Publications by authors named "Stefano Forli"

68 Publications

AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings.

J Chem Inf Model 2021 Aug 19;61(8):3891-3898. Epub 2021 Jul 19.

Department of Integrative Structural and Computational Biology, Scripps Research, La Jolla, 92037 California, United States.

AutoDock Vina is arguably one of the fastest and most widely used open-source programs for molecular docking. However, compared to other programs in the AutoDock Suite, it lacks support for modeling specific features such as macrocycles or explicit water molecules. Here, we describe the implementation of this functionality in AutoDock Vina 1.2.0. Additionally, AutoDock Vina 1.2.0 supports the AutoDock4.2 scoring function, simultaneous docking of multiple ligands, and a batch mode for docking a large number of ligands. Furthermore, we implemented Python bindings to facilitate scripting and the development of docking workflows. This work is an effort toward the unification of the features of the AutoDock4 and AutoDock Vina programs. The source code is available at https://github.com/ccsb-scripps/AutoDock-Vina.
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http://dx.doi.org/10.1021/acs.jcim.1c00203DOI Listing
August 2021

Improving Docking Power for Short Peptides Using Random Forest.

J Chem Inf Model 2021 06 14;61(6):3074-3090. Epub 2021 Jun 14.

Koliber Biosciences, Inc., 12265 World Trade Drive, Suite G, San Diego, California 92128, United States.

In recent years, therapeutic peptides have gained a lot interest as demonstrated by the 60 peptides approved as drugs in major markets and 150+ peptides currently in clinical trials. However, while small molecule docking is routinely used in rational drug design efforts, docking peptides has proven challenging partly because docking scoring functions, developed and calibrated for small molecules, perform poorly for these molecules. Here, we present random forest classifiers trained to discriminate correctly docked peptides. We show that, for a testing set of 47 protein-peptide complexes, structurally dissimilar from the training set and previously used to benchmark AutoDock Vina's ability to dock short peptides, these random forest classifiers improve docking power from ∼25% for AutoDock scoring functions to an average of ∼70%. These results pave the way for peptide-docking success rates comparable to those of small molecule docking. To develop these classifiers, we compiled the ProptPep37_2021 data set, a curated, high-quality set of 322 crystallographic protein-peptides complexes annotated with structural similarity information. The data set also provides a collection of high-quality putative poses with a range of deviations from the crystallographic pose, providing correct and incorrect poses (i.e., decoys) of the peptide for each entry. The ProptPep37_2021 data set as well as the classifiers presented here are freely available.
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http://dx.doi.org/10.1021/acs.jcim.1c00573DOI Listing
June 2021

Discovery of Potent Coumarin-Based Kinetic Stabilizers of Amyloidogenic Immunoglobulin Light Chains Using Structure-Based Design.

J Med Chem 2021 05 3;64(9):6273-6299. Epub 2021 May 3.

Department of Chemistry, The Scripps Research Institute, La Jolla, California 92037, United States.

In immunoglobulin light-chain (LC) amyloidosis, transient unfolding or unfolding and proteolysis enable aggregation of LC proteins, causing potentially fatal organ damage. A drug that kinetically stabilizes LCs could suppress aggregation; however, LC sequences are variable and have no natural ligands, hindering drug development efforts. We previously identified high-throughput screening hits that bind to a site at the interface between the two variable domains of the LC homodimer. We hypothesized that extending the stabilizers beyond this initially characterized binding site would improve affinity. Here, using protease sensitivity assays, we identified stabilizers that can be divided into four substructures. Some stabilizers exhibit nanomolar EC values, a 3000-fold enhancement over the screening hits. Crystal structures reveal a key π-π stacking interaction with a conserved tyrosine residue that was not utilized by the screening hits. These data provide a foundation for developing LC stabilizers with improved binding selectivity and enhanced physicochemical properties.
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http://dx.doi.org/10.1021/acs.jmedchem.1c00339DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8428256PMC
May 2021

Biased Docking for Protein-Ligand Pose Prediction.

Methods Mol Biol 2021 ;2266:39-72

Department of Integrative Structural and Computational Biology, Scripps Research, La Jolla, CA, USA.

The interaction between a protein and its ligands is one of the basic and most important processes in biological chemistry. Docking methods aim to predict the molecular 3D structure of protein-ligand complexes starting from coordinates of the protein and the ligand separately. They are widely used in both industry and academia, especially in the context of drug development projects. AutoDock4 is one of the most popular docking tools and, as for any docking method, its performance is highly system dependent. Knowledge about specific protein-ligand interactions on a particular target can be used to successfully overcome this limitation. Here, we describe how to apply the AutoDock Bias protocol, a simple and elegant strategy that allows users to incorporate target-specific information through a modified scoring function that biases the ligand structure towards those poses (or conformations) that establish selected interactions. We discuss two examples using different bias sources. In the first, we show how to steer dockings towards interactions derived from crystal structures of the receptor with different ligands; in the second example, we define and apply hydrophobic biases derived from Molecular Dynamics simulations in mixed solvents. Finally, we discuss general concepts of biased docking, its performance in pose prediction, and virtual screening campaigns as well as other potential applications.
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http://dx.doi.org/10.1007/978-1-0716-1209-5_3DOI Listing
April 2021

Accelerating AutoDock4 with GPUs and Gradient-Based Local Search.

J Chem Theory Comput 2021 Feb 6;17(2):1060-1073. Epub 2021 Jan 6.

Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California 92037, United States.

AutoDock4 is a widely used program for docking small molecules to macromolecular targets. It describes ligand-receptor interactions using a physics-inspired scoring function that has been proven useful in a variety of drug discovery projects. However, compared to more modern and recent software, AutoDock4 has longer execution times, limiting its applicability to large scale dockings. To address this problem, we describe an OpenCL implementation of AutoDock4, called AutoDock-GPU, that leverages the highly parallel architecture of GPU hardware to reduce docking runtime by up to 350-fold with respect to a single-threaded process. Moreover, we introduce the gradient-based local search method ADADELTA, as well as an improved version of the Solis-Wets random optimizer from AutoDock4. These efficient local search algorithms significantly reduce the number of calls to the scoring function that are needed to produce good results. The improvements reported here, both in terms of docking throughput and search efficiency, facilitate the use of the AutoDock4 scoring function in large scale virtual screening.
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http://dx.doi.org/10.1021/acs.jctc.0c01006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8063785PMC
February 2021

A Strain-Specific Inhibitor of Receptor-Bound HIV-1 Targets a Pocket near the Fusion Peptide.

Cell Rep 2020 11;33(8):108428

Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA; Center for HIV/AIDS Vaccine Immunology and Immunogen Discovery, International AIDS Vaccine Initiative Neutralizing Antibody Center, and Collaboration for AIDS Vaccine Discovery, The Scripps Research Institute, La Jolla, CA 92037, USA. Electronic address:

Disruption of viral fusion represents a viable, albeit under-explored, target for HIV therapeutics. Here, while studying the receptor-bound envelope glycoprotein conformation by cryoelectron microscopy (cryo-EM), we identify a pocket near the base of the trimer containing a bound detergent molecule and perform in silico drug screening by using a library of drug-like and commercially available molecules. After down-selection, we solve cryo-EM structures that validate the binding of two small molecule hits in very similar manners to the predicted binding poses, including interactions with aromatic residues within the fusion peptide. One of the molecules demonstrates low micromolar inhibition of the autologous virus by using a very rare phenylalanine in the fusion peptide and stabilizing the surrounding region. This work demonstrates that small molecules can target the fusion process, providing an additional target for anti-HIV therapeutics, and highlights the need to explore how fusion peptide sequence variations affect receptor-mediated conformational states across diverse HIV strains.
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http://dx.doi.org/10.1016/j.celrep.2020.108428DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7701285PMC
November 2020

Selective and Effective: Current Progress in Computational Structure-Based Drug Discovery of Targeted Covalent Inhibitors.

Trends Pharmacol Sci 2020 12 2;41(12):1038-1049. Epub 2020 Nov 2.

Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA. Electronic address:

Targeted covalent inhibitors are currently showing great promise for systems that are normally difficult to target with small molecule therapies. This renewed interest has spurred the refinement of existing computational methods as well as the designof new ones, expanding the toolbox for discovery and optimization of selectiveand effective covalent inhibitors. Commonly applied approaches are covalentdocking methods that predict the conformation of the covalent complex with known residues. More recently, a new predictive method, reactive docking, was developed, building on the growing corpus of data generated by large proteomics experiments. This method was successfully used in several 'inverse drug discovery' programs that use high-throughput techniques to isolate effective compounds based on screening of entire compound libraries based on desired phenotypes.
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http://dx.doi.org/10.1016/j.tips.2020.10.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7669701PMC
December 2020

Structure, lipid scrambling activity and role in autophagosome formation of ATG9A.

Nat Struct Mol Biol 2020 12 26;27(12):1194-1201. Epub 2020 Oct 26.

Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA.

De novo formation of the double-membrane compartment autophagosome is seeded by small vesicles carrying membrane protein autophagy-related 9 (ATG9), the function of which remains unknown. Here we find that ATG9A scrambles phospholipids of membranes in vitro. Cryo-EM structures of human ATG9A reveal a trimer with a solvated central pore, which is connected laterally to the cytosol through the cavity within each protomer. Similarities to ABC exporters suggest that ATG9A could be a transporter that uses the central pore to function. Moreover, molecular dynamics simulation suggests that the central pore opens laterally to accommodate lipid headgroups, thereby enabling lipids to flip. Mutations in the pore reduce scrambling activity and yield markedly smaller autophagosomes, indicating that lipid scrambling by ATG9A is essential for membrane expansion. We propose ATG9A acts as a membrane-embedded funnel to facilitate lipid flipping and to redistribute lipids added to the outer leaflet of ATG9 vesicles, thereby enabling growth into autophagosomes.
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http://dx.doi.org/10.1038/s41594-020-00520-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718406PMC
December 2020

Synthetic, Mechanistic, and Biological Interrogation of Chemical Space En Route to (-)-Bilobalide.

J Am Chem Soc 2020 10 16;142(43):18599-18618. Epub 2020 Oct 16.

Department of Chemistry, Scripps Research, La Jolla, California 92037, United States.

Here we interrogate the structurally dense (1.64 mcbits/Å) GABA receptor antagonist bilobalide, intermediates en route to its synthesis, and related mechanistic questions. C isotope labeling identifies an unexpected bromine migration en route to an α-selective, catalytic asymmetric Reformatsky reaction, ruling out an asymmetric allylation pathway. Experiment and computation converge on the driving forces behind two surprising observations. First, an oxetane acetal persists in concentrated mineral acid (1.5 M DCl in THF-/DO); its longevity is correlated to destabilizing steric clash between substituents upon ring-opening. Second, a regioselective oxidation of -hydroxybilobalide is found to rely on lactone acidification through lone-pair delocalization, which leads to extremely rapid intermolecular enolate equilibration. We also establish equivalent effects of (-)-bilobalide and the nonconvulsive sesquiterpene (-)-jiadifenolide on action potential-independent inhibitory currents at GABAergic synapses, using (+)-bilobalide as a negative control. The high information density of bilobalide distinguishes it from other scaffolds and may characterize natural product (NP) space more generally. Therefore, we also include a Python script to quickly (ca. 132 000 molecules/min) calculate information content (Böttcher scores), which may prove helpful to identify important features of NP space.
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http://dx.doi.org/10.1021/jacs.0c08231DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7727090PMC
October 2020

The AutoDock suite at 30.

Protein Sci 2021 01 12;30(1):31-43. Epub 2020 Sep 12.

Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, USA.

The AutoDock suite provides a comprehensive toolset for computational ligand docking and drug design and development. The suite builds on 30 years of methods development, including empirical free energy force fields, docking engines, methods for site prediction, and interactive tools for visualization and analysis. Specialized tools are available for challenging systems, including covalent inhibitors, peptides, compounds with macrocycles, systems where ordered hydration plays a key role, and systems with substantial receptor flexibility. All methods in the AutoDock suite are freely available for use and reuse, which has engendered the continued growth of a diverse community of primary users and third-party developers.
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http://dx.doi.org/10.1002/pro.3934DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7737764PMC
January 2021

An Activity-Guided Map of Electrophile-Cysteine Interactions in Primary Human T Cells.

Cell 2020 08 29;182(4):1009-1026.e29. Epub 2020 Jul 29.

Department of Chemistry, The Scripps Research Institute, La Jolla, CA 92037, USA. Electronic address:

Electrophilic compounds originating from nature or chemical synthesis have profound effects on immune cells. These compounds are thought to act by cysteine modification to alter the functions of immune-relevant proteins; however, our understanding of electrophile-sensitive cysteines in the human immune proteome remains limited. Here, we present a global map of cysteines in primary human T cells that are susceptible to covalent modification by electrophilic small molecules. More than 3,000 covalently liganded cysteines were found on functionally and structurally diverse proteins, including many that play fundamental roles in immunology. We further show that electrophilic compounds can impair T cell activation by distinct mechanisms involving the direct functional perturbation and/or degradation of proteins. Our findings reveal a rich content of ligandable cysteines in human T cells and point to electrophilic small molecules as a fertile source for chemical probes and ultimately therapeutics that modulate immunological processes and their associated disorders.
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http://dx.doi.org/10.1016/j.cell.2020.07.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775622PMC
August 2020

GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research.

ArXiv 2020 Jul 6. Epub 2020 Jul 6.

Protein-ligand docking is an in silico tool used to screen potential drug compounds for their ability to bind to a given protein receptor within a drug-discovery campaign. Experimental drug screening is expensive and time consuming, and it is desirable to carry out large scale docking calculations in a high-throughput manner to narrow the experimental search space. Few of the existing computational docking tools were designed with high performance computing in mind. Therefore, optimizations to maximize use of high-performance computational resources available at leadership-class computing facilities enables these facilities to be leveraged for drug discovery. Here we present the porting, optimization, and validation of the AutoDock-GPU program for the Summit supercomputer, and its application to initial compound screening efforts to target proteins of the SARS-CoV-2 virus responsible for the current COVID-19 pandemic.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7359529PMC
July 2020

Structural basis for the stabilization of amyloidogenic immunoglobulin light chains by hydantoins.

Bioorg Med Chem Lett 2020 08 16;30(16):127356. Epub 2020 Jun 16.

Department of Chemistry, The Scripps Research Institute, La Jolla, CA 92037, USA; The Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, CA 92037, USA. Electronic address:

Misfolding and aggregation of immunoglobulin light chains (LCs) leads to the degeneration of post-mitotic tissue in the disease immunoglobulin LC amyloidosis (AL). We previously reported the discovery of small molecule kinetic stabilizers of the native dimeric structure of full-length LCs, which slow or stop the LC aggregation cascade at the outset. A predominant structural category of kinetic stabilizers emerging from the high-throughput screen are coumarins substituted at the 7-position, which bind at the interface between the two variable domains of the light chain dimer. Here, we report the binding mode of another, more polar, LC kinetic stabilizer chemotype, 3,5-substituted hydantoins. Computational docking, solution nuclear magnetic resonance experiments, and x-ray crystallography show that the aromatic substructure emerging from the hydantoin 3-position occupies the same LC binding site as the coumarin ring. Notably, the hydantoin ring extends beyond the binding site mapped out by the coumarin hits. The hydantoin ring makes hydrogen bonds with both LC monomers simultaneously. The alkyl substructure at the hydantoin 5-position partially occupies a novel binding pocket proximal to the pocket occupied by the coumarin substructure. Overall, the hydantoin structural data suggest that a larger area of the LC variable-domain-variable-domain dimer interface is amenable to small molecule binding than previously demonstrated, which should facilitate development of more potent full-length LC kinetic stabilizers.
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http://dx.doi.org/10.1016/j.bmcl.2020.127356DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7402200PMC
August 2020

Initial Analysis of the Arylomycin D Antibiotics.

J Nat Prod 2020 07 2;83(7):2112-2121. Epub 2020 Jul 2.

Department of Chemistry, The Scripps Research Institute, La Jolla, California 92037, United States.

The arylomycins are a class of natural product antibiotics that inhibit bacterial type I signal peptidase and are under development as therapeutics. Four classes of arylomycins are known, arylomycins A-D. Previously, we reported the synthesis and analysis of representatives of the A, B, and C classes and showed that their spectrum of activity has the potential to be much broader than originally assumed. Along with a comparison of the mechanism of acquired and innate resistance, this led us to suggest that the arylomycins are latent antibiotics, antibiotics that once possessed broad-spectrum activity, but which upon examination today, have only narrow spectrum activity due to prior selection for resistance in the course of the competition with other microorganisms that drove their evolution in the first place. Interestingly, actinocarbasin, the only identified member of the arylomycin D class, has been reported to have activity against MRSA. To confirm and understand this activity, several actinocarbasin derivatives were synthesized. We demonstrate that the previously reported structure of actinocarbasin is incorrect, identify what is likely the correct scaffold, confirm that scaffold has activity against MRSA, and determine the origin of this activity.
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http://dx.doi.org/10.1021/acs.jnatprod.9b01174DOI Listing
July 2020

Discovery of small-molecule enzyme activators by activity-based protein profiling.

Nat Chem Biol 2020 09 8;16(9):997-1005. Epub 2020 Jun 8.

Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, USA.

Activity-based protein profiling (ABPP) has been used extensively to discover and optimize selective inhibitors of enzymes. Here, we show that ABPP can also be implemented to identify the converse-small-molecule enzyme activators. Using a kinetically controlled, fluorescence polarization-ABPP assay, we identify compounds that stimulate the activity of LYPLAL1-a poorly characterized serine hydrolase with complex genetic links to human metabolic traits. We apply ABPP-guided medicinal chemistry to advance a lead into a selective LYPLAL1 activator suitable for use in vivo. Structural simulations coupled to mutational, biochemical and biophysical analyses indicate that this compound increases LYPLAL1's catalytic activity likely by enhancing the efficiency of the catalytic triad charge-relay system. Treatment with this LYPLAL1 activator confers beneficial effects in a mouse model of diet-induced obesity. These findings reveal a new mode of pharmacological regulation for this large enzyme family and suggest that ABPP may aid discovery of activators for additional enzyme classes.
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http://dx.doi.org/10.1038/s41589-020-0555-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442688PMC
September 2020

Art and Science of the Cellular Mesoscale.

Trends Biochem Sci 2020 06 21;45(6):472-483. Epub 2020 Mar 21.

Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA.

Experimental information from microscopy, structural biology, and bioinformatics may be integrated to build structural models of entire cells with molecular detail. This integrative modeling is challenging in several ways: the intrinsic complexity of biology results in models with many closely packed and heterogeneous components; the wealth of available experimental data is scattered among multiple resources and must be gathered, reconciled, and curated; and computational infrastructure is only now gaining the capability of modeling and visualizing systems of this complexity. We present recent efforts to address these challenges, both with artistic approaches to depicting the cellular mesoscale, and development and application of methods to build quantitative models.
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http://dx.doi.org/10.1016/j.tibs.2020.02.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7230070PMC
June 2020

Charting Hydrogen Bond Anisotropy.

J Chem Theory Comput 2020 Apr 10;16(4):2846-2856. Epub 2020 Mar 10.

Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California 92037, United States.

A hydrogen bond (HB) is an essential interaction in countless phenomena, regulating the chemistry of life. HBs are characterized by two features, strength and directionality, with a high degree of heterogeneity across different chemical groups. These characteristics are dependent on the electronic configuration of the atoms involved in the interaction, which, in turn, is influenced strongly by the local molecular environment. Studies based on the analysis of HB in the solid phase, such as X-ray crystallography, suffer from significant biases due to packing forces. These will tend to better describe strong HBs at the expenses of weak ones, which will be either distorted or under-represented. Using quantum mechanics (QM), we calculated interaction energies for about a hundred acceptors and donors in a rigorously defined set of geometries. We performed 180,000 independent QM calculations, covering all relevant angular components, mapping strength and directionality in a context free from external biases, with both single-site and cooperative HBs. By quantifying directionality, we show that there is no correlation with strength; therefore, these two components need to be addressed separately. Results demonstrate that there are very strong HB acceptors (e.g., dimethyl sulfoxide) with nearly isotropic interactions and weak ones (e.g., thioacetone) with a sharp directional profile. Similarly, groups can have comparable directional propensity but be very distant in the strength spectrum (e.g., thioacetone and pyridine). Results provide a new perspective on the way HB directionality is described, with implications for biophysics and molecular recognition that ultimately can influence chemical biology, protein engineering, and drug design.
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http://dx.doi.org/10.1021/acs.jctc.9b01248DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7325729PMC
April 2020

Structural basis for strand-transfer inhibitor binding to HIV intasomes.

Science 2020 02 30;367(6479):810-814. Epub 2020 Jan 30.

The Salk Institute for Biological Studies, Laboratory of Genetics, La Jolla, CA 92037, USA.

The HIV intasome is a large nucleoprotein assembly that mediates the integration of a DNA copy of the viral genome into host chromatin. Intasomes are targeted by the latest generation of antiretroviral drugs, integrase strand-transfer inhibitors (INSTIs). Challenges associated with lentiviral intasome biochemistry have hindered high-resolution structural studies of how INSTIs bind to their native drug target. Here, we present high-resolution cryo-electron microscopy structures of HIV intasomes bound to the latest generation of INSTIs. These structures highlight how small changes in the integrase active site can have notable implications for drug binding and design and provide mechanistic insights into why a leading INSTI retains efficacy against a broad spectrum of drug-resistant variants. The data have implications for expanding effective treatments available for HIV-infected individuals.
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http://dx.doi.org/10.1126/science.aay8015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7357238PMC
February 2020

Integrative X-ray Structure and Molecular Modeling for the Rationalization of Procaspase-8 Inhibitor Potency and Selectivity.

ACS Chem Biol 2020 02 23;15(2):575-586. Epub 2020 Jan 23.

Departments of Biological Chemistry and Chemistry and Biochemistry, David Geffen School of Medicine , University of California, Los Angeles , 405 Hilgard Avenue , Los Angeles , California 90095 , United States.

Caspases are a critical class of proteases involved in regulating programmed cell death and other biological processes. Selective inhibitors of individual caspases, however, are lacking, due in large part to the high structural similarity found in the active sites of these enzymes. We recently discovered a small-molecule inhibitor, , that covalently binds the zymogen, or inactive precursor (pro-form), of caspase-8, but not other caspases, pointing to an untapped potential of procaspases as targets for chemical probes. Realizing this goal would benefit from a structural understanding of how small molecules bind to and inhibit caspase zymogens. There have, however, been very few reported procaspase structures. Here, we employ X-ray crystallography to elucidate a procaspase-8 crystal structure in complex with , which reveals large conformational changes in active-site loops that accommodate the intramolecular cleavage events required for protease activation. Combining these structural insights with molecular modeling and mutagenesis-based biochemical assays, we elucidate key interactions required for inhibition of procaspase-8. Our findings inform the mechanism of caspase activation and its disruption by small molecules and, more generally, have implications for the development of small molecule inhibitors and/or activators that target alternative (e.g., inactive precursor) protein states to ultimately expand the druggable proteome.
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http://dx.doi.org/10.1021/acschembio.0c00019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7370820PMC
February 2020

D3R Grand Challenge 4: prospective pose prediction of BACE1 ligands with AutoDock-GPU.

J Comput Aided Mol Des 2019 12 6;33(12):1071-1081. Epub 2019 Nov 6.

Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, USA.

In this paper we describe our approaches to predict the binding mode of twenty BACE1 ligands as part of Grand Challenge 4 (GC4), organized by the Drug Design Data Resource. Calculations for all submissions (except for one, which used AutoDock4.2) were performed using AutoDock-GPU, the new GPU-accelerated version of AutoDock4 implemented in OpenCL, which features a gradient-based local search. The pose prediction challenge was organized in two stages. In Stage 1a, the protein conformations associated with each of the ligands were undisclosed, so we docked each ligand to a set of eleven receptor conformations, chosen to maximize the diversity of binding pocket topography. Protein conformations were made available in Stage 1b, making it a re-docking task. For all calculations, macrocyclic conformations were sampled on the fly during docking, taking the target structure into account. To leverage information from existing structures containing BACE1 bound to ligands available in the PDB, we tested biased docking and pose filter protocols to facilitate poses resembling those experimentally determined. Both pose filters and biased docking resulted in more accurate docked poses, enabling us to predict for both Stages 1a and 1b ligand poses within 2 Å RMSD from the crystallographic pose. Nevertheless, many of the ligands could be correctly docked without using existing structural information, demonstrating the usefulness of physics-based scoring functions, such as the one used in AutoDock4, for structure based drug design.
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http://dx.doi.org/10.1007/s10822-019-00241-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7325737PMC
December 2019

Comparison of affinity ranking using AutoDock-GPU and MM-GBSA scores for BACE-1 inhibitors in the D3R Grand Challenge 4.

J Comput Aided Mol Des 2019 12 6;33(12):1011-1020. Epub 2019 Nov 6.

Department of Pharmaceutical Sciences, University of California, Irvine, Irvine, USA.

Molecular docking has been successfully used in computer-aided molecular design projects for the identification of ligand poses within protein binding sites. However, relying on docking scores to rank different ligands with respect to their experimental affinities might not be sufficient. It is believed that the binding scores calculated using molecular mechanics combined with the Poisson-Boltzman surface area (MM-PBSA) or generalized Born surface area (MM-GBSA) can predict binding affinities more accurately. In this perspective, we decided to take part in Stage 2 of the Drug Design Data Resource (D3R) Grand Challenge 4 (GC4) to compare the performance of a quick scoring function, AutoDock4, to that of MM-GBSA in predicting the binding affinities of a set of [Formula: see text]-Amyloid Cleaving Enzyme 1 (BACE-1) ligands. Our results show that re-scoring docking poses using MM-GBSA did not improve the correlation with experimental affinities. We further did a retrospective analysis of the results and found that our MM-GBSA protocol is sensitive to details in the protein-ligand system: (i) neutral ligands are more adapted to MM-GBSA calculations than charged ligands, (ii) predicted binding affinities depend on the initial conformation of the BACE-1 receptor, (iii) protonating the aspartyl dyad of BACE-1 correctly results in more accurate binding affinity predictions.
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http://dx.doi.org/10.1007/s10822-019-00240-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7027993PMC
December 2019

Expedited mapping of the ligandable proteome using fully functionalized enantiomeric probe pairs.

Nat Chem 2019 12 28;11(12):1113-1123. Epub 2019 Oct 28.

Department of Chemistry, The Scripps Research Institute, La Jolla, CA, USA.

A fundamental challenge in chemical biology and medicine is to understand and expand the fraction of the human proteome that can be targeted by small molecules. We recently described a strategy that integrates fragment-based ligand discovery with chemical proteomics to furnish global portraits of reversible small-molecule/protein interactions in human cells. Excavating clear structure-activity relationships from these 'ligandability' maps, however, was confounded by the distinct physicochemical properties and corresponding overall protein-binding potential of individual fragments. Here, we describe a compelling solution to this problem by introducing a next-generation set of fully functionalized fragments differing only in absolute stereochemistry. Using these enantiomeric probe pairs, or 'enantioprobes', we identify numerous stereoselective protein-fragment interactions in cells and show that these interactions occur at functional sites on proteins from diverse classes. Our findings thus indicate that incorporating chirality into fully functionalized fragment libraries provides a robust and streamlined method to discover ligandable proteins in cells.
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http://dx.doi.org/10.1038/s41557-019-0351-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874898PMC
December 2019

SuFEx-enabled, agnostic discovery of covalent inhibitors of human neutrophil elastase.

Proc Natl Acad Sci U S A 2019 09 4;116(38):18808-18814. Epub 2019 Sep 4.

Department of Chemistry, The Scripps Research Institute, La Jolla, CA 92037;

Sulfur fluoride exchange (SuFEx) has emerged as the new generation of click chemistry. We report here a SuFEx-enabled, agnostic approach for the discovery and optimization of covalent inhibitors of human neutrophil elastase (hNE). Evaluation of our ever-growing collection of SuFExable compounds toward various biological assays unexpectedly revealed a selective and covalent hNE inhibitor: benzene-1,2-disulfonyl fluoride. Synthetic derivatization of the initial hit led to a more potent agent, 2-(fluorosulfonyl)phenyl fluorosulfate with IC 0.24 μM and greater than 833-fold selectivity over the homologous neutrophil serine protease, cathepsin G. The optimized, yet simple benzenoid probe only modified active hNE and not its denatured form.
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http://dx.doi.org/10.1073/pnas.1909972116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6754619PMC
September 2019

AutoGridFR: Improvements on AutoDock Affinity Maps and Associated Software Tools.

J Comput Chem 2019 12 22;40(32):2882-2886. Epub 2019 Aug 22.

Integrated Computational and Structural Biology, The Scripps Research Institute, La Jolla, California.

Precomputed affinity maps are used by AutoDock to efficiently describe rigid biomolecules called receptors in automated docking. These maps greatly speed up the docking process and allow users to experiment with the forcefield. Here, we present AutoGridFR (AGFR): a software tool facilitating the calculation of these maps. We describe a new version of the AutoSite algorithm that improves the description of binding pockets automatically detected on receptors, and an algorithm for adding affinity gradients which help search methods optimize solution using fewer evaluations of the scoring functions. AGFR supports the calculation of maps for various advanced docking techniques such as covalent docking, hydrated docking, and docking with flexible receptor sidechains. Maps are stored in a single file along with metadata supporting data provenance, reproducibility, and facilitating their management. Finally, maps can be calculated from the command line or through a modern graphical user interface which also supports their visualization. © 2019 Wiley Periodicals, Inc.
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http://dx.doi.org/10.1002/jcc.26054DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7737998PMC
December 2019

Integrative modeling of the HIV-1 ribonucleoprotein complex.

PLoS Comput Biol 2019 06 13;15(6):e1007150. Epub 2019 Jun 13.

Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, United States of America.

A coarse-grain computational method integrates biophysical and structural data to generate models of HIV-1 genomic RNA, nucleocapsid and integrase condensed into a mature ribonucleoprotein complex. Several hypotheses for the initial structure of the genomic RNA and oligomeric state of integrase are tested. In these models, integrase interaction captures features of the relative distribution of gRNA in the immature virion and increases the size of the RNP globule, and exclusion of nucleocapsid from regions with RNA secondary structure drives an asymmetric placement of the dimerized 5'UTR at the surface of the RNP globule.
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http://dx.doi.org/10.1371/journal.pcbi.1007150DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6592547PMC
June 2019

Novel Intersubunit Interaction Critical for HIV-1 Core Assembly Defines a Potentially Targetable Inhibitor Binding Pocket.

mBio 2019 03 12;10(2). Epub 2019 Mar 12.

Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, USA

HIV-1 capsid protein (CA) plays critical roles in both early and late stages of the viral replication cycle. Mutagenesis and structural experiments have revealed that capsid core stability significantly affects uncoating and initiation of reverse transcription in host cells. This has led to efforts in developing antivirals targeting CA and its assembly, although none of the currently identified compounds are used in the clinic for treatment of HIV infection. A specific interaction that is primarily present in pentameric interfaces in the HIV-1 capsid core was identified and is reported to be important for CA assembly. This is shown by multidisciplinary characterization of CA site-directed mutants using biochemical analysis of virus-like particle formation, transmission electron microscopy of assembly, crystallographic studies, and molecular dynamic simulations. The data are consistent with a model where a hydrogen bond between CA residues E28 and K30' from neighboring N-terminal domains (CAs) is important for CA pentamer interactions during core assembly. This pentamer-preferred interaction forms part of an -terminal omain nterface (NDI) pocket that is amenable to antiviral targeting. Precise assembly and disassembly of the HIV-1 capsid core are key to the success of viral replication. The forces that govern capsid core formation and dissociation involve intricate interactions between pentamers and hexamers formed by HIV-1 CA. We identified one particular interaction between E28 of one CA and K30' of the adjacent CA that appears more frequently in pentamers than in hexamers and that is important for capsid assembly. Targeting the corresponding site could lead to the development of antivirals which disrupt this interaction and affect capsid assembly.
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http://dx.doi.org/10.1128/mBio.02858-18DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6414707PMC
March 2019

AutoDock Bias: improving binding mode prediction and virtual screening using known protein-ligand interactions.

Bioinformatics 2019 10;35(19):3836-3838

Departamento de Química Biológica e IQUIBICEN-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Buenos Aires C1428EHA, Argentina.

Summary: The performance of docking calculations can be improved by tuning parameters for the system of interest, e.g. biasing the results towards the formation of relevant protein-ligand interactions, such as known ligand pharmacophore or interaction sites derived from cosolvent molecular dynamics. AutoDock Bias is a straightforward and easy to use script-based method that allows the introduction of different types of user-defined biases for fine-tuning AutoDock4 docking calculations.

Availability And Implementation: AutoDock Bias is distributed with MGLTools (since version 1.5.7), and freely available on the web at http://ccsb.scripps.edu/mgltools/ or http://autodockbias.wordpress.com.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btz152DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6761960PMC
October 2019

Massive-Scale Binding Free Energy Simulations of HIV Integrase Complexes Using Asynchronous Replica Exchange Framework Implemented on the IBM WCG Distributed Network.

J Chem Inf Model 2019 04 22;59(4):1382-1397. Epub 2019 Feb 22.

Center for Biophysics and Computational Biology and Department of Chemistry , Temple University , Philadelphia , Pennsylvania 19122 , United States.

To perform massive-scale replica exchange molecular dynamics (REMD) simulations for calculating binding free energies of protein-ligand complexes, we implemented the asynchronous replica exchange (AsyncRE) framework of the binding energy distribution analysis method (BEDAM) in implicit solvent on the IBM World Community Grid (WCG) and optimized the simulation parameters to reduce the overhead and improve the prediction power of the WCG AsyncRE simulations. We also performed the first massive-scale binding free energy calculations using the WCG distributed computing grid and 301 ligands from the SAMPL4 challenge for large-scale binding free energy predictions of HIV-1 integrase complexes. In total there are ∼10000 simulated complexes, ∼1 million replicas, and ∼2000 μs of aggregated MD simulations. Running AsyncRE MD simulations on the WCG requires accepting a trade-off between the number of replicas that can be run (breadth) and the number of full RE cycles that can be completed per replica (depth). As compared with synchronous Replica Exchange (SyncRE) running on tightly coupled clusters like XSEDE, on the WCG many more replicas can be launched simultaneously on heterogeneous distributed hardware, but each full RE cycle requires more overhead. We compared the WCG results with that from AutoDock and more advanced RE simulations including the use of flattening potentials to accelerate sampling of selected degrees of freedom of ligands and/or receptors related to slow dynamics due to high energy barriers. We propose a suitable strategy of RE simulations to refine high throughput docking results which can be matched to corresponding computing resources: from HPC clusters, to small or medium-size distributed campus grids, and finally to massive-scale computing networks including millions of CPUs like the resources available on the WCG.
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http://dx.doi.org/10.1021/acs.jcim.8b00817DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6496938PMC
April 2019

Structural Basis of Altered Potency and Efficacy Displayed by a Major in Vivo Metabolite of the Antidiabetic PPARγ Drug Pioglitazone.

J Med Chem 2019 02 7;62(4):2008-2023. Epub 2019 Feb 7.

Department of Integrative Structural and Computational Biology , The Scripps Research Institute , La Jolla , California 92037 , United States.

Pioglitazone (Pio) is a Food and Drug Administration-approved drug for type-2 diabetes that binds and activates the nuclear receptor peroxisome proliferator-activated receptor γ (PPARγ), yet it remains unclear how in vivo Pio metabolites affect PPARγ structure and function. Here, we present a structure-function comparison of Pio and its most abundant in vivo metabolite, 1-hydroxypioglitazone (PioOH). PioOH displayed a lower binding affinity and reduced potency in co-regulator recruitment assays. X-ray crystallography and molecular docking analysis of PioOH-bound PPARγ ligand-binding domain revealed an altered hydrogen bonding network, including the formation of water-mediated bonds, which could underlie its altered biochemical phenotype. NMR spectroscopy and hydrogen/deuterium exchange mass spectrometry analysis coupled to activity assays revealed that PioOH better stabilizes the PPARγ activation function-2 (AF-2) co-activator binding surface and better enhances co-activator binding, affording slightly better transcriptional efficacy. These results indicating that Pio hydroxylation affects its potency and efficacy as a PPARγ agonist contributes to our understanding of PPARγ-drug metabolite interactions.
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http://dx.doi.org/10.1021/acs.jmedchem.8b01573DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6898968PMC
February 2019

Humanized GPIbα-von Willebrand factor interaction in the mouse.

Blood Adv 2018 10;2(19):2522-2532

Department of Molecular Medicine, MERU-Roon Research Center on Vascular Biology, and.

The interaction of platelet glycoprotein Ibα (GPIbα) with von Willebrand factor (VWF) initiates hemostasis after vascular injury and also contributes to pathological thrombosis. GPIbα binding to the VWF A1 domain (VWFA1) is a target for antithrombotic intervention, but attempts to develop pharmacologic inhibitors have been hindered by the lack of animal models because of the species specificity of the interaction. To address this problem, we generated a knockin mouse with exon 28-encoding domains A1 and A2 replaced by the human homolog (VWF). VWF mice (M1HA) were crossbred with a transgenic mouse strain expressing human GPIbα on platelets (mGPIbα;hGPIbα; H1MA) to generate a new strain (H1HA) with humanized GPIbα-VWFA1 binding. Plasma VWF levels in the latter 3 strains were similar to those of wild-type mice (M1MA). Compared with the strains that had homospecific GPIbα-VWF pairing (M1MA and H1HA), M1HA mice of those with heterospecific pairing had a markedly greater prolongation of tail bleeding time and attenuation of thrombogenesis after injury to the carotid artery than H1MA mice. Measurements of GPIbα-VWFA1 binding affinity by surface plasmon resonance agreed with the extent of observed functional defects. Ristocetin-induced platelet aggregation was similar in H1HA mouse and human platelet-rich plasma, and it was comparably inhibited by monoclonal antibody NMC-4, which is known to block human GPIbα-VWFA1 binding, which also inhibited FeCl-induced mouse carotid artery thrombosis. Thus, the H1HA mouse strain is a fully humanized model of platelet GPIbα-VWFA1 binding that provides mechanistic and pharmacologic information relevant to human hemostatic and thrombotic disorders.
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http://dx.doi.org/10.1182/bloodadvances.2018023507DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6177644PMC
October 2018
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