A molecular dynamics investigation of CDK8/CycC and ligand binding: conformational flexibility and implication in drug discovery

Enriching Anticancer Drug Pipeline with Potential Inhibitors of Cyclin-Dependent Kinase-8 Identified from Natural Products

Cyclin-dependent kinase 8 (CDK8) is highly expressed in various cancers and common complex human diseases, and an important therapeutic target for drug discovery and development. The CDK8 inhibitors are actively sought after, especially among natural products. We performed a virtual screening using the ZINC library comprising approximately 90,000 natural compounds. We applied Lipinski's rule of five, absorption, distribution, metabolism, excretion, and toxicity properties, and pan-assay interference compounds filter to eliminate promiscuous binders. Subsequently, the filtered compounds underwent molecular docking to predict their binding affinity and interactions with the CDK8 protein. Interaction analysis were carried out to elucidate the interaction mechanism of the screened hits with binding pockets of the CDK8. The ZINC02152165, ZINC04236005, and ZINC02134595 were selected with appreciable specificity and affinity with CDK8. An all-atom molecular dynamic (MD) simulation followed by essential dynamics was performed for 200 ns. Taken together, the results suggest that ZINC02152165, ZINC04236005, and ZINC02134595 can be harnessed as potential leads in therapeutic development. Moreover, the binding of the molecules brings change in protein conformation in a way that blocks the ATP-binding site of the protein, obstructing its kinase activity. These new findings from natural products offer insights into the molecular mechanisms underlying CDK8 inhibition. CDK8 was previously associated with behavioral and neurological diseases such as autism spectrum disorder, and cancers, for example, colorectal, prostate, breast, and acute myeloid leukemia. Hence, we call for further research and experimental validation, and with an eye to inform future clinical drug discovery and development in these therapeutic fields.

Systematic computational strategies for identifying protein targets and lead discovery

Computational algorithms and tools have retrenched the drug discovery and development timeline. The applicability of computational approaches has gained immense relevance owing to the dramatic surge in the structural information of biomacromolecules and their heteromolecular complexes. Computational methods are now extensively used in identifying new protein targets, druggability assessment, pharmacophore mapping, molecular docking, the virtual screening of lead molecules, bioactivity prediction, molecular dynamics of protein-ligand complexes, affinity prediction, and for designing better ligands. Herein, we provide an overview of salient components of recently reported computational drug-discovery workflows that includes algorithms, tools, and databases for protein target identification and optimized ligand selection.

Highlighting the Major Role of Cyclin C in Cyclin-Dependent Kinase 8 Activity through Molecular Dynamics Simulations

Dysregulation of cyclin-dependent kinase 8 (CDK8) activity has been associated with many diseases, including colorectal and breast cancer. As usual in the CDK family, the activity of CDK8 is controlled by a regulatory protein called cyclin C (CycC). But, while human CDK family members are generally activated in two steps, that is, the binding of the cyclin to CDK and the phosphorylation of a residue in the CDK activation loop, CDK8 does not require the phosphorylation step to be active. Another peculiarity of CDK8 is its ability to be associated with CycC while adopting an inactive form. These specificities raise the question of the role of CycC in the complex CDK8-CycC, which appears to be more complex than the other members of the CDK family. Through molecular dynamics (MD) simulations and binding free energy calculations, we investigated the effect of CycC on the structure and dynamics of CDK8. In a second step, we particularly focused our investigation on the structural and molecular basis of the protein-protein interaction between the two partners by finely analyzing the energetic contribution of residues and simulating the transition between the active and the inactive form. We found that CycC has a stabilizing effect on CDK8, and we identified specific interaction hotspots within its interaction surface compared to other human CDK/Cyc pairs. Targeting these specific interaction hotspots could be a promising approach in terms of specificity to effectively disrupt the interaction between CDK8. The simulation of the conformational transition from the inactive to the active form of CDK8 suggests that the residue Glu99 of CycC is involved in the orientation of three conserved arginines of CDK8. Thus, this residue may assume the role of the missing phosphorylation step in the activation mechanism of CDK8. In a more general view, these results point to the importance of keeping the CycC in computational studies when studying the human CDK8 protein in both the active and the inactive form.

Computational Exploration of Anti-cancer Potential of Flavonoids against Cyclin-Dependent Kinase 8: An In Silico Molecular Docking and Dynamic Approach

Over the centuries, cancer has been considered one of the significant health threats. It holds the position in the list of deadliest diseases over the globe. In women, breast cancer is the most common among many cancers and is the second most common cancer all over the world, while lung cancer is the first. Cyclin-dependent kinase 8 (CDK8) has been identified as a critical oncogenic driver that is found in breast cancer and associated with tumor progression. Flavonoids were virtually screened against CDK8 using molecular docking, drug-likeness, ADMET prediction, and a molecular dynamics (MD) simulation approach to determine the potential flavonoid structure against CDK8. The results indicated that ZINC000005854718 showed the highest negative binding affinity of -10.7 kcal/mol with the targeted protein and passed all the drug-likeness parameters. Performed molecular dynamics simulation showed that docked complex systems have good conformational stability over 100 ns in different temperatures (298, 300, 305, 310, and 320 K). The comparison between calculated binding free energy via MM/PB(GB)SA methods and binding affinity calculated via molecular docking suggested tight binding of ZINC000005854718 with targeted protein. The results concluded that ZINC000005854718 has drug-like properties with tight and stable binding with the targeted protein.

Estimation of Drug-Target Residence Time by Targeted Molecular Dynamics Simulations

Drug-target residence time has emerged as a key selection factor in drug discovery since the binding duration of a drug molecule to its protein target can significantly impact its in vivo efficacy. The challenge in studying the residence time, in early drug discovery stages, lies in how to cost-effectively determine the residence time for the systematic assessment of compounds. Currently, there is still a lack of computational protocols to quickly estimate such a measure, particularly for large and flexible protein targets and drugs. Here, we report an efficient computational protocol, based on targeted molecular dynamics, to rank drug candidates by their residence time and to obtain insights into ligand-target dissociation mechanisms. The method was assessed on a dataset of 10 arylpyrazole inhibitors of CDK8, a large, flexible, and clinically important target, for which the experimental residence time of the inhibitors ranges from minutes to hours. The compounds were correctly ranked according to their estimated residence time scores compared to their experimental values. The analysis of protein-ligand interactions along the dissociation trajectories highlighted the favorable contribution of hydrophobic contacts to residence time and revealed key residues that strongly affect compound residence time.

From Data to Knowledge: Systematic Review of Tools for Automatic Analysis of Molecular Dynamics Output

An increasing number of crystal structures available on one side, and the boost of computational power available for computer-aided drug design tasks on the other, have caused that the structure-based drug design tools are intensively used in the drug development pipelines. Docking and molecular dynamics simulations, key representatives of the structure-based approaches, provide detailed information about the potential interaction of a ligand with a target receptor. However, at the same time, they require a three-dimensional structure of a protein and a relatively high amount of computational resources. Nowadays, as both docking and molecular dynamics are much more extensively used, the amount of data output from these procedures is also growing. Therefore, there are also more and more approaches that facilitate the analysis and interpretation of the results of structure-based tools. In this review, we will comprehensively summarize approaches for handling molecular dynamics simulations output. It will cover both statistical and machine-learning-based tools, as well as various forms of depiction of molecular dynamics output.

Molecular Structure-Based Screening of the Constituents of Calotropis procera Identifies Potential Inhibitors of Diabetes Mellitus Target Alpha Glucosidase

Diabetes mellitus is a disorder characterized by higher levels of blood glucose due to impaired insulin mechanisms. Alpha glucosidase is a critical drug target implicated in the mechanisms of diabetes mellitus and its inhibition controls hyperglycemia. Since the existing standard synthetic drugs have therapeutic limitations, it is imperative to identify new potent inhibitors of natural product origin which may slow carbohydrate digestion and absorption via alpha glucosidase. Since plant extracts from Calotropis procera have been extensively used in the treatment of diabetes mellitus, the present study used molecular docking and dynamics simulation techniques to screen its constituents against the receptor alpha glucosidase. Taraxasterol, syriogenin, isorhamnetin-3-O-robinobioside and calotoxin were identified as potential novel lead compounds with plausible binding energies of −40.2, −35.1, −34.3 and −34.3 kJ/mol against alpha glucosidase, respectively. The residues Trp⁴⁸¹, Asp⁵¹⁸, Leu⁶⁷⁷, Leu⁶⁷⁸ and Leu⁶⁸⁰ were identified as critical for binding and the compounds were predicted as alpha glucosidase inhibitors. Structurally similar compounds with Tanimoto coefficients greater than 0.7 were reported experimentally to be inhibitors of alpha glucosidase or antidiabetic. The structures of the molecules may serve as templates for the design of novel inhibitors and warrant in vitro assaying to corroborate their antidiabetic potential.

Angel or Devil ? - CDK8 as the new drug target

Cyclin-dependent kinase 8 (CDK8) plays an momentous role in transcription regulation by forming kinase module or transcription factor phosphorylation. A large number of evidences have identified CDK8 as an important factor in cancer occurrence and development. In addition, CDK8 also participates in the regulation of cancer cell stress response to radiotherapy and chemotherapy, assists tumor cell invasion, metastasis, and drug resistance. Therefore, CDK8 is regarded as a promising target for cancer therapy. Most studies in recent years supported the role of CDK8 as a carcinogen, however, under certain conditions, CDK8 exists as a tumor suppressor. The functional diversity of CDK8 and its exceptional role in different types of cancer have aroused great interest from scientists but even more controversy during the discovery of CDK8 inhibitors. In addition, CDK8 appears to be an effective target for inflammation diseases and immune system disorders. Therefore, we summarized the research results of CDK8, involving physiological/pathogenic mechanisms and the development status of compounds targeting CDK8, provide a reference for the feasibility evaluation of CDK8 as a therapeutic target, and guidance for researchers who are involved in this field for the first time.

Chatterboxes: the structural and functional diversity of cyclins

Proteins of the cyclin family have divergent sequences and execute diverse roles within the cell while sharing a common fold: the cyclin box domain. Structural studies of cyclins have played a key role in our characterization and understanding of cellular processes that they control, though to date only ten of the 29 CDK-activating cyclins have been structurally characterized by X-ray crystallography or cryo-electron microscopy with or without their cognate kinases. In this review, we survey the available structures of human cyclins, highlighting their molecular features in the context of their cellular roles. We pay particular attention to how cyclin activity is regulated through fine control of degradation motif recognition and ubiquitination. Finally, we discuss the emergent roles of cyclins independent of their roles as cyclin-dependent protein kinase activators, demonstrating the cyclin box domain to be a versatile and generalized scaffolding domain for protein-protein interactions across the cellular machinery.

Transient States and Barriers from Molecular Simulations and the Milestoning Theory: Kinetics in Ligand-Protein Recognition and Compound Design

This study presents a novel computational approach to study molecular recognition and binding kinetics for drug-like compounds dissociating from a flexible protein system. The intermediates and their free energy profile during ligand association and dissociation processes control ligand-protein binding kinetics and bring a more complete picture of ligand-protein binding. The method applied the milestoning theory to extract kinetics and thermodynamics information from running short classical molecular dynamics (MD) simulations for frames from a given dissociation path. High-dimensional ligand-protein motions (3N-6 degrees of freedom) during ligand dissociation were reduced by use of principal component modes for assigning more than 100 milestones, and classical MD runs were allowed to travel multiple milestones to efficiently obtain ensemble distribution of initial structures for MD simulations and estimate the transition time and rate during ligand traveling between milestones. We used five pyrazolourea ligands and cyclin-dependent kinase 8 with cyclin C (CDK8/CycC) as our model system as well as metadynamics and a pathway search method to sample dissociation pathways. With our strategy, we constructed the free energy profile for highly mobile biomolecular systems. The computed binding free energy and residence time correctly ranked the pyrazolourea ligand series, in agreement with experimental data. Guided by a barrier of a ligand passing an αC helix and activation loop, we introduced one hydroxyl group to parent compounds to design our ligands with increased residence time and validated our prediction by experiments. This work provides a novel and robust approach to investigate dissociation kinetics of large and flexible systems for understanding unbinding mechanisms and designing new small-molecule drugs with desired binding kinetics.

De Novo Missense Substitutions in the Gene Encoding CDK8, a Regulator of the Mediator Complex, Cause a Syndromic Developmental Disorder

The Mediator is an evolutionarily conserved, multi-subunit complex that regulates multiple steps of transcription. Mediator activity is regulated by the reversible association of a four-subunit module comprising CDK8 or CDK19 kinases, together with cyclin C, MED12 or MED12L, and MED13 or MED13L. Mutations in MED12, MED13, and MED13L were previously identified in syndromic developmental disorders with overlapping phenotypes. Here, we report CDK8 mutations (located at 13q12.13) that cause a phenotypically related disorder. Using whole-exome or whole-genome sequencing, and by international collaboration, we identified eight different heterozygous missense CDK8 substitutions, including 10 shown to have arisen de novo, in 12 unrelated subjects; a recurrent mutation, c.185C>T (p.Ser62Leu), was present in five individuals. All predicted substitutions localize to the ATP-binding pocket of the kinase domain. Affected individuals have overlapping phenotypes characterized by hypotonia, mild to moderate intellectual disability, behavioral disorders, and variable facial dysmorphism. Congenital heart disease occurred in six subjects; additional features present in multiple individuals included agenesis of the corpus callosum, ano-rectal malformations, seizures, and hearing or visual impairments. To evaluate the functional impact of the mutations, we measured phosphorylation at STAT1-Ser727, a known CDK8 substrate, in a CDK8 and CDK19 CRISPR double-knockout cell line transfected with wild-type (WT) or mutant CDK8 constructs. These experiments demonstrated a reduction in STAT1 phosphorylation by all mutants, in most cases to a similar extent as in a kinase-dead control. We conclude that missense mutations in CDK8 cause a developmental disorder that has phenotypic similarity to syndromes associated with mutations in other subunits of the Mediator kinase module, indicating probable overlap in pathogenic mechanisms.

Discovery of CDK8/CycC Ligands with a New Virtual Screening Tool

Selective inhibition of cyclin-dependent kinase 8 and cyclin C (CDK8/CycC) has been suggested as a promising strategy for decreasing mitogenic signals in cancer cells with reduced toxicity toward normal cells. We developed a novel virtual screening protocol for drug development and applied it to the discovery of new CDK8/CycC type II ligands, which is likely to achieve long residence time and specificity. We first analyzed the binding thermodynamics of 11 published pyrazolourea ligands using molecular dynamics simulations and a free-energy calculation method, VM2, and extracted the key binding information to assist virtual screening. The urea moiety was found to be the critical structural contributor of the reference ligands. Starting with the urea moiety, we conducted substructure-based searches with our newly developed superposition and single-point energy evaluation method, followed by free-energy calculations, and singled out three purchasable compounds for bioassay testing. The ranking from the experimental results is completely consistent with the predicted rankings. A potent drug-like compound was found to have a K_d value of 42.5 nm, which is similar to those of the most potent reference ligands; this provided a good starting point for further improvement. This study shows that our novel virtual screening protocol is an accurate and efficient tool for drug development.