Screening of Matrix Metalloproteinases Available from the Protein Data Bank: Insights into Biological Functions, Domain Organization, and Zinc Binding Groups

Where developmental toxicity meets explainable artificial intelligence: state-of-the-art and perspectives

INTRODUCTION

The application of Artificial Intelligence (AI) to predictive toxicology is rapidly increasing, particularly aiming to develop non-testing methods that effectively address ethical concerns and reduce economic costs. In this context, Developmental Toxicity (Dev Tox) stands as a key human health endpoint, especially significant for safeguarding maternal and child well-being.

AREAS COVERED

This review outlines the existing methods employed in Dev Tox predictions and underscores the benefits of utilizing New Approach Methodologies (NAMs), specifically focusing on eXplainable Artificial Intelligence (XAI), which proves highly efficient in constructing reliable and transparent models aligned with recommendations from international regulatory bodies.

EXPERT OPINION

The limited availability of high-quality data and the absence of dependable Dev Tox methodologies render XAI an appealing avenue for systematically developing interpretable and transparent models, which hold immense potential for both scientific evaluations and regulatory decision-making.

Virtual Reverse Screening Approach to Target Type 2 Cannabinoid Receptor

A screening pool consisting of 617710 drug-like query molecules properly filtered from the ChEMBL database was employed for a ligand-based reverse screening toward the type 2 cannabinoid receptor (CB₂) target. By using our recently developed PLATO polypharmacological web platform, 233 out of 617710 drug-like molecules were prioritized on the basis of the predicted bioactivity values, better than 0.2 μM with a probability of about 98%, toward the CB₂ target. Building on these results, the occurrence of putative CB₂-related targets was also investigated for prospective repurposing studies.

Getting Insights into Structural and Energetic Properties of Reciprocal Peptide-Protein Interactions

Peptide-protein interactions play a key role for many cellular and metabolic processes involved in the onset of largely spread diseases such as cancer and neurodegenerative pathologies. Despite the progress in the structural characterization of peptide-protein interfaces, the in-depth knowledge of the molecular details behind their interactions is still a daunting task. Here, we present the first comprehensive in silico morphological and energetic study of peptide binding sites by focusing on both peptide and protein standpoints. Starting from the PixelDB database, a nonredundant benchmark collection of high-quality 3D crystallographic structures of peptide-protein complexes, a classification analysis of the most representative categories based on the nature of each cocrystallized peptide has been carried out. Several interpretable geometrical and energetic descriptors have been computed both from peptide and target protein sides in the attempt to unveil physicochemical and structural causative correlations. Finally, we investigated the most frequent peptide-protein residue pairs at the binding interface and made extensive energetic analyses, based on GRID MIFs, with the aim to study the peptide affinity-enhancing interactions to be further exploited in rational drug design strategies.

Ethyl Acetohydroxamate Incorporated Chalcones: Unveiling a Novel Class of Chalcones for Multitarget Monoamine Oxidase-B Inhibitors Against Alzheimer's Disease

BACKGROUND

Chalcones are considered as the selective scaffold for the inhibition of MAO-B.

OBJECTIVES

A previously synthesized ethyl acetohydroxamate-chalcones (L1-L22) were studied for their inhibitory activities against human recombinant monoamine oxidase A and B (hMAO-A and hMAO-B, respectively) and acetylcholinesterase (AChE) as multi-target directed ligands for the treatment of Alzheimer's Disease (AD).

METHODS

Enzyme inhibition studies of MAO-A, MAO-B and AChE is carried out. Computational studies such as Molecular docking, Molecular Mechanics/Generalized Born Surface Area calculations, ADMET prediction, and protein target prediction are also performed.

RESULTS

Among the screened compounds, compound L3 has most potent hMAO-B inhibition with an IC50 value of 0.028 ± 0.0016 µM, and other compounds, L1, L2, L4, L8, L12, and L21 showed significant potent hMAO-B inhibition with IC50 values of 0.051 ± 0.0014, 0.086 ± 0.0035, 0.036 ± 0.0011, 0.096 ± 0.0061, 0.083 ± 0.0016, and 0.038 ± 0.0021 µM, respectively. On the other hand, among the tested compounds, compound L13 showed highest hMAO-A inhibition with an IC50 value of 0.51± 0.051 µM and L9 has a significant value of 1.85 ± 0.045 µM. However, the compounds L3 and L4 only showed high selectivities for hMAO-B with Selectivity Index (SI) values of 621.4 and 416.7, respectively. Among the substituents in ring A of ethyl acetohydroxamate-chalcones (L1-L9), F atom at p-position (L3) showed highest inhibitory effect against hMAO-B. This result supports the uniqness and bizarre behavior of fluorine. Moreover, chalcones L3, L4, L9, L11, and L12 showed potential AChE inhibitory effect with IC50 values of 0.67, 0.85, 0.39, 0.30, and 0.45 µM, respectively. Inhibitions of hMAO-B by L3 or L4 were recovered to the level of the reversible reference (lazabemide), and were competitive with Ki values of 0.0030 ± 0.0002 and 0.0046 ± 0.0005 µM, respectively. Inhibitions of AChE by L3 and L11 were of the competitive and mixed types with Ki values of 0.30 ± 0.044 and 0.14 ± 0.0054 µM, respectively.

CONCLUSION

The studies indicated that L3 and L4 are considered to be promising multitarget drug molecules with potent, selective, and reversible competitive inhibitors of hMAO-B and with highly potent AChE inhibitory effect.

Bcr-Abl Allosteric Inhibitors: Where We Are and Where We Are Going to

The fusion oncoprotein Bcr-Abl is an aberrant tyrosine kinase responsible for chronic myeloid leukemia and acute lymphoblastic leukemia. The auto-inhibition regulatory module observed in the progenitor kinase c-Abl is lost in the aberrant Bcr-Abl, because of the lack of the N-myristoylated cap able to bind the myristoyl binding pocket also conserved in the Bcr-Abl kinase domain. A way to overcome the occurrence of resistance phenomena frequently observed for Bcr-Abl orthosteric drugs is the rational design of allosteric ligands approaching the so-called myristoyl binding pocket. The discovery of these allosteric inhibitors although very difficult and extremely challenging, represents a valuable option to minimize drug resistance, mostly due to the occurrence of mutations more frequently affecting orthosteric pockets, and to enhance target selectivity with lower off-target effects. In this perspective, we will elucidate at a molecular level the structural bases behind the Bcr-Abl allosteric control and will show how artificial intelligence can be effective to drive the automated de novo design towards off-patent regions of the chemical space.

Design, synthesis and biological evaluation of oxygenated chalcones as potent and selective MAO-B inhibitors

The present study documents the synthesis of oxygenated chalcone (O1-O26) derivatives and their abilities to inhibit monoamine oxidases. All 26 derivatives examined showed potent inhibitory activity against MAO-B. Compound O23 showed the greatest inhibitory activity against MAO-B with an IC₅₀ value of 0.0021 µM, followed by compounds O10 and O17 (IC₅₀ = 0.0030 and 0.0034 µM, respectively). In addition, most of the derivatives potently inhibited MAO-A and O6 was the most potent inhibitor with an IC₅₀ value of 0.029 µM, followed by O3, O4, O9, and O2 (IC₅₀ = 0.035, 0.053, 0.072, and 0.082 µM, respectively). O23 had a high selectivity index (SI) value for MAO-B of 138.1, and O20 (IC₅₀ value for MAO-B = 0.010 µM) had an extremely high SI of >4000. In dialysis experiments, inhibitions of MAO-A and MAO-B by O6 and O23, respectively, were recovered to their respective reversible reference levels, demonstrating both are reversible inhibitors. Kinetic studies revealed that O6 and O23 competitively inhibited MAO-A and MAO-B, respectively, with respective K_i values of 0.016 ± 0.0007 and 0.00050 ± 0.00003 µM. Lead compound are also non-toxic at 200 µg/mL in normal rat spleen cells. Molecular docking simulations and subsequent Molecular Mechanics/Generalized Born Surface Area calculations provided a rationale that explained experimental data.

Accelerating Drug Discovery by Early Protein Drug Target Prediction Based on a Multi-Fingerprint Similarity Search

In this continuing work, we have updated our recently proposed Multi-fingerprint Similarity Search algorithm (MuSSel) by enabling the generation of dominant ionized species at a physiological pH and the exploration of a larger data domain, which included more than half a million high-quality small molecules extracted from the latest release of ChEMBL (version 24.1, at the time of writing). Provided with a high biological assay confidence score, these selected compounds explored up to 2822 protein drug targets. To improve the data accuracy, samples marked as prodrugs or with equivocal biological annotations were not considered. Notably, MuSSel performances were overall improved by using an object-relational database management system based on PostgreSQL. In order to challenge the real effectiveness of MuSSel in predicting relevant therapeutic drug targets, we analyzed a pool of 36 external bioactive compounds published in the Journal of Medicinal Chemistry from October to December 2018. This study demonstrates that the use of highly curated chemical and biological experimental data on one side, and a powerful multi-fingerprint search algorithm on the other, can be of the utmost importance in addressing the fate of newly conceived small molecules, by strongly reducing the attrition of early phases of drug discovery programs.

Design, Synthesis, and Biological Evaluation of Tetrahydro-β-carboline Derivatives as Selective Sub-Nanomolar Gelatinase Inhibitors

Targeting matrix metalloproteinases (MMPs) is a pursued strategy for treating several pathological conditions, such as multiple sclerosis and cancer. Herein, a series of novel tetrahydro-β-carboline derivatives with outstanding inhibitory activity toward MMPs are present. In particular, compounds 9 f, 9 g, 9 h and 9 i show sub-nanomolar IC₅₀ values. Interestingly, compounds 9 g and 9 i also provide remarkable selectivity toward gelatinases; IC₅₀ =0.15 nm for both toward MMP-2 and IC₅₀ =0.63 and 0.58 nm, respectively, toward MMP-9. Molecular docking simulations, performed by employing quantum mechanics based partial charges, shed light on the rationale behind binding involving specific interactions with key residues of S1' and S3' domains. Taken together, these studies indicate that tetrahydro-β-carboline represents a promising scaffold for the design of novel inhibitors able to target MMPs and selectively bias gelatinases, over the desirable range of the pharmacokinetics spectrum.

Network pharmacology-based approach of novel traditional Chinese medicine formula for treatment of acute skin inflammation in silico

Matrix metalloproteinase-9 (MMP-9) appears to play an important role in acute skin inflammation. Subantimicrobial dose of tetracycline has been demonstrated to inhibit the activity of MMP-9 protein. However, long-term use tetracycline will induce side effect. The catalytic site of MMP-9 is located at zinc-binding amino acids, His401, His405 and His411. We attempted to search novel medicine formula as MMP-9 inhibitors from traditional Chinese medicine (TCM) database by using in silico studies. We utilized high-throughput virtual screening to find which natural compounds could bind to the zinc-binding site. The quantitative structure-activity relationship (QSAR) models, which constructed by scaffold of MMP-9 inhibitors and its activities, were employed to predict the bio-activity of the natural compounds for MMP-9. The results showed that Celacinnine, Lobelanidine and Celallocinnine were qualified to interact with zinc-binding site and displayed well predictive activity. We found that celallocinnine was the best TCM compound for zinc binging sites of MMP-9 because the stable interactions were observed under dynamic condition. In addition, Celacinnine and Lobelanidine could interact with MMP-9 related protein that identified by drug-target interaction network analysis. Thus, we suggested the herbs Hypericum patulum, Sedum acre, and Tripterygium wilfordii that containing Celallocinnine, Celacinnine and Lobelanidine might be a novel medicine formula to avoid the side effect of tetracycline and increase the efficacy of treatment.

Effects of Mutations on Structure-Function Relationships of Matrix Metalloproteinase-1

Matrix metalloproteinase-1 (MMP-1) is one of the most widely studied enzymes involved in collagen degradation. Mutations of specific residues in the MMP-1 hemopexin-like (HPX) domain have been shown to modulate activity of the MMP-1 catalytic (CAT) domain. In order to reveal the structural and conformational effects of such mutations, a molecular dynamics (MD) study was performed of in silico mutated residues in the X-ray crystallographic structure of MMP-1 complexed with a collagen-model triple-helical peptide (THP). The results indicate an important role of the mutated residues in MMP-1 interactions with the THP and communication between the CAT and the HPX domains. Each mutation has a distinct impact on the correlated motions in the MMP-1•THP. An increased collagenase activity corresponded to the appearance of a unique anti-correlated motion and decreased correlated motions, while decreased collagenase activity corresponded both to increased and decreased anti-correlated motions.

Human Aquaporin-4 and Molecular Modeling: Historical Perspective and View to the Future

Among the different aquaporins (AQPs), human aquaporin-4 (hAQP4) has attracted the greatest interest in recent years as a new promising therapeutic target. Such a membrane protein is, in fact, involved in a multiple sclerosis-like immunopathology called Neuromyelitis Optica (NMO) and in several disorders resulting from imbalanced water homeostasis such as deafness and cerebral edema. The gap of knowledge in its functioning and dynamics at the atomistic level of detail has hindered the development of rational strategies for designing hAQP4 modulators. The application, lately, of molecular modeling has proved able to fill this gap providing a breeding ground to rationally address compounds targeting hAQP4. In this review, we give an overview of the important advances obtained in this field through the application of Molecular Dynamics (MD) and other complementary modeling techniques. The case studies presented herein are discussed with the aim of providing important clues for computational chemists and biophysicists interested in this field and looking for new challenges.

Mind the Gap! A Journey towards Computational Toxicology

Computational methods have advanced toxicology towards the development of target-specific models based on a clear cause-effect rationale. However, the predictive potential of these models presents strengths and weaknesses. On the good side, in silico models are valuable cheap alternatives to in vitro and in vivo experiments. On the other, the unconscious use of in silico methods can mislead end-users with elusive results. The focus of this review is on the basic scientific and regulatory recommendations in the derivation and application of computational models. Attention is paid to examine the interplay between computational toxicology and drug discovery and development. Avoiding the easy temptation of an overoptimistic future, we report our view on what can, or cannot, realistically be done. Indeed, studies of safety/toxicity represent a key element of chemical prioritization programs carried out by chemical industries, and primarily by pharmaceutical companies.

Discovery of potent inhibitor for matrix metalloproteinase-9 by pharmacophore based modeling and dynamics simulation studies

Matrix metalloproteinase-9 (MMP-9) is an attractive target for anticancer therapy. In the present study ligand based pharmacophore modeling was performed to elucidate the structural elements for a diverse class of MMP-9 inhibitors. The pharmacophore model was validated through Güner-Henry (GH) scoring method. The final pharmacophore model consisted of three hydrogen bond acceptors (HBA), and two ring aromatic regions (RA). This model was utilized to screen the natural compound database to seek novel compounds as MMP-9 inhibitors. The identified hits were validated using molecular docking and molecular dynamics simulation studies. Finally, one compound named Hinokiflavone from Juniperus communis had high binding free energy of -26.54kJ/mol compared with the known inhibitors of MMP-9. Cytotoxicity for hinokiflavone was evaluated by MTT assay. Inhibition of MMP-9 in the presence of hinokiflavone was detected by gelatin zymography and gelatinolytic inhibition assay. Results revealed that the natural compounds derived based on the developed pharmacophore model would be useful for further design and development of MMP-9 inhibitors.

Sulphonamides: Deserving class as MMP inhibitors?

The importance of sulphonamide moiety in medicinal chemistry cannot be ignored as it constitutes an important class of extensively used drugs. Recently, sulphonamides have also been reported for their matrix metalloproteinase (MMP) inhibitory activity. MMPs are calcium- and zinc-dependent endopeptidases, involved in both inter- and intra-cellular activity. This review documents the emergence of sulphonamides as matrix metalloproteinase inhibitors (MMPIs) from the first generation to the recent third generation MMPIs, their mode of action - how sulphonamides act on MMPs? as well as the structure activity relationship along with their therapeutic uses in chronic obstructive pulmonary disease (COPD), ulcer, asthma, arthritis and cancer. From this review, readers can get answer for the question- is sulphonamides a potential class of MMPIs?

Insights into the complex formed by matrix metalloproteinase-2 and alloxan inhibitors: molecular dynamics simulations and free energy calculations

Matrix metalloproteinases (MMP) are well-known biological targets implicated in tumour progression, homeostatic regulation, innate immunity, impaired delivery of pro-apoptotic ligands, and the release and cleavage of cell-surface receptors. Hence, the development of potent and selective inhibitors targeting these enzymes continues to be eagerly sought. In this paper, a number of alloxan-based compounds, initially conceived to bias other therapeutically relevant enzymes, were rationally modified and successfully repurposed to inhibit MMP-2 (also named gelatinase A) in the nanomolar range. Importantly, the alloxan core makes its debut as zinc binding group since it ensures a stable tetrahedral coordination of the catalytic zinc ion in concert with the three histidines of the HExxHxxGxxH metzincin signature motif, further stabilized by a hydrogen bond with the glutamate residue belonging to the same motif. The molecular decoration of the alloxan core with a biphenyl privileged structure allowed to sample the deep S₁′ specificity pocket of MMP-2 and to relate the high affinity towards this enzyme with the chance of forming a hydrogen bond network with the backbone of Leu116 and Asn147 and the side chains of Tyr144, Thr145 and Arg149 at the bottom of the pocket. The effect of even slight structural changes in determining the interaction at the S₁′ subsite of MMP-2 as well as the nature and strength of the binding is elucidated via molecular dynamics simulations and free energy calculations. Among the herein presented compounds, the highest affinity (pIC₅₀ = 7.06) is found for BAM, a compound exhibiting also selectivity (>20) towards MMP-2, as compared to MMP-9, the other member of the gelatinases.

D184E mutation in aquaporin-4 gene impairs water permeability and links to deafness

Aquaporins (AQPs) play a physiological role in several organs and tissues, and their alteration is associated with disorders of water regulation. The identification of molecular interactions, which are crucial in determining the rate of water flux through the channel, is of pivotal role for the discovery of molecules able to target those interactions and therefore to be used for pathologies ascribable to an altered AQP-dependent water balance. In the present study, a mutational screening of human aquaporin-4 (AQP4) gene was performed on subjects with variable degrees of hearing loss. One heterozygous missense mutation was identified in a Spanish sporadic case, leading to an Asp/Glu amino acid substitution at position 184 (D184E). A BLAST analysis revealed that the amino acid D184 is conserved across species, consistently with a crucial role in the structure/function of AQP4 water channels. The mutation induces a significant reduction in water permeability as measured by the Xenopus laevis oocytes swelling assay and by the use of mammalian cells by total internal reflection microscopy. By Western blot, immunofluorescence and 2D Blue Native/SDS-PAGE we show that the reduction in water permeability is not ascribable to a reduced expression of AQP4 mutant protein or to its incorrect plasma membrane targeting and aggregation into orthogonal arrays of particles. Molecular dynamics simulation provided a molecular explanation of the mechanism whereby the mutation induces a loss of function of the channel. Substituting glutamate for aspartate affects the mobility of the D loop, which acquires a higher propensity to equilibrate in a "closed conformation", thus affecting the rate of water flux. We speculate that this mutation, combined with other genetic defects or concurrently with certain environmental stimuli, could confer a higher susceptibility to deafness.

Analysis of X-ray structures of matrix metalloproteinases via chaotic map clustering

Background

Matrix metalloproteinases (MMPs) are well-known biological targets implicated in tumour progression, homeostatic regulation, innate immunity, impaired delivery of pro-apoptotic ligands, and the release and cleavage of cell-surface receptors. With this in mind, the perception of the intimate relationships among diverse MMPs could be a solid basis for accelerated learning in designing new selective MMP inhibitors. In this regard, decrypting the latent molecular reasons in order to elucidate similarity among MMPs is a key challenge.

Results

We describe a pairwise variant of the non-parametric chaotic map clustering (CMC) algorithm and its application to 104 X-ray MMP structures. In this analysis electrostatic potentials are computed and used as input for the CMC algorithm. It was shown that differences between proteins reflect genuine variation of their electrostatic potentials. In addition, the analysis has been also extended to analyze the protein primary structures and the molecular shapes of the MMP co-crystallised ligands.

Conclusions

The CMC algorithm was shown to be a valuable tool in knowledge acquisition and transfer from MMP structures. Based on the variation of electrostatic potentials, CMC was successful in analysing the MMP target family landscape and different subsites. The first investigation resulted in rational figure interpretation of both domain organization as well as of substrate specificity classifications. The second made it possible to distinguish the MMP classes, demonstrating the high specificity of the S₁' pocket, to detect both the occurrence of punctual mutations of ionisable residues and different side-chain conformations that likely account for induced-fit phenomena. In addition, CMC demonstrated a potential comparable to the most popular UPGMA (Unweighted Pair Group Method with Arithmetic mean) method that, at present, represents a standard clustering bioinformatics approach. Interestingly, CMC and UPGMA resulted in closely comparable outcomes, but often CMC produced more informative and more easy interpretable dendrograms. Finally, CMC was successful for standard pairwise analysis (i.e., Smith-Waterman algorithm) of protein sequences and was used to convincingly explain the complementarity existing between the molecular shapes of the co-crystallised ligand molecules and the accessible MMP void volumes.

Structure-based chemogenomics: analysis of protein family landscapes

Analysis of the three-dimensional structures of protein ligand complexes provides valuable insight into both the common interaction patterns within a target family and the discriminating features between the different members of a target family. Knowledge of the common interaction patterns helps to design target family focused chemical libraries for hit finding, while the discriminating features can be exploited to optimize the selectivity profile of a lead compound against particular member of a target family. Herein, we review the computational tools which have been developed to analyze crystal structures of members of a target family.