A systematic computational analysis of human matrix metalloproteinase 13 (MMP-13) crystal structures and structure-based identification of prospective drug candidates as MMP-13 inhibitors repurposable for osteoarthritis

Novel drug discovery approaches for MMP-13 inhibitors in the treatment of osteoarthritis

Recently, the key role of matrix metalloproteinase-13 (MMP-13) in a variety of diseases has attracted much attention. In the field of osteoarthritis (OA) treatment, the study of MMP-13 inhibitors has become a hotspot, and the development of selective MMP-13 inhibitors is a key direction of OA treatment strategies. This paper aims to summarize the latest research progress on MMP-13 inhibitors in drug design and delivery systems in OA treatment, in order to provide new ideas and strategies for the development of MMP-13 inhibitors. In the context of drug design, researchers have utilized innovative drug discovery strategies to developed a number of potential MMP-13 inhibitors by accurately simulating the active site and analyzing the structure of known inhibitors. With regard to delivery systems, nanotechnology has been extensively employed to enhance the targeting and bioavailability of MMP-13 inhibitors, effectively improving therapeutic efficacy through precise delivery to the lesion site. The latest research developments not only reveal the significant potential of MMP-13 inhibitors in disease treatment, but also provide new directions and challenges for future research.

Machine learning-based predictive modeling, virtual screening and biological evaluation studies for identification of potential inhibitors of MMP-13

Matrix Metalloproteinase-13 (MMP-13) is a collagenase that regulates the homeostasis of the extracellular matrix (ECM) and basement membrane, as well as the breakdown of type II collagen. Recent research studies on the molecular and cellular mechanisms of cartilage degradation suggest that MMP-13 overexpression triggers osteoarthritis and is considered a promising target for osteoarthritis treatment. The present work employs machine learning-based virtual screening and structure-based rational drug design approaches to identify potential inhibitors of MMP-13 with diverse chemical scaffolds. The twelve top-scoring screened compounds were subjected to biological evaluation to validate the robustness and predictive modeling of ML-based Virtual Screening. It was observed that eight compounds exhibited approximately 44%-60% inhibition at 0.1 µM concentration, and the IC50 lies in the range of 1.9-2.3 µM against MMP-13. Interestingly, two of the compounds, DP01473 and RH01617, showed potent dose-dependent inhibitory activity. Compound DP01473 inhibited MMP-13 by 44%, 50%, and 70%, while compound RH01617 inhibited MMP-13 by 54%, 55%, and 57% at 0.1 μM, 1 μM, and 10 μM concentrations, respectively, and can be further optimized for the design and development of more potent MMP-13 inhibitors.Communicated by Ramaswamy H. Sarma.

Structural basis for the binding of a selective inverse agonist AF64394 with the human G-protein coupled receptor 3 (GPR3)

The orphan class A G-protein coupled receptor 3 (GPR3) is highly expressed in brain and linked with various neuronal functions, and therefore, expected to play a vital role in the progression of Alzheimer's disease. In view of the lack of its experimental structure, we describe herein the three-dimensional structure and conformational dynamics of GPR3 complexed with the inverse agonist AF64394. The GPR3 model was predicted using the Iterative Threading ASSEmbly Refinement (I-TASSER) method. The Induced Fit Docking predicted two unique poses, Pose 1 and Pose 2, for AF64394, and then, molecular dynamics (MD) simulations followed by binding free-energy calculation revealed the Pose 1 as a very stable pose with the least fluctuation during the MD simulation while the Pose 2 underwent a significant fluctuation. The [1,2,4]triazolo[1,5-a]pyrimidine core was engaged in multiple hydrogen bonds (H-bonds), such as a water-mediated H-bond between the triazole nitrogen and T31, two direct H-bonds between the protonated triazole-ring nitrogen and V186 and T279, a direct H-bond between the secondary amine and V187. The phenyl substituent of AF64394 exhibited aromatic π-π stacking interactions with F97, F101, W43 and Y280. AF64394 showed a direct interaction with E28 and polar interactions with H96, T31 and T279. Throughout the MD simulation, the toggle switch residues, F120 and W260, remained in close contact, indicating that the GPR3 conformation represented an inactive state. The 4-(3-chloro-5-isopropoxyphenethyl) group resided near to the toggle switch residues. The insights gained here are expected to be useful in the structure-based design of new ligands targeting GPR3 modulation. Communicated by Ramaswamy H. Sarma.

Design and Synthesis of Water-Soluble and Potent MMP-13 Inhibitors with Activity in Human Osteosarcoma Cells

Osteoarthritis is a degenerative disease, often resulting in chronic joint pain and commonly affecting elderly people. Current treatments with anti-inflammatory drugs are palliative, making the discovery of new treatments necessary. The inhibition of matrix metalloproteinase MMP-13 is a validated strategy to prevent the progression of this common joint disorder. We recently described polybrominated benzotriazole derivatives with nanomolar inhibitory activity and a promising selectivity profile against this collagenase. In this work, we have extended the study in order to explore the influence of bromine atoms and the nature of the S1′ heterocyclic interacting moiety on the solubility/selectivity balance of this type of compound. Drug target interactions have been assessed through a combination of molecular modeling studies and NMR experiments. Compound 9a has been identified as a water-soluble and highly potent inhibitor with activity in MG-63 human osteosarcoma cells.