Stefano Forli

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IMPORTANCE TO THE FIELD: Virtual screening is a computer-based technique for identifying promising compounds to bind to a target molecule of known structure. Given the rapidly increasing number of protein and nucleic acid structures, virtual screening continues to grow as an effective method for the discovery of new inhibitors and drug molecules. AREAS(More)
Small molecules are powerful tools for investigating protein function and can serve as leads for new therapeutics. Most human proteins, however, lack small-molecule ligands, and entire protein classes are considered 'undruggable'. Fragment-based ligand discovery can identify small-molecule probes for proteins that have proven difficult to target using(More)
Computational docking can be used to predict bound conformations and free energies of binding for small-molecule ligands to macromolecular targets. Docking is widely used for the study of biomolecular interactions and mechanisms, and it is applied to structure-based drug design. The methods are fast enough to allow virtual screening of ligand libraries(More)
Zinc is present in a wide variety of proteins and is important in the metabolism of most organisms. Zinc metalloenzymes are therapeutically relevant targets in diseases such as cancer, heart disease, bacterial infection, and Alzheimer's disease. In most cases a drug molecule targeting such enzymes establishes an interaction that coordinates with the zinc(More)
Human immunodeficiency virus type 1 (HIV-1) integrase is one of three virally encoded enzymes essential for replication and, therefore, a rational choice as a drug target for the treatment of HIV-1-infected individuals. In 2007, raltegravir became the first integrase inhibitor approved for use in the treatment of HIV-infected patients, more than a decade(More)
In modeling ligand-protein interactions, the representation and role of water are of great importance. We introduce a force field and hydration docking method that enables the automated prediction of waters mediating the binding of ligands with target proteins. The method presumes no prior knowledge of the apo or holo protein hydration state and is(More)
As knowledge of individual biological processes grows, it becomes increasingly useful to frame new findings within their larger biological contexts in order to generate new systems-scale hypotheses. This report highlights two major iterations of a whole virus model of HIV-1, generated with the cellPACK software. cellPACK integrates structural and systems(More)
Docking is commonly applied to drug design efforts, especially high-throughput virtual screenings of small molecules, to identify new compounds that bind to a given target. Despite great advances and successful applications in recent years, a number of issues remain unsolved. Most of the challenges and problems faced when running docking experiments are(More)
Isoniazid (INH) is usually administered to treat latent Mycobacterium tuberculosis (Mtb) infections and is used in combination therapy to treat active tuberculosis (TB). Unfortunately, resistance to this drug is hampering its clinical effectiveness. INH is a prodrug that must be activated by Mtb catalase-peroxidase (KatG) before it can inhibit InhA (Mtb(More)
We describe two methods of automated covalent docking using Autodock4: the two-point attractor method and the flexible side chain method. Both methods were applied to a training set of 20 diverse protein-ligand covalent complexes, evaluating their reliability in predicting the crystallographic pose of the ligands. The flexible side chain method performed(More)