Scripps Research · La Jolla, CA

Molecular Modeling
& Drug Design

We develop computational methods and apply them to therapeutically relevant targets to unravel new biology for drug design.

Our Mission

We develop computational methods and apply them to therapeutically relevant targets, combining tool building with active drug discovery to unravel new biology and accelerate the path to new medicines.

Affiliations & Resources
Member Lab

Center for Computational Structural Biology (CCSB)

The Forli Lab is one of the members of CCSB at Scripps Research, a collaborative hub uniting computational and structural biology to advance our understanding of biological systems.

NIH-Funded Resource

Resource for Structure-based Computational Drug Discovery and Design (RSD3)

Directed by Dr. Stefano Forli, RSD3 is a national NIH-funded resource supporting structure-based computational drug discovery and design for the broader research community.

Our Focus

Our methods aim at predicting and analyzing the interactions of small organic molecules (either synthetic or from natural sources) with biological macromolecular structures such as proteins and DNA/RNA.

To model such interactions, we need to understand the physical components that orchestrate them: from the large-scale breathing movements that protein structures show in solution, down to the key role that a single water molecule can play in modulating the binding affinity of a potential drug candidate.

Our Approach

Our research requires multi-disciplinary skills that combine computer science and chemistry, physics and biology, mathematics and medicinal chemistry. Beside docking, we use MD simulations, pharmacophores, and mesoscale modeling tools, and make extensive use of Python, as well as C++.

FEATURED PROJECT

AutoDock

AutoDock is a suite of open-source automated docking tools. It is designed to predict how small molecules, such as substrates or drug candidates, bind to a receptor of known 3D structure.

FEATURED PROJECT

OpenPandemics COVID-19

The Forli Lab led the OpenPandemics effort in collaboration with IBM to fight COVID-19.