Docking and scoring: applications to drug discovery in the interactomics era

Pirfenidone Is an Agonistic Ligand for PPARα and Improves NASH by Activation of SIRT1/LKB1/pAMPK

Nonalcoholic steatohepatitis (NASH) is recognized by hepatic lipid accumulation, inflammation, and fibrosis. No studies have evaluated the prolonged‐release pirfenidone (PR‐PFD) properties on NASH features. The aim of this study is to evaluate how PR‐PFD performs on metabolic functions, and provide insight on a mouse model of human NASH. Male C57BL/6J mice were fed with either normo diet or high‐fat/carbohydrate diet for 16 weeks and a subgroup also fed with PR‐PFD (300 mg/kg/day). An insulin tolerance test was performed at the end of treatment. Histological analysis, determination of serum hormones, adipocytokines measurement, and evaluation of proteins by western blot was performed. Molecular docking, in silico site‐directed mutagenesis, and in vitro experiments using HepG2 cultured cells were performed to validate PR‐PFD binding to peroxisome proliferator–activated receptor alpha (PPAR‐α), activation of PPAR‐α promoter, and sirtuin 1 (SIRT1) protein expression. Compared with the high‐fat group, the PR‐PFD‐treated mice displayed less weight gain, cholesterol, very low density lipoprotein and triglycerides, and showed a significant reduction of hepatic macrosteatosis, inflammation, hepatocyte ballooning, fibrosis, epididymal fat, and total adiposity. PR‐PFD restored levels of insulin, glucagon, adiponectin, and resistin along with improved insulin resistance. Noteworthy, SIRT1–liver kinase B1–phospho‐5′ adenosine monophosphate–activated protein kinase signaling and the PPAR‐α/carnitine O‐palmitoyltransferase 1/acyl‐CoA oxidase 1 pathway were clearly induced in high fat + PR‐PFD mice. In HepG2 cells incubated with palmitate, PR‐PFD induced activation and nuclear translocation of both PPARα and SIRT1, which correlated with increased SIRT1 phosphorylated in serine 47, suggesting a positive feedback loop between the two proteins. These results were confirmed with both synthetic PPAR‐α and SIRT1 activators and inhibitors. Finally, we found that PR‐PFD is a true agonist/ligand for PPAR‐α. Conclusions: PR‐PFD provided an anti‐steatogenic effect and protection for inflammation and fibrosis.

Exploring the free-energy landscape of carbohydrate-protein complexes: development and validation of scoring functions considering the binding-site topology

Carbohydrates play a key role in a variety of physiological and pathological processes and, hence, represent a rich source for the development of novel therapeutic agents. Being able to predict binding mode and binding affinity is an essential, yet lacking, aspect of the structure-based design of carbohydrate-based ligands. We assembled a diverse data set comprising 273 carbohydrate-protein crystal structures with known binding affinity and evaluated the prediction accuracy of a large collection of well-established scoring and free-energy functions, as well as combinations thereof. Unfortunately, the tested functions were not capable of reproducing binding affinities in the studied complexes. To simplify the complex free-energy surface of carbohydrate-protein systems, we classified the studied proteins according to the topology and solvent exposure of the carbohydrate-binding site into five distinct categories. A free-energy model based on the proposed classification scheme reproduced binding affinities in the carbohydrate data set with an r(2) of 0.71 and root-mean-squared-error of 1.25 kcal/mol (N = 236). The improvement in model performance underlines the significance of the differences in the local micro-environments of carbohydrate-binding sites and demonstrates the usefulness of calibrating free-energy functions individually according to binding-site topology and solvent exposure.

Biomimetic design of platelet adhesion inhibitors to block integrin α2β1-collagen interactions: II. Inhibitor library, screening, and experimental validation

Platelet adhesion on collagen mediated by integrin α2β1 has been proven important in arterial thrombus formation, leading to an exigent demand on development of potent inhibitors for the integrin α2β1-collagen binding. In the present study, a biomimetic design strategy of platelet adhesion inhibitors was established, based on the affinity binding model of integrin proposed in part I. First, a heptapeptide library containing 8000 candidates was designed to functionally mimic the binding motif of integrin α2β1. Then, each heptapeptide in the library was docked onto a collagen molecule for the assessment of its affinity, followed by a screening based on its structure similarity to the original structure in the affinity binding model. Eight candidates were then selected for further screening by molecular dynamics (MD) simulations. Thereafter, three candidates chosen from MD simulations were separately added into the physiological saline containing separated integrin and collagen, to check their abilities for blocking the integrin-collagen interaction using MD simulations. Of these three candidates, significant inhibition was observed in the presence of LWWNSYY. Finally, the binding affinity of LWWNSYY for collagen was demonstrated by isothermal titration calorimetry. Moreover, significant inhibition of platelet adhesion in the presence of LWWNSYY has been experimentally validated. This work has thus developed an effective strategy for the biomimetic design of peptide-based platelet adhesion inhibitors.

Scoring function based on weighted residue network

Molecular docking is an important method for the research of protein-protein interaction and recognition. A protein can be considered as a network when the residues are treated as its nodes. With the contact energy between residues as link weight, a weighted residue network is constructed in this paper. Two weighted parameters (strength and weighted average nearest neighbors' degree) are introduced into this model at the same time. The stability of a protein is characterized by its strength. The global topological properties of the protein-protein complex are reflected by the weighted average nearest neighbors' degree. Based on this weighted network model and these two parameters, a new docking scoring function is proposed in this paper. The scoring and ranking for 42 systems' bound and unbounded docking results are performed with this new scoring function. Comparing the results obtained from this new scoring function with that from the pair potentials scoring function, we found that this new scoring function has a similar performance to the pair potentials on some items, and this new scoring function can get a better success rate. The calculation of this new scoring function is easy, and the result of its scoring and ranking is acceptable. This work can help us better understand the mechanisms of protein-protein interactions and recognition.