AI-Assisted Bioinformatics
Machine learning-enabled workflows for biomarker discovery, variant prioritization, and predictive genomics.
Molecular Design
Refine lead structures for preclinical success.
Enhance binding affinity, kinetic stability, and drug-like properties using GROMACS molecular dynamics, ML-driven QSAR models, and ADMET toxicity filters.
Lead Optimization
Refine hit compounds into selective, drug-like leads.
Improve target selectivity, binding affinity, and metabolic stability while minimizing off-target toxicity.
Molecular dynamics (MD) simulations
Verify binding stability and structural flexibility over time using GROMACS and AMBER.
Free energy calculations
Refine docking predictions with MM-GBSA and Free Energy Perturbation (FEP) scoring.
ADMET predictive modeling
Assess bioavailability, hepatic clearance, BBB permeation, and hERG toxicity using pkCSM and SwissADME.
GROMACSHigh-performance molecular dynamics simulator.
AMBERAssisted Model Building with Energy Refinement suite.
SwissADMEPredicts ADME parameters, drug-likeness, and medicinal chemistry friendliness.
pkCSMPredicts small-molecule pharmacokinetics using graph signatures.
MM-GBSAMolecular Mechanics Generalized Born Surface Area calculations.
Why RASA
Why Choose RASA?
Multi-Platform Expertise
Support for Illumina, Oxford Nanopore, PacBio HiFi, and 10x Genomics platforms.
End-to-End Analysis
From raw sequencing data to biological interpretation and publication-ready reports.
Cloud-Ready Infrastructure
Deployable on AWS, Google Cloud, HPC clusters, and secure on-premise environments.
Reproducible Workflows
Built using Nextflow, Snakemake, Docker, and Singularity for enterprise-grade bioinformatics operations.
Accelerate therapeutic discovery with RASA.
Get in touch with our Pune-based computational drug design experts to coordinate target screens or dynamics calculations.
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