Binding and sensing diverse small molecules using shape-complementary pseudocycles.

We describe an approach for designing high-affinity small molecule-binding proteins poised for downstream sensing. We use deep learning-generated pseudocycles with repeating structural units surrounding central binding pockets with widely varying shapes that depend on the geometry and number of the repeat units. We dock small molecules of interest into the most shape complementary of these pseudocycles, design the interaction surfaces for high binding affinity, and experimentally screen to identify designs with the highest affinity. We obtain binders to four diverse molecules, including the polar and flexible methotrexate and thyroxine. Taking advantage of the modular repeat structure and central binding pockets, we construct chemically induced dimerization systems and low-noise nanopore sensors by splitting designs into domains that reassemble upon ligand addition.

Expansive discovery of chemically diverse structured macrocyclic oligoamides.

Small macrocycles with four or fewer amino acids are among the most potent natural products known, but there is currently no way to systematically generate such compounds. We describe a computational method for identifying ordered macrocycles composed of alpha, beta, gamma, and 17 other amino acid backbone chemistries, which we used to predict 14.9 million closed cycles composed of >42,000 monomer combinations. We chemically synthesized 18 macrocycles predicted to adopt single low-energy states and determined their x-ray or nuclear magnetic resonance structures; 15 of these were very close to the design models. We illustrate the therapeutic potential of these macrocycle designs by developing selective inhibitors of three protein targets of current interest. By opening up a vast space of readily synthesizable drug-like macrocycles, our results should considerably enhance structure-based drug design.

De novo design of diverse small molecule binders and sensors using Shape Complementary Pseudocycles.

A general method for designing proteins to bind and sense any small molecule of interest would be widely useful. Due to the small number of atoms to interact with, binding to small molecules with high affinity requires highly shape complementary pockets, and transducing binding events into signals is challenging. Here we describe an integrated deep learning and energy based approach for designing high shape complementarity binders to small molecules that are poised for downstream sensing applications. We employ deep learning generated psuedocycles with repeating structural units surrounding central pockets; depending on the geometry of the structural unit and repeat number, these pockets span wide ranges of sizes and shapes. For a small molecule target of interest, we extensively sample high shape complementarity pseudocycles to generate large numbers of customized potential binding pockets; the ligand binding poses and the interacting interfaces are then optimized for high affinity binding. We computationally design binders to four diverse molecules, including for the first time polar flexible molecules such as methotrexate and thyroxine, which are expressed at high levels and have nanomolar affinities straight out of the computer. Co-crystal structures are nearly identical to the design models. Taking advantage of the modular repeating structure of pseudocycles and central location of the binding pockets, we constructed low noise nanopore sensors and chemically induced dimerization systems by splitting the binders into domains which assemble into the original pseudocycle pocket upon target molecule addition.

Exploration of Structured Symmetric Cyclic Peptides as Ligands for Metal-Organic Frameworks.

Despite remarkable advances in the assembly of highly structured coordination polymers and metal-organic frameworks, the rational design of such materials using more conformationally flexible organic ligands such as peptides remains challenging. In an effort to make the design of such materials fully programmable, we first developed a computational design method for generating metal-mediated 3D frameworks using rigid and symmetric peptide macrocycles with metal-coordinating sidechains. We solved the structures of six crystalline networks involving conformationally constrained 6 to 12 residue cyclic peptides with C2, C3, and S2 internal symmetry and three different types of metals (Zn2+, Co2+, or Cu2+) by single-crystal X-ray diffraction, which reveals how the peptide sequences, backbone symmetries, and metal coordination preferences drive the assembly of the resulting structures. In contrast to smaller ligands, these peptides associate through peptide-peptide interactions without full coordination of the metals, contrary to one of the assumptions underlying our computational design method. The cyclic peptides are the largest peptidic ligands reported to form crystalline coordination polymers with transition metals to date, and while more work is required to develop methods for fully programming their crystal structures, the combination of high chemical diversity with synthetic accessibility makes them attractive building blocks for engineering a broader set of new crystalline materials for use in applications such as sensing, asymmetric catalysis, and chiral separation.

Generation of Potent and Stable GLP-1 Analogues Via "Serine Ligation".

Peptide and protein bioconjugation technologies have revolutionized our ability to site-specifically or chemoselectively install a variety of functional groups for applications in chemical biology and medicine, including the enhancement of bioavailability. Here, we introduce a site-specific bioconjugation strategy inspired by chemical ligation at serine that relies on a noncanonical amino acid containing a 1-amino-2-hydroxy functional group and a salicylaldehyde ester. More specifically, we harness this technology to generate analogues of glucagon-like peptide-1 that resemble Semaglutide, a long-lasting blockbuster drug currently used in the clinic to regulate glucose levels in the blood. We identify peptides that are more potent than unmodified peptide and equipotent to Semaglutide in a cell-based activation assay, improve the stability in human serum, and increase glucose disposal efficiency in vivo. This approach demonstrates the potential of "serine ligation" for various applications in chemical biology, with a particular focus on generating stabilized peptide therapeutics.

IMPDH1 retinal variants control filament architecture to tune allosteric regulation.

Inosine-5'-monophosphate dehydrogenase (IMPDH), a key regulatory enzyme in purine nucleotide biosynthesis, dynamically assembles filaments in response to changes in metabolic demand. Humans have two isoforms: IMPDH2 filaments reduce sensitivity to feedback inhibition, while IMPDH1 assembly remains uncharacterized. IMPDH1 plays a unique role in retinal metabolism, and point mutants cause blindness. Here, in a series of cryogenic-electron microscopy structures we show that human IMPDH1 assembles polymorphic filaments with different assembly interfaces in extended and compressed states. Retina-specific splice variants introduce structural elements that reduce sensitivity to GTP inhibition, including stabilization of the extended filament form. Finally, we show that IMPDH1 disease mutations fall into two classes: one disrupts GTP regulation and the other has no effect on GTP regulation or filament assembly. These findings provide a foundation for understanding the role of IMPDH1 in retinal function and disease and demonstrate the diverse mechanisms by which metabolic enzyme filaments are allosterically regulated.

Evaluation of VGF peptides as potential anti-obesity candidates in pre-clinical animal models.

VGF is a peptide precursor expressed in neuroendocrine cells that is suggested to play a role in the regulation of energy homeostasis. VGF is proteolytically cleaved to yield multiple bioactive peptides. However, the specific actions of VGF-derived peptides on energy homeostasis remain unclear. The aim of the present work was to investigate the role of VGF-derived peptides in energy homeostasis and explore the pharmacological actions of VGF-derived peptides on body weight in preclinical animal models. VGF-derived peptides (NERP-1, NERP-2, PGH-NH2, PGH-OH, NERP-4, TLQP-21, TLQP-30, TLQP-62, HHPD-41, AQEE-30, and LQEQ-19) were synthesized and screened for their ability to affect neuronal activity in vitro on hypothalamic brain slices and modulate food intake and energy expenditure after acute central administration in vivo. In addition, the effects of NERP-1, NERP-2, PGH-NH2, TLQP-21, TLQP-62, and HHPD-41 on energy homeostasis were studied after chronic central infusion. NERP-1, PGH-NH2, HHPD-41, and TLQP-62 increased the functional activity of hypothalamic neuronal networks. However, none of the peptides altered energy homeostasis after either acute or chronic ICV administration. The present data do not support the potential use of the tested VGF-derived peptides as novel anti-obesity drug candidates.