Allosteric Modulators of Protein-Protein Interactions (PPIs)

Identification of a potent PCNA-p15-interaction inhibitor by autodisplay-based peptide library screening

Proliferating cell nuclear antigen (PCNA) is an essential factor for DNA metabolism. The influence of PCNA on DNA replication and repair, combined with the high expression rate of PCNA in various tumours renders PCNA a promising target for cancer therapy. In this context, an autodisplay-based screening method was developed to identify peptidic PCNA interaction inhibitors. A 12-mer randomized peptide library consisting of 2.54 × 106 colony-forming units was constructed and displayed at the surface of Escherichia coli BL21 (DE3) cells by autodisplay. Cells exhibiting an enhanced binding to fluorescent mScarlet-I-PCNA were enriched in four sorting rounds by flow cytometry. This led to the discovery of five peptide variants with affinity to mScarlet-I-PCNA. Among these, P3 (TCPLRWITHDHP) exhibited the highest binding signal. Subsequent flow cytometric analysis revealed a dissociation constant of 0.62 μM for PCNA-P3 interaction. Furthermore, the inhibition of PCNA interactions was investigated using p15, a PIP-box containing protein involved in DNA replication and repair. P3 inhibited the PCNA-p1551-70 interaction with a half maximal inhibitory activity of 16.2 μM, characterizing P3 as a potent inhibitor of the PCNA-p15 interaction.

ASD2023: towards the integrating landscapes of allosteric knowledgebase

Allosteric regulation, induced by perturbations at an allosteric site topographically distinct from the orthosteric site, is one of the most direct and efficient ways to fine-tune macromolecular function. The Allosteric Database (ASD; accessible online at http://mdl.shsmu.edu.cn/ASD) has been systematically developed since 2009 to provide comprehensive information on allosteric regulation. In recent years, allostery has seen sustained growth and wide-ranging applications in life sciences, from basic research to new therapeutics development, while also elucidating emerging obstacles across allosteric research stages. To overcome these challenges and maintain high-quality data center services, novel features were curated in the ASD2023 update: (i) 66 589 potential allosteric sites, covering > 80% of the human proteome and constituting the human allosteric pocketome; (ii) 748 allosteric protein-protein interaction (PPI) modulators with clear mechanisms, aiding protein machine studies and PPI-targeted drug discovery; (iii) 'Allosteric Hit-to-Lead,' a pioneering dataset providing panoramic views from 87 well-defined allosteric hits to 6565 leads and (iv) 456 dualsteric modulators for exploring the simultaneous regulation of allosteric and orthosteric sites. Meanwhile, ASD2023 maintains a significant growth of foundational allosteric data. Based on these efforts, the allosteric knowledgebase is progressively evolving towards an integrated landscape, facilitating advancements in allosteric target identification, mechanistic exploration and drug discovery.

Harnessing the druggability at orthosteric and allosteric sites of PD-1 for small molecule discovery by an integrated in silico pipeline

The PD-1/PD-L1 interaction is a promising target for small molecule inhibitors in cancer immunotherapy, but targeting this interface has been challenging. While efforts have been made to identify compounds that target the orthosteric sites, no reports have explored the potential of small molecules to target the allosteric region of PD-1. Therefore, our study aims to establish a pipeline to identify small molecules that can effectively bind to either the orthosteric or allosteric pockets of PD-1. We categorized the PD-1 interface into two hot-spot zones (P-and N-zones) based on extensive analysis of its structural, dynamical, and energetic properties. These zones correspond to the orthosteric and allosteric PPI sites, respectively, targeted by monoclonal antibodies. We used a guided virtual screening workflow to identify hits from ∼7 million compounds library, which were then clustered based on structural similarity and assessed by interaction fingerprinting. The selective and diverse chemical representatives were subjected to MD simulations and binding energetics calculations to filter out false positives and identify actual binders. Binding poses metadynamics calculations confirmed the stability of the final hits in the pocket. This study emphasizes the need for an integrated pipeline that uses molecular dynamics simulations and binding energetics to identify potential binders for the dynamic PD-1/PD-L1 interface, due to the lack of small molecule co-crystals. Only a few potential binders were discovered from a large pool of molecules targeting both the allosteric and orthosteric zones. Our results suggest that the allosteric site has more potential than the orthosteric site for inhibitor design. The identified "computational hits" hold potential as starting points for in vitro evaluations followed by hit-to-lead optimization. Overall, this study represents an effort to establish a computational pipeline for exploring and enriching both the allosteric and orthosteric sites of PPI interfaces, "a tough but indispensable nut to crack".

Metadynamics simulations of ligands binding to protein surfaces: a novel tool for rational drug design

Structure-based drug design protocols may encounter difficulties to investigate poses when the biomolecular targets do not exhibit typical binding pockets. In this study, by providing two concrete examples from our labs, we suggest that the combination of metadynamics free energy methods (validated against affinity measurements), along with experimental structural information (by X-ray crystallography and NMR), can help to identify the poses of ligands on protein surfaces. The simulation workflow proposed here was implemented in a widely used code, namely GROMACS, and it could straightforwardly be applied to various drug-design campaigns targeting ligands' binding to protein surfaces.

Study of FOXO1-interacting proteins using TurboID-based proximity labeling technology

BACKGROUND

Protein‒protein interactions (PPIs) are the foundation of the life activities of cells. TurboID is a biotin ligase with higher catalytic efficiency than BioID or APEX that reduces the required labeling time from 18 h to 10 min. Since many proteins participate in binding and catalytic events that are very short-lived, it is theoretically possible to find relatively novel binding proteins using the TurboID technique. Cell proliferation, apoptosis, autophagy, oxidative stress and metabolic disorders underlie many diseases, and forkhead box transcription factor 1 (FOXO1) plays a key role in these physiological and pathological processes.

RESULTS

The FOXO1-TurboID fusion gene was transfected into U251 astrocytes, and a cell line stably expressing FOXO1 was constructed. While constructing the FOXO1 overexpression plasmid, we also added the gene sequence of TurboID to perform biotin labeling experiments in the successfully fabricated cell line to look for FOXO1 reciprocal proteins. Label-free mass spectrometry analysis was performed, and 325 interacting proteins were found. A total of 176 proteins were identified in the FOXO1 overexpression group, and 227 proteins were identified in the Lipopolysaccharide -treated group (Lipopolysaccharide, LPS). Wild-type U251 cells were used to exclude interference from nonspecific binding. The FOXO1-interacting proteins hnRNPK and RBM14 were selected for immunoprecipitation and immunofluorescence verification.

CONCLUSION

The TurboID technique was used to select the FOXO1-interacting proteins, and after removing the proteins identified in the blank group, a large number of interacting proteins were found in both positive groups. This study lays a foundation for further study of the function of FOXO1 and the regulatory network in which it is involved.

Crystallographic mining of ASK1 regulators to unravel the intricate PPI interfaces for the discovery of small molecule

Protein seldom performs biological activities in isolation. Understanding the protein–protein interactions’ physical rewiring in response to pathological conditions or pathogen infection can help advance our comprehension of disease etiology, progression, and pathogenesis, which allow us to explore the alternate route to control the regulation of key target interactions, timely and effectively. Nonalcoholic steatohepatitis (NASH) is now a global public health problem exacerbated due to the lack of appropriate treatments. The most advanced anti-NASH lead compound (selonsertib) is withdrawn, though it is able to inhibit its target Apoptosis signal-regulating kinase 1 (ASK1) completely, indicating the necessity to explore alternate routes rather than complete inhibition. Understanding the interaction fingerprints of endogenous regulators at the molecular level that underpin disease formation and progression may spur the rationale of designing therapeutic strategies. Based on our analysis and thorough literature survey of the various key regulators and PTMs, the current review emphasizes PPI-based drug discovery’s relevance for NASH conditions. The lack of structural detail (interface sites) of ASK1 and its regulators makes it challenging to characterize the PPI interfaces. This review summarizes key regulators interaction fingerprinting of ASK1, which can be explored further to restore the homeostasis from its hyperactive states for therapeutics intervention against NASH.

Recent Advances in Cancer Drug Discovery Through the Use of Phenotypic Reporter Systems, Connectivity Mapping, and Pooled CRISPR Screening

Multi-omic approaches offer an unprecedented overview of the development, plasticity, and resistance of cancer. However, the translation from anti-cancer compounds identified in vitro to clinically active drugs have a notoriously low success rate. Here, we review how technical advances in cell culture, robotics, computational biology, and development of reporter systems have transformed drug discovery, enabling screening approaches tailored to clinically relevant functional readouts (e.g., bypassing drug resistance). Illustrating with selected examples of “success stories,” we describe the process of phenotype-based high-throughput drug screening to target malignant cells or the immune system. Second, we describe computational approaches that link transcriptomic profiling of cancers with existing pharmaceutical compounds to accelerate drug repurposing. Finally, we review how CRISPR-based screening can be applied for the discovery of mechanisms of drug resistance and sensitization. Overall, we explore how the complementary strengths of each of these approaches allow them to transform the paradigm of pre-clinical drug development.

Challenges in Discovering Drugs That Target the Protein-Protein Interactions of Disordered Proteins

Protein–protein interactions (PPIs) outnumber proteins and are crucial to many fundamental processes; in consequence, PPIs are associated with several pathological conditions including neurodegeneration and modulating them by drugs constitutes a potentially major class of therapy. Classically, however, the discovery of small molecules for use as drugs entails targeting individual proteins rather than targeting PPIs. This is largely because discovering small molecules to modulate PPIs has been seen as extremely challenging. Here, we review the difficulties and limitations of strategies to discover drugs that target PPIs directly or indirectly, taking as examples the disordered proteins involved in neurodegenerative diseases.

Mechanism of activation and the rewired network: New drug design concepts

Precision oncology benefits from effective early phase drug discovery decisions. Recently, drugging inactive protein conformations has shown impressive successes, raising the cardinal questions of which targets can profit and what are the principles of the active/inactive protein pharmacology. Cancer driver mutations have been established to mimic the protein activation mechanism. We suggest that the decision whether to target an inactive (or active) conformation should largely rest on the protein mechanism of activation. We next discuss the recent identification of double (multiple) same-allele driver mutations and their impact on cell proliferation and suggest that like single driver mutations, double drivers also mimic the mechanism of activation. We further suggest that the structural perturbations of double (multiple) in cis mutations may reveal new surfaces/pockets for drug design. Finally, we underscore the preeminent role of the cellular network which is deregulated in cancer. Our structure-based review and outlook updates the traditional Mechanism of Action, informs decisions, and calls attention to the intrinsic activation mechanism of the target protein and the rewired tumor-specific network, ushering innovative considerations in precision medicine.

Pepscan Approach for the Identification of Protein-Protein Interfaces: Lessons from Experiment

PEPscan is an old approach that has recently gained renewed interest for the identification of interfering peptides (IPs), i.e., peptides able to interfere with protein-protein interactions (PPIs). Its principle is to slice a protein sequence as a series of short overlapping peptides that are synthesized on a peptide array and tested for their ability to bind a partner, with positive spots corresponding to candidate IPs. PEPscan has been applied with a rather large success in various contexts, but the structural determinants underlying this success remain obscure. Here, we analyze the results of 14 PEPscan experiments, and confront the in vitro results with the available structural information. PEPscan identifies candidate IPs in limited numbers that in all cases correspond to solvent-accessible regions of the structures, their location at the protein-protein interface remaining to be further demonstrated. A strong point of PEPscan seems to be its ability to identify specific IPs. IPs identified from the same protein differ depending on the target PPI, and correspond to patches not frequently involved in the interactions seen in the 3D structures available. Overall, PEPscan seems to provide a cheap and rapid manner to identify candidate IPs, that also comes with room for improvement.

Exploring the Human Cytomegalovirus Core Nuclear Egress Complex as a Novel Antiviral Target: A New Type of Small Molecule Inhibitors

Nuclear egress is an essential process in the replication of human cytomegalovirus (HCMV), as it enables the migration of newly formed viral capsids from the nucleus into the cytoplasm. Inhibition of the HCMV core nuclear egress complex (core NEC), composed of viral proteins pUL50 and pUL53, has been proposed as a potential new target for the treatment of HCMV infection and disease. Here, we present a new type of small molecule inhibitors of HCMV core NEC formation, which inhibit the pUL50-pUL53 interaction at nanomolar concentrations. These inhibitors, i.e., verteporfin and merbromin, were identified through the screening of the Prestwick Chemical Library^® of approved drug compounds. The inhibitory effect of merbromin is both compound- and target-specific, as no inhibition was seen for other mercury-organic compounds. Furthermore, merbromin does not inhibit an unrelated protein-protein interaction either. More importantly, merbromin was found to inhibit HCMV infection of cells in three different assays, as well as to disrupt HCMV NEC nuclear rim formation. Thus, while not being an ideal drug candidate by itself, merbromin may serve as a blueprint for small molecules with high HCMV core NEC inhibitory potential, as candidates for novel anti-herpesviral drugs.

Improving target assessment in biomedical research: the GOT-IT recommendations

Academic research plays a key role in identifying new drug targets, including understanding target biology and links between targets and disease states. To lead to new drugs, however, research must progress from purely academic exploration to the initiation of efforts to identify and test a drug candidate in clinical trials, which are typically conducted by the biopharma industry. This transition can be facilitated by a timely focus on target assessment aspects such as target-related safety issues, druggability and assayability, as well as the potential for target modulation to achieve differentiation from established therapies. Here, we present recommendations from the GOT-IT working group, which have been designed to support academic scientists and funders of translational research in identifying and prioritizing target assessment activities and in defining a critical path to reach scientific goals as well as goals related to licensing, partnering with industry or initiating clinical development programmes. Based on sets of guiding questions for different areas of target assessment, the GOT-IT framework is intended to stimulate academic scientists' awareness of factors that make translational research more robust and efficient, and to facilitate academia-industry collaboration.

Analyzing In Silico the Relationship Between the Activation of the Edema Factor and Its Interaction With Calmodulin

Molecular dynamics (MD) simulations have been recorded on the complex between the edema factor (EF) of Bacilllus anthracis and calmodulin (CaM), starting from a structure with the orthosteric inhibitor adefovir bound in the EF catalytic site. The starting structure has been destabilized by alternately suppressing different co-factors, such as adefovir ligand or ions, revealing several long-distance correlations between the conformation of CaM, the geometry of the CaM/EF interface, the enzymatic site and the overall organization of the complex. An allosteric communication between CaM/EF interface and the EF catalytic site, highlighted by these correlations, was confirmed by several bioinformatics approaches from the literature. A network of hydrogen bonds and stacking interactions extending from the helix V of of CaM, and the residues of the switches A, B and C, and connecting to catalytic site residues, is a plausible candidate for the mediation of allosteric communication. The greatest variability in volume between the different MD conditions was also found for cavities present at the EF/CaM interface and in the EF catalytic site. The similarity between the predictions from literature and the volume variability might introduce the volume variability as new descriptor of allostery.

A Coarse-Grained Methodology Identifies Intrinsic Mechanisms That Dissociate Interacting Protein Pairs

We address the problem of triggering dissociation events between proteins that have formed a complex. We have collected a set of 25 non-redundant, functionally diverse protein complexes having high-resolution three-dimensional structures in both the unbound and bound forms. We unify elastic network models with perturbation response scanning (PRS) methodology as an efficient approach for predicting residues that have the propensity to trigger dissociation of an interacting protein pair, using the three-dimensional structures of the bound and unbound proteins as input. PRS reveals that while for a group of protein pairs, residues involved in the conformational shifts are confined to regions with large motions, there are others where they originate from parts of the protein unaffected structurally by binding. Strikingly, only a few of the complexes have interface residues responsible for dissociation. We find two main modes of response: In one mode, remote control of dissociation in which disruption of the electrostatic potential distribution along protein surfaces play the major role; in the alternative mode, mechanical control of dissociation by remote residues prevail. In the former, dissociation is triggered by changes in the local environment of the protein, e.g., pH or ionic strength, while in the latter, specific perturbations arriving at the controlling residues, e.g., via binding to a third interacting partner is required for decomplexation. We resolve the observations by relying on an electromechanical coupling model which reduces to the usual elastic network result in the limit of the lack of coupling. We validate the approach by illustrating the biological significance of top residues selected by PRS on select cases where we show that the residues whose perturbation leads to the observed conformational changes correspond to either functionally important or highly conserved residues in the complex.

Discovery of cryptic allosteric sites using reversed allosteric communication by a combined computational and experimental strategy

Allostery, which is one of the most direct and efficient methods to fine-tune protein functions, has gained increasing recognition in drug discovery. However, there are several challenges associated with the identification of allosteric sites, which is the fundamental cornerstone of drug design. Previous studies on allosteric site predictions have focused on communication signals propagating from the allosteric sites to the orthosteric sites. However, recent biochemical studies have revealed that allosteric coupling is bidirectional and that orthosteric perturbations can modulate allosteric sites through reversed allosteric communication. Here, we proposed a new framework for the prediction of allosteric sites based on reversed allosteric communication using a combination of computational and experimental strategies (molecular dynamics simulations, Markov state models, and site-directed mutagenesis). The desirable performance of our approach was demonstrated by predicting the known allosteric site of the small molecule MDL-801 in nicotinamide dinucleotide (NAD⁺)-dependent protein lysine deacetylase sirtuin 6 (Sirt6). A potential novel cryptic allosteric site located around the L116, R119, and S120 residues within the dynamic ensemble of Sirt6 was identified. The allosteric effect of the predicted site was further quantified and validated using both computational and experimental approaches. This study proposed a state-of-the-art computational pipeline for detecting allosteric sites based on reversed allosteric communication. This method enabled the identification of a previously uncharacterized potential cryptic allosteric site on Sirt6, which provides a starting point for allosteric drug design that can aid the identification of candidate pockets in other therapeutic targets.

Using reversed allosteric communication, we performed MD simulations, MSMs, and mutagenesis experiments, to discover allosteric sites. It reproduced the known allosteric site for MDL-801 on Sirt6 and uncovered a novel cryptic allosteric Pocket X.