• Quantitative Structure Activity Relationship (QSAR) studies on phytomolecules, derivatives/analogues.

QSAR modelling studies through Discovery Studio (DS, Accelrys, USA), Sybyl-X (Certara, USA), Scigress Explorer (Fujitsu, Poland), ADME-Works-Model-Builder (Fujitsu, Poland), V-Life QSAR (V-Life Tech. Pvt. Ltd., Pune, India) provides easy access to the hundreds of molecular descriptors, proven in biological systems to correlate with activity. Easily apply modeling techniques such as Bayesian models, multiple linear regression, Partial Least Squares (PLS), Genetic Functional Analysis (GFA), and more. Extend the basic functionality of the package by adding an advanced neural network component and VAMP descriptors, a semi-empirical quantum mechanical method for rapidly calculating accurate electronic properties for thousands of candidate compounds.

• Calculation of different physico-chemical (2D & 3D) properties of compounds.

• Prediction of binding site, binding affinity score (docking energy) and exploration of mechanism of action.

• Oral bioavailability screening study using extended Lipinski’s Rule of Five.

• Predictive ADME (Pharmacokinetics parameters) screening studies.

Make use of pre-built validated models (DISCOVERY STUDIO, ACCELRYS INC., USA, and SYBYL-X, CERTARA INC., USA) for a broad range of critical pharmacological endpoints, including: aqueous solubility, Blood-Brain Barrier penetration, intestinal absorption, Hepatotoxicity and many more.

ADME Descriptors include: Get an early assessment of your compounds by calculating the predicted absorption, distribution, metabolism, excretion and toxicity (ADMET) properties for collections of molecules such as synthesis candidates, vendor libraries, and screening collections. Use the calculated results to eliminate compounds with unfavorable ADMET characteristics and evaluate proposed structural refinements, designed to improve ADMET properties prior to synthesis.

• Human intestinal absorption

• Aqueous solubility

• Blood brain barrier penetration

• Plasma protein binding

• CYP2D6 binding

• Hepatotoxicity

• Filter sets of small molecules for undesirable function groups based on published SMARTS rules

• Predictive Toxicology screening studies.

Evaluate your compounds’ performance in experimental assays and animal models. Compute and validate assessments of the toxic and environmental effects of chemicals solely from their molecular structure. TOPKAT (TOxicity Prediction by Komputer Assisted Technology) employs robust and cross-validated Quantitative Structure Toxicity Relationship (QSTR) models for assessing various measures of toxicity and utilizing the patented Optimal Predictive Space validation method to assist in interpreting the results (TOPKAT, Discovery Studio Software, Accelrys Inc., USA).

• Rodent carcinogenicity

• Ames mutagenicity

• Rat oral LD50

• Rat chronic LOAEL

• Developmental toxicity potential

• Skin sensitization

• Fathead minnow LC50

• Daphnia magna EC50

• Weight of evidence rodent

• Rat maximum tolerated dose

• Aerobic biodegradability

• Eye irritancy

• Log P

• Rabbit skin irritancy

• Rat inhalation toxicity LC50

• Rat maximum tolerated dose

• Biological Sequence Analysis- Biological sequence analysis using different bioinformatics approaches/resources, comparative genomics, transcriptomics and proteomics studies, ESTs assembly, Functional & Structural annotation, Pathway enzymes mapping, substrate-enzymes interaction studies (docking), protein structure prediction/modeling, genome/proteome wide conserved motif identification using weight matrix approach e.g., transcription factor binding site prediction, conserved pattern identification & matching in other systems etc.

• Systems Pharmacology Screening Studies - Systems pharmacology or systems chemical biology and toxicology screening studies perform through MetaDrug (Thomson Reuters, USA) software for the assessment of would-be therapeutic indications, off-target effects, and potential toxic end points of novel small molecule compounds. We can predict human metabolism, toxicity, and mode of action of compounds from both structural and experimental data in a unique way. Researchers that uses these predictive data can approach their analysis starting from these multiple points, resulting in maximum flexibility and applicability throughout the drug development pipeline. When starting with a compound structure, metabolites are first predicted, then QSAR models are applied to predict ADME/Tox properties. Potential targets are then identified, leveraging an extensive database of chemical structures and pharmacological activities, and visualized in the context of pathways, cell processes, toxicity and disease networks that are perturbed by the compound and its metabolites.


• Compound Based Pathway Analysis
• Compound Comparison
• Drug Target Assessment
• Structure-based ADME/Tox and Safety
• Pharmacology Analysis
• Genomic/Proteomic/Metabolomic
• Data Analysis with a Focus on
• Pharmacology and Safety Assessment
• HCS and HTS Data Analysis
• Metabolite Prediction and Ranking
• Compound Profiling
• Drug Repositioning