Structural exploration for the refinement of anticancer matrix metalloproteinase-2 inhibitor designing approaches through robust validated multi-QSARs

A fragment-based exploration of diverse MMP-9 inhibitors through classification-dependent structural assessment

Matrix metalloproteinases (MMPs) are belonging to the Zn2+-dependent metalloenzymes. These can degenerate the extracellular matrix (ECM) that is entailed with various biological processes. Among the MMP family members, MMP-9 is associated with several pathophysiological circumstances. Apart from wound healing, remodeling of bone, inflammatory mechanisms, and rheumatoid arthritis, MMP-9 has also significant roles in tumor invasion and metastasis. Therefore, MMP-9 has been in the spotlight of anticancer drug discovery programs for more than a decade. In this present study, classification-based QSAR techniques along with fragment-based data mining have been carried out on divergent MMP-9 inhibitors to point out the important structural attributes. This current study may be able to elucidate the importance of several pivotal molecular fragments such as sulfonamide, hydroxamate, i-butyl, and ethoxy functions for imparting potential MMP-9 inhibition. These observations are in correlation with the ligand-bound co-crystal structures of MMP-9. Therefore, these findings are beneficial for the design and discovery of effective MMP-9 inhibitors in the future.

An updated patent review of matrix metalloproteinase (MMP) inhibitors (2021-present)

INTRODUCTION

Matrix metalloproteinases (MMPs) are strongly interlinked with the progression and mechanisms of several life-threatening diseases including cancer. Thus, novel MMP inhibitors (MMPIs) as promising drug candidates can be effective in combating these diseases. However, no MMPIs are marketed to date due to poor pharmacokinetics and lower selectivity. Therefore, this review was performed to study the newer MMPIs patented after the COVID-19 period for an updated perspective on MMPIs.

AREAS COVERED

This review highlights patents related to MMPIs, and their therapeutic implications published between January 2021 and August 2023 available in the Google Patents, Patentscope, and Espacenet databases.

EXPERT OPINION

Despite various MMP-related patents disclosed up to 2020, newer patent applications in the post-COVID-19 period decreased a lot. Besides major MMPs, other isoforms (i.e. MMP-3 and MMP-7) have gained attention recently for drug development. This may open up newer dimensions targeting these MMPs for therapeutic advancements. The isoform selectivity and bioavailability are major concerns for effective MMPI development. Thus, adopting theoretical approaches and experimental methodologies can unveil the development of novel MMPIs with improved pharmacokinetic profiles. Nevertheless, the involvement of MMPs in cancer, and the mechanisms of such MMPs in other diseases should be extensively studied for novel MMPI development.

Assessing structural insights into in-house arylsulfonyl L-(+) glutamine MMP-2 inhibitors as promising anticancer agents through structure-based computational modelling approaches

MMP-2 is potentially contributing to several cancer progressions including leukaemias. Therefore, considering MMP-2 as a promising target, novel anticancer compounds may be designed. Here, 32 in-house arylsulfonyl L-(+) glutamines were subjected to various structure-based computational modelling approaches to recognize crucial structural attributes along with the spatial orientation for higher MMP-2 inhibition. Again, the docking-based 2D-QSAR study revealed that the Coulomb energy conferred by Tyr142 and total interaction energy conferred by Ala84 was crucial for MMP-2 inhibition. Importantly, the docking-dependent CoMFA and CoMSIA study revealed the importance of favourable steric, electrostatic, and hydrophobic substituents at the terminal phenyl ring. The MD simulation study revealed a lower fluctuation in the RMSD, RMSF, and Rg values indicating stable binding interactions of MMP-2 and these molecules. Moreover, the residual hydrogen bond and their interaction analysis disclosed crucial amino acid residues responsible for forming potential hydrogen bonding for higher MMP-2 inhibition. The results can effectively aid in the design and discovery of promising small-molecule drug-like MMP-2 inhibitors with greater anticancer potential in the future.

A quantitative structural analysis of AR-42 derivatives as HDAC1 inhibitors for the identification of promising structural contributors

Alteration and abnormal epigenetic mechanisms can lead to the aberration of normal biological functions and the occurrence of several diseases. The histone deacetylase (HDAC) family of enzymes is one of the prime regulators of epigenetic functions modifying the histone proteins, and thus, regulating epigenetics directly. HDAC1 is one of those HDACs which have important contributions to cellular epigenetics. The abnormality of HDAC is correlated to the occurrence, progression, and poor prognosis in several disease conditions namely neurodegenerative disorders, cancer cell proliferation, metastasis, chemotherapy resistance, and survival in various cancers. Therefore, the progress of potent and effective HDAC1 inhibitors is one of the prime approaches to combat such diseases. In this study, both regression and classification-based molecular modelling studies were conducted on some AR-42 derivatives as HDAC1 inhibitors to elucidate the crucial structural aspects that are responsible for regulating their biological responses. This study revealed that the molecular polarizability, van der Waals volume, the presence of aromatic rings as well as the higher number of hydrogen bond acceptors might affect prominently their inhibitory activity and might be responsible for proper fitting and interactions at the HDAC1 active site to pertain effective inhibition.

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.

Insight into the structural requirements of gelatinases (MMP-2 and MMP-9) inhibitors by multiple validated molecular modelling approaches: Part II

Inhibition of the matrix metalloproteinases (MMPs) is effective against metastasis of secondary tumours. Previous MMP inhibitors have failed in clinical trials due to their off-target toxicity in solid tumours. Thus, newer MMP inhibitors now have paramount importance. Here, different molecular modelling techniques were applied on a dataset of 110 gelatinase (MMP-2 and MMP-9) inhibitors. The objectives of the present study were to identify structural fingerprints for gelatinase inhibition and also to develop statistically validated QSAR models for the screening and prediction of different derivatives as MMP-2 (gelatinase A) and MMP-9 (gelatinase B) inhibitors. The Bayesian classification study provided the ROC values for the training set of 0.837 and 0.815 for MMP-2 and MMP-9, respectively. The linear model also produced the leave-one-out cross-validated Q² of 0.805 (eq. 1, MMP-2) and 0.724 (eq. 2, MMP-9), an r² of 0.845 (eq. 1, MMP-2) and 0.782 (eq. 2, MMP-9), an r²_Pred of 0.806 (eq. 1, MMP-2) and 0.732 (eq. 2, MMP-9). Similarly, non-linear learning models were also statistically significant and reliable. Overall, this study may help in the rational design of newer compounds with higher gelatinase inhibition to fight against both primary and secondary cancers in future.

Ligand-based design of anticancer MMP2 inhibitors: a review

MMP2, a Zn²⁺-dependent metalloproteinase, is related to cancer and angiogenesis. Inhibition of this enzyme might result in a potential antimetastatic drug to leverage the anticancer drug armory. In silico or computer-aided ligand-based drug design is a method of rational drug design that takes multiple chemometrics (i.e., multi-quantitative structure-activity relationship methods) into account for virtually selecting or developing a series of probable selective MMP2 inhibitors. Though existing matrix metalloproteinase inhibitors have shown plausible pan-matrix metalloproteinase (MMP) activity, they have resulted in various adverse effects leading to their being rescinded in later phases of clinical trials. Therefore a review of the ligand-based designing methods of MMP2 inhibitors would result in an explicit route map toward successfully designing and synthesizing novel and selective MMP2 inhibitors.

Insight into the structural requirement of aryl sulphonamide based gelatinases (MMP-2 and MMP-9) inhibitors - Part I: 2D-QSAR, 3D-QSAR topomer CoMFA and Naïve Bayes studies - First report of 3D-QSAR Topomer CoMFA analysis for MMP-9 inhibitors and jointly inhibitors of gelatinases together

Gelatinases [gelatinase A - matrix metalloproteinase-2 (MMP-2), gelatinase B - matrix metalloproteinase-9 (MMP-9)] play key roles in many disease conditions including cancer. Despite some research work on gelatinases inhibitors both jointly and individually had been reported, challenges still exist in achieving potency as well as selectivity. Here in part I of a series of work, we have reported the structural requirement of some arylsulfonamides. In particular, regression-based 2D-QSARs, topomer CoMFA (comparative molecular field analysis) and Bayesian classification models were constructed to refine structural features for attaining better gelatinase inhibitory activity. The 2D-QSAR models exhibited good statistical significance. The descriptors nsssN, SHBint6, SHBint7, PubchemFP629 were directly correlated with the MMP-2 binding affinities whereas nsssN, SHBint10 and AATS2i were directly proportional to MMP-9 binding affinities. The topomer CoMFA results indicated that the steric and electrostatic fields play key roles in gelatinase inhibition. The established Naïve Bayes prediction models were evaluated by fivefold cross validation and an external test set. Furthermore, important molecular descriptors related to MMP-2 and MMP-9 binding affinities and some active/inactive fragments were identified. Thus, these observations may be helpful for further work of aryl sulphonamide based gelatinase inhibitors in future.

Whether the Validation of the Predictive Potential of Toxicity Models is a Solved Task?

Different kinds of biological activities are defined by complex biochemical interactions, which are termed as a "mathematical function" not only of the molecular structure but also for some additional circumstances, such as physicochemical conditions, interactions via energy and information effects between a substance and organisms, organs, cells. These circumstances lead to the great complexity of prediction for biochemical endpoints, since all "details" of corresponding phenomena are practically unavailable for the accurate registration and analysis. Researchers have not a possibility to carry out and analyse all possible ways of the biochemical interactions, which define toxicological or therapeutically attractive effects via direct experiment. Consequently, a compromise, i.e. the development of predictive models of the above phenomena, becomes necessary. However, the estimation of the predictive potential of these models remains a task that is solved only partially. This mini-review presents a collection of attempts to be used for the above-mentioned task, two special statistical indices are proposed, which may be a measure of the predictive potential of models. These indices are (i) Index of Ideality of Correlation; and (ii) Correlation Contradiction Index.

QSAR modelling on a series of arylsulfonamide-based hydroxamates as potent MMP-2 inhibitors

Matrix metalloproteinase-2 (MMP-2) is a lucrative therapeutic target as far as anticancer drug discovery is concerned. Overexpression of MMP-2 is found to facilitate tumour propagation through the involvement of vascular endothelial growth factor (VEGF). However, even after different techniques, finding a target-specific MMP-2 inhibitor with respectable pharmacodynamic properties is still a challenging task. Regression-dependent quantitative structure-activity relationship (QSAR) strategies might be among the possible drug design methods to explore the essential structural features that would be valuable to find a suitable MMP-2 inhibitor. In this paper, 72 molecules were explored using the PaDEL descriptors and stepwise multiple linear regression (S-MLR). The partial least squares (PLS) method was also used to create a viable statistical model with an acceptable metric related to these models. The final statistical models were formed with statistical parameters within acceptable range (r² = 0.797, Q² = 0.725 and r²_pred = 0.643 for the MLR model, and r² = 0.780, Q² = 0.685 and r²_pred = 0.666 for the PLS model). The models were analysed and compared with those already published on the same endpoint.

Development of Matrix Metalloproteinase-2 Inhibitors for Cardioprotection

The objective of our present study is to develop novel inhibitors for MMP-2 for acute cardioprotection. In a series of pilot studies, novel substituted carboxylic acid derivatives were synthesized based on imidazole and thiazole scaffolds and then tested in a screeening cascade for MMP inhibition. We found that the MMP-inhibiting effects of imidazole and thiazole carboxylic acid-based compounds are superior in efficacy in comparison to the conventional hydroxamic acid derivatives of the same molecules. Based on these results, a 568-membered focused library of imidazole and thiazole compounds was generated in silico and then the library members were docked to the 3D model of MMP-2 followed by an in vitro medium throughput screening (MTS) based on a fluorescent assay employing MMP-2 catalytic domain. Altogether 45 compounds showed a docking score of >70, from which 30 compounds were successfully synthesized. Based on the MMP-2 inhibitory tests using gelatin zymography, 7 compounds were then selected and tested in neonatal rat cardiac myocytes subjected to simulated I/R injury. Six compounds showed significant cardio-cytoprotecion and the most effective compound (MMPI-1154) significantly decreased infarct size when applied at 1 μM in an ex vivo model for acute myocardial infarction. This is the first demonstration that imidazole and thiazole carboxylic acid-based compounds are more efficacious MMP-2 inhibitor than their hydroxamic acid derivatives. MMPI-1154 is a promising novel cardio-cytoprotective imidazole-carboxylic acid MMP-2 inhibitor lead candidate for the treatment of acute myocardial infarction.