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CADD and Informatics Services CADD and Informatics Services

CADD and Informatics Services

We provide wide range of standalone and integrated CADD & Informatics services to enable candidate progression at every stage of the program.

We follow a holistic approach to discovery projects by investigating the target of interest and understanding the biomolecular mechanism. We have standardized methodology and developed innovative approaches through highly skilled scientists for solving complex problems related to discovery. The CADD facility routinely supports discovery projects starting from target identification to positioning of the candidate compound. We have a wide range of tools available for compound optimization. We have proven expertise in collaborative small molecule and niche therapeutics modalities, namely Peptides, Target protein degradation (PROTAC & Molecular glues), Antibody and ADC design, and Oligonucleotides (includes aptamer and siRNA) related drug discovery projects.

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Various Techniques and Tools, CADD & Informatics

Virtual Screening

Virtual screening is a powerful modeling technique to identify novel hit compounds in any discovery program. It is routinely deployed in drug discovery projects for compound ideation and conceptualization. Virtual screening has multiple applications including hit scouting and hit-to-lead optimization. The techniques deal with computational or in silico analog of biological screening to score, rank, and/or filter a set of structures using one or more computational procedures. This helps to decide which compounds to screen, which libraries to synthesize, and which compounds to purchase from an external source. Virtual screening uses both structures and ligand or compound-guided computational methods, or a combination of both. We have access to multi-billion commercially available compound databases and an in-house curated Aurimine database, focusing on potential target related compounds. This database is routinely used to carry out virtual screening studies to facilitate the compound design and ideation. We have established active learning embedded GIGA scale virtual screening- in silico structure-based hit finding based on protein structure or known ligands to expediate hit finding and optimization.

Structure-based Design Approach

Structure-based design approach exploits disease-related targets by experimentally determining 3-dimensional structure (e.g. X-ray, NMR, or Cryo-EM) or a homology model (in case of unavailability of experimental structure). This method is performed to predict the binding pose of the molecule in the binding site and estimate probable binding affinity or a score representing the strength of binding. We extensively use docking and molecular dynamics simulation to shortlist compounds that may become a good hit or lead for a project. We have established physics-based simulation such as long-range (micro-second to milli-second) MD simulation, MMGBSA, free energy perturbation (FEP) related methods to support compound ideation and optimization.

Ligand-based Design Approach

Ligand or compound-based design is another powerful modeling technique used in CADD. Some of the most used techniques routinely deployed at Aurigene include pharmacophore modeling, quantitative structure-activity relationship (QSAR), or knowledge-based expert methods, for compound design and ideation. We use a ligand-based design approach such as de novo design, scaffold hopping, ligand hybridization, fragment-linking and related techniques. The ligand-based approach is not limited to compound designs but is also deployed in a predictive model. Predictive models built using AI/ML techniques are used at our facility to determine compound potency, selectivity, and physico-chemical properties. This in turn facilitates the project progress.

ADMET property prediction

In-vitro Absorption Distribution Metabolism and Excretion- Pharmacokinetics and pharmacodynamics is an important aspect in drug discovery. Pharmacokinetics (PK) is in other words termed as “What the body does to the drug” such as absorption, distribution, metabolism, elimination (disposition). Pharmacodynamics (PD) can be termed as “What the drug does to the body” such as desired effects – efficacy, undesired effects – toxicity. The quality of lead candidate is judged based on the PK and PD property. The In Silico ADME prediction facilitate possible ADME related challenges faced during the preclinical development stage. In this context we have access to several ADMETox prediction models (ML based property predictions, profile QSAR) to facilitate compound property optimization.

Why Aurigene CADD and Bioinformatics Services?

3-D virtual reality facility

High-end software for simulation & modeling (Schrodinger, MolSoft)

NVIDIA GPU cluster to support high end simulation and modeling

Team led by domain expert in CADD and Informatics

Other Services

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