous metal particles and ions from implant devices are known to cause severe toxic events with symptoms ranging from adverse local tissue reactions to systemic toxicities, potentially leading to the development of cancers, heart conditions, and neurological disorders. Toxicity mechanisms, also known as Adverse Outcome Pathways (AOPs), that explain these metal-induced toxicities are severely understudied. Therefore, we deployed in silico structure- and knowledge-based approaches to identify proteome-level perturbations caused by metals and pathways that link these events to human diseases. We captured 177 structure-based, 347 knowledge-based, and 402 imputed metal-gene/protein relationships for chromium, cobalt, molybdenum, nickel, and titanium. We prioritized 72 proteins hypothesized to directly contact implant surfaces and contribute to adverse outcomes. Results of this exploratory analysis were formalized as structured AOPs. We considered three case studies reflecting the following possible situations: (i) the metal-protein-disease relationship was previously known; (ii) the metal-protein, protein-disease, and metal-disease relationships were individually known but were not linked (as a unified AOP); and (iii) one of three relationships was unknown and was imputed by our methods. These situations were illustrated by case studies on nickel-induced allergy/hypersensitivity, cobalt-induced heart failure, and titanium-induced periprosthetic osteolysis, respectively. All workflows, data, and results are freely available in https://github.com/DnlRKorn/Knowledge_Based_Metallomics/. An interactive view of select data is available at the ROBOKOP Neo4j Browser at http://robokopkg.renci.org/browser/.

Conserved coronavirus proteins as targets of broad-spectrum antivirals.

Coronaviruses are a class of single-stranded, positive-sense RNA viruses that have caused three major outbreaks over the past two decades: Middle East respiratory syndrome-related coronavirus (MERS-CoV), severe acute respiratory syndrome coronavirus (SARS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). All outbreaks have been associated with significant morbidity and mortality. In this study, we have identified and explored conserved binding sites in the key coronavirus proteins for the development of broad-spectrum direct acting anti-coronaviral compounds and validated the significance of this conservation for drug discovery with existing experimental data. We have identified four coronaviral proteins with highly conserved binding site sequence and 3D structure similarity: PLpro, Mpro, nsp10-nsp16 complex(methyltransferase), and nsp15 endoribonuclease. We have compiled all available experimental data for known antiviral medications inhibiting these targets and identified compounds active against multiple coronaviruses. The identified compounds representing potential broad-spectrum antivirals include: GC376, which is active against six viral Mpro (out of six tested, as described in research literature); mycophenolic acid, which is active against four viral PLpro (out of four); and emetine, which is active against four viral RdRp (out of four). The approach described in this study for coronaviruses, which combines the assessment of sequence and structure conservation across a viral family with the analysis of accessible chemical structure - antiviral activity data, can be explored for the development of broad-spectrum drugs for multiple viral families.

A Case Study of Calcium Carbonate Crystallization during Reverse Osmosis Water Desalination in Presence of Novel Fluorescent-Tagged Antiscalants.

Calcium carbonate scaling in reverse osmosis (RO) desalination process is studied in the presence of two novel fluorescent-tagged scale inhibitors 1,8-naphthalimide-tagged polyacrylate (PAA-F1) and 1-hydroxy-7-(6-methoxy-1,3-dioxo-1H-benzo[de]isoquinolin-2(3H)-yl)heptane-1,1-diyl-bis(phosphonic acid) (HEDP-F) by fluorescent microscopy (FM) and scanning electron microscopy (SEM). Both antiscalants diminished the mean size of calcite crystals relative to the blank experiment. The behavior and localization of HEDP-F and PAA-F1 during calcite scale formation on membrane surface was found to be significantly different from the distribution in similar RO experiments with gypsum, reported earlier. In the former case, both antiscalants are concentrated exactly on the surface of calcium carbonate crystals, while in the latter one they form their own phases (Ca-HEDP-F and Ca-PAA-F1) and are not detected on gypsum scale. The difference is interpreted in terms of interplay between background calcium concentration and sparingly soluble calcium salts' solubility. HEDP-F reveals slightly higher efficiency than PAA-F1 against calcite scale formation, while PAA-F exhibits a higher ability to change calcite morphology. It is demonstrated that there is a lack of correlation between antiscaling efficacy and ability of antiscalant to change calcium carbonate morphology in a particular case study. An application of fluorescent-tagged antiscalants in RO experiments provides a unique possibility to track the scale inhibitor molecules' localization during calcite scale formation. Fluorescent-tagged antiscalants are presumed to become a very powerful tool in membrane scaling inhibition studies.

Mapping co-regulatory interactions among ligand-binding sites in ryanodine receptor 1.

Ryanodine receptor 1 (RyR1) is an intracellular calcium ion (Ca2+ ) release channel required for skeletal muscle contraction. Although cryo-electron microscopy identified binding sites of three coactivators Ca2+ , ATP, and caffeine (CFF), the mechanism of co-regulation and synergy of these activators is unknown. Here, we report allosteric connections among the three ligand-binding sites and pore region in (i) Ca2+ bound-closed, (ii) ATP/CFF bound-closed, (iii) Ca2+ /ATP/CFF bound-closed, and (iv) Ca2+ /ATP/CFF bound-open RyR1 states. We identified two dominant networks of interactions that mediate communication between the Ca2+ -binding site and pore region in Ca2+ bound-closed state, which partially overlapped with the pore communications in ATP/CFF bound-closed RyR1 state. In Ca2+ /ATP/CFF bound-closed and -open RyR1 states, co-regulatory interactions were analogous to communications in the Ca2+ bound-closed and ATP/CFF bound-closed states. Both ATP- and CFF-binding sites mediate communication between the Ca2+ -binding site and the pore region in Ca2+ /ATP/CFF bound-open RyR1 structure. We conclude that Ca2+ , ATP, and CFF propagate their effects to the pore region through a network of overlapping interactions that mediate allosteric control and molecular synergy in channel regulation.