Enabling late-stage drug diversification by high-throughput experimentation with geometric deep learning

Late-stage functionalization is an economical approach to optimize the properties of drug candidates. However, the chemical complexity of drug molecules often makes late-stage diversification challenging. To address this problem, a late-stage functionalization platform based on geometric deep learning and high-throughput reaction screening was developed. Considering borylation as a critical step in late-stage functionalization, the computational model predicted reaction yields for diverse reaction conditions with a mean absolute error margin of 4-5%, while the reactivity of novel reactions with known and unknown substrates was classified with a balanced accuracy of 92% and 67%, respectively. The regioselectivity of the major products was accurately captured with a classifier F-score of 67%. When applied to 23 diverse commercial drug molecules, the platform successfully identified numerous opportunities for structural diversification. The influence of steric and electronic information on model performance was quantified, and a comprehensive simple user-friendly reaction format was introduced that proved to be a key enabler for seamlessly integrating deep learning and high-throughput experimentation for late-stage functionalization.

Evaluation of 3'-phosphate as a transient protecting group for controlled enzymatic synthesis of DNA and XNA oligonucleotides

Chemically modified oligonucleotides have advanced as important therapeutic tools as reflected by the recent advent of mRNA vaccines and the FDA-approval of various siRNA and antisense oligonucleotides. These sequences are typically accessed by solid-phase synthesis which despite numerous advantages is restricted to short sequences and displays a limited tolerance to functional groups. Controlled enzymatic synthesis is an emerging alternative synthetic methodology that circumvents the limitations of traditional solid-phase synthesis. So far, most approaches strived to improve controlled enzymatic synthesis of canonical DNA and no potential routes to access xenonucleic acids (XNAs) have been reported. In this context, we have investigated the possibility of using phosphate as a transient protecting group for controlled enzymatic synthesis of DNA and locked nucleic acid (LNA) oligonucleotides. Phosphate is ubiquitously employed in natural systems and we demonstrate that this group displays most characteristics required for controlled enzymatic synthesis. We have devised robust synthetic pathways leading to these challenging compounds and we have discovered a hitherto unknown phosphatase activity of various DNA polymerases. These findings open up directions for the design of protected DNA and XNA nucleoside triphosphates for controlled enzymatic synthesis of chemically modified nucleic acids.

Screening methods for enzyme-mediated alcohol oxidation

Alcohol oxidation for the generation of carbonyl groups, is an essential reaction for the preparation of fine chemicals. Although a number of chemical procedures have been reported, biocatalysis is a promising alternative for more sustainable and selective processes. To speed up the discovery of novel (bio)catalysts for industrial applications, efficient screening approaches need to be established. Here, we report on an enzyme-mediated alcohol oxidation screening platform to rapidly detect the activities and selectivities of three classes of biocatalysts; ketoreductases (KREDs), alcohol oxidases (AlcOXs) and laccase-mediator systems (LMSs) with diverse substrates.

Virus-inspired designs of antimicrobial nanocapsules

Antimicrobial resistance is becoming a serious burden for drug design. The challenges are in finding novel approaches for effectively targeting a number of different bacterial strains, and in delivering these to the site of action. We propose here a novel approach that exploits the assembly of antimicrobial peptidic units in nanocapsules that can penetrate and rupture the bacterial membrane. Additionally, the chemical versatility of the designed units can be tailored to specific targets and to the delivery of genetic material in the cell. The proposed design exploits a β-annulus (sequence ITHVGGVGGSIMAPVAVSRQLVGS) triskelion unit from the Tomato Bushy Stunt Virus, able to self assemble in solution, and functionalised with antimicrobial sequences to form dodecahedral antimicrobial nanocapsules. The stability and the activity of the antimicrobial β-annulus capsule is measured by molecular dynamics simulations in water and in the presence of model membranes.

Nanocapsule designs for antimicrobial resistance

The pressing need of new antimicrobial products is growing stronger, particularly because of widespread antimicrobial resistance, endangering our ability to treat common infections. The recent coronavirus pandemic has dramatically highlighted the necessity of effective antibacterial and antiviral protection. This work explores at the molecular level the mechanism of action of antibacterial nanocapsules assembled in virus-like particles, their stability and their interaction with mammal and antimicrobial model membranes. We use Molecular Dynamics with force-fields of different granularity and protein design strategies to study the stability, self-assembly and membrane poration properties of these nanocapsules.

Engineering Chirally Blind Protein Pseudocapsids into Antibacterial Persisters

Antimicrobial resistance stimulates the search for antimicrobial forms that may be less subject to acquired resistance. Here we report a conceptual design of protein pseudocapsids exhibiting a broad spectrum of antimicrobial activities. Unlike conventional antibiotics, these agents are effective against phenotypic bacterial variants, while clearing "superbugs" in vivo without toxicity. The design adopts an icosahedral architecture that is polymorphic in size, but not in shape, and that is available in both l and d epimeric forms. Using a combination of nanoscale and single-cell imaging we demonstrate that such pseudocapsids inflict rapid and irreparable damage to bacterial cells. In phospholipid membranes they rapidly convert into nanopores, which remain confined to the binding positions of individual pseudocapsids. This mechanism ensures precisely delivered influxes of high antimicrobial doses, rendering the design a versatile platform for engineering structurally diverse and functionally persistent antimicrobial agents.

Lipid Head Group Parameterization for GROMOS 54A8: A Consistent Approach with Protein Force Field Description

Membranes are a crucial component of both bacterial and mammalian cells, being involved in signaling, transport, and compartmentalization. This versatility requires a variety of lipid species to tailor the membrane’s behavior as needed, increasing the complexity of the system. Molecular dynamics simulations have been successfully applied to study model membranes and their interactions with proteins, elucidating some crucial mechanisms at the atomistic detail and thus complementing experimental techniques. An accurate description of the functional interplay of the diverse membrane components crucially depends on the selected parameters that define the adopted force field. A coherent parameterization for lipids and proteins is therefore needed. In this work, we propose and validate new lipid head group parameters for the GROMOS 54A8 force field, making use of recently published parametrizations for key chemical moieties present in lipids. We make use additionally of a new canonical set of partial charges for lipids, chosen to be consistent with the parameterization of soluble molecules such as proteins. We test the derived parameters on five phosphocholine model bilayers, composed of lipid patches four times larger than the ones used in previous studies, and run 500 ns long simulations of each system. Reproduction of experimental data like area per lipid and deuterium order parameters is good and comparable with previous parameterizations, as well as the description of liquid crystal to gel-phase transition. On the other hand, the orientational behavior of the head groups is more realistic for this new parameter set, and this can be crucial in the description of interactions with other polar molecules. For that reason, we tested the interaction of the antimicrobial peptide lactoferricin with two model membranes showing that the new parameters lead to a weaker peptide–membrane binding and give a more realistic outcome in comparing binding to antimicrobial versus mammal membranes.