The Histone Deacetylase Family: Structural Features and Application of Combined Computational Methods.

Histone deacetylases (HDACs) are crucial in gene transcription, removing acetyl groups from histones. They also influence the deacetylation of non-histone proteins, contributing to the regulation of various biological processes. Thus, HDACs play pivotal roles in various diseases, including cancer, neurodegenerative disorders, and inflammatory conditions, highlighting their potential as therapeutic targets. This paper reviews the structure and function of the four classes of human HDACs. While four HDAC inhibitors are currently available for treating hematological malignancies, numerous others are undergoing clinical trials. However, their non-selective toxicity necessitates ongoing research into safer and more efficient class-selective or isoform-selective inhibitors. Computational methods have aided the discovery of HDAC inhibitors with the desired potency and/or selectivity. These methods include ligand-based approaches, such as scaffold hopping, pharmacophore modeling, three-dimensional quantitative structure-activity relationships, and structure-based virtual screening (molecular docking). Moreover, recent developments in the field of molecular dynamics simulations, combined with Poisson-Boltzmann/molecular mechanics generalized Born surface area techniques, have improved the prediction of ligand binding affinity. In this review, we delve into the ways in which these methods have contributed to designing and identifying HDAC inhibitors.

Targeting non-coding RNAs: Perspectives and challenges of in-silico approaches.

The growing information currently available on the central role of non-coding RNAs (ncRNAs) including microRNAs (miRNAS) and long non-coding RNAs (lncRNAs) for chronic and degenerative human diseases makes them attractive therapeutic targets. RNAs carry out different functional roles in human biology and are deeply deregulated in several diseases. So far, different attempts to therapeutically target the 3D RNA structures with small molecules have been reported. In this scenario, the development of computational tools suitable for describing RNA structures and their potential interactions with small molecules is gaining more and more interest. Here, we describe the most suitable strategies to study ncRNAs through computational tools. We focus on methods capable of predicting 2D and 3D ncRNA structures. Furthermore, we describe computational tools to identify, design and optimize small molecule ncRNA binders. This review aims to outline the state of the art and perspectives of computational methods for ncRNAs over the past decade.

Spatial communication systems across languages reflect universal action constraints.

The extent to which languages share properties reflecting the non-linguistic constraints of the speakers who speak them is key to the debate regarding the relationship between language and cognition. A critical case is spatial communication, where it has been argued that semantic universals should exist, if anywhere. Here, using an experimental paradigm able to separate variation within a language from variation between languages, we tested the use of spatial demonstratives-the most fundamental and frequent spatial terms across languages. In n = 874 speakers across 29 languages, we show that speakers of all tested languages use spatial demonstratives as a function of being able to reach or act on an object being referred to. In some languages, the position of the addressee is also relevant in selecting between demonstrative forms. Commonalities and differences across languages in spatial communication can be understood in terms of universal constraints on action shaping spatial language and cognition.

Repeat After Me? Both Children With and Without Autism Commonly Align Their Language With That of Their Caregivers.

Linguistic repetitions in children are conceptualized as negative in children with autism - echolalia, without communicative purpose - and positive in typically developing (TD) children - linguistic alignment involved in shared engagement, common ground and language acquisition. To investigate this apparent contradiction we analyzed spontaneous speech in 67 parent-child dyads from a longitudinal corpus (30 minutes of play activities at 6 visits over 2 years). We included 32 children with autism and 35 linguistically matched TD children (mean age at recruitment 32.76 and 20.27 months). We found a small number of exact repetitions in both groups (roughly 1% of utterances across visits), which increased over time in children with autism and decreased in the TD group. Partial repetitions were much more frequent: children reused caregivers' words at high rates regardless of diagnostic group (24% of utterances at first visit), and this increased in frequency (but not level) over time, faster for TD children (at final visit: 33% for autism, 40% for TD). The same happened for partial repetition of syntax and semantic alignment. However, chance alignment (as measured by surrogate pairs) also increased and findings for developmental changes were reliable only for syntactic and semantic alignment. Children with richer linguistic abilities also displayed a higher tendency to partially re-use their caregivers' language (alignment rates and semantic alignment). This highlights that all children commonly re-used the words, syntax, and topics of their caregivers, albeit with some quantitative differences, and that most repetition was at least potentially productive, with repeated language being re-contextualized and integrated with non-repeated language. The salience of echolalia in ASD might be partially explained by slight differences in frequency, amplified by lower semantic alignment, persistence over time, and expectations of echolalia. More in-depth qualitative and quantitative analyses of how repetitions are used and received in context are needed.

Discovery of first novel sigma/HDACi dual-ligands with a potent in vitro antiproliferative activity.

Designing and discovering compounds for dual-target inhibitors is challenging to synthesize new, safer, and more efficient drugs than single-target drugs, especially to treat multifactorial diseases such as cancer. The simultaneous regulation of multiple targets might represent an alternative synthetic approach to optimize patient compliance and tolerance, minimizing the risk of target-based drug resistance due to the modulation of a few targets. To this end, we conceived for the first time the design and synthesis of dual-ligands σR/HDACi to evaluate possible employment as innovative candidates to address this complex disease. Among all synthesized compounds screened for several tumoral cell lines, compound 6 (Kiσ1R = 38 ± 3.7; Kiσ2R = 2917 ± 769 and HDACs IC50 = 0.59 µM) is the most promising candidate as an antiproliferative agent with an IC50 of 0.9 µM on the HCT116 cell line and no significant toxicity to normal cells. Studies of molecular docking, which confirmed the affinity over σ1R and a pan-HDACs inhibitory behavior, support a possible balanced affinity and activity between both targets.

Hit identification of novel small molecules interfering with MALAT1 triplex by a structure-based virtual screening.

Nowadays, RNA is an attractive target for the design of new small molecules with different pharmacological activities. Among several RNA molecules, long noncoding RNAs (lncRNAs) are extensively reported to be involved in cancer pathogenesis. In particular, the overexpression of lncRNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) plays an important role in the development of multiple myeloma (MM). Starting from the crystallographic structure of the triple-helical stability element at the 3'-end of MALAT1, we performed a structure-based virtual screening of a large commercial database, previously filtered according to the drug-like properties. After a thermodynamic analysis, we selected five compounds for the in vitro assays. Compound M5, characterized by a diazaindene scaffold, emerged as the most promising molecule enabling the destabilization of the MALAT1 triplex structure and antiproliferative activity on in vitro models of MM. M5 is proposed as a lead compound to be further optimized for improving its affinity toward MALAT1.

Uncovering Novel Capsaicin Inhibitory Activity towards Human Carbonic Anhydrase Isoforms IX and XII by Combining In Silico and In Vitro Studies.

Hot pepper (Capsicum annuum) represents one of the most widespread functional foods of the Mediterranean diet, and is associated with a reduced risk of developing cardiovascular disease, cancer, and mental disorders. In particular, its bioactive spicy molecules, named Capsaicinoids, exhibit polypharmacological properties. Among them, Capsaicin (trans-8-methyl-N-vanillyl-6-nonenamide) is the most studied and reported in variegated scientific contributions for its beneficial effects, often linked to mechanisms of action unrelated to the activation of Transient Receptor Potential Vanilloid 1 (TRPV1). In this study, we present the application of in silico methods to Capsaicin for evaluating its inhibitory activity against the tumor-associated human (h) expressed CA IX and XII. In vitro assays confirmed Capsaicin inhibitory activity towards the most relevant tumor-related hCA isoforms. In particular, the hCAs IX and XII showed an experimental KI value of 0.28 µM and 0.064 µM, respectively. Then, an A549 model of non-small cell lung cancer, typically characterized by an elevated expression of hCA IX and XII, was employed to test the inhibitory effects of Capsaicin in vitro under both normoxic and hypoxic conditions. Finally, the migration assay revealed that Capsaicin [10 µM] inhibits cells from moving in the A549 cells model.

Identification of pyrrolo[3',4':3,4]cyclohepta[1,2-d][1,2]oxazoles as promising new candidates for the treatment of lymphomas.

Unsatisfactory outcomes for relapsed/refractory lymphoma patients prompt continuing efforts to develop new therapeutic strategies. Our previous studies on pyrrole-based anti-lymphoma agents led us to synthesize a new series of twenty-six pyrrolo[3',4':3,4]cyclohepta[1,2-d] [1,2]oxazole derivatives and study their antiproliferative effects against a panel of four non-Hodgkin lymphoma cell lines. Several candidates showed significant anti-proliferative effects, with IC50's reaching the sub-micromolar range in at least one cell line, with compound 3z demonstrating sub-micromolar growth inhibitory effects towards the entire panel. The VL51 cell line was the most sensitive, with an IC50 value of 0.10 µM for 3z. Our earlier studies had shown that tubulin was a prominent target of many of our oxazole derivatives. We therefore examined their effects on tubulin assembly and colchicine binding. While 3u and 3z did not appear to target tubulin, good activity was observed with 3d and 3p. Molecular docking and molecular dynamics simulations allowed us to rationalize the binding mode of the synthesized compounds toward tubulin. All ligands exhibited a better affinity for the colchicine site, confirming their specificity for this binding pocket. In particular, a better affinity and free energy of binding was observed for 3d and 3p. This result was confirmed by experimental data, indicating that, although both 3d and 3p significantly affected tubulin assembly, only 3d showed activity comparable to that of combretastatin A-4, while 3p was about 4-fold less active. Cell cycle analysis showed that compounds 3u and especially 3z induced a block in G2/M, a strong decrease in S phase even at low compound concentrations and apoptosis through the mitochondrial pathway. Thus, the mechanism of action of 3u and 3z remains to be elucidated. Very high selectivity toward cancer cells and low toxicity in human peripheral blood lymphocytes were observed, highlighting the good potential of these agents in cancer therapy and encouraging further exploration of this compound class to obtain new small molecules as effective lymphoma treatments.

Natural language processing for humanitarian action: Opportunities, challenges, and the path toward humanitarian NLP.

Natural language processing (NLP) is a rapidly evolving field at the intersection of linguistics, computer science, and artificial intelligence, which is concerned with developing methods to process and generate language at scale. Modern NLP tools have the potential to support humanitarian action at multiple stages of the humanitarian response cycle. Both internal reports, secondary text data (e.g., social media data, news media articles, or interviews with affected individuals), and external-facing documents like Humanitarian Needs Overviews (HNOs) encode information relevant to monitoring, anticipating, or responding to humanitarian crises. Yet, lack of awareness of the concrete opportunities offered by state-of-the-art techniques, as well as constraints posed by resource scarcity, limit adoption of NLP tools in the humanitarian sector. This paper provides a pragmatically-minded primer to the emerging field of humanitarian NLP, reviewing existing initiatives in the space of humanitarian NLP, highlighting potentially impactful applications of NLP in the humanitarian sector, and describing criteria, challenges, and potential solutions for large-scale adoption. In addition, as one of the main bottlenecks is the lack of data and standards for this domain, we present recent initiatives (the DEEP and HumSet) which are directly aimed at addressing these gaps. With this work, we hope to motivate humanitarians and NLP experts to create long-term impact-driven synergies and to co-develop an ambitious roadmap for the field.

Caregiver linguistic alignment to autistic and typically developing children: A natural language processing approach illuminates the interactive components of language development.

BACKGROUND: Language development is a highly interactive activity. However, most research on linguistic environment has focused on the quantity and complexity of linguistic input to children, with current models showing that complexity facilitates language in both typically developing (TD) and autistic children. AIMS: After reviewing existing work on caregiver engagement of children's utterances, we aim to operationalize such engagement with automated measures of linguistic alignment, thereby providing scalable tools to assess caregivers' active reuse of their children's language. By assessing the presence of alignment, its sensitivity to the child's individual differences and how well it predicts language development beyond current models across the two groups, we showcase the usefulness of the approach and provide initial empirical foundations for further conceptual and empirical investigations. METHODS: We measure lexical, syntactic and semantic types of caregiver alignment in a longitudinal corpus involving 32 adult-autistic child and 35 adult-TD child dyads, with children between 2 and 5 years of age. We assess the extent to which caregivers repeat their children's words, syntax, and semantics, and whether these repetitions predict language development beyond more standard predictors. RESULTS: Caregivers tend to re-use their child's language in a way that is related to the child's individual, primarily linguistic, differences. Caregivers' alignment provides unique information improving our ability to predict future language development in both typical and autistic children. CONCLUSIONS: We provide evidence that language development also relies on interactive conversational processes, previously understudied. We share carefully detailed methods, and open-source scripts so as to systematically extend our approach to new contexts and languages.

TERRA G-quadruplex stabilization as a new therapeutic strategy for multiple myeloma.

BACKGROUND: Multiple myeloma (MM) is a hematologic malignancy characterized by high genomic instability, and telomere dysfunction is an important cause of acquired genomic alterations. Telomeric repeat-containing RNA (TERRA) transcripts are long non-coding RNAs involved in telomere stability through the interaction with shelterin complex. Dysregulation of TERRAs has been reported across several cancer types. We recently identified a small molecule, hit 17, which stabilizes the secondary structure of TERRA. In this study, we investigated in vitro and in vivo anti-MM activities of hit 17. METHODS: Anti-proliferative activity of hit 17 was evaluated in different MM cell lines by cell proliferation assay, and the apoptotic process was analyzed by flow cytometry. Gene and protein expressions were detected by RT-qPCR and western blotting, respectively. Microarray analysis was used to analyze the transcriptome profile. The effect of hit 17 on telomeric structure was evaluated by chromatin immunoprecipitation. Further evaluation in vivo was proceeded upon NCI-H929 and AMO-1 xenograft models. RESULTS: TERRA G4 stabilization induced in vitro dissociation of telomeric repeat-binding factor 2 (TRF2) from telomeres leading to the activation of ATM-dependent DNA damage response, cell cycle arrest, proliferation block, and apoptotic death in MM cell lines. In addition, up-regulation of TERRA transcription was observed upon DNA damage and TRF2 loss. Transcriptome analysis followed by gene set enrichment analysis (GSEA) confirmed the involvement of the above-mentioned processes and other pathways such as E2F, MYC, oxidative phosphorylation, and DNA repair genes as early events following hit 17-induced TERRA stabilization. Moreover, hit 17 exerted anti-tumor activity against MM xenograft models. CONCLUSION: Our findings provide evidence that targeting TERRA by hit 17 could represent a promising strategy for a novel therapeutic approach to MM.

Natural Language Processing Markers for Psychosis and Other Psychiatric Disorders: Emerging Themes and Research Agenda From a Cross-Linguistic Workshop.

This workshop summary on natural language processing (NLP) markers for psychosis and other psychiatric disorders presents some of the clinical and research issues that NLP markers might address and some of the activities needed to move in that direction. We propose that the optimal development of NLP markers would occur in the context of research efforts to map out the underlying mechanisms of psychosis and other disorders. In this workshop, we identified some of the challenges to be addressed in developing and implementing NLP markers-based Clinical Decision Support Systems (CDSSs) in psychiatric practice, especially with respect to psychosis. Of note, a CDSS is meant to enhance decision-making by clinicians by providing additional relevant information primarily through software (although CDSSs are not without risks). In psychiatry, a field that relies on subjective clinical ratings that condense rich temporal behavioral information, the inclusion of computational quantitative NLP markers can plausibly lead to operationalized decision models in place of idiosyncratic ones, although ethical issues must always be paramount.

Studying Psychosis Using Natural Language Generation: A Review of Emerging Opportunities.

Disrupted language in psychotic disorders, such as schizophrenia, can manifest as false contents and formal deviations, often described as thought disorder. These features play a critical role in the social dysfunction associated with psychosis, but we continue to lack insights regarding how and why these symptoms develop. Natural language generation (NLG) is a field of computer science that focuses on generating human-like language for various applications. The theory that psychosis is related to the evolution of language in humans suggests that NLG systems that are sufficiently evolved to generate human-like language may also exhibit psychosis-like features. In this conceptual review, we propose using NLG systems that are at various stages of development as in silico tools to study linguistic features of psychosis. We argue that a program of in silico experimental research on the network architecture, function, learning rules, and training of NLG systems can help us understand better why thought disorder occurs in patients. This will allow us to gain a better understanding of the relationship between language and psychosis and potentially pave the way for new therapeutic approaches to address this vexing challenge.

Case report: Incidence and prognostic value of brain MRI lesions and elevated cerebrospinal fluid protein in children with Guillain-Barré syndrome.

Background: Guillain-Barrè syndrome (GBS) is an acute immune-mediated disorder affecting peripheral nerves and nerve roots with a variable clinical course and outcome. Epidemiologic analyses have revealed that the incidence of the syndrome increases linearly among the age. The clinical diagnosis of GBS is based on the family history, physical and neurological examination, electrodiagnostic exams, and cerebrospinal fluid analysis with the classical presence of albumin-cytologic dissociation. Prognosis is associated with the severity of clinical signs and the type of peripheral nerves involved. Methods: This study aims to clarify which clinical features can be used for prognostic purposes. We evaluated the correlation between (1) brain MRI lesions and grade of disability; (2) brain MRI lesions and elevated cerebrospinal fluid (CSF) protein; and (3) increased levels of CSF protein and grade of disability. Statistical analysis extracted from these data indicated a good correlation to be a prognostic indicator in children affected by GBS. We found little evidence regarding laboratory tests, imaging, and prognosis. We enrolled 12 continuous patients who met the Brighton criteria for GBS in this retrospective study. Each patient was clinically evaluated at the time of disease onset to assess the GBS disability score and after 2 weeks. Results: We estimated Pearson's correlation index to evaluate the possible correlation between MRI and disability and CSF protein levels and disability. The correlation coefficient was 0.92 and 0.85, respectively. In addition, we developed a graph to see the trend of the disability values, proteins in the CSF, and damage assessed with MRI in the 12 patients. It seems that these parameters have a parallel trend and a good correlation in each patient. Finally, we calculated the correlation between MRI and CSF protein values, with an r-value of 0.87. The values suggest a correlation among the MRI score, CSF protein, and prognosis. Conclusion: The MRI and CSF laboratory parameters can be important tools for the clinician not only for diagnosis but also to evaluate the possible worsening of general conditions or the need to prepare measures to support life parameters. Patients who need ventilatory support could be established early from patients who have less severe GBS and can begin rehabilitation earlier. We suggest MRI should be performed routinely in children with GBS to be able to estimate the evolution of the clinical condition.

Exploiting DNA Ligase III addiction of multiple myeloma by flavonoid Rhamnetin.

BACKGROUND: DNA ligases are crucial for DNA repair and cell replication since they catalyze the final steps in which DNA breaks are joined. DNA Ligase III (LIG3) exerts a pivotal role in Alternative-Non-Homologous End Joining Repair (Alt-NHEJ), an error-prone DNA repair pathway often up-regulated in genomically unstable cancer, such as Multiple Myeloma (MM). Based on the three-dimensional (3D) LIG3 structure, we performed a computational screening to identify LIG3-targeting natural compounds as potential candidates to counteract Alt-NHEJ activity in MM. METHODS: Virtual screening was conducted by interrogating the Phenol Explorer database. Validation of binding to LIG3 recombinant protein was performed by Saturation Transfer Difference (STD)-nuclear magnetic resonance (NMR) experiments. Cell viability was analyzed by Cell Titer-Glo assay; apoptosis was evaluated by flow cytometric analysis following Annexin V-7AAD staining. Alt-NHEJ repair modulation was evaluated using plasmid re-joining assay and Cytoscan HD. DNA Damage Response protein levels were analyzed by Western blot of whole and fractionated protein extracts and immunofluorescence analysis. The mitochondrial DNA (mtDNA) copy number was determined by qPCR. In vivo activity was evaluated in NOD-SCID mice subcutaneously engrafted with MM cells. RESULTS: Here, we provide evidence that a natural flavonoid Rhamnetin (RHM), selected by a computational approach, counteracts LIG3 activity and killed Alt-NHEJ-dependent MM cells. Indeed, Nuclear Magnetic Resonance (NMR) showed binding of RHM to LIG3 protein and functional experiments revealed that RHM interferes with LIG3-driven nuclear and mitochondrial DNA repair, leading to significant anti-MM activity in vitro and in vivo. CONCLUSION: Taken together, our findings provide proof of concept that RHM targets LIG3 addiction in MM and may represent therefore a novel promising anti-tumor natural agent to be investigated in an early clinical setting.

Development of [1,2]oxazoloisoindoles tubulin polymerization inhibitors: Further chemical modifications and potential therapeutic effects against lymphomas.

Lymphomas are among the ten most common cancers, and, although progress has been achieved in increasing survival, there is still an unmet need for more effective therapeutic approaches, including better options for patients with refractory tumors that initially respond but then relapse. The lack of effective alternative treatment options highlights the need to develop new therapeutic strategies capable of improving survival prospects for lymphoma patients. Herein, we describe the identification and exploration of the SAR of a series of [1,2]oxazolo[5,4-e]isoindoles as potent small molecules that bind to the colchicine site of tubulin and that have promise for the treatment of refractory lymphomas. Exploration of the chemical space of this class of compounds at the pyrrole moiety and at the [1,2]oxazole ring highlighted two compounds bearing a 3,5-dimethoxybenzyl and a 3,4,5-trimethoxybenzyl group as potent candidates and showed that structural modifications at the isoxazole moiety are generally not favorable for activity. The two best candidates showed efficacy against different lymphoma histotypes and displayed 88 and 80% inhibition of colchicine binding fitting well into the colchicine pocket, as demonstrated by X-ray crystallography T2R-TTL-complexes, docking and thermodynamic analysis of the tubulin-colchicine complex structure. These results were confirmed by transcriptome data, thus indicating [1,2]oxazolo[5,4-e]isoindoles are promising candidates as antitubulin agents for the treatment of refractory lymphomas.

The New Microtubule-Targeting Agent SIX2G Induces Immunogenic Cell Death in Multiple Myeloma.

Microtubule-targeting agents (MTAs) are effective drugs for cancer treatment. A novel diaryl [1,2]oxazole class of compounds binding the colchicine site was synthesized as cis-restricted-combretastatin-A-4-analogue and then chemically modified to have improved solubility and a wider therapeutic index as compared to vinca alkaloids and taxanes. On these bases, a new class of tricyclic compounds, containing the [1,2]oxazole ring and an isoindole moiety, has been synthetized, among which SIX2G emerged as improved MTA. Several findings highlighted the ability of some chemotherapeutics to induce immunogenic cell death (ICD), which is defined by the cell surface translocation of Calreticulin (CALR) via dissociation of the PP1/GADD34 complex. In this regard, we computationally predicted the ability of SIX2G to induce CALR exposure by interacting with the PP1 RVxF domain. We then assessed both the potential cytotoxic and immunogenic activity of SIX2G on in vitro models of multiple myeloma (MM), which is an incurable hematological malignancy characterized by an immunosuppressive milieu. We found that the treatment with SIX2G inhibited cell viability by inducing G2/M phase cell cycle arrest and apoptosis. Moreover, we observed the increase of hallmarks of ICD such as CALR exposure, ATP release and phospho-eIF2α protein level. Through co-culture experiments with immune cells, we demonstrated the increase of (i) CD86 maturation marker on dendritic cells, (ii) CD69 activation marker on cytotoxic T cells, and (iii) phagocytosis of tumor cells following treatment with SIX2G, confirming the onset of an immunogenic cascade. In conclusion, our findings provide a framework for further development of SIX2G as a new potential anti-MM agent.

Neuroscout, a unified platform for generalizable and reproducible fMRI research.

Functional magnetic resonance imaging (fMRI) has revolutionized cognitive neuroscience, but methodological barriers limit the generalizability of findings from the lab to the real world. Here, we present Neuroscout, an end-to-end platform for analysis of naturalistic fMRI data designed to facilitate the adoption of robust and generalizable research practices. Neuroscout leverages state-of-the-art machine learning models to automatically annotate stimuli from dozens of fMRI studies using naturalistic stimuli-such as movies and narratives-allowing researchers to easily test neuroscientific hypotheses across multiple ecologically-valid datasets. In addition, Neuroscout builds on a robust ecosystem of open tools and standards to provide an easy-to-use analysis builder and a fully automated execution engine that reduce the burden of reproducible research. Through a series of meta-analytic case studies, we validate the automatic feature extraction approach and demonstrate its potential to support more robust fMRI research. Owing to its ease of use and a high degree of automation, Neuroscout makes it possible to overcome modeling challenges commonly arising in naturalistic analysis and to easily scale analyses within and across datasets, democratizing generalizable fMRI research.

Riluzole-Rasagiline Hybrids: Toward the Development of Multi-Target-Directed Ligands for Amyotrophic Lateral Sclerosis.

Polypharmacology is a new trend in amyotrophic lateral sclerosis (ALS) therapy and an effective way of addressing a multifactorial etiology involving excitotoxicity, mitochondrial dysfunction, oxidative stress, and microglial activation. Inspired by a reported clinical trial, we converted a riluzole (1)-rasagiline (2) combination into single-molecule multi-target-directed ligands. By a ligand-based approach, the highly structurally integrated hybrids 3-8 were designed and synthesized. Through a target- and phenotypic-based screening pipeline, we identified hit compound 6. It showed monoamine oxidase A (MAO-A) inhibitory activity (IC50 = 6.9 µM) rationalized by in silico studies as well as in vitro brain permeability. By using neuronal and non-neuronal cell models, including ALS-patient-derived cells, we disclosed for 6 a neuroprotective/neuroinflammatory profile similar to that of the parent compounds and their combination. Furthermore, the unexpected MAO inhibitory activity of 1 (IC50 = 8.7 µM) might add a piece to the puzzle of its anti-ALS molecular profile.