The goal of our research is to use computational tools to unravel and understand physico-chemical rules behind biological processes.
We develop new, cutting-edge computational methods that allow us to predict and analyze the interactions of small organic molecules (either synthetic or from natural sources) with biological macromolecular structures such as proteins and DNA/RNA.
We apply these tools in combination with other molecular modeling techniques to investigate and interpret the nature of biological events from a mechanistic and thermodynamic perspective, and rapidly explore the chemical space to identify molecular modulators of therapeutically relevant targets. We have a number of collaborations within Scripps Research as well as with researchers from other academic institutions and pharmaceutical industries.
We develop computational tools for structure based drug design, especially molecular docking software. AutoDock and AutoDock Vina are open-source software and part of the most widely used docking suite, previously developed in the Molecular Graphics Lab, now CCSB. We are developing the next generation of docking engines and the virtual screening tools, designing improved energy potentials, better Free Energy of Binding estimates, and new protocols for drug design.
The goal is to make docking more accurate and useful by making it faster and more chemically meaningful. We are improving the description of the chemical, physical and thermodynamic terms to include torsional preferences of rotatable bonds, a more precise description of non-covalent interactions, and, most importantly, of solvation effects. For this, we look up to modern force fields, electronic structure methods, and molecular dynamics simulations. At the same time, in conjunction with GPU computation, we explore new search algorithms to navigate the energy landscape.
The development of our code is performed in collaboration with hardware and software industry partners.
Covalent Inhibitor High Throughput Screening
Modeling of covalent binders is non-trivial, especially in a high-throughput fashion. Several covalent methods are now available but the majority of these approaches is effective when information about the target structures is known (i.e. covalent binding site).
Driven by the need to overcome this barrier, we are designing the Reactive Docking method, an approach that allows prospective prediction of covalent binding sites on a protein, through the simulation of the reaction event between the covalent residue and the warhead of the ligand. Furthermore, Reactive Docking allows to model different residues and various types of warheads.
This method was successfully applied to several targets and it is suitable for the HTVS of covalent modifiers for the discovery of new covalent binding sites on different proteins.
HIV-1 Life cycle
The search for drugs that can interfere with different steps of the HIV-1 life cycle is still a subject of great interest, since the currently available drugs are not able to eradicate the infection. We are targeting the Capsid protein of the HIV-1 by implementing a strategy based on conventional and reactive docking for the Virtual screening of small molecules that could modulate the viral assembly. Reactive Docking approach is being used to screen small molecules with a SuFEx warhead, that could tightly bind to the identified pocket.
The Forli lab is part of the HIV Interaction in Viral Evolution Center (HIVE)
Molecular modeling applications
Application of molecular modeling techniques, like molecular dynamics, molecular pharmacophores, and virtual screenings.