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.

An In Silico Investigation of Potential EGFR Inhibitors for the Clinical Treatment of Colorectal Cancer.

Colorectal cancer possesses the third highest diagnostic rate and is the second leading cause of cancer death in the USA as reported by NIH. Epidermal Growth Factor Receptor (EGFR), a transmembrane protein, participates in PLC gamma-1, RAS-RAF-MEK-MAPKs, phosphatidylinositol-3 kinase, Akt pathways and plays a key role in normal functioning of cell division, cell differentiation, apoptosis and migration. This protein is found to be overexpressed in more than 60% of the colorectal cancers. Overexpressed EGFR advances the tumorigenic properties through cell cycle dysregulation and activates signaling pathways linked to cancer such as WNT/ß-catenin, transforming growth factor ß (TGF-ß) and phosphoinositide-3-kinase (PI3K). Inhibiting the overexpressed EGFR protein has been proposed for the treatment and many inhibitors have been reported suppressing the activity of EGFR. However, patients in malignant state of cancer show resistance to those inhibitors, which open a wide space to research for the discovery of novel inhibitors. The present study employed Molecular Docking and Virtual Screening to find novel inhibitors with high affinity against EGFR. Molecular docking of existing inhibitors resulted in the compound titled as BGB-283 (PubChem CID-89670174) having the highest score, which was subjected to similarity search to retrieve the drugs with similar structure. The virtual screening concluded a compound SCHEMBL18435602 (PubChem CID-126517400) which revealed a better affinity with the target protein. A comparative study of both the compounds showed equivalent pharmacokinetic properties. These identified drugs have a high potential to act as EGFR inhibitors and can show promising results in the research of colorectal cancer.

Development of MLR and SVM Aided QSAR Models to Identify Common SAR of GABA Uptake Herbal Inhibitors used in the Treatment of Schizophrenia.

BACKGROUND: Alterations in GABAnergic system are implicated in the pathophysiology of schizophrenia. Available antipsychotics that target GABA receptor form a desirable therapeutic strategy in the treatment regimen of schizophrenia, unfortunately, suffer serious setback due to their prolonged side effects. The present investigation focuses on developing QSAR models from the biological activity of herbal compounds and their derivatives that promise to be alternative candidates to GABA uptake inhibitors. METHODS: Three sets of compounds were undertaken in the study to develop QSAR models. The first set consisted of nine compounds which included Magnolol, Honokiol and other GABA acting established compounds. The second set consisted of 16 derivatives of N-diarylalkenylpiperidinecarboxylic acid. The third QSAR dataset was made up of thirty two compounds which were Magnolol and Honokiol derivatives. Multiple linear regressions (MLR) and support vector machine (SVM) supervised quantitative structure-activity relationship (QSAR) models were developed to predict the biological activity of these three sets. The purpose of taking three QSAR sets of diverse chemical structures but identical in their GABA targeting and pharmacological action was to identify common chemical structure features responsible for structure-activity relationship (SAR). RESULTS: Linear and non-linear QSAR models confirmed that the three sets shared common structural descriptors derived from WHIM (Weighted Holistic Invariant Molecular descriptors), 3D-MoRSE and Eigenvalue classes. CONCLUSION: It was concluded that properties like electro negativity and polarizability play a crucial role in controlling the activity of herbal compounds against GABA receptor.

Virtual Screening Approaches in Identification of Bioactive Compounds Akin to Delphinidin as Potential HER2 Inhibitors for the Treatment of Breast Cancer.

Small molecule tyrosine kinase inhibitors targeting HER 2 receptors have emerged as an important therapeutic approach in inhibition of downstream proliferation and survival signals for the treatment of breast cancers. Recent drug discovery efforts have demonstrated that naturally occurring polyphenolic compounds like delphinidin have potential to inhibit proliferation and promote apoptosis of breast cancer cells by targeting HER2 receptors. While delphinidin may thus reduce tumour size, it is associated with serious side effects like dysphonia. Owing to the narrow therapeutic window of delphinidin, the present study aimed to identify high affinity compounds targeting HER2 with safer pharmacological profiles than delphinidin through virtual screening approaches. Delphinidin served as the query parent for identification of structurally similar compounds by Tanimoto-based similarity searching with a threshold of 95% against the PubChem database. The compounds retrieved were further subjected to Lipinski and Verber's filters to obtain drug like agents, then further filtered by diversity based screens with a cut off of 0.6. The compound with Pubchem ID: 91596862 was identified to have higher affinity than its parent. In addition it also proved to be non-toxic with a better ADMET profile and higher kinase activity. The compound identified in the study can be put to further in vitro drug testing to complement the present study.

Molecular docking based screening of GABA (A) receptor inhibitors from plant derivatives.

UNLABELLED: The present antipsychotic drugs have known to show serious concerns like extra pyramidal side effects therefore, pursuit for novel antipsychotic GABAnergic drugs has lately focused on the folkloric medicine from plant derivatives as better treatment option of schizophrenia. The present study centers to identify potential inhibitors of plant origin for GABA receptor through in silico approaches. Three compound datasets were undertaken in the study. The first set consisted of seven compounds which included Magnolol, Honokiol and other plant derivatives. The second set consisted of 16 derivatives of N-diarylalkenyl-piperidinecarboxylic acid synthesized by Zheng et al., 2006. The third dataset had thirty two compounds which were Magnolol and Honokiol analogues synthesized by Fuchs et al., 2014. All the compounds were docked at the allosteric site of the GABA (A) receptor. The compounds were further tested for ADMET and biological activity. We observed Honokiol and its derivatives demonstrated superior druglike properties than any compound undertaken in the study. Further, compound 61 [2-(4-methoxyphenyl)-4-propylphenol] of dataset three - a synthetic derivative of honokiol had better profile than its parent compound. In a possible attempt to identify compound with even better efficacious compound than 61, virtual screening was performed, 135 compounds akin to compound 61 were retrieved. Interestingly none of the 135 compounds showed better druggable properties than compound 61. Our in silico pharmacological profiling of compounds is in coherence and is complemented by the findings of Fuchs et al, which also revealed compound 61 to be the good potentiator of GABA receptor. ABBREVIATIONS: GABA (A) R - Gamma Amino Butyric Acid Receptor, subtype A, GPCR - G Protein Coupled Receptor, OPLS - Optimized Potentials for Liquid Simulations, PDB - Protein Data Bank, PLP - Piece wise Linear Potential, T.E.S.T - Toxicity Estimation Software Tool, TCM - Traditional Chinese Medicine.

Identification of High Affinity Non-Peptidic Small Molecule Inhibitors of MDM2-p53 Interactions through Structure-Based Virtual Screening Strategies.

BACKGROUND: Approaches in disruption of MDM2-p53 interactions have now emerged as an important therapeutic strategy in resurrecting wild type p53 functional status. The present study highlights virtual screening strategies in identification of high affinity small molecule non-peptidic inhibitors. Nutlin3A and RG7112 belonging to compound class of Cis-imidazoline, MI219 of Spiro-oxindole class and Benzodiazepine derived TDP 665759 served as query small molecules for similarity search with a threshold of 95%. The query molecules and the similar molecules corresponding to each query were docked at the transactivation binding cleft of MDM2 protein. Aided by MolDock algorithm, high affinity compound against MDM2 was retrieved. Patch Dock supervised Protein-Protein interactions were established between MDM2 and ligand (query and similar) bound and free states of p53. Compounds with PubCid 68870345, 77819398, 71132874, and 11952782 respectively structurally similar to Nutlin3A, RG7112, Mi219 and TDP 665759 demonstrated higher affinity to MDM2 in comparison to their parent compounds. Evident from the protein-protein interaction studies, all the similar compounds except for 77819398 (similar to RG 7112) showed appreciable inhibitory potential. Of particular relevance, compound 68870345 akin to Nutlin 3A had highest inhibitory potential that respectively showed 1.3, 1.2, 1.16 and 1.26 folds higher inhibitory potential than Nutilin 3A, MI 219, RG 7112 and TDP 1665759. Compound 68870345 was further mapped for structure based pharamacophoric features. In the study, we report Cis-imidazoline derivative compound; Pubcid: 68870345 to have highest inhibitory potential in blocking MDM2-p53 interactions hitherto discovered.

Identification and Pharmacological Analysis of High Efficacy Small Molecule Inhibitors of EGF-EGFR Interactions in Clinical Treatment of Non-Small Cell Lung Carcinoma: a Computational Approach.

Inhibition of EGFR-EGF interactions forms an important therapeutic rationale in treatment of non-small cell lung carcinoma. Established inhibitors have been successful in reducing proliferative processes observed in NSCLC, however patients suffer serious side effects. Considering the narrow therapeutic window of present EGFR inhibitors, the present study centred on identifying high efficacy EGFR inhibitors through structure based virtual screening strategies. Established inhibitors - Afatinib, Dacomitinib, Erlotinib, Lapatinib, Rociletinib formed parent compounds to retrieve similar compounds by linear fingerprint based tanimoto search with a threshold of 90%. The compounds (parents and respective similars) were docked at the EGF binding cleft of EGFR. Patch dock supervised protein-protein interactions were established between EGF and ligand (query and similar) bound and free states of EGFR. Compounds ADS103317, AKOS024836912, AGN-PC-0MXVWT, GNF-Pf-3539, SCHEMBL15205939 were retrieved respectively similar to Afatinib, Dacomitinib, Erlotinib, Lapatinib, Rociletinib. Compound- AGN-PC-0MXVWT akin to Erlotinib showed highest affinity against EGFR amongst all the compounds (parent and similar) assessed in the study. Further, AGN-PC-0MXVWT brought about significant blocking of EGFR-EGF interactions in addition showed appreciable ADMET properties and pharmacophoric features. In the study, we report AGN-PC-0MXVWT to be an efficient and high efficacy inhibitor of EGFR-EGF interactions identified through computational approaches.