AlloViz: A tool for the calculation and visualisation of protein allosteric communication networks

Allostery, the presence of functional interactions between distant parts of proteins, is a critical concept in the field of biochemistry and molecular biology, particularly in the context of protein function and regulation. Understanding the principles of allosteric regulation is essential for advancing our knowledge of biology and developing new therapeutic strategies. This paper presents AlloViz, an open-source Python package designed to quantitatively determine, analyse, and visually represent allosteric communication networks on the basis of molecular dynamics (MD) simulation data. The software integrates well-known techniques for understanding allosteric properties simplifying the process of accessing, rationalising, and representing protein allostery and communication routes. It overcomes the inefficiency of having multiple methods with heterogeneous implementations and showcases the advantages of using MD simulations and multiple replicas to obtain statistically sound information on protein dynamics; it also enables the calculation of "consensus-like" scores aggregating methods that consider multiple structural aspects of allosteric networks. We demonstrate the features of AlloViz on two proteins: β-arrestin 1, a key player for regulating G protein-coupled receptor (GPCR) signalling, and the protein tyrosine phosphatase 1B, an important pharmaceutical target for allosteric inhibitors. The software includes comprehensive documentation and examples, tutorials, and a user-friendly graphical interface.

Mining the Dynamical Properties of Substrate and FAD Binding Pockets of LSD1: Hints for New Inhibitor Design Direction

Lysine-specific demethylase 1 (LSD1), a highly sophisticated epigenetic regulator, orchestrates a range of critical cellular processes, holding promising therapeutic potential for treating diverse diseases. However, the clinical research progress targeting LSD1 is very slow. After 20 years of research, only one small-molecule drug, BEA-17, targeting the degradation of LSD1 and CoREST has been approved by the U.S. Food and Drug Administration. The primary reason for this may be the lack of abundant structural data regarding its intricate functions. To gain a deeper understanding of its conformational dynamics and guide the drug design process, we conducted molecular dynamics simulations to explore the conformational states of LSD1 in the apo state and under the influence of cofactors of flavin adenine dinucleotide (FAD) and CoREST. Our results showed that, across all states, the substrate binding pocket exhibited high flexibility, whereas the FAD binding pocket remained more stable. These distinct dynamical properties are essential for LSD1's ability to bind various substrates while maintaining efficient demethylation activity. Both pockets can be enlarged by merging with adjacent pockets, although only the substrate binding pocket can shrink into smaller pockets. These new pocket shapes can inform inhibitor design, particularly for selectively FAD-competitive inhibitors of LSD1, given the presence of numerous FAD-dependent enzymes in the human body. More interestingly, in the absence of FAD binding, the united substrate and FAD binding pocket are partitioned by the conserved residue of Tyr761, offering valuable insights for the design of inhibitors that disrupt the crucial steric role of Tyr761 and the redox role of FAD. Additionally, we identified pockets that positively or negatively correlate with the substrate and FAD binding pockets, which can be exploited for the design of allosteric or concurrent inhibitors. Our results reveal the intricate dynamical properties of LSD1 as well as multiple novel conformational states, which deepen our understanding of its sophisticated functions and aid in the rational design of new inhibitors.

G protein-coupled receptors (GPCRs): advances in structures, mechanisms, and drug discovery

G protein-coupled receptors (GPCRs), the largest family of human membrane proteins and an important class of drug targets, play a role in maintaining numerous physiological processes. Agonist or antagonist, orthosteric effects or allosteric effects, and biased signaling or balanced signaling, characterize the complexity of GPCR dynamic features. In this study, we first review the structural advancements, activation mechanisms, and functional diversity of GPCRs. We then focus on GPCR drug discovery by revealing the detailed drug-target interactions and the underlying mechanisms of orthosteric drugs approved by the US Food and Drug Administration in the past five years. Particularly, an up-to-date analysis is performed on available GPCR structures complexed with synthetic small-molecule allosteric modulators to elucidate key receptor-ligand interactions and allosteric mechanisms. Finally, we highlight how the widespread GPCR-druggable allosteric sites can guide structure- or mechanism-based drug design and propose prospects of designing bitopic ligands for the future therapeutic potential of targeting this receptor family.

Machine learning approaches in predicting allosteric sites

Allosteric regulation is a fundamental biological mechanism that can control critical cellular processes via allosteric modulator binding to protein distal functional sites. The advantages of allosteric modulators over orthosteric ones have sparked the development of numerous computational approaches, such as the identification of allosteric binding sites, to facilitate allosteric drug discovery. Building on the success of machine learning (ML) models for solving complex problems in biology and chemistry, several ML models for predicting allosteric sites have been developed. In this review, we provide an overview of these models and discuss future perspectives powered by the field of artificial intelligence such as protein language models.

Current Trends in Sirtuin Activator and Inhibitor Development

Sirtuins are NAD+-dependent protein deacylases and key metabolic regulators, coupling the cellular energy state with selective lysine deacylation to regulate many downstream cellular processes. Humans encode seven sirtuin isoforms (Sirt1-7) with diverse subcellular localization and deacylase targets. Sirtuins are considered protective anti-aging proteins since increased sirtuin activity is canonically associated with lifespan extension and decreased activity with developing aging-related diseases. However, sirtuins can also assume detrimental cellular roles where increased activity contributes to pathophysiology. Modulation of sirtuin activity by activators and inhibitors thus holds substantial potential for defining the cellular roles of sirtuins in health and disease and developing therapeutics. Instead of being comprehensive, this review discusses the well-characterized sirtuin activators and inhibitors available to date, particularly those with demonstrated selectivity, potency, and cellular activity. This review also provides recommendations regarding the best-in-class sirtuin activators and inhibitors for practical research as sirtuin modulator discovery and refinement evolve.

Modulation of Allostery with Multiple Mechanisms by Hotspot Mutations in TetR

Modulating allosteric coupling offers unique opportunities for biomedical applications. Such efforts can benefit from efficient prediction and evaluation of allostery hotspot residues that dictate the degree of cooperativity between distant sites. We demonstrate that effects of allostery hotspot mutations can be evaluated qualitatively and semiquantitatively by molecular dynamics simulations in a bacterial tetracycline repressor (TetR). The simulations recapitulate the effects of these mutations on abolishing the induction function of TetR and provide a rationale for the different rescuabilities observed to restore allosteric coupling of the hotspot mutations. We demonstrate that the same noninducible phenotype could be the result of perturbations in distinct structural and energetic properties of TetR. Our work underscores the value of explicitly computing the functional free energy landscapes to effectively evaluate and rank hotspot mutations despite the prevalence of compensatory interactions and therefore provides quantitative guidance to allostery modulation for therapeutic and engineering applications.

A Structure-Based Allosteric Modulator Design Paradigm

Importance: Allosteric drugs bound to topologically distal allosteric sites hold a substantial promise in modulating therapeutic targets deemed undruggable at their orthosteric sites. Traditionally, allosteric modulator discovery has predominantly relied on serendipitous high-throughput screening. Nevertheless, the landscape has undergone a transformative shift due to recent advancements in our understanding of allosteric modulation mechanisms, coupled with a significant increase in the accessibility of allosteric structural data. These factors have extensively promoted the development of various computational methodologies, especially for machine-learning approaches, to guide the rational design of structure-based allosteric modulators. Highlights: We here presented a comprehensive structure-based allosteric modulator design paradigm encompassing 3 critical stages: drug target acquisition, allosteric binding site, and modulator discovery. The recent advances in computational methods in each stage are encapsulated. Furthermore, we delve into analyzing the successes and obstacles encountered in the rational design of allosteric modulators. Conclusion: The structure-based allosteric modulator design paradigm holds immense potential for the rational design of allosteric modulators. We hope that this review would heighten awareness of the use of structure-based computational methodologies in advancing the field of allosteric drug discovery.

Allosteric modulation of SHP2: Quest from known to unknown

Src homology-2 domain-containing protein tyrosine phosphatase-2 (SHP2) is a key regulatory factor in the cell cycle and its activating mutations play an important role in the development of various cancers, making it an important target for antitumor drugs. Due to the highly conserved amino acid sequence and positively charged nature of the active site of SHP2, it is difficult to discover inhibitors with high affinity for the catalytic site of SHP2 and sufficient cell permeability, making it considered an "undruggable" target. However, the discovery of allosteric regulation mechanisms provides new opportunities for transforming undruggable targets into druggable ones. Given the limitations of orthosteric inhibitors, SHP2 allosteric inhibitors have become a more selective and safer research direction. In this review, we elucidate the oncogenic mechanism of SHP2 and summarize the discovery methods of SHP2 allosteric inhibitors, providing new strategies for the design and improvement of SHP2 allosteric inhibitors.

A focus on harnessing big data and artificial intelligence: revolutionizing drug discovery from traditional Chinese medicine sources

The advent of big data-driven artificial intelligence (AI) modeling has profoundly impacted the realm of drug discovery. Chen et al. (Q. Lv et al., Chem. Sci., 2023, https://doi.org/10.1039/D3SC02139D) have paved a way for modern drug discovery from traditional Chinese medicine (TCM) sources through their efforts over the past decade. They achieved this by creating TCMBank, the most extensive systematic central resource for TCM, which integrates standardized TCM-related big data and streamlines the AI-based drug discovery process.

Research progress of indole-fused derivatives as allosteric modulators: Opportunities for drug development

Allosteric modulation is a direct and effective method for regulating the function of biological macromolecules, which play vital roles in various cellular activities. Unlike orthosteric modulators, allosteric modulators bind to sites distant from the protein's orthosteric/active site and can have specific effects on the protein's function or activity without competing with endogenous ligands. Compared to traditional orthosteric modulators, allosteric modulators offer several advantages, including reduced side effects, greater specificity, and lower toxicity, making them a promising strategy for developing novel drugs. Indole-fused architectures are widely distributed in natural products and bioactive drug leads, displaying diverse biological activities that attract the interest of both chemists and biologists in drug discovery. Currently, an increasing number of indole-fused compounds have exhibited potent activities in allosteric modulation. In this review, we provide a brief summary of examples of allosteric modulators based on the indole-fused complex architecture, highlighting the strategies for drug design/discovery and the structure-activity relationships of allosteric modulators from the perspective of medicinal chemistry.

Recent applications of computational methods to allosteric drug discovery

Interest in exploiting allosteric sites for the development of new therapeutics has grown considerably over the last two decades. The chief driving force behind the interest in allostery for drug discovery stems from the fact that in comparison to orthosteric sites, allosteric sites are less conserved across a protein family, thereby offering greater opportunity for selectivity and ultimately tolerability. While there is significant overlap between structure-based drug design for orthosteric and allosteric sites, allosteric sites offer additional challenges mostly involving the need to better understand protein flexibility and its relationship to protein function. Here we examine the extent to which structure-based drug design is impacting allosteric drug design by highlighting several targets across a variety of target classes.

Green and efficient one-pot three-component synthesis of novel drug-like furo[2,3–d]pyrimidines as potential active site inhibitors and putative allosteric hotspots modulators of both SARS-CoV-2 MPro and PLPro

In this paper, an environmentally benign, convenient, and efficient one-pot three-component reaction has been developed for the regioselective synthesis of novel 5-aroyl(or heteroaroyl)-6-(alkylamino)-1,3-dimethylfuro[2,3-d]pyrimidine-2,4(1H,3H)-diones (4a‒n) through the sequential condensation of aryl(or heteroaryl)glyoxal monohydrates (1a‒g), 1,3-dimethylbarbituric acid (2), and alkyl(viz. cyclohexyl or tert-butyl)isocyanides (3a or 3b) catalyzed by ultra-low loading ZrOCl₂•8H₂O (just 2 mol%) in water at 50 ˚C. After synthesis and characterization of the mentioned furo[2,3-d]pyrimidines (4a‒n), their multi-targeting inhibitory properties were investigated against the active site and putative allosteric hotspots of both SARS-CoV-2 main protease (M^Pro) and papain-like protease (PL^Pro) based on molecular docking studies and compare the attained results with various medicinal compounds which approximately in three past years were used, introduced, and or repurposed to fight against COVID-19. Furthermore, drug-likeness properties of the mentioned small heterocyclic frameworks (4a‒n) have been explored using in silico ADMET analyses. Interestingly, the molecular docking studies and ADMET-related data revealed that the novel series of furo[2,3-d]pyrimidines (4a‒n), especially 5-(3,4-methylendioxybenzoyl)-6-(cyclohexylamino)-1,3-dimethylfuro[2,3-d]pyrimidine-2,4(1H,3H)-dione (4g) as hit one is potential COVID-19 drug candidate, can subject to further in vitro and in vivo studies. It is worthwhile to note that the protein-ligand-type molecular docking studies on the human body temperature-dependent M^Pro protein that surprisingly contains zinc^II (Zn^II) ion between His41/Cys145 catalytic dyad in the active site, which undoubtedly can make new plans for designing novel SARS-CoV-2 M^Pro inhibitors, is performed for the first time in this paper, to the best of our knowledge.

Identification and Inhibition of the Druggable Allosteric Site of SARS-CoV-2 NSP10/NSP16 Methyltransferase through Computational Approaches

Since its emergence in early 2019, the respiratory infectious virus, SARS-CoV-2, has ravaged the health of millions of people globally and has affected almost every sphere of life. Many efforts are being made to combat the COVID-19 pandemic’s emerging and recurrent waves caused by its evolving and more infectious variants. As a result, novel and unexpected targets for SARS-CoV-2 have been considered for drug discovery. 2′-O-Methyltransferase (nsp10/nsp16) is a significant and appealing target in the SARS-CoV-2 life cycle because it protects viral RNA from the host degradative enzymes via a cap formation process. In this work, we propose prospective allosteric inhibitors that target the allosteric site, SARS-CoV-2 MTase. Four drug libraries containing ~119,483 compounds were screened against the allosteric site of SARS-CoV-2 MTase identified in our research. The identified best compounds exhibited robust molecular interactions and alloscore-score rankings with the allosteric site of SARS-CoV-2 MTase. Moreover, to further assess the dynamic stability of these compounds (CHEMBL2229121, ZINC000009464451, SPECS AK-91811684151, NCI-ID = 715319), a 100 ns molecular dynamics simulation, along with its holo-form, was performed to provide insights on the dynamic nature of these allosteric inhibitors at the allosteric site of the SARS-CoV-2 MTase. Additionally, investigations of MM-GBSA binding free energies revealed a good perspective for these allosteric inhibitor–enzyme complexes, indicating their robust antagonistic action on SARS-CoV-2 (nsp10/nsp16) methyltransferase. We conclude that these allosteric repressive agents should be further evaluated through investigational assessments in order to combat the proliferation of SARS-CoV-2.

The Role of Conformational Dynamics and Allostery in the Control of Distinct Efficacies of Agonists to the Glucocorticoid Receptor

Glucocorticoid receptor (GR) regulates various cellular functions. Given its broad influence on metabolic activities, it has been the target of drug discovery for decades. However, how drugs induce conformational changes in GR has remained elusive. Herein, we used five GR agonists (dex, AZ938, pred, cor, and dibC) with different efficacies to investigate which aspect of the ligand induced the differences in efficacy. We performed molecular dynamics simulations on the five systems (dex-, AZ938-, pred-, cor-, and dibC-bound systems) and observed a distinct discrepancy in the conformation of the cofactor TIF2. Moreover, we discovered ligand-induced differences regarding the level of conformational changes posed by the binding of cofactor TIF2 and identified a pair of essential residues D590 and T39. We further found a positive correlation between the efficacies of ligands and the interaction of the two binding pockets’ domains, where D590 and T739 were involved, implying their significance in the participation of allosteric communication. Using community network analysis, two essential communities containing D590 and T739 were identified with their connectivity correlating to the efficacy of ligands. The potential communication pathways between these two residues were revealed. These results revealed the underlying mechanism of allosteric communication between the ligand-binding and cofactor-binding pockets and identified a pair of important residues in the allosteric communication pathway, which can serve as a guide for future drug discovery.

Coarse grained modelling highlights the binding differences in the two different allosteric sites of the Human Kinesin EG5 and its implications in inhibitor design

Kinesins involved in mitotic cell division have gained prominence as promising chemotherapy targets. One such kinesin, EG5, a motor protein responsible for cell division, is a validated chemotherapy target with several compounds at various stages of clinical trials. EG5 has an active site and two different allosteric sites that are known to have ligand specificity. Upon ligand binding, EG5's motor domain will no longer undergo nucleotide-dependent conformational changes required to complete the catalytic cycle. However, there is a lack of in-depth knowledge on the mechanism of inhibitor binding to the two different allosteric sites. To understand the EG5's inhibition mechanism and interactions at allosteric sites and other functionally important regions, we generated two coarse-grained models, Gaussian Network Model (GNM) and Anisotropic Network Model (ANM), to identify the dynamics and its correlation to EG5's function. The first three slowest modes of GNM showed marked differences between the various models of EG5. In the first mode, when the inhibitor is bound at allosteric site 1, there is a presence of a hinge region around residue 166, which is not found when the inhibitor is bound at allosteric site 2 or allosteric sites 1 and 2. The third slowest mode showed a distinctive positively correlated region when the inhibitor is bound at allosteric site 2. These differences indicated that the mechanism of binding at allosteric site 1 and allosteric site 2 are unique. Further, it was observed that the simultaneous ligand binding at allosteric sites 1 and 2 shares structural dynamics and interactions that were found while ligand binds at allosteric sites 1 and 2 independently, leading to a new mechanism. Taken together, our observations suggest that there are different mechanisms at play in each inhibitor bound system considered.

Therapeutic Targeting the Allosteric Cysteinome of RAS and Kinase Families

Allosteric mechanisms are pervasive in nature, but human-designed allosteric perturbagens are rare. The history of KRAS^G12C inhibitor development suggests that covalent chemistry may be a key to expanding the armamentarium of allosteric inhibitors. In that effort, irreversible targeting of a cysteine converted a non-deal allosteric binding pocket and low affinity ligands into a tractable drugging strategy. Here we examine the feasibility of expanding this approach to other allosteric pockets of RAS and kinase family members, given that both protein families are regulators of vital cellular processes that are often dysregulated in cancer and other human diseases. Moreover, these heavily studied families are the subject of numerous drug development campaigns that have resulted, sometimes serendipitously, in the discovery of allosteric inhibitors. We consequently conducted a comprehensive search for cysteines, a commonly targeted amino acid for covalent drugs, using AlphaFold-generated structures of those families. This new analysis presents potential opportunities for allosteric targeting of validated and understudied drug targets, with an emphasis on cancer therapy.

Allosteric pluripotency: challenges and opportunities

Allosteric pluripotency arises when the functional response of an allosteric receptor to an allosteric stimulus depends on additional allosteric modulators. Here, we discuss allosteric pluripotency as observed in the prototypical Protein Kinase A (PKA) as well as in other signaling systems, from typical multidomain signaling proteins to bacterial enzymes. We identify key drivers of pluripotent allostery and illustrate how hypothesizing allosteric pluripotency may solve apparent discrepancies currently present in the literature regarding the dual nature of known allosteric modulators. We also outline the implications of allosteric pluripotency for cellular signaling and allosteric drug design, and analyze the challenges and opportunities opened by the pluripotent nature of allostery.

Autopromotion of K-Ras4B Feedback Activation Through an SOS-Mediated Long-Range Allosteric Effect

The Ras-specific guanine nucleotide exchange factors Son of Sevenless (SOS) regulates Ras activation by converting inactive GDP-bound to active GTP-bound states. The catalytic activity of Ras is further allosterically regulated by GTP−Ras bound to a distal site through a positive feedback loop. To address the mechanism underlying the long-range allosteric activation of the catalytic K-Ras4B by an additional allosteric GTP–Ras through SOS, we employed molecular dynamics simulation of the K-Ras4B^G13D•SOS^cat complex with and without an allosteric GTP-bound K-Ras4B^G13D. We found that the binding of an allosteric GTP−K-Ras4B^G13D enhanced the affinity between the catalytic K-Ras4B^G13D and SOS^cat, forming a more stable conformational state. The peeling away of the switch I from the nucleotide binding site facilitated the dissociation of GDP, thereby contributing to the increased nucleotide exchange rate. The community networks further showed stronger edge connection upon allosteric GTP−K-Ras4B^G13D binding, which represented an increased interaction between catalytic K-Ras4B^G13D and SOS^cat. Moreover, GTP−K-Ras4B^G13D binding transmitted allosteric signaling pathways though the Cdc25 domain of SOS that enhanced the allosteric regulatory from the K-Ras4B^G13D allosteric site to the catalytic site. This study may provide an in-depth mechanism for abnormal activation and allosteric regulation of K-Ras4B^G13D.

Mechanistic Insights Into Co-Administration of Allosteric and Orthosteric Drugs to Overcome Drug-Resistance in T315I BCR-ABL1

Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm, driven by the BCR-ABL1 fusion oncoprotein. The discovery of orthosteric BCR-ABL1 tyrosine kinase inhibitors (TKIs) targeting its active ATP-binding pocket, such as first-generation Imatinib and second-generation Nilotinib (NIL), has profoundly revolutionized the therapeutic landscape of CML. However, currently targeted therapeutics still face considerable challenges with the inevitable emergence of drug-resistant mutations within BCR-ABL1. One of the most common resistant mutations in BCR-ABL1 is the T315I gatekeeper mutation, which confers resistance to most current TKIs in use. To resolve such conundrum, co-administration of orthosteric TKIs and allosteric drugs offers a novel paradigm to tackle drug resistance. Remarkably, previous studies have confirmed that the dual targeting BCR-ABL1 utilizing orthosteric TKI NIL and allosteric inhibitor ABL001 resulted in eradication of the CML xenograft tumors, exhibiting promising therapeutic potential. Previous studies have demonstrated the cooperated mechanism of two drugs. However, the conformational landscapes of synergistic effects remain unclear, hampering future efforts in optimizations and improvements. Hence, extensive large-scale molecular dynamics (MD) simulations of wide type (WT), WT-NIL, T315I, T315I-NIL, T315I-ABL001 and T315I-ABL001-NIL systems were carried out in an attempt to address such question. Simulation data revealed that the dynamic landscape of NIL-bound BCR-ABL1 was significantly reshaped upon ABL001 binding, as it shifted from an active conformation towards an inactive conformation. The community network of allosteric signaling was analyzed to elucidate the atomistic overview of allosteric regulation within BCR-ABL1. Moreover, binding free energy analysis unveiled that the affinity of NIL to BCR-ABL1 increased by the induction of ABL001, which led to its favorable binding and the release of drug resistance. The findings uncovered the in-depth structural mechanisms underpinning dual-targeting towards T315I BCR-ABL1 to overcome its drug resistance and will offer guidance for the rational design of next generations of BCR-ABL1 modulators and future combinatory therapeutic regimens.

Deciphering the Mechanism of Gilteritinib Overcoming Lorlatinib Resistance to the Double Mutant I1171N/F1174I in Anaplastic Lymphoma Kinase

Anaplastic lymphoma kinase (ALK) is validated as a therapeutic molecular target in multiple malignancies, such as non-small cell lung cancer (NSCLC). However, the feasibility of targeted therapies exerted by ALK inhibitors is inevitably hindered owing to drug resistance. The emergence of clinically acquired drug mutations has become a major challenge to targeted therapies and personalized medicines. Thus, elucidating the mechanism of resistance to ALK inhibitors is helpful for providing new therapeutic strategies for the design of next-generation drug. Here, we used molecular docking and multiple molecular dynamics simulations combined with correlated and energetical analyses to explore the mechanism of how gilteritinib overcomes lorlatinib resistance to the double mutant ALK I1171N/F1174I. We found that the conformational dynamics of the ALK kinase domain was reduced by the double mutations I1171N/F1174I. Moreover, energetical and structural analyses implied that the double mutations largely disturbed the conserved hydrogen bonding interactions from the hinge residues Glu1197 and Met1199 in the lorlatinib-bound state, whereas they had no discernible adverse impact on the binding affinity and stability of gilteritinib-bound state. These discrepancies created the capacity of the double mutant ALK I1171N/F1174I to confer drug resistance to lorlatinib. Our result anticipates to provide a mechanistic insight into the mechanism of drug resistance induced by ALK I1171N/F1174I that are resistant to lorlatinib treatment in NSCLC.

Harnessing Reversed Allosteric Communication: A Novel Strategy for Allosteric Drug Discovery

Allostery is a fundamental and extensive mechanism of intramolecular signal transmission. Allosteric drugs possess several unique pharmacological advantages over traditional orthosteric drugs, including greater selectivity, better physicochemical properties, and lower off-target toxicity. However, owing to the complexity of allosteric regulation, experimental approaches for the development of allosteric modulators are traditionally serendipitous. Recently, the reversed allosteric communication theory has been proposed, providing a feasible tool for the unbiased detection of allosteric sites. Herein, we review the latest research on the reversed allosteric communication effect using the examples of sirtuin 6, epidermal growth factor receptor, 3-phosphoinositide-dependent protein kinase 1, and Related to A and C kinases (RAC) serine/threonine protein kinase B and recapitulate the methodologies of reversed allosteric communication strategy. The novel reversed allosteric communication strategy greatly expands the horizon of allosteric site identification and allosteric mechanism exploration and is expected to accelerate an end-to-end framework for drug discovery.

Atomic-scale insights into allosteric inhibition and evolutional rescue mechanism of Streptococcus thermophilus Cas9 by the anti-CRISPR protein AcrIIA6

CRISPR-Cas systems are prokaryotic adaptive immunity against invading phages and plasmids. Phages have evolved diverse protein inhibitors of CRISPR-Cas systems, called anti-CRISPR (Acr) proteins, to neutralize this CRISPR machinery. In response, bacteria have co-evolved Cas variants to escape phage's anti-CRISPR strategies, called anti-anti-CRISPR systems. Here we explore the anti-CRISPR allosteric inhibition and anti-anti-CRISPR rescue mechanisms between Streptococcus thermophilus Cas9 (St1Cas9) and the anti-CRISPR protein AcrIIA6 at the atomic level, by generating mutants of key residues in St1Cas9. Extensive unbiased molecular dynamics simulations show that the functional motions of St1Cas9 in the presence of AcrIIA6 differ substantially from those of St1Cas9 alone. AcrIIA6 binding triggers a shift of St1Cas9 conformational ensemble towards a less catalytically competent state; this state significantly compromises protospacer adjacent motif (PAM) recognition and nuclease activity by altering interdependently conformational dynamics and allosteric signals among nuclease domains, PAM-interacting (PI) regions, and AcrIIA6 binding motifs. Via in vitro DNA cleavage assays, we further elucidate the rescue mechanism of efficiently escaping AcrIIA6 inhibition harboring St1Cas9 triple mutations (G993K/K1008M/K1010E) in the PI domain and identify the evolutionary landscape of such mutational escape within species. Our results provide mechanistic insights into Acr proteins as natural brakes for the CRISPR-Cas systems and a promising potential for the design of allosteric Acr peptidomimetics.