Biology subjects

Tummino, T. A.

Publications and source records attributed to Tummino, T. A..

8 recordsLinked to original sources

bioRxiv2026

Library docking for Cannabinoid-2 Receptor ligands

Cannabinoid receptors are therapeutically promising GPCRs that are also interesting test systems for structure-based methods, which have targeted them previously. Here we used the CB2 receptor as a template to explore several topical questions in library docking. Whereas an earlier campaign against the CB1 receptor led to potent but relatively non-selective ligands, here we found that targeting interactions with polar, orthosteric site residues led to subtype-selective ligands. Docking hit rate and especially hit affinity improved in moving from a 7 million to a 2.6 billion molecule library. Similar to earlier studies, docking against active and inactive states of the receptor did not reliably bias toward the discovery of agonists or inverse agonists. Cryo-EM structures of two of the new agonists, each in a different chemotype, superposed well on the docking predictions. Correspondingly, structure-based optimization led to 10- to 140-fold improvements within three different series, also consistent with well-behaved ligand families. Hit rates with a fully enumerated 2.6 billion molecule library resembled those of an implied 11 billion molecule library from a building-block method, consistent with the latters ability to explore this space, though higher affinities were discovered from the fully enumerated set. Overall, eight diverse families of ligands, with potencies <100 nM and mostly unrelated to previously known ligands were found. Implications for future studies are considered.

biochemistry↗

bioRxiv2025

A database for large-scale docking and experimental results

The rapid expansion of readily accessible compounds over the past six years has transformed molecular docking, improving hit rates and affinities. While many millions of molecules may score well in a docking campaign, the results are rarely fully shared, hindering the benchmarking of machine learning and chemical space exploration methods that seek to explore the expanding chemical spaces. To address this gap, we develop a website providing access to recent large library campaigns, including poses, scores, and in vitro results for campaigns against 11 targets, with 6.3 billion molecules docked and 3729 compounds experimentally tested. In a simple proof-of-concept study that speaks to the new librarys utility, we use the new database to train machine learning models to predict docking scores and to find the top 0.01% scoring molecules while evaluating only 1% of the library. Even in these proof-of-concept studies, some interesting trends emerge: unsurprisingly, as models train on larger sets, they perform better; less expected, models could achieve high correlations with docking scores and yet still fail to enrich the new docking-discovered ligands, or even the top 0.01% of docking-ranked molecules. It will be interesting to see how these trends develop for methods more sophisticated than the simple proof-of-concept studies undertaken here; the database is openly available at lsd.docking.org.

biophysics↗

bioRxiv2023

Structure-based discovery of cannabinoid-1 receptor agonists with reduced side effects

Large library docking can reveal unexpected chemotypes that complement the structures of biological targets. Seeking new agonists for the cannabinoid-1 receptor (CB1R), we docked 74 million tangible molecules, prioritizing 46 high ranking ones for de novo synthesis and testing. Nine were active by radioligand competition, a 20% hit-rate. Structure-based optimization of one of the most potent of these (Ki = 0.7 {micro}M) led to 4042, a 1.9 nM ligand and a full CB1R agonist. A cryo-EM structure of the purified enantiomer of 4042 ( 1350) in complex with CB1R-Gi1 confirmed its docked pose. The new agonist was strongly analgesic, with generally a 5-10-fold therapeutic window over sedation and catalepsy and no observable conditioned place preference. These findings suggest that new cannabinoid chemotypes may disentangle characteristic cannabinoid side-effects from their analgesia, supporting the further development of cannabinoids as pain therapeutics.

pharmacology and toxicology↗

bioRxiv2021

Colloidal aggregators in biochemical SARS-CoV-2 repurposing screens

To fight the SARS-CoV-2 pandemic, much effort has been directed toward drug repurposing, testing investigational and approved drugs against several viral or human proteins in vitro. Here we investigate the impact of colloidal aggregation, a common artifact in early drug discovery, in these repurposing screens. We selected 56 drugs reported to be active in biochemical assays and tested them for aggregation by both dynamic light scattering and by enzyme counter screening with and without detergent; seventeen of these drugs formed colloids at concentrations similar to their literature reported IC50s. To investigate the occurrence of colloidal aggregators more generally in repurposing libraries, we further selected 15 drugs that had physical properties resembling known aggregators from a common repurposing library, and found that 6 of these aggregated at micromolar concentrations. An attraction of repurposing is that drugs active on one target are considered de-risked on another. This study suggests not only that many of the drugs repurposed for SARS-CoV-2 in biochemical assays are artifacts, but that, more generally, when screened at relevant concentrations, drugs can act artifactually via colloidal aggregation. Understanding the role of aggregation, and detecting its effects rapidly, will allow the community to focus on those drugs and leads that genuinely have potential for treating COVID-19. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/458413v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@bfe5a2org.highwire.dtl.DTLVardef@7d05a1org.highwire.dtl.DTLVardef@1fcc3a5org.highwire.dtl.DTLVardef@190a153_HPS_FORMAT_FIGEXP M_FIG Table of Contents Graphic C_FIG

biochemistry↗

bioRxiv2021

Crystal structures of the σ2 receptor template large-library docking for selective chemotypes active in vivo

The {sigma}2 receptor is a poorly understood transmembrane receptor that has attracted intense interest in many areas of biology including cancer imaging, Alzheimers disease, schizophrenia, and neuropathic pain. However, little is known regarding the molecular details of the receptor, and few highly selective ligands are available. Here, we report the crystal structure of the {sigma}2 receptor in complex with the clinical drug candidate roluperidone and the probe compound PB28. These structures, in turn, templated a large-scale docking screen of 490 million make-on-demand molecules. Of these, 484 compounds were synthesized and tested, prioritizing not only high-ranking docked molecules, but also those with mediocre and poor scores. Overall, 127 compounds with binding affinities superior to 1 M were identified, all in new chemotypes, 31 of which had affinities superior to 50 nM. Intriguingly, hit rate fell smoothly and monotonically with docking score. Seeking to develop selective and biologically active probe molecules, we optimized three of the original docking hits for potency and for selectivity, achieving affinities in the 3 to 48 nM range and to up to 250-fold selectivity vs. the {sigma}1 receptor. Crystal structures of the newly discovered ligands bound to the {sigma}2 receptor were subsequently determined, confirming the docked poses. To investigate the contribution of the {sigma}2 receptor in pain processing, and to distinguish it from the contribution of the {sigma}1 receptor, two potent {sigma}2-selective and one potent {sigma}1/{sigma}2 non-selective ligand were tested for efficacy in a mouse model of neuropathic pain. All three ligands demonstrated timedependent decreases in mechanical hypersensitivity in the spared nerve injury model, supporting a role for the {sigma}2 receptor in nociception, and a possible role for {sigma}1/{sigma}2 polypharmacology. This study illustrates the opportunities for rapid discovery of in vivo active and selective probes to study under-explored areas of biology using structurebased screens of diverse, ultra-large libraries following the elucidation of protein structures.

pharmacology and toxicology↗

bioRxiv2021

Phospholipidosis is a shared mechanism underlying the in vitro antiviral activity of many repurposed drugs against SARS-CoV-2

Repurposing drugs as treatments for COVID-19 has drawn much attention. A common strategy has been to screen for established drugs, typically developed for other indications, that are antiviral in cells or organisms. Intriguingly, most of the drugs that have emerged from these campaigns, though diverse in structure, share a common physical property: cationic amphiphilicity. Provoked by the similarity of these repurposed drugs to those inducing phospholipidosis, a well-known drug side effect, we investigated phospholipidosis as a mechanism for antiviral activity. We tested 23 cationic amphiphilic drugs--including those from phenotypic screens and others that we ourselves had found--for induction of phospholipidosis in cell culture. We found that most of the repurposed drugs, which included hydroxychloroquine, azithromycin, amiodarone, and four others that have already progressed to clinical trials, induced phospholipidosis in the same concentration range as their antiviral activity; indeed, there was a strong monotonic correlation between antiviral efficacy and the magnitude of the phospholipidosis. Conversely, drugs active against the same targets that did not induce phospholipidosis were not antiviral. Phospholipidosis depends on the gross physical properties of drugs, and does not reflect specific target-based activities, rather it may be considered a confound in early drug discovery. Understanding its role in infection, and detecting its effects rapidly, will allow the community to better distinguish between drugs and lead compounds that more directly impact COVID-19 from the large proportion of molecules that manifest this confounding effect, saving much time, effort and cost. One Sentence SummaryDrug-induced phospholipidosis is a single mechanism that may explain the in vitro efficacy of a wide-variety of therapeutics repurposed for COVID-19.

pharmacology and toxicology↗

bioRxiv2020

A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing

An outbreak of the novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 290,000 people since the end of 2019, killed over 12,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven efficacy nor are there vaccines for its prevention. Unfortunately, the scientific community has little knowledge of the molecular details of SARS-CoV-2 infection. To illuminate this, we cloned, tagged and expressed 26 of the 29 viral proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), which identified 332 high confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 existing FDA-approved drugs, drugs in clinical trials and/or preclinical compounds, that we are currently evaluating for efficacy in live SARS-CoV-2 infection assays. The identification of host dependency factors mediating virus infection may provide key insights into effective molecular targets for developing broadly acting antiviral therapeutics against SARS-CoV-2 and other deadly coronavirus strains.

systems biology↗

bioRxiv2020

Simultaneous classification of neuroactive compounds in zebrafish

Neuroactive compounds are crucial tools in drug discovery and neuroscience, but it remains difficult to discover neuroactive compounds with new mechanisms of action. To address this need, researchers have developed mid-throughput phenotype-first approaches using zebrafish. This study introduces an open, non-commercial, and extensible hardware/software platform that captures and analyzes drugmodulated phenotypic responses larval zebrafish. We provide full specifications, computer-aided design (CAD) documents, and source code. Accompanying this study, we are also publicly depositing phenotypic data on 3.9 million animals and 34,000 compounds. The data include a high-replicate benchmark set on 14 compounds, a wellcontrolled reference set of 648 known neuroactive compounds, 20 specialized reference sets, a library of 1,520 FDA-approved drugs, 3 screening libraries. This open data resource is curated, structured, tied to extensive metadata, and available under a Creative Commons CC-BY license.

systems biology↗