A preliminary in silico lead series of 2-phthalimidinoglutaric acid analogues designed as MMP-3 inhibitors

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.

The Effective Treatment of Purpurin on Inflammation and Adjuvant-Induced Arthritis

Rubia cordifolia L. (Rubiaceae), one of the traditional anti-rheumatic herbal medicines in China, has been used to treat rheumatoid arthritis (RA) since ancient times. Purpurin, an active compound of Rubia cordifolia L., has been identified in previous studies and exerts antibacterial, antigenotoxic, anticancer, and antioxidant effects. However, the efficacy and the underlying mechanism of purpurin to alleviate RA are unclear. In this study, the effect of purpurin on inflammation was investigated using macrophage RAW264.7 inflammatory cells, induced by lipopolysaccharide (LPS), and adjuvant-induced arthritis (AIA) rat was established to explore the effect of purpurin on joint damage and immune disorders; the network pharmacology and molecular docking were integrated to dig out the prospective target. Purpurin showed significantly anti-inflammatory effect by reducing the content of IL-6, TNF-α, and IL-1β and increasing IL-10. Besides, purpurin obviously improved joint injury and hypotoxicity in the liver and spleen and regulated the level of FOXP3 and CD4+/CD8+. Furthermore, purpurin reduced the MMP3 content of AIA rats. Network pharmacology and molecular docking also suggested that MMP3 may be the key target of purpurin against RA. The results of this study strongly indicated that purpurin has a potential effect on anti-RA.

Ultrasound-Assisted Water Extraction of Gentiopicroside, Isogentisin, and Polyphenols from Willow Gentian “Dust” Supported by Hydroxypropyl-β-Cyclodextrin as Cage Molecules

The residue after sieving (“dust”) from the willow gentian underground parts is an unexploited herbal tea by-product, although it contains valuable bioactive compounds. Cyclodextrins as efficient green co-solvents, cage molecules, and multifunctional excipients could improve the extraction and contribute to the added value of the resulting extracts. The objective of this study was to determine the optimal conditions for the extraction of gentiopicroside, isogentisin, and total phenolics (TPC) from willow gentian “dust” using ultrasound-assisted water extraction coupled with hydroxypropyl-β-cyclodextrin (HPβCD). The influence of extraction temperature (X1: 20–80 °C), time (X2: 20–50 min), and HPβCD concentration (X3: 2–4% w/v) was analyzed employing the response surface methodology (RSM). The optimal extraction conditions for simultaneously maximizing the extraction yield of all monitored responses were X1: 74.89 °C, X2: 32.57 min, and X3: 3.01% w/v. The experimentally obtained response values under these conditions (46.96 mg/g DW for gentiopicroside, 0.51 mg/g DW for isogentisin, and 12.99 mg GAE/g DW for TPC) were in close agreement with those predicted, thus confirming the suitability and good predictive accuracy of the developed RSM models. Overall, the developed extraction system could be an applicable alternative strategy to improve the extraction of bioactive compounds from the underutilized “dust” of willow gentian underground parts.

Pseudomonas aeruginosa Biofilm Formation and Its Control

Microbes are hardly seen as planktonic species and are most commonly found as biofilm communities in cases of chronic infections. Biofilms are regarded as a biological condition, where a large group of microorganisms gets adhered to a biotic or abiotic surface. In this context, Pseudomonas aeruginosa, a Gram-negative nosocomial pathogen is the main causative organism responsible for life-threatening and persistent infections in individuals affected with cystic fibrosis and other lung ailments. The bacteria can form a strong biofilm structure when it adheres to a surface suitable for the development of a biofilm matrix. These bacterial biofilms pose higher natural resistance to conventional antibiotic therapy due to their multiple tolerance mechanisms. This prevailing condition has led to an increasing rate of treatment failures associated with P. aeruginosa biofilm infections. A better understanding of the effect of a diverse group of antibiotics on established biofilms would be necessary to avoid inappropriate treatment strategies. Hence, the search for other alternative strategies as effective biofilm treatment options has become a growing area of research. The current review aims to give an overview of the mechanisms governing biofilm formation and the different strategies employed so far in the control of biofilm infections caused by P. aeruginosa. Moreover, this review can also help researchers to search for new antibiofilm agents to tackle the effect of biofilm infections that are currently imprudent to conventional antibiotics.

Statistical analysis, optimization, and prioritization of virtual screening parameters for zinc enzymes including the anthrax toxin lethal factor

The anthrax toxin lethal factor (LF) and matrix metalloproteinase-3 (MMP-3, stromelysin-1) are popular zinc metalloenzyme drug targets, with LF primarily responsible for anthrax-related toxicity and host death, while MMP-3 is involved in cancer- and rheumatic disease-related tissue remodeling. A number of in silico screening techniques, most notably docking and scoring, have proven useful for identifying new potential drug scaffolds targeting LF and MMP-3, as well as for optimizing lead compounds and investigating mechanisms of action. However, virtual screening outcomes can vary significantly depending on the specific docking parameters chosen, and systematic statistical significance analyses are needed to prioritize key parameters for screening small molecules against these zinc systems. In the current work, we present a series of chi-square statistical analyses of virtual screening outcomes for cocrystallized LF and MMP-3 inhibitors docked into their respective targets, evaluated by predicted enzyme-inhibitor dissociation constant and root-mean-square deviation (RMSD) between predicted and experimental bound configurations, and we present a series of preferred parameters for use with these systems in the industry-standard Surflex-Dock screening program, for use by researchers utilizing in silico techniques to discover and optimize new scaffolds.

Mechanism of immunomodulatory drugs' action in the treatment of multiple myeloma

Although immunomodulatory drugs (IMiDs), such as thalidomide, lenalidomide, and pomalidomide, are widely used in the treatment of multiple myeloma (MM), the molecular mechanism of IMiDs' action is largely unknown. In this review, we will summarize recent advances in the application of IMiDs in MM cancer treatment as well as their effects on immunomodulatory activities, anti-angiogenic activities, intervention of cell surface adhesion molecules between myeloma cells and bone marrow stromal cells, anti-inflammatory activities, anti-proliferation, pro-apoptotic effects, cell cycle arrest, and inhibition of cell migration and metastasis. In addition, the potential IMiDs' target protein, IMiDs' target protein's functional role, and the potential molecular mechanisms of IMiDs resistance will be discussed. We wish, by presentation of our naive discussion, that this review article will facilitate further investigation in these fields.

Evaluation of Density Functionals, SCC-DFTB, Neglect of Diatomic Differential Overlap (NDDO) Models and Molecular Mechanics Methods for Prolyl-Leucyl-Glycinamide (PLG) and Structural Derivatives

Prolyl-leucyl-glycinamide (PLG) is a unique endogenous peptide that modulates dopamine receptor subtypes of the D(2) receptor family within the CNS. We seek to elucidate the structural basis and molecular mechanism by which PLG and its analogues modulate dopamine receptors, toward the development of new therapeutics to treat Parkinson's disease, tardive dyskinesia and schizophrenia. As a first step toward establishing a validated protocol for accurate computational modeling of PLG and associated peptidomimetic analogues, we evaluated the accuracy of density functional theory (DFT), wavefunction theory (WFT), and molecular mechanics (MM) calculations for PLG and for a library of structurally related small molecules. We first tested twelve local and nonlocal density functionals, Hartree-Fock (HF) theory, four "semiempirical" methods of the neglect of diatomic differential overlap (NDDO) type, and one self-consistent-charge nonorthogonal tight-binding (SCC-DFTB) method as implemented in two software suites, against coupled-cluster benchmark geometries for 4-methylthiazolidine, a small molecule that comprises key structural features present in our PLG analogue library. DFT and HF calculations were done with the MG3S augmented polarized triple-zeta basis set. We find that for 4-methylthiazolidine bond distances, DFT significantly outperforms NDDO, and both SCC-DFTB versions we evaluated perform worse than HF theory and are less accurate than 83% of the density functionals tested. The top five functionals for 4-methylthiazolidine were M05-2X, mPW1PW, B97-2, M06-2X, and PBEh, with mean unsigned errors (MUEs) in bond length of 0.0017, 0.0020, 0.0023, 0.0025 and 0.0027 Å, respectively. The widely used B3LYP functional ranked 11(th) out of twelve functionals evaluated, slightly below SCC-DFTB, and is significantly less accurate for 4-methylthiazolidine bond distances (MUE = 0.0095 Å) than the best local functional (M06-L, MUE = 0.0030 Å), which is far less computationally costly. Based on that initial analysis, we obtained new M05-2X benchmark geometric parameters for PLG and a library of eleven peptidomimetic derivatives, which we in turn used to examine the accuracy of thirty-four popular molecular mechanics (MM) force fields, four NDDO approaches, and SCC-DFTB for the full compound structures. Here, we found that ∼70% of the MM force fields tested superior to the best semiempirical and SCC-DFTB codings. Moreover, AMBER-type force fields proved most accurate among MM methods for this class of small-molecule peptidomimetics; the AMBER-type methods comprised eight out of the top ten molecular mechanics options we tested.

Screening Outside the Catalytic Site: Inhibition of Macromolecular Inter-actions Through Structure-Based Virtual Ligand Screening Experiments

During these last 15 years, drug discovery strategies have essentially focused on identifying small molecules able to inhibit catalytic sites. However, other mechanisms could be targeted. Protein-protein interactions play crucial roles in a number of biological processes, and, as such, their disruption or stabilization is becoming an area of intense activity. Along the same line, inhibition of protein-membrane could be of major importance in several disease indications. Despite the many challenges associated with the development of such classes of interaction modulators, there has been considerable success in the recent years. Importantly, through the existence of protein hot-spots and the presence of druggable pockets at the macromolecular interfaces or in their vicinities, it has been possible to find small molecule effectors using a variety of screening techniques, including combined virtual ligand-in vitro screening strategy. Indeed such in silico-in vitro protocols emerge as the method of choice to facilitate our quest of novel drug-like compounds or of mechanistic probes aiming at facilitating the understanding of molecular reactions involved in the Health and Disease process. In this review, we comment recent successes of combined in silico-in vitro screening methods applied to modulating macromolecular interactions with a special emphasis on protein-membrane interactions.

In silico pharmacology for drug discovery: applications to targets and beyond

Computational (in silico) methods have been developed and widely applied to pharmacology hypothesis development and testing. These in silico methods include databases, quantitative structure-activity relationships, similarity searching, pharmacophores, homology models and other molecular modeling, machine learning, data mining, network analysis tools and data analysis tools that use a computer. Such methods have seen frequent use in the discovery and optimization of novel molecules with affinity to a target, the clarification of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The first part of this review discussed the methods that have been used for virtual ligand and target-based screening and profiling to predict biological activity. The aim of this second part of the review is to illustrate some of the varied applications of in silico methods for pharmacology in terms of the targets addressed. We will also discuss some of the advantages and disadvantages of in silico methods with respect to in vitro and in vivo methods for pharmacology research. Our conclusion is that the in silico pharmacology paradigm is ongoing and presents a rich array of opportunities that will assist in expediating the discovery of new targets, and ultimately lead to compounds with predicted biological activity for these novel targets.