Biology subjects

Abel, R.

Publications and source records attributed to Abel, R..

5 recordsLinked to original sources

bioRxiv2026

Toward a Random Background for Ligand Optimization

Ligand optimization is central to drug discovery as hundreds of analogs might be designed and synthesized between an initial hit and a therapeutic candidate. The efficiency of this process is unclear, at least partly because there is no random background for optimization against which to compare. Such a random background might emerge from synthetically accessible but otherwise systematic random small substitutions across starting ligands, measuring likelihood of achieving a substantial improvement in affinity/potency or other property by any single perturbation. Recent literature and ligand-affinity/potency databases suggest that perhaps 10% of analogs with minor modifications improve upon a parents potency substantially (by [≥]10-fold), but this number is clouded by reporting bias, intentional improvement, and inter-group reproducibility. To begin to establish a background expectation for ligand optimization, we comprehensively and systematically modified 18 lead molecules across six targets with single atom changes; 257 compounds were synthesized. Unexpectedly, 11.2% of these random small perturbation analogs improved potency by [≥]10-fold over their parents. Conversely, these more potent analogs typically had worse in vitro pharmacokinetics (e.g. reduced metabolic stability, lower plasma free fraction). While it was possible to find analogs where the potency increase compensated for inferior exposure and half-life, resulting in more potent compounds in vivo, overall a frustrated landscape for ligand optimization is revealed. This study begins to establish a background expectation for ligand potency optimization and offers a simple strategy to do so. It also begins to quantify the challenges confronting the field in moving beyond in vitro potency.

pharmacology and toxicology↗

bioRxiv2024

Runaway resorption of microcracks contributes to age-related hip-fracture patients

Microdefects, including microcracks and resorption trenches, may be important contributors to bone fragility. 3D microdefect morphology was imaged using synchrotron micro-CT to develop a classification system for investigating the relationship with bone mechanics and hip-fractures. Femoral heads from ageing hip-fracture patients (n=5, 74-82 years) were compared to ageing non-fracture controls (n=5, 72-84 years). Two trabecular cores were prepared from the chiasma; one was imaged using synchrotron micro-CT to measure microdefects and one was mechanically tested to measure tensile strength. Morphological and mechanical data were compared and correlated using Mann Whitney U test and Pearsons rank correlation. Microdefects varied and were classified into four categories based on shape and measurable parameters. Hip-fracture donors exhibited significantly higher density of all microdefects (p<0.05). Microdefect volume was strongly negatively correlated with ultimate tensile strength (p<0.05) and stiffness (p<0.05). Microdefects might contribute to loss of bone strength and fragility fracture via runaway resorption. Microcracks could promote focussed osteoclastic resorption and the formation of resorption pits which create stress risers leading to the re-formation of microcracks under continued load. CT-based classification methods should be used to explore the complex interaction between microdefects, metabolism, and bone fracture mechanics.

bioengineering↗

bioRxiv2021

Bioluminescent Synthetic Cells Communicate with Natural Cells and Self-Activate Light-Responsive Proteins

Development of regulated cellular processes and signaling methods in synthetic cells is essential for their integration with living materials. Light is an attractive tool to achieve this, but the limited penetration depth into tissue of visible light restricts its usability for in-vivo applications. Here, we describe the synthesis and application of blue-light-generating synthetic cells using bioluminescence, dismissing the need for an external light source. First, the lipid membrane and internal composition of light-producing synthetic cells were optimized to enable high-intensity emission. Next, we show these cells capacity for triggering bioprocesses in natural cells by initiating asexual sporulation of dark-grown mycelial cells of the fungus Trichoderma atroviride in a quorum-sensing like mechanism. Finally, we demonstrate regulated transcription and membrane recruitment in synthetic cells using bioluminescent self-activating fusion proteins. These functionalities pave the way for deploying synthetic cells as embeddable microscale light sources that are capable of activating engineered processes inside tissues.

bioengineering↗

bioRxiv2020

Is structure based drug design ready for selectivity optimization?

Alchemical free energy calculations are now widely used to drive or maintain potency in small molecule lead optimization with a roughly 1 kcal/mol accuracy. Despite this, the potential to use free energy calculations to drive optimization of compound selectivity among two similar targets has been relatively unexplored in published studies. In the most optimistic scenario, the similarity of binding sites might lead to a fortuitous cancellation of errors and allow selectivity to be predicted more accurately than affinity. Here, we assess the accuracy with which selectivity can be predicted in the context of small molecule kinase inhibitors, considering the very similar binding sites of human kinases CDK2 and CDK9, as well as another series of ligands attempting to achieve selectivity between the more distantly related kinases CDK2 and ERK2. Using a Bayesian analysis approach, we separate systematic from statistical error and quantify the correlation in systematic errors between selectivity targets. We find that, in the CDK2/CDK9 case, a high correlation in systematic errors suggests free energy calculations can have significant impact in aiding chemists in achieving selectivity, while in more distantly related kinases (CDK2/ERK2), the correlation in systematic error suggests fortuitous cancellation may even occur between systems that are not as closely related. In both cases, the correlation in systematic error suggests that longer simulations are beneficial to properly balance statistical error with systematic error to take full advantage of the increase in apparent free energy calculation accuracy in selectivity prediction.

biophysics↗

bioRxiv2017

Predicting resistance of clinical Abl mutations to targeted kinase inhibitors using alchemical free-energy calculations

The therapeutic effect of targeted kinase inhibitors can be significantly reduced by intrinsic or acquired resistance mutations that modulate the affinity of the drug for the kinase. In cancer, the majority of missense mutations are rare, making it difficult to predict their impact on inhibitor affinity. This complicates the practice of precision medicine, pairing of patients with clinical trials, and development of next-generation inhibitors. Here, we examine the potential for alchemical free-energy calculations to predict how kinase mutations modulate inhibitor affinities to Abl, a major target in chronic myelogenous leukemia (CML). We find these calculations can achieve useful accuracy in predicting resistance for a set of eight FDA-approved kinase inhibitors across 144 clinically-identified point mutations, achieving a root mean square error in binding free energy changes of [Formula] kcal/mol (95% confidence interval) and correctly classifying mutations as resistant or susceptible with [Formula] accuracy. Since these calculations are fast on modern GPUs, this benchmark establishes the potential for physical modeling to collaboratively support the rapid assessment and anticipation of the potential for patient mutations to affect drug potency in clinical applications.

cancer biology↗