Structure-Guided Design of Potent Inhibitors of SARS-CoV-2 3CL Protease: Structural, Biochemical, an
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WDR5 is a chromatin-regulatory scaffold protein overexpressed in various cancers and a potential epigenetic drug target for the treatment of mixed-lineage leukemia. In this a paper, we describe the discovery of potent and selective WDR5-WINsite inhibitors using fragment-based methods and structure-based design. NMR-based screening of a large fragment library identified several chemically distinct hit series that bind to the WIN site within WDR5. Members of a 6,7-dihydro-5$H$pyrrolo[1,2-$a$]imidazole fragment class were expanded using a structure-based design approach to arrive at lead compounds with dissociation constants <10 nM and micromolar cellular activity against an AML-leukemia cell line. These compounds represent starting points for the discovery of clinically useful WDR5 inhibitors for the treatment of cancer.
The M protein of group A streptococci (Strep A) is a major virulence determinant and protective antigen. The N-terminal region of the M protein is variable in sequence, defines the M/emm type, and contains epitopes that elicit opsonic antibodies that protect animals from challenge infections. Although there are >200 M types of Strep A, there is now evidence that structurally related M proteins can be grouped into clusters and that immunity may be cluster-specific in addition to M type-specific. This observation has led to recent studies of structure-based design of multivalent M peptide vaccines to select peptides predicted to cross-react with heterologous M types to improve vaccine coverage. In the current study, we have applied a refined series of peptide structural algorithms to predict immunological cross-reactivity among 117N-terminal M peptides representing the most prevalent M types of Strep A. Based on the results of the structural analyses, in combination with global M type prevalence data, we constructed a 32-valent vaccine containing 19 cross-reactive vaccine candidates predicted to cross-react with 37 heterologous M peptides to which were added 13 type-specific M peptides. Further, the 4-protein recombinant vaccine was immunogenic in rabbits and elicited significant levels of antibodies against 31/32 (97%) vaccine peptides and 28/37 (76%) peptides predicted to cross-react. The vaccine antisera also promoted opsonophagocytic killing of vaccine and cross-reactive M types of Strep A. Based on a recent analysis of M type prevalence of Strep A, the potential global coverage of the 32-valent vaccine is ~90%, ranging from 68% in Africa to 95% in North America. Our results indicate the utility of structure-based design that may be applied to future studies of broadly protective M peptide vaccines.
We describe the use of comparative structural analysis and structure-guided molecular design to develop potent and selective inhibitors (10d and (S)-17b) of matrix metalloproteinase 13 (MMP-13). We applied a three-step process, starting with a comparative analysis of the X-ray crystallographic structure of compound 5 in complex with MMP-13 with published structures of known MMP-13·inhibitor complexes followed by molecular design and synthesis of potent but nonselective zinc-chelating MMP inhibitors (e.g., 10a and 10b). After demonstrating that the pharmacophores of the chelating inhibitors (S)-10a, (R)-10a, and 10b were binding within the MMP-13 active site, the Zn 2+ chelating unit was replaced with nonchelating polar residues that bridged over the Zn 2+ binding site and reached into a solvent accessible area. After two rounds of structural optimization, these design approaches led to small molecule MMP-13 inhibitors 10d and (S)-17b, which bind within the substrate-binding site of MMP-13 and surround the catalytically active Zn 2+ ion without chelating to the metal. These compounds exhibit at least 500-fold selectivity versus other MMPs.
We report two generative deep-learning models that predict amino acid sequences and 3D protein structures on the basis of secondary-structure design objectives via either the overall content or the per-residue structure. Both models are robust regarding imperfect inputs and offer de novo design capacity because they can discover new protein sequences not yet discovered from natural mechanisms or systems. The residue-level secondary-structure design model generally yields higher accuracy and more diverse sequences. These findings suggest unexplored opportunities for protein designs and functional outcomes within the vast amino acid sequences beyond known proteins. Our models, based on an attention-based diffusion model and trained on a dataset extracted from experimentally known 3D protein structures, offer numerous downstream applications in the conditional generative design of various biological or engineering systems. Future work could include additional conditioning and an exploration of other functional properties of the generated proteins for various properties beyond structural objectives.
KRAS has long been referred to as an ‘undruggable’ target due to its high affinity for its cognate ligands (GDP and GTP) and its lack of readily exploited allosteric binding pockets. Recent progress in the development of covalent inhibitors of KRAS G12C has revealed that occupancy of an allosteric binding site located between the α3-helix and switch-II loop of KRAS G12C —sometimes referred to as the ‘switch-II pocket’—holds great potential in the design of direct inhibitors of KRAS G12C . In studying diverse switch-II pocket binders during the development of sotorasib (AMG 510), the first FDA-approved inhibitor of KRAS G12C , we found the dramatic conformational flexibility of the switch-II pocket posing significant challenges toward the structure-based design of inhibitors. Here, we present our computational approaches for dealing with receptor flexibility in the prediction of ligand binding pose and binding affinity. For binding pose prediction, we modified the covalent docking program CovDock to allow for protein conformational mobility. This new docking approach, termed as FlexCovDock, improves success rates from 55 to 89% for binding pose prediction on a dataset of 10 cross-docking cases and has been prospectively validated across diverse ligand chemotypes. For binding affinity prediction, we found standard free energy perturbation (FEP) methods could not adequately handle the significant conformational change of the switch-II loop. We developed a new computational strategy to accelerate conformational transitions through the use of targeted protein mutations. Using this methodology, the mean unsigned error (MUE) of binding affinity prediction were reduced from 1.44 to 0.89 kcal/mol on a set of 14 compounds. These approaches were of significant use in facilitating the structure-based design of KRAS G12C inhibitors and are anticipated to be of further use in the design of covalent (and noncovalent) inhibitors of other conformationally labile protein targets.
Design of interfaces with thermodynamic and kinetic specificity is of great importance for hydrogen storage from both an applied and fundamental perspective. Here, in order to destabilize the metal hydride and protect the dehydrogenated products from oxidizing, a unique core-shell structure of porous Mg(BH4)2-based framework with a thin layer (no more than 5 nm) of MgCl2 additives on the surface, has been proposed and synthesized via a wet-chemical method. The local structure and electronic state of the present complex system are systematically investigated to understand the correlation between the distribution of additives and dehydrogenation property of Mg(BH4)2. A significant improvement is achieved for hydrogen desorption with chlorides: initial hydrogen release from MgCl2 decorated ..gamma..-phase Mg(BH4)2 particles commences at 100 °C and reaches a maximum of 9.4 wt% at 385 °C. Besides the decreased decomposition temperature, an activation barrier of about 76.4 kJ mol-1 lower than that of Mg(BH4)2 without MgCl2 is obtained. Moreover, MgCl2 decoration can also prevent the whole decomposed system (both Mg- and B- elements) from oxidizing, which is a necessary condition to reversibility.
Systems and methods for optimizing a lattice structure design are disclosed herein. In some embodiments, a method for optimizing a lattice structure design can include (i) modeling the lattice structure with a component-wise reduced-order model (CWROM) and (ii) optimizing the CWROM based on a selected criterion using a topology optimization algorithm for lattice design. The selected criterion can include a boundary condition and a load applied to the lattice structure. By modeling the lattice structure as a CWROM, the optimization process can be very fast while still permitting the accurate computation of physical quantities of the lattice structure.
Despite recent advances in therapeutic options, hepatitis C virus (HCV) remains a severe global disease burden, and a vaccine can substantially reduce its incidence. Due to its extremely high sequence variability, HCV can readily escape the immune response; thus, an effective vaccine must target conserved, functionally important epitopes. Using the structure of a broadly neutralizing antibody in complex with a conserved linear epitope from the HCV E2 envelope glycoprotein (residues 412 to 423; epitope I), we performed structure-based design of immunogens to induce antibody responses to this epitope. This resulted in epitope-based immunogens based on a cyclic defensin protein, as well as a bivalent immunogen with two copies of the epitope on the E2 surface. We solved the X-ray structure of a cyclic immunogen in complex with the HCV1 antibody and confirmed preservation of the epitope conformation and the HCV1 interface. Mice vaccinated with our designed immunogens produced robust antibody responses to epitope I, and their serum could neutralize HCV. Notably, the cyclic designs induced greater epitope-specific responses and neutralization than the native peptide epitope. Beyond successfully designing several novel HCV immunogens, this study demonstrates the principle that neutralizing anti-HCV antibodies can be induced by epitope-based, engineered vaccines and provides the basis for further efforts in structure-based design of HCV vaccines. IMPORTANCE Hepatitis C virus is a leading cause of liver disease and liver cancer, with approximately 3% of the world's population infected. To combat this virus, an effective vaccine would have distinct advantages over current therapeutic options, yet experimental vaccines have not been successful to date, due in part to the virus's high sequence variability leading to immune escape. In this study, we rationally designed several vaccine immunogens based on the structure of a conserved epitope that is the target of broadly neutralizing antibodies. In vivo results in mice indicated that these antigens elicited epitope-specific neutralizing antibodies, with various degrees of potency and breadth. These promising results suggest that a rational design approach can be used to generate an effective vaccine for this virus.
Using reported glutathione S-transferase omega 1 (GSTO1- 1) cocrystal structures, we designed and synthesized acrylamide-containing compounds that covalently bind to Cys32 on the catalytic site. Starting from a thiazole derivative 10 (GSTO1-1 IC 50 = 0.6 $μ$M), compound 18 was synthesized and cocrystallized with GSTO1. Modification on the amide moiety of hit compound 10 significantly increased the GSTO1-1 inhibitory potency. We solved the cocrystal structures of new derivatives, 37 and 44, bearing an amide side chain bound to GSTO1. These new structures showed a reorientation of the phenyl thiazole core of inhibitors, 37 and 44, when compared to 18. Furthermore, guided by the cocrystal structure of GSTO1:44, analogue 49 was designed, resulting in the most potent GSTO1-1 inhibitor (IC 50 = 0.22 ± 0.02 nM) known to date. We believe that our data will form the basis for future studies of developing GSTO1-1 as a new drug target for cancer therapy.
The Proton Power Upgrade (PPU) project is underway at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory. The project will double the proton accelerator power from 1.4 MW to 2.8 MW, increase power to the First Target Station (FTS), and enable a future Second Target Station (STS). The power increase partly comes from raising proton energy from 1.0 GeV to 1.3 GeV. The STS will operate at 0.7 MW at 15 Hz when completed. Until then, PPU will provide the capability to operate the FTS at 2.0 MW at 60 Hz. Maximum power at the FTS to date has been 1.4 MW at 60 Hz with 1.0 GeV protons. A new mercury target module design to operate reliably under PPU conditions has been completed after a multi-year effort. The design philosophy and assessment of the structural analysis are described here. This target underwent an unprecedented design and analysis process for SNS using the latest engineering techniques and incorporating years of operating lessons and outcomes from R&D to meet structural design criteria. Finally, it also incorporates high-flow gas injection to further mitigate pulse fatigue stresses as well as cavitation damage to the mercury vessel.
Literature shows there has been extensive research and testing done in the area of wall panels and frangible materials. There is evidence from past research that shows it is possible to vent a structure that has had an accidental internal explosion [1]. The reviewed literature shows that most designs vent the entire wall panel versus a frangible material attached to the wall panel. The frangible material attachment points are important to determine the overall loading of the wall panel structure [2]. The materials used in the reviewed literature were securely attached as well as strong enough to remain intact during the pressure loading to move the entire wall panel. Since the vented wall panel was the weakest part of the overall structure, the other walls of the structure were substantially larger. The structure was usually built from concrete and large amounts of steel with dirt and sand over the top of the structure.The study will be conducted at Sandia National Laboratories located in Albuquerque New Mexico. The skeletal structural design for evaluation is a rectangular frame with a square grid pattern constructed from steel. The skeletal structure has been given to the researcher as a design requirement. The grid pattern will be evaluated strictly on plastic deformation and the loading that is applied from the frangible material. The frangible material tested will either fit into the grid or will be a veneer lightly attached to the structure frame. The frangible material may be required on both sides of the structure to adequately represent the application.
Manipulating matter with a scanning tunneling microscope (STM) enables the creation of atomically defined artificial structures that host designer quantum states. However, the time-consuming nature of the manipulation process, coupled with the sensitivity of the STM tip, constrains the exploration of diverse configurations and limits the size of the designed features. In this study, we present a reinforcement learning (RL)-based framework for creating artificial structures by spatially manipulating carbon monoxide (CO) molecules on a copper substrate by using the STM tip. The automated workflow combines molecule detection and manipulation, employing deep-learning-based object detection to locate CO molecules and linear assignment algorithms to allocate these molecules to designated target sites. We initially perform molecule maneuvering based on randomized parameter sampling for sample bias, tunneling current set point, and manipulation speed. This data set is then structured into an action trajectory used to train an RL agent. The model is subsequently deployed on the STM for real-time fine-tuning of the manipulation parameters during structure construction. Our approach incorporates path-planning protocols coupled with active drift compensation to enable atomically precise fabrication of structures with significantly reduced human input while realizing larger-scale artificial lattices with the desired electronic properties. Furthermore, using our approach, we demonstrate the automated construction of an extended artificial graphene lattice and confirm the existence of a characteristic Dirac point in its electronic structure. Further challenges regarding the RL-based structural assembly scalability are discussed.
Myeloid cell leukemia 1 (Mcl-1), an antiapoptotic member of the Bcl-2 family of proteins, has emerged as an attractive target for cancer therapy. Mcl-1 upregulation is often found in many human cancers and is associated with high tumor grade, poor survival, and resistance to chemotherapy. Here, we describe a series of potent and selective tricyclic indole diazepinone Mcl-1 inhibitors that were discovered and further optimized using structure-based design. These compounds exhibit picomolar binding affinity and mechanism-based cellular efficacy, including growth inhibition and caspase induction in Mcl-1-sensitive cells. Furthermore, they represent useful compounds to study the implication of Mcl-1 inhibition in cancer and serve as potentially useful starting points toward the discovery of anti-Mcl-1 therapeutics.
Cellular infection by HIV-1 is initiated with a binding event between the viral envelope glycoprotein gp120 and the cellular receptor protein CD4. The CD4-gp120 interface is dominated by two hotspots: a hydrophobic gp120 cavity capped by Phe43{sub CD4} and an electrostatic interaction between residues Arg59{sub CD4} and Asp368{sub gp120}. The CD4 mimetic small-molecule NBD-556 (1) binds within the gp120 cavity; however, 1 and related congeners demonstrate limited viral neutralization breadth. Herein, we report the design, synthesis, characterization, and X-ray structures of gp120 in complex with small molecules that simultaneously engage both binding hotspots. The compounds specifically inhibit viral infection of 42 tier 2 clades B and C viruses and are shown to be antagonists of entry into CD4-negative cells. Dual hotspot design thus provides both a means to enhance neutralization potency of HIV-1 entry inhibitors and a novel structural paradigm for inhibiting the CD4-gp120 protein-protein interaction.
Bcl-2 and Bcl-xL are key apoptosis regulators and attractive cancer therapeutic targets. We have designed and optimized a class of small-molecule inhibitors of Bcl-2 and Bcl-xL containing a 4,5-diphenyl-1H-pyrrole-3-carboxylic acid core structure. A 1.4 {angstrom} resolution crystal structure of a lead compound, 12, complexed with Bcl-xL has provided a basis for our optimization. The most potent compounds, 14 and 15, bind to Bcl-2 and Bcl-xL with subnanomolar K{sub i} values and are potent antagonists of Bcl-2 and Bcl-xL in functional assays. Compounds 14 and 15 inhibit cell growth with low nanomolar IC{sub 50} values in multiple small-cell lung cancer cell lines and induce robust apoptosis in cancer cells at concentrations as low as 10 nM. Compound 14 also achieves strong antitumor activity in an animal model of human cancer.
Synthetic polymeric nanofiltration membrane processes offer an alternate low-energy option to energy-intensive distillation to fractionate similar size organic solvents for chemical, petroleum, food and biotechnology industries. Here, in this study, we synthesize and test a new class of structure-by-design hydrophilic polymeric brush membranes, that address the limitations of commercial polymer membranes, are tunable and exhibit commercially relevant filtration performance. Because these brush membranes are grafted by Single Electron Transfer-Living Radical Polymerization (SET-LRP) and replace statistically random phase inversion or interfacial polymerization used for synthesizing commercial polymer membranes, their porous structure can be remodeled by varying their morphology and chemistry. We graft hydroxyethyl methacrylate (HEMA) brush structures with short and long crosslinkers, demonstrate two competing phenomena - pore stiffening and opening - and obtain high selectivity at reasonable permeability for commercially relevant methanol/toluene separation. This new class of stable, tunable, and scalable membranes offers exciting opportunities to reduce energy for separation of organic solvents.