Protein-protein Interaction Interface Research Articles

A structurally informed human protein-protein interactome reveals proteome-wide perturbations caused by disease mutations.

To assist the translation of genetic findings to disease pathobiology and therapeutics discovery, we present an ensemble deep learning framework, termed PIONEER (Protein-protein InteractiOn iNtErfacE pRediction), that predicts protein-binding partner-specific interfaces for all known protein interactions in humans and seven other common model organisms to generate comprehensive structurally informed protein interactomes. We demonstrate that PIONEER outperforms existing state-of-the-art methods and experimentally validate its predictions. We show that disease-associated mutations are enriched in PIONEER-predicted protein-protein interfaces and explore their impact on disease prognosis and drug responses. We identify 586 significant protein-protein interactions (PPIs) enriched with PIONEER-predicted interface somatic mutations (termed oncoPPIs) from analysis of approximately 11,000 whole exomes across 33 cancer types and show significant associations of oncoPPIs with patient survival and drug responses. PIONEER, implemented as both a web server platform and a software package, identifies functional consequences of disease-associated alleles and offers a deep learning tool for precision medicine at multiscale interactome network levels.

Multiple Functional Protein-Protein Interaction Interfaces Allosterically Regulate ATP-Binding in Cyclin-Dependent Kinase-1.

The ATP-dependent phosphorylation activity of cyclin-dependent kinase 1 (CDK1), an essential enzyme for cell cycle progression, is regulated by interactions with Cyclin-B, substrate, and Cks proteins. We have recently shown that active site acetylation in CDK1 abrogated binding to Cyclin-B which posits an intriguing long-range communication between the catalytic site and the protein-protein interaction (PPI) interface. Now, we demonstrate a general allosteric link between the CDK1 active site and all three of its PPI interfaces through atomistic molecular dynamics (MD) simulations. Specifically, we examined ATP binding free energies to CDK1 in native nonacetylated (K33wt) and acetylated (K33Ac) forms as well as the acetyl-mimic K33Q and the acetyl-null K33R mutant forms, which are accessible in vitro. In agreement with experiments, ATP binding is stronger in K33wt relative to the other three perturbed states. Free energy decomposition reveals, in addition to expected local changes, significant and selective nonlocal entropic responses to ATP binding/perturbation of K33 from the -helix, activation loop (A-loop), and - H segments in CDK1 which interface with Cyclin-B, substrate, and Cks proteins, respectively. Statistical analysis reveals that while entropic responses of protein segments to active site perturbations are on average correlated with their dynamical changes, such correlations are lost in about 9%-48% of the dataset depending on the segment. Besides proving the bi-directional communication between the active site and the CDK1:Cyclin-B interface, our study uncovers a hitherto unknown mode of ATP binding regulation by multiple PPI interfaces in CDK1.

Discovery of Biphenyl Derivatives to Target Hsp70-Bim Protein-Protein Interaction in Chronic Myeloid Leukemia by Scaffold Hopping Strategy.

Hsp70-Bim protein-protein interaction (PPI) is the most recently identified specific target in chronic myeloid leukemia (CML) therapy. Herein, we developed a new class of Hsp70-Bim PPI inhibitors via scaffold hopping of S1g-10, the most potent Hsp70-Bim PPI inhibitor thus far. Through structure-activity relationship (SAR) study, we obtained a biphenyl scaffold compound JL-15 with a 5.6-fold improvement in Hsp70-Bim PPI suppression (Kd = 123 vs 688 nM) and a 4-fold improvement in water solubility (29.42 vs 7.19 μg/mL) compared to S1g-10. It maintains comparable apoptosis induction capability with S1g-10 against both TKI-sensitive and TKI-resistant CML cell lines in an Hsp70-Bim-dependent manner. Additionally, through SAR, 1H-15N TRSOY-NMR, and molecular docking, we revealed that Lys319 is a "hot spot" in the Hsp70-Bim PPI interface. Collectively, these results provide a novel chemical scaffold and structural insights for the rational design of Hsp70-Bim PPI inhibitors.

Modulation of biophysical properties of nucleocapsid protein in the mutant spectrum of SARS-CoV-2.

Genetic diversity is a hallmark of RNA viruses and the basis for their evolutionary success. Taking advantage of the uniquely large genomic database of SARS-CoV-2, we examine the impact of mutations across the spectrum of viable amino acid sequences on the biophysical phenotypes of the highly expressed and multifunctional nucleocapsid protein. We find variation in the physicochemical parameters of its extended intrinsically disordered regions (IDRs) sufficient to allow local plasticity, but also observe functional constraints that similarly occur in related coronaviruses. In biophysical experiments with several N-protein species carrying mutations associated with major variants, we find that point mutations in the IDRs can have nonlocal impact and modulate thermodynamic stability, secondary structure, protein oligomeric state, particle formation, and liquid-liquid phase separation. In the Omicron variant, distant mutations in different IDRs have compensatory effects in shifting a delicate balance of interactions controlling protein assembly properties, and include the creation of a new protein-protein interaction interface in the N-terminal IDR through the defining P13L mutation. A picture emerges where genetic diversity is accompanied by significant variation in biophysical characteristics of functional N-protein species, in particular in the IDRs.

Modulation of biophysical properties of nucleocapsid protein in the mutant spectrum of SARS-CoV-2

Genetic diversity is a hallmark of RNA viruses and the basis for their evolutionary success. Taking advantage of the uniquely large genomic database of SARS-CoV-2, we examine the impact of mutations across the spectrum of viable amino acid sequences on the biophysical phenotypes of the highly expressed and multifunctional nucleocapsid protein. We find variation in the physicochemical parameters of its extended intrinsically disordered regions (IDRs) sufficient to allow local plasticity, but also observe functional constraints that similarly occur in related coronaviruses. In biophysical experiments with several N-protein species carrying mutations associated with major variants, we find that point mutations in the IDRs can have nonlocal impact and modulate thermodynamic stability, secondary structure, protein oligomeric state, particle formation, and liquid-liquid phase separation. In the Omicron variant, distant mutations in different IDRs have compensatory effects in shifting a delicate balance of interactions controlling protein assembly properties, and include the creation of a new protein-protein interaction interface in the N-terminal IDR through the defining P13L mutation. A picture emerges where genetic diversity is accompanied by significant variation in biophysical characteristics of functional N-protein species, in particular in the IDRs.

Engineering of the start condensation domain with improved N-decanoyl catalytic activity for daptomycin biosynthesis.

Daptomycin, a lipopeptide comprising an N-decanoyl fatty acyl chain and a peptide core, is used clinically as an antimicrobial agent. The start condensation domain (dptC1) is an enzyme that catalyzes the lipoinitiation step of the daptomycin synthesis. In this study, we integrated enzymology, protein engineering, and computer simulation to study the substrate selectivity of the start condensation domain (dptC1) and to screen mutants with improved activity for decanoyl loading. Through molecular docking and computer simulation, the fatty acyl substrate channel and the protein-protein interaction interface of dptC1 are analyzed. Key residues at the protein-protein interface between dptC1 and the acyl carrier were mutated, and a single-point mutant showed more than three-folds improved catalytic efficiency of the target n-decanoyl substrate in comparing with the wild type. Moreover, molecular dynamics simulations suggested that mutants with increased catalytic activity may correlated with a more "open" and contracted substrate binding channel. Our work provides a new perspective for the elucidation of lipopeptide natural products biosynthesis, and also provides new resources to enrich its diversity and optimize the production of important components.

Hydrophobic core evolution of major histocompatibility complex class I chain-related protein A for dramatic enhancing binding affinity

Interface residues at sites of protein–protein interaction (PPI) are the focus for affinity optimisation. However, protein hydrophobic cores (HCs) play critical roles and shape the protein surface. We hypothesise that manipulating protein HCs can enhance PPI interaction affinities. A cell stress molecule, major histocompatibility complex class I chain-related protein A (MICA), binds to the natural killer group 2D (NKG2D) homodimer to form three molecule interactions. MICA was used as a study subject to support our hypothesis. We redesigned MICA HCs by directed mutagenesis and isolated high-affinity variants through a newly designed partial-denature panning (PDP) method. A few mutations in MICA HCs increased the NKG2D–MICA interaction affinity by 325–5613-fold. Crystal structures of the NKG2D–MICA variant complexes indicated that mutagenesis of MICA HCs stabilised helical elements for decreasing intermolecular interactive free energy (ΔG) of the NKG2D–MICA heterotrimer. The repacking of MICA HC mutants maintained overall surface residues and the authentic binding specificity of MICA. In conclusion, this study provides a new method for MICA redesign and affinity optimisation through HC manipulation without mutating PPI interface residues. Our study introduces a novel approach to protein manipulation, potentially expanding the toolkit for protein affinity optimisation.

Abstract 5785: Shedding light on PARP1-E2F1 interaction by Cryo-EM

Abstract Cell division is orchestrated by a complex network of interactions between proteins involved in numerous signaling pathways that control cell proliferation. One of these main players is the E2F family of transcription factors. The role of these key players is to regulate the expression of several genes important in cell proliferation, particularly those involved in progression through G1 and into the S-phase of the cell cycle. In fact, cell cycle deregulation is a hallmark of cancer, and multiple studies have highlighted the critical role of E2F hyperactivation in tumor progression, angiogenesis, and metastasis. However, targeting a master regulator of cell growth will also have a pernicious effect on non-cancerous cells, thus limiting its applications. In order to overwhelm these restrictions, we propose a therapeutic approach in which E2F transcriptional activity is specifically reduced in cells with hyperactivation of the pathway, such as cancer cells.We and others have shown that poly (ADP-ribose) polymerase 1 (PARP1) is a transcriptional co-activator of E2F1 and, owing to this, loss of PARP results in cell cycle re-regulation and reduction of tumor growth. Interestingly, this effect of PARP1 does not depend on its enzymatic activity, thus opening a completely new strategic approach. Furthermore, considering that most oncogenic processes are associated with cell cycle deregulation, disruption of PARP1-E2F1 interaction could provide a new therapeutic target with a wide spectrum of indications in cancer. Currently, we lack comprehensive structural details regarding the PARP-1/E2F1 protein-protein interaction. To address this, we used cryo-EM to investigate both the standalone structure of PARP1 (full length) and its interaction with E2F1. This approach yielded high-resolution structural insights into the PARP1-E2F1 complex, enabling precise identification of the protein-protein interaction interface (PPI). Through this exploration of structural and molecular determinants governing this interaction, we aim to develop innovative strategies for designing drugs targeted at disrupting this complex. This work was supported by Agencia Estatal de Investigación (AEl/10.13039/501100011033), Xunta de Galicia (GPC GI-1862, ED431B 2020/26; ED431G 2019/02) and European Regional Development Fund-ERDF. Citation Format: Pablo Iglesias, Ester Casajus-Pelegay, Maria Moreno-Morcillo, Lara González-Rendo, Laura Porres-Ventin, Victor M. Arce, Rafael Fernandez-Leiro, Jose A. Costoya. Shedding light on PARP1-E2F1 interaction by Cryo-EM [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5785.

Exploring the binding mechanism of a small molecular Hsp70-Bim PPI inhibitor through molecular dynamic simulation.

The interface of Hsp70-Bim protein-protein interaction (PPI) has been identified as a specific target for Chronic Myeloid Leukemia (CML) therapy and the specific inhibitors were developed to exhibit in vivo anti-leukemia activities. Herein, we explored the binding mechanism of a Hsp70-Bim inhibitor, 6-(cyclohexylthio)-3-((2-morpholinoethyl) amino)-1-oxo-1H-phenalene-2-carbonitrile (S1g-6), to Hsp70 at the atomic level by MD simulation. TYR-149, THR-222, ALA-223, and GLY-224 on Hsp70 were identified as four key residues that contribute to Hsp70/S1g-6 complex. Moreover, the site mutation validation demonstrated the TYR-149 of Hsp70 is a "hot-spot" in the Hsp70-Bim PPI interface. These results could benefit the design of further inhibitors to occupy the Bim binding site on the Hsp70 surface. The binding mechanism of S1g-6 and Hsp70 was predicted through the molecular dynamics (MD) method by Gromacs-2021.3. The MD simulation was performed with 100-ps NVT and 100-ps NPT ensemble, and the force field was chosen as the Charmm36 force field. The temperature was set as 300K, the time step was 2fs and the total MD simulation time was 500ns.

Discovery of (2-(4-Substituted phenyl)quinolin-4-yl)(4-isopropylpiperazin-1-yl)methanone Derivatives as Potent Proprotein Convertase Subtilisin/Kexin Type 9 Inhibitors.

Inhibition of proprotein convertase subtilisin/kexin type 9 (PCSK9) plays an increasingly important role in the treatment of hyperlipidemia. In pursuit of potent small molecules that block the PCSK9/low-density lipoprotein receptor (LDLR) protein-protein interaction (PPI), a series of 2-phenylquinoline-4-carboxylic acid derivatives were designed and synthesized based on previously derived molecules. In the in vitro PPI inhibition test, compounds M1, M12, M14, M18 and M27 exhibited potent activities with IC50 values of 6.25 μM, 0.91 μM, 2.81 μM, 4.26 μM and 0.76 μM, respectively, compared with SBC-115337 (IC50 value of 9.24 μM). Molecular docking and molecular dynamics simulations revealed the importance of hydrophobic interactions in the binding of inhibitors to the PPI interface of PCSK9. In LDLR expression and LDL uptake assays, the tested compounds M1, M12 and M14 were found to restore LDLR expression levels and to increase the extracellular LDL uptake capacity of HepG2 cells in the presence of exogenous PCSK9. Collectively, novel small-molecule PCSK9/LDLR PPI inhibitors (especially M12) with in vitro lipid lowering ability, were discovered as lead compounds for further development of hypolipidemic drugs.

Structure-guided screening of protein-protein interaction for the identification of Myc-Max heterodimer complex modulators

De-regulation of oncogenic myelocytomatosis (c-Myc or Myc) transcription factor is one of the most common molecular anomalies encountered in human cancers, and it is typically linked to many aggressive malignancies including breast, lung, cervix, colon glioblastomas, and other haematological organs. The Myc belongs to the basic helix-loop-helix zipper protein family (bHLH-ZIP), and its dimerization with another principal interactor protein partner Myc-associated factor X (Max) is essentially required for cellular transformation, cell growth and proliferation, and transcriptional activation. Intermolecular interactions have been evaluated between hetero-dimer Myc-Max protein, which identified protein-protein interaction (PPI) specific modulators using highly précised molecular docking study followed by long-range interaction stability analyzed through molecular dynamic (MD) simulation. Moreover, ADME profile analyses have been estimated for screened hit compounds. MM-GBSA-based binding free energy (ΔG) estimations have been performed for all screened hit compounds obtained from multi-step molecular docking-based virtual screening technique. According to the employed various rigorous multi-chemometric techniques, four identified inhibitors/modulators appear to have a considerable number of intermolecular contacts with hotspot residues in the hetero-dimer interface region of the Myc-Max PPI complex. However, identified hit compounds might need further structural optimization or extensive biophysical analyses for better understanding of the molecular mechanism for exhibiting the Myc-Max PPI interface binding stability. Communicated by Ramaswamy H. Sarma

Electrophile Scanning Reveals Reactivity Hotspots for the Design of Covalent Peptide Binders.

Protein-protein interactions (PPIs) are intriguing targets in drug discovery and development. Peptides are well suited to target PPIs, which typically present with large surface areas lacking distinct features and deep binding pockets. To improve binding interactions with these topologies and advance the development of PPI-focused therapeutics, potential ligands can be equipped with electrophilic groups to enable binding through covalent mechanisms of action. We report a strategy termed electrophile scanning to identify reactivity hotspots in a known peptide ligand and demonstrate its application in a model PPI. Cysteine mutants of a known ligand are used to install protein-reactive modifiers via a palladium oxidative addition complex (Pd-OAC). Reactivity hotspots are revealed by cross-linking reactions with the target protein under physiological conditions. In a model PPI with the 9-mer peptide antigen VL9 and major histocompatibility complex (MHC) class I protein HLA-E, we identify two reactivity hotspots that afford up to 87% conversion to the protein-peptide conjugate within 4 h. The reactions are specific to the target protein in vitro and dependent on the peptide sequence. Moreover, the cross-linked peptide successfully inhibits molecular recognition of HLA-E by CD94-NKG2A possibly due to structural changes enacted at the PPI interface. The results illustrate the potential application of electrophile scanning as a tool for rapid discovery and development of covalent peptide binders.

Bioinformatics insights into CENP-T and CENP-W protein-protein interaction disruptive amino acid substitution in the CENP-T-W complex.

Kinetochores are multi-protein assemblies present at the centromere of the human chromosome and play a crucial role in cellular mitosis. The CENP-T and CENP-W chains form a heterodimer, which is an integral part of the inner kinetochore, interacting with the linker DNA on one side and the outer kinetochore on the other. Additionally, the CENP-T-W dimer interacts with other regulatory proteins involved in forming inner kinetochores. The specific roles of different amino acids in the CENP-W at the protein-protein interaction (PPI) interface during the CENP-T-W dimer formation remain incompletely understood. Since cell division goes awry in diseases like cancer, this CENP-T-W partnership is a potential target for new drugs that could restore healthy cell division. We employed molecular docking, binding free energy calculations, and molecular dynamics (MD) simulations to investigate the disruptive effects of amino acids substitutions in the CENP-W chain on CENP-T-W dimer formation. By conducting a molecular docking study and analysing hydrogen bonding interactions, we identified key residues in CENP-W (ASN-46, ARG-53, LEU-83, SER-86, ARG-87, and GLY-88) for further investigation. Through site-directed mutagenesis and subsequent binding free energy calculations, we refined the selection of mutant. We chose four mutants (N46K, R53K, L83K, and R87E) of CENP-W to assess their comparative potential in forming CENP-T-W dimer. Our analysis from 250 ns long revealed that the substitution of LEU83 and ARG53 residues in CENP-W with the LYS significantly disrupts the formation of CENP-T-W dimer. In conclusion, LEU83 and ARG53 play a critical role in CENP-T and CENP-W dimerization which is ultimately required for cellular mitosis. Our findings not only deepen our understanding of cell division but also hint at exciting drug-target possibilities.

Linking Chemical Fragments, “Gluing” Protein Complexes, Connecting across Cultures

AbstractThis invited Team Profile was created by Michelle Arkin and Adam Renslo from the University of California, San Francisco in the USA and Luc Brunsveld and Christian Ottmann from the Eindhoven University of Technology in the Netherlands. They recently published an article on designing molecular glues for the 14‐3‐3/estrogen receptor (ER) protein‐protein interaction (PPI). Molecular glues increase the binding between two proteins by binding at the PPI interface. While they hold exciting promise to induce new biology and treat disease, systematic approaches to discover glues are just becoming available. Fragment‐based drug discovery has been used to discover inhibitors of PPI; here, the team demonstrated a fragment discovery and linking strategy to create a new molecular glue for 14‐3‐3/ER, an anticancer target. “From Tethered to Freestanding Stabilizers of 14‐3‐3 Protein‐Protein Interactions though Fragment Linking”, E. J. Visser, P. Jaishankar, E. Sijbesma, M. A. M. Pennings, E. M. F. Vandenboorn, X. Guillory, R. J. Neitz, J. Morrow, S. Dutta, A. R. Renslo, L. Brunsveld, M. R. Arkin, C. Ottmann, Angew. Chem. Int. Ed. 2023, 62, e202308004.

Peptidomimetics for CVD screened via TRADD-TRAF2 complex interface assessments.

The main aim of this study is to screen and develop Peptidomimetics to treat atherosclerosis (AS) which is a Cardio Vascular Disease (CVD). Peptidomimetics were obtained from the protein-protein interaction interface of TRADD (Tumor necrosis factor receptor type 1-associated DEATH domain protein) and TRAF2 (TNF receptor-associated factor 2) complex. TRADD-TRAF2 interaction is critical in AS pathogenesis since it assists a series of signal transducers that activate NF-κB. Conceptually, the triggered NF-κB makes an extensive amount of nitric oxide (NO) synthesized by inducible nitric oxide synthase (iNOS), which boons the progress of AS. The examined TRADD-TRAF2 complex (PDB ID: 1F3V) and its interaction details revealed that the sequence range W11-G165 of TRADD highly interacts with TRAF2. The sequence range W11-G165 was selected for the design and preparation of the inhibitory peptide in silico. The selected sequence was mutated with the alanine scanning method to have a range of inhibitory peptides. With the help of different in silico tools, the top three, namely MIP11-25L, MIP131-143h, and MIP149-164m peptides showed the best interaction with the critical residues of TRAF2. Thus, these three peptides were used for generating peptidomimetics using pepMMsMIMIC, a peptidomimetics virtual screening tool. Around 600 peptidomimetics were identified & and retrieved for further screening by employing molecular docking tools and MD (Molecular Dynamics) simulations. Density Functional Theory (DFT) and ADMET predictions were applied to validate the screened peptidomimetics druggability. In the results, peptidomimic compounds MMs03918858 and MMs03927281 with binding energy values of -9.6kcal/mol and - 9.1kcal/mol respectively were screened as the best and are proposed for further pre-clinical studies.

Discovering covalent inhibitors of protein-protein interactions from trillions of sulfur(VI) fluoride exchange-modified oligonucleotides.

Molecules that covalently engage target proteins are widely used as activity-based probes and covalent drugs. The performance of these covalent inhibitors is, however, often compromised by the paradox of efficacy and risk, which demands a balance between reactivity and selectivity. The challenge is more evident when targeting protein-protein interactions owing to their low ligandability and undefined reactivity. Here we report sulfur(VI) fluoride exchange (SuFEx) in vitro selection, a general platform for high-throughput discovery of covalent inhibitors from trillions of SuFEx-modified oligonucleotides. With SuFEx in vitro selection, we identified covalent inhibitors that cross-link distinct residues of the SARS-CoV-2 spike protein at its protein-protein interaction interface with the human angiotensin-converting enzyme 2. A separate suite of covalent inhibitors was isolated for the human complement C5 protein. In both cases, we observed a clear disconnection between binding affinity and cross-linking reactivity, indicating that direct search for the aimed reactivity-as enabled by SuFEx in vitro selection-is vital for discovering covalent inhibitors of high selectivity and potency.

Delineation of the CENP-LN sub-complex dissociation mechanism upon multisite phosphorylation during mitosis

Phosphorylation is the most prevalent form of regulation in cells, organizing virtually all cellular functions, including survival, motility, differentiation, proliferation, and metabolism. This regulatory function has been largely conserved from the primitive single-cell to the more complex multicellular organisms. More than a third of proteins in eukaryotes are phosphorylated, and essentially every class of protein undergoes regulation by phosphorylation. A decline in the cellular level of CENP-L and CENP-N (components of the constitutive centromere associated network) has earlier been reported and linked to cyclin-dependent kinase (CDK) phosphorylation upon transition into mitosis. Given the importance of posttranslational modifications in cell cycle regulation, mechanistic comprehension of the impact of phosphorylation on both proteins (CENP-L and CENP-N) is of high significance. Through the application of diverse computational analytical techniques, including atomistic molecular dynamics simulations, the mechanism of kinetochore mis-localization and dissociation of the CENP-LN sub-complex in mitosis was delineated. We showed that the phosphorylation of both components of the sub-complex induces global conformational destabilizing effects on the proteins, combined with changes in the electrostatic potential and increase in steric clashes around the protein-protein interaction interface. This, consistent with earlier experimental reports, suggest that the multisite phosphorylation of the CENP-LN sub-complex plays a crucial role in the regulation of cell division. Communicated by Ramaswamy H. Sarma

Prediction of transient and permanent protein interactions using AI methods.

Protein-protein interactions (PPIs) can be classified as permanent or transient interactions based on their stability or lifetime. Understanding the precise details of such protein interactions will pave the way for the discovery of inhibitors and for understanding the nature and function of PPIs. In the present work, 43 relevant physicochemical, geometrical and structural features were calculated for a curated dataset from the literature, comprising of 402 protein-protein complexes of permanent and transient categories, and 5 different Supervised Machine Learning models were developed with Scikit-learn to predict transient and permanent PPI. Additionally, deep learning method with Artificial Neural Network was also performed using Tensor Flow and Keras. Predicted models achieved accuracy ranging from 76.54% to 82.71% and k-NN has achieved the highest accuracy. Detailed analysis of these methods revealed that Interface areas such as Percent interface accessible area, Interface accessible area and Total interface area and the parameters defining the shape of the PPI interface such as Planarity, Eccentricity and Circularity are the most discriminating factors between these two categories. The present method could serve as an effective tool to understand the mechanism of protein association and to predict the transient and permanent interactions, which could supplement the costly and time-consuming experimental techniques.

A potent phosphodiester Keap1-Nrf2 protein-protein interaction inhibitor as the efficient treatment of Alzheimer's disease

The Keap1-Nrf2 pathway has been established as a therapeutic target for Alzheimer's disease (AD). Directly inhibiting the protein-protein interaction (PPI) between Keap1 and Nrf2 has been reported as an effective strategy for treating AD. Our group has validated this in an AD mouse model for the first time using the inhibitor 1,4-diaminonaphthalene NXPZ-2 with high concentrations. In the present study, we reported a new phosphodiester containing diaminonaphthalene compound, POZL, designed to target the PPI interface using a structure-based design strategy to combat oxidative stress in AD pathogenesis. Our crystallographic verification confirms that POZL shows potent Keap1-Nrf2 inhibition. Remarkably, POZL showed its high in vivo anti-AD efficacy at a much lower dosage compared to NXPZ-2 in the transgenic APP/PS1 AD mouse model. POZL treatment in the transgenic mice could effectively ameliorate learning and memory dysfunction by promoting the Nrf2 nuclear translocation. As a result, the oxidative stress and AD biomarker expression such as BACE1 and hyperphosphorylation of Tau were significantly reduced, and the synaptic function was recovered. HE and Nissl staining confirmed that POZL improved brain tissue pathological changes by enhancing neuron quantity and function. Furthermore, it was confirmed that POZL could effectively reverse Aβ-caused synaptic damage by activating Nrf2 in primary cultured cortical neurons. Collectively, our findings demonstrated that the phosphodiester diaminonaphthalene Keap1-Nrf2 PPI inhibitor could be regarded as a promising preclinical candidate of AD.

Performance of the Classification of Critical Residues at the Interface of BMPs Complexes Pondered with the Ground-State Energy Feature using Random Forest Classifier

This work is focused on implementing and evaluating the Random Forest Classifier (RFC), among other classical machine learning models, on predicting the residues at the interface of protein-protein interactions (PPI) that contribute most of the binding free energy (called hot spots and hot regions). The dataset comprises twenty-nine bone morphogenetic proteins (BMPs) complexes from the Protein Data Bank (PDB). We used just six features such as B-factor, hydrophobicity index, prevalence score, accessible surface area (ASA), conservation score, and the ground-state energy of the amino acids, which were calculated using the Density Functional Theory (DFT). Proving and testing several machine learning methods, we selected the RCF because of its better performance using classical classification metrics and tests. An optimal parameter selection of the RFC reached a better performance using this dataset with around 90 % with the correct class assigned (hot spot & hot region / non-hot spot hot region) residues.