Targeting protein-protein interactions with low molecular weight and short peptide modulators: insights on disease pathways and starting points for drug discovery.

INTRODUCTION: Protein-protein interactions (PPIs) have been often considered undruggable targets although they are attractive for the discovery of new therapeutics. The spread of artificial intelligence and machine learning complemented with experimental methods is likely to change the perspectives of protein-protein modulator research. Noteworthy, some novel low molecular weight (LMW) and short peptide modulators of PPIs are already in clinical trials for the treatment of relevant diseases. AREAS COVERED: This review focuses on the main molecular properties of protein-protein interfaces and on key concepts pertaining to the modulation of PPIs. The authors survey recently reported state-of-the-art methods dealing with the rational design of PPI modulators and highlight the role of several computer-based approaches. EXPERT OPINION: Interfering specifically with large protein interfaces is still an open challenge. The initial concerns about the unfavorable physicochemical properties of many of these modulators are nowadays less acute with several molecules lying beyond the rule of 5, orally available and successful in clinical trials. As the cost of biologics interfering with PPIs is very high, it would seem reasonable to put more effort, both in academia and the private sectors, on actively developing novel low molecular weight compounds and short peptides to perform this task.

ELIOT: A platform to navigate the E3 pocketome and aid the design of new PROTACs.

Proteolysis-targeting chimeras (PROTACs) are novel therapeutics for the treatment of human disease. They exploit the enormous potential of the E3 ligases, a class of proteins that mark a target protein for degradation via the ubiquitin-proteasome system. Despite the existence of several E3 ligase-related databases, the choice of the functioning ligase is limited to only 1.6% of those available, probably due to the fragmentary understanding of their structures and their known ligands; in fact, none of the existing databases report detailed studies covering their 3D structure or their pockets. Here, we report ELIOT (E3 LIgase pocketOme navigaTor), an accurate and complete platform containing the E3 ligase pocketome to enable navigation and selection of new E3 ligases and new ligands for the design of new PROTACs. All E3 ligase pockets were characterized with innovative 3D descriptors including their PROTAC-ability score, and similarity analyses between E3 pockets are presented. Tissue specificity and their degree of involvement in patients with specific cancer types are also annotated for each E3 ligase, enabling appropriate selection for the design of a PROTAC with improved specificity. All data are available at https://eliot.moldiscovery.com.

An Integrated Machine Learning Model To Spot Peptide Binding Pockets in 3D Protein Screening.

The prediction of peptide-protein binding sites is of utmost importance to tackle the onset of severe neurodegenerative diseases and cancer. In this work, we detail a novel machine learning model based on Linear Discriminant Analysis (LDA) demonstrating to be highly predictive in detecting the putative protein binding regions of small peptides. Starting from 439 high-quality pockets derived from peptide-protein crystallographic complexes, three sets of well-established peptide-binding regions were first selected through a Partitioning Around Medoids (PAM) clustering algorithm based on morphological and energetic 3D GRID-MIF molecular descriptors. Next, the best combination between all the putative interacting peptide pockets and related GRID-MIF scores was automatically explored by using the LDA-based protocol implemented in BioGPS. This approach proved successful to recognize the actual interacting peptide regions (that is, AUC = 0.86 and partial ROC enrichment at 5% of 0.48) from all the other pockets of the protein. Validated on two external collections sets, including 445 and 347 crystallographic peptide-protein complexes, our LDA-based model could be effective to further run peptide-protein virtual screening campaigns.

Exploring Ligand Binding Domain Dynamics in the NRs Superfamily.

Nuclear receptors (NRs) are transcription factors that play an important role in multiple diseases, such as cancer, inflammation, and metabolic disorders. They share a common structural organization composed of five domains, of which the ligand-binding domain (LBD) can adopt different conformations in response to substrate, agonist, and antagonist binding, leading to distinct transcription effects. A key feature of NRs is, indeed, their intrinsic dynamics that make them a challenging target in drug discovery. This work aims to provide a meaningful investigation of NR structural variability to outline a dynamic profile for each of them. To do that, we propose a methodology based on the computation and comparison of protein cavities among the crystallographic structures of NR LBDs. First, pockets were detected with the FLAPsite algorithm and then an "all against all" approach was applied by comparing each pair of pockets within the same sub-family on the basis of their similarity score. The analysis concerned all the detectable cavities in NRs, with particular attention paid to the active site pockets. This approach can guide the investigation of NR intrinsic dynamics, the selection of reference structures to be used in drug design and the easy identification of alternative binding sites.

Getting Insights into Structural and Energetic Properties of Reciprocal Peptide-Protein Interactions.

Peptide-protein interactions play a key role for many cellular and metabolic processes involved in the onset of largely spread diseases such as cancer and neurodegenerative pathologies. Despite the progress in the structural characterization of peptide-protein interfaces, the in-depth knowledge of the molecular details behind their interactions is still a daunting task. Here, we present the first comprehensive in silico morphological and energetic study of peptide binding sites by focusing on both peptide and protein standpoints. Starting from the PixelDB database, a nonredundant benchmark collection of high-quality 3D crystallographic structures of peptide-protein complexes, a classification analysis of the most representative categories based on the nature of each cocrystallized peptide has been carried out. Several interpretable geometrical and energetic descriptors have been computed both from peptide and target protein sides in the attempt to unveil physicochemical and structural causative correlations. Finally, we investigated the most frequent peptide-protein residue pairs at the binding interface and made extensive energetic analyses, based on GRID MIFs, with the aim to study the peptide affinity-enhancing interactions to be further exploited in rational drug design strategies.

Incidence and type of brain herniation associated with intracranial meningioma in dogs and cats.

The incidence of brain herniation (BH) in association with intracranial meningioma (ICM) in dogs and cats is poorly described. The aim of this study was to evaluate the rate and type of brain herniations in client-owned dogs and cats with ICMs and to determine the meningioma volume (MV) relative to cranial cavity volume (CCV). A retrospective magnetic resonance imaging (MRI) analysis study of 24 cats and 45 dogs with ICMs was conducted to ascertain the presence and characteristics of BH. MV and CCV were measured and their ratio was calculated for each animal. Correlations of MV/CCV with independent variables were analyzed. BH was encountered in 24/24 cats (100%) and 30/45 dogs (66.7%) with ICMs. In cats, the most frequent presentation was foramenal herniation (FMH; 23/24, 95.8%), followed by caudotentorial (CTH; 21/24, 87.5%) and subfalcine (SH; 18/24, 75.0%) herniation. In dogs, the most frequent presentation was SH (28/45; 62.2%), followed by CTH (9/45; 20%) and FMH (2/45; 4.4%). Relative to dogs, cats with ICM had greater incidences of FMH (P<0.001) and CTH (P<0.001). Mean MV/CCV ratio was higher in cats (0.098) than in dogs (0.038; P<0.001). The most common clinical sign of ICM was altered behavior in cats (43%, P<0.01) and seizures in dogs (74.4%, P<0.001). In conclusion, cats were found to be more likely than dogs to present FMH and CTH, with a proportionally greater neoplasia volume.

Clinical features of muscle cramp in 14 dogs.

BACKGROUND: Muscle cramps (MCs) are prolonged, involuntary, painful muscle contractions characterized by an acute onset and short duration, caused by peripheral nerve hyperactivity. OBJECTIVES: To provide a detailed description of the clinical features and diagnostic findings in dogs affected by MCs. ANIMALS: Fourteen dogs. METHODS: Multicenter retrospective case series. Cases were recruited by a call to veterinary neurologists working in referral practices. Medical records and videotapes were searched for dogs showing MCs. The follow-up was obtained by telephone communication with the owner and the referring veterinarian. RESULTS: Three patterns of presentation were identified depending on the number of affected limbs and presence/absence of migration of MCs to other limbs. In 9/14 (64%) of dogs, MCs were triggered by prompting the dogs to move. 8/14 (58%) dogs were overtly painful with 6/14 (42%) showing mild discomfort. The cause of MCs was hypocalcemia in 11/14 (79%) dogs: 9 dogs were affected by primary hypoparathyrodism, 1 dog by intestinal lymphoma and 1 dog by protein losing enteropathy. In 3/14 cases (21%) the cause was not identified, and all 3 dogs were German Shepherds. CONCLUSIONS AND CLINICAL IMPORTANCE: Muscle cramps can manifest in 1 of 3 clinical patterns. Muscle cramps are elicited when dogs are encouraged to move and do not always appear as painful events, showing in some cases only discomfort. The main cause of MCs in this study was hypocalcemia consequent to primary hypoparathyroidism. In dogs having MCs of unknown etiology, idiopathic disease or paroxysmal dyskinesia could not be ruled out.

Central nervous system metastasis of an intradural malignant peripheral nerve sheath tumor in a dog.

An 8-yr-old French Bulldog was presented with a non-ambulatory tetraparesis. Magnetic resonance showed an intradurally located mass at the level of the right second cervical nerve root. The mass was surgically removed and the dog was ambulatory within 4 d. A 10-mo post-surgical imaging follow-up revealed a recurrence of the primary mass and another intradural/intramedullary mass at the level of the first thoracic vertebral body. Overall histological features were suggestive of malignant peripheral nerve sheath tumor (MPNST) for both masses. Immunohistochemistry was found weak but diffusely positive for S-100 and neurono-specific enolase for both masses. A diagnosis of primary MPNST for the cervical mass and of metastasis for the thoracic mass was made, possibly disseminated via the subarachnoidal space. To our knowledge, the central nervous system metastasis of MPNSTs has not previously been reported in dogs. The clinician should be aware that these tumors, albeit rarely, can metastasize to the central nervous system.

Neurological abnormalities in 97 dogs with detectable pituitary masses.

Background: Pituitary tumours are common neoplasms of the sellar region in small animals. However, detailed information regarding the spectrum and severity of possible neurological signs are lacking. Objective: To retrospectively describe the neurological abnormalities in a population of dogs with a detectable pituitary mass (DPM) and relate them with the size of the mass and magnetic resonance imaging (MRI) signs of brain compression (BC). Client-owned dogs were included in the study if they had MRI showing a DPM and a detailed neurological examination. The neurological signs were evaluated in relation to the pituitary height/brain ratio (P:B ratio) and the presence/absence of brain compression. Results: Ninety-seven dogs were enrolled. Besides abnormal mentation and behaviour (77%), gait (61%) and cranial nerve abnormalities (44%), other unreported neurological signs observed included postural abnormalities (21%), pain and/or hyperesthesia (25%) and abnormal postural and proprioceptive reactions (49%). The majority of dogs with DPM had signs of BC. The presence of a high pituitary height/brain area and BC represented a risk factor for developing mental status abnormalities. Conclusion: Neurological signs recorded in DPM-affected dogs include not only the typical forebrain signs but also gait disturbances and hyperesthesia. Neurological signs are positively associated with increased P:B ratio and MRI signs of brain compression.

A Pipeline To Enhance Ligand Virtual Screening: Integrating Molecular Dynamics and Fingerprints for Ligand and Proteins.

The importance of taking into account protein flexibility in drug design and virtual ligand screening (VS) has been widely debated in the literature, and molecular dynamics (MD) has been recognized as one of the most powerful tools for investigating intrinsic protein dynamics. Nevertheless, deciphering the amount of information hidden in MD simulations and recognizing a significant minimal set of states to be used in virtual screening experiments can be quite complicated. Here we present an integrated MD-FLAP (molecular dynamics-fingerprints for ligand and proteins) approach, comprising a pipeline of molecular dynamics, clustering and linear discriminant analysis, for enhancing accuracy and efficacy in VS campaigns. We first extracted a limited number of representative structures from tens of nanoseconds of MD trajectories by means of the k-medoids clustering algorithm as implemented in the BiKi Life Science Suite ( http://www.bikitech.com [accessed July 21, 2015]). Then, instead of applying arbitrary selection criteria, that is, RMSD, pharmacophore properties, or enrichment performances, we allowed the linear discriminant analysis algorithm implemented in FLAP ( http://www.moldiscovery.com [accessed July 21, 2015]) to automatically choose the best performing conformational states among medoids and X-ray structures. Retrospective virtual screenings confirmed that ensemble receptor protocols outperform single rigid receptor approaches, proved that computationally generated conformations comprise the same quantity/quality of information included in X-ray structures, and pointed to the MD-FLAP approach as a valuable tool for improving VS performances.

Papillary meningioma in the dog: A clinicopathological case series study.

Papillary meningioma (PM) is one of the most aggressive variants of meningioma in humans and classified as grade III by WHO system. To date, the biological behavior of PM is still not clear in dogs. This study investigated the correlation between histopathological findings of 16 canine PMs and follow up data. Moreover, the expression of doublecortin, E-cadherin, and N-cadherin was investigated by immunohistochemistry. The supratentorial compartment resulted the most common involved. Despite the low grade of histological malignancy, 87.5% of dogs that underwent surgery experienced tumor recurrence. Intratumoral necrosis was observed in a strict correlation with malignancy histological parameter and tumor recurrence. The post-surgery mean survival time was much lower than thus observed in the most common histological subtypes. This data were also confirmed in dogs that received a conservative treatment alone. Tumors with a severe clinical behavior showed a high N-cadherin expression versus a low or absent E-cadherin expression.

BioGPS: navigating biological space to predict polypharmacology, off-targeting, and selectivity.

The structural comparison of protein binding sites is increasingly important in drug design; identifying structurally similar sites can be useful for techniques such as drug repurposing, and also in a polypharmacological approach to deliberately affect multiple targets in a disease pathway, or to explain unwanted off-target effects. Once similar sites are identified, identifying local differences can aid in the design of selectivity. Such an approach moves away from the classical "one target one drug" approach and toward a wider systems biology paradigm. Here, we report a semiautomated approach, called BioGPS, that is based on the software FLAP which combines GRID Molecular Interactions Fields (MIFs) and pharmacophoric fingerprints. BioGPS comprises the automatic preparation of protein structure data, identification of binding sites, and subsequent comparison by aligning the sites and directly comparing the MIFs. Chemometric approaches are included to reduce the complexity of the resulting data on large datasets, enabling focus on the most relevant information. Individual site similarities can be analyzed in terms of their Pharmacophoric Interaction Field (PIF) similarity, and importantly the differences in their PIFs can be extracted. Here we describe the BioGPS approach, and demonstrate its applicability to rationalize off-target effects (ERα and SERCA), to classify protein families and explain polypharmacology (ABL1 kinase and NQO2), and to rationalize selectivity between subfamilies (MAP kinases p38α/ERK2 and PPARδ/PPARγ). The examples shown demonstrate a significant validation of the method and illustrate the effectiveness of the approach.

Molecular interaction fields and 3D-QSAR studies of p53-MDM2 inhibitors suggest additional features of ligand-target interaction.

The design and optimization of small molecule inhibitors of the murine double minute clone 2-p53 (p53-MDM2) interaction has attracted a great deal of interest as a way to novel anticancer therapies. Herein we report 3D-QSAR studies of 41 small molecule inhibitors based on the use of molecular interaction fields and docking experiments as part of an approach to generating predictive models of MDM2 affinity and shedding further light on the structural elements of the ligand-target interaction. These studies have yielded predictive models explaining much of the variance of the 41 compound training set and satisfactorily predicting with 75% success an external test set of 36 compounds. Not surprisingly, and in full agreement with previous data, inspection of the 3D-QSAR coefficients reveals that the major driving force for potent inhibition is given by the hydrophobic interaction between the inhibitors and the p53 binding cleft of MDM2. More surprisingly, and challenging previous suggestions, the projection of the 3D-QSAR coefficients back onto the experimental structures of MDM2 provides an intriguing hypothesis concerning an active role played by the N-terminal region of MDM2 in ligand binding.

Targeting the conformational transitions of MDM2 and MDMX: insights into dissimilarities and similarities of p53 recognition.

MDM2 and MDMX are oncogenic homologue proteins that regulate the activity and stability of p53, a tumor suppressor protein involved in more than 50% of human cancers. While the large body of experiments so far accumulated has validated MDM2 as a therapeutically important target for the development of anticancer drugs, it is only recently that MDMX has also become an attractive target for the treatment of tumor cells expressing wild type p53. The availability of structural information of the N-terminal domain of MDM2 in complex with p53-derived peptides and inhibitors, and the very recent disclosure of the crystal structure of the N-terminal domain of MDMX bound to a p53 peptide, offer an unprecedented opportunity to provide insight into the molecular basis of p53 recognition and the identification of discriminating features affecting the binding of the tumor suppressor protein at MDM2 and MDMX. By using coarse graining simulations, in this study we report the exploration of the conformational transitions featured in the pathway leading from the apo-MDM2 and apo-MDMX states to the p53-bound MDM2 and p53-bound MDMX states, respectively. The results have enabled us to identify a pool of diverse conformational states of the oncogenic proteins that affect the binding of p53 and the presence of conserved and non-conserved interactions along the conformational transition pathway that may be exploited in the design of selective and dual modulators of MDM2 and MDMX activity.

Novel TOPP descriptors in 3D-QSAR analysis of apoptosis inducing 4-aryl-4H-chromenes: comparison versus other 2D- and 3D-descriptors.

Novel 3D-descriptors using Triplets Of Pharmacophoric Points (TOPP) were evaluated in QSAR-studies on 80 apoptosis-inducing 4-aryl-4H-chromenes. A predictive QSAR model was obtained using PLS, confirmed by means of internal and external validations. Performance of the TOPP approach was compared with that of other 2D- and 3D-descriptors; statistical analysis indicates that TOPP descriptors perform best. A ranking of TOPP>GRIND>BCI 4096=ECFP>FCFP>GRID-GOLPE>>DRAGON>>>MDL 166 was achieved. Finally, in a 'consensus' analysis predictions obtained using the single methods were compared with an average approach using six out of eight methods. The use of the average is statistically superior to the single methods. Beyond it, the use of several methods can help to easily investigate the presence/absence of outliers according to the 'consensus' of the predicted values: agreement among all the methods indicates a precise prediction, whereas large differences between predicted values (for the same compounds by different methods) would demand caution when using such predictions.

A true "triphasic" pattern: thoracolumbar spinal tumor in a young dog.

An 8-month-old male Bernese Mountain Dog was referred with a history of hindlimb weakness that progressed to paresis on the right side. An intradural mass was detected in the spinal canal at the level of the 2nd and 3rd lumbar vertebrae. During surgical removal, 2 small fragments of the mass were prepared for cytologic examination by the squash technique. Cytologic examination revealed 3 different cell types: mesenchymal (stromal) cells, epithelial cells, and small undifferentiated hyperchromatic cells. On the basis of location and the triphasic cytologic pattern, a diagnosis of spinal nephroblastoma (thoracolumbar spinal tumor of young dogs) was made; histologic examination of the mass confirmed the cytologic diagnosis. To our knowledge, this is the first report of a triphasic pattern in a cytologic sample; recognizing this pattern is an important aid in reaching a definitive cytologic diagnosis.

Squash-prep cytology in the diagnosis of canine and feline nervous system lesions: a study of 42 cases.

BACKGROUND: The increased sophistication of imaging techniques in veterinary medicine allows the detection of a wide variety of intracranial and intraspinal lesions; however, imaging often does not provide a definitive diagnosis for nervous system (NS) lesions. Cytology is emerging as a useful diagnostic tool for obtaining a fast and accurate assessment of NS lesions, but little information is available for dogs and cats. OBJECTIVES: The purpose of this study was to assess the accuracy of cytologic evaluation of squash samples from NS lesions in dogs and cats and to consider cytology-based diagnostic guidelines and sources of misdiagnosis. METHODS: Cytologic specimens from masses localized in the central and peripheral NS taken during surgery or postmortem examination were classified into 3 groups according to the final histopathologic diagnosis: Group 1 = completely correct diagnosis, when the cytologic diagnosis and final histologic diagnosis were exactly correlated; Group 2 = partial correlation, when the cytologic diagnosis only partially correlated with the final histologic diagnosis, and Group 3 = no correlation, when the cytologic diagnosis was incorrect and there was no correlation with the general histologic type of lesion. The diagnostic accuracy of cytopathology was calculated by considering the histopathologic diagnosis as the "gold standard," and calculating a 95% confidence interval (CI). RESULTS: A total of 42 animals (33 dogs and 9 cats) were included in the study. The cytologic diagnoses were classified in Group 1 for 32 cases (76%; 95% CI 0.63-0.89), in Group 2 for 6 cases (14%; 95% CI 0.04-0.25), and in Group 3 for 4 cases (10%; 95% CI 0.006-0.18). Considering both complete and partial correlation as an adequate result, cytologic diagnosis was satisfactory in 90% of biopsies. CONCLUSIONS: Although the current series of cases is relatively small, cytologic evaluation of squash preparations can be considered a fairly accurate and reliable tool in the diagnosis of NS lesions.