Protein–protein interactions as druggable targets: recent technological advances

Electrostatic Impact of Brefeldin A on Thiocyanate Probes Surrounding the Interface of Arf1-BFA-ARNO4M, a Protein-Drug-Protein Complex

Protein-protein interactions regulate many cellular processes, making them ideal drug candidates. Design of such drugs, however, is hindered by a lack of understanding of the factors that contribute to the interaction specificity. Specific protein-protein complexes possess both structural and electrostatic complementarity, and while structural complementarity of protein complexes has been extensively investigated, fundamental understanding of the complicated networks of electrostatic interactions at these interfaces is lacking, thus hindering the rational design of orthosterically binding small molecules. To better understand the electrostatic interactions at protein interfaces and how a small molecule could contribute to and fit within that environment, we used a model protein-drug-protein system, Arf1-BFA-ARNO4M, to investigate how small molecule brefeldin A (BFA) perturbs the Arf1-ARNO4M interface. By using nitrile probe labeled Arf1 sites and measuring vibrational Stark effects as well as temperature dependent infrared shifts, we measured changes in the electric field and hydrogen bonding at this interface upon BFA binding. At all five probe locations of Arf1, we found that the vibrational shifts resulting from BFA binding corroborate trends found in Poisson-Boltzmann calculations of surface potentials of Arf1-ARNO4M and Arf1-BFA-ARNO4M, where BFA contributes negative electrostatic potential to the protein interface. The data also corroborate previous hypotheses about the mechanism of interfacial binding and confirm that alternating patches of hydrophobic and polar interactions lead to BFA binding specificity. These findings demonstrate the impact of BFA on this protein-protein interface and have implications for the design of other interfacial drug candidates.

Drug discovery by targeting the protein-protein interactions involved in autophagy

Autophagy is a cellular process in which proteins and organelles are engulfed in autophagosomal vesicles and transported to the lysosome/vacuole for degradation. Protein-protein interactions (PPIs) play a crucial role at many stages of autophagy, which present formidable but attainable targets for autophagy regulation. Moreover, selective regulation of PPIs tends to have a lower risk in causing undesired off-target effects in the context of a complicated biological network. Thus, small-molecule regulators, including peptides and peptidomimetics, targeting the critical PPIs involved in autophagy provide a new opportunity for innovative drug discovery. This article provides general background knowledge of the critical PPIs involved in autophagy and reviews a range of successful attempts on discovering regulators targeting those PPIs. Successful strategies and existing limitations in this field are also discussed.

State of the art in protein-protein interactions within the fungi kingdom

Proteins rarely exert their function by themselves. Protein-protein interactions (PPIs) regulate virtually every biological process that takes place in a cell. Such interactions are targets for new therapeutic agents against all sorts of diseases, through the screening and design of a variety of inhibitors. Here we discuss several aspects of PPIs that contribute to prediction of protein function and drug discovery. As the high-throughput techniques continue to release biological data, targets for fungal therapeutics that rely on PPIs are being proposed worldwide. Computational approaches have reduced the time taken to develop new therapeutic approaches. The near future brings the possibility of developing new PPI and interaction network inhibitors and a revolution in the way we treat fungal diseases.

A review on structural mechanisms of protein-persistent organic pollutant (POP) interactions

With the advent of the industrial revolution, the accumulation of persistent organic pollutants (POPs) in the environment has become ubiquitous. POPs are halogen-containing organic molecules that accumulate, and remain in the environment for a long time, thus causing toxic effects in living organisms. POPs exhibit a high affinity towards biological macromolecules such as nucleic acids, proteins and lipids, causing genotoxicity and impairment of homeostasis in living organisms. Proteins are essential members of the biological assembly, as they stipulate all necessary processes for the survival of an organism. Owing to their stereochemical features, POPs and their metabolites form energetically favourable complexes with proteins, as supported by biological and dose-dependent toxicological studies. Although individual studies have reported the biological aspects of protein-POP interactions, no comprehensive study summarizing the structural mechanisms, thermodynamics and kinetics of protein-POP complexes is available. The current review identifies and classifies protein-POP interaction according to the structural and functional basis of proteins into five major protein targets, including digestive and other enzymes, serum proteins, transcription factors, transporters, and G-protein coupled receptors. Further, analysis detailing the molecular interactions and structural mechanism evidenced that H-bonds, van der Waals, and hydrophobic interactions essentially mediate the formation of protein-POP complexes. Moreover, interaction of POPs alters the protein conformation through kinetic and thermodynamic processes like competitive inhibition and allostery to modulate the cellular signalling processes, resulting in various pathological conditions such as cancers and inflammations. In summary, the review provides a comprehensive insight into the critical structural/molecular aspects of protein-POP interactions.

Artificial Intelligence and Machine Learning Technology Driven Modern Drug Discovery and Development

The discovery and advances of medicines may be considered as the ultimate relevant translational science effort that adds to human invulnerability and happiness. But advancing a fresh medication is a quite convoluted, costly, and protracted operation, normally costing USD ~2.6 billion and consuming a mean time span of 12 years. Methods to cut back expenditure and hasten new drug discovery have prompted an arduous and compelling brainstorming exercise in the pharmaceutical industry. The engagement of Artificial Intelligence (AI), including the deep-learning (DL) component in particular, has been facilitated by the employment of classified big data, in concert with strikingly reinforced computing prowess and cloud storage, across all fields. AI has energized computer-facilitated drug discovery. An unrestricted espousing of machine learning (ML), especially DL, in many scientific specialties, and the technological refinements in computing hardware and software, in concert with various aspects of the problem, sustain this progress. ML algorithms have been extensively engaged for computer-facilitated drug discovery. DL methods, such as artificial neural networks (ANNs) comprising multiple buried processing layers, have of late seen a resurgence due to their capability to power automatic attribute elicitations from the input data, coupled with their ability to obtain nonlinear input-output pertinencies. Such features of DL methods augment classical ML techniques which bank on human-contrived molecular descriptors. A major part of the early reluctance concerning utility of AI in pharmaceutical discovery has begun to melt, thereby advancing medicinal chemistry. AI, along with modern experimental technical knowledge, is anticipated to invigorate the quest for new and improved pharmaceuticals in an expeditious, economical, and increasingly compelling manner. DL-facilitated methods have just initiated kickstarting for some integral issues in drug discovery. Many technological advances, such as "message-passing paradigms", "spatial-symmetry-preserving networks", "hybrid de novo design", and other ingenious ML exemplars, will definitely come to be pervasively widespread and help dissect many of the biggest, and most intriguing inquiries. Open data allocation and model augmentation will exert a decisive hold during the progress of drug discovery employing AI. This review will address the impending utilizations of AI to refine and bolster the drug discovery operation.

Modeling the MreB-CbtA Interaction to Facilitate the Prediction and Design of Candidate Antibacterial Peptides

Protein-protein interactions (PPIs) have emerged as promising targets for PPI modulators as alternative drugs because they are essential for most biochemical processes in living organisms. In recent years, a spotlight has been put on the development of peptide-based PPI inhibitors as the next-generation therapeutics to combat antimicrobial resistance taking cognizance of protein-based PPI-modulators that interact with target proteins to inhibit function. Although protein-based PPI inhibitors are not effective therapeutic agents because of their high molecular weights, they could serve as sources for peptide-based pharmaceutics if the target-inhibitor complex is accessible and well characterized. The Escherichia coli (E. coli) toxin protein, CbtA, has been identified as a protein-based PPI modulator that binds to the bacterial actin homolog MreB leading to the perturbation of its polymerization dynamics; and consequently has been suggested to have antibacterial properties. Unfortunately, however, the three-dimensional structures of CbtA and the MreB-CbtA complex are currently not available to facilitate the optimization process of the pharmacological properties of CbtA. In this study, computer modeling strategies were used to predict key MreB-CbtA interactions to facilitate the design of antiMreB peptide candidates. A model of the E. coli CbtA was built using the trRosetta software and its stability was assessed through molecular dynamics (MD) simulations. The modeling and simulations data pointed to a model with reasonable quality and stability. Also, the HADDOCK software was used to predict a possible MreB-CbtA complex, which was characterized through MD simulations and compared with MreB-MreB dimmer. The results suggest that CbtA inhibits MreB through the competitive mechanism whereby CbtA competes with MreB monomers for the interprotofilament interface leading to interference with double protofilament formation. Additionally, by using the antiBP software to predict antibacterial peptides in CbtA, and the MreB-CbtA complex as the reference structure to determine important interactions and contacts, candidate antiMreB peptides were suggested. The peptide sequences could be useful in a rational antimicrobial peptide hybridization strategy to design novel antibiotics. All-inclusive, the data reveal the molecular basis of MreB inhibition by CbtA and can be incorporated in the design/development of the next-generation antibacterial peptides targeting MreB.

Intracellular Delivery of Antibodies for Selective Cell Signaling Interference

Many intracellular signaling events remain poorly characterized due to a general lack of tools to interfere with "undruggable" targets. Antibodies have the potential to elucidate intracellular mechanisms via targeted disruption of cell signaling cascades because of their ability to bind to a target with high specificity and affinity. However, due to their size and chemical composition, antibodies cannot innately cross the cell membrane, and thus access to the cytosol with these macromolecules has been limited. Here, we describe strategies for accessing the intracellular space with recombinant antibodies mediated by cationic lipid nanoparticles to selectively disrupt intracellular signaling events. Together, our results demonstrate the use of recombinantly produced antibodies, delivered at concentrations of 10 nM, to selectively interfere with signaling driven by a single posttranslational modification. Efficient intracellular delivery of engineered antibodies opens up possibilities for modulation of previously "undruggable" targets, including for potential therapeutic applications.

Novel peptide-based inhibitor for targeted inhibition of T cell function

Novel immunosuppressants are sought to overcome the side effects of currently used drugs. T cells play a central role in the functioning of the immune system; hence, drugs that specifically inhibit T cell function are expected to be better immunosuppressants with fewer side effects than the ones currently used. Peptides that interfere with crucial protein-protein interactions (PPIs) have been shown to influence cell physiology and have therapeutic potential. In this study, we designed a peptide, GVITAA, which specifically inhibits the function of lymphocyte-specific protein kinase (LCK), a signaling molecule that is mainly expressed in T cells and is responsible for positively regulating T cell function. Aspartate Histidine -Histidine Cysteine (DHHC21) -LCK is an important PPI present in T cells; DHHC21 interacts with LCK and targets the kinase to membrane rafts by adding a palmitoyl group. GVITAA is a ten amino acid peptide that interferes with the DHHC21-LCK interaction, prevents the membrane localization of LCK, and inhibits LCK-mediated initiation of complex signal transduction pathways required for T cell activation. In this study, we present evidence that the GVITAA peptide when conjugated with a cell-penetrating peptide-human immunodeficiency virus transactivator of transcription (TAT) and incubated with mouse T cells specifically inhibits LCK-mediated T cell receptor signaling, cytokine secretion, and T cell proliferation. This peptide does not affect other non-T cell functions and is non-toxic. A similar strategy was also tested and demonstrated in human peripheral T cells.

Targeting small GTPases and their downstream pathways with intracellular macromolecule binders to define alternative therapeutic strategies in cancer

The RAS superfamily of small GTPases regulates major physiological cellular processes. Mutation or deregulation of these small GTPases, their regulators and/or their effectors are associated with many diseases including cancer. Hence, targeting these classes of proteins is an important therapeutic strategy in cancer. This has been recently achieved with the approval of the first KRASG12C covalent inhibitors for the clinic. However, many other mutants and small GTPases are still considered as 'undruggable' with small molecule inhibitors because of a lack of well-defined pocket(s) at their surface. Therefore, alternative therapeutic strategies have been developed to target these proteins. In this review, we discuss the use of intracellular antibodies and derivatives - reagents that bind their antigen inside the cells - for the discovery of novel inhibitory mechanisms, targetable features and therapeutic strategies to inhibit small GTPases and their downstream pathways. These reagents are also versatile tools used to better understand the biological mechanisms regulated by small GTPases and to accelerate the drug discovery process.

Mapping, Structure and Modulation of PPI

Because of the key relevance of protein–protein interactions (PPI) in diseases, the modulation of protein-protein complexes is of relevant clinical significance. The successful design of binding compounds modulating PPI requires a detailed knowledge of the involved protein-protein system at molecular level, and investigation of the structural motifs that drive the association of the proteins at the recognition interface. These elements represent hot spots of the protein binding free energy, define the complex lifetime and possible modulation strategies. Here, we review the advanced technologies used to map the PPI involved in human diseases, to investigate the structure-function features of protein complexes, and to discover effective ligands that modulate the PPI for therapeutic intervention.

A cell permeable bimane-constrained PCNA-interacting peptide

The human sliding clamp protein known as proliferating cell nuclear antigen (PCNA) orchestrates DNA-replication and -repair and as such is an ideal therapeutic target for proliferative diseases, including cancer. Peptides derived from the human p21 protein bind PCNA with high affinity via a 3₁₀-helical binding conformation and are known to shut down DNA-replication. Here, we present studies on short analogues of p21 peptides (143-151) conformationally constrained with a covalent linker between i, i + 4 separated cysteine residues at positions 145 and 149 to access peptidomimetics that target PCNA. The resulting macrocycles bind PCNA with K _D values ranging from 570 nM to 3.86 μM, with the bimane-constrained peptide 7 proving the most potent. Subsequent X-ray crystallography and computational modelling studies of the macrocyclic peptides bound to PCNA indicated only the high-affinity peptide 7 adopted the classical 3₁₀-helical binding conformation. This suggests the 3₁₀-helical conformation is critical to high affinity PCNA binding, however NMR secondary shift analysis of peptide 7 revealed this secondary structure was not well-defined in solution. Peptide 7 is cell permeable and localised to the cell cytosol of breast cancer cells (MDA-MB-468), revealed by confocal microscopy showing blue fluorescence of the bimane linker. The inherent fluorescence of the bimane moiety present in peptide 7 allowed it to be directly imaged in the cell uptake assay, without attachment of an auxiliary fluorescent tag. This highlights a significant benefit of using a bimane constraint to access conformationally constrained macrocyclic peptides. This study identifies a small peptidomimetic that binds PCNA with higher affinity than previous reported p21 macrocycles, and is cell permeable, providing a significant advance toward development of a PCNA inhibitor for therapeutic applications.

Machine Learning in Drug Discovery: A Review

This review provides the feasible literature on drug discovery through ML tools and techniques that are enforced in every phase of drug development to accelerate the research process and deduce the risk and expenditure in clinical trials. Machine learning techniques improve the decision-making in pharmaceutical data across various applications like QSAR analysis, hit discoveries, de novo drug architectures to retrieve accurate outcomes. Target validation, prognostic biomarkers, digital pathology are considered under problem statements in this review. ML challenges must be applicable for the main cause of inadequacy in interpretability outcomes that may restrict the applications in drug discovery. In clinical trials, absolute and methodological data must be generated to tackle many puzzles in validating ML techniques, improving decision-making, promoting awareness in ML approaches, and deducing risk failures in drug discovery.

Identification of the key target profiles underlying the drugs of narrow therapeutic index for treating cancer and cardiovascular disease

An appropriate therapeutic index is crucial for drug discovery and development since narrow therapeutic index (NTI) drugs with slight dosage variation may induce severe adverse drug reactions or potential treatment failure. To date, the shared characteristics underlying the targets of NTI drugs have been explored by several studies, which have been applied to identify potential drug targets. However, the association between the drug therapeutic index and the related disease has not been dissected, which is important for revealing the NTI drug mechanism and optimizing drug design. Therefore, in this study, two classes of disease (cancers and cardiovascular disorders) with the largest number of NTI drugs were selected, and the target property of the corresponding NTI drugs was analyzed. By calculating the biological system profiles and human protein–protein interaction (PPI) network properties of drug targets and adopting an AI-based algorithm, differentiated features between two diseases were discovered to reveal the distinct underlying mechanisms of NTI drugs in different diseases. Consequently, ten shared features and four unique features were identified for both diseases to distinguish NTI from NNTI drug targets. These computational discoveries, as well as the newly found features, suggest that in the clinical study of avoiding narrow therapeutic index in those diseases, the ability of target to be a hub and the efficiency of target signaling in the human PPI network should be considered, and it could thus provide novel guidance in the drug discovery and clinical research process and help to estimate the drug safety of cancer and cardiovascular disease.

Recent advances in β-catenin/BCL9 protein-protein interaction inhibitors

Wnt/β-catenin signaling is crucial both in normal embryonic development and throughout the life of an organism. Moreover, aberrant Wnt signaling has been associated with various diseases, especially cancer and fibrosis. Recent research suggests that direct targeting of the β-catenin/BCL9 protein-protein interaction (PPI) is a promising strategy to block the Wnt pathway. Progress in understanding the cocrystalline complex and mechanism of action of the β-catenin/BCL9 interaction facilitates the discovery process of its inhibitors, but only a few inhibitors have been reported. In this review, the discovery and development of β-catenin/BCL9 PPI inhibitors in the areas of drug design, structure-activity relationships and biological and biochemical properties are summarized. In addition, perspectives for the future development of β-catenin/BCL9 PPI inhibitors are explored.

A cell-based screening method using an intracellular antibody for discovering small molecules targeting the translocation protein LMO2

Intracellular antibodies are tools that can be used directly for target validation by interfering with properties like protein-protein interactions. An alternative use of intracellular antibodies in drug discovery is developing small-molecule surrogates using antibody-derived (Abd) technology. We previously used this strategy with an in vitro competitive surface plasmon resonance method that relied on high-affinity antibody fragments to obtain RAS-binding compounds. We now describe a novel implementation of the Abd method with a cell-based intracellular antibody-guided screening method that we have applied to the chromosomal translocation protein LMO2. We have identified a chemical series of anti-LMO2 Abd compounds that bind at the same LMO2 location as the inhibitory anti-LMO2 intracellular antibody combining site. Intracellular antibodies could therefore be used in cell-based screens to identify chemical surrogates of their binding sites and potentially be applied to any challenging proteins, such as transcription factors that have been considered undruggable.

The androgen receptor/filamin A complex as a target in prostate cancer microenvironment

Prostate cancer represents the major cause of cancer-related death in men and patients frequently develop drug-resistance and metastatic disease. Most studies focus on hormone-resistance mechanisms related to androgen receptor mutations or to the acquired property of prostate cancer cells to over-activate signaling pathways. Tumor microenvironment plays a critical role in prostate cancer progression. However, the mechanism involving androgen/androgen receptor signaling in cancer associated fibroblasts and consequences for prostate cancer progression still remains elusive. We now report that prostate cancer associated fibroblasts express a transcriptional-incompetent androgen receptor. Upon androgen challenging, the receptor co-localizes with the scaffold protein filamin A in the extra-nuclear compartment of fibroblasts, thus mediating their migration and invasiveness. Cancer-associated fibroblasts move towards epithelial prostate cancer cells in 2D and 3D cultures, thereby inducing an increase of the prostate cancer organoid size. Androgen enhances both these effects through androgen receptor/filamin A complex assembly in cancer-associated fibroblasts. An androgen receptor-derived stapled peptide, which disrupts the androgen receptor/filamin A complex assembly, abolishes the androgen-dependent migration and invasiveness of cancer associated fibroblasts. Notably, the peptide impairs the androgen-induced invasiveness of CAFs in 2D models and reduces the overall tumor area in androgen-treated 3D co-culture. The androgen receptor in association with β1 integrin and membrane type-matrix metalloproteinase 1 activates a protease cascade triggering extracellular matrix remodeling. The peptide also impairs the androgen activation of this cascade. This study offers a potential new marker, the androgen receptor/filamin A complex, and a new therapeutic approach targeting intracellular pathways activated by the androgen/androgen receptor axis in prostate cancer-associated fibroblasts. Such a strategy, alone or in combination with conventional therapies, may allow a more efficient treatment of prostate cancer.

The Discovery of a Putative Allosteric Site in the SARS-CoV-2 Spike Protein Using an Integrated Structural/Dynamic Approach

SARS-CoV-2 has caused the largest pandemic of the twenty-first century (COVID-19), threatening the life and economy of all countries in the world. The identification of novel therapies and vaccines that can mitigate or control this global health threat is among the most important challenges facing biomedical sciences. To construct a long-term strategy to fight both SARS-CoV-2 and other possible future threats from coronaviruses, it is critical to understand the molecular mechanisms underlying the virus action. The viral entry and associated infectivity stems from the formation of the SARS-CoV-2 spike protein complex with angiotensin-converting enzyme 2 (ACE2). The detection of putative allosteric sites on the viral spike protein molecule can be used to elucidate the molecular pathways that can be targeted with allosteric drugs to weaken the spike-ACE2 interaction and, thus, reduce viral infectivity. In this study, we present the results of the application of different computational methods aimed at detecting allosteric sites on the SARS-CoV-2 spike protein. The adopted tools consisted of the protein contact networks (PCNs), SEPAS (Affinity by Flexibility), and perturbation response scanning (PRS) based on elastic network modes. All of these methods were applied to the ACE2 complex with both the SARS-CoV2 and SARS-CoV spike proteins. All of the adopted analyses converged toward a specific region (allosteric modulation region [AMR]), present in both complexes and predicted to act as an allosteric site modulating the binding of the spike protein with ACE2. Preliminary results on hepcidin (a molecule with strong structural and sequence with AMR) indicated an inhibitory effect on the binding affinity of the spike protein toward the ACE2 protein.

Polyglutamine spinocerebellar ataxias: emerging therapeutic targets

INTRODUCTION

Six of the most frequent dominantly inherited spinocerebellar ataxias (SCAs) worldwide - SCA1, SCA2, SCA3, SCA6, SCA7, and SCA17 - are caused by an expansion of a polyglutamine (polyQ) tract in the corresponding proteins. While the identification of the causative mutation has advanced knowledge on the pathogenesis of polyQ SCAs, effective therapeutics able to mitigate the severe clinical manifestation of these highly incapacitating disorders are not yet available.

AREAS COVERED

This review provides a comprehensive and critical perspective on well-established and emerging therapeutic targets for polyQ SCAs; it aims to inspire prospective drug discovery efforts.

EXPERT OPINION

The landscape of polyQ SCAs therapeutic targets and strategies includes (1) the mutant genes and proteins themselves, (2) enhancement of endogenous protein quality control responses, (3) abnormal protein-protein interactions of the mutant proteins, (4) disturbed neuronal function, (5) mitochondrial function, energy availability and oxidative stress, and (6) glial dysfunction, growth factor or hormone imbalances. Challenges include gaining a clearer definition of therapeutic targets for the drugs in clinical development, the discovery of novel drug-like molecules for challenging key targets, and the attainment of a stronger translation of preclinical findings to the clinic.

Antibody-protein binding and conformational changes: identifying allosteric signalling pathways to engineer a better effector response

Numerous monoclonal antibodies have been developed successfully for the treatment of various diseases. Nevertheless, the development of biotherapeutic antibodies is complex, expensive, and time-consuming, and to facilitate this process, careful structural analysis beyond the antibody binding site is required to develop a more efficacious antibody. In this work, we focused on protein antigens, since they induce the largest antibody changes, and provide interesting cases to compare and contrast. The structures of 15 anti-protein antibodies were analysed to compare the antigen-bound/unbound forms. Surprisingly, three different classes of binding-induced changes were identified. In class (B1), the antigen binding fragment distorted significantly, and we found changes in the loop region of the heavy chain's constant domain; this corresponds well with expected allosteric movements. In class (B2), we found changes in the same loop region without the overall distortion. In class (B3), these changes did not present, and only local changes at the complementarity determining regions were found. Consequently, structural analysis of antibodies is crucial for therapeutic development. Careful evaluation of allosteric movements must be undertaken to develop better effector responses, especially during the transformation of these antibodies from small fragments at the discovery stage to full antibodies at the subsequent development stages.

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.

Applying Antibodies Inside Cells: Principles and Recent Advances in Neurobiology, Virology and Oncology

To interfere with cell function, many scientists rely on methods that target DNA or RNA due to the ease with which they can be applied. Proteins are usually the final executors of function but are targeted only indirectly by these methods. Recent advances in targeted degradation of proteins based on proteolysis-targeting chimaeras (PROTACs), ubiquibodies, deGradFP (degrade Green Fluorescent Protein) and other approaches have demonstrated the potential of interfering directly at the protein level for research and therapy. Proteins can be targeted directly and very specifically by antibodies, but using antibodies inside cells has so far been considered to be challenging. However, it is possible to deliver antibodies or other proteins into the cytosol using standard laboratory equipment. Physical methods such as electroporation have been demonstrated to be efficient and validated thoroughly over time. The expression of intracellular antibodies (intrabodies) inside cells is another way to interfere with intracellular targets at the protein level. Methodological strategies to target the inside of cells with antibodies, including delivered antibodies and expressed antibodies, as well as applications in the research areas of neurobiology, viral infections and oncology, are reviewed here. Antibodies have already been used to interfere with a wide range of intracellular targets. Disease-related targets included proteins associated with neurodegenerative diseases such as Parkinson's disease (α-synuclein), Alzheimer's disease (amyloid-β) or Huntington's disease (mutant huntingtin [mHtt]). The applications of intrabodies in the context of viral infections include targeting proteins associated with HIV (e.g. HIV1-TAT, Rev, Vif, gp41, gp120, gp160) and different oncoviruses such as human papillomavirus (HPV), hepatitis B virus (HBV), hepatitis C virus (HCV) and Epstein-Barr virus, and they have been used to interfere with various targets related to different processes in cancer, including oncogenic pathways, proliferation, cell cycle, apoptosis, metastasis, angiogenesis or neo-antigens (e.g. p53, human epidermal growth factor receptor-2 [HER2], signal transducer and activator of transcription 3 [STAT3], RAS-related RHO-GTPase B (RHOB), cortactin, vascular endothelial growth factor receptor 2 [VEGFR2], Ras, Bcr-Abl). Interfering at the protein level allows questions to be addressed that may remain unanswered using alternative methods. This review addresses why direct targeting of proteins allows unique insights, what is currently feasible in vitro, and how this relates to potential therapeutic applications.

Beclin 1-ATG14L Protein-Protein Interaction Inhibitor Selectively Inhibits Autophagy through Disruption of VPS34 Complex I

Autophagy, a catabolic recycling process, has been implicated as a critical pathway in cancer. Its role in maintaining cellular homeostasis helps to nourish hypoxic, nutrient-starved tumors and protects them from chemotherapy-induced death. Recent efforts to target autophagy in cancer have focused on kinase inhibition, which has led to molecules that lack specificity due to the multiple roles of key kinases in this pathway. For example, the lipid kinase VPS34 is present in two multiprotein complexes responsible for the generation of phosphatidylinositol-3-phosphate. Complex I generates the autophagosome, and Complex II is crucial for endosomal trafficking. Molecules targeting VPS34 inhibit both complexes, which inhibits autophagy but causes undesirable defects in vesicle trafficking. The lack of specific autophagy modulators has limited the utility of autophagy inhibition as a therapeutic strategy. We hypothesize that disruption of the Beclin 1-ATG14L protein-protein interaction, which is required for the formation, proper localization, and function of VPS34 Complex I but not Complex II, will disrupt Complex I formation and selectively inhibit autophagy. To this end, a high-throughput, cellular NanoBRET assay was developed targeting this interaction. An initial screen of 2560 molecules yielded 19 hits that effectively disrupted the interaction, and it was confirmed that one hit disrupted VPS34 Complex I formation and inhibited autophagy. In addition, the molecule did not disrupt the Beclin 1-UVRAG interaction, critical for VPS34 Complex II, and thus had little impact on vesicle trafficking. This molecule is a promising new tool that is critical for understanding how modulation of the Beclin 1-ATG14L interaction affects autophagy. More broadly, its discovery demonstrates that targeting protein-protein interactions found within the autophagy pathway is a viable strategy for the discovery of autophagy-specific probes and therapeutics.

Microglial Drug Targets in AD: Opportunities and Challenges in Drug Discovery and Development

Alzheimer’s disease (AD) is a large and increasing unmet medical need with no disease-modifying treatment currently available. Genetic evidence from genome-wide association studies (GWASs) and gene network analysis has clearly revealed a key role of the innate immune system in the brain, of which microglia are the most important element. Single-nucleotide polymorphisms (SNPs) in genes predominantly expressed in microglia have been associated with altered risk of developing AD. Furthermore, microglia-specific pathways are affected on the messenger RNA (mRNA) expression level in post-mortem AD tissue and in mouse models of AD. Together these findings have increased the interest in microglia biology, and numerous scientific reports have proposed microglial molecules and pathways as drug targets for AD. Target identification and validation are generally the first steps in drug discovery. Both target validation and drug lead identification for central nervous system (CNS) targets and diseases entail additional significant obstacles compared to peripheral targets and diseases. This makes CNS drug discovery, even with well-validated targets, challenging. In this article, we will illustrate the special challenges of AD drug discovery by discussing the viability/practicality of possible microglia drug targets including cluster of differentiation 33 (CD33), K_Ca3.1, kynurenines, ionotropic P2 receptor 7 (P2X7), programmed death-1 (PD-1), Toll-like receptors (TLRs), and triggering receptor expressed in myeloid cells 2 (TREM2).

Protein-protein interactions in bacteria: a promising and challenging avenue towards the discovery of new antibiotics

Antibiotics are potent pharmacological weapons against bacterial infections; however, the growing antibiotic resistance of microorganisms is compromising the efficacy of the currently available pharmacotherapies. Even though antimicrobial resistance is not a new problem, antibiotic development has failed to match the growth of resistant pathogens and hence, it is highly critical to discover new anti-infective drugs with novel mechanisms of action which will help reducing the burden of multidrug-resistant microorganisms. Protein–protein interactions (PPIs) are involved in a myriad of vital cellular processes and have become an attractive target to treat diseases. Therefore, targeting PPI networks in bacteria may offer a new and unconventional point of intervention to develop novel anti-infective drugs which can combat the ever-increasing rate of multidrug-resistant bacteria. This review describes the progress achieved towards the discovery of molecules that disrupt PPI systems in bacteria for which inhibitors have been identified and whose targets could represent an alternative lead discovery strategy to obtain new anti-infective molecules.

Targeted Intracellular Delivery of Antibodies: The State of the Art

A dominant area of antibody research is the extension of the use of this mighty experimental and therapeutic tool for the specific detection of molecules for diagnostics, visualization, and activity blocking. Despite the ability to raise antibodies against different proteins, numerous applications of antibodies in basic research fields, clinical practice, and biotechnology are restricted to permeabilized cells or extracellular antigens, such as membrane or secreted proteins. With the exception of small groups of autoantibodies, natural antibodies to intracellular targets cannot be used within living cells. This excludes the scope of a major class of intracellular targets, including some infamous cancer-associated molecules. Some of these targets are still not druggable via small molecules because of large flat contact areas and the absence of deep hydrophobic pockets in which small molecules can insert and perturb their activity. Thus, the development of technologies for the targeted intracellular delivery of antibodies, their fragments, or antibody-like molecules is extremely important. Various strategies for intracellular targeting of antibodies via protein-transduction domains or their mimics, liposomes, polymer vesicles, and viral envelopes, are reviewed in this article. The pitfalls, challenges, and perspectives of these technologies are discussed.

Advances and challenges in targeting IRF5, a key regulator of inflammation

Interferon regulatory factor 5 (IRF5) belongs to a family of transcription factors, originally implicated in antiviral responses and interferon production. However, studies conducted in different laboratories over the last decade have placed IRF5 as a central regulator of the inflammatory response. It has become clear that IRF5 contributes to the pathogenesis of many inflammatory and autoimmune diseases, such as rheumatoid arthritis, inflammatory bowel disease and systemic lupus erythematosus. Given the role of IRF5 in physiology and disease, IRF5 represents a potential therapeutic target. However, despite a significant interest from the pharmaceutical industry, inhibitors that interfere with the IRF5 pathway remain elusive. Here, we review the advances made by various studies in targeting multiple steps of signalling leading to IRF5 activation with their therapeutic potential, and the possible complications of such strategies are discussed.

Artificial intelligence in drug design

Thanks to the fast improvement of the computing power and the rapid development of the computational chemistry and biology, the computer-aided drug design techniques have been successfully applied in almost every stage of the drug discovery and development pipeline to speed up the process of research and reduce the cost and risk related to preclinical and clinical trials. Owing to the development of machine learning theory and the accumulation of pharmacological data, the artificial intelligence (AI) technology, as a powerful data mining tool, has cut a figure in various fields of the drug design, such as virtual screening, activity scoring, quantitative structure-activity relationship (QSAR) analysis, de novo drug design, and in silico evaluation of absorption, distribution, metabolism, excretion and toxicity (ADME/T) properties. Although it is still challenging to provide a physical explanation of the AI-based models, it indeed has been acting as a great power to help manipulating the drug discovery through the versatile frameworks. Recently, due to the strong generalization ability and powerful feature extraction capability, deep learning methods have been employed in predicting the molecular properties as well as generating the desired molecules, which will further promote the application of AI technologies in the field of drug design.

Inhibitors of protein-protein interactions (PPIs): an analysis of scaffold choices and buried surface area

Protein-protein interactions (PPI) were once considered 'undruggable', but clinical successes, driven by advanced methods in drug discovery, have challenged that notion. Here, we review the last three years of literature on PPI inhibitors to understand what is working and why. From the 66 recently reported PPI inhibitors, we found that the average molecular weight was significantly greater than 500Da, but that this trend was driven, in large part, by the contribution of peptide-based compounds. Despite differences in average molecular weight, we found that compounds based on small molecules or peptides were almost equally likely to be potent inhibitors (K_D<1μM). Finally, we found PPIs with buried surface area (BSA) less than 2000Ų were more likely to be inhibited by small molecules, while PPIs with larger BSA values were typically inhibited by peptides. PPIs with BSA values over 4000Ų seemed to create a particular challenge, especially for orthosteric small molecules. Thus, it seems important to choose the inhibitor scaffold based on the properties of the target interaction. Moreover, this survey suggests a (more nuanced) conclusion to the question of whether PPIs are good drug targets; namely, that some PPIs are readily 'druggable' given the right choice of scaffold, while others still seem to deserve the 'undruggable' moniker.

Molecular engineering solutions for therapeutic peptide delivery

Proteins and their interactions in and out of cells must be well-orchestrated for the healthy functioning and regulation of the body. Even the slightest disharmony can cause diseases. Therapeutic peptides are short amino acid sequences (generally considered <50 amino acids) that can naturally mimic the binding interfaces between proteins and thus, influence protein-protein interactions. Because of their fidelity of binding, peptides are a promising next generation of personalized medicines to reinstate biological harmony. Peptides as a group are highly selective, relatively safe, and biocompatible. However, they are also vulnerable to many in vivo pharmacologic barriers limiting their clinical translation. Current advances in molecular, chemical, and nanoparticle engineering are helping to overcome these previously insurmountable obstacles and improve the future of peptides as active and highly selective therapeutics. In this review, we focus on self-assembled vehicles as nanoparticles to carry and protect therapeutic peptides through this journey, and deliver them to the desired tissue.

Astrocytes and the Warning Signs of Intracerebral Hemorrhagic Stroke

Two decades into the two thousands, intracerebral hemorrhagic stroke (ICH) continues to reap lives across the globe. In the US, nearly 12,000 people suffer from ICH every year. Half of them survive, but many are left with permanent physical and cognitive disabilities, the severity of which depends on the location and broadness of the brain region affected by the hemorrhage. The ongoing efforts to identify risk factors for hemorrhagic stroke have been instrumental for the development of new medical practices to prevent, aid the recovery and reduce the risk of recurring ICH. Recent efforts approach the study of ICH from a different angle, providing information on how we can limit brain damage by manipulating astrocyte receptors. These results provide a novel understanding of how astrocytes contribute to brain injury and recovery from small ICH. Here, we discuss current knowledge on the risk factors and molecular pathology of ICH and the functional properties of astrocytes and their role in ICH. Last, we discuss candidate astrocyte receptors that may prove to be valuable therapeutic targets to treat ICH. Together, these findings provide basic and clinical scientists useful information for the future development of strategies to improve the detection of small ICH, limit brain damage, and prevent the onset of more severe episodes of brain hemorrhage.

Affimer proteins inhibit immune complex binding to FcγRIIIa with high specificity through competitive and allosteric modes of action

Protein-protein interactions are essential for the control of cellular functions and are critical for regulation of the immune system. One example is the binding of Fc regions of IgG to the Fc gamma receptors (FcγRs). High sequence identity (98%) between the genes encoding FcγRIIIa (expressed on macrophages and natural killer cells) and FcγRIIIb (expressed on neutrophils) has prevented the development of monospecific agents against these therapeutic targets. We now report the identification of FcγRIIIa-specific artificial binding proteins called "Affimer" that block IgG binding and abrogate FcγRIIIa-mediated downstream effector functions in macrophages, namely TNF release and phagocytosis. Cocrystal structures and molecular dynamics simulations have revealed the structural basis of this specificity for two Affimer proteins: One binds directly to the Fc binding site, whereas the other acts allosterically.

Intracellular immunization against HIV infection with an intracellular antibody that mimics HIV integrase binding to the cellular LEDGF protein

Preventing the protein-protein interaction of the cellular chromatin binding protein Lens Epithelium-Derived Growth Factor (LEDGF) and human immunodeficiency virus (HIV) integrase is an important possible strategy for anti-viral treatment for AIDS. We have used Intracellular Antibody Capture technology to isolate a single VH antibody domain that binds to LEDGF. The crystal structure of the LEDGF-VH complex reveals that the single domain antibody mimics the effect of binding of HIV integrase to LEDGF which is crucial for HIV propagation. CD4-expressing T cell lines were constructed to constitutively express the LEDGF-binding VH and these cells showed interference with HIV viral replication, assayed by virus capsid protein p24 production. Therefore, pre-conditioning cells to express antibody fragments confers effective intracellular immunization for preventing chronic viral replication and can be a way to prevent HIV spread in infected patients. This raises the prospect that intracellular immunization strategies that focus on cellular components of viral integrase protein interactions can be used to combat the problems associated with latent HIV virus re-emergence in patients. New genome editing development, such as using CRISPR/cas9, offer the prospect intracellularly immunized T cells in HIV+ patients.

Privileged Substructures to Modulate Protein-Protein Interactions

Given the difficulties to identify chemical probes that can modulate protein-protein interactions (PPIs), actors in the field have started to agree on the necessity to use PPI-tailored screening chemical collections. However, which type of scaffolds may promote the binding of compounds to PPI targets remains unclear. In this big data analysis, we have identified a list of privileged chemical substructures that are most often observed within inhibitors of PPIs. Using molecular frameworks as a way to perceive chemical substructures with the combination of an experimental and a machine-learning based predicted data set of iPPI compounds, we propose a list of privileged substructures in the form of scaffolds and chemical moieties that can be substantially chemically functionalized and do not present any toxicophore nor pan-assay interference (PAINS) alerts. We think that such chemical guidance will be valuable for medicinal chemists in their attempt to identify initial quality chemical probes on PPI targets.

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.

Intrinsic protein disorder in oncogenic KRAS signaling

How Ras, and in particular its most abundant oncogenic isoform K-Ras4B, is activated and signals in proliferating cells, poses some of the most challenging questions in cancer cell biology. In this paper, we ask how intrinsically disordered regions in K-Ras4B and its effectors help promote proliferative signaling. Conformational disorder allows spanning long distances, supports hinge motions, promotes anchoring in membranes, permits segments to fulfil multiple roles, and broadly is crucial for activation mechanisms and intensified oncogenic signaling. Here, we provide an overview illustrating some of the key mechanisms through which conformational disorder can promote oncogenesis, with K-Ras4B signaling serving as an example. We discuss (1) GTP-bound KRas4B activation through membrane attachment; (2) how farnesylation and palmitoylation can promote isoform functional specificity; (3) calmodulin binding and PI3K activation; (4) how Ras activates its RASSF5 cofactor, thereby stimulating signaling of the Hippo pathway and repressing proliferation; and (5) how intrinsically disordered segments in Raf help its attachment to the membrane and activation. Collectively, we provide the first inclusive review of the roles of intrinsic protein disorder in oncogenic Ras-driven signaling. We believe that a broad picture helps to grasp and formulate key mechanisms in Ras cancer biology and assists in therapeutic intervention.

Computational analysis of calculated physicochemical and ADMET properties of protein-protein interaction inhibitors

The modulation of PPIs by low molecular weight chemical compounds, particularly by orally bioavailable molecules, would be very valuable in numerous disease indications. However, it is known that PPI inhibitors (iPPIs) tend to have properties that are linked to poor Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) and in some cases to poor clinical outcomes. Previously reported in silico analyses of iPPIs have essentially focused on physicochemical properties but several other ADMET parameters would be important to assess. In order to gain new insights into the ADMET properties of iPPIs, computations were carried out on eight datasets collected from several databases. These datasets involve compounds targeting enzymes, GPCRs, ion channels, nuclear receptors, allosteric modulators, oral marketed drugs, oral natural product-derived marketed drugs and iPPIs. Several trends are reported that should assist the design and optimization of future PPI inhibitors, either for drug discovery endeavors or for chemical biology projects.

A precisely positioned chiral center in an i, i + 7 tether modulates the helicity of the backbone peptide

A chiral center of R absolute configuration at the γ-position to the C-terminal of a 10-membered tether could function to efficiently induce helicity of the backbone peptides.

Relaxin' the brain: a case for targeting the nucleus incertus network and relaxin-3/RXFP3 system in neuropsychiatric disorders

Relaxin‐3 has been proposed to modulate emotional–behavioural functions such as arousal and behavioural activation, appetite regulation, stress responses, anxiety, memory, sleep and circadian rhythm. The nucleus incertus (NI), in the midline tegmentum close to the fourth ventricle, projects widely throughout the brain and is the primary site of relaxin‐3 neurons. Over recent years, a number of preclinical studies have explored the function of the NI and relaxin‐3 signalling, including reports of mRNA or peptide expression changes in the NI in response to behavioural or pharmacological manipulations, effects of lesions or electrical or pharmacological manipulations of the NI, effects of central microinfusions of relaxin‐3 or related agonist or antagonist ligands on physiology and behaviour, and the impact of relaxin‐3 gene deletion or knockdown. Although these individual studies reveal facets of the likely functional relevance of the NI and relaxin‐3 systems for human physiology and behaviour, the differences observed in responses between species (e.g. rat vs. mouse), the clearly identified heterogeneity of NI neurons and procedural differences between laboratories are some of the factors that have prevented a precise understanding of their function. This review aims to draw attention to the current preclinical evidence available that suggests the relevance of the NI/relaxin‐3 system to the pathology and/or symptoms of certain neuropsychiatric disorders and to provide cognizant directions for future research to effectively and efficiently uncover its therapeutic potential.

Linked Articles

This article is part of a themed section on Recent Progress in the Understanding of Relaxin Family Peptides and their Receptors. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.10/issuetoc

New insights into transcriptional and leukemogenic mechanisms of AML1-ETO and E2A fusion proteins

BACKGROUND

Nearly 15% of acute myeloid leukemia (AML) cases are caused by aberrant expression of AML1-ETO, a fusion protein generated by the t(8;21) chromosomal translocation. Since its discovery, AML1-ETO has served as a prototype to understand how leukemia fusion proteins deregulate transcription to promote leukemogenesis. Another leukemia fusion protein, E2A-Pbx1, generated by the t(1;19) translocation, is involved in acute lymphoblastic leukemias (ALLs). While AML1-ETO and E2A-Pbx1 are structurally unrelated fusion proteins, we have recently shown that a common axis, the ETO/E-protein interaction, is involved in the regulation of both fusion proteins, underscoring the importance of studying protein-protein interactions in elucidating the mechanisms of leukemia fusion proteins.

OBJECTIVE

In this review, we aim to summarize these new developments while also providing a historic overview of the related early studies.

METHODS

A total of 218 publications were reviewed in this article, a majority of which were published after 2004.We also downloaded 3D structures of AML1-ETO domains from Protein Data Bank and provided a systematic summary of their structures.

RESULTS

By reviewing the literature, we summarized early and recent findings on AML1-ETO, including its protein-protein interactions, transcriptional and leukemogenic mechanisms, as well as the recently reported involvement of ETO family corepressors in regulating the function of E2A-Pbx1.

CONCLUSION

While the recent development in genomic and structural studies has clearly demonstrated that the fusion proteins function by directly regulating transcription, a further understanding of the underlying mechanisms, including crosstalk with other transcription factors and cofactors, and the protein-protein interactions in the context of native proteins, may be necessary for the development of highly targeted drugs for leukemia therapy.

Lipid raft-like liposomes used for targeted delivery of a chimeric entry-inhibitor peptide with anti-HIV-1 activity

The work reports the design and synthesis of a chimeric peptide that is composed of the peptide sequences of two entry inhibitors which target different sites of HIV-1 gp41. The chimeric peptide offers the advantage of targeting two gp41 regions simultaneously: the fusion peptide and the loop both of which are membrane active and participate in the membrane fusion process. We therefore use lipid raft-like liposomes as a tool to specifically direct the chimeric inhibitor peptide to the membrane domains where the HIV-1 envelope protein is located. Moreover, the liposomes that mimic the viral membrane composition protect the chimeric peptide against proteolytic digestion thereby increasing the stability of the peptide. The described liposome preparations are suitable nanosystems for managing hydrophobic entry-inhibitor peptides as putative therapeutics.

Biophysics in drug discovery: impact, challenges and opportunities

Over the past 25 years, biophysical technologies such as X-ray crystallography, nuclear magnetic resonance spectroscopy, surface plasmon resonance spectroscopy and isothermal titration calorimetry have become key components of drug discovery platforms in many pharmaceutical companies and academic laboratories. There have been great improvements in the speed, sensitivity and range of possible measurements, providing high-resolution mechanistic, kinetic, thermodynamic and structural information on compound-target interactions. This Review provides a framework to understand this evolution by describing the key biophysical methods, the information they can provide and the ways in which they can be applied at different stages of the drug discovery process. We also discuss the challenges for current technologies and future opportunities to use biophysical methods to solve drug discovery problems.

Predicting Protein-Protein Interactions Using BiGGER: Case Studies

The importance of understanding interactomes makes preeminent the study of protein interactions and protein complexes. Traditionally, protein interactions have been elucidated by experimental methods or, with lower impact, by simulation with protein docking algorithms. This article describes features and applications of the BiGGER docking algorithm, which stands at the interface of these two approaches. BiGGER is a user-friendly docking algorithm that was specifically designed to incorporate experimental data at different stages of the simulation, to either guide the search for correct structures or help evaluate the results, in order to combine the reliability of hard data with the convenience of simulations. Herein, the applications of BiGGER are described by illustrative applications divided in three Case Studies: (Case Study A) in which no specific contact data is available; (Case Study B) when different experimental data (e.g., site-directed mutagenesis, properties of the complex, NMR chemical shift perturbation mapping, electron tunneling) on one of the partners is available; and (Case Study C) when experimental data are available for both interacting surfaces, which are used during the search and/or evaluation stage of the docking. This algorithm has been extensively used, evidencing its usefulness in a wide range of different biological research fields.

New prospects for targeting telomerase beyond the telomere

Telomerase activity is responsible for the maintenance of chromosome end structures (telomeres) and cancer cell immortality in most human malignancies, making telomerase an attractive therapeutic target. The rationale for targeting components of the telomerase holoenzyme has been strengthened by accumulating evidence indicating that these molecules have extra-telomeric functions in tumour cell survival and proliferation. This Review discusses current knowledge of the biogenesis, structure and multiple functions of telomerase-associated molecules intertwined with recent advances in drug discovery approaches. We also describe the fertile ground available for the pursuit of next-generation small-molecule inhibitors of telomerase.

Personalized and targeted therapy of esophageal squamous cell carcinoma: an update

Esophageal squamous cell carcinoma (ESCC) is a deadly disease that requires extensive research. In this review, we update recent progress in the research area of targeted therapy for ESCC. SOX2 and its associated proteins (e.g., ΔNP63α), which regulate lineage survival of ESCC cells, are proposed as therapeutic targets. It is believed that targeting the lineage-survival mechanism may be more effective than targeting other mechanisms. With the advent of a new era of personalized targeted therapy, there is a need to move from the tumor-centric model into an organismic model.