Peptide Tethering: Pocket-Directed Fragment Screening for Peptidomimetic Inhibitor Discovery

In silico screening of protein-binding peptides with an application to developing peptide inhibitors against antibiotic resistance

The field of therapeutic peptides is experiencing a surge, fueled by their advantageous features. These include predictable metabolism, enhanced safety profile, high selectivity, and reduced off-target effects compared with small-molecule drugs. Despite progress in addressing limitations associated with peptide drugs, a significant bottleneck remains: the absence of a large-scale in silico screening method for a given protein target structure. Such methods have proven invaluable in accelerating small-molecule drug discovery. The high flexibility of peptide structures and the large diversity of peptide sequences greatly hinder the development of urgently needed computational methods. Here, we report a method called MDockPeP2_VS to address these challenges. It integrates molecular docking with structural conservation between protein folding and protein-peptide binding. Briefly, we discovered that when the interfacial residues are conserved, a sequence fragment derived from a monomeric protein exhibits a high propensity to bind a target protein with a similar conformation. This valuable insight significantly reduces the search space for peptide conformations, resulting in a substantial reduction in computational time and making in silico peptide screening practical. We applied MDockPeP2_VS to develop peptide inhibitors targeting the TEM-1 β-lactamase of Escherichia coli, a key mechanism behind antibiotic resistance in gram-negative bacteria. Among the top 10 peptides selected from in silico screening, TF7 (KTYLAQAAATG) showed significant inhibition of β-lactamase activity with a K i value of 1.37 ± 0.37 µM. This fully automated, large-scale structure-based in silico peptide screening software is available for free download at https://zougrouptoolkit.missouri.edu/mdockpep2_vs/download.html.

Recent Advances in Peptide Drug Discovery: Novel Strategies and Targeted Protein Degradation

Recent technological advancements, including computer-assisted drug discovery, gene-editing techniques, and high-throughput screening approaches, have greatly expanded the palette of methods for the discovery of peptides available to researchers. These emerging strategies, driven by recent advances in bioinformatics and multi-omics, have significantly improved the efficiency of peptide drug discovery when compared with traditional in vitro and in vivo methods, cutting costs and improving their reliability. An added benefit of peptide-based drugs is the ability to precisely target protein-protein interactions, which are normally a particularly challenging aspect of drug discovery. Another recent breakthrough in this field is targeted protein degradation through proteolysis-targeting chimeras. These revolutionary compounds represent a noteworthy advancement over traditional small-molecule inhibitors due to their unique mechanism of action, which allows for the degradation of specific proteins with unprecedented specificity. The inclusion of a peptide as a protein-of-interest-targeting moiety allows for improved versatility and the possibility of targeting otherwise undruggable proteins. In this review, we discuss various novel wet-lab and computational multi-omic methods for peptide drug discovery, provide an overview of therapeutic agents discovered through these cutting-edge techniques, and discuss the potential for the therapeutic delivery of peptide-based drugs.

Crafting Unnatural Peptide Macrocycles via Rh(III)-Catalyzed Carboamidation

Contemporary developments in the field of peptide macrocyclization methodology are imperative for enabling the advance of drug design in medicinal chemistry. This report discloses a Rh(III)-catalyzed macrocyclization via carboamidation, reacting acryloyl-peptide-dioxazolone precursors and arylboronic acids to form complex cyclic peptides with concomitant incorporation of noncanonical α-amino acids. The diverse and modular technology allows for expedient access to a wide variety of cyclic peptides from 4 to 15 amino acids in size and features simultaneous formation of unnatural phenylalanine and tyrosine derivatives with up to >20:1 diastereoselectivity. The reaction showcases an expansive substrate scope with 45 examples and is compatible with the majority of standard protected amino acids used in Fmoc-solid phase peptide synthesis. The methodology is applied to the synthesis of multiple peptidomimetic macrocyclic analogs, including derivatives of cyclosomatostatin and gramicidin S.

Inhibition of CREB Binding and Function with a Dual-Targeting Ligand

CBP/p300 is a master transcriptional coactivator that regulates gene activation by interacting with multiple transcriptional activators. Dysregulation of protein-protein interactions (PPIs) between the CBP/p300 KIX domain and its activators is implicated in a number of cancers, including breast, leukemia, and colorectal cancer. However, KIX is typically considered "undruggable" because of its shallow binding surfaces lacking both significant topology and promiscuous binding profiles. We previously reported a dual-targeting peptide (MybLL-tide) that inhibits the KIX-Myb interaction with excellent specificity and potency. Here, we demonstrate a branched, second-generation analogue, CREBLL-tide, that inhibits the KIX-CREB PPI with higher potency and selectivity. Additionally, the best of these CREBLL-tide analogues shows excellent and selective antiproliferation activity in breast cancer cells. These results indicate that CREBLL-tide is an effective tool for assessing the role of KIX-activator interactions in breast cancer and expanding the dual-targeting strategy for inhibiting KIX and other coactivators that contain multiple binding surfaces.

Assessing the fast prediction of peptide conformers and the impact of non-natural modifications

We present an assessment of different approaches to predict peptide structures using modeling tools. Several small molecule, protein, and peptide-focused methodologies were used for the fast prediction of conformers for peptides shorter than 30 amino acids. We assessed the effect of including restraints based on annotated or predicted secondary structure motifs. A number of peptides in bound conformations and in solution were collected to compare the tools. In addition, we studied the impact of changing single amino acids to non-natural residues using molecular dynamics simulations. Deep learning methods such as AlphaFold2, or the combination of physics-based approaches with secondary structure information, produce the most accurate results for natural sequences. In the case of peptides with non-natural modifications, modeling the peptide containing natural amino acids first and then modifying and simulating the peptide using benchmarked force fields is a recommended pipeline. The results can guide the modeling of oligopeptides for drug discovery projects.

Integrated Molecular Modeling and Machine Learning for Drug Design

Modern therapeutic development often involves several stages that are interconnected, and multiple iterations are usually required to bring a new drug to the market. Computational approaches have increasingly become an indispensable part of helping reduce the time and cost of the research and development of new drugs. In this Perspective, we summarize our recent efforts on integrating molecular modeling and machine learning to develop computational tools for modulator design, including a pocket-guided rational design approach based on AlphaSpace to target protein-protein interactions, delta machine learning scoring functions for protein-ligand docking as well as virtual screening, and state-of-the-art deep learning models to predict calculated and experimental molecular properties based on molecular mechanics optimized geometries. Meanwhile, we discuss remaining challenges and promising directions for further development and use a retrospective example of FDA approved kinase inhibitor Erlotinib to demonstrate the use of these newly developed computational tools.

Amphiphilic small molecule antimicrobials: From cationic antimicrobial peptides (CAMPs) to mechanism-related, structurally-diverse antimicrobials

Bacterial infections are characterized by their rapid and widespread proliferation, leading to significant morbidity. Despite the availability of a variety of antimicrobial drugs, the resistance exhibited by pathogenic microorganisms towards these drugs demonstrates a consistent upward trajectory year after year. This trend can be attributed to the abuse or misuse of antibiotics. Although antimicrobial peptides can avoid the emergence of drug resistance to a certain extent, their clinical application has been hindered by factors such as their high production cost, poor in vivo stability, and potential cytotoxicity. Consequently, there arises an urgent need for the development of novel antimicrobial drugs. Small-molecule amphiphatic antimicrobials have a good prospect for research and development. These peptides hold the potential to address several issues, including the high cost of antimicrobial peptide production, poor in vivo stability, and cytotoxicity. Moreover, they exhibit the capability to overcome bacterial resistance, thereby considerably satisfying market demands and clinical needs. This paper reviews recent research pertaining to small molecule host-defending amphiphatic antimicrobials with cationic amphiphilic structures. It focuses on the design concepts, inherent relationships, drug-like properties, antimicrobial activities, application prospects, and emerging screening methods for novel antimicrobial. This review assumes paramount importance in mitigating the current shortcomings of antimicrobial agents. It also provides potential new ideas and methodologies for the research and development of antimicrobial agents.

Designing Cyclic-Constrained Peptides to Inhibit Human Phosphoglycerate Dehydrogenase

Although loop epitopes at protein-protein binding interfaces often play key roles in mediating oligomer formation and interaction specificity, their binding sites are underexplored as drug targets owing to their high flexibility, relatively few hot spots, and solvent accessibility. Prior attempts to develop molecules that mimic loop epitopes to disrupt protein oligomers have had limited success. In this study, we used structure-based approaches to design and optimize cyclic-constrained peptides based on loop epitopes at the human phosphoglycerate dehydrogenase (PHGDH) dimer interface, which is an obligate homo-dimer with activity strongly dependent on the oligomeric state. The experimental validations showed that these cyclic peptides inhibit PHGDH activity by directly binding to the dimer interface and disrupting the obligate homo-oligomer formation. Our results demonstrate that loop epitope derived cyclic peptides with rationally designed affinity-enhancing substitutions can modulate obligate protein homo-oligomers, which can be used to design peptide inhibitors for other seemingly intractable oligomeric proteins.

Two-Step Validation Approach for Tools To Study the DNA Repair Enzyme SNM1A

We report a two-step validation approach to evaluate the suitability of metal-binding groups for targeting DNA damage-repair metalloenzymes using model enzyme SNM1A. A fragment-based screening approach was first used to identify metal-binding fragments suitable for targeting the enzyme. Effective fragments were then incorporated into oligonucleotides using the copper-catalysed azide-alkyne cycloaddition reaction. These modified oligonucleotides were recognised by SNM1A at >1000-fold lower concentrations than their fragment counterparts. The exonuclease SNM1A is a key enzyme involved in the repair of interstrand crosslinks, a highly cytotoxic form of DNA damage. However, SNM1A and other enzymes of this class are poorly understood, as there is a lack of tools available to facilitate their study. Our novel approach of incorporating functional fragments into oligonucleotides is broadly applicable to generating modified oligonucleotide structures with high affinity for DNA damage-repair enzymes.

Molecular Complementarity of Proteomimetic Materials for Target-Specific Recognition and Recognition-Mediated Complex Functions

As biomolecules essential for sustaining life, proteins are generated from long chains of 20 different α-amino acids that are folded into unique 3D structures. In particular, many proteins have molecular recognition functions owing to their binding pockets, which have complementary shapes, charges, and polarities for specific targets, making these biopolymers unique and highly valuable for biomedical and biocatalytic applications. Based on the understanding of protein structures and microenvironments, molecular complementarity can be exhibited by synthesizable and modifiable materials. This has prompted researchers to explore the proteomimetic potentials of a diverse range of materials, including biologically available peptides and oligonucleotides, synthetic supramolecules, inorganic molecules, and related coordination networks. To fully resemble a protein, proteomimetic materials perform the molecular recognition to mediate complex molecular functions, such as allosteric regulation, signal transduction, enzymatic reactions, and stimuli-responsive motions; this can also expand the landscape of their potential bio-applications. This review focuses on the recognitive aspects of proteomimetic designs derived for individual materials and their conformations. Recent progress provides insights to help guide the development of advanced protein mimicry with material heterogeneity, design modularity, and tailored functionality. The perspectives and challenges of current proteomimetic designs and tools are also discussed in relation to future applications.

Rational peptide design for inhibition of the KIX-MLL interaction

The kinase-inducible domain interacting (KIX) domain is an integral part of the general transcriptional coactivator CREB-binding protein, and has been associated with leukemia, cancer, and various viral diseases. Hence, the KIX domain has attracted considerable attention in drug discovery and development. Here, we rationally designed a KIX inhibitor using a peptide fragment corresponding to the transactivation domain (TAD) of the transcriptional activator, mixed-lineage leukemia protein (MLL). We performed theoretical saturation mutagenesis using the Rosetta software to search for mutants expected to bind KIX more tightly than the wild-type MLL TAD. Mutant peptides with higher helical propensities were selected for experimental characterization. We found that the T2857W mutant of the MLL TAD peptide had the highest binding affinity for KIX compared to the other 12 peptides designed in this study. Moreover, the peptide had a high inhibitory effect on the KIX-MLL interaction with a half-maximal inhibitory concentration close to the dissociation constant for this interaction. To our knowledge, this peptide has the highest affinity for KIX among all previously reported inhibitors that target the MLL site of KIX. Thus, our approach may be useful for rationally developing helical peptides that inhibit protein-protein interactions implicated in the progression of various diseases.

Late-Stage Modification of Oligopeptides by Nickel-Catalyzed Stereoselective Radical Addition to Dehydroalanine

Radical addition to dehydroalanine (Dha) represents an appealing, modular strategy to access non-canonical peptide analogues for drug discovery. Prior studies on radical addition to the Dha residue of peptides and proteins have demonstrated outstanding functional group compatibility, but the lack of stereoselectivity has limited the synthetic utility of this approach. Herein, we address this challenge by employing chiral nickel catalysts to control the stereoselectivity of radical addition to Dha on oligopeptides. The conditions accommodate a variety of primary and secondary electrophiles to introduce polyethylene glycol, biotin, halo-tag, and hydrophobic and hydrophilic side chains to the peptide. The reaction features catalyst control to largely override substrate-based control of stereochemical outcome for modification of short peptides. We anticipate that the discovery of chiral nickel complexes that confer catalyst control will allow rapid, late-stage modification of peptides featuring nonnatural sidechains.

Synthesis and Studies of Bulky Cycloalkyl α,β-Dehydroamino Acids that Enhance Proteolytic Stability

Three new bulky cycloalkyl α,β-dehydroamino acids (ΔAAs) have been designed and synthesized. Each residue enhances the rigidity of model peptides and their stability to proteolysis, with larger ring sizes exhibiting greater effects. Peptides containing bulky cycloalkyl ΔAAs are inert to conjugate addition by a nucleophilic thiol. The results suggest that these residues will be effective tools for improving the proteolytic stability of bioactive peptides.