Docking and binding free energy calculations of sirtuin inhibitors

Mitochondrial sirtuins: Energy dynamics and cancer metabolism

Mitochondria are pivotal for energy regulation and are linked to cancer. Mitochondrial sirtuins, (Sirtuin) SIRT3, SIRT4, and SIRT5, play crucial roles in cancer metabolism. This review explores their impact on cellular processes, with a focus on the NAD+ interplay and the modulation of their enzymatic activities. The varied roles of SIRT3, SIRT4, and SIRT5 in metabolic adaptation and cancer are outlined, emphasizing their tumor suppressor or oncogenic nature. We propose new insights into sirtuin biology, and cancer therapeutics, suggesting an integrated proteomics and metabolomics approach for a comprehensive understanding of mitochondrial sirtuins in cancer.

Application of Ligand- and Structure-Based Prediction Models for the Design of Alkylhydrazide-Based HDAC3 Inhibitors as Novel Anti-Cancer Compounds

Histone deacetylases (HDAC) represent promising epigenetic targets for several diseases including different cancer types. The HDAC inhibitors approved to date are pan-HDAC inhibitors and most show a poor selectivity profile, side effects, and in particular hydroxamic-acid-based inhibitors lack good pharmacokinetic profiles. Therefore, the development of isoform-selective non-hydroxamic acid HDAC inhibitors is a highly regarded field in medicinal chemistry. In this study, we analyzed different ligand-based and structure-based drug design techniques to predict the binding mode and inhibitory activity of recently developed alkylhydrazide HDAC inhibitors. Alkylhydrazides have recently attracted more attention as they have shown promising effects in various cancer cell lines. In this work, pharmacophore models and atom-based quantitative structure-activity relationship (QSAR) models were generated and evaluated. The binding mode of the studied compounds was determined using molecular docking as well as molecular dynamics simulations and compared with known crystal structures. Calculated free energies of binding were also considered to generate QSAR models. The created models show a good explanation of in vitro data and were used to develop novel HDAC3 inhibitors.

Modeling disruption of Apis mellifera (honey bee) odorant-binding protein function with high-affinity binders

Chemical toxins pose a great threat to honey bee health because they affect memory and cognition, diminish immunity, and increase susceptibility to infection, resulting in decreased colony performance, reproduction, and survival. Although the behavioral effects of sub-lethal chemical exposure on honey bees have been intensively studied, how xenobiotics affect olfaction, at the molecular level, still needs to be elucidated. In the present work, in silico tools, such as molecular docking, binding free energy calculations, and molecular dynamics simulations are used to predict if environmental chemicals have stronger binding affinities to honey bee antennal odorant-binding protein 14 (OBP14) than the representative floral odors citralva, eugenol, and the fluorescent probe 1-N-phenylnaphthylamine. Based on structural analysis, 21 chemicals from crop pesticides, household appliances, cosmetics, food, public health-related products, and other sources, many of which are pervasive in the hive environment, have higher binding affinities than the floral odors. These results suggest that chemical exposures are likely to interfere with the honey bee's sense of smell and this disruptive mechanism may be responsible for the lower associative learning and memory based on olfaction found in bees exposed to pesticides. Moreover, bees mainly rely on olfactory cues to perceive their environment and orient themselves as well as to discriminate and identify their food, predators, nestmates, and diseased individuals that need to be removed with hygienic behavior. In summary, sub-lethal exposure to environmental toxins can contribute to colony collapse in several ways from the disruption of proper olfaction functioning.

Docking, Binding Free Energy Calculations and In Vitro Characterization of Pyrazine Linked 2-Aminobenzamides as Novel Class I Histone Deacetylase (HDAC) Inhibitors

Class I histone deacetylases, HDAC1, HDAC2, and HDAC3, represent potential targets for cancer treatment. However, the development of isoform-selective drugs for these enzymes remains challenging due to their high sequence and structural similarity. In the current study, we applied a computational approach to predict the selectivity profile of developed inhibitors. Molecular docking followed by MD simulation and calculation of binding free energy was performed for a dataset of 2-aminobenzamides comprising 30 previously developed inhibitors. For each HDAC isoform, a significant correlation was found between the binding free energy values and in vitro inhibitory activities. The predictive accuracy and reliability of the best preforming models were assessed on an external test set of newly designed and synthesized inhibitors. The developed binding free-energy models are cost-effective methods and help to reduce the time required to prioritize compounds for further studies.

In silico insights into potential gut microbial modulation of NAD+ metabolism and longevity

Recent evidence has prompted the notion of gut-microbial signatures as an indirect marker of aging and aging-associated decline in humans. However, the underlying host-symbiont molecular interactions contributing to these signatures remain poorly understood. In this study, we address this gap using cheminformatic analyses to elucidate potential gut microbial metabolites that may perturb the longevity-associated NAD+ metabolic network. In silico ADMET, KEGG interaction analysis, molecular docking, molecular dynamics simulation, and molecular mechanics calculation predict a large number of safe and bioavailable microbial metabolites to be direct and/or indirect activators of NAD+-dependent sirtuin proteins. Our simulation results suggest dihydropteroate, phenylpyruvic acid, indole-3-propionic acid, phenyllactic acid, all-trans-retinoic acid, and multiple deoxy-, methyl-, and cyclic nucleotides from intestinal microbiota as the best-performing regulators of NAD+ metabolism. Retracing these molecules to their source microorganisms also suggest commensal Escherichia, Bacteroides, Bifidobacteria, and Lactobacilli to be associated with the highest number of pro-longevity metabolites. These findings from our early-stage study, therefore, provide an informatics-based context for previous evidence in the area and grant novel insights for future clinical investigation intersecting anti-aging drug discovery, probiotics, and gut microbial signatures.

Molecular Dynamics Simulations Reveal the Modulated Mechanism of STING Conformation

Stimulator of interferon genes (STING), which is an integral ER-membrane protein, could induce an antiviral state and boost antitumor immunity. Recent experiments reported that different small molecules could modulate the conformation of the STING. However, the mechanism of small molecules modulating the conformation of STING is still unknown. To illustrate the conformational modulated mechanism of STING by small molecules at atomic level, we investigated the interactions between STING and the small molecules: cGAMP and diABZI with molecular dynamics (MD) simulations method. Interestingly, we found that the residues of STING in the binding pocket are more flexible in the monomers of STING than that in the dimer of STING. We also demonstrated that cGAMP and diABZI have a similar binding mode to STING monomers/dimer, and π-π stacking interactions play important roles for the agonists and STING. Our study proposed mechanistic insights into the STING conformation modulated by small molecules and we suggested that the special molecule (e. g. diABZI) could induce the conformational transition of STING from the "open" monomers to the "closed" dimer state. Our research may provide a clue for the development of cancer immunotherapy.

Thermodynamics and Kinetics of Drug-Target Binding by Molecular Simulation

Computational studies play an increasingly important role in chemistry and biophysics, mainly thanks to improvements in hardware and algorithms. In drug discovery and development, computational studies can reduce the costs and risks of bringing a new medicine to market. Computational simulations are mainly used to optimize promising new compounds by estimating their binding affinity to proteins. This is challenging due to the complexity of the simulated system. To assess the present and future value of simulation for drug discovery, we review key applications of advanced methods for sampling complex free-energy landscapes at near nonergodicity conditions and for estimating the rate coefficients of very slow processes of pharmacological interest. We outline the statistical mechanics and computational background behind this research, including methods such as steered molecular dynamics and metadynamics. We review recent applications to pharmacology and drug discovery and discuss possible guidelines for the practitioner. Recent trends in machine learning are also briefly discussed. Thanks to the rapid development of methods for characterizing and quantifying rare events, simulation's role in drug discovery is likely to expand, making it a valuable complement to experimental and clinical approaches.

Mitochondrial Sirtuin 3: New emerging biological function and therapeutic target

Sirtuin 3 (SIRT3) is one of the most prominent deacetylases that can regulate acetylation levels in mitochondria, which are essential for eukaryotic life and inextricably linked to the metabolism of multiple organs. Hitherto, SIRT3 has been substantiated to be involved in almost all aspects of mitochondrial metabolism and homeostasis, protecting mitochondria from a variety of damage. Accumulating evidence has recently documented that SIRT3 is associated with many types of human diseases, including age-related diseases, cancer, heart disease and metabolic diseases, indicating that SIRT3 can be a potential therapeutic target. Here we focus on summarizing the intricate mechanisms of SIRT3 in human diseases, and recent notable advances in the field of small-molecule activators or inhibitors targeting SIRT3 as well as their potential therapeutic applications for future drug discovery.

Structural Insight into the Interactions between Structurally Similar Inhibitors and SIRT6

Sirtuin 6 (SIRT6) is an NAD+-dependent deacetylase with a significant role in 20% of all cancers, such as colon cancers and rectal adenocarcinoma. However, there is currently no effective drug for cancers related to SIRT6. To explore potential inhibitors of SIRT6, it is essential to reveal details of the interaction mechanisms between inhibitors and SIRT6 at the atomic level. The nature of small molecules from herbs have many advantages as inhibitors. Based on the conformational characteristics of the inhibitor Compound 9 (Asinex ID: BAS13555470), we explored the natural molecule Scutellarin, one compound of Huang Qin, which is an effective herb for curing cancer that has been described in the Traditional Chinese Medicine (TCMS) library. We investigated the interactions between SIRT6 and the inhibitors using molecular dynamics (MD) simulations. We illustrated that the structurally similar inhibitors have a similar binding mode to SIRT6 with residues—Leu9, Phe64, Val115, His133 and Trp188. Hydrophobic and π-stacking interactions play important roles in the interactions between SIRT6 and inhibitors. In summary, our results reveal the interactive mechanism of SIRT6 and the inhibitors and we also provide Scutellarin as a new potential inhibitor of SIRT6. Our study provides a new potential way to explore potential inhibitors from TCMS.

A Comparative Linear Interaction Energy and MM/PBSA Study on SIRT1-Ligand Binding Free Energy Calculation

Binding free energy (ΔGbind) computation can play an important role in prioritizing compounds to be evaluated experimentally on their affinity for target proteins, yet fast and accurate ΔGbind calculation remains an elusive task. In this study, we compare the performance of two popular end-point methods, i.e., linear interaction energy (LIE) and molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA), with respect to their ability to correlate calculated binding affinities of 27 thieno[3,2-d]pyrimidine-6-carboxamide-derived sirtuin 1 (SIRT1) inhibitors with experimental data. Compared with the standard single-trajectory setup of MM/PBSA, our study elucidates that LIE allows to obtain direct ("absolute") values for SIRT1 binding free energies with lower compute requirements, while the accuracy in calculating relative values for ΔGbind is comparable (Pearson's r = 0.72 and 0.64 for LIE and MM/PBSA, respectively). We also investigate the potential of combining multiple docking poses in iterative LIE models and find that Boltzmann-like weighting of outcomes of simulations starting from different poses can retrieve appropriate binding orientations. In addition, we find that in this particular case study the LIE and MM/PBSA models can be optimized by neglecting the contributions from electrostatic and polar interactions to the ΔGbind calculations.

In silico and in vitro identification of candidate SIRT1 activators from Indonesian medicinal plants compounds database

Sirtuin 1 (SIRT1) is a class III family of protein histone deacetylases involved in NAD⁺-dependent deacetylation reactions. It has been suggested that SIRT1 activators may have a protective role against type 2 diabetes, the aging process, and inflammation. This study aimed to explore and identify medicinal plant compounds from Indonesian Herbal Database (HerbalDB) that might potentially become a candidate for SIRT1 activators through a combination of in silico and in vitro methods. Two pharmacophore models were developed using co-crystalized ligands that allosterically bind with SIRT1 similar to the putative ligands used by SIRT1 activators. Then, these were used for the virtual screening of HerbalDB. The identified compounds were subjected to molecular docking and 50 ns molecular dynamics simulation. Molecular dynamics simulation was analyzed using MM-GB(PB)SA methods. The compounds identified by these methods were tested in an in vitro study using a SIRT-Glo™ luminescence assay. Virtual screening using structure-based pharmacophores predicted that mulberrin as the best candidate SIRT1 activator. Virtual screening using ligand-based pharmacophores predicted that gartanin, quinidine, and quinine to be the best candidates as SIRT1 activators. The molecular docking studies showed the important residues involved were Ile223 and Ile227 at the allosteric region. The MM-GB(PB)SA calculations confirmed that mulberrin, gartanin, quinidine, quinine showed activity at allosteric region and their EC₅₀ in vitro values are 2.10; 1.79; 1.71; 1.14 μM, respectively. Based on in silico and in vitro study results, mulberin, gartanin, quinidine, and quinine had good activity as SIRT1 activators.

Computer-aided design, synthesis and biological characterization of novel inhibitors for PKMYT1

In the current work, we applied computational methods to analyze the membrane-associated inhibitory kinase PKMYT1 and small molecule inhibitors. PKMYT1 regulates the cell cycle at G2/M transition and phosphorylates Thr14 and Tyr15 in the Cdk1-cyclin B complex. A combination of in silico and in vitro screening was applied to identify novel PKMYT1 inhibitors. The computational approach combined structural analysis, molecular docking, binding free energy calculations, and quantitative structure-activity relationship (QSAR) models. In addition, a computational fragment growing approach was applied to a set of previously identified diaminopyrimidines. Based on the derived computational models, several derivatives were synthesized and tested in vitro on PKMYT1. Novel inhibitors active in the sub-micromolar range were identified which provide the basis for further characterization of PKMYT1 as putative target for cancer therapy.

Recent Developments and Applications of the MMPBSA Method

The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach has been widely applied as an efficient and reliable free energy simulation method to model molecular recognition, such as for protein-ligand binding interactions. In this review, we focus on recent developments and applications of the MMPBSA method. The methodology review covers solvation terms, the entropy term, extensions to membrane proteins and high-speed screening, and new automation toolkits. Recent applications in various important biomedical and chemical fields are also reviewed. We conclude with a few future directions aimed at making MMPBSA a more robust and efficient method.

Pharmacokinetics and effects of tetrabromobisphenol a (TBBPA) to early life stages of zebrafish (Danio rerio)

In silico and in vivo approaches were combined in an aggregate exposure pathway (AEP) to assess accumulation and effects of waterborne exposures of early life stages of zebrafish (Danio rerio) to tetrabromobisphenol A (TBBPA). Three metabolites, two of which were isomers, were detected in fish. Two additional metabolites were detected in the exposure solution. Based on kinetics modeling, proportions of TBBPA that were bioaccumulated and metabolized were 19.33% and 8.88%, respectively. Effects of TBBPA and its metabolites were predicted by use of in silico, surflex-Dock simulations that they were capable of interacting with ThRα and activating associated signaling pathways. TBBPA had a greater toxic contribution than its metabolites did when we evaluated the toxicity of these substances based on the toxicity unit method. The half of the internal lethal dose (ILD₅₀) was 18.33 μg TBBPA/g at 74 hpf. This finding was further confirmed by changes in expressions of ThRα and other NRs as well as associated genes in their signal pathways. Specifically, exposure to 1.6 × 10², 3.3 × 10² or 6.5 × 10² μg TBBPA/L significantly down-regulated expression of ThRα and associated genes, ncor, c1d, ncoa2, ncoa3, and ncoa4, in the AR pathway and of er2a and er2b genes in the ER pathway.

Interactions of omeprazole-based analogues with cytochrome P450 2C19: a computational study

Cytochrome P450 2C19 (CYP2C19) is one of 57 drug metabolizing enzymes in humans and is responsible for the metabolism of ∼7-10% of drugs in clinical use. Recently omeprazole-based analogues were reported to be the potent inhibitors of CYP2C19 and have the potential to be used as the tool compounds for studying the substrate selectivity of CYP2C19. However, the binding modes of these compounds with CYP2C19 remain to be elucidated. In this study, a combination of molecular docking, molecular dynamics (MD), and MM/GBSA calculations was employed to systematically investigate the interactions between these compounds and CYP2C19. The binding modes of these analogues were analyzed in detail. The results indicated that the inclusion of explicit active site water molecules could improve binding energy prediction when the water molecules formed a hydrogen bonding network between the ligand and protein. We also found that the effect of active site water molecules on binding free energy prediction was dependent on the ligand binding modes. Our results unravel the interactions of these omeprazole-based analogues with CYP2C19 and might be helpful for the future design of potent CYP2C19 inhibitors with improved metabolic properties.

Lumican Peptides: Rational Design Targeting ALK5/TGFBRI

Lumican, a small leucine rich proteoglycan (SLRP), is a component of extracellular matrix which also functions as a matrikine regulating multiple cell activities. In the cornea, lumican maintains corneal transparency by regulating collagen fibrillogenesis, promoting corneal epithelial wound healing, regulating gene expression and maintaining corneal homeostasis. We have recently shown that a peptide designed from the 13 C-terminal amino acids of lumican (LumC13) binds to ALK5/TGFBR1 (type1 receptor of TGFβ) to promote wound healing. Herein we evaluate the mechanism by which this synthetic C-terminal amphiphilic peptide (LumC13), binds to ALK5. These studies clearly reveal that LumC13-ALK5 form a stable complex. In order to determine the minimal amino acids required for the formation of a stable lumican/ALK5 complex derivatives of LumC13 were designed and their binding to ALK5 investigated in silico. These LumC13 derivatives were tested both in vitro and in vivo to evaluate their ability to promote corneal epithelial cell migration and corneal wound healing, respectively. These validations add to the therapeutic value of LumC13 (Lumikine) and aid its clinical relevance of promoting the healing of corneal epithelium debridement. Moreover, our data validates the efficacy of our computational approach to design active peptides based on interactions of receptor and chemokine/ligand.

The Current State of NAD+ -Dependent Histone Deacetylases (Sirtuins) as Novel Therapeutic Targets

Sirtuins are NAD⁺ -dependent protein deacylases that cleave off acetyl, as well as other acyl groups, from the ε-amino group of lysines in histones and other substrate proteins. Seven sirtuin isotypes (Sirt1-7) have been identified in mammalian cells. As sirtuins are involved in the regulation of various physiological processes such as cell survival, cell cycle progression, apoptosis, DNA repair, cell metabolism, and caloric restriction, a dysregulation of their enzymatic activity has been associated with the pathogenesis of neoplastic, metabolic, infectious, and neurodegenerative diseases. Thus, sirtuins are promising targets for pharmaceutical intervention. Growing interest in a modulation of sirtuin activity has prompted the discovery of several small molecules, able to inhibit or activate certain sirtuin isotypes. Herein, we give an update to our previous review on the topic in this journal (Schemies, 2010), focusing on recent developments in sirtuin biology, sirtuin modulators, and their potential as novel therapeutic agents.

Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies

HIGHLIGHTS

Many CNS targets are being explored for multi-target drug design

New databases and cheminformatic methods enable prediction of primary pharmaceutical target and off-targets of compounds

QSAR, virtual screening and docking methods increase the potential of rational drug design

The diverse cerebral mechanisms implicated in Central Nervous System (CNS) diseases together with the heterogeneous and overlapping nature of phenotypes indicated that multitarget strategies may be appropriate for the improved treatment of complex brain diseases. Understanding how the neurotransmitter systems interact is also important in optimizing therapeutic strategies. Pharmacological intervention on one target will often influence another one, such as the well-established serotonin-dopamine interaction or the dopamine-glutamate interaction. It is now accepted that drug action can involve plural targets and that polypharmacological interaction with multiple targets, to address disease in more subtle and effective ways, is a key concept for development of novel drug candidates against complex CNS diseases. A multi-target therapeutic strategy for Alzheimer‘s disease resulted in the development of very effective Multi-Target Designed Ligands (MTDL) that act on both the cholinergic and monoaminergic systems, and also retard the progression of neurodegeneration by inhibiting amyloid aggregation. Many compounds already in databases have been investigated as ligands for multiple targets in drug-discovery programs. A probabilistic method, the Parzen-Rosenblatt Window approach, was used to build a “predictor” model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. Based on all these findings, it is concluded that multipotent ligands targeting AChE/MAO-A/MAO-B and also D₁-R/D₂-R/5-HT_2A-R/H₃-R are promising novel drug candidates with improved efficacy and beneficial neuroleptic and procognitive activities in treatment of Alzheimer's and related neurodegenerative diseases. Structural information for drug targets permits docking and virtual screening and exploration of the molecular determinants of binding, hence facilitating the design of multi-targeted drugs. The crystal structures and models of enzymes of the monoaminergic and cholinergic systems have been used to investigate the structural origins of target selectivity and to identify molecular determinants, in order to design MTDLs.

Structure-Based Design of Peptidic Inhibitors of the Interaction between CC Chemokine Ligand 5 (CCL5) and Human Neutrophil Peptides 1 (HNP1)

Protein-protein interactions (PPIs) are receiving increasing interest, much sparked by the realization that they represent druggable targets. Recently, we successfully developed a peptidic inhibitor, RRYGTSKYQ ("SKY" peptide), that shows high potential in vitro and in vivo to interrupt a PPI between the platelet-borne chemokine CCL5 and the neutrophil-derived granule protein HNP1. This PPI plays a vital role in monocyte adhesion, representing a key mechanism in acute and chronic inflammatory diseases. Here, we present extensive and detailed computational methods applied to develop the SKY peptide. We combined experimentally determined binding affinities (KD) of several orthologs of CCL5 with HNP1 with in silico studies to identify the most likely heterodimeric CCL5-HNP1 complex which was subsequently used as a starting structure to rationally design peptidic inhibitors. Our method represents a fast and simple approach that can be widely applied to determine other protein-protein complexes and moreover to design inhibitors or stabilizers of protein-protein interaction.

5-Benzylidene-hydantoin is a new scaffold for SIRT inhibition: From virtual screening to activity assays

Sirtuins (SIRTs) are a family of enzymes able to catalyze the deacetylation of the N-acetyl lysines of both histone and non-histone substrates. Inhibition of SIRTs catalytic activity was recently reported in the literature as being beneficial in human diseases, with very promising applications in cancer therapy and enzymatic neurodegeneration. By combining a structure-based virtual screening of the Specs database with cell-based assays, we identified the 5-benzylidene-hydantoin as new scaffold for the inhibition of SIRT2 catalytic activity. Compound 97 (Specs ID AH-487/41657829), active in the low μM range against SIRT2, showed the optimal physicochemical properties for passive absorption as well as relatively low cytotoxicity in vitro. Further studies revealed non-competitive and mixed-type kinetics toward acetyl-lysine substrates and NAD(+), respectively, and a non-selective profile for SIRT inhibition. A binding mode consistent with the experimental evidence was proposed by molecular modeling. Additionally, the levels of acetyl-p53 were shown to be increased in HeLa cells treated with 97. Taken together, these results encourage further investigation of 5-benzylidene-hydantoin derivatives for their SIRT-related therapeutic effects.