Analysis of X-ray Structures of Matrix Metalloproteinases via Chaotic Map Clustering

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>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.</p

A k-NN Algorithm for Predicting Oral Sub-Chronic Toxicity in the Rat

Summary Repeated dose toxicity is of the utmost importance to characterize the toxicological profile o

Structure-Based Design and Optimization of Multitarget-Directed 2H-Chromen-2-one Derivatives as Potent Inhibitors of Monoamine Oxidase B and Cholinesterases

The multifactorial nature of Alzheimer’s disease calls for the development of multitarget agents addressing key pathogenic processes. To this end, by following a docking-assisted hybridization strategy, a number of aminocoumarins were designed, prepared, and tested as monoamine oxidases (MAOs) and acetyl- and butyryl-cholinesterase (AChE and BChE) inhibitors. Highly flexible N-benzyl-N-alkyloxy coumarins 2–12 showed good inhibitory activities at MAO-B, AChE, and BChE but low selectivity. More rigid inhibitors, bearing meta- and para-xylyl linkers, displayed good inhibitory activities and high MAO-B selectivity. Compounds 21, 24, 37, and 39, the last two featuring an improved hydrophilic/lipophilic balance, exhibited excellent activity profiles with nanomolar inhibitory potency toward hMAO-B, high hMAO-B over hMAO-A selectivity and submicromolar potency at hAChE. Cell-based assays of BBB permeation, neurotoxicity, and neuroprotection supported the potential of compound 37 as a BBB-permeant neuroprotective agent against H2O2-induced oxidative stress with poor interaction as P-gp substrate and very low cytotoxicity

8‐Aminomethyl‐7‐hydroxy‐4‐methylcoumarins as Multitarget Leads for Alzheimer's Disease

This is the peer reviewed version of the following article: Domínguez, J., Fernández-Nieto, F., Brea, J., Catto, M., Paleo, M., & Porto, S. et al. (2016). 8-Aminomethyl-7-hydroxy-4-methylcoumarins as Multitarget Leads for Alzheimer's Disease. Chemistryselect, 1(11), 2742-2749, which has been published in final form at https://doi.org/10.1002/slct.201600735. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived VersionsThis work is part of our ongoing research in the discovery of multitarget therapeutic agents for Alzheimer's disease (AD). A literature screening, based on our recently proposed pharmacophore, led to the identification of 8‐aminomethyl‐7‐hydroxy‐4‐methyl coumarins as potential multitarget leads for AD. The results of a computer‐assisted protocol developed by us to validate multitarget hits for AD indicated that our coumarin candidates were viable leads only for AChE inhibition as later validated by biological assays. The results of BChE binding and propidium displacement assays indicate that our first generation compounds bind to the PAS site in AChE. We designed new generations of coumarin derivatives with a longer substituent at position 8 aimed at leads with more efficient interaction at the catalytic anionic site (CAS). Inhibition data and docking simulations indicated that an anilino‐capping group reached the CAS region of AChE and determined also a higher inhibitory potency towards BChE. The best compound obtained, with a N‐benzylpiperidine fragment, displayed sub‐micromolar affinity for AChE, affinity for BChE, and precluded Aβ‐amyloid aggregation with a potency similar to that of 9,10‐anthraquinone, making it a multitarget lead viable for further improvementFinancial support from the Ministerio de Economia y Competitividad of Spain (Project CTQ2014‐55208‐P) and the Xunta de Galicia (10CSA209063PR and GRC2014/029) is gratefully acknowledged. The Italian authors thank the University of Bari for partial financial support (Fondi di Ateneo 2014–2015)S

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

A Chemocentric Approach to the Identification of Cancer Targets

A novel chemocentric approach to identifying cancer-relevant targets is introduced. Starting with a large chemical collection, the strategy uses the list of small molecule hits arising from a differential cytotoxicity screening on tumor HCT116 and normal MRC-5 cell lines to identify proteins associated with cancer emerging from a differential virtual target profiling of the most selective compounds detected in both cell lines. It is shown that this smart combination of differential in vitro and in silico screenings (DIVISS) is capable of detecting a list of proteins that are already well accepted cancer drug targets, while complementing it with additional proteins that, targeted selectively or in combination with others, could lead to synergistic benefits for cancer therapeutics. The complete list of 115 proteins identified as being hit uniquely by compounds showing selective antiproliferative effects for tumor cell lines is provided