Virtual Screening, Molecular Interaction Field, Molecular Dynamics, Docking, Density Functional, and ADMET Properties of Novel AChE Inhibitors in Alzheimer's Disease

3D-QSAR, molecular docking, simulation dynamic and ADMET studies on new quinolines derivatives against colorectal carcinoma activity

Cancer is the uncontrolled spread of abnormal cells that results in abnormal tissue growth in the affected organ. One of the most important organs is exposed to the growth of colon cancer cells, which start in the large intestine (colon) or the rectum. Several therapeutic protocols were used to treat different kinds of cancer. Recently, several studies have targeted tubulin and microtubules due to their remarkable prefoliation. Also, recent research shows that quinoline compounds have significant efficacy against human colorectal cancer. So, the present work investigated the potential of thirty quinoline compounds as tubulin inhibitors using computational methods. A 3D-QSAR approach using two contours (CoMFA and CoMSIA), molecular docking simulation to determine the binding type of the complexes (ligand-receptor), molecular dynamics simulation and identifying pharmacokinetic characteristics were used to design molecules. For all compounds designed (T1-5), molecular docking was used to compare the stability by type of binding. The ADMET has been utilized for molecules with good stability in molecular docking (T1-3); these compounds have good medicinal characteristics. Furthermore, a molecular dynamics simulation (MD) at 100 ns was performed to confirm the stability of the T1-3 compounds; the molecules (T1-3) remained the most stable throughout the simulation. The compounds T1, T2 and T3 are the best-designed drugs for colorectal carcinoma treatments.Communicated by Ramaswamy H. Sarma.

Allosteric Modulators of Potential Targets Related to Alzheimer's Disease: a Review

Among neurodegenerative disorders, Alzheimer's disease (AD) is the most common type of dementia, and there is an urgent need to discover new and efficacious forms of treatment for it. Pathological patterns of AD include cholinergic dysfunction, increased β-amyloid (Aβ) peptide concentration, the appearance of neurofibrillary tangles, among others, all of which are strongly associated with specific biological targets. Interactions observed between these targets and potential drug candidates in AD most often occur by competitive mechanisms driven by orthosteric ligands that sometimes result in the production of side effects. In this context, the allosteric mechanism represents a key strategy; this can be regarded as the selective modulation of such targets by allosteric modulators in an advantageous manner, as this may decrease the likelihood of side effects. The purpose of this review is to present an overview of compounds that act as allosteric modulators of the main biological targets related to AD.

In Silico Studies in Drug Research Against Neurodegenerative Diseases

Background

Neurodegenerative diseases such as Alzheimer's disease (AD), amyotrophic lateral sclerosis, Parkinson's disease (PD), spinal cerebellar ataxias, and spinal and bulbar muscular atrophy are described by slow and selective degeneration of neurons and axons in the central nervous system (CNS) and constitute one of the major challenges of modern medicine. Computer-aided or in silico drug design methods have matured into powerful tools for reducing the number of ligands that should be screened in experimental assays.

Methods

In the present review, the authors provide a basic background about neurodegenerative diseases and in silico techniques in the drug research. Furthermore, they review the various in silico studies reported against various targets in neurodegenerative diseases, including homology modeling, molecular docking, virtual high-throughput screening, quantitative structure activity relationship (QSAR), hologram quantitative structure activity relationship (HQSAR), 3D pharmacophore mapping, proteochemometrics modeling (PCM), fingerprints, fragment-based drug discovery, Monte Carlo simulation, molecular dynamic (MD) simulation, quantum-mechanical methods for drug design, support vector machines, and machine learning approaches.

Results

Detailed analysis of the recently reported case studies revealed that the majority of them use a sequential combination of ligand and structure-based virtual screening techniques, with particular focus on pharmacophore models and the docking approach.

Conclusion

Neurodegenerative diseases have a multifactorial pathoetiological origin, so scientists have become persuaded that a multi-target therapeutic strategy aimed at the simultaneous targeting of multiple proteins (and therefore etiologies) involved in the development of a disease is recommended in future.

Exploring putative inhibitors of Death Associated Protein Kinase 1 (DAPK1) via targeting Gly-Glu-Leu (GEL) and Pro-Glu-Asn (PEN) substrate recognition motifs

Recently, a new signaling complex Death Associated Protein Kinase 1 (DAPK1) ̶ N-methyl-D-aspartate receptor subtype 2B (NMDAR2B or NR2B) engaged in the neuronal death cascade was identified and it was found that after stroke injury, N-methyl-D-aspartate glutamate (NMDA) receptors interact with DAPK1 through NR2B subunit and lead to excitotoxicity via over-activation of NMDA receptors. An acute brain injury, such as stroke, is a serious life-threatening medical condition which occurs due to poor blood supply to the brain and further leads to neuronal cell death. During a stroke, activated DAPK1 migrates towards the extra-synaptic site and binds to NR2B subunit of NMDA receptor. It is this DAPK1-NR2B interaction that arbitrates the pathological processes like apoptosis, necrosis, and autophagy of neuronal cells observed in stroke injury, hence we aimed to inhibit this vital interaction to prevent neuronal damage. In the present study, using PubChem database, we applied an integrative approach of virtual screening and molecular dynamic simulations and identified a potential lead compound 11 that interrupts DAPK1-NR2B interaction by competing with both ATP and substrate for their binding sites on DAPK1. This inhibitor was found potent and considerably selective to DAPK1 as it made direct contact with the ATP binding sites as well as substrate recognition motifs: Gly-Glu-Leu (GEL) and Pro-Glu-Asn (PEN). Further in vitro and in vivo experiments are demanded to validate the efficacy of compound 11 nevertheless, it can be considered as suitable starting point for designing DAPK1 inhibitors.

Current insights into computer-aided immunotherapeutic design strategies

Drug designing costs as well as design of immunotherapeutic agents could be nearly halved through the involvement of computer-aided drug designing methods in discovery and research. The inter-disciplinary, time-, and money-consuming process of drug discovery is amended by the development of drug designing, the technique of creating or finding a molecule that can render stimulatory or inhibitory activity upon various biological organisms. Meanwhile, the advancements made within this scientific domain in the last couple of decades have significantly modified and affected the way new bioactive molecules have been produced by the pharmaceutical industry. In this regard, improvements made in hardware solutions and computational techniques along with their efficient integration with biological processes have revolutionized the in silico methods in speeding up the lead identification and optimization processes. In this review, we will discuss various methods of recent computer-aided drug designing techniques that forms the basis of modern day drug discovery projects.

In silico design and search for acetylcholinesterase inhibitors in Alzheimer's disease with a suitable pharmacokinetic profile and low toxicity

Alzheimer's disease is a complex neurodegenerative disorder of the central nervous system, characterized by amyloid-β deposits, τ-protein aggregation, oxidative stress and reduced levels of acetylcholine in the brain. One pharmacological approach is to restore acetylcholine level by inhibiting acetylcholinesterase (AChE) with reversible inhibitors, such as galanthamine, thus helping to improve the cognitive symptoms of the disease. In order to design new galanthamine derivatives and search for novel, potential inhibitors with improved interactions, as well as a suitable pharmacokinetic profile and low toxicity, several molecular modeling techniques were applied. These techniques included the investigation of AChE-drug complexes (1QT1 and 1ACJ Protein Data Bank codes), ligand-binding sites calculation within the active site of the enzyme, pharmacophore perception of galanthamine derivatives, virtual screening, toxicophorical analysis and estimation of pharmacokinetics properties. A total of four galanthamine derivatives having a N-alkyl-phenyl chain were designed, since the tertiary amine substituents could reach the peripheral anionic site that is not occupied by galanthamine. In addition, 12 drug-like compounds from the Ilibdiverse database were selected by virtual screening as novel, hypothetical AChE inhibitors. The toxicophorical analysis revealed that only four proposed inhibitors have chemical groups able to develop mutagenicity and chromosome damage. The remaining compounds showed only mild or none toxicophorical alerts. At least three screened compounds presented theoric parameters consistent with good oral bioavailability. The designed molecules have the potential to become new lead compounds that might guide the design of drugs with optimized pharmacodynamic and pharmacokinetic properties in order to improve the treatment of Alzheimer's disease by creating new pharmacotherapeutic options.

Molecular interactions of cholinesterases inhibitors using in silico methods: current status and future prospects

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by a low amount of acetylcholine (ACh) in hippocampus and cortex. Acetylcholinesterase (AChE) is one of the most important enzymes in many living organisms including human being and other vertebrates, insects like mosquitoes, among others. Several reports have been published where it has been clearly shown that the genesis of amyloid protein plaques associated with AD is connected to modifications of both AChE and butyrylcholinesterase (BChE), since the plaque is significantly decreased in AD patients using cholinesterase inhibitors (ChEIs). This review gives some examples of these inhibitors discovered during past couple of years that have shown very prominent interactions at the active site triad of the proteins as well as different other parts of the active site like, peripheral anionic site (PAS), oxyanionic hole, anionic subsite or acyl binding pocket (ABP). Most of the inhibition and their interactions have been visualized by X-ray crystallography, but some of the other inhibitors have been studied either by molecular docking or molecular dynamic (MD) simulations or by both the in silico methods. Some of these prominent studies have been crucially observed and reported here.

Current topics in computer-aided drug design

The addition of computer-aided drug design (CADD) technologies to the research and drug discovery approaches could lead to a reduction of up to 50% in the cost of drug design. Designing a drug is the process of finding or creating a molecule which has a specific activity on a biological organism. Development and drug discovery is a time-consuming, expensive, and interdisciplinary process whereas scientific advancements during the past two decades have altered the way pharmaceutical research produces new bioactive molecules. Advances in computational techniques and hardware solutions have enabled in silico methods to speed up lead optimization and identification. We will review current topics in computer-aided molecular design underscoring some of the most recent approaches and interdisciplinary processes. We will discuss some of the most efficient pathways and design.