CATALYST Pharmacophore Models and Their Utility As Queries for Searching 3D Databases

Drug-drug interaction (DDI) is the phenomenon of alteration of the pharmacological activity of a drug(s) when another drug(s) is co-administered in cases of so-called polypharmacy. There are three types of DDIs: pharmacokinetic (PK), pharmacodynamic, and pharmaceutical. PK is the most frequent type of DDI, which often appears as a result of the inhibition or induction of drug-metabolising enzymes (DME). In this review, we summarise in silico methods that may be applied for the prediction of the inhibition or induction of DMEs and describe appropriate computational methods for DDI prediction, showing the current situation and perspectives of these approaches in medicinal and pharmaceutical chemistry. We review sources of information on DDI, which can be used in pharmaceutical investigations and medicinal practice and/or for the creation of computational models. The problem of the inaccuracy and redundancy of these data are discussed. We provide information on the state-of-the-art physiologically- based pharmacokinetic modelling (PBPK) approaches and DME-based in silico methods. In the section on ligand-based methods, we describe pharmacophore models, molecular field analysis, quantitative structure-activity relationships (QSAR), and similarity analysis applied to the prediction of DDI related to the inhibition or induction of DME. In conclusion, we discuss the problems of DDI severity assessment, mention factors that influence severity, and highlight the issues, perspectives and practical using of in silico methods.

Download Full-text

Combiphore (Structure and Ligand Based Pharmacophore) - Approach for the Design of GPR40 Modulators in the Management of Diabetes

Current Drug Discovery Technologies ◽

10.2174/1570163815666181008165822 ◽

2020 ◽

Vol 17 (2) ◽

pp. 233-247

Author(s):

Krishna A. Gajjar ◽

Anuradha K. Gajjar

Keyword(s):

Molecular Docking ◽

Structural Information ◽

Docking Studies ◽

Structural Motif ◽

Roc Curve Analysis ◽

Ligand Complex ◽

Discovery Studio ◽

Protein Ligand Interactions ◽

Ligand Interactions ◽

Pharmacophore Models

Background: Pharmacophore mapping and molecular docking can be synergistically integrated to improve the drug design and discovery process. A rational strategy, combiphore approach, derived from the combined study of Structure and Ligand based pharmacophore has been described to identify novel GPR40 modulators. Methods: DISCOtech module from Discovery studio was used for the generation of the Structure and Ligand based pharmacophore models which gave hydrophobic aromatic, ring aromatic and negative ionizable as essential pharmacophoric features. The generated models were validated by screening active and inactive datasets, GH scoring and ROC curve analysis. The best model was exposed as a 3D query to screen the hits from databases like GLASS (GPCR-Ligand Association), GPCR SARfari and Mini-Maybridge. Various filters were applied to retrieve the hit molecules having good drug-like properties. A known protein structure of hGPR40 (pdb: 4PHU) having TAK-875 as ligand complex was used to perform the molecular docking studies; using SYBYL-X 1.2 software. Results and Conclusion: Clustering both the models gave RMSD of 0.89. Therefore, the present approach explored the maximum features by combining both ligand and structure based pharmacophore models. A common structural motif as identified in combiphore for GPR40 modulation consists of the para-substituted phenyl propionic acid scaffold. Therefore, the combiphore approach, whereby maximum structural information (from both ligand and biological protein) is explored, gives maximum insights into the plausible protein-ligand interactions and provides potential lead candidates as exemplified in this study.

Download Full-text

Discovery of New Phosphoinositide 3-kinase Delta (PI3Kδ) Inhibitors via Virtual Screening using Crystallography-derived Pharmacophore Modelling and QSAR Analysis

Medicinal Chemistry ◽

10.2174/1573406415666190222125333 ◽

2019 ◽

Vol 15 (6) ◽

pp. 588-601 ◽

Cited By ~ 1

Author(s):

Mahmoud A. Al-Sha'er ◽

Rua'a A. Al-Aqtash ◽

Mutasem O. Taha

Keyword(s):

Virtual Screening ◽

Inflammatory Diseases ◽

Qsar Model ◽

Qsar Analysis ◽

Pharmacophore Modelling ◽

Physicochemical Descriptors ◽

Qsar Modelling ◽

Ic50 Values ◽

Phosphoinositide 3 Kinase ◽

Pharmacophore Models

Background: PI3Kδ is predominantly expressed in hematopoietic cells and participates in the activation of leukocytes. PI3Kδ inhibition is a promising approach for treating inflammatory diseases and leukocyte malignancies. Accordingly, we decided to model PI3Kδ binding. Methods: Seventeen PI3Kδ crystallographic complexes were used to extract 94 pharmacophore models. QSAR modelling was subsequently used to select the superior pharmacophore(s) that best explain bioactivity variation within a list of 79 diverse inhibitors (i.e., upon combination with other physicochemical descriptors). Results: The best QSAR model (r2 = 0.71, r2 LOO = 0.70, r2 press against external testing list of 15 compounds = 0.80) included a single crystallographic pharmacophore of optimal explanatory qualities. The resulting pharmacophore and QSAR model were used to screen the National Cancer Institute (NCI) database for new PI3Kδ inhibitors. Two hits showed low micromolar IC50 values. Conclusion: Crystallography-based pharmacophores were successfully combined with QSAR analysis for the identification of novel PI3Kδ inhibitors.

Download Full-text

Discovery of novel potential KIT inhibitors for the treatment of gastrointestinal stromal tumor

Open Life Sciences ◽

10.1515/biol-2021-0036 ◽

2021 ◽

Vol 16 (1) ◽

pp. 303-310

Author(s):

Lili Jiang ◽

Zhongmin Zhang ◽

Zhen Wang ◽

Yong Liu

Keyword(s):

Molecular Docking ◽

Gastrointestinal Stromal Tumor ◽

Pharmacophore Modeling ◽

Stromal Tumor ◽

Strong Hydrogen Bond ◽

Ligand Complex ◽

Hydrogen Bond Interaction ◽

Mutant Proteins ◽

Docking Simulations ◽

Pharmacophore Models

Abstract Numerous inhibitors of tyrosine-protein kinase KIT, a receptor tyrosine kinase, have been explored as a viable therapy for the treatment of gastrointestinal stromal tumor (GIST). However, drug resistance due to acquired mutations in KIT makes these drugs almost useless. The present study was designed to screen the novel inhibitors against the activity of the KIT mutants through pharmacophore modeling and molecular docking. The best two pharmacophore models were established using the KIT mutants’ crystal complexes and were used to screen the new compounds with possible KIT inhibitory activity against both activation loop and ATP-binding mutants. As a result, two compounds were identified as potential candidates from the virtual screening, which satisfied the potential binding capabilities, molecular modeling characteristics, and predicted absorption, distribution, metabolism, excretion, toxicity (ADMET) properties. Further molecular docking simulations showed that two compounds made strong hydrogen bond interaction with different KIT mutant proteins. Our results indicated that pharmacophore models based on the receptor–ligand complex had excellent ability to screen KIT inhibitors, and two compounds may have the potential to develop further as the future KIT inhibitors for GIST treatment.

Download Full-text

New methods for topological clustering and spatial access in object-oriented 3D databases

Proceedings of the ninth ACM international symposium on Advances in geographic information systems - GIS '01 ◽

10.1145/512161.512194 ◽

2001 ◽

Cited By ~ 4

Author(s):

M. Breunig ◽

A. B. Cremers ◽

W. Müller ◽

J. Siebeck

Keyword(s):

Object Oriented ◽

Spatial Access ◽

New Methods ◽

3D Databases

Download Full-text

Predicting hiCE inhibitors based upon pharmacophore models derived from the receptor and its ligands

Science China Chemistry ◽

10.1007/s11426-013-4952-3 ◽

2013 ◽

Vol 56 (10) ◽

pp. 1402-1412 ◽

Cited By ~ 2

Author(s):

GuoDong Zhang ◽

Hu Ge ◽

Qiong Gu ◽

Jun Xu

Keyword(s):

Pharmacophore Models

Download Full-text

Combinatorial Screening of COX-2 Inhibitors from Chinese Herbs Based on Multiple Structure-Based Pharmacophores

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.791-793.269 ◽

2013 ◽

Vol 791-793 ◽

pp. 269-273

Author(s):

Yan Ling Zhang ◽

Yuan Ming Wang ◽

Yan Jiang Qiao

Keyword(s):

Chinese Medicine ◽

Traditional Chinese Medicine ◽

Protein Data Bank ◽

Data Bank ◽

Chinese Herbs ◽

Combinatorial Screening ◽

Cox 2 ◽

Appraisal Index ◽

Cox 2 Inhibitors ◽

Pharmacophore Models

Ten structure-based pharmacophore models of Cyclooxygenase 2 (COX-2) inhibitors were generated by LigandScout based on COX-2 inhibitor complexes from the Protein Data Bank (PDB). The potential COX-2 inhibitors were identified from traditional Chinese medicine with the method of combinatorial screening with ten models. Based on the screening results of MDDR and the metrics of E, A% and comprehensive appraisal index (CAI), the threshold of hit frequency of molecules was defined and used to identify the active molecules from Chinese herbs. The molecules hit by not less than six pharmacophore models were taken as the screening objects of COX-2 inhibitor, and 1103 molecules were obtained.

Download Full-text

Truly Target-Focused Pharmacophore Modeling: A Novel Tool for Mapping Intermolecular Surfaces

Molecules ◽

10.3390/molecules23081959 ◽

2018 ◽

Vol 23 (8) ◽

pp. 1959 ◽

Cited By ~ 14

Author(s):

Jérémie Mortier ◽

Pratik Dhakal ◽

Andrea Volkamer

Keyword(s):

Protein Interactions ◽

Pharmacophore Modeling ◽

Macromolecular Structure ◽

Target Structure ◽

Protein Protein Interactions ◽

Energy Functions ◽

Chemical Structures ◽

Molecular Interaction Fields ◽

Protein Classes ◽

Pharmacophore Models

Pharmacophore models are an accurate and minimal tridimensional abstraction of intermolecular interactions between chemical structures, usually derived from a group of molecules or from a ligand-target complex. Only a limited amount of solutions exists to model comprehensive pharmacophores using the information of a particular target structure without knowledge of any binding ligand. In this work, an automated and customable tool for truly target-focused (T²F) pharmacophore modeling is introduced. Key molecular interaction fields of a macromolecular structure are calculated using the AutoGRID energy functions. The most relevant points are selected by a newly developed filtering cascade and clustered to pharmacophore features with a density-based algorithm. Using five different protein classes, the ability of this method to identify essential pharmacophore features was compared to structure-based pharmacophores derived from ligand-target interactions. This method represents an extremely valuable instrument for drug design in a situation of scarce ligand information available, but also in the case of underexplored therapeutic targets, as well as to investigate protein allosteric pockets and protein-protein interactions.

Download Full-text

A Definitive Pharmacophore Modelling Study on CDK2 ATP Pocket Binders: Tracing the Path of New Virtual High-Throughput Screenings

Current Drug Discovery Technologies ◽

10.2174/1570163816666190620113944 ◽

2020 ◽

Vol 17 (5) ◽

pp. 740-747 ◽

Cited By ~ 1

Author(s):

Marco Tutone ◽

Giulia Culletta ◽

Luca Livecchi ◽

Anna M. Almerico

Keyword(s):

Protein Interactions ◽

Roc Curves ◽

Md Simulations ◽

Eukaryotic Cell ◽

Energy Calculation ◽

Pharmacophore Modelling ◽

Cyclin Dependent Kinases ◽

Long Time ◽

Cycle Regulation ◽

Pharmacophore Models

Cyclin Dependent Kinases-2 (CDK2) are members of serine/threonine protein kinases family. They play an important role in the regulation events of the eukaryotic cell division cycle, especially during the G1 to S phase transition. Experimental evidence indicate that excessive expression of CDK2s should cause abnormal cell cycle regulation. Therefore, since a long time, CDK2s have been considered potential therapeutic targets for cancer therapy. In this work, onehundred and forty-nine complexes of inhibitors bound in the CDK2-ATP pocket were submitted to short MD simulations (10ns) and free energy calculation. Comparison with experimental data (Ki, Kd and pIC50) revealed that short simulations are exhaustive to examine the crucial ligand-protein interactions within the complexes. Information collected on MD simulations of protein-ligand complexes has been used to perform a molecular modelling approach that incorporates flexibility into structure-based pharmacophore modelling (Common Hits Approach, CHA). The high number of pharmacophore models resulting from the MD simulation was thus reduced to a few representative groups of pharmacophore models. The performance of the models has been assessed by using the ROC curves analysis. This definitive set of validated pharmacophore models could be used to screen in-house and/or commercial datasets for detection of new CDK-2 inhibitors. We provide the models to all the researchers involved in this field.

Download Full-text