Prediction of improved antimicrobial mastoparan derivatives by 3D-QSAR-CoMSIA/CoMFA and computational mutagenesis

Natural Compounds Therapeutic Features in Brain Disorders by Experimental, Bioinformatics and Cheminformatics Methods

BACKGROUND

Synthetic compounds with pharmaceutical applications in brain disorders are daily designed and synthesized, with well first effects but also seldom severe side effects. This imposes the search for alternative therapies based on the pharmaceutical potentials of natural compounds. The natural compounds isolated from various plants and arthropods venom are well known for their antimicrobial (antibacterial, antiviral) and antiinflammatory activities, but more studies are needed for a better understanding of their structural and pharmacological features with new therapeutic applications.

OBJECTIVES

Here we present some structural and pharmaceutical features of natural compounds isolated from plants and arthropods venom relevant for their efficiency and potency in brain disorders. We present the polytherapeutic effects of natural compounds belonging to terpenes (limonene), monoterpenoids (1,8-cineole) and stilbenes (resveratrol), as well as natural peptides (apamin, mastoparan and melittin).

METHODS

Various experimental and in silico methods are presented with special attention on bioinformatics (natural compounds database, artificial neural network) and cheminformatics (QSAR, drug design, computational mutagenesis, molecular docking).

RESULTS

In the present paper we reviewed: (i) recent studies regarding the pharmacological potential of natural compounds in the brain; (ii) the most useful databases containing molecular and functional features of natural compounds; and (iii) the most important molecular descriptors of natural compounds in comparison with a few synthetic compounds.

CONCLUSION

Our paper indicates that natural compounds are a real alternative for nervous system therapy and represents a helpful tool for the future papers focused on the study of the natural compounds.

Potential Therapeutic Approaches to Alzheimer's Disease By Bioinformatics, Cheminformatics And Predicted Adme-Tox Tools

BACKGROUND

Alzheimer's disease (AD) is considered a severe, irreversible and progressive neurodegenerative disorder. Currently, the pharmacological management of AD is based on a few clinically approved acethylcholinesterase (AChE) and N-methyl-D-aspartate (NMDA) receptor ligands, with unclear molecular mechanisms and severe side effects.

METHODS

Here, we reviewed the most recent bioinformatics, cheminformatics (SAR, drug design, molecular docking, friendly databases, ADME-Tox) and experimental data on relevant structurebiological activity relationships and molecular mechanisms of some natural and synthetic compounds with possible anti-AD effects (inhibitors of AChE, NMDA receptors, beta-secretase, amyloid beta (Aβ), redox metals) or acting on multiple AD targets at once. We considered: (i) in silico supported by experimental studies regarding the pharmacological potential of natural compounds as resveratrol, natural alkaloids, flavonoids isolated from various plants and donepezil, galantamine, rivastagmine and memantine derivatives, (ii) the most important pharmacokinetic descriptors of natural compounds in comparison with donepezil, memantine and galantamine.

RESULTS

In silico and experimental methods applied to synthetic compounds led to the identification of new AChE inhibitors, NMDA antagonists, multipotent hybrids targeting different AD processes and metal-organic compounds acting as Aβ inhibitors. Natural compounds appear as multipotent agents, acting on several AD pathways: cholinesterases, NMDA receptors, secretases or Aβ, but their efficiency in vivo and their correct dosage should be determined.

CONCLUSION

Bioinformatics, cheminformatics and ADME-Tox methods can be very helpful in the quest for an effective anti-AD treatment, allowing the identification of novel drugs, enhancing the druggability of molecular targets and providing a deeper understanding of AD pathological mechanisms.

Structure-biological function relationship extended to mitotic arrest-deficient 2-like protein Mad2 native and mutants-new opportunity for genetic disorder control

Overexpression of mitotic arrest-deficient proteins Mad1 and Mad2, two components of spindle assembly checkpoint, is a risk factor for chromosomal instability (CIN) and a trigger of many genetic disorders. Mad2 transition from inactive open (O-Mad2) to active closed (C-Mad2) conformations or Mad2 binding to specific partners (cell-division cycle protein 20 (Cdc20) or Mad1) were targets of previous pharmacogenomics studies. Here, Mad2 binding to Cdc20 and the interconversion rate from open to closed Mad2 were predicted and the molecular features with a critical contribution to these processes were determined by extending the quantitative structure-activity relationship (QSAR) method to large-size proteins such as Mad2. QSAR models were built based on available published data on 23 Mad2 mutants inducing CIN-related functional changes. The most relevant descriptors identified for predicting Mad2 native and mutants action mechanism and their involvement in genetic disorders are the steric (van der Waals area and solvent accessible area and their subdivided) and energetic van der Waals energy descriptors. The reliability of our QSAR models is indicated by significant values of statistical coefficients: Cross-validated correlation q² (0.53–0.65) and fitted correlation r² (0.82–0.90). Moreover, based on established QSAR equations, we rationally design and analyze nine de novo Mad2 mutants as possible promoters of CIN.