Computationally designed high specificity inhibitors delineate the roles of BCL2 family proteins in cancer

Accurate de novo design of heterochiral protein-protein interactions

Abiotic D-proteins that selectively bind to natural L-proteins have gained significant biotechnological interest. However, the underlying structural principles governing such heterochiral protein-protein interactions remain largely unknown. In this study, we present the de novo design of D-proteins consisting of 50-65 residues, aiming to target specific surface regions of L-proteins or L-peptides. Our designer D-protein binders exhibit nanomolar affinity toward an artificial L-peptide, as well as two naturally occurring proteins of therapeutic significance: the D5 domain of human tropomyosin receptor kinase A (TrkA) and human interleukin-6 (IL-6). Notably, these D-protein binders demonstrate high enantiomeric specificity and target specificity. In cell-based experiments, designer D-protein binders effectively inhibited the downstream signaling of TrkA and IL-6 with high potency. Moreover, these binders exhibited remarkable thermal stability and resistance to protease degradation. Crystal structure of the designed heterochiral D-protein-L-peptide complex, obtained at a resolution of 2.0 Å, closely resembled the design model, indicating that the computational method employed is highly accurate. Furthermore, the crystal structure provides valuable information regarding the interactions between helical L-peptides and D-proteins, particularly elucidating a novel mode of heterochiral helix-helix interactions. Leveraging the design of D-proteins specifically targeting L-peptides or L-proteins opens up avenues for systematic exploration of the mirror-image protein universe, paving the way for a diverse range of applications.

Soybean β-Conglycinin and Cowpea β-Vignin Peptides Inhibit Breast and Prostate Cancer Cell Growth: An In Silico and In Vitro Approach

B-cell lymphoma 2 protein (Bcl-2) is an important regulator of cell apoptosis. Inhibitors that mirror the structural domain 3 (BH3) of Bcl-2 can activate apoptosis in cancer cells, making them a promising target for anticancer treatment. Hence, the present study aimed to investigate potential BH3-mimetic peptides from two vicilin-derived legume proteins from soybean and cowpea bean. The proteins were isolated and sequentially hydrolyzed with pepsin/pancreatin. Peptides < 3 kDa from vicilin-derived proteins from soybean and cowpea beans experimentally inhibited the growth of cultivated breast and prostate cancer cells. In silico analysis allowed the identification of six potential candidates, all predicted to be able to interact with the BH3 domain. The VIPAAY peptide from the soybean β-conglycinin β subunit showed the highest potential to interact with Bcl-2, comparable to Venetoclax, a well-known anticancer drug. Further experiments are needed to confirm this study's findings.

Massively parallel measurement of protein-protein interactions by sequencing using MP3-seq

Protein-protein interactions (PPIs) regulate many cellular processes and engineered PPIs have cell and gene therapy applications. Here, we introduce massively parallel PPI measurement by sequencing (MP3-seq), an easy-to-use and highly scalable yeast two-hybrid approach for measuring PPIs. In MP3-seq, DNA barcodes are associated with specific protein pairs and barcode enrichment can be read by sequencing to provide a direct measure of interaction strength. We show that MP3-seq is highly quantitative and scales to over 100,000 interactions. We apply MP3-seq to characterize interactions between families of rationally designed heterodimers and to investigate elements conferring specificity to coiled-coil interactions. Lastly, we predict coiled heterodimer structures using AlphaFold-Multimer (AF-M) and train linear models on physics-based energy terms to predict MP3-seq values. We find that AF-M-based models could be valuable for prescreening interactions but experimentally measuring interactions remains necessary to rank their strengths quantitatively.

De novo design of mini-protein binders broadly neutralizing Clostridioides difficile toxin B variants

Clostridioides difficile toxin B (TcdB) is the key virulence factor accounting for C. difficile infection-associated symptoms. Effectively neutralizing different TcdB variants with a universal solution poses a significant challenge. Here we present the de novo design and characterization of pan-specific mini-protein binders against major TcdB subtypes. Our design successfully binds to the first receptor binding interface (RBI-1) of the varied TcdB subtypes, exhibiting affinities ranging from 20 pM to 10 nM. The cryo-electron microscopy (cryo-EM) structures of the mini protein binder in complex with TcdB1 and TcdB4 are consistent with the computational design models. The engineered and evolved variants of the mini-protein binder and chondroitin sulfate proteoglycan 4 (CSPG4), another natural receptor that binds to the second RBI (RBI-2) of TcdB, better neutralize major TcdB variants both in cells and in vivo, as demonstrated by the colon-loop assay using female mice. Our findings provide valuable starting points for the development of therapeutics targeting C. difficile infections (CDI).

Preclinical proof of principle for orally delivered Th17 antagonist miniproteins

Interleukin (IL)-23 and IL-17 are well-validated therapeutic targets in autoinflammatory diseases. Antibodies targeting IL-23 and IL-17 have shown clinical efficacy but are limited by high costs, safety risks, lack of sustained efficacy, and poor patient convenience as they require parenteral administration. Here, we present designed miniproteins inhibiting IL-23R and IL-17 with antibody-like, low picomolar affinities at a fraction of the molecular size. The minibinders potently block cell signaling in vitro and are extremely stable, enabling oral administration and low-cost manufacturing. The orally administered IL-23R minibinder shows efficacy better than a clinical anti-IL-23 antibody in mouse colitis and has a favorable pharmacokinetics (PK) and biodistribution profile in rats. This work demonstrates that orally administered de novo-designed minibinders can reach a therapeutic target past the gut epithelial barrier. With high potency, gut stability, and straightforward manufacturability, de novo-designed minibinders are a promising modality for oral biologics.

Discovery of a Covalent Inhibitor That Overcame Resistance to Venetoclax in AML Cells Overexpressing BFL-1

Clinical and biological studies have shown that overexpression of BFL-1 is one contributing factor to venetoclax resistance. The resistance might be overcome by a potent BFL-1 inhibitor, but such an inhibitor is rare. In this study, we show that 56, featuring an acrylamide moiety, inhibited the BFL-1/BID interaction with a Ki value of 105 nM. More interestingly, 56 formed an irreversible conjugation adduct at the C55 residue of BFL-1. 56 was a selective BFL-1 inhibitor, and its MCL-1 binding affinity was 10-fold weaker, while it did not bind BCL-2 and BCL-xL. Mechanistic studies showed that 56 overcame venetoclax resistance in isogenic AML cell lines MOLM-13-OE and MV4-11-OE, which both overexpressed BFL-1. More importantly, 56 and venetoclax combination promoted stronger apoptosis induction than either single agent. Collectively, our data show that 56 overcame resistance to venetoclax in AML cells overexpressing BFL-1. These attributes make 56 a promising candidate for future optimization.

Discovery and optimization of (2-naphthylthio)acetic acid derivative as selective Bfl-1 inhibitor

Bcl-2 anti-apoptotic protein family suppresses cell death by deploying a surface groove to capture the critical BH3 α-helix of pro-apoptotic members. Bfl-1 is a relatively understudied member of this family, though it has been implicated in the pathogenesis and chemoresistance of a variety of human cancers. Reported small molecular Bfl-1 inhibitors encountered the issue of either lack in potency or poor selectivity against its most homologous member Mcl-1. In order to tackle this issue, compound library was screened and a hit compound UMI-77 was identified. We modified its chemical structure to remove the characteristic of PAINS (pan-assay interference compounds), demonstrated the real binding affinity and achieved selectivity against Mcl-1 under the guidance of computational modeling. After optimization 15 was obtained as leading compound to block Bfl-1/BIM interaction in vitro with more than 10-fold selectivity over Mcl-1. We believe 15 is of great value for the exploration of Bfl-1 biological function and its potential as therapeutic target.

Ergodicity Breaking and Self-Destruction of Cancer Cells by Induced Genome Chaos

During the progression of some cancer cells, the degree of genome instability may increase, leading to genome chaos in populations of malignant cells. While normally chaos is associated with ergodicity, i.e., the state when the time averages of relevant parameters are equal to their phase space averages, the situation with cancer propagation is more complex. Chromothripsis, a catastrophic massive genomic rearrangement, is observed in many types of cancer, leading to increased mutation rates. We present an entropic model of genome chaos and ergodicity and experimental evidence that increasing the degree of chaos beyond the non-ergodic threshold may lead to the self-destruction of some tumor cells. We study time and population averages of chromothripsis frequency in cloned rhabdomyosarcomas from rat stem cells. Clones with frequency above 10% result in cell apoptosis, possibly due to mutations in the BCL2 gene. Potentially, this can be used for suppressing cancer cells by shifting them into a non-ergodic proliferation regime.

Anti-proliferative activity, molecular genetics, docking analysis, and computational calculations of uracil cellulosic aldehyde derivatives

In this study, the oxidation of microcrystalline cellulose using NaIO4 to yield the corresponding cellulose aldehyde utilized microwave irradiation as a green tool, the obtained cellulosic aldehyde was confirmed through spectral analysis and it has an active site to react with the synthesized uracil acetamide to afford the corresponding arylidene cellulosic MDAU(4), the latter compound which can easily due to presence of active CH=group behind a cyano group react with nitrogen nucleophile's and cyclized with hydrazine hydrate to give pyrazole cellulosic MDPA(5). The spectral analysis of the obtained cellulosic derivatives was confirmed with FT-IR, NMR, and SEM. Additionally, a neutral red uptake analysis has been used to investigate the cytotoxic activity of the cellulosic compounds MDAC(2), MDAU(4), and MDAP(5) against the cancer cells A549 and Caco2. After 48 h, Compound MDAU(4) had a stronger inhibitory effect on the growth of A549 and Caco2, compared to standard values. Then, using QRT-PCR, the appearance sites of the genes -Catenin, c-Myc, Cyclin D1, and MMP7 in A549 cells were examined. By reducing the expression levels of the Wnt signaling cascade genes -Catenin, c-Myc, Cyclin D1, and MMP7 when administered to A549 cells, compound MDAU(4) was shown in this investigation to be a viable candidate compared to lung cancer. Additionally, docking simulation was used to explore the uracil cellulosic heterocycles attached to different proteins, and computational investigations of these compounds looked at how well their physical characteristics matched the outcomes of their experiments.

Massively parallel protein-protein interaction measurement by sequencing (MP3-seq) enables rapid screening of protein heterodimers

Protein-protein interactions (PPIs) regulate many cellular processes, and engineered PPIs have cell and gene therapy applications. Here we introduce massively parallel protein-protein interaction measurement by sequencing (MP3-seq), an easy-to-use and highly scalable yeast-two-hybrid approach for measuring PPIs. In MP3-seq, DNA barcodes are associated with specific protein pairs, and barcode enrichment can be read by sequencing to provide a direct measure of interaction strength. We show that MP3-seq is highly quantitative and scales to over 100,000 interactions. We apply MP3-seq to characterize interactions between families of rationally designed heterodimers and to investigate elements conferring specificity to coiled-coil interactions. Finally, we predict coiled heterodimer structures using AlphaFold-Multimer (AF-M) and train linear models on physics simulation energy terms to predict MP3-seq values. We find that AF-M and AF-M complex prediction-based models could be valuable for pre-screening interactions, but that measuring interactions experimentally remains necessary to rank their strengths quantitatively.

In silico investigation of nonsynonymous single nucleotide polymorphisms in BCL2 apoptosis regulator gene to design novel protein-based drugs against cancer

BCL2 apoptosis regulator gene encodes Bcl-2 pro-survival protein, which plays an important role to evade apoptosis in various cancers. Moreover, single nucleotide polymorphisms (SNPs) in the BCL2 gene can be nonsynonymous (nsSNPs), which might affect the protein stability and probably its function. Therefore, we implement cutting-edge computational techniques based on the Spherical Polar Fourier and Monte-Carlo algorithms to investigate the impact of these SNPs on the B cell lymphoma-2 (Bcl-2) stability and therapeutic potential of protein-based molecules to inhibit this protein. As a result, we identified two nsSNPs (Q118R and R129C) to be deleterious and highly conserved, having a negative effect on protein stability. Additionally, molecular docking and molecular dynamics simulations confirmed the decreased binding affinity of mutated Bcl-2 variants to bind three-helix bundle protein inhibitor as these mutations occurred in the protein-protein binding site. Overall, this computational approach investigating nsSNPs provides a useful basis for designing novel molecules to inhibit Bcl-2 pro-survival pathway in malignant cells.

A dataset comprised of binding interactions for 104,972 antibodies against a SARS-CoV-2 peptide

The dataset presented here contains quantitative binding scores of scFv-format antibodies against a SARS-CoV-2 target peptide collected via an AlphaSeq assay that can be used in the development and benchmarking of machine learning models. Starting from three seed sequences identified from a phage display campaign using a human naïve library, four sets of 29,900 antibodies were designed in silico by creating all k = 1 mutations and random k = 2 and k = 3 mutations throughout the complementary-determining regions (CDRs). Of the 119,600 designs, 104,972 were successfully built in to the AlphaSeq library and target binding was subsequently measured with 71,384 designs resulting in a predicted affinity value for at least one of the triplicate measurements. Data include antibodies with predicted affinity measurements ranging from 37 pM to 22 mM. To our knowledge, this dataset is the largest, publicly available dataset that contains antibody sequences, antigen sequence and quantitative measurements of binding scores and provides an opportunity to serve as a benchmark to evaluate antibody-specific representation models for machine learning.

Measurement(s)	Antibody Binding
Technology Type(s)	AlphaSeq
Factor Type(s)	Antibody sequence
Sample Characteristic - Organism	Homo sapiens

Computational Tools and Strategies to Develop Peptide-Based Inhibitors of Protein-Protein Interactions

Protein-protein interactions play crucial and subtle roles in many biological processes and modifications of their fine mechanisms generally result in severe diseases. Peptide derivatives are very promising therapeutic agents for modulating protein-protein associations with sizes and specificities between those of small compounds and antibodies. For the same reasons, rational design of peptide-based inhibitors naturally borrows and combines computational methods from both protein-ligand and protein-protein research fields. In this chapter, we aim to provide an overview of computational tools and approaches used for identifying and optimizing peptides that target protein-protein interfaces with high affinity and specificity. We hope that this review will help to implement appropriate in silico strategies for peptide-based drug design that builds on available information for the systems of interest.

BCL-XL inhibition induces an FGFR4-mediated rescue response in colorectal cancer

The heterogeneous therapy response observed in colorectal cancer is in part due to cancer stem cells (CSCs) that resist chemotherapeutic insults. The anti-apoptotic protein BCL-XL plays a critical role in protecting CSCs from cell death, where its inhibition with high doses of BH3 mimetics can induce apoptosis. Here, we screen a compound library for synergy with low-dose BCL-XL inhibitor A-1155463 to identify pathways that regulate sensitivity to BCL-XL inhibition and reveal that fibroblast growth factor receptor (FGFR)4 inhibition effectively sensitizes to A-1155463 both in vitro and in vivo. Mechanistically, we identify a rescue response that is activated upon BCL-XL inhibition and leads to rapid FGF2 secretion and subsequent FGFR4-mediated post-translational stabilization of MCL-1. FGFR4 inhibition prevents MCL-1 upregulation and thereby sensitizes CSCs to BCL-XL inhibition. Altogether, our findings suggest a cell transferable induction of a FGF2/FGFR4 rescue response in CRC that is induced upon BCL-XL inhibition and leads to MCL-1 upregulation.

Computational design of an apoptogenic protein that binds BCL-xL and MCL-1 simultaneously and potently

One of the hallmarks of cancer cells is their ability to evade apoptosis, which confers survival advantages and resistance to anti-cancer drugs. Cancers often exhibit overexpression of anti-apoptotic BCL-2 proteins, the loss of which triggers apoptosis. In particular, the inhibition of both BCL-xL and MCL-1, but neither one individually, synergistically enhances apoptotic cell death. Here, we report computational design to produce a protein that inhibits both BCL-xL and MCL-1 simultaneously. To a reported artificial three-helix bundle whose second helix was designed to bind MCL-1, we added a fourth helix and designed it to bind BCL-xL. After structural validation of the design and further structure-based sequence design, we produced a dual-binding protein that interacts with both BCL-xL and MCL-1 with apparent dissociation constants of 820 pM and 196 pM, respectively. Expression of this dual binder in a subset of cancer cells induced apoptotic cell death at levels significantly higher than those induced by the pro-apoptotic BIM protein. With a genetic fusion of a mitochondria-targeting sequence or the BH3 sequence of BIM, the activity of the dual binder was enhanced even further. These data suggest that targeted delivery of this dual binder alone or as a part of a modular protein to cancers in the form of protein, mRNA, or DNA may be an effective way to induce cancer cell apoptosis.

Designer proteins that competitively inhibit Gαq by targeting its effector site

During signal transduction, the G protein, Gαq, binds and activates phospholipase C-β isozymes. Several diseases have been shown to manifest upon constitutively activating mutation of Gαq, such as uveal melanoma. Therefore, methods are needed to directly inhibit Gαq. Previously, we demonstrated that a peptide derived from a helix-turn-helix (HTH) region of PLC-β3 (residues 852-878) binds Gαq with low micromolar affinity and inhibits Gαq by competing with full-length PLC-β isozymes for binding. Since the HTH peptide is unstructured in the absence of Gαq, we hypothesized that embedding the HTH in a folded protein might stabilize the binding-competent conformation and further improve the potency of inhibition. Using the molecular modeling software Rosetta, we searched the Protein Data Bank for proteins with similar HTH structures near their surface. The candidate proteins were computationally docked against Gαq, and their surfaces were redesigned to stabilize this interaction. We then used yeast surface display to affinity mature the designs. The most potent design bound Gαq/i with high affinity in vitro (KD = 18 nM) and inhibited activation of PLC-β isozymes in HEK293 cells. We anticipate that our genetically encoded inhibitor will help interrogate the role of Gαq in healthy and disease model systems. Our work demonstrates that grafting interaction motifs into folded proteins is a powerful approach for generating inhibitors of protein-protein interactions.

Protein Assembly by Design

Proteins are nature's primary building blocks for the construction of sophisticated molecular machines and dynamic materials, ranging from protein complexes such as photosystem II and nitrogenase that drive biogeochemical cycles to cytoskeletal assemblies and muscle fibers for motion. Such natural systems have inspired extensive efforts in the rational design of artificial protein assemblies in the last two decades. As molecular building blocks, proteins are highly complex, in terms of both their three-dimensional structures and chemical compositions. To enable control over the self-assembly of such complex molecules, scientists have devised many creative strategies by combining tools and principles of experimental and computational biophysics, supramolecular chemistry, inorganic chemistry, materials science, and polymer chemistry, among others. Owing to these innovative strategies, what started as a purely structure-building exercise two decades ago has, in short order, led to artificial protein assemblies with unprecedented structures and functions and protein-based materials with unusual properties. Our goal in this review is to give an overview of this exciting and highly interdisciplinary area of research, first outlining the design strategies and tools that have been devised for controlling protein self-assembly, then describing the diverse structures of artificial protein assemblies, and finally highlighting the emergent properties and functions of these assemblies.

Towards optimizing peptide-based inhibitors of protein-protein interactions: predictive saturation variation scanning (PreSaVS)

A simple-to-implement and experimentally validated computational workflow for sequence modification of peptide inhibitors of protein–protein interactions (PPIs) is described.

An experimentally validated approach for in silico modification of peptide based protein–protein interaction inhibitors is described.

The fellowship of the RING: BRCA1, its partner BARD1 and their liaison in DNA repair and cancer

The breast cancer type 1 susceptibility protein (BRCA1) and its partner - the BRCA1-associated RING domain protein 1 (BARD1) - are key players in a plethora of fundamental biological functions including, among others, DNA repair, replication fork protection, cell cycle progression, telomere maintenance, chromatin remodeling, apoptosis and tumor suppression. However, mutations in their encoding genes transform them into dangerous threats, and substantially increase the risk of developing cancer and other malignancies during the lifetime of the affected individuals. Understanding how BRCA1 and BARD1 perform their biological activities therefore not only provides a powerful mean to prevent such fatal occurrences but can also pave the way to the development of new targeted therapeutics. Thus, through this review work we aim at presenting the major efforts focused on the functional characterization and structural insights of BRCA1 and BARD1, per se and in combination with all their principal mediators and regulators, and on the multifaceted roles these proteins play in the maintenance of human genome integrity.

Computationally Designed ACE2 Decoy Receptor Binds SARS-CoV-2 Spike (S) Protein with Tight Nanomolar Affinity

Even with the availability of vaccines, therapeutic options for COVID-19 still remain highly desirable, especially in hospitalized patients with moderate or severe disease. Soluble ACE2 (sACE2) is a promising therapeutic candidate that neutralizes SARS CoV-2 infection by acting as a decoy. Using computational mutagenesis, we designed a number of sACE2 derivatives carrying three to four mutations. The top-predicted sACE2 decoy based on the in silico mutagenesis scan was subjected to molecular dynamics and free-energy calculations for further validation. After illuminating the mechanism of increased binding for our designed sACE2 derivative, the design was verified experimentally by flow cytometry and BLI-binding experiments. The computationally designed sACE2 decoy (ACE2-FFWF) bound the receptor-binding domain of SARS-CoV-2 tightly with low nanomolar affinity and ninefold affinity enhancement over the wild type. Furthermore, cell surface expression was slightly greater than wild-type ACE2, suggesting that the design is well-folded and stable. Having an arsenal of high-affinity sACE2 derivatives will help to buffer against the emergence of SARS CoV-2 variants. Here, we show that computational methods have become sufficiently accurate for the design of therapeutics for current and future viral pandemics.

Virotherapy in Germany-Recent Activities in Virus Engineering, Preclinical Development, and Clinical Studies

Virotherapy research involves the development, exploration, and application of oncolytic viruses that combine direct killing of cancer cells by viral infection, replication, and spread (oncolysis) with indirect killing by induction of anti-tumor immune responses. Oncolytic viruses can also be engineered to genetically deliver therapeutic proteins for direct or indirect cancer cell killing. In this review—as part of the special edition on “State-of-the-Art Viral Vector Gene Therapy in Germany”—the German community of virotherapists provides an overview of their recent research activities that cover endeavors from screening and engineering viruses as oncolytic cancer therapeutics to their clinical translation in investigator-initiated and sponsored multi-center trials. Preclinical research explores multiple viral platforms, including new isolates, serotypes, or fitness mutants, and pursues unique approaches to engineer them towards increased safety, shielded or targeted delivery, selective or enhanced replication, improved immune activation, delivery of therapeutic proteins or RNA, and redirecting antiviral immunity for cancer cell killing. Moreover, several oncolytic virus-based combination therapies are under investigation. Clinical trials in Germany explore the safety and potency of virotherapeutics based on parvo-, vaccinia, herpes, measles, reo-, adeno-, vesicular stomatitis, and coxsackie viruses, including viruses encoding therapeutic proteins or combinations with immune checkpoint inhibitors. These research advances represent exciting vantage points for future endeavors of the German virotherapy community collectively aimed at the implementation of effective virotherapeutics in clinical oncology.

Optimization of Benzothiazole and Thiazole Hydrazones as Inhibitors of Schistosome BCL-2

Limited therapeutic options are available for the treatment of human schistosomiasis caused by the parasitic Schistosoma flatworm. The B cell lymphoma-2 (BCL-2)-regulated apoptotic cell death pathway in schistosomes was recently characterized and shown to share similarities with the intrinsic apoptosis pathway in humans. Here, we exploit structural differences in the human and schistosome BCL-2 (sBCL-2) pro-survival proteins toward a novel treatment strategy for schistosomiasis. The benzothiazole hydrazone scaffold previously employed to target human BCL-XL was repurposed as a starting point to target sBCL-2. We utilized X-ray structural data to inform optimization and then applied a scaffold-hop strategy to identify the 5-carboxamide thiazole hydrazone scaffold (43) with potent sBCL-2 activity (IC₅₀ 30 nM). Human BCL-XL potency (IC₅₀ 13 nM) was inadvertently preserved during the optimization process. The lead analogues from this study exhibit on-target activity in model fibroblast cell lines dependent on either sBCL-2 or human BCL-XL for survival. Further optimization of the thiazole hydrazone class is required to exhibit activity in schistosomes and enhance the potential of this strategy for treating schistosomiasis.

Transferrin receptor targeting by de novo sheet extension

The de novo design of polar protein-protein interactions is challenging because of the thermodynamic cost of stripping water away from the polar groups. Here, we describe a general approach for designing proteins which complement exposed polar backbone groups at the edge of beta sheets with geometrically matched beta strands. We used this approach to computationally design small proteins that bind to an exposed beta sheet on the human transferrin receptor (hTfR), which shuttles interacting proteins across the blood-brain barrier (BBB), opening up avenues for drug delivery into the brain. We describe a design which binds hTfR with a 20 nM Kd, is hyperstable, and crosses an in vitro microfluidic organ-on-a-chip model of the human BBB. Our design approach provides a general strategy for creating binders to protein targets with exposed surface beta edge strands.

Bottom-up de novo design of functional proteins with complex structural features

De novo protein design has enabled the creation of new protein structures. However, the design of functional proteins has proved challenging, in part due to the difficulty of transplanting structurally complex functional sites to available protein structures. Here, we used a bottom-up approach to build de novo proteins tailored to accommodate structurally complex functional motifs. We applied the bottom-up strategy to successfully design five folds for four distinct binding motifs, including a bifunctionalized protein with two motifs. Crystal structures confirmed the atomic-level accuracy of the computational designs. These de novo proteins were functional as components of biosensors to monitor antibody responses and as orthogonal ligands to modulate synthetic signaling receptors in engineered mammalian cells. Our work demonstrates the potential of bottom-up approaches to accommodate complex structural motifs, which will be essential to endow de novo proteins with elaborate biochemical functions, such as molecular recognition or catalysis.

Multimeric antibodies from antigen-specific human IgM+ memory B cells restrict Plasmodium parasites

Multimeric immunoglobulin-like molecules arose early in vertebrate evolution, yet the unique contributions of multimeric IgM antibodies to infection control are not well understood. This is partially due to the difficulty of distinguishing low-affinity IgM, secreted rapidly by plasmablasts, from high-affinity antibodies derived from later-arising memory cells. We developed a pipeline to express B cell receptors (BCRs) from Plasmodium falciparum–specific IgM⁺ and IgG⁺ human memory B cells (MBCs) as both IgM and IgG molecules. BCRs from both subsets were somatically hypermutated and exhibited comparable monomeric affinity. Crystallization of one IgM⁺ MBC-derived antibody complexed with antigen defined a linear epitope within a conserved Plasmodium protein. In its physiological multimeric state, this antibody displayed exponentially higher antigen binding than a clonally identical IgG monomer, and more effectively inhibited P. falciparum invasion. Forced multimerization of this IgG significantly improved both antigen binding and parasite restriction, underscoring how avidity can alter antibody function. This work demonstrates the potential of high-avidity IgM in both therapeutics and vaccines.

De novo design of modular and tunable protein biosensors

Naturally occurring protein switches have been repurposed for the development of biosensors and reporters for cellular and clinical applications¹. However, the number of such switches is limited, and reengineering them is challenging. Here we show that a general class of protein-based biosensors can be created by inverting the flow of information through de novo designed protein switches in which the binding of a peptide key triggers biological outputs of interest². The designed sensors are modular molecular devices with a closed dark state and an open luminescent state; analyte binding drives the switch from the closed to the open state. Because the sensor is based on the thermodynamic coupling of analyte binding to sensor activation, only one target binding domain is required, which simplifies sensor design and allows direct readout in solution. We create biosensors that can sensitively detect the anti-apoptosis protein BCL-2, the IgG1 Fc domain, the HER2 receptor, and Botulinum neurotoxin B, as well as biosensors for cardiac troponin I and an anti-hepatitis B virus antibody with the high sensitivity required to detect these molecules clinically. Given the need for diagnostic tools to track the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)³, we used the approach to design sensors for the SARS-CoV-2 spike protein and antibodies against the membrane and nucleocapsid proteins. The former, which incorporates a de novo designed spike receptor binding domain (RBD) binder⁴, has a limit of detection of 15 pM and a luminescence signal 50-fold higher than the background level. The modularity and sensitivity of the platform should enable the rapid construction of sensors for a wide range of analytes, and highlights the power of de novo protein design to create multi-state protein systems with new and useful functions.

Incorporation of sensing modalities into de novo designed fluorescence-activating proteins

Through the efforts of many groups, a wide range of fluorescent protein reporters and sensors based on green fluorescent protein and its relatives have been engineered in recent years. Here we explore the incorporation of sensing modalities into de novo designed fluorescence-activating proteins, called mini-fluorescence-activating proteins (mFAPs), that bind and stabilize the fluorescent cis-planar state of the fluorogenic compound DFHBI. We show through further design that the fluorescence intensity and specificity of mFAPs for different chromophores can be tuned, and the fluorescence made sensitive to pH and Ca²⁺ for real-time fluorescence reporting. Bipartite split mFAPs enable real-time monitoring of protein-protein association and (unlike widely used split GFP reporter systems) are fully reversible, allowing direct readout of association and dissociation events. The relative ease with which sensing modalities can be incorporated and advantages in smaller size and photostability make de novo designed fluorescence-activating proteins attractive candidates for optical sensor engineering.

Daidzein Induces Intrinsic Pathway of Apoptosis along with ER α/β Ratio Alteration and ROS Production

Background:

Low risk of breast cancer is observed among females consuming a moderate quantity of soy throughout their life. The present study was conducted to evaluate the anticancer potential of Daidzein, one of the major Isoflavones in soy using Human breast cancer cells MCF-7.

Methods:

MCF-7 were subjected to various doses of Daidzein treatment to determine the IC50 value. Onset of apoptosis was ascertained by AnnexinV assay and caspase 3/7 activity post treatment. Expression of pro-apoptotic protein Bax and anti-apoptotic protein Bcl2 was also assessed to further confirm apoptotic mode of cell death. ROS production post treatment with Daidzein was assessed to ascertain the apoptosis via intrinsic pathway. Expression of ER α and ER β was evaluated by western blot analysis.

Results:

Human breast cancer cells MCF-7 were found to be sensitive to Daidzein treatment, with an IC₅₀ value of 50µM. Increased percentage of treated cells stained with Annexin V confirmed apoptosis mediated cell death. Activity of Caspase 3/7 activity was found to be 1.4-fold higher in Daidzein treated cells than control cells, confirming apoptosis. Daidzein caused over expression of Bax and down-regulated expression of Bcl2. There has been an outburst of ROS in Daidzein treated cells indicating that Daidzein induces apoptosis via intrinsic pathway. A decrease in the expression of ER α and increase in levels of ER β has been observed which are conducive indicator of apoptosis.

Conclusions:

In conclusion, the present study suggests that Daidzein induces apoptosis in MCF-7 cells by mitochondrial pathway along with lowering the ratio of ER α/β and an outburst of Reactive Oxygen Species(ROS).

Selective Affimers Recognise the BCL-2 Family Proteins BCL-xL and MCL-1 through Noncanonical Structural Motifs*

The BCL-2 family is a challenging group of proteins to target selectively due to sequence and structural homologies across the family. Selective ligands for the BCL-2 family regulators of apoptosis are useful as probes to understand cell biology and apoptotic signalling pathways, and as starting points for inhibitor design. We have used phage display to isolate Affimer reagents (non-antibody-binding proteins based on a conserved scaffold) to identify ligands for MCL-1, BCL-xL , BCL-2, BAK and BAX, then used multiple biophysical characterisation methods to probe the interactions. We established that purified Affimers elicit selective recognition of their target BCL-2 protein. For anti-apoptotic targets BCL-xL and MCL-1, competitive inhibition of their canonical protein-protein interactions is demonstrated. Co-crystal structures reveal an unprecedented mode of molecular recognition; where a BH3 helix is normally bound, flexible loops from the Affimer dock into the BH3 binding cleft. Moreover, the Affimers induce a change in the target proteins towards a desirable drug-bound-like conformation. These proof-of-concept studies indicate that Affimers could be used as alternative templates to inspire the design of selective BCL-2 family modulators and more generally other protein-protein interaction inhibitors.

Deep mutagenesis in the study of COVID-19: a technical overview for the proteomics community

INTRODUCTION

The spike (S) of SARS coronavirus 2 (SARS-CoV-2) engages angiotensin-converting enzyme 2 (ACE2) on a host cell to trigger viral-cell membrane fusion and infection. The extracellular region of ACE2 can be administered as a soluble decoy to compete for binding sites on the receptor-binding domain (RBD) of S, but it has only moderate affinity and efficacy. The RBD, which is targeted by neutralizing antibodies, may also change and adapt through mutation as SARS-CoV-2 becomes endemic, posing challenges for therapeutic and vaccine development.

AREAS COVERED

Deep mutagenesis is a Big Data approach to characterizing sequence variants. A deep mutational scan of ACE2 expressed on human cells identified mutations that increase S affinity and guided the engineering of a potent and broad soluble receptor decoy. A deep mutational scan of the RBD displayed on the surface of yeast has revealed residues tolerant of mutational changes that may act as a source for drug resistance and antigenic drift.

EXPERT OPINION

Deep mutagenesis requires a selection of diverse sequence variants; an in vitro evolution experiment that is tracked with next-generation sequencing. The choice of expression system, diversity of the variant library and selection strategy have important consequences for data quality and interpretation.

De novo design of modular and tunable allosteric biosensors

Naturally occurring allosteric protein switches have been repurposed for developing novel biosensors and reporters for cellular and clinical applications ¹ , but the number of such switches is limited, and engineering them is often challenging as each is different. Here, we show that a very general class of allosteric protein-based biosensors can be created by inverting the flow of information through de novo designed protein switches in which binding of a peptide key triggers biological outputs of interest ² . Using broadly applicable design principles, we allosterically couple binding of protein analytes of interest to the reconstitution of luciferase activity and a bioluminescent readout through the association of designed lock and key proteins. Because the sensor is based purely on thermodynamic coupling of analyte binding to switch activation, only one target binding domain is required, which simplifies sensor design and allows direct readout in solution. We demonstrate the modularity of this platform by creating biosensors that, with little optimization, sensitively detect the anti-apoptosis protein Bcl-2, the hIgG1 Fc domain, the Her2 receptor, and Botulinum neurotoxin B, as well as biosensors for cardiac Troponin I and an anti-Hepatitis B virus (HBV) antibody that achieve the sub-nanomolar sensitivity necessary to detect clinically relevant concentrations of these molecules. Given the current need for diagnostic tools for tracking COVID-19 ³ , we use the approach to design sensors of antibodies against SARS-CoV-2 protein epitopes and of the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein. The latter, which incorporates a de novo designed RBD binder, has a limit of detection of 15pM with an up to seventeen fold increase in luminescence upon addition of RBD. The modularity and sensitivity of the platform should enable the rapid construction of sensors for a wide range of analytes and highlights the power of de novo protein design to create multi-state protein systems with new and useful functions.

Optimization of Protein Thermostability and Exploitation of Recognition Behavior to Engineer Altered Protein-DNA Recognition

The redesign of a macromolecular binding interface and corresponding alteration of recognition specificity is a challenging endeavor that remains recalcitrant to computational approaches. This is particularly true for the redesign of DNA binding specificity, which is highly dependent upon bending, hydrogen bonds, electrostatic contacts, and the presence of solvent and counterions throughout the molecular interface. Thus, redesign of protein-DNA binding specificity generally requires iterative rounds of amino acid randomization coupled to selections. Here, we describe the importance of scaffold thermostability for protein engineering, coupled with a strategy that exploits the protein's specificity profile, to redesign the specificity of a pair of meganucleases toward three separate genomic targets. We determine and describe a series of changes in protein sequence, stability, structure, and activity that accumulate during the engineering process, culminating in fully retargeted endonucleases.

Engineered receptors for human cytomegalovirus that are orthogonal to normal human biology

A trimeric glycoprotein complex on the surface of human cytomegalovirus (HCMV) binds to platelet-derived growth factor (PDGF) receptor α (PDGFRα) to mediate host cell recognition and fusion of the viral and cellular membranes. Soluble PDGFRα potently neutralizes HCMV in tissue culture, and its potential use as an antiviral therapeutic has the benefit that any escape mutants will likely be attenuated. However, PDGFRα binds multiple PDGF ligands in the human body as part of developmental programs in embryogenesis and continuing through adulthood. Any therapies with soluble receptor therefore come with serious efficacy and safety concerns, especially for the treatment of congenital HCMV. Soluble virus receptors that are orthogonal to human biology might resolve these concerns. This engineering problem is solved by deep mutational scanning on the D2-D3 domains of PDGFRα to identify variants that maintain interactions with the HCMV glycoprotein trimer in the presence of competing PDGF ligands. Competition by PDGFs is conformation-dependent, whereas HCMV trimer binding is independent of proper D2-D3 conformation, and many mutations at the receptor-PDGF interface are suitable for functionally separating trimer from PDGF interactions. Purified soluble PDGFRα carrying a targeted mutation succeeded in displaying wild type affinity for HCMV trimer with a simultaneous loss of PDGF binding, and neutralizes trimer-only and trimer/pentamer-expressing HCMV strains infecting fibroblasts or epithelial cells. Overall, this work makes important progress in the realization of soluble HCMV receptors for clinical application.

Human cytomegalovirus (HCMV) causes severe disease in transplant recipients and immunocompromised patients, and infections in a fetus or neonate are responsible for life-long neurological defects. Cell entry is in part mediated by a trimeric glycoprotein complex on the viral surface, which binds tightly to the host receptor PDGFRα. The soluble extracellular region of PDGFRα can be used as an antiviral agent to potently neutralize the virus in vitro. However, PDGFRα ordinarily binds growth factors in the human body to regulate developmental programs, which will limit the in vivo efficacy and safety of soluble PDGFRα. Using saturation mutagenesis and selections in human cell culture, mutations in PDGFRα are identified that eliminate off-target growth factor interactions while preserving HCMV binding and neutralization.

BCL-2 family deregulation in colorectal cancer: potential for BH3 mimetics in therapy

Apoptosis is a form of programmed cell death that is essential for tissue homeostasis. De-regulation of the balance between proliferation and apoptosis contributes to tumor initiation. Particularly in the colon where apoptosis is a crucial process in intestinal turnover, inhibition of apoptosis facilitates transformation and tumor progression. The BCL-2 family of proteins are key regulators of apoptosis and have been implicated in colorectal cancer (CRC) initiation, progression and resistance to therapy. In this review we outline the current knowledge on the BCL-2 family-regulated intrinsic apoptosis pathway and mechanisms by which it is de-regulated in CRC. We further review BH3 mimetics as a therapeutic opportunity to target this pathway and evaluate their potential for CRC treatment.

Inhibition of Anti-Apoptotic Bcl-2 Proteins in Preclinical and Clinical Studies: Current Overview in Cancer

The dynamic interplay between pro-death and pro-survival Bcl-2 family proteins is responsible for a cell’s fate. Due to the recognized relevance of this family in cancer progression and response to therapy, different efforts have made in recent years in order to develop small molecules able to target anti-apoptotic proteins such as Bcl-2, Bcl-xL and Mcl-1. The limitations of the first Bcl-2 family targeted drugs, regarding on-target and off-target toxicities, have been overcome with the development of venetoclax (ABT-199), the first BH3 mimetic inhibitor approved by the FDA. The purpose of this review is to discuss the state-of-the-art in the development of drugs targeting Bcl-2 anti-apoptotic proteins and to highlight the potential of their application as single agents or in combination for improving anti-cancer therapy, focusing in particular on solid tumors.

The advent of de novo proteins for cancer immunotherapy

Engineered proteins are revolutionizing immunotherapy, but advances are still needed to harness their full potential. Traditional protein engineering methods use naturally existing proteins as a starting point, and therefore, are intrinsically limited to small alterations of a protein's natural structure and function. Conversely, computational de novo protein design is free of such limitation, and can produce a virtually infinite number of novel protein sequences, folds, and functions. Recently, we used de novo protein engineering to create Neoleukin-2/15 (Neo-2/15), a protein mimetic of the function of both interleukin-2 (IL-2) and interleukin-15 (IL-15). To our knowledge, Neo-2/15 is the first de novo protein with immunotherapeutic activity, and in murine cancer models, it has demonstrated enhanced therapeutic potency and reduced toxicity compared to IL-2. De novo protein design is already showcasing its tremendous potential for driving the next wave of protein-based therapeutics that are explicitly engineered to treat disease.

Mammalian Surface Display Screening of Diverse Cystine-Dense Peptide Libraries for Difficult-to-Drug Targets

Many diseases are mediated by targets that are not amenable to conventional small-molecule drug approaches. While antibody-based drugs have undeniable utility, peptides of the 1-9 kDa size range (10-80 amino acids) have drawn interest as alternate drug scaffolds This is born of a desire to identify compounds with the advantages of antibody-based therapeutics (affinity, potency, specificity, and ability to disrupt protein:protein interactions) without all of their liabilities (large size, expensive manufacturing, and necessity of humanization). Of these alternate scaffolds, cystine-dense peptides (CDPs) have several specific benefits. Due to their stable intra-chain disulfide bridges, CDPs often demonstrate resistance to heat and proteolysis, along with low immunogenicity. These properties do not require chemical modifications, permitting CDP screening by conventional genetic means. The cystine topology of a typical CDP requires an oxidative environment, and we have found that the mammalian secretory pathway is most effective at allowing diverse CDPs to achieve a stable fold. As such, high-diversity screens to identify CDPs that interact with targets of interest can be efficiently conducted using mammalian surface display. In this protocol, we present the theory and tools to conduct a mammalian surface display screen for CDPs that bind with targets of interest, including the steps to validate binding and mature the affinity of preliminary candidates. With these methods, CDPs of all kinds can be brought to bear against targets that would benefit from a peptide-based intervention.

A selective BCL-XL PROTAC degrader achieves safe and potent antitumor activity

BCL-X_L is a well-validated cancer target. However, the on-target and dose-limiting thrombocytopenia limits the use of BCL-X_L inhibitors such as ABT263 as safe and effective anticancer agents. To reduce the toxicity of ABT263, we converted it into DT2216, a BCL-X_L proteolysis targeting chimera (PROTAC), that targets BCL-X_L to the Von Hippel-Lindau (VHL) E3 ligase for degradation. We found that DT2216 was more potent against various BCL-X_L-dependent leukemia and cancer cells but significantly less toxic to platelets than ABT263 in vitro because VHL is poorly expressed in platelets. In vivo, DT2216 effectively inhibits the growth of several xenograft tumors as a single agent or in combination with other chemotherapeutic agents, without causing significant thrombocytopenia. These findings demonstrate the potential to use PROTAC technology to reduce on-target drug toxicities and rescue the therapeutic potential of previously undruggable targets. Furthermore, DT2216 may be developed as a safe first-in-class anticancer agent targeting BCL-X_L.

Advances in protein structure prediction and design

The prediction of protein three-dimensional structure from amino acid sequence has been a grand challenge problem in computational biophysics for decades, owing to its intrinsic scientific interest and also to the many potential applications for robust protein structure prediction algorithms, from genome interpretation to protein function prediction. More recently, the inverse problem - designing an amino acid sequence that will fold into a specified three-dimensional structure - has attracted growing attention as a potential route to the rational engineering of proteins with functions useful in biotechnology and medicine. Methods for the prediction and design of protein structures have advanced dramatically in the past decade. Increases in computing power and the rapid growth in protein sequence and structure databases have fuelled the development of new data-intensive and computationally demanding approaches for structure prediction. New algorithms for designing protein folds and protein-protein interfaces have been used to engineer novel high-order assemblies and to design from scratch fluorescent proteins with novel or enhanced properties, as well as signalling proteins with therapeutic potential. In this Review, we describe current approaches for protein structure prediction and design and highlight a selection of the successful applications they have enabled.

Profilin and formin constitute a pacemaker system for robust actin filament growth

The actin cytoskeleton drives many essential biological processes, from cell morphogenesis to motility. Assembly of functional actin networks requires control over the speed at which actin filaments grow. How this can be achieved at the high and variable levels of soluble actin subunits found in cells is unclear. Here we reconstitute assembly of mammalian, non-muscle actin filaments from physiological concentrations of profilin-actin. We discover that under these conditions, filament growth is limited by profilin dissociating from the filament end and the speed of elongation becomes insensitive to the concentration of soluble subunits. Profilin release can be directly promoted by formin actin polymerases even at saturating profilin-actin concentrations. We demonstrate that mammalian cells indeed operate at the limit to actin filament growth imposed by profilin and formins. Our results reveal how synergy between profilin and formins generates robust filament growth rates that are resilient to changes in the soluble subunit concentration.

Designed for life: biocompatible de novo designed proteins and components

A principal goal of synthetic biology is the de novo design or redesign of biomolecular components. In addition to revealing fundamentally important information regarding natural biomolecular engineering and biochemistry, functional building blocks will ultimately be provided for applications including the manufacture of valuable products and therapeutics. To fully realize this ambitious goal, the designed components must be biocompatible, working in concert with natural biochemical processes and pathways, while not adversely affecting cellular function. For example, de novo protein design has provided us with a wide repertoire of structures and functions, including those that can be assembled and function in vivo. Here we discuss such biocompatible designs, as well as others that have the potential to become biocompatible, including non-protein molecules, and routes to achieving full biological integration.

Multi-input chemical control of protein dimerization for programming graded cellular responses

Chemical and optogenetic methods for post-translationally controlling protein function have enabled modulation and engineering of cellular functions. However, most of these methods only confer single-input, single-output control. To increase the diversity of post-translational behaviors that can be programmed, we built a system based on a single protein receiver that can integrate multiple drug inputs, including approved therapeutics. Our system translates drug inputs into diverse outputs using a suite of engineered reader proteins to provide variable dimerization states of the receiver protein. We show that our single receiver protein architecture can be used to program a variety of cellular responses, including graded and proportional dual-output control of transcription and mammalian cell signaling. We apply our tools to titrate the competing activities of the Rac and Rho GTPases to control cell morphology. Our versatile tool set will enable researchers to post-translationally program mammalian cellular processes and to engineer cell therapies.

De novo design of bioactive protein switches

Allosteric regulation of protein function is widespread in biology, but is challenging for de novo protein design as it requires the explicit design of multiple states with comparable free energies. Here we explore the possibility of designing switchable protein systems de novo, through the modulation of competing inter- and intramolecular interactions. We design a static, five-helix 'cage' with a single interface that can interact either intramolecularly with a terminal 'latch' helix or intermolecularly with a peptide 'key'. Encoded on the latch are functional motifs for binding, degradation or nuclear export that function only when the key displaces the latch from the cage. We describe orthogonal cage-key systems that function in vitro, in yeast and in mammalian cells with up to 40-fold activation of function by key. The ability to design switchable protein functions that are controlled by induced conformational change is a milestone for de novo protein design, and opens up new avenues for synthetic biology and cell engineering.

Structures of BCL-2 in complex with venetoclax reveal the molecular basis of resistance mutations

Venetoclax is a first-in-class cancer therapy that interacts with the cellular apoptotic machinery promoting apoptosis. Treatment of patients suffering chronic lymphocytic leukaemia with this BCL-2 antagonist has revealed emergence of a drug-selected BCL-2 mutation (G101V) in some patients failing therapy. To understand the molecular basis of this acquired resistance we describe the crystal structures of venetoclax bound to both BCL-2 and the G101V mutant. The pose of venetoclax in its binding site on BCL-2 reveals small but unexpected differences as compared to published structures of complexes with venetoclax analogues. The G101V mutant complex structure and mutant binding assays reveal that resistance is acquired by a knock-on effect of V101 on an adjacent residue, E152, with venetoclax binding restored by a E152A mutation. This provides a framework for considering analogues of venetoclax that might be effective in combating this mutation.

The BCL-2 mutation G101V reduces venetoclax affinity and confers drug resistance in patients with chronic lymphocytic leukaemia. Here, the authors present crystal structures and biochemical analyses of venetoclax bound to BCL-2 and the G101V mutant, revealing the structural basis for venetoclax resistance.

Investigating the Molecular Basis of N-Substituted 1-Hydroxy-4-Sulfamoyl-2-Naphthoate Compounds Binding to Mcl1

Myeloid cell leukemia-1 (Mcl1) is an anti–apoptotic protein that has gained considerable attention due to its overexpression activity prevents cell death. Therefore, a potential inhibitor that specifically targets Mcl1 with higher binding affinity is necessary. Recently, a series of N-substituted 1-hydroxy-4-sulfamoyl-2-naphthoate compounds was reported that targets Mcl1, but its binding mechanism remains unexplored. Here, we attempted to explore the molecular mechanism of binding to Mcl1 using advanced computational approaches: pharmacophore-based 3D-QSAR, docking, and MD simulation. The selected pharmacophore—NNRRR—yielded a statistically significant 3D-QSAR model containing high confidence scores (R2 = 0.9209, Q2 = 0.8459, and RMSE = 0.3473). The contour maps—comprising hydrogen bond donor, hydrophobic, negative ionic and electron withdrawal effects—from our 3D-QSAR model identified the favorable regions crucial for maximum activity. Furthermore, the external validation of the selected model using enrichment and decoys analysis reveals a high predictive power. Also, the screening capacity of the selected model had scores of 0.94, 0.90, and 8.26 from ROC, AUC, and RIE analysis, respectively. The molecular docking of the highly active compound—C40; 4-(N-benzyl-N-(4-(4-chloro-3,5-dimethylphenoxy) phenyl) sulfamoyl)-1-hydroxy-2-naphthoate—predicted the low-energy conformational pose, and the MD simulation revealed crucial details responsible for the molecular mechanism of binding with Mcl1.

Tertiary Structural Motif Sequence Statistics Enable Facile Prediction and Design of Peptides that Bind Anti-apoptotic Bfl-1 and Mcl-1

Understanding the relationship between protein sequence and structure well enough to design new proteins with desired functions is a longstanding goal in protein science. Here, we show that recurring tertiary structural motifs (TERMs) in the PDB provide rich information for protein-peptide interaction prediction and design. TERM statistics can be used to predict peptide binding energies for Bcl-2 family proteins as accurately as widely used structure-based tools. Furthermore, design using TERM energies (dTERMen) rapidly and reliably generates high-affinity peptide binders of anti-apoptotic proteins Bfl-1 and Mcl-1 with just 15%-38% sequence identity to any known native Bcl-2 family protein ligand. High-resolution structures of four designed peptides bound to their targets provide opportunities to analyze the strengths and limitations of the computational design method. Our results support dTERMen as a powerful approach that can complement existing tools for protein engineering.