Evaluation of QSAR Equations for Virtual Screening
نویسندگان
چکیده
منابع مشابه
QSAR Models and Virtual Screening for Discovery of New Analgesic Leads
The search for new selective pharmacological agents with no significant side-effects is an increasing requirement for the development of new drugs to be used in the treatment of acute and chronic pain. In the present study, a new series of compounds (VAM 1, 6, 10, 11, 12, 24) has been screening in QSARLDA mathematic models and pharmacologically evaluated. The antinociceptive properties of the...
متن کامل3D QSAR pharmacophore based virtual screening and molecular docking for identification of potential HSP90 inhibitors.
Chemical features based 3D pharmacophore models were developed for HSP90 based on the known inhibitors using Discovery Studio V2.1. An optimal pharmacophore model was brought forth and validated using a decoy set, external test set and Fischer's randomization method. The best five features pharmacophore model, Hypo1, includes two hydrogen bond acceptors, three hydrophobic features, which has th...
متن کاملQSAR Classification Model for Antibacterial Compounds and Its Use in Virtual Screening
As novel and drug-resistant bacterial strains continue to present an emerging health threat, the development of new antibacterial agents is critical. This includes making improvements to existing antibacterial scaffolds as well as identifying novel ones. The aim of this study is to apply a Bayesian classification QSAR approach to rapidly screen chemical libraries for compounds predicted to have...
متن کاملEvaluation of machine-learning methods for ligand-based virtual screening
Machine-learning methods can be used for virtual screening by analysing the structural characteristics of molecules of known (in)activity, and we here discuss the use of kernel discrimination and naive Bayesian classifier (NBC) methods for this purpose. We report a kernel method that allows the processing of molecules represented by binary, integer and real-valued descriptors, and show that it ...
متن کامل3D QSAR Studies, Pharmacophore Modeling and Virtual Screening on a Series of Steroidal Aromatase Inhibitors
Aromatase inhibitors are the most important targets in treatment of estrogen-dependent cancers. In order to search for potent steroidal aromatase inhibitors (SAIs) with lower side effects and overcome cellular resistance, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of SAIs to build 3D QSAR models. The rel...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Molecular Sciences
سال: 2020
ISSN: 1422-0067
DOI: 10.3390/ijms21217828