Molecular Modeling

Molecular modeling is an integral part of modern drug discovery and helps you deliver interesting chemical equity faster. NUVISAN uses cutting-edge technologies and expertise to rationalize and predict the behavior of molecules through simulation and, in that way, increase the success rate of wet-lab experimentation. We support you in rationalizing your data and making informed research decisions. Trust us to provide the expertise you need to more rapidly achieve your research goals.

Molecular modeling allows NUVISAN researchers to accelerate the development of new and efficacious treatments. Our in silico drug discovery experts offer a comprehensive suite of molecular modeling services to help you advance your drug discovery programs with greater accuracy, efficiency, and speed.

Our modeling team works with you throughout the complete discovery pipeline, starting with target identification. It is crucial to select a target that is not only implicated in a disease but also druggable by a small molecule. With in silico binding pocket characterization toward druggability, the surface of a macromolecular target is studied to detect cavities with sufficient size and physicochemical properties. Molecular dynamics (MD) simulations add information about the stability of pockets and the opening of transient or cryptic pockets. Druggability analysis will ultimately increase your chances of developing small molecules with high affinity and drug-like properties.

In hit identification, our computational researchers have extensive experience with structure-based virtual screening approaches. NUVISAN can virtually screen million-scale internal and external compound libraries for active chemical matter against your well-defined target structure. We have vast experience employing molecular docking, 3D pharmacophore-based, shape-based, and similarity/machine-learning-based approaches for virtual screening. Compared to a traditional high-throughput screening, we can identify potent molecules but only need to test a fraction of compounds in vitro. In the absence of structural information for the macromolecular target, ligand-based methods trained on known binders can be utilized to perform a virtual screening. We also provide target structure prediction with well-established homology modeling or AI-based methodologies, such as AlphaFold.

Beyond hit identification, we can assist with the design–make–test–analyze (DMTA) optimization cycles in terms of potency, selectivity, and physchem/drug metabolism and pharmacokinetics (DMPK) properties. Our molecular modeling toolbox includes molecular docking, MD simulations, free energy calculations, solvent analysis, and cheminformatics.

At NUVISAN, we are committed to providing state-of-the-art molecular modeling services to accelerate your drug discovery and development program. Our team of in silico drug discovery experts utilize the latest software and techniques on a highly performant computing infrastructure (CPU and GPU cluster) to generate accurate and reliable predictions. Trust us to help you optimize your drug-design process and bring lifesaving treatments to patients faster.