Arthur J. Olson

In thinking back on Richard Lerner's impact on our lab's trajectory at Scripps Research, we see his fingerprints on all the efforts we have undertaken over the last 40 years. Immunology and virology have been a continuing driving focus in our software development and application within the Molecular Graphics Lab (now the Center for Computational Structural Biology – CCSB), spurred on by the marriage of chemistry with biology that Richard enabled at Scripps. Many of our earliest and continuing computational docking targets have been focused on HIV with collaborations with Chi‐Huey Wong and Barry Sharpless. Along with subsequent computational work with Jeff Kelly, Reza Ghadiri, Udi Keinan and Ben Cravatt we have been able to sustain continuous efforts in developing and applying docking and other computational technologies to structural chemistry problems. In this remembrance, we give our reflections of Richard Lerner's character, vision, and his inspiration in our scientific lives and in the environment that he created at Scripps Research.

Models of insulin secretory vesicles from pancreatic beta cells have been created using the cellPACK suite of tools to research, curate, construct and visualise the current state of knowledge. The model integrates experimental information from proteomics, structural biology, cryoelectron microscopy and X-ray tomography, and is used to generate models of mature and immature vesicles. A new method was developed to generate a confidence score that reconciles inconsistencies between three available proteomes using expert annotations of cellular localisation. The models are used to simulate soft X-ray tomograms, allowing quantification of features that are observed in experimental tomograms, and in turn, allowing interpretation of X-ray tomograms at the molecular level.

CellPAINT is an interactive digital tool that allows non-expert users to create illustrations of the molecular structure of cells and viruses. We present a new release with several key enhancements, including the ability to generate custom ingredients from structure information in the Protein Data Bank, and interaction, grouping, and locking functions that streamline the creation of assemblies and illustration of large, complex scenes. An example of CellPAINT as a tool for hypothesis generation in the interpretation of cryoelectron tomograms is presented. CellPAINT is freely available at http://ccsb.scripps.edu/cellpaint.

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.

Tuberculosis, caused by Mycobacterium tuberculosis (M. tuberculosis), kills 1.6 million people annually. To bridge the gap between structure- and cell-based drug discovery strategies, we are pioneering a computer-aided discovery paradigm that merges structure-based virtual screening with ligand-based, machine learning methods trained with cell-based data. This approach successfully identified N-(3-methoxyphenyl)-7-nitrobenzo[c][1,2,5]oxadiazol-4-amine (JSF-2164) as an inhibitor of purified InhA with whole-cell efficacy versus in vitro cultured M. tuberculosis. When the intrabacterial drug metabolism (IBDM) platform was leveraged, mechanistic studies demonstrated that JSF-2164 underwent a rapid F₄₂₀H₂-dependent biotransformation within M. tuberculosis to afford intrabacterial nitric oxide and two amines, identified as JSF-3616 and JSF-3617. Thus, metabolism of JSF-2164 obscured the InhA inhibition phenotype within cultured M. tuberculosis. This study demonstrates a new docking/Bayesian computational strategy to combine cell- and target-based drug screening and the need to probe intrabacterial metabolism when clarifying the antitubercular mechanism of action.

Visualization of biological mesoscale models provides a glimpse at the inner workings of living cells. One of the most complex components of these models is DNA, which is of fundamental importance for all forms of life. Modeling the 3D structure of genomes has previously only been attempted by sequential approaches. We present the first parallel approach for the instant construction of DNA structures. Traditionally, such structures are generated with algorithms like random walk, which have inherent sequential constraints. These algorithms result in the desired structure, are easy to control, and simple to formulate. Their execution, however, is very time‐consuming, as they are not designed to exploit parallelism. We propose an approach to parallelize the process, facilitating an implementation on the GPU.

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 in vitro 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 (CA_NTDs) is important for CA pentamer interactions during core assembly. This pentamer-preferred interaction forms part of an N-terminal domain interface (NDI) pocket that is amenable to antiviral targeting. IMPORTANCE 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.