Design of Libraries Targeting Protein-Protein Interfaces

Fluorescent p53 helix mimetics pairing anticancer and bioimaging properties

Fluorescent therapeutic molecules offer a unique platform to study cellular uptake and biological pathways of drug candidates. Inhibition of the p53-HDM2 protein complex with the reactivation of the p53 pathway leading to apoptosis is a promising way to overcome the barriers and challenges in cancer therapeutic design. Although p53 helix mimetics based on the 'hotspots' design using either helical or non-helical backbones are known, cell-permeable and biocompatible inherently fluorescent helix mimetics have not yet been described. We report theragnostic helix mimetics featuring both therapeutic and bioimaging properties in a cancer cell model for the first time. The solvatochromic phthalimide unit in the scaffold functions as a site to append the hotspot mimicking residues, helps in the intramolecular hydrogen bonding mediated pre-organization of side chains on one face, and importantly, exhibits intrinsic fluorescence. The design of the mimetics, synthesis, conformational studies, and molecular docking results are discussed. In vitro cytotoxicity studies were carried out on four cell lines: U87MG (human glioblastoma), A549 (human non-small cell lung cancer), MDA-MB-231 (human triple-negative breast cancer) and HEK293 (non-cancerous cell line). The molecules showed anticancer activity in the micromolar range. The fluorescence properties provided valuable insights into their cellular permeability, distribution, and selectivity towards cancer cells and can shed light on their mechanisms of action.

Construction of a synthetic methodology-based library and its application in identifying a GIT/PIX protein-protein interaction inhibitor

In recent years, the flourishing of synthetic methodology studies has provided concise access to numerous molecules with new chemical space. These compounds form a large library with unique scaffolds, but their application in hit discovery is not systematically evaluated. In this work, we establish a synthetic methodology-based compound library (SMBL), integrated with compounds obtained from our synthetic researches, as well as their virtual derivatives in significantly larger scale. We screen the library and identify small-molecule inhibitors to interrupt the protein-protein interaction (PPI) of GIT1/β-Pix complex, an unrevealed target involved in gastric cancer metastasis. The inhibitor 14-5-18 with a spiro[bicyclo[2.2.1]heptane-2,3'-indolin]-2'-one scaffold, considerably retards gastric cancer metastasis in vitro and in vivo. Since the PPI targets are considered undruggable as they are hard to target, the successful application illustrates the structural specificity of SMBL, demonstrating its potential to be utilized as compound source for more challenging targets.

Fast Rescoring Protocols to Improve the Performance of Structure-Based Virtual Screening Performed on Protein-Protein Interfaces

Protein-protein interactions (PPIs) are attractive targets for drug design because of their essential role in numerous cellular processes and disease pathways. However, in general, PPIs display exposed binding pockets at the interface, and as such, have been largely unexploited for therapeutic interventions with low-molecular weight compounds. Here, we used docking and various rescoring strategies in an attempt to recover PPI inhibitors from a set of active and inactive molecules for 11 targets collected in ChEMBL and PubChem. Our focus is on the screening power of the various developed protocols and on using fast approaches so as to be able to apply such a strategy to the screening of ultralarge libraries in the future. First, we docked compounds into each target using the fast "pscreen" mode of the structure-based virtual screening (VS) package Surflex. Subsequently, the docking poses were postprocessed to derive a set of 3D topological descriptors: (i) shape similarity and (ii) interaction fingerprint similarity with a co-crystallized inhibitor, (iii) solvent-accessible surface area, and (iv) extent of deviation from the geometric center of a reference inhibitor. The derivatized descriptors, together with descriptor-scaled scoring functions, were utilized to investigate possible impacts on VS performance metrics. Moreover, four standalone scoring functions, RF-Score-VS (machine-learning), DLIGAND2 (knowledge-based), Vinardo (empirical), and X-SCORE (empirical), were employed to rescore the PPI compounds. Collectively, the results indicate that the topological scoring algorithms could be valuable both at a global level, with up to 79% increase in areas under the receiver operating characteristic curve for some targets, and in early stages, with up to a 4-fold increase in enrichment factors at 1% of the screened collections. Outstandingly, DLIGAND2 emerged as the best scoring function on this data set, outperforming all rescoring techniques in terms of VS metrics. The described methodology could help in the rational design of small-molecule PPI inhibitors and has direct applications in many therapeutic areas, including cancer, CNS, and infectious diseases such as COVID-19.

A Million Crystal Structures: The Whole Is Greater than the Sum of Its Parts

The founding in 1965 of what is now called the Cambridge Structural Database (CSD) has reaped dividends in numerous and diverse areas of chemical research. Each of the million or so crystal structures in the database was solved for its own particular reason, but collected together, the structures can be reused to address a multitude of new problems. In this Review, which is focused mainly on the last 10 years, we chronicle the contribution of the CSD to research into molecular geometries, molecular interactions, and molecular assemblies and demonstrate its value in the design of biologically active molecules and the solid forms in which they are delivered. Its potential in other commercially relevant areas is described, including gas storage and delivery, thin films, and (opto)electronics. The CSD also aids the solution of new crystal structures. Because no scientific instrument is without shortcomings, the limitations of CSD research are assessed. We emphasize the importance of maintaining database quality: notwithstanding the arrival of big data and machine learning, it remains perilous to ignore the principle of garbage in, garbage out. Finally, we explain why the CSD must evolve with the world around it to ensure it remains fit for purpose in the years ahead.

Synthesis of Terpyridines: Simple Reactions-What Could Possibly Go Wrong?

The preparation of 24-functionalized 12,22:26,32-terpyridines (4'-functionalized 3,2:6',3''-terpyridines) by the reaction of three 4-alkoxybenzaldehydes with 3-acetylpyridine and ammonia was investigated; under identical reaction conditions, two (R = nC4H9, C2H5) gave the expected products whereas a third (R = nC3H7) gave only a cyclohexanol derivative derived from the condensation of three molecules of 3-acetylpyridine with two of 4-(n-propoxy)benzaldehyde. A comprehensive survey of ''unexpected'' products from reactions of ArCOCH3 derivatives with aromatic aldehydes is presented. Three different types of alternative product are identified.

Homo- and Heterodimerization of Proteins in Cell Signaling: Inhibition and Drug Design

Protein dimerization controls many physiological processes in the body. Proteins form homo-, hetero-, or oligomerization in the cellular environment to regulate the cellular processes. Any deregulation of these processes may result in a disease state. Protein-protein interactions (PPIs) can be inhibited by antibodies, small molecules, or peptides, and inhibition of PPI has therapeutic value. PPI drug discovery research has steadily increased in the last decade, and a few PPI inhibitors have already reached the pharmaceutical market. Several PPI inhibitors are in clinical trials. With advancements in structural and molecular biology methods, several methods are now available to study protein homo- and heterodimerization and their inhibition by drug-like molecules. Recently developed methods to study PPI such as proximity ligation assay and enzyme-fragment complementation assay that detect the PPI in the cellular environment are described with examples. At present, the methods used to design PPI inhibitors can be classified into three major groups: (1) structure-based drug design, (2) high-throughput screening, and (3) fragment-based drug design. In this chapter, we have described some of the experimental methods to study PPIs and their inhibition. Examples of homo- and heterodimers of proteins, their structural and functional aspects, and some of the inhibitors that have clinical importance are discussed. The design of PPI inhibitors of epidermal growth factor receptor heterodimers and CD2-CD58 is discussed in detail.

Natural products used as a chemical library for protein-protein interaction targeted drug discovery

Protein-protein interactions (PPIs), which are essential for cellular processes, have been recognized as attractive therapeutic targets. Therefore, the construction of a PPI-focused chemical library is an inevitable necessity for future drug discovery. Natural products have been used as traditional medicines to treat human diseases for millennia; in addition, their molecular scaffolds have been used in diverse approved drugs and drug candidates. The recent discovery of the ability of natural products to inhibit PPIs led us to use natural products as a chemical library for PPI-targeted drug discovery. In this study, we collected natural products (NPDB) from non-commercial and in-house databases to analyze their similarities to small-molecule PPI inhibitors (iPPIs) and FDA-approved drugs by using eight molecular descriptors. Then, we evaluated the distribution of NPDB and iPPIs in the chemical space, represented by the molecular fingerprint and molecular scaffolds, to identify the promising scaffolds, which could interfere with PPIs. To investigate the ability of natural products to inhibit PPI targets, molecular docking was used. Then, we predicted a set of high-potency natural products by using the iPPI-likeness score based on a docking score-weighted model. These selected natural products showed high binding affinities to the PPI target, namely XIAP, which were validated in an in vitro experiment. In addition, the natural products with novel scaffolds might provide a promising starting point for further medicinal chemistry developments. Overall, our study shows the potency of natural products in targeting PPIs, which might help in the design of a PPI-focused chemical library for future drug discovery.

Targeting the Genome-Stability Hub Ctf4 by Stapled-Peptide Design

The exploitation of synthetic lethality by small-molecule targeting of pathways that maintain genomic stability is an attractive chemotherapeutic approach. The Ctf4/AND-1 protein hub, which links DNA replication, repair, and chromosome segregation, represents a novel target for the synthetic lethality approach. Herein, we report the design, optimization, and validation of double-click stapled peptides encoding the Ctf4-interacting peptide (CIP) of the replicative helicase subunit Sld5. By screening stapling positions in the Sld5 CIP, we identified an unorthodox i,i+6 stapled peptide with improved, submicromolar binding to Ctf4. The mode of interaction with Ctf4 was confirmed by a crystal structure of the stapled Sld5 peptide bound to Ctf4. The stapled Sld5 peptide was able to displace the Ctf4 partner DNA polymerase α from the replisome in yeast extracts. Our study provides proof-of-principle evidence for the development of small-molecule inhibitors of the human CTF4 orthologue AND-1.

Imbalance in chemical space: How to facilitate the identification of protein-protein interaction inhibitors

Protein-protein interactions (PPIs) play vital roles in life and provide new opportunities for therapeutic interventions. In this large data analysis, 3,300 inhibitors of PPIs (iPPIs) were compared to 17 reference datasets of collectively ~566,000 compounds (including natural compounds, existing drugs, active compounds on conventional targets, etc.) using a chemoinformatics approach. Using this procedure, we showed that comparable classes of PPI targets can be formed using either the similarity of their ligands or the shared properties of their binding cavities, constituting a proof-of-concept that not only can binding pockets be used to group PPI targets, but that these pockets certainly condition the properties of their corresponding ligands. These results demonstrate that matching regions in both chemical space and target space can be found. Such identified classes of targets could lead to the design of PPI-class-specific chemical libraries and therefore facilitate the development of iPPIs to the stage of drug candidates.

An Intriguing Correlation Based on the Superimposition of Residue Pairs with Inhibitors that Target Protein-Protein Interfaces

Druggable sites on protein-protein interfaces are difficult to predict. To survey inhibitor-binding sites onto which residues are superimposed at protein-protein interfaces, we analyzed publicly available information for 39 inhibitors that target the protein-protein interfaces of 8 drug targets. By focusing on the differences between residues that were superimposed with inhibitors and non-superimposed residues, we observed clear differences in the distances and changes in the solvent-accessible surface areas (∆SASA). Based on the observation that two or more residues were superimposed onto inhibitors in 37 (95%) of 39 protein-inhibitor complexes, we focused on the two-residue relationships. Application of a cross-validation procedure confirmed a linear negative correlation between the absolute value of the dihedral angle and the sum of the ∆SASAs of the residues. Finally, we applied the regression equation of this correlation to four inhibitors that bind to new sites not bound by the 39 inhibitors as well as additional inhibitors of different targets. Our results shed light on the two-residue correlation between the absolute value of the dihedral angle and the sum of the ∆SASA, which may be a useful relationship for identifying the key two-residues as potential targets of protein-protein interfaces.

Diversity-Oriented Synthesis of a Library of Star-Shaped 2H-Imidazolines

A library of star-shaped 2H-imidazolines has been synthesized via Debus-Radziszewski condensation from 1,2-diketones and ketone starting materials. Selective reduction of one imine group of the 2H-imidazole intermediate with LiAlH4 or catalytic flow hydrogenation furnished 2H-imidazolines, which could be conveniently diversified by reacting the amine N with electrophiles, resulting in a set of 21 amide-, carbamate-, urea-, and allylamine-containing products. In total, five points of diversification could be used, which allow the production of a set of functionally diverse compounds. The synthesis of acylated 2H-imidazolidines resulted in intrinsically labile compounds, which spontaneously degraded to acyclic derivatives, as shown for the reaction of 2H-imidazolidine with hexylisocyanate.

Overcoming Chemical, Biological, and Computational Challenges in the Development of Inhibitors Targeting Protein-Protein Interactions

Protein-protein interactions (PPIs) underlie the majority of biological processes, signaling, and disease. Approaches to modulate PPIs with small molecules have therefore attracted increasing interest over the past decade. However, there are a number of challenges inherent in developing small-molecule PPI inhibitors that have prevented these approaches from reaching their full potential. From target validation to small-molecule screening and lead optimization, identifying therapeutically relevant PPIs that can be successfully modulated by small molecules is not a simple task. Following the recent review by Arkin et al., which summarized the lessons learnt from prior successes, we focus in this article on the specific challenges of developing PPI inhibitors and detail the recent advances in chemistry, biology, and computation that facilitate overcoming them. We conclude by providing a perspective on the field and outlining four innovations that we see as key enabling steps for successful development of small-molecule inhibitors targeting PPIs.

In silico design of low molecular weight protein-protein interaction inhibitors: Overall concept and recent advances

Protein-protein interactions (PPIs) are carrying out diverse functions in living systems and are playing a major role in the health and disease states. Low molecular weight (LMW) "drug-like" inhibitors of PPIs would be very valuable not only to enhance our understanding over physiological processes but also for drug discovery endeavors. However, PPIs were deemed intractable by LMW chemicals during many years. But today, with the new experimental and in silico technologies that have been developed, about 50 PPIs have already been inhibited by LMW molecules. Here, we first focus on general concepts about protein-protein interactions, present a consensual view about ligandable pockets at the protein interfaces and the possibilities of using fast and cost effective structure-based virtual screening methods to identify PPI hits. We then discuss the design of compound collections dedicated to PPIs. Recent financial analyses of the field suggest that LMW PPI modulators could be gaining momentum over biologics in the coming years supporting further research in this area.

Targeting protein-protein interactions for drug discovery

Protein-protein interactions are associated with key activities and pathways in the cell, and in that regard are promising targets for drug discovery. However, in terms of small molecule drugs, this promise has not been realized. The physical nature of many protein-protein interaction surfaces renders them unable to support binding of small drug-like molecules. In addition, there are other unique hurdles presented by this class that make the drug development process difficult and risky. Nevertheless, success stories have begun to steadily appear in this field. These experiences are starting to provide general strategies and tools to help overcome the problems inherent in pursuing protein-protein interaction targets. These lessons should improve the rate of success as these systems are pursued in the future.

Rational design of protein–protein interaction inhibitors

Low molecular weight compound competing for the binding of the p53 tumor suppressor to the MDM2 oncoprotein.

A re-examination of the MDM2/p53 interaction leads to revised design criteria for novel inhibitors

The general model of epitope-type MDM2 inhibitor was developed based on the structural information on the complexes between MDM2 and various low molecular weight ligands found in the PDB database. Application of this model to our in-house library has led us to a new scaffold capable of interrupting protein-protein interactions. A synthetic library based on this and related scaffolds resulted in new classes of compounds that possess biochemical and cellular activity and good pharmacokinetic properties. We assume that such general approach to PPI inhibitors design may be useful for the development of inhibitors of various PPI types, including Bcl/XL.

Drug-Like Protein-Protein Interaction Modulators: Challenges and Opportunities for Drug Discovery and Chemical Biology

[Formula: see text] Fundamental processes in living cells are largely controlled by macromolecular interactions and among them, protein-protein interactions (PPIs) have a critical role while their dysregulations can contribute to the pathogenesis of numerous diseases. Although PPIs were considered as attractive pharmaceutical targets already some years ago, they have been thus far largely unexploited for therapeutic interventions with low molecular weight compounds. Several limiting factors, from technological hurdles to conceptual barriers, are known, which, taken together, explain why research in this area has been relatively slow. However, this last decade, the scientific community has challenged the dogma and became more enthusiastic about the modulation of PPIs with small drug-like molecules. In fact, several success stories were reported both, at the preclinical and clinical stages. In this review article, written for the 2014 International Summer School in Chemoinformatics (Strasbourg, France), we discuss in silico tools (essentially post 2012) and databases that can assist the design of low molecular weight PPI modulators (these tools can be found at www.vls3d.com). We first introduce the field of protein-protein interaction research, discuss key challenges and comment recently reported in silico packages, protocols and databases dedicated to PPIs. Then, we illustrate how in silico methods can be used and combined with experimental work to identify PPI modulators.

Focused chemical libraries--design and enrichment: an example of protein-protein interaction chemical space

One of the many obstacles in the development of new drugs lies in the limited number of therapeutic targets and in the quality of screening collections of compounds. In this review, we present general strategies for building target-focused chemical libraries with a particular emphasis on protein-protein interactions (PPIs). We describe the chemical spaces spanned by nine commercially available PPI-focused libraries and compare them to our 2P2I3D academic library, dedicated to orthosteric PPI modulators. We show that although PPI-focused libraries have been designed using different strategies, they share common subspaces. PPI inhibitors are larger and more hydrophobic than standard drugs; however, an effort has been made to improve the drug-likeness of focused chemical libraries dedicated to this challenging class of targets.

Oncogenic protein interfaces: small molecules, big challenges

Historically, targeting protein-protein interactions with small molecules was not thought possible because the corresponding interfaces were considered mostly flat and featureless and therefore 'undruggable'. Instead, such interactions were targeted with larger molecules, such as peptides and antibodies. However, the past decade has seen encouraging breakthroughs through the refinement of existing techniques and the development of new ones, together with the identification and exploitation of unexpected aspects of protein-protein interaction surfaces. In this Review, we describe some of the latest techniques to discover modulators of protein-protein interactions and how current drug discovery approaches have been adapted to successfully target these interfaces.

Exploiting structural information for drug-target assessment

The amount of known protein structures is continuously growing, exhibited in over 95,000 3D structures freely available via the PDB. Over the last decade, pharmaceutical research has sparked interest in computationally extracting information from this large data pool, resulting in a homology-driven knowledge transfer from annotated to new structures. Studying protein structures with respect to understanding and modulating their functional behavior means analyzing their centers of action. Therefore, the detection and description of potential binding sites on the protein surface is a major step towards protein classification and assessment. Subsequently, these representations can be incorporated to compare proteins, and to predict their druggability or function. Especially in the context of target identification and polypharmacology, automated tools for large-scale target comparisons are highly needed. In this article, developments for automated structure-based target assessment are reviewed and remaining challenges as well as future perspectives are discussed.

2P2I HUNTER: a tool for filtering orthosteric protein-protein interaction modulators via a dedicated support vector machine

Over the last 10 years, protein-protein interactions (PPIs) have shown increasing potential as new therapeutic targets. As a consequence, PPIs are today the most screened target class in high-throughput screening (HTS). The development of broad chemical libraries dedicated to these particular targets is essential; however, the chemical space associated with this 'high-hanging fruit' is still under debate. Here, we analyse the properties of 40 non-redundant small molecules present in the 2P2I database (http://2p2idb.cnrs-mrs.fr/) to define a general profile of orthosteric inhibitors and propose an original protocol to filter general screening libraries using a support vector machine (SVM) with 11 standard Dragon molecular descriptors. The filtering protocol has been validated using external datasets from PubChem BioAssay and results from in-house screening campaigns. This external blind validation demonstrated the ability of the SVM model to reduce the size of the filtered chemical library by eliminating up to 96% of the compounds as well as enhancing the proportion of active compounds by up to a factor of 8. We believe that the resulting chemical space identified in this paper will provide the scientific community with a concrete support to search for PPI inhibitors during HTS campaigns.