PRDX1 Interfering Peptide Disrupts Amino Acids 70-90 of PRDX1 to Inhibit the TLR4/NF-κB Signaling Pathway and Attenuate Neuroinflammation and Ischemic Brain Injury.

Ischemic stroke ranks among the leading causes of death and disability in humans and is accompanied by motor and cognitive impairment. However, the precise mechanisms underlying injury after stroke and effective treatment strategies require further investigation. Peroxiredoxin-1 (PRDX1) triggers an extensive inflammatory cascade that plays a pivotal role in the pathology of ischemic stroke, resulting in severe brain damage from activated microglia. In the present study, we used molecular dynamics simulation and nuclear magnetic resonance to detect the interaction between PRDX1 and a specific interfering peptide. We used behavioral, morphological, and molecular experimental methods to demonstrate the effect of PRDX1-peptide on cerebral ischemia-reperfusion (I/R) in mice and to investigate the related mechanism. We found that PRDX1-peptide bound specifically to PRDX1 and improved motor and cognitive functions in I/R mice. In addition, pretreatment with PRDX1-peptide reduced the infarct area and decreased the number of apoptotic cells in the penumbra. Furthermore, PRDX1-peptide inhibited microglial activation and downregulated proinflammatory cytokines including IL-1ß, IL-6, and TNF-α through inhibition of the TLR4/NF-κB signaling pathway, thereby attenuating ischemic brain injury. Our findings clarify the precise mechanism underlying PRDX1-induced inflammation after ischemic stroke and suggest that the PRDX1-peptide can significantly alleviate the postischemic inflammatory response by interfering with PRDX1 amino acids 70-90 and thereby inhibiting the TLR4/NF-κB signaling pathway. Our study provides a theoretical basis for a new therapeutic strategy to treat ischemic stroke.

Pan-KRAS inhibitors suppress proliferation through feedback regulation in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is currently one of the most lethal cancers worldwide. Several basic studies have confirmed that Kirsten rat sarcoma virus (KRAS) is a key driver gene for the occurrence of PDAC, and KRAS mutations have also been found in most patients in clinical studies. In this study, two pan-KRAS inhibitors, BI-2852 and BAY-293, were chosen as chemical probes to investigate their antitumor potency in PDAC. Their inhibitory effects on KRAS activation were validated in vitro and their antiproliferative potency in PDAC cell lines were profiled, with half-maximal inhibitory concentration (IC50) values of approximately 1 µM, demonstrating the therapeutic potential of pan-KRAS inhibitors in the treatment of PDAC. However, feedback regulation in the KRAS pathway weakened inhibitor activity, which was observed by a 50 times difference in BAY-293 from in vitro activity. Furthermore, pan-KRAS inhibitors effectively inhibited cell proliferation in 3D organoids cultured from PDAC patient samples; however, there were some variations between individuals. These results provide a sufficient theoretical foundation for KRAS as a clinical therapeutic target and for the application of pan-KRAS inhibitors in the treatment of PDAC, with important scientific significance in translational medicine.

In vitro biolayer interferometry analysis of acetylcholinesterase as a potential target of aryl-organophosphorus flame-retardants.

Organophosphorus flame retardants (OPFRs) have been implicated as neurotoxicants, but their potential neurotoxicity and mechanisms remain poorly understood. Herein, we investigated the neurotoxicity of selected OPFRs using zebrafish as a model organism. Environmentally relevant concentrations (3-1500 nM) of three classes of OPFRs (aryl-OPFRs, chlorinated-OPFRs, and alkyl-OPFRs) were tested in zebrafish larvae (2-144 h post-fertilisation) alongside the neurotoxic chemical chlorpyrifos (CPF) that inhibits acetylcholinesterase (AChE). Exposure to aryl-OPFRs and CPF inhibited AChE activities, while chlorinated- and alkyl-OPFRs did not inhibit these enzymes. Biolayer interferometry (BLI) was used to probe interactions between OPFRs and AChE. The association and dissociation response curves showed that, like CPF, all three selected aryl-OPFRs, triphenyl phosphate (TPHP), tricresyl phosphate (TCP) and cresyl diphenyl phosphate (CDP), bound directly to AChE. The affinity constant (KD) for TPHP, TCP, CDP and CPF was 2.18 × 10-4, 5.47 × 10-5, 1.05 × 10-4 and 1.70 × 10-5 M, respectively. In addition, molecular docking revealed that TPHP, TCP, CDP and CPF bound to AChE with glide scores of - 7.8, - 8.3, - 8.1 and - 7.3, respectively. Furthermore, the calculated binding affinity between OPFRs and AChE correlated well with the KD values measured by BLI. The present study revealed that aryl-OPFRs can act as potent AChE inhibitors, and may therefore present a significant ecological risk to aquatic organisms.

Unraveling allosteric landscapes of allosterome with ASD.

Allosteric regulation is one of the most direct and efficient ways to fine-tune protein function; it is induced by the binding of a ligand at an allosteric site that is topographically distinct from an orthosteric site. The Allosteric Database (ASD, available online at http://mdl.shsmu.edu.cn/ASD) was developed ten years ago to provide comprehensive information related to allosteric regulation. In recent years, allosteric regulation has received great attention in biological research, bioengineering, and drug discovery, leading to the emergence of entire allosteric landscapes as allosteromes. To facilitate research from the perspective of the allosterome, in ASD 2019, novel features were curated as follows: (i) >10 000 potential allosteric sites of human proteins were deposited for allosteric drug discovery; (ii) 7 human allosterome maps, including protease and ion channel maps, were built to reveal allosteric evolution within families; (iii) 1312 somatic missense mutations at allosteric sites were collected from patient samples from 33 cancer types and (iv) 1493 pharmacophores extracted from allosteric sites were provided for modulator screening. Over the past ten years, the ASD has become a central resource for studying allosteric regulation and will play more important roles in both target identification and allosteric drug discovery in the future.

A Novel Allosteric Inhibitor of Phosphoglycerate Mutase 1 Suppresses Growth and Metastasis of Non-Small-Cell Lung Cancer.

Phosphoglycerate mutase 1 (PGAM1) plays a pivotal role in cancer metabolism and tumor progression via its metabolic activity and interaction with other proteins like α-smooth muscle actin (ACTA2). Allosteric regulation is considered to be an innovative strategy to discover a highly selective and potent inhibitor targeting PGAM1. Here, we identified a novel PGAM1 allosteric inhibitor, HKB99, via structure-based optimization. HKB99 acted to allosterically block conformational change of PGAM1 during catalytic process and PGAM1-ACTA2 interaction. HKB99 suppressed tumor growth and metastasis and overcame erlotinib resistance in non-small-cell lung cancer (NSCLC). Mechanistically, HKB99 enhanced the oxidative stress and altered multiple signaling pathways including the activation of JNK/c-Jun and suppression of AKT and ERK. Collectively, the study highlights the potential of PGAM1 as a therapeutic target in NSCLC and reveals a distinct mechanism by which HKB99 inhibits both metabolic activity and nonmetabolic function of PGAM1 by allosteric regulation.

AlloDriver: a method for the identification and analysis of cancer driver targets.

Identifying the variants that alter protein function is a promising strategy for deciphering the biological consequences of somatic mutations during tumorigenesis, which could provide novel targets for the development of cancer therapies. Here, based on our previously developed method, we present a strategy called AlloDriver that identifies cancer driver genes/proteins as possible targets from mutations. AlloDriver utilizes structural and dynamic features to prioritize potentially functional genes/proteins in individual cancers via mapping mutations generated from clinical cancer samples to allosteric/orthosteric sites derived from three-dimensional protein structures. This strategy exhibits desirable performance in the reemergence of known cancer driver mutations and genes/proteins from clinical samples. Significantly, the practicability of AlloDriver to discover novel cancer driver proteins in head and neck squamous cell carcinoma (HNSC) was tested in a real case of human protein tyrosine phosphatase, receptor type K (PTPRK) through a L1143F driver mutation located at the allosteric site of PTPRK, which was experimentally validated by cell proliferation assay. AlloDriver is expected to help to uncover innovative molecular mechanisms of tumorigenesis by perturbing proteins and to discover novel targets based on cancer driver mutations. The AlloDriver is freely available to all users at http://mdl.shsmu.edu.cn/ALD.

Allosteric Methods and Their Applications: Facilitating the Discovery of Allosteric Drugs and the Investigation of Allosteric Mechanisms.

Allostery, or allosteric regulation, is the phenomenon in which protein functional activity is altered by the binding of an effector at an allosteric site that is topographically distinct from the orthosteric, active site. As one of the most direct and efficient ways to regulate protein function, allostery has played a fundamental role in innumerable biological processes of all living organisms, including enzyme catalysis, signal transduction, cell metabolism, and gene transcription. It is thus considered as "the second secret of life". The abnormality of allosteric communication networks between allosteric and orthosteric sites is associated with the pathogenesis of human diseases. Allosteric modulators, by attaching to structurally diverse allosteric sites, offer the potential for differential selectivity and improved safety compared with orthosteric drugs that bind to conserved orthosteric sites. Harnessing allostery has thus been regarded as a novel strategy for drug discovery. Despite much progress having been made in the repertoire of allostery since the turn of the millennium, the identification of allosteric drugs for therapeutic targets and the elucidation of allosteric mechanisms still present substantial challenges. These challenges are derived from the difficulties in the identification of allosteric sites and mutations, the assessment of allosteric protein-modulator interactions, the screening of allosteric modulators, and the elucidation of allosteric mechanisms in biological systems. To address these issues, we have developed a panel of allosteric services for specific allosteric applications over the past decade, including (i) the creation of the Allosteric Database, with the aim of providing comprehensive allosteric information such as allosteric proteins, modulators, sites, pathways, etc., (ii) the construction of the ASBench benchmark of high-quality allosteric sites for the development of computational methods for predicting allosteric sites, (iii) the development of Allosite and AllositePro for the prediction of the location of allosteric sites in proteins, (iv) the development of the Alloscore scoring function for the evaluation of allosteric protein-modulator interactions, (v) the development of Allosterome for evolutionary analysis of query allosteric sites/modulators within the human proteome, (vi) the development of AlloDriver for the prediction of allosteric mutagenesis, and (vii) the development of AlloFinder for the virtual screening of allosteric modulators and the investigation of allosteric mechanisms. Importantly, we have validated computationally predicted allosteric sites, mutations, and modulators in the real cases of sirtuin 6, casein kinase 2α, phosphodiesterase 10A, and signal transduction and activation of transcription 3. Furthermore, our developed allosteric methods have been widely exploited by other users around the world for allosteric research. Therefore, these allosteric services are expected to expedite the discovery of allosteric drugs and the investigation of allosteric mechanisms.

Are the Apo Proteins Suitable for the Rational Discovery of Allosteric Drugs?

Allosteric modulators, by targeting the less-conserved allosteric sites, represent an innovative strategy in drug discovery. These modulators have a distinctive advantage over orthosteric ligands that attach to the conserved, functional orthosteric sites. However, in structure-based drug design, it remains unclear whether allosteric protein structures determined without orthosteric ligand binding are suitable for allosteric drug screening. In this study, we performed large-scale conformational samplings of six representative allosteric proteins uncomplexed ( apo) and complexed ( holo) with orthosteric ligands to explore the effect of orthosteric site binding on the conformational dynamics of allosteric sites. The results, coupled with the redocking evaluation of allosteric modulators to their apo and holo proteins using their MD trajectories, indicated that orthosteric site binding had an effect on the dynamics of the allosteric sites and allosteric modulators preferentially bound to their holo proteins. According to the analysis data, we constructed a new correlation model for quantifying the allosteric site change driven by substrate binding to the orthosteric site. These results highlight the strong demand to select holo allosteric proteins as initial inputs in structure-based allosteric drug screening when the distance between orthosteric and allosteric sites in the protein is below 5 Å, which is expected to contribute to allosteric drug discovery.

The high conserved cellular receptors of avian leukosis virus subgroup J in Chinese local chickens contributes to its wide host range.

Avian leukosis virus (ALV) is a tumor-inducing virus that spreads among most chicken species, causing serious financial losses for the poultry industry. Subgroup J avian leukosis virus (ALV-J) is a recombinant exogenous ALV, which shows more extensive host range in comparison with other subgroups, especially in Chinese local chickens. To identify the relationship between ALV-J host range and the polymorphism of its cellular receptors, we performed a wide range epidemiological investigation of current ALV-J infection in Chinese local chickens, and discovered that all the 18 local chicken breeds being investigated from main local chicken breeding provinces were ALV-J positive. Furthermore, we cloned ALV-J cellular receptor genes of chNHE1 and chANXA2 of these 18 chicken breeds. Sequence alignment demonstrated that despite several regular mutations at the nucleotide level, there were no corresponding amino acid mutations for either chNHE1 gene or chANXA2 gene. Additionally, virus entry assay indicated that the level of viral enter into cells is stable among different chicken breeds. Results of this study indicated that the wide host range of ALV-J in Chinese local chickens was partially due to the high conservatism of its cellular receptors, and also provide target sites for drug design of resistance to ALV-J infection.

AlloFinder: a strategy for allosteric modulator discovery and allosterome analyses.

Allostery tweaks innumerable biological processes and plays a fundamental role in human disease and drug discovery. Exploration of allostery has thus been regarded as a crucial requirement for research on biological mechanisms and the development of novel therapeutics. Here, based on our previously developed allosteric data and methods, we present an interactive platform called AlloFinder that identifies potential endogenous or exogenous allosteric modulators and their involvement in human allosterome. AlloFinder automatically amalgamates allosteric site identification, allosteric screening and allosteric scoring evaluation of modulator-protein complexes to identify allosteric modulators, followed by allosterome mapping analyses of predicted allosteric sites and modulators in human proteome. This web server exhibits prominent performance in the reemergence of allosteric metabolites and exogenous allosteric modulators in known allosteric proteins. Specifically, AlloFinder enables identification of allosteric metabolites for metabolic enzymes and screening of potential allosteric compounds for disease-related targets. Significantly, the feasibility of AlloFinder to discover allosteric modulators was tested in a real case of signal transduction and activation of transcription 3 (STAT3) and validated by mutagenesis and functional experiments. Collectively, AlloFinder is expected to contribute to exploration of the mechanisms of allosteric regulation between metabolites and metabolic enzymes, and to accelerate allosteric drug discovery. The AlloFinder web server is freely available to all users at http://mdl.shsmu.edu.cn/ALF/.

Improved Method for the Identification and Validation of Allosteric Sites.

Allosteric regulation induced by modulators binding to different, often distant, allosteric sites allows for exquisite control of protein functional activity. The structural diversity of allosteric sites endows allosteric modulators with high selectivity and low toxicity. Targeting allosteric sites, a novel tactic in drug discovery, has garnered much attention in the scientific community, and the identification of allosteric sites has become an important component of the development of allosteric drugs. Here we present AllositePro, a method which predicts allosteric sites in proteins by combining pocket features with perturbation analysis. The performance of AllositePro is superior to that of the other currently available methods. Using AllositePro, we predicted a novel allosteric site in cyclin-dependent kinase 2 (CDK2) and validated it by site-directed mutagenesis assay. Thus, the AllositePro method provides an effective way to identify allosteric sites and could be a useful strategy for allosteric drug discovery.

Proteome-Scale Investigation of Protein Allosteric Regulation Perturbed by Somatic Mutations in 7,000 Cancer Genomes.

The allosteric regulation triggering the protein's functional activity via conformational changes is an intrinsic function of protein under many physiological and pathological conditions, including cancer. Identification of the biological effects of specific somatic variants on allosteric proteins and the phenotypes that they alter during tumor initiation and progression is a central challenge for cancer genomes in the post-genomic era. Here, we mapped more than 47,000 somatic missense mutations observed in approximately 7,000 tumor-normal matched samples across 33 cancer types into protein allosteric sites to prioritize the mutated allosteric proteins and we tested our prediction in cancer cell lines. We found that the deleterious mutations identified in cancer genomes were more significantly enriched at protein allosteric sites than tolerated mutations, suggesting a critical role for protein allosteric variants in cancer. Next, we developed a statistical approach, namely AlloDriver, and further identified 15 potential mutated allosteric proteins during pan-cancer and individual cancer-type analyses. More importantly, we experimentally confirmed that p.Pro360Ala on PDE10A played a potential oncogenic role in mediating tumorigenesis in non-small cell lung cancer (NSCLC). In summary, these findings shed light on the role of allosteric regulation during tumorigenesis and provide a useful tool for the timely development of targeted cancer therapies.

BitterX: a tool for understanding bitter taste in humans.

BitterX is an open-access tool aimed at providing a platform for identifying human bitter taste receptors, TAS2Rs, for small molecules. It predicts TAS2Rs from the molecular structures of arbitrary chemicals by integrating two individual functionalities: bitterant verification and TAS2R recognition. Using BitterX, several novel bitterants and their receptors were predicted and experimentally validated in the study. Therefore, BitterX may be an effective method for deciphering bitter taste coding and could be a useful tool for both basic bitter research in academia and new bitterant discoveries in the industry.

Alloscore: a method for predicting allosteric ligand-protein interactions.

UNLABELLED: Allosteric ligands have increasingly gained attention as potential therapeutic agents due to their higher target selectivity and lower toxicity compared with classic orthosteric ligands. Despite the great interest in the development of allosteric drugs as a new tactic in drug discovery, the understanding of the ligand-protein interactions underlying allosteric binding represents a key challenge. Herein, we introduce Alloscore, a web server that predicts the binding affinities of allosteric ligand-protein interactions. This method exhibits prominent performance in describing allosteric binding and could be useful in allosteric virtual screening and the structural optimization of allosteric agonists/antagonists. AVAILABILITY AND IMPLEMENTATION: The Alloscore server and tutorials are freely available at http://mdl.shsmu.edu.cn/alloscore CONTACT: jian.zhang@sjtu.edu.cn SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

ASD v3.0: unraveling allosteric regulation with structural mechanisms and biological networks.

Allosteric regulation, the most direct and efficient way of regulating protein function, is induced by the binding of a ligand at one site that is topographically distinct from an orthosteric site. Allosteric Database (ASD, available online at http://mdl.shsmu.edu.cn/ASD) has been developed to provide comprehensive information featuring allosteric regulation. With increasing data, fundamental questions pertaining to allostery are currently receiving more attention from the mechanism of allosteric changes in an individual protein to the entire effect of the changes in the interconnected network in the cell. Thus, the following novel features were added to this updated version: (i) structural mechanisms of more than 1600 allosteric actions were elucidated by a comparison of site structures before and after the binding of an modulator; (ii) 261 allosteric networks were identified to unveil how the allosteric action in a single protein would propagate to affect downstream proteins; (iii) two of the largest human allosteromes, protein kinases and GPCRs, were thoroughly constructed; and (iv) web interface and data organization were completely redesigned for efficient access. In addition, allosteric data have largely expanded in this update. These updates are useful for facilitating the investigation of allosteric mechanisms, dynamic networks and drug discoveries.

The Mechanism of ATP-Dependent Allosteric Protection of Akt Kinase Phosphorylation.

Kinases use ATP to phosphorylate substrates; recent findings underscore the additional regulatory roles of ATP. Here, we propose a mechanism for allosteric regulation of Akt1 kinase phosphorylation by ATP. Our 4.7-µs molecular dynamics simulations of Akt1 and its mutants in the ATP/ADP bound/unbound states revealed that ATP occupancy of the ATP-binding site stabilizes the closed conformation, allosterically protecting pT308 by restraining phosphatase access and key interconnected residues on the ATP→pT308 allosteric pathway. Following ATP→ADP hydrolysis, pT308 is exposed and readily dephosphorylated. Site-directed mutagenesis validated these predictions and indicated that the mutations do not impair PDK1 and PP2A phosphatase recruitment. We further probed the function of residues around pT308 at the atomic level, and predicted and experimentally confirmed that Akt1(H194R/R273H) double mutant rescues pathology-related Akt1(R273H). Analysis of classical Akt homologs suggests that this mechanism can provide a general model of allosteric kinase regulation by ATP; as such, it offers a potential avenue for allosteric drug discovery.

ASBench: benchmarking sets for allosteric discovery.

Allostery allows for the fine-tuning of protein function. Targeting allosteric sites is gaining increasing recognition as a novel strategy in drug design. The key challenge in the discovery of allosteric sites has strongly motivated the development of computational methods and thus high-quality, publicly accessible standard data have become indispensable. Here, we report benchmarking data for experimentally determined allosteric sites through a complex process, including a 'Core set' with 235 unique allosteric sites and a 'Core-Diversity set' with 147 structurally diverse allosteric sites. These benchmarking sets can be exploited to develop efficient computational methods to predict unknown allosteric sites in proteins and reveal unique allosteric ligand-protein interactions to guide allosteric drug design.

The structural basis of ATP as an allosteric modulator.

Adenosine-5'-triphosphate (ATP) is generally regarded as a substrate for energy currency and protein modification. Recent findings uncovered the allosteric function of ATP in cellular signal transduction but little is understood about this critical behavior of ATP. Through extensive analysis of ATP in solution and proteins, we found that the free ATP can exist in the compact and extended conformations in solution, and the two different conformational characteristics may be responsible for ATP to exert distinct biological functions: ATP molecules adopt both compact and extended conformations in the allosteric binding sites but conserve extended conformations in the substrate binding sites. Nudged elastic band simulations unveiled the distinct dynamic processes of ATP binding to the corresponding allosteric and substrate binding sites of uridine monophosphate kinase, and suggested that in solution ATP preferentially binds to the substrate binding sites of proteins. When the ATP molecules occupy the allosteric binding sites, the allosteric trigger from ATP to fuel allosteric communication between allosteric and functional sites is stemmed mainly from the triphosphate part of ATP, with a small number from the adenine part of ATP. Taken together, our results provide overall understanding of ATP allosteric functions responsible for regulation in biological systems.

Estimation of acute oral toxicity in rat using local lazy learning.

BACKGROUND: Acute toxicity means the ability of a substance to cause adverse effects within a short period following dosing or exposure, which is usually the first step in the toxicological investigations of unknown substances. The median lethal dose, LD50, is frequently used as a general indicator of a substance's acute toxicity, and there is a high demand on developing non-animal-based prediction of LD50. Unfortunately, it is difficult to accurately predict compound LD50 using a single QSAR model, because the acute toxicity may involve complex mechanisms and multiple biochemical processes. RESULTS: In this study, we reported the use of local lazy learning (LLL) methods, which could capture subtle local structure-toxicity relationships around each query compound, to develop LD50 prediction models: (a) local lazy regression (LLR): a linear regression model built using k neighbors; (b) SA: the arithmetical mean of the activities of k nearest neighbors; (c) SR: the weighted mean of the activities of k nearest neighbors; (d) GP: the projection point of the compound on the line defined by its two nearest neighbors. We defined the applicability domain (AD) to decide to what an extent and under what circumstances the prediction is reliable. In the end, we developed a consensus model based on the predicted values of individual LLL models, yielding correlation coefficients R(2) of 0.712 on a test set containing 2,896 compounds. CONCLUSION: Encouraged by the promising results, we expect that our consensus LLL model of LD50 would become a useful tool for predicting acute toxicity. All models developed in this study are available via http://www.dddc.ac.cn/admetus.