Molecular Design Targeting On Tau Protein For Alzheimer’s Disease

Alzheimer’s disease (AD), commonly known as senile dementia, is a commonneurodegenerative disease. It is characterized by the presence of numerous extracellularamyloid plaques due to amyloid-β abnormal deposition in the brain and of intracellularneurofibrillary tangles (NFTs) resulting from Tau protein self-aggregation process. Withthe increase of human life span and the aging of population, this disease has brought ahuge economic burden and mental stress to both family and society, but currently thereis no known cure. Faced with this situation, new highly potent anti-AD drug discoveryis urgently needed. In recent years, the drug discovery targeting on Tau protein hasattracted an increasing number of researchers, and Tau protein self-aggregationinhibitors and GSK3β inhibitors are exactly the typical representatives amongtherapeutic strategies targeting on Tau protein.In this paper, R-group search technology based on Topomer CoMFA model wasemployed in studies on molecular design of Phenylthiazolyl-Hydrazide (PTH)derivatives, Aminothienopyridazine (ATPZ) derivatives,3-Anilino-4-arylmaleimidederivatives, pyrazolopyrimidine derivatives and pyrazol-5-one derivatives. Among fivesystems, PTHs and ATPZs are Tau protein self-aggregation inhibitors and the last threesystems targeting on GSK3β can inhibit Tau protein hyperphosphorylation. In addition,molecular docking was used to meticulously study the binding moede between GSK3βreceptor and its lignds. The research results are as follows:①T au protein self-aggregation inhibitors–PTH derivatives: Topomer CoMFA wasemployed in three-dimensional quantitative structure-activity relationship (3D-QSAR)study of26samples. The Topomer CoMFA model had good fitting ability and predictiveability. The optimum principal components, r~2, q~2, r~2predof the model are5,0.971,0.519and0.889, respectively. The model was used to search R-groups with special activitycontribution from ZINC database. Using sample1with the highest activity as thetemplate, we employed the R-groups selected to alternately substitute for thecorresponding R-groups of sample1; as a result, we got a total of25new compoundsand their activities were further predicted by the Topomer CoMFA model, and20ofthem had higher activity than the template molecule. This research showed thatTopomer Search could be effectively used in molecular design; meanwhile, themolecules designed provide new candidate drugs for drug development of AD. ②T au protein self-aggregation inhibitors–ATPZ derivatives: R-groups of56samples are bulky and their structures are complex, so the Topomer CoMFA model wasnot ideal. Then Bayesian statistical method using the general descriptors proposed byPaul Labute was employed in two-dimensional quantitative structure-activityrelationship (2D-QSAR) study of56samples. As a result, the model had good fittingability and predictive ability. Accuracy rate of the model predicting no activity samplesreached100%, that of the model predicting activity samples attained73.3%, and theresult of20test set samples to verify the model was good. Hence, this model could beused to predict the activity of new ATPZs compounds, and the model showed thathydrophobic, polarization rate and electrostatic interaction are important molecularproperties which influence molecular activity.③G SK3β inhibitors–3-Anilino-4-arylmaleimide derivatives:3Topomer CoMFA3D-QSAR model were established by different cutting modes, and the r~2, q~2, r~2predof theoptimal model are0.928,0.790and0.726, respectively. Based on this model, R-groupsearch technology was used to obtain R-groups with special activity contribution fromZINC database containing125058drug-like compounds. We employed the5R1-groupsand2R2-groups selected to alternately substitute for the R1and R2of sample44; as aresult, we got a total of10new molecules and their activities were further predicted bythe optimal Topomer CoMFA model. It turned out that their molecular activity valueswere all higher than that of the template molecule. In addition, Molecular dockingresults showed that hydrogen bonding interaction, hydrophobic interaction andelectrostatic interaction are main factors affecting binding affinity; Arg141is mainlyinvolved in the specific ligand-kinase interactions, while residues Asp133, Val135,Gln185and Thr138are responsible for the binding affinity.④G SK3β inhibitors–pyrazolopyrimidine derivatives: Using4different cuttingmodes to establish Topomer CoMFA model, to our disappointment, none of them issatisfactory. Later, molecular docking was employed to predict the binding orientationof small molecule to the protein target with purpose to predict the binding affinity of thesmall molecules. Molecular docking results show that the main interactions betweenligand and GSK3β are hydrogen bonding interaction, hydrophobic interaction andelectrostatic interaction, and Van der Waals interaction also affects ligand activity;Val135, Val70, Ile62, Leu132, Val135, Leu188, H2O568, Lys183, Lys85, Gln185arekey residues for ATP competitive GSK3β inhibitors.⑤G SK3β inhibitors–pyrazol-5-one derivatives: To illuminate the relationship between the structure of R-groups and molecular activities, Topomer CoMFA wasemployed in three-dimensional quantitative structure-activity relationship (3D-QSAR)study of49pyrazol-5-one derivatives with the same core structure. The optimumprincipal components, r~2, q~2, r~2predof the model are3,0.839,0.623and0.526,respectively. The model was used to search R-groups with special activity contributionfrom ZINC database. By No.1molecule filtering, there were4R1-groups and4R2-groups selected. We used them to alternately substitute for the R1and R2of sample1; as a result, we got a total of16new compounds and their predicted activities werehigher than that of the template molecule. Furthermore, molecular docking resultsshowed that hydrogen bonding interaction and electrostatic interaction are key factorsaffecting binding affinity; Asp133, Val135, Asp200, Lys85, Gln185and Lys183arecritical residues for hydrogen bonding interaction. Based on this part research,suggestions in designing pyrazol-5-one derivatives as GSK3β inhibitors: bulky andelectronegative groups at the para-position of ring A, bulky and hydrophobic groups atthe meta-position of ring C, minor and electronegative substituents at the para-positionof ring C and electropositive and hydrophilic groups at the ortho-position of ring C arefavorable for the inhibitory activity.