A computer-simulated mechanism of familial Alzheimer’s disease: Mutations enhance thermal dynamics and favor looser substrate-binding to γ-secretase

Emerging structures and dynamic mechanisms of γ-secretase for Alzheimer's disease

γ-Secretase, called "the proteasome of the membrane," is a membrane-embedded protease complex that cleaves 150+ peptide substrates with central roles in biology and medicine, including amyloid precursor protein and the Notch family of cell-surface receptors. Mutations in γ-secretase and amyloid precursor protein lead to early-onset familial Alzheimer's disease. γ-Secretase has thus served as a critical drug target for treating familial Alzheimer's disease and the more common late-onset Alzheimer's disease as well. However, critical gaps remain in understanding the mechanisms of processive proteolysis of substrates, the effects of familial Alzheimer's disease mutations, and allosteric modulation of substrate cleavage by γ-secretase. In this review, we focus on recent studies of structural dynamic mechanisms of γ-secretase. Different mechanisms, including the "Fit-Stay-Trim," "Sliding-Unwinding," and "Tilting-Unwinding," have been proposed for substrate proteolysis of amyloid precursor protein by γ-secretase based on all-atom molecular dynamics simulations. While an incorrect registry of the Notch1 substrate was identified in the cryo-electron microscopy structure of Notch1-bound γ-secretase, molecular dynamics simulations on a resolved model of Notch1-bound γ-secretase that was reconstructed using the amyloid precursor protein-bound γ-secretase as a template successfully captured γ-secretase activation for proper cleavages of both wildtype and mutant Notch, being consistent with biochemical experimental findings. The approach could be potentially applied to decipher the processing mechanisms of various substrates by γ-secretase. In addition, controversy over the effects of familial Alzheimer's disease mutations, particularly the issue of whether they stabilize or destabilize γ-secretase-substrate complexes, is discussed. Finally, an outlook is provided for future studies of γ-secretase, including pathways of substrate binding and product release, effects of modulators on familial Alzheimer's disease mutations of the γ-secretase-substrate complexes. Comprehensive understanding of the functional mechanisms of γ-secretase will greatly facilitate the rational design of effective drug molecules for treating familial Alzheimer's disease and perhaps Alzheimer's disease in general.

Molecular recognition between volatile molecules and odorant binding proteins 7 by homology modeling, molecular docking and molecular dynamics simulation

BACKGROUND

Odorant-binding proteins (OBPs) in insects are key to detection and recognition of external chemical signals associated with survival. OBP7 in Spodoptera frugiperda's larval stage (SfruOBP7) may search for host plants by sensing plant volatiles, which are important sources of pest attractants and repellents. However, the atomic-level basis of binding modes remains elusive.

RESULTS

SfruOBP7 structure was constructed through homology modeling, and complex models of six plant volatiles ((E)-2-hexenol, α-pinene, (Z)-3-hexenyl acetate, lauric acid, O-cymene and 1-octanol) and SfruOBP7 were obtained through molecular docking. To study the detailed interactions between the six plant volatile molecules and SfruOBP7, we conducted three 300 ns molecular dynamics simulations for each study object. The correlation coefficients between binding free energy obtained by molecular mechanics/generalized Born surface area together with solvated interaction energy methods and experimental values are 0.90 and 0.88, respectively, showing a good correlation. By comparing binding free energy along with interaction patterns between SfruOBP7 and the six volatile molecules, hotspot residues of SfruOBP7 when binding with different volatile molecules were determined. Hydrophobic interactions stemming from van der Waals interactions play a significant role in SfruOBP7 and these plant volatile systems.

CONCLUSION

The optimized three-dimensional structure of SfruOBP7 and its binding modes with six plant volatiles revealed their interactions, thus providing a means for estimating the binding energies of other plant volatiles. Our study will help to guide the rational design of effective and selective insect attractants. © 2024 Society of Chemical Industry.

Analysis of E2F1 single-nucleotide polymorphisms reveals deleterious non-synonymous substitutions that disrupt E2F1-RB protein interaction in cancer

Cancer is a medical condition that is caused by the abnormal growth and division of cells, leading to the formation of tumors. The E2F1 and RB pathways are critical in regulating cell cycle, and their dysregulation can contribute to the development of cancer. In this study, we analyzed experimentally reported SNPs in E2F1 and assessed their effects on the binding affinity with RB. Out of 46, nine mutations were predicted as deleterious, and further analysis revealed four highly destabilizing mutations (L206W, R232C, I254T, A267T) that significantly altered the protein structure. Molecular docking of wild-type and mutant E2F1 with RB revealed a docking score of -242 kcal/mol for wild-type, while the mutant complexes had scores ranging from -217 to -220 kcal/mol. Molecular simulation analysis revealed variations in the dynamics features of both mutant and wild-type complexes due to the acquired mutations. Furthermore, the total binding free energy for the wild-type E2F1-RB complex was -64.89 kcal/mol, while those of the L206W, R232C, I254T, and A267T E2F1-RB mutants were -45.90 kcal/mol, -53.52 kcal/mol, -55.67 kcal/mol, and -61.22 kcal/mol, respectively. Our study is the first to extensively analyze E2F1 gene mutations and identifies candidate mutations for further validation and potential targeting for cancer therapeutics.

Molecular Dynamics Activation of γ-Secretase for Cleavage of the Notch1 Substrate

γ-Secretase is an intramembrane aspartyl protease complex that cleaves the transmembrane domain of over 150 peptide substrates, including amyloid precursor protein (APP) and the Notch family of receptors, via two conserved aspartates D257 and D385 in the presenilin-1 (PS1) catalytic subunit. However, while the activation of γ-secretase for cleavage of APP has been widely studied, the cleavage of Notch by γ-secretase remains poorly explored. Here, we combined Gaussian accelerated molecular dynamics (GaMD) simulations and mass spectrometry (MS) analysis of proteolytic products to present the first dynamic models for cleavage of Notch by γ-secretase. MS showed that γ-secretase cleaved the WT Notch at Notch residue G34, while cleavage of the L36F mutant Notch occurred at Notch residue C33. Initially, we prepared our simulation systems starting from the cryoEM structure of Notch-bound γ-secretase (PDB: 6IDF) and failed to capture the proper cleavages of WT and L36F Notch by γ-secretase. We then discovered an incorrect registry of the Notch substrate in the PS1 active site through alignment of the experimental structure of Notch-bound (PDB: 6IDF) and APP-bound γ-secretase (PDB: 6IYC). Every residue of the APP substrate was systematically mutated to the corresponding Notch residue to prepare a resolved model of Notch-bound γ-secretase complexes. GaMD simulations of the resolved model successfully captured γ-secretase activation for proper cleavages of both WT and L36F mutant Notch. Our findings presented here provided mechanistic insights into the structural dynamics and enzyme-substrate interactions required for γ-secretase activation for cleavage of Notch and other substrates.

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.

Effects of presenilin-1 familial Alzheimer's disease mutations on γ-secretase activation for cleavage of amyloid precursor protein

Presenilin-1 (PS1) is the catalytic subunit of γ-secretase which cleaves within the transmembrane domain of over 150 peptide substrates. Dominant missense mutations in PS1 cause early-onset familial Alzheimer's disease (FAD); however, the exact pathogenic mechanism remains unknown. Here we combined Gaussian accelerated molecular dynamics (GaMD) simulations and biochemical experiments to determine the effects of six representative PS1 FAD mutations (P117L, I143T, L166P, G384A, L435F, and L286V) on the enzyme-substrate interactions between γ-secretase and amyloid precursor protein (APP). Biochemical experiments showed that all six PS1 FAD mutations rendered γ-secretase less active for the endoproteolytic (ε) cleavage of APP. Distinct low-energy conformational states were identified from the free energy profiles of wildtype and PS1 FAD-mutant γ-secretase. The P117L and L286V FAD mutants could still sample the "Active" state for substrate cleavage, but with noticeably reduced conformational space compared with the wildtype. The other mutants hardly visited the "Active" state. The PS1 FAD mutants were found to reduce γ-secretase proteolytic activity by hindering APP residue L49 from proper orientation in the active site and/or disrupting the distance between the catalytic aspartates. Therefore, our findings provide mechanistic insights into how PS1 FAD mutations affect structural dynamics and enzyme-substrate interactions of γ-secretase and APP.

Structural and energetic basis of interaction between human estrogen-related receptor γ and environmental endocrine disruptors from multiple molecular dynamics simulations and free energy predictions

Environmental endocrine disruptors (EEDs), a class of molecules that are widespread in our environment, may adversely affect the endocrine system. Exploring the interactions between these compounds and their potential targets is important for assessing their role in the organism. Focused on the human estrogen-related receptor γ (hERRγ) with BPA, BPB, HPTE, BPE, BP(2,2)(Et), and BP(2,2)(MeO) complexes, respectively, we groped for the mechanisms of conformational changes and interactions of hERRγ when binding to these six EEDs by combining multiple molecular dynamics (MD) simulations with energy prediction (MM-PBSA and solvated interaction energy (SIE)). Dynamics analysis results revealed these six EEDs have different effects on the internal dynamics of hERRγ, resulting in significant changes in the interaction of key residues around Leu268, Val313, Leu345, and Phe435 with EEDs, and thus affected its binding energy with these EEDs. The energy calculations further demonstrated that van der Waals interactions are critical for these EEDs binding to hERRγ. These results present detailed molecular insight into the interaction features between EEDs and hERRγ and help guide the search for safer alternatives to BPA.

Genetics, Functions, and Clinical Impact of Presenilin-1 (PSEN1) Gene

Presenilin-1 (PSEN1) has been verified as an important causative factor for early onset Alzheimer's disease (EOAD). PSEN1 is a part of γ-secretase, and in addition to amyloid precursor protein (APP) cleavage, it can also affect other processes, such as Notch signaling, β-cadherin processing, and calcium metabolism. Several motifs and residues have been identified in PSEN1, which may play a significant role in γ-secretase mechanisms, such as the WNF, GxGD, and PALP motifs. More than 300 mutations have been described in PSEN1; however, the clinical phenotypes related to these mutations may be diverse. In addition to classical EOAD, patients with PSEN1 mutations regularly present with atypical phenotypic symptoms, such as spasticity, seizures, and visual impairment. In vivo and in vitro studies were performed to verify the effect of PSEN1 mutations on EOAD. The pathogenic nature of PSEN1 mutations can be categorized according to the ACMG-AMP guidelines; however, some mutations could not be categorized because they were detected only in a single case, and their presence could not be confirmed in family members. Genetic modifiers, therefore, may play a critical role in the age of disease onset and clinical phenotypes of PSEN1 mutations. This review introduces the role of PSEN1 in γ-secretase, the clinical phenotypes related to its mutations, and possible significant residues of the protein.

Sequence-structure functional implications and molecular simulation of high deleterious nonsynonymous substitutions in IDH1 revealed the mechanism of drug resistance in glioma

In the past few years, various somatic point mutations of isocitrate dehydrogenase (IDH) encoding genes (IDH1 and IDH2) have been identified in a broad range of cancers, including glioma. Despite the important function of IDH1 in tumorigenesis and its very polymorphic nature, it is not yet clear how different nsSNPs affect the structure and function of IDH1. In the present study, we employed different machine learning algorithms to screen nsSNPs in the IDH1 gene that are highly deleterious. From a total of 207 SNPs, all of the servers classified 80 mutations as deleterious. Among the 80 deleterious mutations, 14 were reported to be highly destabilizing using structure-based prediction methods. Three highly destabilizing mutations G15E, W92G, and I333S were further subjected to molecular docking and simulation validation. The docking results and molecular simulation analysis further displayed variation in dynamics features. The results from molecular docking and binding free energy demonstrated reduced binding of the drug in contrast to the wild type. This, consequently, shows the impact of these deleterious substitutions on the binding of the small molecule. PCA (principal component analysis) and FEL (free energy landscape) analysis revealed that these mutations had caused different arrangements to bind small molecules than the wild type where the total internal motion is decreased, thus consequently producing minimal binding effects. This study is the first extensive in silico analysis of the IDH1 gene that can narrow down the candidate mutations for further validation and targeting for therapeutic purposes.

A thermodynamic investigation of amyloid precursor protein processing by human γ-secretase

Human γ-secretase cleaves the transmembrane domains (TMDs) of amyloid precursor protein (APP) into pathologically relevant amyloid-β peptides (Aβs). The detailed mechanisms of the unique endoproteolytic cleavage by the presenilin 1 domain (PS1) of γ-secretase are still poorly understood. Herein, we provide thermodynamic insights into how the α-helical APP TMD is processed by γ-secretase and elucidate the specificity of Aβ48/Aβ49 cleavage using unbiased molecular dynamics and bias-exchange metadynamics simulations. The thermodynamic data show that the unwinding of APP TMD is driven by water hydration in the intracellular pocket of PS1, and the scissile bond T32-L33 or L33-V34 of the APP TMD can slide down and up to interact with D257/D385 to achieve endoproteolysis. In the wild-type system, the L33-V34 scissile bond is more easily hijacked by D257/D385 than T32-L33, resulting in higher Aβ49 cleavage, while the T32N mutation on the APP TMD decreases the energy barrier of the sliding of the scissile bonds and increases the hydrogen bond occupancy for Aβ48 cleavage. In summary, the thermodynamic analysis elucidates possible mechanisms of APP TMD processing by PS1, which might facilitate rational drug design targeting γ-secretase.

Thermodynamic analysis from unbiased molecular dynamics and bias-exchange metadynamics simulations reveals possible mechanisms on how γ-secretase cleaves the transmembrane domains of amyloid precursor protein into amyloid-β peptides.

Structure and mechanism of the γ-secretase intramembrane protease complex

γ-Secretase is a membrane protein complex that proteolyzes within the transmembrane domain of >100 substrates, including those derived from the amyloid precursor protein and the Notch family of cell surface receptors. The nine-transmembrane presenilin is the catalytic component of this aspartyl protease complex that carries out hydrolysis in the lipid bilayer. Advances in cryoelectron microscopy have led to the elucidation of the structure of the γ-secretase complex at atomic resolution. Recently, structures of the enzyme have been determined with bound APP- or Notch-derived substrates, providing insight into the nature of substrate recognition and processing. Molecular dynamics simulations of substrate-bound enzymes suggest dynamic mechanisms of intramembrane proteolysis. Structures of the enzyme bound to small-molecule inhibitors and modulators have also been solved, setting the stage for rational structure-based drug discovery targeting γ-secretase.

Mechanism of Tripeptide Trimming of Amyloid β-Peptide 49 by γ-Secretase

The membrane-embedded γ-secretase complex processively cleaves within the transmembrane domain of amyloid precursor protein (APP) to produce 37-to-43-residue amyloid β-peptides (Aβ) of Alzheimer's disease (AD). Despite its importance in pathogenesis, the mechanism of processive proteolysis by γ-secretase remains poorly understood. Here, mass spectrometry and Western blotting were used to quantify the efficiency of tripeptide trimming of wild-type (WT) and familial AD (FAD) mutant Aβ49. In comparison to WT Aβ49, the efficiency of tripeptide trimming was similar for the I45F, A42T, and V46F Aβ49 FAD mutants but substantially diminished for the I45T and T48P mutants. In parallel with biochemical experiments, all-atom simulations using a novel peptide Gaussian accelerated molecular dynamics (Pep-GaMD) method were applied to investigate the tripeptide trimming of Aβ49 by γ-secretase. The starting structure was the active γ-secretase bound to Aβ49 and APP intracellular domain (AICD), as generated from our previous study that captured the activation of γ-secretase for the initial endoproteolytic cleavage of APP (Bhattarai, A., ACS Cent. Sci. 2020, 6, 969-983). Pep-GaMD simulations captured remarkable structural rearrangements of both the enzyme and substrate, in which hydrogen-bonded catalytic aspartates and water became poised for tripeptide trimming of Aβ49 to Aβ46. These structural changes required a positively charged N-terminus of endoproteolytic coproduct AICD, which could dissociate during conformational rearrangements of the protease and Aβ49. The simulation findings were highly consistent with biochemical experimental data. Taken together, our complementary biochemical experiments and Pep-GaMD simulations have enabled elucidation of the mechanism of tripeptide trimming of Aβ49 by γ-secretase.

Discovery of Novel and Highly Potent Inhibitors of SARS CoV-2 Papain-Like Protease Through Structure-Based Pharmacophore Modeling, Virtual Screening, Molecular Docking, Molecular Dynamics Simulations, and Biological Evaluation

Background and Objective: COVID-19 has struck our society as a great calamity, and the need for effective anti-viral drugs is more urgent than ever. Papain-like protease (PLpro) of SARS CoV-2 plays important roles in virus maturation, dysregulation of host inflammation, and antiviral immune responses, which is being regarded as a promising druggable target for the treatment of COVID-19. Here, we carried out a combined screening approach to identify novel and highly potent PLpro inhibitors for the treatment of COVID-19.

Methods: We used a combined screening approach of structure-based pharmacophore modeling and molecular docking to screen an in-house database containing 35,000 compounds. SARS CoV-2 PLpro inhibition assay was used to carry out the biological evaluation of hit compounds. Molecular dynamics (MD) simulations were conducted to check the stability of the PLpro-hit complexes predicted by molecular docking.

Results: We found that four hit compounds showed excellent inhibitory activities against PLpro with IC₅₀ values ranging from 0.6 to 2.4 μM. Among them, the most promising compound, hit 2 is the best PLpro inhibitor and its inhibitory activity was about 4 times higher than that of the positive control (GRL0617). The study of MD simulations indicated that four hits could bind stably to the active site of PLpro. Further study of interaction analysis indicated that hit 2 could form hydrogen-bond interactions with the key amino acids such as Gln269 and Asp164 in the PLpro-active site.

Conclusion: Hit 2 is a novel and highly potent PLpro inhibitor, which will open the way for the development of clinical PLpro inhibitors for the treatment of COVID-19.

Molecular characterization and structural dynamics of Aquaporin1 from walking catfish in lipid bilayers

Aquaporin's (AQPs) are the major superfamily of small integral membrane proteins that facilitates transportation of water, urea, ammonia, glycerol and ions across biological cell membranes. Despite of recent advancements made in understanding the biology of Aquaporin's, only few isoforms of aquaporin 1 (AQP1) some of the teleost fish species have been characterized at molecular scale. In this study, we made an attempt to elucidate the molecular mechanism of water transportation in AQP1 from walking catfish (Clarias batrachus), a model species capable of breathing in air and inhabits in challenging environments. Using state-of-the-art computational modelling and all-atoms molecular dynamics simulation, we explored the structural dynamics of full-length aquaporin 1 from walking catfish (CbAQP1) in lipid mimetic bilayers. Unlike AQP1 of human and bovine, structural ensembles of CbAQP1 from MD revealed discrete positioning of pore lining residues at the intracellular end. Snapshots from MD simulation displayed differential dynamics of aromatic/arginine (ar/R) filter and extracellular loop C bridging transmembrane (TM) helix H3 and H4. Distinct conformation of large extracellular loops, loop bridging TM2 domain and HB helix along with positioning of selectivity filter lining residues controls the permeability of water across the bilayer. Moreover, the identified unique and conserved lipid binding sites with 100% lipid occupancy signifies lipid mediated structural dynamics of CbAQP1. All-together, this is the first ever report on structural-dynamics of aquaporin 1 in walking catfish which will be useful to understand the molecular basis of transportation of water and other small molecules under varying degree of hyperosmotic environment.

Characterizing the Chemical Space of γ-Secretase Inhibitors and Modulators

γ-Secretase (GS) is one of the most attractive molecular targets for the treatment of Alzheimer's disease (AD). Its key role in the final step of amyloid-β peptides generation and its relationship in the cascade of events for disease development have caught the attention of many pharmaceutical groups. Over the past years, different inhibitors and modulators have been evaluated as promising therapeutics against AD. However, despite the great chemical diversity of the reported compounds, a global classification and visual representation of the chemical space for GS inhibitors and modulators remain unavailable. In the present work, we carried out a two-dimensional (2D) chemical space analysis from different classes and subclasses of GS inhibitors and modulators based on their structural similarity. Along with the novel structural information available for GS complexes, our analysis opens the possibility to identify compounds with high molecular similarity, critical to finding new chemical structures through the optimization of existing compounds and relating them with a potential binding site.