Investigations of Albumin–Insulin Detemir Complexes Using Molecular Dynamics Simulations and Free Energy Calculations

Structure-Based Computational Scanning of Chemical Modification Sites in Biologics

To address the challenges of short half-life, immunogenicity, and nonspecific distribution, chemical modifications of peptide and protein-based drugs have emerged as a versatile strategy for improving their therapeutic efficacy. One such modification involves the derivatization of peptides and proteins with fatty acids, which can protract their half-life, modify their biodistribution, and potentially enable targeted delivery to specific tissues or disease sites of interest. However, the present strategies for the synthesis of such synthetically modified biologics require numerous rounds of experimental testing and often yield unstable, inactive, or heterogeneous products. To address the inefficiencies in designing modified biologics, we developed a hybrid computational workflow that integrates RosettaMatch from the Rosetta suite of protein modeling tools with molecular dynamics (MD) simulations. This approach not only reduces the number of amino acid positions that need to be experimentally tested by targeting only the most promising candidates for modification but also expedites the design of chemically modified biologics with the desired properties, ensuring a rapid and cost-effective development cycle. Although we demonstrate the utility of our method on a peptide therapeutic, GLP-1, with different fatty acid derivatizations, this straightforward approach has the potential to streamline the design process of a diverse range of chemically modified therapeutics, enabling tailored enhancements to their pharmacokinetic properties.

Virtual screening and biological activity evaluation of novel efflux pump inhibitors targeting AdeB

The AdeABC efflux pump is an important mechanism causing multidrug resistance in Acinetobacter baumannii, and its main component AdeB can recognize carbapenems, aminoglycosides, and other multi-class antibiotics and efflux them intracellularly, which is an ideal target for the development of anti-multidrug resistant bacteria drugs. Here, we combined multiple computer-aided drug design methods to target AdeB to identify promising novel structural inhibitors. Virtual screening was performed by molecular docking and molecular dynamics simulation (MD) and 12 potential compounds were identified from the databases. Meanwhile, their biological activities were validated by in vitro activity assays, and ChemDiv L676-2179 (γ-IFN), ChemDiv L676-1461, and Chembridge 53717615 were confirmed to suppress efflux effects and restore antibiotic susceptibility of resistant bacteria, which are expected to be developed as adjuvant drugs for the treatment of multi-drug resistant Acinetobacter baumannii clinical infections.

Progress in Simulation Studies of Insulin Structure and Function

Insulin is a peptide hormone known for chiefly regulating glucose level in blood among several other metabolic processes. Insulin remains the most effective drug for treating diabetes mellitus. Insulin is synthesized in the pancreatic β-cells where it exists in a compact hexameric architecture although its biologically active form is monomeric. Insulin exhibits a sequence of conformational variations during the transition from the hexamer state to its biologically-active monomer state. The structural transitions and the mechanism of action of insulin have been investigated using several experimental and computational methods. This review primarily highlights the contributions of molecular dynamics (MD) simulations in elucidating the atomic-level details of conformational dynamics in insulin, where the structure of the hormone has been probed as a monomer, dimer, and hexamer. The effect of solvent, pH, temperature, and pressure have been probed at the microscopic scale. Given the focus of this review on the structure of the hormone, simulation studies involving interactions between the hormone and its receptor are only briefly highlighted, and studies on other related peptides (e.g., insulin-like growth factors) are not discussed. However, the review highlights conformational dynamics underlying the activities of reported insulin analogs and mimetics. The future prospects for computational methods in developing promising synthetic insulin analogs are also briefly highlighted.

Molecular analysis and therapeutic applications of human serum albumin-fatty acid interactions

Human serum albumin (hSA) is the major carrier protein for fatty acids (FAs) in plasma. Its ability to bind multiple FA moieties with moderate to high affinity has inspired the use of FA conjugation as a safe and natural platform to generate long-lasting therapeutics with enhanced pharmacokinetic properties and superior efficacy. In this frame, the choice of the FA is crucial and a comprehensive elucidation of the molecular interactions of FAs with hSA cannot be left out of consideration. To this intent, we report here a comparative analysis of the binding mode of different FA moieties with hSA. The choice among different albumin-binding FAs and how this influence the pharmacokinetics properties of a broad spectrum of therapeutic molecules will be discussed including a critical description of some clinically relevant FA conjugated therapeutics.

In-silico study of the interactions between acylated glucagon like-peptide-1 analogues and the native receptor

We have performed a series of multiple molecular dynamics (MD) simulations of glucagon-like peptide-1 (GLP-1) and acylated GLP-1 analogues in complex with the endogenous receptor (GLP-1R) to obtain a molecular understanding of how fatty acid (FA) chain structure, acylation position on the peptide, and presence of a linker affect the binding. MD simulations were analysed to extract heatmaps of receptor-peptide interaction patterns and to determine the free energy of binding using the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approach. The extracted free energies from MM-PBSA calculations are in qualitative agreement with experimentally determined potencies. Furthermore, the interaction patterns seen in the receptor-GLP-1 complex simulations resemble previously reported binding interactions validating the simulations. Analysing the receptor-GLP-1 analogue complex simulations, we found that the major differences between the systems stem from FA interactions and positioning of acylation in the peptide. Hydrophobic interactions between the FA chain and a hydrophobic patch on the extracellular domain contribute significantly to the binding affinity. Acylation on Lys26 resulted in noticeably more interactions between the FA chain and the extracellular domain hydrophobic patch than found for acylation on Lys34 and Lys38, respectively. The presence of a charged linker between the peptide and FA chain can potentially stabilise the complex by forming hydrogen bonds to arginine residues in the linker region between the extracellular domain and the transmembrane domain. A molecular understanding of the fatty acid structure and its effect on binding provides important insights into designing acylated agonists for GLP-1R.Communicated by Ramaswamy H. Sarma.

Recent Developments in Free Energy Calculations for Drug Discovery

The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading to calculation of thermodynamic quantities involved in estimation of binding affinities. With recent advancements in computing capability and predictive accuracy, MD based virtual screening has progressed from the domain of theoretical attempts to real application in drug development. Approaches including the Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA), Linear Interaction Energy (LIE), and alchemical methods have been broadly applied to model molecular recognition for drug discovery and lead optimization. Here we review the varied methodology of these approaches, developments enhancing simulation efficiency and reliability, remaining challenges hindering predictive performance, and applications to problems in the fields of medicine and biochemistry.

Exploring the toxic effects and mechanism of methoxylated polybrominated diphenyl ethers (MeO-PBDEs) on thyroxine-binding globulin (TBG): Synergy between spectroscopic and computations

The interaction mechanism between thyroxine-binding globulin (TBG) and three methoxylated polybrominated diphenyl ethers (MeO-PBDEs) was analyzed by steady-state fluorescence, ultraviolet-visible (UV-visible) spectroscopy, circular dichroism (CD), molecular docking and molecular dynamics simulation methods. The results of the molecular docking technique revealed that 2'-MeO-BDE-3, 5-MeO-BDE-47, and 3-MeO-BDE-100 combined with TBG at the active site. The steady-state fluorescence spectra displayed that MeO-PBDEs quenched the endogenous fluorescence of TBG through static quenching mechanism, and complex formation between MeO-PBDEs and TBG was further indicated by UV-vis spectroscopy. The thermodynamic quantities showed that the binding process is spontaneous, and the major forces responsible for the binding are hydrogen bonding and hydrophobic interactions, which are consistent with the results of molecular docking to a certain extent. The results of CD confirmed that the secondary structure of TBG was changed after combining with MeO-PBDEs. The dynamic simulation results illustrated that the protein structure is more compact and changes in the secondary structure of TBG after binding to MeO-PBDEs. Additionally, we also utilized the molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) method to analyze the binding free energy of TBG and MeO-PBDEs. The results suggest that van der Waals force plays an essential role in the combination.