An integrated drug discovery software. MOE is able to track design ideas and ligand modifications with property models, produce correlation plots to visualize Structure, Property, Activity Relationships and visualize hydrophobic and charged protein surface to study aggregation prone regions. It can also automatically align and superpose antibody structures using the MOE Project protocol, generate and search advanced antibody queries with the Project Search application and build full length Ig structures including bispecifics with the Antibody Homology Modeler.
Uses graph-based signatures to develop predictive models of central ADMET properties for drug development. pkCSM provides a platform for the analysis and optimization of pharmacokinetic and toxicity properties implemented in a web interface, and a valuable tool to help medicinal chemists find the balance between potency, safety, and pharmacokinetic properties. pkCSM achieved a performance as good as or better than similar methods currently available.
A web service enabling drug developers to carry out network pharmacology-based prediction and analysis by integrating results from structural biology with systems biology. Its user-friendly GUI interface simplifies essential operations for large-scale screening. Using the predictive docking approach, systemsDock can test a large number of target proteins with good prediction accuracy. This will reduce the number of tests for bioassay. Together with a curated pathway map, systemsDock helps to comprehensively characterize the underlying mechanism of a drug candidate and to interpret its cascading effects, improving the prediction of drug efficacy and safety.
Serves for pharmacophore identification and modeling. MolSign simplifies the pharmacophoric mapping of a molecule by detecting pharmacophoric features such as H-bond donor, H-bond acceptor, positive charge, negative charge and hydrophobe. Additionally, this program embeds features for pattern identification and graphical display of a set of molecules.
Provides a database of chemical tool compounds for targets from medicinal chemistry literature and patents. PROBELIST was developed to help researchers make the best use of these chemicals and to easily locate useful functional inhibitors for a given biological pathway. The data set was annotated in a target-centric way, with the KEGG pathways, gene ontology (GO) terms (molecular function (MF), biological process (BP), and cellular compartment (CC)), reactome pathways, Entrez gene IDs, and Uniprot IDs for each protein target.
Allows an intuitive interactive organization and exploration of chemical small molecule datasets on current desktop computer hardware. Mona is a generic, simple, and interactive compound browser and manager. This package contains two separate algorithms to cluster molecule sets. First, clustering properties employ bins to create clusters of molecules with similar property values. Second, clustering by similarity calculates fingerprints for all molecules, employing the k-medoid algorithm, which requires quadratic time.
Allows users to investigate complex in vitro studies. SIVA consists of three modules: (i) metabolism/transporter and inhibition modules; (ii) pharmaceutical modules; (iii) in vitro distribution modules. It can perform analysis with whole cells, tissue samples and solid dosage form. This program can be used for predicting ADME parameters or intracellular operating concentrations driving qualitative and quantitative in vitro endpoints