Native Binding Research Articles

Reliability of AlphaFold2 Models in Virtual Drug Screening: A Focus on Selected Class A GPCRs.

Protein three-dimensional (3D) structure prediction is one of the most challenging issues in the field of computational biochemistry, which has overwhelmed scientists for almost half a century. A significant breakthrough in structural biology has been established by developing the artificial intelligence (AI) system AlphaFold2 (AF2). The AF2 system provides a state-of-the-art prediction of protein structures from nearly all known protein sequences with high accuracy. This study examined the reliability of AF2 models compared to the experimental structures in drug discovery, focusing on one of the most common protein drug-targeted classes known as G protein-coupled receptors (GPCRs) class A. A total of 32 representative protein targets were selected, including experimental structures of X-ray crystallographic and Cryo-EM structures and their corresponding AF2 models. The quality of AF2 models was assessed using different structure validation tools, including the pLDDT score, RMSD value, MolProbity score, percentage of Ramachandran favored, QMEAN Z-score, and QMEANDisCo Global. The molecular docking was performed using the Genetic Optimization for Ligand Docking (GOLD) software. The AF2 models' reliability in virtual drug screening was determined by their ability to predict the ligand binding poses closest to the native binding pose by assessing the Root Mean Square Deviation (RMSD) metric and docking scoring function. The quality of the docking and scoring function was evaluated using the enrichment factor (EF). Furthermore, the capability of using AF2 models in molecular docking to identify hits with key protein-ligand interactions was analyzed. The posing power results showed that the AF2 models successfully predicted ligand binding poses (RMSD < 2 Å). However, they exhibited lower screening power, with average EF values of 2.24, 2.42, and 1.82 for X-ray, Cryo-EM, and AF2 structures, respectively. Moreover, our study revealed that molecular docking using AF2 models can identify competitive inhibitors. In conclusion, this study found that AF2 models provided docking results comparable to experimental structures, particularly for certain GPCR targets, and could potentially significantly impact drug discovery.

Tetrachloromaxamycins: Divergent Total Synthesis and Initial Assessments.

Divergent total syntheses of binding pocket and peripherally modified tetrachlorovancomycins, a non-native synthetic glycopeptide, and their evaluation are disclosed. Central to the approach is the synthesis of a single late-stage intermediate that bears a residue 4 thioamide ([Ψ[C(═S)NH]Tpg4]tetrachlorovancomycin (3), LLS 15 steps, 14% overall) as a precursor to either of two key pocket modifications and their pairing with any combination of two peripheral modifications conducted without protecting groups. A stereochemical simplification achieved by the addition of two aryl chlorides removes two synthetically challenging atropisomer centers in native glycopeptides and streamlines the synthesis. Key features include in a convergent epimerization-free thioacylation of the AB ring system amine with an N-thioacylbenzotriazolyl DE tetrapeptide (85%) followed by simultaneous room-temperature SNAr macrocyclizations of the CD and DE ring systems (96%). The approach provided 3 from which [Ψ[C(═N)NH]Tpg4]tetrachlorovancomycin (4) and [Ψ(CH2NH)Tpg4]tetrachlorovancomycin (5) were prepared in a single-step and bear binding pocket modifications that convey dual d-Ala-d-Ala/d-Lac ligand binding to overcome vancomycin resistance. The newest maxamycin members are disclosed, bearing two additional peripheral modifications that introduce two independent synergistic MOAs that do not rely on native ligand binding for activity. Ligand binding properties of pocket-modified tetrachlorovancomycins 3-5, antibacterial activity of a key compound series, and PK assessments of two tetrachloromaxamycins are reported.

The Importance of Structural Water in HDAC8 for Correct Binding Pose Applied for Drug Design of Anticancer Molecules.

Validating the docking procedure and maintaining the structural water molecules at HDAC8 catalytic site. Molecular docking simulations play a significant role in Computer-Aided Drug Design, contributing to the development of new molecules. To ensure the reliability of these simulations, a validation process called "self-docking or re-docking" is employed, focusing on the binding mode of a ligand co-crystallized with the protein of interest. In this study, several molecular docking studies were conducted using five X-ray structures of HDAC8-ligand complexes from the PDB. Ligands initially complexed with HDAC8 were removed and re-docked onto the free protein, revealing a poor reproduction of the expected binding mode. In response to this, we observed that most HDAC8-ligand complexes contained one to two water molecules in the catalytic site, which were crucial for maintaining the cocrystallized ligand. These water molecules enhance the binding mode of the co-crystallized ligand by stabilizing the proteinligand complex through hydrogen bond interactions between ligand and water molecules. Notably, these interactions are lost if water molecules are removed, as is often done in classical docking methodologies. Considering this, molecular docking simulations were repeated, both with and without one or two conserved water molecules near Zn+2 in the catalytic cavity. Simulations indicated that replicating the native binding pose of co-crystallized ligands on free HDAC8 without these water molecules was challenging, showing greater coordinate displacements (RMSD) compared to those including conserved water molecules from crystals. The study highlighted the importance of conserved water molecules within the active site, as their presence significantly influenced the successful reproduction of the ligands' native binding modes. The results suggest an optimal molecular docking procedure for validating methods suitable for filtering new HDAC8 inhibitors for future experimental assays.

Physicochemical Stimuli-Mediated Precipitation Approach for the Modulation of Rifampicin's Dissolution and Oral Bioavailability.

The intricate process of protein binding orchestrates crucial drug interactions within the bloodstream, facilitating the formation of soluble complexes. This research endeavours to improve the dissolution and oral bioavailability of Rifampicin (RMP) by strategically manipulating drug-protein binding dynamics and the hydrophobic characteristics of human serum albumin (HSA). Various precipitation techniques leveraging methanol, ammonium sulfate, and heat treatment were meticulously employed to tailor the properties of colloidal albumin (HSA NPs). The resultant complexes underwent comprehensive characterization encompassing evaluations of hydrophobicity, size distribution, surface charge, and structural analyses through FTIR, TG-DSC, XRD, and morphological examinations. The findings revealed a significant binding affinity of 78.07 ± 6.6% with native albumin, aligning with prior research. Notably, the complex RMP-HSA NPs-M13, synthesized via the methanolic precipitation method, exhibited the most substantial complexation, achieving a remarkable 3.5-fold increase, followed by the ammonium sulfate (twofold) and heat treatment (1.07-fold) methods in comparison to native albumin binding. The gastric simulated media exhibited accelerated drug release kinetics, with maximal dissolution achieved within two hours, contrasting with the prolonged release observed under intestinal pH conditions. These findings translated into significant improvements in drug permeation, as evidenced by pharmacokinetic profiles demonstrating elevated Cmax, AUC, t1/2, and MRT values for RMP-HSA NPs-M13 compared to free RMP. In summary, this innovative approach underscores the potential of precipitation methods in engineering stable colloidal carrier systems tailored to enhance the oral bioavailability of poorly soluble drugs, offering a pragmatic and scalable alternative to conventional surfactants, polymers, or high-energy methods for complex formation and production.

SPRank─A Knowledge-Based Scoring Function for RNA-Ligand Pose Prediction and Virtual Screening.

The growing interest in RNA-targeted drugs underscores the need for computational modeling of interactions between RNA molecules and small compounds. Having a reliable scoring function for RNA-ligand interactions is essential for effective computational drug screening. An ideal scoring function should not only predict the native pose for ligand binding but also rank the affinity of the binding for different ligands. However, existing scoring functions are primarily designed to predict the native binding modes for a given RNA-ligand pair and have not been thoroughly assessed for virtual screening purposes. In this paper, we introduce SPRank, a combination of machine-learning and knowledge-based scoring functions developed through a weighted iterative approach, specifically designed to tackle both binding mode prediction and virtual screening challenges. Our approach incorporates third-party docking software, such as rDock and AutoDock Vina, to sample flexible ligands against an ensemble of RNA structures, capturing the conformational flexibility of both the RNA and the ligand. Through rigorous testing, SPRank demonstrates improved performance compared to the tested scoring functions across four test sets comprising 122, 42, 55, and 71 nucleic acid-ligand complexes. Furthermore, SPRank exhibits improved performance in virtual screening tests targeting the HIV-1 TAR ensemble, which highlights its advantage in drug discovery. These results underscore the advantages of SPRank as a potentially promising tool for the RNA-targeted drug design. The source code of SPRank and the data sets are freely accessible at https://github.com/Vfold-RNA/SPRank.

Structural and functional characterization of the IpaD π-helix reveals critical roles in DOC interaction, T3SS apparatus maturation, and Shigella virulence

Shigella spp. are highly pathogenic members of the Enterobacteriaceae family, causing ∼269 million cases of bacillary dysentery and >200,000 deaths each year. Like many Gram-negative pathogens, Shigella rely on their type three secretion system (T3SS) to inject effector proteins into eukaryotic host cells, driving both cellular invasion and evasion of host immune responses. Exposure to the bile salt deoxycholate (DOC) significantly enhances Shigella virulence and is proposed to serve as a critical environmental signal present in the small intestine that prepares Shigella’s T3SS for efficient infection of the colonic epithelium. Here, we uncover critical mechanistic details of the Shigella-specific DOC signaling process by describing the role of a π-helix secondary structure element within the T3SS tip protein IpaD. Biophysical characterization and high-resolution structures of IpaD mutants lacking the π-helix show that it is not required for global protein structure, but that it defines the native DOC binding site and prevents off target interactions. Additionally, Shigella strains expressing the π-helix deletion mutants illustrate the pathogenic importance of its role in guiding DOC interaction as flow cytometry and gentamycin protection assays show that the IpaD π-helix is essential for DOC-mediated apparatus maturation and enhanced invasion of eukaryotic cells. Together, these findings add to our understanding of the complex Shigella pathogenesis pathway and its evolution to respond to environmental bile salts by identifying the π-helix in IpaD as a critical structural element required for translating DOC exposure to virulence enhancement.

Transcription Factor Condensates Mediate Clustering of MET Regulon and Enhancement in Gene Expression.

Some transcription factors (TFs) can form liquid-liquid phase separated (LLPS) condensates. However, the functions of these TF condensates in 3D genome organization and gene regulation remain elusive. In response to methionine (met) starvation, budding yeast TF Met4 and a few co-activators, including Met32, induce a set of genes involved in met biosynthesis. Here, we show that the endogenous Met4 and Met32 form co-localized puncta-like structures in yeast nuclei upon met depletion. Recombinant Met4 and Met32 form mixed droplets with LLPS properties in vitro. In relation to chromatin, Met4 puncta co-localize with target genes, and at least a subset of these target genes is clustered in 3D in a Met4-dependent manner. A MET3pr-GFP reporter inserted near several native Met4 binding sites becomes co-localized with Met4 puncta and displays enhanced transcriptional activity. A Met4 variant with a partial truncation of an intrinsically disordered region (IDR) shows less puncta formation, and this mutant selectively reduces the reporter activity near Met4 binding sites to the basal level. Overall, these results support a model where Met4 and co-activators form condensates to bring multiple target genes into a vicinity with higher local TF concentrations, which facilitates a strong response to methionine depletion.

Biomimetic Charge‐Neutral Anion Receptors for Reversible Binding and Release of Highly Hydrated Phosphate in Water

AbstractControl of phosphate capture and release is vital in environmental, biological, and pharmaceutical contexts. However, the binding of trivalent phosphate (PO43−) in water is exceptionally difficult due to its high hydration energy. Based on the anion coordination chemistry of phosphate, in this study, four charge‐neutral tripodal hexaurea receptors (L1–L4), which were equipped with morpholine and polyethylene glycol terminal groups to enhance their solubility in water, were synthesized to enable the pH‐triggered phosphate binding and release in aqueous solutions. Encouragingly, the receptors were found to bind PO43− anion in a 1 : 1 ratio via hydrogen bonds in 100 % water solutions, with L1 exhibiting the highest binding constant (1.2×103 M−1). These represent the first neutral anion ligands to bind phosphate in 100 % water and demonstrate the potential for phosphate capture and release in water through pH‐triggered mechanisms, mimicking native phosphate binding proteins. Furthermore, L1 can also bind multiple bioavailable phosphate species, which may serve as model systems for probing and modulating phosphate homeostasis in biological and biomedical researches.

Biomimetic Charge-Neutral Anion Receptors for Reversible Binding and Release of Highly Hydrated Phosphate in Water.

Control of phosphate capture and release is vital in environmental, biological, and pharmaceutical contexts. However, the binding of trivalent phosphate (PO4 3-) in water is exceptionally difficult due to its high hydration energy. Based on the anion coordination chemistry of phosphate, in this study, four charge-neutral tripodal hexaurea receptors (L1-L4), which were equipped with morpholine and polyethylene glycol terminal groups to enhance their solubility in water, were synthesized to enable the pH-triggered phosphate binding and release in aqueous solutions. Encouragingly, the receptors were found to bind PO4 3- anion in a 1 : 1 ratio via hydrogen bonds in 100 % water solutions, with L1 exhibiting the highest binding constant (1.2×103 M-1). These represent the first neutral anion ligands to bind phosphate in 100 % water and demonstrate the potential for phosphate capture and release in water through pH-triggered mechanisms, mimicking native phosphate binding proteins. Furthermore, L1 can also bind multiple bioavailable phosphate species, which may serve as model systems for probing and modulating phosphate homeostasis in biological and biomedical researches.

The Chlamydia trachomatis Inc Tri1 interacts with TRAF7 to displace native TRAF7 interacting partners.

Chlamydia trachomatis is the leading cause of bacterial sexually transmitted infections in the USA and of preventable blindness worldwide. This obligate intracellular pathogen replicates within a membrane-bound inclusion, but how it acquires nutrients from the host while avoiding detection by the innate immune system is incompletely understood. C. trachomatis accomplishes this in part through the translocation of a unique set of effectors into the inclusion membrane, the inclusion membrane proteins (Incs). Incs are ideally positioned at the host-pathogen interface to reprogram host signaling by redirecting proteins or organelles to the inclusion. Using a combination of co-affinity purification, immunofluorescence confocal imaging, and proteomics, we characterize the interaction between an early-expressed Inc of unknown function, Tri1, and tumor necrosis factor receptor-associated factor 7 (TRAF7). TRAF7 is a multi-domain protein with a RING finger ubiquitin ligase domain and a C-terminal WD40 domain. TRAF7 regulates several innate immune signaling pathways associated with C. trachomatis infection and is mutated in a subset of tumors. We demonstrate that Tri1 and TRAF7 specifically interact during infection and that TRAF7 is recruited to the inclusion. We further show that the predicted coiled-coil domain of Tri1 is necessary to interact with the TRAF7 WD40 domain. Finally, we demonstrate that Tri1 displaces the native TRAF7 binding partners, mitogen-activated protein kinase kinase kinase 2 (MEKK2), and MEKK3. Together, our results suggest that by displacing TRAF7 native binding partners, Tri1 has the capacity to alter TRAF7 signaling during C. trachomatis infection.IMPORTANCEChlamydia trachomatis is the leading cause of bacterial sexually transmitted infections in the USA and preventable blindness worldwide. Although easily treated with antibiotics, the vast majority of infections are asymptomatic and therefore go untreated, leading to infertility and blindness. This obligate intracellular pathogen evades the immune response, which contributes to these outcomes. Here, we characterize the interaction between a C. trachomatis-secreted effector, Tri1, and a host protein involved in innate immune signaling, TRAF7. We identified host proteins that bind to TRAF7 and demonstrated that Tri1 can displace these proteins upon binding to TRAF7. Remarkably, the region of TRAF7 to which these host proteins bind is often mutated in a subset of human tumors. Our work suggests a mechanism by which Tri1 may alter TRAF7 signaling and has implications not only in the pathogenesis of C. trachomatis infections but also in understanding the role of TRAF7 in cancer.

How arginine inhibits substrate-binding domain 2 elucidated using molecular dynamics simulations.

The substrate-binding domain 2 (SBD2) is an important part of the bacterial glutamine (GLN) transporter and mediates binding and delivery of GLN to the transporter translocation subunit. The SBD2 consists of two domains, D1 and D2, that bind GLN in the space between domains in a closed structure. In the absence of ligand, the SBD2 adopts an open conformation with larger space between domains. The GLN binding and closing are essential for the subsequent transport into the cell. Arginine (ARG) can also bind to SBD2 but does not induce closing and inhibits GLN transport. We use atomistic molecular dynamics (MD) simulations in explicit solvent to study ARG binding in the presence of the open SBD2 structure and observed reversible binding to the native GLN binding site with similar contacts but no transition to a closed SBD2 state. Absolute binding free energy simulations predict a considerable binding affinity of ARG and GLN to the binding site on the D1 domain. Free energy simulations to induce subsequent closing revealed a strong free energy penalty in case of ARG binding in contrast to GLN binding that favors the closed SBD2 state but still retains a free energy barrier for closing. The simulations allowed the identification of the molecular origin of the closing penalty in case of bound ARG and suggested a mutation of lysine at position 373 to alanine that strongly reduced the penalty and allowed closing even in the presence of bound ARG. The study offers an explanation of the molecular mechanism of how ARG competitively inhibits GLN from binding to SBD2 and from triggering the transition to a closed conformation. The proposed Lys373Ala mutation shows promise as a potential tool to validate whether a conformational mismatch between open SBD2 and the translocator is responsible for preventing ARG uptake to the cell.

Competitive Binding of Viral Nuclear Localization Signal Peptide and Inhibitor Ligands to Importin-α Nuclear Transport Protein.

Venezuelan equine encephalitis virus (VEEV) is a highly virulent pathogen whose nuclear localization signal (NLS) sequence from capsid protein binds to the host importin-α transport protein and blocks nuclear import. We studied the molecular mechanisms by which two small ligands, termed I1 and I2, interfere with the binding of VEEV's NLS peptide to importin-α protein. To this end, we performed all-atom replica exchange molecular dynamics simulations probing the competitive binding of the VEEV coreNLS peptide and I1 or I2 ligand to the importin-α major NLS binding site. As a reference, we used our previous simulations, which examined noncompetitive binding of the coreNLS peptide or the inhibitors to importin-α. We found that both inhibitors completely abrogate the native binding of the coreNLS peptide, forcing it to adopt a manifold of nonnative loosely bound poses within the importin-α major NLS binding site. Both inhibitors primarily destabilize the native coreNLS binding by masking its amino acids rather than competing with it for binding to importin-α. Because I2, in contrast to I1, binds off-site localizing on the edge of the major NLS binding site, it inhibits fewer coreNLS native binding interactions than I1. Structural analysis is supported by computations of the free energies of the coreNLS peptide binding to importin-α with or without competition from the inhibitors. Specifically, both inhibitors reduce the free energy gain from coreNLS binding, with I1 causing significantly larger loss than I2. To test our simulations, we performed AlphaScreen experiments measuring IC50 values for both inhibitors. Consistent with in silico results, the IC50 value for I1 was found to be lower than that for I2. We hypothesize that the inhibitory action of I1 and I2 ligands might be specific to the NLS from VEEV's capsid protein.

High-throughput structure determination of an intrinsically disordered protein using cell-free protein crystallization

Intrinsically disordered proteins (IDPs) play a crucial role in various biological phenomena, dynamically changing their conformations in response to external environmental cues. To gain a deeper understanding of these proteins, it is essential to identify the determinants that fix their structures at the atomic level. Here, we developed a pipeline for rapid crystal structure analysis of IDP using a cell-free protein crystallization (CFPC) method. Through this approach, we successfully demonstrated the determination of the structure of an IDP to uncover the key determinants that stabilize its conformation. Specifically, we focused on the 11-residue fragment of c-Myc, which forms an α-helix through dimerization with a binding partner protein. This fragment was strategically recombined with an in-cell crystallizing protein and was expressed in a cell-free system. The resulting crystal structures of the c-Myc fragment were successfully determined at a resolution of 1.92 Å and we confirmed that they are identical to the structures of the complex with the native binding partner protein. This indicates that the environment of the scaffold crystal can fix the structure of c-Myc. Significantly, these crystals were obtained directly from a small reaction mixture (30 µL) incubated for only 72 h. Analysis of eight crystal structures derived from 22 mutants revealed two hydrophobic residues as the key determinants responsible for stabilizing the α-helical structure. These findings underscore the power of our CFPC screening method as a valuable tool for determining the structures of challenging target proteins and elucidating the essential molecular interactions that govern their stability.

Preserved structure and function of human serum albumin self-folded in the oxidative cytoplasm of Escherichia coli

Human serum albumin (HSA), a polypeptide featuring 17 disulfide bonds, acts as a crucial transport protein in human blood plasma. Its extended circulation half-life, mediated by FcRn (neonatal Fc receptor)-facilitated recycling, positions HSA as an excellent carrier for long-acting drug delivery. However, the conventional method of obtaining HSA from human blood faces limitations due to availability and potential contamination risks, such as blood-borne diseases. This study introduced SHuffle, an oxidative Escherichia coli (E. coli) expression system, for the production of recombinant HSA (rHSA) that spontaneously self-folds into its native conformation. This system ensures precise disulfide bond formation and correct folding of cysteine-rich rHSA, eliminating the need for chaperone co-expression or domain fusion of a folding enhancer. The purified rHSA underwent thorough physicochemical characterization, including mass spectrometry, circular dichroism spectroscopy, intrinsic fluorescence spectroscopy, esterase-like activity assay, and size exclusion chromatography, to assess critical quality attributes. Importantly, rHSA maintained native binding affinity to FcRn and the albumin-binding domain. Collectively, our analyses demonstrated a high comparability between rHSA and plasma-derived HSA. The expression of rHSA in E. coli with an oxidizing cytosol provides a secure and cost-effective approach, enhancing the potential of rHSA for diverse medical applications.

Long-Circulating Vasoactive 1,18-Octadecanedioic Acid-Terlipressin Conjugate.

Hepatorenal syndrome (HRS) is a life-threatening complication of end-stage liver disease first reported over a century ago, but its management still poses an unmet challenge. A therapeutic agent found to stabilize the condition is a short cyclic peptide, vasopressin analogue, terlipressin (TP). While TP is commonly prescribed for HRS patients in most parts of the world, it was only recently approved for use in the United States. TP exhibits short circulation half-lives and adverse side effects associated with the dose required. Herein, we present a 1,18-octadecanedioic acid (ODDA) conjugate of the cyclic peptide (ODDA-TP), which enables noncovalent binding to serum albumin via native fatty acid binding modes. ODDA-TP is demonstrated to outperform TP alone in studies including in vitro cellular receptor activation, stability in plasma, pharmacokinetics, and performance in vivo in rats. Specifically, ODDA-TP had an elimination half-life 20 times that of TP alone while exhibiting a superior safety profile.

DMXP: A De Novo Small-Molecule 3D Structure Predictor with Graph Attention Networks.

Generating the three-dimensional (3D) structure of small molecules is crucial in both structure- and ligand-based drug design. Structure-based drug design needs bioactive conformations of compounds for lead identification and optimization. Ligand-based drug design techniques, such as 3D shape similarity search, 3D pharmacophore model, 3D-QSAR, etc., all require high-quality small-molecule ligand conformations to obtain reliable results. Although predicting a small molecular bioactive conformer requires information from the receptor, a crystal structure of the molecule is a proper approximation to its bioactive conformer in a specific receptor because the binding pose of a small molecule in its receptor's binding pockets should be energetically close to the crystal structures. This study presents a de novo small molecular structure predictor (dMXP) with graph attention networks based on crystal data derived from the Cambridge Structural Database (CSD) combined with molecular electrostatic information calculated by density-functional theory (DFT). Two featuring strategies (topological and atomic partial change features) were employed to explore the relation between these features and the 3D crystal structure of a small molecule. These features were then assembled to construct the holistic 3D crystal structure of a molecule. Molecular graphs were encoded using a graph attention mechanism to deal with the issues of the inconsistencies of local substructures contributing to the entire molecular structure. The root-mean-square deviation (RMSDs) of approximately 80% dMXP predicted structures and the native binding poses within receptors are less than 2.0 Å.

Engineering a human P2X2 receptor with altered ligand selectivity in yeast

P2X receptors are a family of ligand gated ion channels found in a range of eukaryotic species including humans but are not naturally present in the yeast Saccharomyces cerevisiae. We demonstrate the first recombinant expression and functional gating of the P2X2 receptor in baker’s yeast. We leverage the yeast host for facile genetic screens of mutant P2X2 by performing site saturation mutagenesis at residues of interest, including SNPs implicated in deafness and at residues involved in native binding. Deep mutational analysis and rounds of genetic engineering yield mutant P2X2 F303Y A304W, which has altered ligand selectivity towards the ATP analog AMP-PNP. The F303Y A304 variant shows over 100-fold increased intracellular calcium amplitudes with AMP-PNP compared to the WT receptor and has a much lower desensitization rate. Since AMP-PNP does not naturally activate P2X receptors, the F303Y A304 P2X2 may be a starting point for downstream applications in chemogenetic cellular control. Interestingly, the A304W mutation selectively destabilizes the desensitized state, which may provide a mechanistic basis for receptor opening with suboptimal agonists. The yeast system represents an inexpensive, scalable platform for ion channel characterization and engineering by circumventing the more expensive and time-consuming methodologies involving mammalian hosts.

GSScore: a novel Graphormer-based shell-like scoring method for protein-ligand docking.

Protein-ligand interactions (PLIs) are essential for cellular activities and drug discovery. But due to the complexity and high cost of experimental methods, there is a great demand for computational approaches to recognize PLI patterns, such as protein-ligand docking. In recent years, more and more models based on machine learning have been developed to directly predict the root mean square deviation (RMSD) of a ligand docking pose with reference to its native binding pose. However, new scoring methods are pressingly needed in methodology for more accurate RMSD prediction. We present a new deep learning-based scoring method for RMSD prediction of protein-ligand docking poses based on a Graphormer method and Shell-like graph architecture, named GSScore. To recognize near-native conformations from a set of poses, GSScore takes atoms as nodes and then establishes the docking interface of protein-ligand into multiple bipartite graphs within different shell ranges. Benefiting from the Graphormer and Shell-like graph architecture, GSScore can effectively capture the subtle differences between energetically favorable near-native conformations and unfavorable non-native poses without extra information. GSScore was extensively evaluated on diverse test sets including a subset of PDBBind version 2019, CASF2016 as well as DUD-E, and obtained significant improvements over existing methods in terms of RMSE, $R$ (Pearson correlation coefficient), Spearman correlation coefficient and Docking power.

Compromise in Docking Power of Liganded Crystal Structures of Mpro SARS-CoV-2 Surpasses 90% Success Rate.

Herein, we present the capacity of three different molecular docking programs (AutoDock, AutoDock Vina, and PLANTS) to identify and reproduce the binding modes of ligands present in 247 covalent and 169 noncovalent complex crystal structures of the severe acute respiratory syndrome coronavirus 2 main protease (Mpro). The compromise in docking power is evaluated with respect to their ability to generate poses similar to the crystal structure binding mode (heavy atoms' root-mean-square deviation < 2 Å) and their ability to recognize the native binding mode with an included compensation for the scoring function error. Noncovalently bound inhibitors are best modeled by AutoDock Vina (90.6% success rate in the active site), while the most relevant results for covalently bound inhibitors are produced by PLANTS (93.0%). AutoDock shows acceptable performance for both types of ligands, 81.1 and 76.4% for noncovalent and covalent complexes, respectively. All three programs manifest worse performance when reproducing surface-bound ligands. Comparison with other works illustrates the importance of crystal structure processing (12% of noncovalent and 26% of covalent ligands had to be manually corrected), proper sampling protocol settings, and inclusion of root-mean-square deviation (RMSD)/scoring function error compensations in crystal structure pose identification. Results are analyzed with respect to a clustering scheme of the noncovalently bound ligands and the chemical reaction type of the covalent ligand bound to the Cys145 residue. A comparison of screening power based on the docking scores of noncovalent ligands from the crystal structures with a "Directory of Useful Decoys, Enhanced" set of known decoys (6562 compounds) and ZINC15 in vivo subset (60,394 compounds) is provided. Ligand and protein input files are provided for future benchmarking purposes.

Small molecule- and peptide-drug conjugates addressing integrins: A story of targeted cancer treatment.

Targeted cancer treatment should avoid side effects and damage to healthy cells commonly encountered during traditional chemotherapy. By combining small molecule or peptidic ligands as homing devices with cytotoxic drugs connected by a cleavable or non-cleavable linker in peptide-drug conjugates (PDCs) or small molecule-drug conjugates (SMDCs), cancer cells and tumours can be selectively targeted. The development of highly affine, selective peptides and small molecules in recent years has allowed PDCs and SMDCs to increasingly compete with antibody-drug conjugates (ADCs). Integrins represent an excellent target for conjugates because they are overexpressed by most cancer cells and because of the broad knowledge about native binding partners as well as the multitude of small-molecule and peptidic ligands that have been developed over the last 30 years. In particular, integrin αVβ3 has been addressed using a variety of different PDCs and SMDCs over the last two decades, following various strategies. This review summarises and describes integrin-addressing PDCs and SMDCs while highlighting points of great interest.