Our Service Areas
Comprehensive solutions tailored to your needs
Virtual Screening & Docking
We provide advanced Virtual Screening and Molecular Docking Analysis services to accelerate structure-based drug discovery and lead optimization. Our computational workflow includes target structure preparation, ligand library curation, active site identification, high-throughput virtual screening, molecular docking, binding affinity estimation, and interaction profiling.
Using industry-standard platforms such as AutoDock, AutoDock Vina, Schrödinger Glide, Discovery Studio, and molecular dynamics validation approaches, we identify high-affinity lead candidates with strong binding stability and favorable interaction patterns. We also integrate ADMET prediction, pharmacokinetic profiling, and structure–activity relationship (SAR) analysis for rational drug design.
Our services support research in cancer therapeutics, antimicrobial discovery, enzyme inhibition studies, and precision medicine. We deliver reproducible computational pipelines, detailed interaction reports, and publication-ready visualizations to transform in silico predictions into actionable drug discovery insights.
Molecular Dynamics (MD) Simulations
We provide advanced Molecular Dynamics (MD) Simulation services to investigate the structural stability, conformational dynamics, and interaction mechanisms of biomolecular systems at atomic resolution. Our workflow includes system preparation, force field selection, solvation, energy minimization, equilibration, production runs, and post-simulation trajectory analysis.
Using high-performance platforms such as GROMACS, AMBER, NAMD, and Desmond, we evaluate RMSD, RMSF, hydrogen bonding, radius of gyration, binding free energy (MM-PBSA/MM-GBSA), and protein–ligand interaction stability. Our simulations support drug discovery, protein engineering, mutation impact studies, and structure-function analysis.
We deliver reproducible computational pipelines, detailed dynamic behavior reports, and publication-ready visualizations to provide deep mechanistic insights for translational research and precision therapeutics.
QSAR (Quantitative Structure-Activity Relationship)
We provide advanced QSAR (Quantitative Structure–Activity Relationship) modeling services to predict the biological activity and toxicity of chemical compounds using robust computational and statistical approaches. Our workflow includes dataset curation, molecular descriptor calculation, feature selection, model development (ML/DL-based algorithms), validation (cross-validation, external validation), and predictive performance assessment.
Leveraging tools such as Python-based cheminformatics libraries, RDKit, scikit-learn, and deep learning frameworks, we develop reliable predictive models to identify lead compounds, optimize structure–activity relationships (SAR), and reduce experimental screening costs. Our services support drug discovery, toxicology, agrochemical research, and regulatory safety assessment.
We deliver interpretable, validated, and publication-ready QSAR models that accelerate rational drug design and data-driven decision-making in modern computational biology and precision therapeutics.
Quantum Chemistry (DFT, QM/MM)
We provide advanced Quantum Chemistry services, including Density Functional Theory (DFT) and QM/MM (Quantum Mechanics/Molecular Mechanics) simulations, to investigate molecular structure, electronic properties, and reaction mechanisms at high precision. Our computational workflow includes geometry optimization, frequency analysis, frontier molecular orbital (HOMO–LUMO) studies, charge distribution, transition state modeling, and energy profile calculations.
Using industry-standard platforms such as Gaussian, ORCA, and hybrid QM/MM frameworks integrated with molecular dynamics tools, we analyze catalytic mechanisms, enzyme–ligand interactions, metal coordination systems, and drug–target electronic interactions. These methods enable accurate prediction of reactivity, binding energetics, and mechanistic pathways.
Our services support drug discovery, enzymology, materials biointerfaces, and computational chemistry research. We deliver reproducible, publication-ready computational reports that provide atomistic-level insights for next-generation precision therapeutics and molecular design.
Homology Modeling & Protein Preparation
We provide comprehensive Homology Modeling and Protein Preparation services to generate accurate three-dimensional protein structures for structure-based research and drug discovery. Our workflow includes template identification (BLAST/PDB search), sequence alignment, model building, loop refinement, side-chain optimization, energy minimization, and structural validation using Ramachandran plot, RMSD, and quality scoring metrics.
Using advanced platforms such as MODELLER, SWISS-MODEL, Discovery Studio, and structure refinement tools, we construct high-confidence models for proteins lacking experimental structures. We further perform protein preparation steps including protonation state assignment, hydrogen addition, missing residue correction, charge optimization, and active site validation to ensure docking and simulation readiness.
Our services support drug discovery, mutation impact studies, enzyme engineering, and functional annotation. We deliver validated, publication-ready structural models optimized for molecular docking, virtual screening, and molecular dynamics simulations.
ADMET & Pharmacokinetic Analysis
We provide comprehensive ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) and Pharmacokinetic Analysis services to evaluate the drug-likeness, safety, and clinical viability of lead compounds at early stages of drug discovery. Our computational workflow includes physicochemical property assessment, Lipinski’s rule evaluation, solubility prediction, permeability analysis, plasma protein binding estimation, CYP450 interaction profiling, toxicity prediction, and bioavailability modeling.
Leveraging advanced in silico platforms, machine learning algorithms, and validated pharmacokinetic models, we predict metabolic stability, half-life, clearance rates, hERG liability, hepatotoxicity, and drug–drug interaction potential. Our integrated approach supports rational lead optimization and reduces late-stage attrition risks.
We deliver scientifically robust, reproducible, and publication-ready ADMET reports that enable data-driven decision-making in precision therapeutics, translational research, and next-generation drug development.
Development of Custom Machine Learning Models
We provide specialized Custom Machine Learning (ML) Model Development services tailored for complex biological, genomic, and drug discovery datasets. Our workflow includes data preprocessing, feature engineering, dimensionality reduction, model selection (supervised/unsupervised learning), hyperparameter optimization, cross-validation, and performance evaluation using robust statistical metrics.
Leveraging advanced frameworks such as scikit-learn, TensorFlow, PyTorch, and bioinformatics-specific libraries, we develop predictive, classification, clustering, and regression models for applications including biomarker discovery, disease risk prediction, drug response modeling, QSAR, multi-omics integration, and precision medicine.
Our solutions emphasize interpretability, reproducibility, and scalability, integrating explainable AI (XAI) approaches to ensure biological relevance and translational impact. We deliver validated, deployment-ready models and comprehensive technical reports to accelerate data-driven innovation in modern computational biology and biotechnology.
Development of Custom Databases
We provide specialized Custom Database Development services designed for large-scale biological, genomic, clinical, and multi-omics data management. Our workflow includes data curation, normalization, schema design, metadata integration, API development, and secure cloud-based deployment to ensure scalable and structured data storage.
Leveraging modern database architectures (SQL/NoSQL), bioinformatics standards (FAIR principles), and interoperable formats (VCF, FASTA, GTF, BAM), we build robust platforms for genomics repositories, variant databases, pharmacogenomics resources, biomarker catalogs, and research data portals. We also integrate advanced search functionalities, annotation pipelines, and visualization dashboards for efficient data retrieval and analysis.
Our solutions emphasize data integrity, reproducibility, security, and regulatory compliance, enabling seamless integration with analytical pipelines and AI-driven workflows to support precision medicine, translational research, and next-generation biotechnology innovations.
Development of Custom Software Tools / Pipelines
We provide end-to-end Custom Software Tool and Bioinformatics Pipeline Development services tailored to complex genomic, transcriptomic, proteomic, and multi-omics workflows. Our expertise includes algorithm design, workflow automation, data integration, high-performance computing (HPC) optimization, and scalable cloud deployment.
We design reproducible and modular pipelines using Python, R, Bash, Nextflow, Snakemake, and containerization technologies (Docker/Singularity) to ensure portability, version control, and regulatory compliance. Our solutions support NGS data processing, variant calling, differential expression analysis, metagenomics, single-cell analysis, and AI-driven bioinformatics applications.
With a focus on automation, reproducibility, and FAIR data principles, we deliver robust, user-friendly, and deployment-ready software tools that accelerate translational research, precision medicine, and next-generation computational biology initiatives.
