Stefano Forli

Virtual Screening with AutoDock: Theory and Practice.

Importance of 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 covered in this review: We describe virtual screening methods that are available in the AutoDock suite of programs and several of our successes in using AutoDock virtual screening in pharmaceutical lead discovery. What the reader will gain: A general overview of the challenges of virtual screening is presented, along with the tools available in the AutoDock suite of programs for addressing these challenges. Take home message: Virtual screening is an effective tool for the discovery of compounds for use as leads in drug discovery, and the free, open source program AutoDock is an effective tool for virtual screening.

Proteome-wide covalent ligand discovery in native biological systems

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 high-throughput screening of complex compound libraries. Although reversibly binding ligands are commonly pursued, covalent fragments provide an alternative route to small-molecule probes, including those that can access regions of proteins that are difficult to target through binding affinity alone. Here we report a quantitative analysis of cysteine-reactive small-molecule fragments screened against thousands of proteins in human proteomes and cells. Covalent ligands were identified for >700 cysteines found in both druggable proteins and proteins deficient in chemical probes, including transcription factors, adaptor/scaffolding proteins, and uncharacterized proteins. Among the atypical ligand–protein interactions discovered were compounds that react preferentially with pro- (inactive) caspases. We used these ligands to distinguish extrinsic apoptosis pathways in human cell lines versus primary human T cells, showing that the former is largely mediated by caspase-8 while the latter depends on both caspase-8 and -10. Fragment-based covalent ligand discovery provides a greatly expanded portrait of the ligandable proteome and furnishes compounds that can illuminate protein functions in native biological systems.

Computational protein–ligand docking and virtual drug screening with the AutoDock suite

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 containing tens of thousands of compounds. This protocol covers the docking and virtual screening methods provided by the AutoDock suite of programs, including a basic docking of a drug molecule with an anticancer target, a virtual screen of this target with a small ligand library, docking with selective receptor flexibility, active site prediction and docking with explicit hydration. The entire protocol will require ∼5 h.

A Force Field with Discrete Displaceable Waters and Desolvation Entropy for Hydrated Ligand Docking

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 potentially useful in the process of structure-based drug discovery. The hydration force field accounts for the entropic and enthalpic contributions of discrete waters to ligand binding, improving energy estimation accuracy and docking performance. The force field has been calibrated and validated on a total of 417 complexes (197 training set; 220 test set), then tested in cross-docking experiments, for a total of 1649 ligand-protein complexes evaluated. The method is computationally efficient and was used to model up to 35 waters during docking. The method was implemented and tested using unaltered AutoDock4 with new force field tables.

AutoDock4(Zn): an improved AutoDock force field for small-molecule docking to zinc metalloproteins.

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 ion. Thus, accurate prediction of the interaction of ligands with zinc is an important aspect of computational docking and virtual screening against zinc containing proteins. We have extended the AutoDock force field to include a specialized potential describing the interactions of zinc-coordinating ligands. This potential describes both the energetic and geometric components of the interaction. The new force field, named AutoDock4Zn, was calibrated on a data set of 292 crystal complexes containing zinc. Redocking experiments show that the force field provides significant improvement in performance in both free energy of binding estimation as well as in root-mean-square deviation from the crystal structure pose. The new force field has been implemented in AutoDock without modification to the source code.

A dynamic model of HIV integrase inhibition and drug resistance.

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 since the approval of the first protease inhibitor (saquinavir, Hoffman La-Roche, 1995) and two decades since the approval of the first reverse transcriptase inhibitor (retrovir, GlaxoSmithKline, 1987). The slow progress toward a clinically effective HIV-1 integrase inhibitor can at least in part be attributed to a poor structural understanding of this key viral protein. Here we describe the development of a restrained molecular dynamics protocol that produces a more accurate model of the active site of this drug target. This model provides an advance on previously described models as it ensures that the catalytic DDE motif makes correct, monodentate interactions with the two active-site magnesium ions. Dynamic restraints applied to this coordination state create models with the correct solvation sphere for the metal ion complex and highlight the coordination sites available for metal-binding ligands. Application of appropriate dynamic flexibility to the core domain allowed the inclusion of multiple conformational states in subsequent docking studies. These models have allowed us to (1) explore the effects of key drug resistance mutations on the dynamic flexibility and conformational preferences of HIV integrase and to (2) study raltegravir binding in the context of these dynamic models of both wild type and the G140S/Q148H drug-resistant enzyme.

Novel Ester and Acid Derivatives of the 1,5-Diarylpyrrole Scaffold as Anti-Inflammatory and Analgesic Agents. Synthesis and in Vitro and in Vivo Biological Evaluation

A new generation of selective cyclooxygenase-2 (COX-2) inhibitors (coxibs) was developed to circumvent the major side effects of cyclooxygenase-1 (COX-1) and COX-2 inhibitors (stomach ulceration and nephrotoxicity). As a consequence, coxibs are extremely valuable in treating acute and chronic inflammatory conditions. However, the use of coxibs, such as rofecoxib (Vioxx), was discontinued because of the high risk of cardiovascular adverse events. More recent clinical findings highlighted how the cardiovascular toxicity of coxibs could be mitigated by an appropriate COX-1 versus COX-2 selectivity. We previously reported a set of substituted 1,5-diarylpyrrole derivatives, selective for COX-2. Here, we describe the synthesis of new 1,5-diarylpyrroles along with their inhibitory effects in vitro, ex vivo, and in vivo toward COX isoenzymes and their analgesic activity. Isopropyl-2-methyl-5-[4-(methylsulfonyl)phenyl]-1-phenyl-1H-pyrrole-3-acetate (10a), a representative member of the series, was selected for pharmacokinetic and metabolic studies.

Virtual screening of integrase inhibitors by large scale binding free energy calculations: the SAMPL4 challenge

AbstractAs part of the SAMPL4 blind challenge, filtered AutoDock Vina ligand docking predictions and large scale binding energy distribution analysis method binding free energy calculations have been applied to the virtual screening of a focused library of candidate binders to the LEDGF site of the HIV integrase protein. The computational protocol leveraged docking and high level atomistic models to improve enrichment. The enrichment factor of our blind predictions ranked best among all of the computational submissions, and second best overall. This work represents to our knowledge the first example of the application of an all-atom physics-based binding free energy model to large scale virtual screening. A total of 285 parallel Hamiltonian replica exchange molecular dynamics absolute protein-ligand binding free energy simulations were conducted starting from docked poses. The setup of the simulations was fully automated, calculations were distributed on multiple computing resources and were completed in a 6-weeks period. The accuracy of the docked poses and the inclusion of intramolecular strain and entropic losses in the binding free energy estimates were the major factors behind the success of the method. Lack of sufficient time and computing resources to investigate additional protonation states of the ligands was a major cause of mispredictions. The experiment demonstrated the applicability of binding free energy modeling to improve hit rates in challenging virtual screening of focused ligand libraries during lead optimization.

3D QSAR studies of the interaction between β-tubulin and microtubule stabilizing antimitotic agents (MSAA). A combined pharmacophore generation and pseudoreceptor modeling approach applied to taxanes and epothilones

Based on the conformer of paclitaxel extracted from the experimental tubulin structure, a pharmacophoric model has been generated and used to find the chemical features common to the taxane and epothilone classes of compounds. This original alignment has been translated into the experimental tubulin binding site obtaining an assembly subsequently submitted to the pseudoreceptor modeling approach. As a result, an original 3D QSAR model, able to evaluate, at a quantitative level, the relationships between the molecular structures and biological data of the studied compounds, has been obtained.

Covalent docking using autodock: Two‐point attractor and flexible side chain methods

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 best, recovering the pose in 75% of cases, with failures for the largest inhibitors tested. Both methods are freely available at the AutoDock website (http://autodock.scripps.edu).