Deciphering the mechanism and binding interactions of Pemetrexed with dsDNA with DNA-targeted chemotherapeutics via spectroscopic, analytical, and simulation studies.

Pemetrexed is a well-known and widely used antineoplastic drug under the category of cytotoxic, folate anti-metabolites that is used in chemotherapeutic treatments, especially in malignant mesothelioma and non-small cell lung carcinoma. Here, the binding mechanism and interactions of Pemetrexed with double strain fish sperm deoxyribonucleic acid (dsDNA) were studied thoroughly both experimentally and theoretically, using multi-spectroscopic techniques and molecular docking simulations. Our ultimate goal is to understand better the potential of such antineoplastic drugs and, hence, to design drugs with high dsDNA binding affinities and fewer adverse effects. We employed several techniques yielding different but complementary results such as UV, fluorescence, thermal denaturation, electrochemical and viscosity, and molecular docking studies under physiological conditions. Our results revealed that the Pemetrexed binds fairly strongly to dsDNA's minor groove through hydrogen bond interactions with the mostly adenine and guanine bases via its p-carbamide and p-carboxylic groups. MD simulations of the drug-dsDNA complex were followed for 50 ns to confirm that interaction is stable and robust electrostatic interactions were due to hydrogen bonding mostly with the adenine and guanine nucleotides in the minor groove.

Integrated Binary QSAR-Driven Virtual Screening and In Vitro Studies for Finding Novel hMAO-B-Selective Inhibitors.

The increased activity of monoamine oxidase (MAO) enzymes may lead to serious consequences since they reduce the level of neurotransmitters and are associated with severe neurodegenerative diseases. The inhibition of this enzyme, especially the B isoform, plays a vital role in the treatment of Parkinson's disease (PD). This study is aimed to find novel human MAO-B (hMAO-B) selective inhibitors. A total of 256.750 compounds from the Otava small molecules database were virtually screened gradually by employing several screening techniques for this purpose. Initially, a high-throughput virtual screening (HTVS) method was employed, and 10% of the molecules having high docking scores were subjected to binary QSAR models for further screening of their therapeutic activities against PD, Alzheimer's disease (AD), and depression as well as for their toxicity and pharmacokinetic properties. Then, enzyme selectivity of the ligands towards the A and B forms that passed through all the filters were studied using the induced-fit docking method and molecular dynamics simulations. At the end of this exhaustive research, we identified two hit molecules ligand 3 (Otava ID: 7131545) and ligand 4 (Otava ID: 7566820). Based on the in vitro results, these two compounds (ligands 3 and 4) together with ligands 1 and 2 found in our previous study showed activity at the nanomolar (nM) level, and the results indicated that these four ligands inhibit hMAO-B better than the FDA-approved drug selegiline.

Proposing Novel MAO-B Hit Inhibitors Using Multidimensional Molecular Modeling Approaches and Application of Binary QSAR Models for Prediction of Their Therapeutic Activity, Pharmacokinetic and Toxicity Properties.

Monoamine oxidase (MAO) enzymes MAO-A and MAO-B play a critical role in the metabolism of monoamine neurotransmitters. Hence, MAO inhibitors are very important for the treatment of several neurodegenerative diseases such as Parkinson's disease (PD), Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS). In this study, 256 750 molecules from Otava Green Chemical Collection were virtually screened for their binding activities as MAO-B inhibitors. Two hit molecules were identified after applying different filters such as high docking scores and selectivity to MAO-B, desired pharmacokinetic profile predictions with binary quantitative structure-activity relationship (QSAR) models. Therapeutic activity prediction as well as pharmacokinetic and toxicity profiles were investigated using MetaCore/MetaDrug platform which is based on a manually curated database of molecular interactions, molecular pathways, gene-disease associations, chemical metabolism, and toxicity information. Particular therapeutic activity and toxic effect predictions are based on the ChemTree ability to correlate structural descriptors to that property using recursive partitioning algorithm. Molecular dynamics (MD) simulations were also performed to make more detailed assessments beyond docking studies. All these calculations were made not only to determine if studied molecules possess the potential to be a MAO-B inhibitor but also to find out whether they carry MAO-B selectivity versus MAO-A. The evaluation of docking results and pharmacokinetic profile predictions together with the MD simulations enabled us to identify one hit molecule (ligand 1, Otava ID: 3463218) which displayed higher selectivity toward MAO-B than a positive control selegiline which is a commercially used drug for PD therapeutic purposes.