A study on quantitative structure–activity relationship and molecular docking of metalloproteinase inhibitors based on L-tyrosine scaffold

Abstract

BackgroundMMP-2 enzyme is a kind of matrix metalloproteinases that digests the denatured collagens and gelatins. It is highly involved in the process of tumor invasion and has been considered as a promising target for cancer therapy. The structural requirements of an MMP-2 inhibitor are: (1) a functional group that binds the zinc ion, and (2) a functional group which interacts with the enzyme backbone and the side chains which undergo effective interactions with the enzyme subsites.MethodsIn the present study, a QSAR model was generated to screen new inhibitors of MMP-2 based on L–hydroxy tyrosine scaffold. Descriptors generation were done by Hyperchem 8, DRAGON and Gaussian98W programs. SPSS and MATLAB programs have been used for multiple linear regression (MLR) and genetic algorithm partial least squares (GA-PLS) analyses and for theoretical validation. Applicability domain of the model was performed to screen new compounds. The binding site potential of all inhibitors was verified by structure-based docking according to their binding energy and then the best inhibitors were selected.ResultsThe best QSAR models in MLR and GA-PLS were reported, with the square correlation coefficient for leave-one-out cross-validation (Q2LOO) larger than 0.921 and 0.900 respectively. The created MLR and GA-PLS models indicated the importance of molecular size, degree of branching, flexibility, shape, three-dimensional coordination of different atoms in a molecule in inhibitory activities against MMP-2.The docking study indicated that lipophilic and hydrogen bonding interactions among the inhibitors and the receptor are involved in a ligand-receptor interaction. The oxygen of carbonyl and sulfonyl groups is important for hydrogen bonds of ligand with Leu82 and Ala83. R2 and R3 substituents play a main role in hydrogen bonding interactions. R1 is sited in the hydrophobic pocket. Methylene group can help a ligand to be fitted in the lipophilic pocket, so two methylene groups are better than one. The Phenyl group can create a π-π interaction with Phe86.ConclusionsThe QSAR and docking analyses demonstrated to be helpful tools in the prediction of anti-cancer activities and a guide to the synthesis of new metalloproteinase inhibitors based on L-tyrosine scaffold.

Deciphering the Inhibition Mechanism of under Trial Hsp90 Inhibitors and Their Analogues: A Comparative Molecular Dynamics Simulation

“…Computational studies have revealed their importance in understanding of biological systems through reliable tools. , The advent of computer speed and capacity took scientists to the level of extracting intricate details through multiscale simulation of biomolecules . To obtain new inhibitors, molecular docking and MD simulations are important techniques to have an insight into mechanisms of macromolecules and to conduct inexpensive investigations against databases. − In recent studies, fascinating work reported against Hsp90 inhibition mechanism through 3D-QSAR approach by building a pharmacophore model of hydrogen bond acceptor, hydrogen bond donor and hydrophobic groups against Hsp90 inhibitors. − These studies are performed on different training data sets of compounds and provided the most suitable pharmacophore features which are essential for the Hsp90 binding mechanism. Meanwhile, in-silico pipelines are applied via structure/ligand-based drug design which considers a binding site favored orientation conformation and estimates the stability of protein–ligand interactions to develop a new drug molecule. , Docking methods build a stable complex via offering preferred orientations and energies of a ligand with the active site of a receptor molecule.…”

Synthesis, docking studies, in vitro cytotoxicity evaluation and DNA damage mechanism of new tyrosine‐based tripeptides

“…[ 3,7,47 ] The ability of peptides to bind to different receptors and be a part of various biochemical pathways allows them to function as potential diagnostic tools and biomarkers. [ 48–55 ]…”

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

“…Apart from that, various ligand-based and structure-based drug design strategies (such as 2D-QSAR; HQSAR; classification-based QSAR through linear discriminant analysis, recursive partitioning, and Bayesian classification; machine learning approaches such as support vector machine (SVM), k -nearest neighbor ( k -NN), decision tree (DT), and random forest (RF); 3D-QSAR pharmacophore mapping; CoMFA, CoMSIA, and topomer CoMFA; 4D-QSAR; molecular docking and MD simulation) have already been carried out by various groups of researchers to accelerate the design and discovery of potential MMPIs targeting the medium-size S1′ pockets for the management of several disease conditions (Table S2). ,,− …”

“…4 These MMPs are grouped into six different classes based on their substrate specificity, i.e., (i) collagenases development of tumors and the invasion of inflammatory cells. 5 As far as the MMPIs are concerned, many of the firstgeneration MMPIs were generally nonselective but some MMPIs exhibited selectivity toward a particular MMP having affinities against others. On the basis of the experimental and clinical evidence associated with MMPs regarding tumor progression and poor prognosis, several MMPIs were designed, synthesized, and evaluated in clinical trials from the late 1980s up to the early 2000s for the management of various types of cancers.…”

“…These MMPs are grouped into six different classes based on their substrate specificity, i.e., (i) collagenases (MMP-1, MMP-8, MMP-13, MMP-18), (ii) gelatinases (MMP-2, MMP-9), (iii) matrilysins (MMP-7, MMP-26), (iv) stromelysins (MMP-3, MMP-10, MMP-11), (v) MT-MMPs (MMP-14, MMP-15, MMP-16, MMP-17, MMP-24, MMP-25), and (vi) miscellaneous MMPs (MMP-12, MMP-19, MMP-20, MMP-21, MMP-22, MMP-23, MMP-28, MMP-29). MMPs are found to execute significant roles in the development of tumors and the invasion of inflammatory cells …”