A CQM-based approach to solving a combinatorial problem with applications in drug design

The use of D-Wave's Leap Hybrid solver is demonstrated here in solving a Knapsack optimization problem: finding meal combinations from a fixed menu that fit a diner's constraints. This is done by first formulating the optimization problem as a Constrained Quadratic Model (CQM) and then submitting it to a quantum annealer. We highlight here the steps needed, as well as the implemented code, and provide solutions from a Chicken and Waffle restaurant menu. Additionally, we discuss how this model may be generalized to find optimal drug molecules within a large search space with many complex, and often contradictory, structures and property constraints.Comment: 10 pages, 2 table

In Silico Prediction of Ligand Binding Energies in Multiple Therapeutic Targets and Diverse Ligand SetsA Case Study on BACE1, TYK2, HSP90, and PERK Proteins

We present here the use of QM/MM LIE (linear interaction energy) based binding free energy calculations that greatly improve the precision and accuracy of predicting experimental binding affinities, in comparison to most current binding free energy methodologies, while maintaining reasonable computational times. Calculations are done for four sets of ligand–protein complexes, chosen on the basis of diversity of protein types and availability of experimental data, totaling 140 ligands binding to therapeutic protein targets BACE1, TYK2, HSP90, and PERK. This method allows calculations for a diverse set of ligands and multiple protein targets without the need for parametrization or extra calculations. The accuracy achieved with this method can be used to guide small molecule computational drug design programs

A Quantum-Inspired Approach to De-Novo Drug Design

Design and optimization of targeted drug-like compounds is an important part of the early stage drug discovery process. In this paper, we describe the use of a novel technique for rapid design of lead-like compounds for the Dengue viral RNA-dependent-RNA polymerase (RdRp). Initially, a large (>billions) fragment-based chemical library is designed by mapping relevant pharmacophores to the target binding pocket. The de-novo synthesis of molecules from fragments is formulated as a quadratic unconstrained binary optimization problem that can be solved using the quantum-inspired Digital Annealer (DA), providing an opportunity to take advantage of this fledgling, groundbreaking technology. The DA constrains the search space of molecules with drug-like properties that match the binding pocket and then optimizes for synthetic feasibility and novelty, thus offering significant commercial advantages over existing techniques

Prospects and Challenges of Phospholipid-Based Prodrugs

Nowadays, the prodrug approach is used already at the early stages of drug development. Lipidic prodrug approach is a growing field for improving a number of drug properties/delivery/therapy aspects, and can offer solutions for various unmet needs. This approach includes drug moiety bound to the lipid carrier, which can be triglyceride, fatty acids, steroid, or phospholipid (PL). The focus of this article is PL-based prodrugs, which includes a PL carrier covalently bound to the active drug moiety. An overview of relevant physiological lipid processing pathways and absorption barriers is provided, followed by drug delivery/therapeutic application of PL-drug conjugates, as well as computational modeling techniques, and a modern bioinformatics tool that can aid in the optimization of PL conjugates. PL-based prodrugs have increased lipophilicity comparing to the parent drug, and can therefore significantly improve the pharmacokinetic profile and overall bioavailability of the parent drug, join the endogenous lipid processing pathways and therefore accomplish drug targeting, e.g., by lymphatic transport, drug release at specific target site(s), or passing the blood-brain barrier. Moreover, an exciting gateway for treating inflammatory diseases and cancer is presented, by utilizing the PL sn-2 position in the prodrug design, aiming for PLA2-mediated activation. Overall, a PL-based prodrug approach shows great potential in improving different drug delivery/therapy aspects, and is expected to grow

Molecular Modeling-Guided Design of Phospholipid-Based Prodrugs

The lipidic prodrug approach is an emerging field for improving a number of biopharmaceutical and drug delivery aspects. Owing to their structure and nature, phospholipid (PL)-based prodrugs may join endogenous lipid processing pathways, and hence significantly improve the pharmacokinetics and/or bioavailability of the drug. Additional advantages of this approach include drug targeting by enzyme-triggered drug release, blood−brain barrier permeability, lymphatic targeting, overcoming drug resistance, or enabling appropriate formulation. The PL-prodrug design includes various structural modalities-different conjugation strategies and/or the use of linkers between the PL and the drug moiety, which considerably influence the prodrug characteristics and the consequent effects. In this article, we describe how molecular modeling can guide the structural design of PL-based prodrugs. Computational simulations can predict the extent of phospholipase A2 (PLA2)-mediated activation, and facilitate prodrug development. Several computational methods have been used to facilitate the design of the pro-drugs, which will be reviewed here, including molecular docking, the free energy perturbation method, molecular dynamics simulations, and free density functional theory. Altogether, the studies described in this article indicate that computational simulation-guided PL-based prodrug molecular design correlates well with the experimental results, allowing for more mechanistic and less empirical development. In the future, the use of molecular modeling techniques to predict the activity of PL-prodrugs should be used earlier in the development process

Phospholipid-Based Prodrugs for Colon-Targeted Drug Delivery: Experimental Study and In-Silico Simulations

In ulcerative colitis (UC), the inflammation is localized in the colon, and one of the successful strategies for colon-targeting drug delivery is the prodrug approach. In this work, we present a novel phospholipid (PL)-based prodrug approach, as a tool for colonic drug targeting in UC. We aim to use the phospholipase A2 (PLA2), an enzyme that is overexpressed in the inflamed colonic tissues of UC patients, as the PL-prodrug activating enzyme, to accomplish the liberation of the parent drug from the prodrug complex at the specific diseased tissue(s). Different linker lengths between the PL and the drug moiety can dictate the rate of activation by PLA2, and subsequently determine the amount of free drugs at the site of action. The feasibility of this approach was studied with newly synthesized PL-Fmoc (fluorenylmethyloxycarbonyl) conjugates, using Fmoc as a model compound for testing our hypothesis. In vitro incubation with bee venom PLA2 demonstrated that a 7-carbon linker between the PL and Fmoc has higher activation rate than a 5-carbon linker. 4-fold higher colonic expression of PLA2 was demonstrated in colonic mucosa of colitis-induced rats when compared to healthy animals, validating our hypothesis of a colitis-targeting prodrug approach. Next, a novel molecular dynamics (MD) simulation was developed for PL-based prodrugs containing clinically relevant drugs. PL-methotrexate conjugate with 6-carbon linker showed the highest extent of PLA2-mediated activation, whereas shorter linkers were activated to a lower extent. In conclusion, this work demonstrates that for carefully designed PL-drug conjugates, PLA2 overexpression in inflamed colonic tissues can be used as prodrug-activating enzyme and drug targeting strategy, including insights into the activation mechanisms in a PLA2 binding site