Rigorous Computational Study Reveals What Docking Overlooks: Double Trouble from Membrane Association in Protein Kinase C Modulators

Insertion Depth Modulates Protein Kinase C-δ-C1b Domain Interactions with Membrane Cholesterol as Revealed by MD Simulations

Protein kinase C delta (PKC-δ) is an important signaling molecule in human cells that has both proapoptotic as well as antiapoptotic functions. These conflicting activities can be modulated by two classes of ligands, phorbol esters and bryostatins. Phorbol esters are known tumor promoters, while bryostatins have anti-cancer properties. This is despite both ligands binding to the C1b domain of PKC-δ (δC1b) with a similar affinity. The molecular mechanism behind this discrepancy in cellular effects remains unknown. Here, we have used molecular dynamics simulations to investigate the structure and intermolecular interactions of these ligands bound to δC1b with heterogeneous membranes. We observed clear interactions between the δC1b-phorbol complex and membrane cholesterol, primarily through the backbone amide of L250 and through the K256 side-chain amine. In contrast, the δC1b-bryostatin complex did not exhibit interactions with cholesterol. Topological maps of the membrane insertion depth of the δC1b-ligand complexes suggest that insertion depth can modulate δC1b interactions with cholesterol. The lack of cholesterol interactions suggests that bryostatin-bound δC1b may not readily translocate to cholesterol-rich domains within the plasma membrane, which could significantly alter the substrate specificity of PKC-δ compared to δC1b-phorbol complexes.

Insights into the behavior of unsaturated diacylglycerols in mixed lipid bilayers in relation to protein kinase C activation-A molecular dynamics simulation study

The lipid second messenger diacylglycerol (DAG) is known for its involvement in many types of cellular signaling, especially as an endogenous agonist for protein kinase C (PKC). Evidence has emerged that the degree of saturation of the DAG molecules can affect PKC activation. DAG molecules with different acyl chain saturation have not only been observed to induce varying extents of PKC activation, but also to express selectivity towards different PKC isozymes. Both qualities are important for precise therapeutic activation of PKC; understanding DAG behavior at the molecular level in different environments has much potential in the development of drugs to target PKC. We used molecular dynamics simulations to study the behavior of two different unsaturated DAG species in lipid environments with varying degrees of unsaturation. We focus on phosphatidylethanolamine (PE) instead of phosphatidylcholine (PC) to more accurately model the relevant biomembranes. The effect of cholesterol (CHOL) on these systems was also explored. We found that both high level of unsaturation in the acyl chains of the DAG species and presence of CHOL in the surrounding membrane increase DAG molecule availability at the lipid-water interface. This can partially explain the previously observed differences in PKC activation strength and specificity, the complete mechanism is, however, likely to be more complex. Our simulations coupled with the current understanding of lipids highlight the need for more simulations of biologically accurate lipid environments in order to determine the correct correlations between molecular mechanisms and biological behavior when studying PKC activation.

Mechanistic Understanding from Molecular Dynamics in Pharmaceutical Research 2: Lipid Membrane in Drug Design

We review the use of molecular dynamics (MD) simulation as a drug design tool in the context of the role that the lipid membrane can play in drug action, i.e., the interaction between candidate drug molecules and lipid membranes. In the standard "lock and key" paradigm, only the interaction between the drug and a specific active site of a specific protein is considered; the environment in which the drug acts is, from a biophysical perspective, far more complex than this. The possible mechanisms though which a drug can be designed to tinker with physiological processes are significantly broader than merely fitting to a single active site of a single protein. In this paper, we focus on the role of the lipid membrane, arguably the most important element outside the proteins themselves, as a case study. We discuss work that has been carried out, using MD simulation, concerning the transfection of drugs through membranes that act as biological barriers in the path of the drugs, the behavior of drug molecules within membranes, how their collective behavior can affect the structure and properties of the membrane and, finally, the role lipid membranes, to which the vast majority of drug target proteins are associated, can play in mediating the interaction between drug and target protein. This review paper is the second in a two-part series covering MD simulation as a tool in pharmaceutical research; both are designed as pedagogical review papers aimed at both pharmaceutical scientists interested in exploring how the tool of MD simulation can be applied to their research and computational scientists interested in exploring the possibility of a pharmaceutical context for their research.

Structural insights into C1-ligand interactions: Filling the gaps by in silico methods

Protein Kinase C isoenzymes (PKCs) are the key mediators of the phosphoinositide signaling pathway, which involves regulated hydrolysis of phosphatidylinositol (4,5)-bisphosphate to diacylglycerol (DAG) and inositol-1,4,5-trisphosphate. Dysregulation of PKCs is implicated in many human diseases making this class of enzymes an important therapeutic target. Specifically, the DAG-sensing cysteine-rich conserved homology-1 (C1) domains of PKCs have emerged as promising targets for pharmaceutical modulation. Despite significant progress, the rational design of the C1 modulators remains challenging due to difficulties associated with structure determination of the C1-ligand complexes. Given the dearth of experimental structural data, computationally derived models have been instrumental in providing atomistic insight into the interactions of the C1 domains with PKC agonists. In this review, we provide an overview of the in silico approaches for seven classes of C1 modulators and outline promising future directions.