An integrated structure- and pharmacophore-based MMP-12 virtual screening

Modulation of NRF2/KEAP1-Mediated Oxidative Stress for Cancer Treatment by Natural Products Using Pharmacophore-Based Screening, Molecular Docking, and Molecular Dynamics Studies

Oxidative stress plays a significant role in the development of cancer. Inhibiting the protein-protein interaction (PPI) between Keap1 and Nrf2 offers a promising strategy to activate the Nrf2 antioxidant pathway, which is normally suppressed by the binding of Keap1 to Nrf2. This study aimed to identify natural compounds capable of targeting the kelch domain of KEAP1 using structure-based drug design methods. A pharmacophore model was constructed based on the KEAP1-inhibitor complex, leading to the selection of 6178 compounds that matched the model. Subsequently, docking and MM/GBSA analyses were conducted, resulting in the identification of 10 compounds with superior binding energies compared to the reference compound. From these, three compounds (ZINC000002123788, ZINC000002111341, and ZINC000002125904) were chosen for further investigation. Ligand-residue interaction analysis revealed specific interactions between these compounds and key residues, indicating their stability within the binding site. ADMET analysis confirmed that the selected compounds possessed desirable drug-like properties. Furthermore, molecular dynamics simulations were performed, demonstrating the stability of the ligand-protein complexes over a 100 ns duration. These findings underscore the potential of the selected natural compounds as agents targeting KEAP1 and provide valuable insights for future experimental studies.

Improvement of binding pose prediction of the MR1 covalent ligands by inclusion of simple pharmacophore constraints and structural waters in the docking process

The major histocompatibility complex (MHC) class I-related molecule, MR1, is a key component of the immune system, presenting antigens to T-cell receptors (TCRs) and modulating the immune response against various antigens. MR1 possesses a compact ligand-binding pocket despite its ability to interact with ligands that can have either agonistic or antagonistic effects on the immune system. Agonistic ligands can stimulate the immune response, while antagonistic ligands do not elicit an immune response. In most cases, ligand binding to MR1 is mediated through a covalent bond with Lys43. However, recent studies have suggested that a variety of small molecules can interact with the MR1-binding site. In this study, we have used several approaches to improve the binding pose prediction of covalent ligands to MR1, including docking in mutated receptors, and imposing simple pharmacophore constraints and structural water molecules. The careful assignment of pharmacophore constraints and inclusion of structural water molecules in the challenging docking process of covalent docking improved the binding pose prediction and virtual screening performance. In a retrospective virtual screening, the proposed approach exhibited EF1% and EF2% values of 7.4 and 5.5, respectively. Conversely, when using the mutated receptor, both EF1% and EF2% were recorded as 0 for the conventional docking method. The performance of the pharmacophore constraints was also evaluated on other covalent docking cases, and compared to previously reported results for common covalent docking methods. The proposed approach achieved an average RMSD of 2.55, while AutoDock4, CovDock, FITTED, GOLD, ICM-Pro, and MOE exhibited average RMSD values of 3.0, 2.93, 3.04, 4.93, 2.44, and 3.36, respectively. Our results demonstrate that the inclusion of simple pharmacophore constraints and structural waters can improve the prediction of binding poses of covalent ligands to MR1, which can aid in the discovery of novel immunotherapeutic agents.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03694-w.

Matrix Metalloproteinases Inhibitors in Cancer Treatment: An Updated Review (2013-2023)

Matrix metalloproteinases (MMPs) are identifiable members of proteolytic enzymes that can degrade a wide range of proteins in the extracellular matrix (ECM). MMPs can be categorized into six groups based on their substrate specificity and structural differences: collagenases, gelatinases, stromelysins, matrilysins, metalloelastase, and membrane-type MMPs. MMPs have been linked to a wide variety of biological processes, such as cell transformation and carcinogenesis. Over time, MMPs have been evaluated for their role in cancer progression, migration, and metastasis. Accordingly, various MMPs have become attractive therapeutic targets for anticancer drug development. The first generations of broad-spectrum MMP inhibitors displayed effective inhibitory activities but failed in clinical trials due to poor selectivity. Thanks to the evolution of X-ray crystallography, NMR analysis, and homology modeling studies, it has been possible to characterize the active sites of various MMPs and, consequently, to develop more selective, second-generation MMP inhibitors. In this review, we summarize the computational and synthesis approaches used in the development of MMP inhibitors and their evaluation as potential anticancer agents.

Torilis japonica Extract Suppresses the Induction of Atopic Inflammation

As one of the major intractable allergic disorders, atopic inflammation is commonly accompanied by itching, dry skin, and inflammation. Atopic inflammation deteriorates the quality of life and has no fundamental cure, so it is crucial to urgently explore and develop natural resources for long-term treatment without any side effects. This study aimed to verify Torilis japonica extract (TJE)'s relieving effect and mechanism against atopic inflammation using skin cells and skin equivalent models, as well as to investigate torilin's effect (obtained from TJE) and other unknown components as marker compounds. Torilin concentration was verified in TJE using high-performance liquid chromatography and analyzed the unknown components using nuclear magnetic resonance spectroscopy. Furthermore, TJE's cytotoxicity, regenerative effect, and cell cycle regulation effects were confirmed using skin cells with atopic inflammation (human dermal fibroblasts and HaCaT keratinocytes) by using TNF-α and IFN-γ treatments. Consequently, TJE was demonstrated to regulate TARC and CTACK expressions as chemokines and those of interleukin-4, -5, and -13 as cytokines related to atopic inflammation. TJE was further confirmed to affect the matrix metalloproteinase-1, -2, and -9 expressions, which are essential in skin damage. Lastly, this study confirmed TJE's relieving effect against atopic inflammation through a 3D skin model and RhCE model using human dermal fibroblasts and HaCaT keratinocytes. These findings on atopic inflammation verified torilin's relieving effects and TJE's other components.

Selective Inhibitors of Medium-Size S1' Pocket Matrix Metalloproteinases: A Stepping Stone of Future Drug Discovery

Among various matrix metalloproteinases (MMPs), MMPs having medium-size S1' pockets are established as promising biomolecular targets for executing crucial roles in cancer, cardiovascular diseases, and neurodegenerative diseases. However, no such MMP inhibitors (MMPIs) are available to date as drug candidates despite a lot of continuous research work for more than three decades. Due to a high degree of structural resemblance among these MMPs, designing selective MMPIs is quite challenging. However, the variability and uniqueness of the S1' pockets of these MMPs make them promising targets for designing selective MMPIs. In this perspective, the overall structural aspects of medium-size S1' pocket MMPs including the unique binding patterns of enzyme-inhibitor interactions have been discussed in detail to acquire knowledge regarding selective inhibitor designing. This overall knowledge will surely be a curtain raiser for the designing of selective MMPIs as drug candidates in the future.

Direct Keap1-kelch inhibitors as potential drug candidates for oxidative stress-orchestrated diseases: A review on In silico perspective

The recent outcry in the search for direct keap1 inhibitors requires a quicker and more effective drug discovery process which is an inherent property of the Computer Aided Drug Discovery (CADD) to bring drug candidates into the clinic for patient's use. This Keap1 (negative regulator of ARE master activator) is emerging as a therapeutic strategy to combat oxidative stress-orchestrated diseases. The advances in computer algorithm and compound databases require that we highlight the functionalities that this technology possesses that can be exploited to target Keap1-Nrf2 PPI. Therefore, in this review, we uncover the in silico approaches that had been exploited towards the identification of keap1 inhibition in the light of appropriate fitting with relevant amino acid residues, we found 3 and 16 other compounds that perfectly fit keap1 kelch pocket/domain. Our goal is to harness the parameters that could orchestrate keap1 surface druggability by utilizing hotspot regions for virtual fragment screening and identification of hotspot residues.

The compromise of virtual screening and its impact on drug discovery

Introduction: Docking and structure-based virtual screening (VS) have been standard approaches in structure-based design for over two decades. However, our understanding of the limitations, potential, and strength of these techniques has enhanced, raising expectations. Areas covered: Based on a survey of reports in the past five years, we assess whether VS: (1) predicts binding poses in agreement with crystallographic data (when available); (2) is a superior screening tool, as often claimed; (3) is successful in identifying chemical scaffolds that can be starting points for subsequent lead optimization cycles. Data shows that knowledge of the target and its chemotypes in postprocessing lead to viable hits in early drug discovery endeavors. Expert opinion: VS is capable of accurate placements in the pocket for the most part, but does not consistently score screening collections accurately. What matters is capitalization on available resources to get closer to a viable lead or optimizable series. Integration of approaches, subjective hit selection guided by knowledge of the receptor or endogenous ligand, libraries driven by experimental guides, validation studies to identify the best docking/scoring that reproduces experimental findings, constraints regarding receptor-ligand interactions, thoroughly designed methodologies, and predefined cutoff scoring criteria strengthen VS's position in pharmaceutical research.

Homology Modeling of 5-alpha-Reductase 2 Using Available Experimental Data

5-Alpha-reductase 2 is an interesting pharmaceutical target for the treatment of several diseases, including prostate cancer, benign prostatic hyperplasia, male pattern baldness, acne, and hirsutism. One of the main approaches in computer aided drug design is structure-based drug discovery. However, the experimental 3D structure of 5-alpha-reductase 2 is not available at present. Therefore, a homology modeling method and molecular dynamics simulation were used to develop a reliable model of 5-alpha-reductase 2 for inhibitor pose prediction and virtual screening. Despite the low sequence identity between the target and template sequences, a useful 3D model of 5-alpha-reductase 2 was generated by the inclusion of experimental data.