Identification Mechanism of BACE1 on Inhibitors Probed by Using Multiple Separate Molecular Dynamics Simulations and Comparative Calculations of Binding Free Energies

Elucidating the suppressive mechanism of four inhibitors on VP39 and unique conformational changes with protein in mode 2

Methyltransferase VP39 is an important target for the treatment of monkeypox, and inhibition of VP39 can effectively suppresses the transcription and translation of early viral RNA. However, very few inhibitors have been designed against VP39 and other viral MTases. In this work, four inhibitors (SFG, TO507, TO427 and TO1119) were used to investigate the binding mechanism with VP39. Moreover, VP39 has different modes of existence, but we do not understand the interaction mechanism of the complex system formed by the inhibitors with different modes of VP39, so we performed 1000 ns molecular dynamics simulations of the complexes formed by four inhibitors with VP39 in mode 1 and mode 2, and performed energy calculation and conformational analysis. The results of binding free energy showed that in the inhibitors-VP39 (mode 1) systems, TO507 and TO427 had a strong inhibitory effect on VP39, and residues ASP95, ARG97, PHE115 and VAL139 played important roles in the binding process of all four systems. Surprisingly, in the inhibitors-VP39 (mode 2) systems, four inhibitors underwent a large conformational change, with the amino acid moieties of the inhibitors undergoing a nearly 90° folding. And this change reduced the inhibitory effect of the inhibitors on VP39. In addition, the inhibitor TO507 also had a good inhibition effect on nsp14 of SARS-CoV-2 and NS5 of Zika virus. Therefore, this study suggests new ideas for the design and improvement of pan-MTase inhibitors, which are important for the treatment of pandemic infectious diseases, such as monkeypox and SARS-CoV-2.

Advancing Alzheimer's Therapy: Computational strategies and treatment innovations

Alzheimer's disease (AD) is a multifaceted neurodegenerative condition distinguished by the occurrence of memory impairment, cognitive deterioration, and neuronal impairment. Despite extensive research efforts, conventional treatment strategies primarily focus on symptom management, highlighting the need for innovative therapeutic approaches. This review explores the challenges of AD treatment and the integration of computational methodologies to advance therapeutic interventions. A comprehensive analysis of recent literature was conducted to elucidate the broad scope of Alzheimer's etiology and the limitations of conventional drug discovery approaches. Our findings underscore the critical role of computational models in elucidating disease mechanisms, identifying therapeutic targets, and expediting drug discovery. Through computational simulations, researchers can predict drug efficacy, optimize lead compounds, and facilitate personalized medicine approaches. Moreover, machine learning algorithms enhance early diagnosis and enable precision medicine strategies by analyzing multi-modal datasets. Case studies highlight the application of computational techniques in AD therapeutics, including the suppression of crucial proteins implicated in disease progression and the repurposing of existing drugs for AD management. Computational models elucidate the interplay between oxidative stress and neurodegeneration, offering insights into potential therapeutic interventions. Collaborative efforts between computational biologists, pharmacologists, and clinicians are essential to translate computational insights into clinically actionable interventions, ultimately improving patient outcomes and addressing the unmet medical needs of individuals affected by AD. Overall, integrating computational methodologies represents a promising paradigm shift in AD therapeutics, offering innovative solutions to overcome existing challenges and transform the landscape of AD treatment.

A stilbenoid, rhapontigenin, isolated from the root of Rheum palmatum L. acts as a potent BACE1 inhibitor

Seven compounds, comprising three anthraquinones and four stilbenoids, were isolated from the roots of Rheum palmatum L. These compounds include chrysophanol (1), aloe-emodin (2), aloe-emodin 8-O-β-D-glucopyranoside (3), desoxyrhapontigenin (4), rhapontigenin (5), desoxyrhaponticin (6), and piceatannol 3'-O-β-D-glucopyranoside (7). Among these, compound 5 showed potent β-site amyloid precursor protein cleaving enzyme 1 (BACE1) inhibitory activity with an IC50 value of 0.256 ± 0.008 μM, making it the most effective inhibitor obtained from herbal extracts to date, followed by compounds 3 (1.164 ± 0.108 μM), 6 (1.213 ± 0.193 μM), 7 (1.270 ± 0.130 μM), and 4 (2.028 ± 0.108 μM). Furthermore, kinetic analysis revealed that compound 5 acted as a mixed type-I inhibitor with an inhibition constant Ki value of 0.28 ± 0.07 μM. Notably, compound 2 exhibited potent Aβ aggregation inhibition with an IC50 value of 3.56 ± 0.19 μM, whereas compound 5 showed low Aβ aggregation inhibition with an IC50 value of >40 μM. The docking simulations revealed that compound 5 had a high binding affinity and interacted with TYR132, predicting it as a key residue for inhibition via hydrophobic interaction, and with THR133 via hydrogen bonding, in the flap region of BACE1. These results suggest that stilbenoids generally exhibit higher BACE1 inhibitory activity than that of anthraquinones, and that compound 5 (rhapontigenin) could be a promising candidate for the treatment of Alzheimer's disease as a potent BACE1 inhibitor.

Conformations of KRAS4B Affected by Its Partner Binding and G12C Mutation: Insights from GaMD Trajectory-Image Transformation-Based Deep Learning

Binding of partners and mutations highly affects the conformational dynamics of KRAS4B, which is of significance for deeply understanding its function. Gaussian accelerated molecular dynamics (GaMD) simulations followed by deep learning (DL) and principal component analysis (PCA) were carried out to probe the effect of G12C and binding of three partners NF1, RAF1, and SOS1 on the conformation alterations of KRAS4B. DL reveals that G12C and binding of partners result in alterations in the contacts of key structure domains, such as the switch domains SW1 and SW2 together with the loops L4, L5, and P-loop. Binding of NF1, RAF1, and SOS1 constrains the structural fluctuation of SW1, SW2, L4, and L5; on the contrary, G12C leads to the instability of these four structure domains. The analyses of free energy landscapes (FELs) and PCA also show that binding of partners maintains the stability of the conformational states of KRAS4B while G12C induces greater mobility of the switch domains SW1 and SW2, which produces significant impacts on the interactions of GTP with SW1, L4, and L5. Our findings suggest that partner binding and G12C play important roles in the activity and allosteric regulation of KRAS4B, which may theoretically aid in further understanding the function of KRAS4B.

Mutations influence the conformational dynamics of the GDP/KRAS complex

Mutations near allosteric sites can have a significant impact on the function of KRAS. Three specific mutations, K104Q, G12D/K104Q, and G12D/G75A, which are located near allosteric positions, were selected to investigate the molecular mechanisms behind mutation-induced influences on the activity of KRAS. Gaussian accelerated molecular dynamics (GaMD) simulations followed by the principal component analysis (PCA) were performed to improve the sampling of conformational states. The results revealed that these mutations significantly alter the structural flexibility, correlated motions, and dynamic behavior of the switch regions that are essential for KRAS binding to effectors or regulators. Furthermore, the mutations have a significant impact on the hydrogen bonding interactions between GDP and the switch regions, as well as on the electrostatic interactions of magnesium ions (Mg2+) with these regions. Our results verified that these mutations strongly influence the binding of KRAS to its effectors or regulators and allosterically regulate the activity. We believe that this work can provide valuable theoretical insights into a deeper understanding of KRAS function.

Roles of Accelerated Molecular Dynamics Simulations in Predictions of Binding Kinetic Parameters

Rational predictions on binding kinetics parameters of drugs to targets play significant roles in future drug designs. Full conformational samplings of targets are requisite for accurate predictions of binding kinetic parameters. In this review, we mainly focus on the applications of enhanced sampling technologies in calculations of binding kinetics parameters and residence time of drugs. The methods involved in molecular dynamics simulations are applied to not only probe conformational changes of targets but also reveal calculations of residence time that is significant for drug efficiency. For this review, special attention are paid to accelerated molecular dynamics (aMD) and Gaussian aMD (GaMD) simulations that have been adopted to predict the association or disassociation rate constant. We also expect that this review can provide useful information for future drug design.

Exploring potent aldose reductase inhibitors for anti-diabetic (anti-hyperglycemic) therapy: integrating structure-based drug design, and MMGBSA approaches

Aldose reductase (AR) is an important target in the development of therapeutics against hyper-glycemia-induced health complications such as retinopathy, etc. In this study, we employed a combination of structure-based drug design, molecular simulation, and free energy calculation approaches to identify potential hit molecules against anti-diabetic (anti-hyperglycemic)-induced health complications. The 3D structure of aldoreductase was screened for multiple compound libraries (1,00,000 compounds) and identified as ZINC35671852, ZINC78774792 from the ZINC database, Diamino-di nitro-methyl dioctyl phthalate, and Penta-o-galloyl-glucose from the South African natural compounds database, and Bisindolylmethane thiosemi-carbazides and Bisindolylme-thane-hydrazone from the Inhouse database for this study. The mode of binding interactions of the selected compounds later predicted their aldose reductase inhibitory potential. These com-pounds interact with the key active site residues through hydrogen bonds, salt bridges, and π-π interactions. The structural dynamics and binding free energy results further revealed that these compounds possess stable dynamics with excellent binding free energy scores. The structures of the lead inhibitors can serve as templates for developing novel inhibitors, and in vitro testing to confirm their anti-diabetic potential is warranted. The current study is the first to design small molecule inhibitors for the aldoreductase protein that can be used in the development of therapeutic agents to treat diabetes.

Exploring conformation changes of Janus kinase 2 pseudokinase mediated by mutations through Gaussian accelerated molecular dynamics and principal component analysis

The pseudokinase domain (JH2) of the protein tyrosine kinase (Janus kinase 2, JAK2) regulates the activity of a tyrosine kinase domain (JH1) in JAK2, which is further affected by mutations in the JH2. In this work, Gaussian accelerated molecular dynamics (GaMD) simulations followed by construction of free energy landscapes (FELs) and principal component analysis (PCA) were performed to study effect of two mutations V617F and V617F/E596A on the conformations of the ATP-bound JH2. The dynamic analyses reveal that mutations affect the structural flexibility and correlated motions of the JH2, meanwhile also change the dynamics behavior of the P-loop and αC-helix of the JH2. The information from FELs unveils that mutations induce less energy states than the free JH2 and the WT one. The analyses of interaction networks uncover that mutations affect the salt bridge interactions of ATP with K581, K677 and R715 and alter hydrogen bonding interactions (HBIs) of ATP with the JH2. The changes in conformations of the JH2 and ATP-JH2 interaction networks caused by mutations in turn generate effect on the activity regulations of the JH2 on the JH1. This work is expected to provide significant theoretical helps for deeply understanding the function of the JH2 and drug design toward JAK2.Communicated by Ramaswamy H. Sarma.