Design, synthesis and biological evaluation of novel copper-chelating acetylcholinesterase inhibitors with pyridine and N-benzylpiperidine fragments.

Cholinergic depletion is the direct cause of disability and dementia among AD patients. AChE is a classical and key target of cholinergic disorders. Some new inhibitors of AChE combining pyridine, acylhydrazone and N-benzylpiperidine fragments were developed in this work. The hit structure was optimized to yield the compound 21 with an IC50 value of 6.62 nM against AChE, while almost no inhibitory effect against BChE. ADMET predictions and PAMPA permeability evaluation showed good drug-like property. The higher activity with an intermediate alkyl chain substitution indicates a new binding mode of inhibitor with AChE. This finding provides new insights into the binding mechanism and is helpful for discovery of novel high-activity AChE inhibitors.

Discovery of FIXa inhibitors by combination of pharmacophore modeling, molecular docking, and 3D-QSAR modeling.

Human Coagulation Factor IXa (FIXa), specifically inhibited at the initiation stage of the blood coagulation cascade, is an excellent target for developing selective and safe anticoagulants. To explore this inhibitory mechanism, 86 FIXa inhibitors were selected to generate pharmacophore models and subsequently SAR models. Both best pharmacophore model and ROC curve were built through the Receptor-Ligand Pharmacophore Generation module. CoMFA model based on molecular docking and PLS factor analysis methods were developed. Model propagations values are q2 = 0.709, r2 = 0.949, and r2pred = 0.905. The satisfactory q2 value of 0.609, r2 value of 0.962, and r2pred value of 0.819 for CoMSIA indicated that the CoMFA and CoMSIA models are both available to predict the inhibitory activity on FIXa. On the basis of pharmacophore modeling, molecular docking, and 3D-QSAR modeling screening, six molecules are screened as potential FIXa inhibitors.

Pharmacophore modeling, molecular docking and molecular dynamics studies on natural products database to discover novel skeleton as non-purine xanthine oxidase inhibitors.

Gout is a common inflammatory arthritis caused by the deposition of urate crystals within joints. It is increasingly in prevalence during the past few decades as shown by the epidemiological survey results. Xanthine oxidase (XO) is a key enzyme to transfer hypoxanthine and xanthine to uric acid, whose overproduction leads to gout. Therefore, inhibiting the activity of xanthine oxidase is an important way to reduce the production of urate. In the study, in order to identify the potential natural products targeting XO, pharmacophore modeling was employed to filter databases. Here, two methods, pharmacophore based on ligand and pharmacophore based on receptor-ligand, were constructed by Discovery Studio. Then GOLD was used to refine the potential compounds with higher fitness scores. Finally, molecular docking and dynamics simulations were employed to analyze the interactions between compounds and protein. The best hypothesis was set as a 3D query to screen database, returning 785 and 297 compounds respectively. A merged set of the above 1082 molecules was subjected to molecular docking, which returned 144 hits with high-fitness scores. These molecules were clustered in four main kinds depending on different backbones. What is more, molecular docking showed that the representative compounds established key interactions with the amino acid residues in the protein, and the RMSD and RMSF of molecular dynamics results showed that these compounds can stabilize the protein. The information represented in the study confirmed previous reports. And it may assist to discover and design new backbones as potential XO inhibitors based on natural products.

Discovery of novel indoleamine 2,3-dioxygenase 1 (IDO1) inhibitors by virtual screening.

In this study, a combination of virtual screening methods were utilized to identify novel potential indoleamine 2,3-dioxygenase 1 (IDO1) inhibitors. A series of IDO1 potential inhibitors were identified by a combination of following steps: Lipinski's Rule of Five, Veber rules filter, molecular docking, HipHop pharmacophores, 3D-Quantitative structure activity relationship (3D-QSAR) studies and Pan-assay Interference Compounds (PAINS) filter. Three known categories of IDO1 inhibitors were used to constructed pharmacophores and 3D-QSAR models. Four point pharmacophores (RHDA) of IDO1 inhibitors were generated from the training set. The 3D-QSAR models were obtained using partial least squares (PLS) analyze based on the docking conformation alignment from the training set. The leave-one-out correlation (q2) and non-cross-validated correlation coefficient (r2pred) of the best CoMFA model were 0.601 and 0.546, and the ones from the best CoMSIA model were 0.506 and 0.541, respectively. Six hits from Specs database were identified and analyzed to confirm their binding modes and key interactions to the amino acid residues in the protein. This work may provide novel backbones for new generation of inhibitors of IDO1.

Pharmacophore modeling, molecular docking and molecular dynamics simulations toward identifying lead compounds for Chk1.

Checkpoint kinase 1 (Chk1), a serine/threonine protein kinase, plays an important role in G2/M checkpoint, which is a key regulator in response to DNA damage. In this study, the structure-based drug design approach and molecular dynamics (MD) simulations were used to explore potent Chk1 inhibitors. A series of the best fitting candidates were picked out from the Specs database. Out of these, five candidates were submitted for MD simulations to explore the stability of complex. The result indicates that these five candidates could be considered potential Chk1 inhibitors and represents a promising starting point for developing potent inhibitors of Chk1 for the treatment of tumor.

In silico Discovery of Novel FXa Inhibitors by Pharmacophore Modeling and Molecular Docking.

Coagulation Factor Xa (FXa) is the crucial enzyme at the convergent point of the intrinsic and extrinsic coagulation pathways. The inhibition of FXa is an effective approach against thrombotic diseases. In the present study, a specific strategy is reported to discover 10 novel FXa inhibitors based on ligand-based (pharmacophore) virtual screening and molecular docking analysis from a dataset of specs(containing 220000 molecules). The binding modes analysis provide insights into the contribution of particular structural moieties of the compounds towards their activity against FXa, and 10 novel structural compounds were discovered as potent candidate molecules. This work could be helpful in further design and development of FXa inhibitors.