Identification of High-affinity Small Molecules Targeting Gamma Secretase for the Treatment of Alzheimer's Disease.

BACKGROUND: Alzheimers Disease (AD) is a neurodegenerative disease which is characterized by the deposition of amyloid plaques in the brain- a concept supported by most of the researchers worldwide. The main component of the plaques being amyloid-beta (Aß42) results from the sequential cleavage of Amyloid precursor protein (APP) by beta and gamma secretase. This present study intends to inhibit the formation of amyloid plaques by blocking the action of gamma secretase protein with Inhibitors (GSI). METHODS: A number of Gamma Secretase Inhibitors (GSI) were targeted to the protein by molecular docking. The inhibitor having the best affinity was used as a subject for further virtual screening methods to obtain similar compounds. The generated compounds were docked again at the same docking site on the protein to find a compound with higher affinity to inhibit the protein. The highlights of virtually screened compound consisted of Pharmacophore Mapping of the docking site. These steps were followed by comparative assessments for both the compounds, obtained from the two aforesaid docking studies, which included interaction energy descriptors, ADMET profiling and PreADMET evaluations. RESULTS: 111 GSI classified as azepines, sulfonamides and peptide isosteres were used in the study. By molecular docking an amorpholino-amide, compound (22), was identified to be the high affinity compound GSI along with its better interaction profiles.The virtually screened pubchem compound AKOS001083915 (CID:24462213) shows the best affinity with gamma secretase. Collective Pharmacophore mapping (H bonds, electrostatic profile, binding pattern and solvent accesibility) shows a stable interaction. The resulting ADMETand Descriptor values were nearly equivalent. CONCLUSION: These compounds identified herein hold a potential as Gamma Secretase inhibitors.According to PreADMET values the compound AKOS001083915 is effective and specific to the target protein. Its BOILED-egg plot analysis infers the compound permeable to blood brain barrier.Comparative study for both the compounds resulted in having nearly equivalent properties. These compounds have the capacity to inhibit the protein which is indirectly responsible for the formation of amyloid plaques and can be further put to in vitro pharmacokinetic and dynamic studies.

Structure-Based Virtual Screening for the Identification of High Affinity Compounds as Potent VEGFR2 Inhibitors for the Treatment of Renal Cell Carcinoma.

INTRODUCTION: Renal Cell Carcinoma is a common type of renal cancer-causing deaths worldwide which is characterized by sustained angiogenesis. VEGF and its receptors play a major role in physiologic and pathologic angiogenesis, which is marked in tumour progression and metastasis development. Induction of VEGF genes occur due to hypoxic condition induced by tumour growth after a critical size in cancerous cell. Signal transduction networks originated by VEGFA/VEGFR2, (a notable ligand-receptor complex in the VEGF system) leads to major angiogenesis events ranging from endothelial cell proliferation, to new vessel formation, Furthermore, differential expression of VEGF-VEGFR mRNA also found in different types of RCC. AIM: The aim of present study is to inhibit the VEGFR2 protein by the action of certain inhibitors and then to search an efficient inhibitor. MATERIALS AND METHODS: A total of 23 potential inhibitors were searched and used to target the protein using the concept of molecular docking. Among 23 inhibitors, CHEMBL346631 shows best affinity with the target protein and was used for high throughput virtual screening to find similar compounds. The compound obtained from virtual screeningSCHEMBL469307, shows much more better affinity with VEGFR2 than CHEMBL346631. CONCLUSION: Relative study for both the compounds showed a minor difference in relevant properties. The compound SCHEMBL469307 have a high potential to inhibit the VGFR2 protein and can be backed for future studies in Renal Cell Carcinoma.

Molecular dynamic simulations reveal suboptimal binding of salbutamol in T164I variant of ß2 adrenergic receptor.

The natural variant C491T (rs1800088) in ADRB2 gene substitutes Threonine to Isoleucine at 164th position in ß2AR and results in receptor sequestration and altered binding of agonists. Present investigation pursues to identify the effect of T164I variation on function and structure of ß2AR through systematic computational approaches. The study, in addition, addresses altered binding of salbutamol in T164I variant through molecular dynamic simulations. Methods involving changes in free energy, solvent accessibility surface area, root mean square deviations and analysis of binding cavity revealed structural perturbations in receptor to incur upon T164I substitution. For comprehensive understanding of receptor upon substitution, OPLS force field aided molecular dynamic simulations were performed for 10 ns. Simulations revealed massive structural departure for T164I ß2AR variant from the native state along with considerably higher root mean square fluctuations of residues near the cavity. Affinity prediction by molecular docking showed two folds reduced affinity of salbutamol in T164I variant. To validate the credibility docking results, simulations for ligand-receptor complex were performed which demonstrated unstable salbutamol-T164I ß2AR complex formation. Further, analysis of interactions in course of simulations revealed reduced ligand-receptor interactions of salbutamol in T164I variant. Taken together, studies herein provide structural rationales for suboptimal binding of salbutamol in T164I variant through integrated molecular modeling approaches.