Advanced molecular dynamics simulation methods for kinase drug discovery

Identification of Potent ADCK3 Inhibitors through Structure-Based Virtual Screening

ADCK3 is a member of the UbiB family of atypical protein kinases in humans, with homologues in archaea, bacteria, and eukaryotes. In lieu of protein kinase activity, ADCK3 plays a role in the biosynthesis of coenzyme Q10 (CoQ10), and inactivating mutations can cause a CoQ10 deficiency and ataxia. However, the exact functions of ADCK3 are still unclear, and small-molecule inhibitors could be useful as chemical probes to elucidate its molecular mechanisms. In this study, we applied structure-based virtual screening (VS) to discover a novel chemical series of ADCK3 inhibitors. Through extensive structural analysis of the active-site residues, we developed a pharmacophore model and applied it to a large-scale VS. Out of ∼170,000 compounds virtually screened, 800 top-ranking candidate compounds were selected and tested in both ADCK3 and p38 biochemical assays for hit validation. In total, 129 compounds were confirmed as ADCK3 inhibitors, and among them, 114 compounds are selective against p38, which was used as a counter-target. Molecular dynamics (MD) simulations were then conducted to predict the binding modes of the most potent compounds within the ADCK3 active site. Through metadynamics analysis, we successfully detected the key amino acid residues that govern intermolecular interactions. The findings provided in this study can serve as a promising starting point for drug development.

Interactions between curcumin and human salt-induced kinase 3 elucidated from computational tools and experimental methods

Natural products are widely used for treating mitochondrial dysfunction-related diseases and cancers. Curcumin, a well-known natural product, can be potentially used to treat cancer. Human salt-induced kinase 3 (SIK3) is one of the target proteins for curcumin. However, the interactions between curcumin and human SIK3 have not yet been investigated in detail. In this study, we studied the binding models for the interactions between curcumin and human SIK3 using computational tools such as homology modeling, molecular docking, molecular dynamics simulations, and binding free energy calculations. The open activity loop conformation of SIK3 with the ketoenol form of curcumin was the optimal binding model. The I72, V80, A93, Y144, A145, and L195 residues played a key role for curcumin binding with human SIK3. The interactions between curcumin and human SIK3 were also investigated using the kinase assay. Moreover, curcumin exhibited an IC₅₀ (half-maximal inhibitory concentration) value of 131 nM, and it showed significant antiproliferative activities of 9.62 ± 0.33 µM and 72.37 ± 0.37 µM against the MCF-7 and MDA-MB-23 cell lines, respectively. This study provides detailed information on the binding of curcumin with human SIK3 and may facilitate the design of novel salt-inducible kinases inhibitors.

Identification of novel inhibitors of S-adenosyl-L-homocysteine hydrolase via structure-based virtual screening and molecular dynamics simulations

S-adenosyl-L-homocysteine hydrolase (SAHase) is an important regulator in the methylation reactions in many organisms and thus is crucial for numerous cellular functions. In recent years, SAHase has become one of the popular targets for drug design, and SAHase inhibitors have exhibited potent antiviral activity. In this study, we established the complex-based pharmacophore models based on the known crystal complex of SAHase (PDB ID: 1A7A) to screen the drug-likeness compounds of ChEMBL database. Then, three molecular docking programs were used to validate the reliability of compounds, involving Libdock, CDOCKER, and AutoDock Vina programs. The four promising hit compounds (CHEMBL420751, CHEMBL346387, CHEMBL1569958, and CHEMBL4206648) were performed molecular dynamics simulations and MM-PBSA calculations to evaluate their stability and binding-free energy in the binding site of SAHase. After screening and analyzing, the hit compounds CHEMBL420751 and CHEMBL346387 were suggested to further research to obtain novel potential SAHase inhibitors. A series of computer-aided drug design methods, including pharmacophore, molecular docking, molecular dynamics simulation and MM-PBSA calculations, were employed in this study to identity novel inhibitors of S-adenosyl-L-homocysteine hydrolase (SAHase). Some compounds from virtual screening could form various interactions with key residues of SAHase. Among them, compounds CHEMBL346387 and CHEMBL420751 exhibited potent binding affinity from molecular docking and MM-PBSA, and maintained good stability at the binding site during molecular dynamics simulations as well. All these results indicated that the selected compounds might have the potential to be novel SAHase inhibitors.

Exercise improves choroid plexus epithelial cells metabolism to prevent glial cell-associated neurodegeneration

Recent studies have shown that physical activities can prevent aging-related neurodegeneration. Exercise improves the metabolic landscape of the body. However, the role of these differential metabolites in preventing neurovascular unit degeneration (NVU) is still unclear. Here, we performed single-cell analysis of brain tissue from young and old mice. Normalized mutual information (NMI) was used to measure heterogeneity between each pair of cells using the non-negative Matrix Factorization (NMF) method. Astrocytes and choroid plexus epithelial cells (CPC), two types of CNS glial cells, differed significantly in heterogeneity depending on their aging status and intercellular interactions. The MetaboAnalyst 5.0 database and the scMetabolism package were used to analyze and calculate the differential metabolic pathways associated with aging in the CPC. These mRNAs and corresponding proteins were involved in the metabolites (R)-3-Hydroxybutyric acid, 2-Hydroxyglutarate, 2-Ketobutyric acid, 3-Hydroxyanthranilic acid, Fumaric acid, L-Leucine, and Oxidized glutathione pathways in CPC. Our results showed that CPC age heterogeneity-associated proteins (ECHS1, GSTT1, HSD17B10, LDHA, and LDHB) might be directly targeted by the metabolite of oxidized glutathione (GSSG). Further molecular dynamics and free-energy simulations confirmed the insight into GSSG's targeting function and free-energy barrier on these CPC age heterogeneity-associated proteins. By inhibiting these proteins in CPC, GSSG inhibits brain energy metabolism, whereas exercise improves the metabolic pathway activity of CPC in NVU by regulating GSSG homeostasis. In order to develop drugs targeting neurodegenerative diseases, further studies are needed to understand how physical exercise enhances NVU function and metabolism by modulating CPC-glial cell interactions.

Clostridial Neurotoxins: Structure, Function and Implications to Other Bacterial Toxins

Gram-positive bacteria are ancient organisms. Many bacteria, including Gram-positive bacteria, produce toxins to manipulate the host, leading to various diseases. While the targets of Gram-positive bacterial toxins are diverse, many of those toxins use a similar mechanism to invade host cells and exert their functions. Clostridial neurotoxins produced by Clostridial tetani and Clostridial botulinum provide a classical example to illustrate the structure-function relationship of bacterial toxins. Here, we critically review the recent progress of the structure-function relationship of clostridial neurotoxins, including the diversity of the clostridial neurotoxins, the mode of actions, and the flexible structures required for the activation of toxins. The mechanism clostridial neurotoxins use for triggering their activity is shared with many other Gram-positive bacterial toxins, especially molten globule-type structures. This review also summarizes the implications of the molten globule-type flexible structures to other Gram-positive bacterial toxins. Understanding these highly dynamic flexible structures in solution and their role in the function of bacterial toxins not only fills in the missing link of the high-resolution structures from X-ray crystallography but also provides vital information for better designing antidotes against those toxins.

Chemical Probes for Understudied Kinases: Challenges and Opportunities

Over 20 years after the approval of the first-in-class protein kinase inhibitor imatinib, the biological function of a significant fraction of the human kinome remains poorly understood while most research continues to be focused on few well-validated targets. Given the strong genetic evidence for involvement of many kinases in health and disease, the understudied fraction of the kinome holds a large and unexplored potential for future therapies. Specific chemical probes are indispensable tools to interrogate biology enabling proper preclinical validation of novel kinase targets. In this Perspective, we highlight recent case studies illustrating the development of high-quality chemical probes for less-studied kinases and their application in target validation. We spotlight emerging techniques and approaches employed in the generation of chemical probes for protein kinases and beyond and discuss the associated challenges and opportunities.

Preliminary modelling as the first stage of targeted organic synthesis

The review aims to present a classification and applicability analysis of methods for preliminary molecular modelling for targeted organic, catalytic and biocatalytic synthesis. The following three main approaches are considered as a primary classification of the methods: modelling of the target – ligand coordination without structural information on both the target and the resulting complex; calculations based on experimentally obtained structural information about the target; and dynamic simulation of the target – ligand complex and the reaction mechanism with calculation of the free energy of the reaction. The review is meant for synthetic chemists to be used as a guide for building an algorithm for preliminary modelling and synthesis of structures with specified properties.

The bibliography includes 353 references.

Molecular Dynamics Simulations in Designing DARPins as Phosphorylation-Specific Protein Binders of ERK2

Extracellular signal-regulated kinases 1 and 2 (ERK1/2) play key roles in promoting cell survival and proliferation through the phosphorylation of various substrates. Remarkable antitumour activity is found in many inhibitors that act upstream of the ERK pathway. However, drug-resistant tumour cells invariably emerge after their use due to the reactivation of ERK1/2 signalling. ERK1/2 inhibitors have shown clinical efficacy as a therapeutic strategy for the treatment of tumours with mitogen-activated protein kinase (MAPK) upstream target mutations. These inhibitors may be used as a possible strategy to overcome acquired resistance to MAPK inhibitors. Here, we report a class of repeat proteins-designed ankyrin repeat protein (DARPin) macromolecules targeting ERK2 as inhibitors. The structural basis of ERK2-DARPin interactions based on molecular dynamics (MD) simulations was studied. The information was then used to predict stabilizing mutations employing a web-based algorithm, MAESTRO. To evaluate whether these design strategies were successfully deployed, we performed all-atom, explicit-solvent molecular dynamics (MD) simulations. Two mutations, Ala → Asp and Ser → Leu, were found to perform better than the original sequence (DARPin E40) based on the associated energy and key residues involved in protein-protein interaction. MD simulations and analysis of the data obtained on these mutations supported our predictions.

The QSAR Paradigm in Fragment-Based Drug Discovery: From the Virtual Generation of Target Inhibitors to Multi-Scale Modeling

Fragment-Based Drug Design (FBDD) has established itself as a promising approach in modern drug discovery, accelerating and improving lead optimization, while playing a crucial role in diminishing the high attrition rates at all stages in the drug development process. On the other hand, FBDD has benefited from the application of computational methodologies, where the models derived from the Quantitative Structure-Activity Relationships (QSAR) have become consolidated tools. This mini-review focuses on the evolution and main applications of the QSAR paradigm in the context of FBDD in the last five years. This report places particular emphasis on the QSAR models derived from fragment-based topological approaches to extract physicochemical and/or structural information, allowing to design potentially novel mono- or multi-target inhibitors from relatively large and heterogeneous databases. Here, we also discuss the need to apply multi-scale modeling, to exemplify how different datasets based on target inhibition can be simultaneously integrated and predicted together with other relevant endpoints such as the biological activity against non-biomolecular targets, as well as in vitro and in vivo toxicity and pharmacokinetic properties. In this context, seminal papers are briefly analyzed. As huge amounts of data continue to accumulate in the domains of the chemical, biological and biomedical sciences, it has become clear that drug discovery must be viewed as a multi-scale optimization process. An ideal multi-scale approach should integrate diverse chemical and biological data and also serve as a knowledge generator, enabling the design of potentially optimal chemicals that may become therapeutic agents.

Dasatinib-SIK2 Binding Elucidated by Homology Modeling, Molecular Docking, and Dynamics Simulations

Salt-inducible kinases (SIKs) are calcium/calmodulin-dependent protein kinase (CAMK)-like (CAMKL) family members implicated in insulin signal transduction, metabolic regulation, inflammatory response, and other processes. Here, we focused on SIK2, which is a target of the Food and Drug Administration (FDA)-approved pan inhibitor N-(2-chloro-6-methylphenyl)-2-(6-(4-(2-hydroxyethyl)piperazin-1-yl)-2-methylpyrimidin-4-ylamino)thiazole-5-carboxamide (dasatinib), and constructed four representative SIK2 structures by homology modeling. We investigated the interactions between dasatinib and SIK2 via molecular docking, molecular dynamics simulation, and binding free energy calculation and found that dasatinib showed strong binding affinity for SIK2. Binding free energy calculations suggested that the modification of various dasatinib regions may provide useful information for drug design and to guide the discovery of novel dasatinib-based SIK2 inhibitors.

Molecular Simulation Elaborating the Mechanism of 1β-Hydroxy Alantolactone Inhibiting Ubiquitin-Conjugating Enzyme UbcH5s

1β-hydroxy alantolactone, a sesquiterpene lactone, exhibits potent anti-inflammatory and anticancer activities. Recently, it has been found to target UbcH5s by covalently bonding with Cys85 specifically, but the exact molecular basis remains unclear. Here, we analyzed the structural specificity of the catalytic site of UbcH5s by comparing them with other E2 proteins. Molecular dynamics was performed to detect the structural stability of the catalytic site. Docking method was then used to predict conformations of ligand docked at the catalytic site of UbcH5s. The electrostatic surface and charge distribution of ligand and proteins were analyzed by quantitative calculation. Molecular dynamics was used to detect the stability of docking complexes of 1β-hydroxy alantolactone and UbcH5s, the covalently bonded intermediates and the products. The QM/MM methodology was used to calculate the free energy barrier of hydrogen transfer and formation of covalent bond between 15-position carbon of ligand and Cys85. Results revealed that the structure of the catalytic site is stable, and 1β-hydroxy alantolactone can dock at the catalytic site with correct conformation. Molecular dynamics further demonstrates that 1β-hydroxy alantolactone can steadily combine with UbcH5s. Intermediate and product of catalytic reaction are also certified to be stable. Besides, Asp112 and Asn114 function as anchors to fix ligand, ensuring it steadily docked at catalytic site to complete covalent reaction. More importantly, we have found that Cys85 of UbcH5c is more efficient to form a covalent bond with the ligand in comparison with UbcH5a and UbcH5b. Our results successfully explained the mechanism of 1β-hydroxy alantolactone covalently bonding with UbcH5s. Such molecular mechanism may provide a better insight into the molecular development or modification for ubiquitin-related drugs.

In silico Methods for Design of Kinase Inhibitors as Anticancer Drugs

Rational drug design implies usage of molecular modeling techniques such as pharmacophore modeling, molecular dynamics, virtual screening, and molecular docking to explain the activity of biomolecules, define molecular determinants for interaction with the drug target, and design more efficient drug candidates. Kinases play an essential role in cell function and therefore are extensively studied targets in drug design and discovery. Kinase inhibitors are clinically very important and widely used antineoplastic drugs. In this review, computational methods used in rational drug design of kinase inhibitors are discussed and compared, considering some representative case studies.

New approaches for computing ligand-receptor binding kinetics

The recent and growing evidence that the efficacy of a drug can be correlated to target binding kinetics has seeded the development of a multitude of novel methods aimed at computing rate constants for receptor-ligand binding processes, as well as gaining an understanding of the binding and unbinding pathways and the determinants of structure-kinetic relationships. These new approaches include various types of enhanced sampling molecular dynamics simulations and the combination of energy-based models with chemometric analysis. We assess these approaches in the light of the varying levels of complexity of protein-ligand binding processes.

Structural and Dynamic Insights into the Mechanism of Allosteric Signal Transmission in ERK2-Mediated MKP3 Activation

The mitogen-activated protein kinases (MAPKs) are key components of cellular signal transduction pathways, which are down-regulated by the MAPK phosphatases (MKPs). Catalytic activity of the MKPs is controlled both by their ability to recognize selective MAPKs and by allosteric activation upon binding to MAPK substrates. Here, we use a combination of experimental and computational techniques to elucidate the molecular mechanism for the ERK2-induced MKP3 activation. Mutational and kinetic study shows that the ³³⁴FNFM³³⁷ motif in the MKP3 catalytic domain is essential for MKP3-mediated ERK2 inactivation and is responsible for ERK2-mediated MKP3 activation. The long-term molecular dynamics (MD) simulations further reveal a complete dynamic process in which the catalytic domain of MKP3 gradually changes to a conformation that resembles an active MKP catalytic domain over the time scale of the simulation, providing a direct time-dependent observation of allosteric signal transmission in ERK2-induced MKP3 activation.