Structure-based mechanism of riboregulation of the metabolic enzyme SHMT1.

RNA can directly control protein activity in a process called riboregulation; only a few mechanisms of riboregulation have been described in detail, none of which have been characterized on structural grounds. Here, we present a comprehensive structural, functional, and phylogenetic analysis of riboregulation of cytosolic serine hydroxymethyltransferase (SHMT1), the enzyme interconverting serine and glycine in one-carbon metabolism. We have determined the cryoelectron microscopy (cryo-EM) structure of human SHMT1 in its free- and RNA-bound states, and we show that the RNA modulator competes with polyglutamylated folates and acts as an allosteric switch, selectively altering the enzyme's reactivity vs. serine. In addition, we identify the tetrameric assembly and a flap structural motif as key structural elements necessary for binding of RNA to eukaryotic SHMT1. The results presented here suggest that riboregulation may have played a role in evolution of eukaryotic SHMT1 and in compartmentalization of one-carbon metabolism. Our findings provide insights for RNA-based therapeutic strategies targeting this cancer-linked metabolic pathway.

AlPaCas: allele-specific CRISPR gene editing through a protospacer-adjacent-motif (PAM) approach.

Gene therapy of dominantly inherited genetic diseases requires either the selective disruption of the mutant allele or the editing of the specific mutation. The CRISPR-Cas system holds great potential for the genetic correction of single nucleotide variants (SNVs), including dominant mutations. However, distinguishing between single-nucleotide variations in a pathogenic genomic context remains challenging. The presence of a PAM in the disease-causing allele can guide its precise targeting, preserving the functionality of the wild-type allele. The AlPaCas (Aligning Patients to Cas) webserver is an automated pipeline for sequence-based identification and structural analysis of SNV-derived PAMs that satisfy this demand. When provided with a gene/SNV input, AlPaCas can: (i) identify SNV-derived PAMs; (ii) provide a list of available Cas enzymes recognizing the SNV (s); (iii) propose mutational Cas-engineering to enhance the selectivity towards the SNV-derived PAM. With its ability to identify allele-specific genetic variants that can be targeted using already available or engineered Cas enzymes, AlPaCas is at the forefront of advancements in genome editing. AlPaCas is open to all users without a login requirement and is freely available at https://schubert.bio.uniroma1.it/alpacas.

PyPCN: protein contact networks in PyMOL.

MOTIVATION: Protein contact networks (PCNs) represent the 3D structure of a protein using network formalism. Inter-residue contacts are described as binary adjacency matrices, which are derived from the graph representation of residues (as α-carbons, ß-carbons or centroids) and Euclidean distances according to defined thresholds. Functional characterization algorithms are computed on binary adjacency matrices to unveil allosteric, dynamic, and interaction mechanisms in proteins. Such strategies are usually applied in a combinatorial manner, although rarely in seamless and user-friendly implementations. RESULTS: PyPCN is a plugin for PyMOL wrapping more than twenty PCN algorithms and metrics in an easy-to-use graphical user interface, to support PCN analysis. The plugin accepts 3D structures from the Protein Data Bank, user-provided PDBs, or precomputed adjacency matrices. The results are directly mapped to 3D protein structures and organized into interactive diagrams for their visualization. A dedicated graphical user interface combined with PyMOL visual support makes analysis more intuitive and easier, extending the applicability of PCNs. AVAILABILITY AND IMPLEMENTATION: https://github.com/pcnproject/PyPCN.

Making Use of Averaging Methods in MODELLER for Protein Structure Prediction.

Recent advances in protein structure prediction, driven by AlphaFold 2 and machine learning, demonstrate proficiency in static structures but encounter challenges in capturing essential dynamic features crucial for understanding biological function. In this context, homology-based modeling emerges as a cost-effective and computationally efficient alternative. The MODELLER (version 10.5, accessed on 30 November 2023) algorithm can be harnessed for this purpose since it computes intermediate models during simulated annealing, enabling the exploration of attainable configurational states and energies while minimizing its objective function. There have been a few attempts to date to improve the models generated by its algorithm, and in particular, there is no literature regarding the implementation of an averaging procedure involving the intermediate models in the MODELLER algorithm. In this study, we examined MODELLER's output using 225 target-template pairs, extracting the best representatives of intermediate models. Applying an averaging procedure to the selected intermediate structures based on statistical potentials, we aimed to determine: (1) whether averaging improves the quality of structural models during the building phase; (2) if ranking by statistical potentials reliably selects the best models, leading to improved final model quality; (3) whether using a single template versus multiple templates affects the averaging approach; (4) whether the "ensemble" nature of the MODELLER building phase can be harnessed to capture low-energy conformations in holo structures modeling. Our findings indicate that while improvements typically fall short of a few decimal points in the model evaluation metric, a notable fraction of configurations exhibit slightly higher similarity to the native structure than MODELLER's proposed final model. The averaging-building procedure proves particularly beneficial in (1) regions of low sequence identity between the target and template(s), the most challenging aspect of homology modeling; (2) holo protein conformations generation, an area in which MODELLER and related tools usually fall short of the expected performance.

DockingPie: a consensus docking plugin for PyMOL.

MOTIVATION: The primary strategy for predicting the binding mode of small molecules to their receptors and for performing receptor-based virtual screening studies is protein-ligand docking, which is undoubtedly the most popular and successful approach in computer-aided drug discovery. The increased popularity of docking has resulted in the development of different docking algorithms and scoring functions. Nonetheless, it is unlikely that a single approach outperforms the others in terms of reproducibility and precision. In this ground, consensus docking techniques are taking hold. RESULTS: We have developed DockingPie, an open source PyMOL plugin for individual, as well as consensus docking analyses. Smina, AutoDock Vina, ADFR and RxDock are the four docking engines that DockingPie currently supports in an easy and extremely intuitive way, thanks to its integrated docking environment and its GUI, fully integrated within PyMOL. AVAILABILITY AND IMPLEMENTATION: https://github.com/paiardin/DockingPie. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Exploring Innovative Approaches to Isolate a One-Component c-di-GMP Transducer: A Pilot Study.

Environmental nutrients control bacterial biofilm homeostasis, by regulating the intracellular levels of c-di-GMP. One component transducers can sense different classes of small molecules through a periplasmic domain; the nutrient recognition triggers the subsequent regulation of the downstream cytosolic diguanylate cyclase (GGDEF) or phosphodiesterase (EAL) domains, via transmembrane helix(ces), to finally change c-di-GMP levels.Protein studies on such transducers have been mainly carried out on isolated domains due to the presence of the transmembrane portion. Nevertheless, the cleavage of GGDEF and EAL-containing proteins could be detrimental since both tertiary and quaternary structures could be allosterically controlled; to by-pass this limitation, studies on the corresponding full-length proteins are highly desired.We have in silico selected a GGDEF-EAL transducer from Dyella thiooxydans (ann. A0A160N0B7), whose periplasmic binding domain was predicted to bind to arginine, a nutrient often associated with chronic infections and biofilm. This protein has been used as an in vitro tool for the identification of the best approach for its isolation, including (i) protein engineering to produce a water-soluble version via QTY (Glutamine, Threonine, and Tyrosine) code or (ii) nanodiscs assembly. The results on this "prototype" may represent the proof-of-concept for future isolation of other transmembrane proteins sharing the same architecture, including more complex nutrient-based transducers controlling c-di-GMP levels.

When Just One Phosphate Is One Too Many: The Multifaceted Interplay between Myc and Kinases.

Myc transcription factors are key regulators of many cellular processes, with Myc target genes crucially implicated in the management of cell proliferation and stem pluripotency, energy metabolism, protein synthesis, angiogenesis, DNA damage response, and apoptosis. Given the wide involvement of Myc in cellular dynamics, it is not surprising that its overexpression is frequently associated with cancer. Noteworthy, in cancer cells where high Myc levels are maintained, the overexpression of Myc-associated kinases is often observed and required to foster tumour cells' proliferation. A mutual interplay exists between Myc and kinases: the latter, which are Myc transcriptional targets, phosphorylate Myc, allowing its transcriptional activity, highlighting a clear regulatory loop. At the protein level, Myc activity and turnover is also tightly regulated by kinases, with a finely tuned balance between translation and rapid protein degradation. In this perspective, we focus on the cross-regulation of Myc and its associated protein kinases underlying similar and redundant mechanisms of regulation at different levels, from transcriptional to post-translational events. Furthermore, a review of the indirect effects of known kinase inhibitors on Myc provides an opportunity to identify alternative and combined therapeutic approaches for cancer treatment.

PyMod 3: a complete suite for structural bioinformatics in PyMOL.

SUMMARY: The PyMod project is designed to act as a fully integrated interface between the popular molecular graphics viewer PyMOL, and some of the most frequently used tools for structural bioinformatics, e.g. BLAST, HMMER, Clustal, MUSCLE, PSIPRED, DOPE and MODELLER. Here we report its latest release, PyMod 3, which has been completely renewed with a graphical interface written in PyQt, to make it compatible with the most recent PyMOL versions, and has been extended with a large set of new functionalities compared to its predecessor, i.e. PyMod 2. Starting from the amino acid sequence of a target protein, users can take advantage of PyMod 3 to carry out all the steps of the homology modeling process (i.e. template searching, target-template sequence alignment, model building and quality assessment). Additionally, the integrated tools in PyMod 3 may also be used alone, in order to extend PyMOL with a wide range of capabilities. Sequence similarity searches, multiple sequence/structure alignment building, phylogenetic trees and evolutionary conservation analyses, domain parsing, single/multiple chains and loop modeling can be performed in the PyMod 3/PyMOL environment. AVAILABILITY AND IMPLEMENTATION: A cross-platform PyMod 3 installer package for Windows, Linux and Mac OS X and a complete user guide with tutorials, are available at https://github.com/pymodproject/pymod. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SMaRT lncRNA controls translation of a G-quadruplex-containing mRNA antagonizing the DHX36 helicase.

Guanine-quadruplexes (G4) included in RNA molecules exert several functions in controlling gene expression at post-transcriptional level; however, the molecular mechanisms of G4-mediated regulation are still poorly understood. Here, we describe a regulatory circuitry operating in the early phases of murine muscle differentiation in which a long non-coding RNA (SMaRT) base pairs with a G4-containing mRNA (Mlx-γ) and represses its translation by counteracting the activity of the DHX36 RNA helicase. The time-restricted, specific effect of lnc-SMaRT on the translation of Mlx-γ isoform modulates the general subcellular localization of total MLX proteins, impacting on their transcriptional output and promoting proper myogenesis and mature myotube formation. Therefore, the circuitry made of lnc-SMaRT, Mlx-γ, and DHX36 not only plays an important role in the control of myogenesis but also unravels a molecular mechanism where G4 structures and G4 unwinding activities are regulated in living cells.

A Short ERAP2 That Binds IRAP Is Expressed in Macrophages Independently of Gene Variation.

The M1 zinc metalloproteases ERAP1, ERAP2, and IRAP play a role in HLA-I antigen presentation by refining the peptidome either in the ER (ERAP1 and ERAP2) or in the endosomes (IRAP). They have also been entrusted with other, although less defined, functions such as the regulation of the angiotensin system and blood pressure. In humans, ERAP1 and IRAP are commonly expressed. ERAP2 instead has evolved under balancing selection that maintains two haplotypes, one of which undergoing RNA splicing leading to nonsense-mediated decay and loss of protein. Hence, likewise in rodents, wherein the ERAP2 gene is missing, about a quarter of the human population does not express ERAP2. We report here that macrophages, but not monocytes or other mononuclear blood cells, express and secrete an ERAP2 shorter form independent of the haplotype. The generation of this "short" ERAP2 is due to an autocatalytic cleavage within a distinctive structural motif and requires an acidic micro-environment. Remarkably, ERAP2 "short" binds IRAP and the two molecules are co-expressed in the endosomes as well as in the cell membrane. Of note, the same phenomenon could be observed in some cancer cells. These data prompt us to reconsider the role of ERAP2, which might have been maintained in humans due to fulfilling a relevant function in its "short" form.

Nutrient Sensing and Biofilm Modulation: The Example of L-arginine in Pseudomonas.

Bacterial biofilm represents a multicellular community embedded within an extracellular matrix attached to a surface. This lifestyle confers to bacterial cells protection against hostile environments, such as antibiotic treatment and host immune response in case of infections. The Pseudomonas genus is characterised by species producing strong biofilms difficult to be eradicated and by an extraordinary metabolic versatility which may support energy and carbon/nitrogen assimilation under multiple environmental conditions. Nutrient availability can be perceived by a Pseudomonas biofilm which, in turn, readapts its metabolism to finally tune its own formation and dispersion. A growing number of papers is now focusing on the mechanism of nutrient perception as a possible strategy to weaken the biofilm barrier by environmental cues. One of the most important nutrients is amino acid L-arginine, a crucial metabolite sustaining bacterial growth both as a carbon and a nitrogen source. Under low-oxygen conditions, L-arginine may also serve for ATP production, thus allowing bacteria to survive in anaerobic environments. L-arginine has been associated with biofilms, virulence, and antibiotic resistance. L-arginine is also a key precursor of regulatory molecules such as polyamines, whose involvement in biofilm homeostasis is reported. Given the biomedical and biotechnological relevance of biofilm control, the state of the art on the effects mediated by the L-arginine nutrient on biofilm modulation is presented, with a special focus on the Pseudomonas biofilm. Possible biotechnological and biomedical applications are also discussed.

The moonlighting RNA-binding activity of cytosolic serine hydroxymethyltransferase contributes to control compartmentalization of serine metabolism.

Enzymes of intermediary metabolism are often reported to have moonlighting functions as RNA-binding proteins and have regulatory roles beyond their primary activities. Human serine hydroxymethyltransferase (SHMT) is essential for the one-carbon metabolism, which sustains growth and proliferation in normal and tumour cells. Here, we characterize the RNA-binding function of cytosolic SHMT (SHMT1) in vitro and using cancer cell models. We show that SHMT1 controls the expression of its mitochondrial counterpart (SHMT2) by binding to the 5'untranslated region of the SHMT2 transcript (UTR2). Importantly, binding to RNA is modulated by metabolites in vitro and the formation of the SHMT1-UTR2 complex inhibits the serine cleavage activity of the SHMT1, without affecting the reverse reaction. Transfection of UTR2 in cancer cells controls SHMT1 activity and reduces cell viability. We propose a novel mechanism of SHMT regulation, which interconnects RNA and metabolites levels to control the cross-talk between cytosolic and mitochondrial compartments of serine metabolism.

PHA-680626 Is an Effective Inhibitor of the Interaction between Aurora-A and N-Myc.

Neuroblastoma is a severe childhood disease, accounting for ~10% of all infant cancers. The amplification of the MYCN gene, coding for the N-Myc transcription factor, is an essential marker correlated with tumor progression and poor prognosis. In neuroblastoma cells, the mitotic kinase Aurora-A (AURKA), also frequently overexpressed in cancer, prevents N-Myc degradation by directly binding to a highly conserved N-Myc region. As a result, elevated levels of N-Myc are observed. During recent years, it has been demonstrated that some ATP competitive inhibitors of AURKA also cause essential conformational changes in the structure of the activation loop of the kinase that prevents N-Myc binding, thus impairing the formation of the AURKA/N-Myc complex. In this study, starting from a screening of crystal structures of AURKA in complexes with known inhibitors, we identified additional compounds affecting the conformation of the kinase activation loop. We assessed the ability of such compounds to disrupt the interaction between AURKA and N-Myc in vitro, using Surface Plasmon Resonance competition assays, and in tumor cell lines overexpressing MYCN, by performing Proximity Ligation Assays. Finally, their effects on N-Myc cellular levels and cell viability were investigated. Our results identify PHA-680626 as an amphosteric inhibitor both in vitro and in MYCN overexpressing cell lines, thus expanding the repertoire of known conformational disrupting inhibitors of the AURKA/N-Myc complex and confirming that altering the conformation of the activation loop of AURKA with a small molecule is an effective strategy to destabilize the AURKA/N-Myc interaction in neuroblastoma cancer cells.

Revisiting the "satisfaction of spatial restraints" approach of MODELLER for protein homology modeling.

The most frequently used approach for protein structure prediction is currently homology modeling. The 3D model building phase of this methodology is critical for obtaining an accurate and biologically useful prediction. The most widely employed tool to perform this task is MODELLER. This program implements the "modeling by satisfaction of spatial restraints" strategy and its core algorithm has not been altered significantly since the early 1990s. In this work, we have explored the idea of modifying MODELLER with two effective, yet computationally light strategies to improve its 3D modeling performance. Firstly, we have investigated how the level of accuracy in the estimation of structural variability between a target protein and its templates in the form of σ values profoundly influences 3D modeling. We show that the σ values produced by MODELLER are on average weakly correlated to the true level of structural divergence between target-template pairs and that increasing this correlation greatly improves the program's predictions, especially in multiple-template modeling. Secondly, we have inquired into how the incorporation of statistical potential terms (such as the DOPE potential) in the MODELLER's objective function impacts positively 3D modeling quality by providing a small but consistent improvement in metrics such as GDT-HA and lDDT and a large increase in stereochemical quality. Python modules to harness this second strategy are freely available at https://github.com/pymodproject/altmod. In summary, we show that there is a large room for improving MODELLER in terms of 3D modeling quality and we propose strategies that could be pursued in order to further increase its performance.

A Single Center Retrospective Review of Patients from Central Italy Tested for Melanoma Predisposition Genes.

BACKGROUND: Cutaneous malignant melanoma (CMM) is one of the most common skin cancers worldwide. CMM pathogenesis involves genetic and environmental factors. Recent studies have led to the identification of new genes involved in CMM susceptibility: beyond CDKN2A and CDK4, BAP1, POT1, and MITF were recently identified as potential high-risk melanoma susceptibility genes. OBJECTIVE: This study is aimed to evaluate the genetic predisposition to CMM in patients from central Italy. METHODS: From 1998 to 2017, genetic testing was performed in 888 cases with multiple primary melanoma and/or familial melanoma. Genetic analyses included the sequencing CDKN2A, CDK4, BAP1, POT1, and MITF in 202 cases, and of only CDKN2A and CDK4 codon 24 in 686 patients. By the evaluation of the personal and familial history, patients were divided in two clinical categories: "low significance" and "high significance" cases. RESULTS: 128 patients (72% belonging to the "high significance" category, 28% belonging to the "low significance" category) were found to carry a DNA change defined as pathogenic, likely pathogenic, variant of unknown significance (VUS)-favoring pathogenic or VUS. CONCLUSIONS: It is important to verify the genetic predisposition in CMM patients for an early diagnosis of further melanomas and/or other tumors associated with the characterized genotype.

A novel CDKN2A in-frame deletion associated with pancreatic cancer-melanoma syndrome.

Pancreatic cancer-melanoma syndrome (PCMS) is an inherited condition in which mutation carriers have an increased risk of malignant melanoma and/or pancreatic cancer. About 30% of PCMS cases carry mutations in CDKN2A. This gene encodes several protein isoforms, one of which, known as p16, regulates the cell-cycle by interacting with CDK4/CDK6 kinases and with several non-CDK proteins. Herein, we report on a novel CDKN2A germline in-frame deletion (c.52_57delACGGCC) found in an Italian family with PCMS. By segregation analysis, the c.52_57delACGGCC was proven to segregate in kindred with cutaneous melanoma (CM), in kindred with CM and pancreatic cancer, and in a single case presenting only with pancreatic cancer. In the literature, duplication mapping in the same genic region has been already reported at the germline level in several unrelated CM cases as a variant of unknown clinical significance. A computational approach for studying the effect of mutational changes over p16 protein structure showed that both the deletion and the duplication of the c.52_57 nucleotides result in protein misfolding and loss of interactors' binding. In conclusion, the present results argue that the quantitative alteration of nucleotides c.52_57 has a pathogenic role in p16 function and that the c.52_57delACGGCC is associated with PCMS.

A novel compound heterozygous genotype associated with aromatic amino acid decarboxylase deficiency: Clinical aspects and biochemical studies.

Aromatic amino acid decarboxylase (AADC) deficiency is a rare autosomal neurometabolic disorder caused by a deficit of AADC, a pyridoxal 5'-phosphate (PLP)-dependent enzyme, which catalyzes the synthesis of dopamine and serotonin. While many studies have highlighted the molecular defects of the homozygous pathogenic variants, so far only a study investigated heterozygous variants at protein level. Here, we report a clinical case of one AADC deficiency compound heterozygous patient bearing the A91V mutation and the novel C410G mutation. To elucidate its enzymatic phenotype, the A91V and C410G homodimers were first expressed in Escherichia coli, purified and characterized. Although both apo variants display an unaltered overall tertiary structure, they show a Ì´ 20-fold decreased PLP binding affinity. The C410G mutation only causes a Ì´ 4-fold decrease of the catalytic efficiency, while the A91V mutation causes a 1300-fold decrease of the kcat/Km, and changes in the holoAADC consisting in a marked alteration of the tertiary structure and the coenzyme microenvironment. Structural analyses of these mutations are in agreement with these data. Unfortunately, the C410G/A91V heterodimer was constructed, expressed and purified in rather modest amount. Anyway, measurements of decarboxylase activity indicate that its putative kcat value is lower than that predicted by averaging the kcat values of the two parental enzymes. This indicates a negative interallelic complementation between the C410G and A91V monomers. Overall, this study allowed to relate the clinical to the enzymatic phenotype of the patient and to extend knowledge in the clinical and molecular pathogenesis of AADC deficiency.

Cysteine 180 Is a Redox Sensor Modulating the Activity of Human Pyridoxal 5'-Phosphate Histidine Decarboxylase.

Histidine decarboxylase is a pyridoxal 5'-phosphate enzyme catalyzing the conversion of histidine to histamine, a bioactive molecule exerting its role in many modulatory processes. The human enzyme is involved in many physiological functions, such as neurotransmission, gastrointestinal track function, cell growth, and differentiation. Here, we studied the functional properties of the human enzyme and, in particular, the effects exerted at the protein level by two cysteine residues: Cys-180 and Cys-418. Surprisingly, the enzyme exists in an equilibrium between a reduced and an oxidized form whose extent depends on the redox state of Cys-180. Moreover, we determined that (i) the two enzymatic redox species exhibit modest structural changes in the coenzyme microenvironment and (ii) the oxidized form is slightly more active and stable than the reduced one. These data are consistent with the model proposed by bioinformatics analyses and molecular dynamics simulations in which the Cys-180 redox state could be responsible for a structural transition affecting the C-terminal domain reorientation leading to active site alterations. Furthermore, the biochemical properties of the purified C180S and C418S variants reveal that C180S behaves like the reduced form of the wild-type enzyme, while C418S is sensitive to reductants like the wild-type enzyme, thus allowing the identification of Cys-180 as the redox sensitive switch. On the other hand, Cys-418 appears to be a residue involved in aggregation propensity. A possible role for Cys-180 as a regulatory switch in response to different cellular redox conditions could be suggested.

PyMod 2.0: improvements in protein sequence-structure analysis and homology modeling within PyMOL.

Motivation: The recently released PyMod GUI integrates many of the individual steps required for protein sequence-structure analysis and homology modeling within the interactive visualization capabilities of PyMOL. Here we describe the improvements introduced into the version 2.0 of PyMod. Results: The original code of PyMod has been completely rewritten and improved in version 2.0 to extend PyMOL with packages such as Clustal Omega, PSIPRED and CAMPO. Integration with the popular web services ESPript and WebLogo is also provided. Finally, a number of new MODELLER functionalities have also been implemented, including SALIGN, modeling of quaternary structures, DOPE scores, disulfide bond modeling and choice of heteroatoms to be included in the final model. Availability and Implementation: PyMod 2.0 installer packages for Windows, Linux and Mac OS X and user guides are available at http://schubert.bio.uniroma1.it/pymod/index.html. The open source code of the project is hosted at https://github.com/pymodproject/pymod. Contact: alessandro.paiardini@uniroma1.it or giacomo.janson@uniroma1.it

Heterozygosis in aromatic amino acid decarboxylase deficiency: Evidence for a positive interallelic complementation between R347Q and R358H mutations.

Aromatic amino acid or Dopa decarboxylase (AADC or DDC) is a homodimeric pyridoxal 5'-phosphate (PLP) enzyme responsible for the generation of the neurotransmitters dopamine and serotonin. AADC deficiency is a rare inborn disease caused by mutations of the AADC gene leading to a defect of AADC enzyme and resulting in impaired dopamine and serotonin synthesis. Until now, only the molecular effects of homozygous mutations were analyzed. However, although heterozygous carriers of AADC deficiency were identified, the molecular aspects of their enzymatic phenotypes are not yet investigated. Here, we focus our attention on the R347Q/R358H and R347Q/R160W heterozygous mutations, and report for the first time the isolation and characterization, in the purified recombinant form, of the R347Q/R358H heterodimer and of the R358H homodimer. The results, integrated with those already known of the R347Q homodimeric variant, provide evidence that (i) the R358H mutation strongly reduces the PLP-binding affinity and the catalytic activity, and (ii) a positive interallelic complementation exists between the R347Q and the R358H mutations. Bioinformatics analyses provide the structural basis for these data. Unfortunately, the R347Q/R160W heterodimer was not obtained in a sufficient amount to allow its purification and characterization. Nevertheless, the biochemical features of the R160W homodimer give a contribution to the enzymatic phenotype of the heterozygous R347Q/R160W and suggest the possible relevance of Arg160 in the proper folding of human DDC. © 2018 IUBMB Life, 70(3):215-223, 2018.