Computational investigation of functional water molecules in GPCRs bound to G protein or arrestin.

G protein-coupled receptors (GPCRs) are membrane proteins constituting the largest family of drug targets. The activated GPCR binds either the heterotrimeric G proteins or arrestin through its activation cycle. Water molecules have been reported to play a role in GPCR activation. Nevertheless, reported studies are focused on the hydrophobic helical bundle region. How water molecules function in GPCR bound either G protein or arrestin is rarely studied. To address this issue, we carried out computational studies on water molecules in both GPCR/G protein complexes and GPCR/arrestin complexes. Using inhomogeneous fluid theory (IFT), we locate all possible hydration sites in GPCRs binding either to G protein or arrestin. We observe that the number of water molecules on the interaction surface between GPCRs and signal proteins are correlated with the insertion depths of the α5-helix from G-protein or "finger loop" from arrestin in GPCRs. In three out of the four simulation pairs, the interfaces of Rhodopsin, M2R and NTSR1 in the G protein-associated systems show more water-mediated hydrogen-bond networks when compared to these in arrestin-associated systems. This reflects that more functionally relevant water molecules may probably be attracted in G protein-associated structures than that in arrestin-associated structures. Moreover, we find the water-mediated interaction networks throughout the NPxxY region and the orthosteric pocket, which may be a key for GPCR activation. Reported studies show that non-biased agonist, which can trigger both GPCR-G protein and GPCR-arrestin activation signal, can result in pharmacologically toxicities. Our comprehensive studies of the hydration sites in GPCR/G protein complexes and GPCR/arrestin complexes may provide important insights in the design of G-protein biased agonists.

Inhibition mechanism of MRTX1133 on KRASG12D: a molecular dynamics simulation and Markov state model study.

The mutant KRAS was considered as an "undruggable" target for decades, especially KRASG12D. It is a great challenge to develop the inhibitors for KRASG12D which lacks the thiol group for covalently binding ligands. The discovery of MRTX1133 solved the dilemma. Interestingly, MRTX1133 can bind to both the inactive and active states of KRASG12D. The binding mechanism of MRTX1133 with KRASG12D, especially how MRTX1133 could bind the active state KRASG12D without triggering the active function of KRASG12D, has not been fully understood. Here, we used a combination of all-atom molecular dynamics simulations and Markov state model (MSM) to understand the inhibition mechanism of MRTX1133 and its analogs. The stationary probabilities derived from MSM show that MRTX1133 and its analogs can stabilize the inactive or active states of KRASG12D into different conformations. More remarkably, by scrutinizing the conformational differences, MRTX1133 and its analogs were hydrogen bonded to Gly60 to stabilize the switch II region and left switch I region in a dynamically inactive conformation, thus achieving an inhibitory effect. Our simulation and analysis provide detailed inhibition mechanism of KRASG12D induced by MRTX1133 and its analogs. This study will provide guidance for future design of novel small molecule inhibitors of KRASG12D.

Propagation of the Allosteric Modulation Induced by Sodium in the δ-Opioid Receptor.

Allosteric sodium in the helix bundle of a G protein-coupled receptor (GPCR) can modulate the receptor activation on the intracellular side. This phenomenon has confounded the GPCR community for decades. In this work, we present a theoretical model that reveals the mechanism of the allosteric modulation induced by sodium in the δ-opioid receptor. We found that the allosteric sodium ion exploits a distinct conformation of the key residue Trp2746.48 to propagate the modulation to helices 5 and 6, which further transmits along the helices and regulates their positions on the intracellular side. This mechanism is supported by subsequent functional assays. Remarkably, our results highlight the contrast between the allosteric effects towards two GPCR partners, the G protein and ß-arrestin, as indicated by the fact that the allosteric modulation initiated by the sodium ion significantly affects the ß-arrestin recruitment, while it alters the G protein signaling only moderately. We believe that the mechanism revealed in this work can be used to explain allosteric effects initiated by sodium in other GPCRs since the allosteric sodium is highly conserved across GPCRs.

Synthesis, structure-activity relationship and biological evaluation of novel arylpiperzines as α1A/1D-AR subselective antagonists for BPH.

A series of novel arylpiperazine derivatives as α1A/1D-adrenergic receptors (AR) subtype selective antagonists were designed, synthesized and evaluated for their antagonistic activities towards α1-ARs (α1A, α1B, and α1D). Compounds 9, 12, 13, 15, 17, 18, 21, 22, 25 and 26 exerted strong antagonistic effects on α1A and/or α1D subtypes over α1B in vitro. SAR analysis indicated that chloride at the ortho-phenyl position for compound 17 was beneficial for the highest α1A/D-AR sub-selectivity. Moreover, molecular docking study of compound 17 with the homology-modeled α1-ARs (α1A, α1B, and α1D) structures exhibited differences of key amino resides in the docking pocket which may influence the subtype selectivity. ILE 193 of α1A was validated as the key residues for binding ligand. This work provides useful information for finding more new potential drugs in clinic in treating benign prostatic hyperplasia (BPH).

A theoretical study on the molecular determinants of the affibody protein Z(Aß3) bound to an amyloid ß peptide.

Amyloid beta (Aß) peptides are small cleavage products of the amyloid precursor protein. Aggregates of Aß peptides are thought to be linked with Alzheimer's and other neurodegenerative diseases. Strategies aimed at inhibiting amyloid formation and promoting Aß clearance have been proposed and investigated in in vitro experiments and in vivo therapies. A recent study indicated that a novel affibody protein ZAß3, which binds to an Aß40 monomer with a binding affinity of 17 nM, is able to prevent the aggregation of Aß40. However, little is known about the energetic contribution of each residue in ZAß3 to the formation of the (ZAß3)2:Aß complex. To address this issue, we carried out unbiased molecular dynamics simulations and molecular mechanics Poisson-Boltzmann surface area calculations. Through the per-residue decomposition scheme, we identified that the van der Waals interactions between the hydrophobic residues of (ZAß3)2 and those at the exterior and interior faces of Aß are the main contributors to the binding of (ZAß3)2 to Aß. Computational alanine scanning identified 5 hot spots, all residing in the binding interface and contributing to the binding of (ZAß3)2 to Aß through the hydrophobic effect. In addition, the amide hydrogen bonds in the 4-strand ß-sheet and the π-π stacking were also analyzed. Overall, our study provides a theoretical basis for future experimental improvement of the ZAß3 peptide binding to Aß.

Structure-based ensemble-QSAR model: a novel approach to the study of the EGFR tyrosine kinase and its inhibitors.

AIM: To develop a novel 3D-QSAR approach for study of the epidermal growth factor receptor tyrosine kinase (EGFR TK) and its inhibitors. METHODS: One hundred thirty nine EGFR TK inhibitors were classified into 3 clusters. Ensemble docking of these inhibitors with 19 EGFR TK crystal structures was performed. Three protein structures that showed the best recognition of each cluster were selected based on the docking results. Then, a novel QSAR (ensemble-QSAR) building method was developed based on the ligand conformations determined by the corresponding protein structures. RESULTS: Compared with the 3D-QSAR model, in which the ligand conformations were determined by a single protein structure, ensemble-QSAR exhibited higher R2 (0.87) and Q2 (0.78) values and thus appeared to be a more reliable and better predictive model. Ensemble-QSAR was also able to more accurately describe the interactions between the target and the ligands. CONCLUSION: The novel ensemble-QSAR model built in this study outperforms the traditional 3D-QSAR model in rationality, and provides a good example of selecting suitable protein structures for docking prediction and for building structure-based QSAR using available protein structures.

Accelerated Discovery of Macrocyclic CDK2 Inhibitor QR-6401 by Generative Models and Structure-Based Drug Design.

Selective CDK2 inhibitors have the potential to provide effective therapeutics for CDK2-dependent cancers and for combating drug resistance due to high cyclin E1 (CCNE1) expression intrinsically or CCNE1 amplification induced by treatment of CDK4/6 inhibitors. Generative models that take advantage of deep learning are being increasingly integrated into early drug discovery for hit identification and lead optimization. Here we report the discovery of a highly potent and selective macrocyclic CDK2 inhibitor QR-6401 (23) accelerated by the application of generative models and structure-based drug design (SBDD). QR-6401 (23) demonstrated robust antitumor efficacy in an OVCAR3 ovarian cancer xenograft model via oral administration.

Discovery of novel EGFR tyrosine kinase inhibitors by structure-based virtual screening.

By using of structure-based virtual screening, 13 novel epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors were discovered from 197,116 compounds in the SPECS database here. Among them, 8 compounds significantly inhibited EGFR kinase activity with IC(50) values lower than 10 µM. 3-{[1-(3-Chloro-4-fluorophenyl)-3,5-dioxo-4-pyrazolidinylidene]methyl}phenyl 2-thiophenecarboxylate (13), particularly, was the most potent inhibitor possessing the IC(50) value of 3.5 µM. The docking studies also provide some useful information that the docking models of the 13 compounds are beneficial to find a new path for designing novel EGFR inhibitors.

Insights into the binding modes of human ß3-adrenergic receptor agonists with ligand-based and receptor-based methods.

Agonists of ß(3)-adrenergic receptor (AR) have been thought as potential drugs for the treatment of obesity, type II diabetes, and overactive bladder. In order to clarify the essential structure-activity relationship and the detailed binding modes of ß(3)-AR agonists as well as to identify new lead compounds activating ß(3)-AR, ligand-based and receptor-based methods were applied. The pharmacophore models were developed based on 144 ß(3)-AR agonists. Meanwhile, the homology model of the ß(3)-AR was built based on the crystal structure of ß(2)-AR. The pharmacophore model and the homology model mapped with each other very well, and some important information was obtained from the docking result. For example, agonists formed similar hydrogen-bonding interactions with residues Asp117, Arg315, and Asn332, π-π stacking interaction with residues Phe308, and hydrophobic interactions with residues Val118, Val121, Ala197, Phe198, Ala199, Phe309, and Phe328 of ß(3)-AR. And the major difference about binding mode from the crystal structures of ß(1)- and ß(2)-ARs is the hydrogen-bonding interaction with the residue Arg315, which corresponds to the residue Asn313 of ß(1)-AR and the residue His296 of ß(2)-AR, respectively. Our findings may be crucial for the design and development of novel selective and potent ß(3)-AR agonists.

Atomistic and Thermodynamic Analysis of N6-Methyladenosine (m6A) Recognition by the Reader Domain of YTHDC1.

N6-Methyladenosine (m6A) is the most frequent modification in eukaryotic messenger RNA (mRNA) and its cellular processing and functions are regulated by the reader proteins YTHDCs and YTHDFs. However, the mechanism of m6A recognition by the reader proteins is still elusive. Here, we investigate this recognition process by combining atomistic simulations, site-directed mutagenesis, and biophysical experiments using YTHDC1 as a model. We find that the N6 methyl group of m6A contributes to the binding through its specific interactions with an aromatic cage (formed by Trp377 and Trp428) and also by favoring the association-prone conformation of m6A-containing RNA in solution. The m6A binding site dynamically equilibrates between multiple metastable conformations with four residues being involved in the regulation of m6A binding (Trp428, Met438, Ser378, and Thr379). Trp428 switches between two conformational states to build and dismantle the aromatic cage. Interestingly, mutating Met438 and Ser378 to alanine does not alter m6A binding to the protein but significantly redistributes the binding enthalpy and entropy terms, i.e., enthalpy-entropy compensation. Such compensation is reasoned by different entropy-enthalpy transduction associated with both conformational changes of the wild-type and mutant proteins and the redistribution of water molecules. In contrast, the point mutant Thr379Val significantly changes the thermal stability and binding capability of YTHDC1 to its natural ligand. Additionally, thermodynamic analysis and free energy calculations shed light on the role of a structural water molecule that synergistically binds to YTHDC1 with m6A and acts as the hub of a hydrogen-bond network. Taken together, the experimental data and simulation results may accelerate the discovery of chemical probes, m6A-editing tools, and drug candidates against reader proteins.

Doxorubicin-loaded hydrogen peroxide self-providing copper nanodots for combination of chemotherapy and acid-induced chemodynamic therapy against breast cancer.

In recent years, chemodynamic therapy (CDT) has gained increasing interest in cancer treatment. In contrast to photodynamic therapy and sonodynamic therapy, extrinsic excitations such as laser or ultrasound are not required in CDT. As a result, the CDT performance is not limited by the penetration depth of the external irritation. However, CDT relies heavily on hydrogen peroxide (H2O2) in the tumour microenvironment (TME). Insufficient H2O2 in the TME limits the CDT performance, and the most reported methods to produce H2O2 in the TME are dependent on oxygen supply, which is restricted by the hypoxic TME. In this study, H2O2 self-providing copper nanodots were proposed, and the drug doxorubicin (DOX) was successfully loaded to construct DOX-nanodots. Our results showed that the nanodots produced H2O2 in the weakly acidic TME due to the peroxo group and further generated the most active hydroxyl radical (OH) through the Fenton-like reaction. This process was pH-dependent and did not occur in a neutral environment. In addition to OH, the nanodots also produced singlet oxygen (1O2) and superoxide anions (O2-) in the cancer cells. The copper nanodots performed promising CDT against breast cancer in vitro and in vivo, with enhanced cell apoptosis and decreased cell proliferation. The combination of chemotherapy and CDT using DOX-nanodots further improved the therapeutic effects. The treatments showed good biocompatibility with no obvious toxicity in major tissues, possibly due to the specific OH generation in the weakly acidic TME. In summary, the H2O2 self-providing copper nanodots in combination with DOX showed promising cancer-curing effects due to the oxygen-independent and tumour-specific production of reactive oxygen species and the cooperation of chemotherapy.

Molecular insights into ago-allosteric modulation of the human glucagon-like peptide-1 receptor.

The glucagon-like peptide-1 (GLP-1) receptor is a validated drug target for metabolic disorders. Ago-allosteric modulators are capable of acting both as agonists on their own and as efficacy enhancers of orthosteric ligands. However, the molecular details of ago-allosterism remain elusive. Here, we report three cryo-electron microscopy structures of GLP-1R bound to (i) compound 2 (an ago-allosteric modulator); (ii) compound 2 and GLP-1; and (iii) compound 2 and LY3502970 (a small molecule agonist), all in complex with heterotrimeric Gs. The structures reveal that compound 2 is covalently bonded to C347 at the cytoplasmic end of TM6 and triggers its outward movement in cooperation with the ECD whose N terminus penetrates into the GLP-1 binding site. This allows compound 2 to execute positive allosteric modulation through enhancement of both agonist binding and G protein coupling. Our findings offer insights into the structural basis of ago-allosterism at GLP-1R and may aid the design of better therapeutics.

The Antibacterial Effects of Supermolecular Nano-Carriers by Combination of Silver and Photodynamic Therapy.

The over-use of antibiotics has promoted multidrug resistance and decreased the efficacy of antibiotic therapy. Thus, it is still in great need to develop efficient treatment strategies to combat the bacteria infection. The antimicrobial photodynamic therapy (aPDT) and silver nanoparticles have been emerged as effective antibacterial methods. However, the silver therapy may induce serious damages to human cells at high concentrations and, the bare silver nanoparticles may rapidly aggregate, which would reduce the antibacterial efficacy. The encapsulation of sliver by nano-carrier is a promising way to avoid its aggregation and facilitates the co-delivery of drugs for combination therapy, which does not require high concentration of sliver to exert antibacterial efficacy. This work constructed a self-assembled supermolecular nano-carrier consisting of the photosensitizers (PSs), the anti-inflammatory agent and silver. The synthesized supermolecular nano-carrier produced reactive oxygen species (ROS) under the exposure of 620-nm laser. It exhibited satisfying biocompatibility in L02 cells. And, this nano-carrier showed excellent antibacterial efficacy in Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) as indicated by bacterial growth and colony formation. Its antibacterial performance is further validated by the bacteria morphology through the scanning electron microscope (SEM), showing severely damaged structures of bacteria. To summary, the supermolecular nano-carrier TCPP-MTX-Ag-NP combining the therapeutic effects of ROS and silver may serve as a novel strategy of treatment for bacterial infection.

Accuracy assessment of protein-based docking programs against RNA targets.

Ribonucleic acid (RNA) molecules play central roles in a variety of biological processes and, hence, are attractive targets for therapeutic intervention. In recent years, molecular docking techniques have become one of the most popular and successful approaches in drug discovery; however, almost all docking programs are protein based. The adaptability of popular docking programs in RNA world has not been systematically evaluated. This paper describes the comprehensive evaluation of two widely used protein-based docking programs--GOLD and Glide--for their docking and virtual screening accuracies against RNA targets. Using multiple docking strategies, both GOLD 4.0 and Glide 5.0 successfully reproduced most binding modes of the 60 tested RNA complexes. Applying different docking/scoring combinations, significant enrichments from the simulated virtual and fragment screening experiments were achieved against tRNA decoding A site of 16S rRNA (rRNA A-site). Our study demonstrated that current protein-based docking programs can fulfill general docking tasks against RNA, and these programs are very helpful in RNA-based drug discovery and design.

Electrospun Conductive Nanofiber Yarn for a Wearable Yarn Supercapacitor with High Volumetric Energy Density.

One-dimensional, flexible yarn-shaped supercapacitors for woven cloth have the potential for use in different kinds of wearable devices. Nevertheless, the challenge that supercapacitors face is low energy density. In this paper, we present a low-cost and large-scale manufacturing method to construct a supercapacitor yarn with high power and high energy density. To construct the novel and flexible poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate)⁻polyacrylonitrile (PDEOT: PSS-PAN)/Ni cotton (PNF/NiC) capacitor yarn, an electrospinning technique was initially used to wrap the polyacrylonitrile (PAN) nanofibers around the core Ni-coated yarn. The PEDOT: PSS⁻PAN nanofiber composite electrode was created using in situ deposition and H3PO4/PVA was used as a gel electrolyte. This electrode material has a yarn/nanofiber/PEDOT: PSS nanoparticle hierarchical structure, providing a high specific area and enhanced pseudocapacitance. The electrode demonstrated a high volumetric capacitance of 26.88 F·cm-3 (at 0.08 A·cm-3), an energy density of 9.56 mWh·cm-3, and a power density of 830 mW·cm-3. In addition, the PNF/NiC capacitor yarns are lightweight, highly flexible, resistant to bending fatigue, can be connected in series or parallel, and may be suitable for a variety of wearable electronic products.

Simulation of spontaneous G protein activation reveals a new intermediate driving GDP unbinding.

Activation of heterotrimeric G proteins is a key step in many signaling cascades. However, a complete mechanism for this process, which requires allosteric communication between binding sites that are ~30 Å apart, remains elusive. We construct an atomically detailed model of G protein activation by combining three powerful computational methods: metadynamics, Markov state models (MSMs), and CARDS analysis of correlated motions. We uncover a mechanism that is consistent with a wide variety of structural and biochemical data. Surprisingly, the rate-limiting step for GDP release correlates with tilting rather than translation of the GPCR-binding helix 5. ß-Strands 1 - 3 and helix 1 emerge as hubs in the allosteric network that links conformational changes in the GPCR-binding site to disordering of the distal nucleotide-binding site and consequent GDP release. Our approach and insights provide foundations for understanding disease-implicated G protein mutants, illuminating slow events in allosteric networks, and examining unbinding processes with slow off-rates.

Choice of Adaptive Sampling Strategy Impacts State Discovery, Transition Probabilities, and the Apparent Mechanism of Conformational Changes.

Interest in atomically detailed simulations has grown significantly with recent advances in computational hardware and Markov state modeling (MSM) methods, yet outstanding questions remain that hinder their widespread adoption. Namely, how do alternative sampling strategies explore conformational space and how might this influence predictions generated from the data? Here, we seek to answer these questions for four commonly used sampling methods: (1) a single long simulation, (2) many short simulations run in parallel, (3) adaptive sampling, and (4) our recently developed goal-oriented sampling algorithm, FAST. We first develop a theoretical framework for analytically calculating the probability of discovering select states on simple landscapes, where we uncover the drastic effects of varying the number and length of simulations. We then use kinetic Monte Carlo simulations on a variety of physically inspired landscapes to characterize the probability of discovering particular states and transition pathways for each of the four methods. Consistently, we find that FAST simulations discover each target state with the highest probability, while traversing realistic pathways. Furthermore, we uncover the potential pathology that short parallel simulations sometimes predict an incorrect transition pathway by crossing large energy barriers that long simulations would typically circumnavigate. We refer to this pathology as "pathway tunneling". To protect against this phenomenon when using adaptive-sampling and FAST simulations, we introduce the FAST-string method. This method enhances sampling along the highest-flux transition paths to refine an MSMs transition probabilities and discriminate between competing pathways. Additionally, we compare the performance of a variety of MSM estimators in describing accurate thermodynamics and kinetics. For adaptive sampling, we recommend simply normalizing the transition counts out of each state after adding small pseudocounts to avoid creating sources or sinks. Lastly, we evaluate whether our insights from simple landscapes hold for all-atom molecular dynamics simulations of the folding of the λ-repressor protein. Remarkably, we find that FAST-contacts predicts the same folding pathway as a set of long simulations but with orders of magnitude less simulation time.

Allosteric inhibitor remotely modulates the conformation of the orthestric pockets in mutant IDH2/R140Q.

Neomorphic mutation R140Q in the metabolic enzyme isocitrate dehydrogenase 2 (IDH2) is found to be a driver mutation in cancers. Recent studies revealed that allosteric inhibitors could selectively inhibit IDH2/R140Q and induce differentiation of TF-1 erythroleukemia and primary human AML cells. However, the allosteric inhibition mechanism is not very clear. Here, we report the results from computational studies that AGI-6780 binds tightly with the divalent cation binding helices at the homodimer interface and prevents the transition of IDH2/R140Q homodimer to a closed conformation that is required for catalysis, resulting in the decrease of the binding free energy of NADPHs. If the allosteric inhibitor is removed, the original open catalytic center of IDH2/R140Q will gradually reorganize to a quasi-closed conformation and the enzymatic activity might recover. Unlike IDH2/R140Q, AGI-6780 locks one monomer of the wild-type IDH2 in an inactive open conformation and the other in a half-closed conformation, which can be used to explain the selectivity of AGI-6780. Our results suggest that conformational changes are the primary contributors to the inhibitory potency of the allosteric inhibitor. Our study will also facilitate the understanding of the inhibitory and selective mechanisms of AG-221 (a promising allosteric inhibitor that has been approved by FDA) for mutant IDH2.

Molecular switches of the κ opioid receptor triggered by 6'-GNTI and 5'-GNTI.

The κ opioid receptor (κOR) is a member of G-protein-coupled receptors, and is considered as a promising drug target for treating neurological diseases. κOR selective 6'-GNTI was proved to be a G-protein biased agonist, whereas 5'-GNTI acts as an antagonist. To investigate the molecular mechanism of how these two ligands induce different behaviors of the receptor, we built two systems containing the 5'-GNTI-κOR complex and the 6'-GNTI-κOR complex, respectively, and performed molecular dynamics simulations of the two systems. We observe that transmembrane (TM) helix 6 of the κOR rotates about 4.6(o) on average in the κOR-6'-GNTI complex. Detailed analyses of the simulation results indicate that E297(6.58) and I294(6.55) play crucial roles in the rotation of TM6. In the simulation of the κOR-5'-GNTI system, it is revealed that 5'-GNTI can stabilize TM6 in the inactive state form. In addition, the kink of TM7 is stabilized by a hydrogen bond between S324(7.47) and the residue V69(1.42) on TM1.

Structure and Dynamics of PD-L1 and an Ultra-High-Affinity PD-1 Receptor Mutant.

The immune checkpoint receptor PD-1 and its ligand, PD-L1, have emerged as key regulators of anti-tumor immunity in humans. Recently, we reported an ultra-high-affinity PD-1 mutant, termed high-affinity consensus (HAC) PD-1, which shows superior therapeutic efficacy in mice compared with antibodies. However, the molecular details underlying the action of this agent remain incompletely understood, and a molecular view of PD-1/PD-L1 interactions in general is only beginning to emerge. Here, we report the structure of HAC PD-1 in complex with PD-L1, showing that it binds PD-L1 using a unique set of polar interactions. Biophysical studies and long-timescale molecular dynamics experiments reveal the mechanisms by which ten point mutations confer a 35,000-fold enhancement in binding affinity, and offer atomic-scale views of the role of conformational dynamics in PD-1/PD-L1 interactions. Finally, we show that the HAC PD-1 exhibits pH-dependent affinity, with pseudo-irreversible binding in a low pH setting akin to the tumor microenvironment.