Evolving Experimental Techniques for Structure-Based Drug Design

Cryo-electron microscopy-based drug design

Structure-based drug design (SBDD) has gained popularity owing to its ability to develop more potent drugs compared to conventional drug-discovery methods. The success of SBDD relies heavily on obtaining the three-dimensional structures of drug targets. X-ray crystallography is the primary method used for solving structures and aiding the SBDD workflow; however, it is not suitable for all targets. With the resolution revolution, enabling routine high-resolution reconstruction of structures, cryogenic electron microscopy (cryo-EM) has emerged as a promising alternative and has attracted increasing attention in SBDD. Cryo-EM offers various advantages over X-ray crystallography and can potentially replace X-ray crystallography in SBDD. To fully utilize cryo-EM in drug discovery, understanding the strengths and weaknesses of this technique and noting the key advancements in the field are crucial. This review provides an overview of the general workflow of cryo-EM in SBDD and highlights technical innovations that enable its application in drug design. Furthermore, the most recent achievements in the cryo-EM methodology for drug discovery are discussed, demonstrating the potential of this technique for advancing drug development. By understanding the capabilities and advancements of cryo-EM, researchers can leverage the benefits of designing more effective drugs. This review concludes with a discussion of the future perspectives of cryo-EM-based SBDD, emphasizing the role of this technique in driving innovations in drug discovery and development. The integration of cryo-EM into the drug design process holds great promise for accelerating the discovery of new and improved therapeutic agents to combat various diseases.

Defining the conformational states that enable transglutaminase 2 to promote cancer cell survival versus cell death

Transglutaminase 2 (TG2) is a GTP-binding/protein-crosslinking enzyme that has been investigated as a therapeutic target for Celiac disease, neurological disorders, and aggressive cancers. TG2 has been suggested to adopt two conformational states that regulate its functions: a GTP-bound, closed conformation, and a calcium-bound, crosslinking-active open conformation. TG2 mutants that constitutively adopt an open conformation are cytotoxic to cancer cells. Thus, small molecules that maintain the open conformation of TG2 could offer a new therapeutic strategy. Here, we investigate TG2, using static and time-resolved small-angle X-ray scattering (SAXS) and single-particle cryoelectron microscopy (cryo-EM), to determine the conformational states responsible for conferring its biological effects. We also describe a newly developed TG2 inhibitor, LM11, that potently kills glioblastoma cells and use SAXS to investigate how LM11 affects the conformational states of TG2. Using SAXS and cryo-EM, we show that guanine nucleotide-bound TG2 adopts a monomeric closed conformation while calcium-bound TG2 assumes an open conformational state that can form higher order oligomers. SAXS analysis also suggests how a TG2 mutant that constitutively adopts the open state binds nucleotides through an alternative mechanism to wildtype TG2. Furthermore, we use time-resolved SAXS to show that LM11 increases the ability of calcium to drive TG2 to an open conformation, which is not reversible by guanine nucleotides and is cytotoxic to cancer cells. Taken together, our findings demonstrate that the conformational dynamics of TG2 are more complex than previously suggested and highlight how conformational stabilization of TG2 by LM11 maintains TG2 in a cytotoxic conformational state.

Cobdock: an accurate and practical machine learning-based consensus blind docking method

Probing the surface of proteins to predict the binding site and binding affinity for a given small molecule is a critical but challenging task in drug discovery. Blind docking addresses this issue by performing docking on binding regions randomly sampled from the entire protein surface. However, compared with local docking, blind docking is less accurate and reliable because the docking space is too largetly sampled. Cavity detection-guided blind docking methods improved the accuracy by using cavity detection (also known as binding site detection) tools to guide the docking procedure. However, it is worth noting that the performance of these methods heavily relies on the quality of the cavity detection tool. This constraint, namely the dependence on a single cavity detection tool, significantly impacts the overall performance of cavity detection-guided methods. To overcome this limitation, we proposed Consensus Blind Dock (CoBDock), a novel blind, parallel docking method that uses machine learning algorithms to integrate docking and cavity detection results to improve not only binding site identification but also pose prediction accuracy. Our experiments on several datasets, including PDBBind 2020, ADS, MTi, DUD-E, and CASF-2016, showed that CoBDock has better binding site and binding mode performance than other state-of-the-art cavity detector tools and blind docking methods.

Structural Insight into Geranylgeranyl Diphosphate Synthase (GGDPS) for Cancer Therapy

Geranylgeranyl diphosphate synthase (GGDPS), the source of the isoprenoid donor in protein geranylgeranylation reactions, has become an attractive target for anticancer therapy due to the reliance of cancers on geranylgeranylated proteins. Current GGDPS inhibitor development focuses on optimizing the drug-target enzyme interactions of nitrogen-containing bisphosphonate-based drugs. To advance GGDPS inhibitor development, understanding the enzyme structure, active site, and ligand/product interactions is essential. Here we provide a comprehensive structure-focused review of GGDPS. We reviewed available yeast and human GGDPS structures and then used AlphaFold modeling to complete unsolved structural aspects of these models. We delineate the elements of higher-order structure formation, product-substrate binding, the electrostatic surface, and small-molecule inhibitor binding. With the rise of structure-based drug design, the information provided here will serve as a valuable tool for rationally optimizing inhibitor selectivity and effectiveness.

Selectivity Mechanism of Pyrrolopyridone Analogues Targeting Bromodomain 2 of Bromodomain-Containing Protein 4 from Molecular Dynamics Simulations

Bromodomain and extra-terminal domain (BET) proteins play an important role in epigenetic regulation and are linked to several diseases; therefore, they are interesting targets. BET has two bromodomains: bromodomain 1 (BD1) and BD2. Selective targeting of BD1 or BD2 may produce different activities and greater effects than pan-BD inhibitors. However, the selective mechanism of the specific core must be studied at the atomic level. This study determined the effectiveness of pyrrolopyridone analogues to selectively inhibit BD2 using a pan-BD inhibitor (ABBV-075) and a selective-BD2 inhibitor (ABBV-744). Molecular dynamics simulations and calculations of binding free energies were used to systematically study the selectivity of BD2 inhibition by the pyrrolopyridone analogues. Overall, the pyrrolopyridone analogue inhibitors targeting BD2 interacted mainly with the following amino acid pairs between bromodomain-containing protein 4 (BRD4)-BD1 and BRD4-BD2 complexes: I146/V439, N140/N433, D144/H437, P82/P375, V87/V380, D88/D381, and Y139/Y432. The pyrrolopyridone analogues targeting BRD4-BD2 were divided into five regions based on selectivity mechanism. These results suggest that the R3 and R5 regions of pyrrolopyridone analogues can be modified to improve the selectivity between BRD4-BD1 and BRD4-BD2. The selectivity of BD2 inhibition by pyrrolopyridone analogues can be used to design novel BD2 inhibitors based on a pyrrolopyridone core.

CHARMM-GUI-Based Induced Fit Docking Workflow to Generate Reliable Protein-Ligand Binding Modes

Molecular docking is a preferred method to predict ligand binding modes and their binding energy to target protein receptors, which is critical in early phase structure-based drug discovery. However, there is a persistent challenge in docking that can be attributed to the induced fit effect, as receptor binding sites undergo induced fit conformational changes upon ligand binding to achieve better binding modes. In this work, based on CHARMM-GUI LBS Finder& Refiner and High-Throughput Simulator, we present a straightforward CHARMM-GUI induced fit docking (CGUI-IFD) workflow to generate reliable protein-ligand binding modes. The CGUI-IFD workflow generates an ensemble of receptor binding site conformations through ligand-binding site (LBS) refinement, runs rigid receptor docking, and performs high-throughput molecular dynamics (MD) simulations of protein-ligand complex structures in explicit solvents. The results are evaluated based on the ligand root-mean-square deviation (RMSD)-based binding stability and the molecular mechanics generalized Born surface area binding energy. For a benchmark test, we used 258 cross-docking protein-ligand pairs across 41 target proteins from the Schrodinger IFD-MD data set. The application of CGUI-IFD on this data set shows 80% success rate (within 2.5 Å RMSD from the experimental structures). We expect that the CGUI-IFD workflow can be useful to generate reliable ligand binding modes for cross-docking cases.

Targeting ATM and ATR for cancer therapeutics: inhibitors in clinic

The DNA Damage and Response (DDR) pathway ensures accurate information transfer from one generation to the next. Alterations in DDR functions have been connected to cancer predisposition, progression, and response to therapy. DNA double-strand break (DSB) is one of the most detrimental DNA defects, causing major chromosomal abnormalities such as translocations and deletions. ATR and ATM kinases recognize this damage and activate proteins involved in cell cycle checkpoint, DNA repair, and apoptosis. Cancer cells have a high DSB burden, and therefore rely on DSB repair for survival. Therefore, targeting DSB repair can sensitize cancer cells to DNA-damaging agents. This review focuses on ATM and ATR, their roles in DNA damage and repair pathways, challenges in targeting them, and inhibitors that are in current clinical trials.

Chaotic advection mixer for capturing transient states of diverse biological macromolecular systems with time-resolved small-angle X-ray scattering

Advances in time-resolved structural techniques, mainly in macromolecular crystallography and small-angle X-ray scattering (SAXS), allow for a detailed view of the dynamics of biological macromolecules and reactions between binding partners. Of particular promise, are mix-and-inject techniques, which offer a wide range of experimental possibility as microfluidic mixers are used to rapidly combine two species just prior to data collection. Most mix-and-inject approaches rely on diffusive mixers, which have been effectively used within crystallography and SAXS for a variety of systems, but their success is dependent on a specific set of conditions to facilitate fast diffusion for mixing. The use of a new chaotic advection mixer designed for microfluidic applications helps to further broaden the types of systems compatible with time-resolved mixing experiments. The chaotic advection mixer can create ultra-thin, alternating layers of liquid, enabling faster diffusion so that even more slowly diffusing molecules, like proteins or nucleic acids, can achieve fast mixing on timescales relevant to biological reactions. This mixer was first used in UV-vis absorbance and SAXS experiments with systems of a variety of molecular weights, and thus diffusion speeds. Careful effort was also dedicated to making a loop-loading sample-delivery system that consumes as little sample as possible, enabling the study of precious, laboratory-purified samples. The combination of the versatile mixer with low sample consumption opens the door to many new applications for mix-and-inject studies.

Approved Nanomedicine against Diseases

Nanomedicine is a branch of medicine using nanotechnology to prevent and treat diseases. Nanotechnology represents one of the most effective approaches in elevating a drug‘s treatment efficacy and reducing toxicity by improving drug solubility, altering biodistribution, and controlling the release. The development of nanotechnology and materials has brought a profound revolution to medicine, significantly affecting the treatment of various major diseases such as cancer, injection, and cardiovascular diseases. Nanomedicine has experienced explosive growth in the past few years. Although the clinical transition of nanomedicine is not very satisfactory, traditional drugs still occupy a dominant position in formulation development, but increasingly active drugs have adopted nanoscale forms to limit side effects and improve efficacy. The review summarized the approved nanomedicine, its indications, and the properties of commonly used nanocarriers and nanotechnology.