Novel Disease-Associated Missense Single-Nucleotide Polymorphisms Variants Predication by Algorithms Tools and Molecular Dynamics Simulation of Human TCIRG1 Gene Causing Congenital Neutropenia and Osteopetrosis

Bicyclic 2-aminopyrimidine derivatives as potent VEGFR-2 inhibitors and apoptosis Inducers: Structure-Guided design, synthesis, anticancer assessment, and in-silico exploration

Anticancer therapy focuses on VEGFR-2 inhibition to disrupt angiogenesis, a critical process that sustains tumor growth and metastasis. This study outlines the synthesis and biological evaluation of 14 newly designed compounds featuring a bicyclic 2-amino-pyrimidine scaffold. In-vitro VEGFR-2 inhibition showed that compounds 55 and 61 were more potent with IC50 of 0.035 μM and 0.043 μM respectively, compared to the reference drug Sorafenib, and revealed selectivity for VEGFR-2 over EGFR. Consequently, 55 and 61 displayed good antiproliferative activities against the tested cell lines A549 (IC50 = 2.67 and 2.71 μM, respectively) and HCT116 (IC50 = 10.87 and 12.17 μM, respectively). The most active compounds were further assessed for their ability to induce apoptosis and preferential effect on wound closure in A549 cells, investigated via the cell scratch assay. Moreover, these compounds substantially reduced the phosphorylation of ERK and AKT, two downstream targets of VEGFR-2. The CAM assay further verified the antiangiogenic potential of lead compounds, revealing a significant reduction of neovascularization. Molecular docking studies performed for compound 55 showed hydrogen bond interactions with Asp1046, Cys919, and Glu885, similar to FDA-approved sorafenib. Moreover, a 100 ns MD simulation confirmed the complex's stability, while other analyses, such as RMSD, RMSF, PCA, and FEL, were performed to characterize protein conformational variations. Thorough SAR analysis, along with findings of cytotoxic activities and in-vitro inhibition of VEGFR-2, supports the potential of these synthetic compounds as VEGFR-2 inhibitors.

Promising thiazolidinedione-thiazole based multi-target and neuroprotective hybrids for Alzheimer's disease: Design, synthesis, in-vitro, in-vivo and in-silico studies

Alzheimer's disease (AD) is marked by low neurotransmitter levels, inflammation, increased oxidative stress, and the aggregation of amyloid-β and tau proteins. The development of hybrid compounds acting as multi-target-directed ligands (MTDLs) is a novel and contemporary approach in Alzheimer's disease therapeutics. The objective of our current research focuses on identifying compounds with balanced, even moderate inhibition potential against multiple targets associated with cholinergic deficit and neuroinflammation. Inspired by our previous study, the thiazolidinedione-thiazole-based framework has been employed to design and synthesize a series of new hybrids. The inhibitory effects of the synthesized compounds on selected enzymes were investigated by employing in-vitro methods. The synergistic inhibition of acetylcholinesterase (AChE), monoamine oxidase-B (MAO-B), β-secretase (BACE-1), cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX) by compound 49 is believed to have a more potent effect in treating Alzheimer's disease. Enzyme kinetic studies and their effect on substrate-enzyme interactions of the compounds with significant inhibitory potency for AChE and MAO-B were also investigated. Central nervous system (CNS) penetration was determined using in-vitro PAMPA assay. A neurotoxicity test on neuroblastoma cell lines (SH-SY5Y) showed that the compounds were non-toxic. Compound 49 showed an excellent neuroprotective effect by significantly reducing H2O2-induced oxidative stress. Antioxidant enzymes were studied in an in-vivo experiment in the brains of male BALB/c mice. Compound 49 showed its ability to reduce the oxidative stress. Furthermore, molecular docking studies and 100 ns MD simulations performed on the AChE, MAO-B, and COX-2 ligand-protein complexes revealed stable conformations of the ligand-protein interactions throughout the simulations.

Computational studies on the functional and structural impact of pathogenic mutations in enzymes

Enzymes are critical biological catalysts involved in maintaining the intricate balance of metabolic processes within living organisms. Mutations in enzymes can result in disruptions to their functionality that may lead to a range of diseases. This review focuses on computational studies that investigate the effects of disease-associated mutations in various enzymes. Through molecular dynamics simulations, multiscale calculations, and machine learning approaches, computational studies provide detailed insights into how mutations impact enzyme structure, dynamics, and catalytic activity. This review emphasizes the increasing impact of computational simulations in understanding molecular mechanisms behind enzyme (dis)function by highlighting the application of key computational methodologies to selected enzyme examples, aiding in the prediction of mutation effects and the development of therapeutic strategies.

Redefining a new frontier in alkaptonuria therapy with AI-driven drug candidate design via in- silico innovation

A rare metabolic condition called alkaptonuria (AKU) is caused by a decrease in homogentisate 1,2 dioxygenase (HGO) activity due to a mutation in homogentisate dioxygenase (HGD) gene. Homogentisic acid is a byproduct of the catabolism of tyrosine and phenylalanine that darkens the urine and accumulates in connective tissues which causes an agonizing arthritis. Employing the use of deep learning artificial intelligence (AI) drug design, this study aims to alleviate the current toxicity of the AKU drugs currently in use, particularly nitisinone, by utilizing the natural flavanol kaempferol molecule as a 4-hydroxyphenylpyruvate dioxygenase inhibitor. Kaempferol was employed to generate three effective de novo drug candidates targeting the enzyme 4-hydroxyphenylpyruvate dioxygenase using an AI drug design tool. We present novel AIK formulations in the present study. The AIK's (Artificial Intelligence Kaempferol) examination of drug-likeliness among the three led to its choice as a possible target. The toxicity assessment research of AIK demonstrates that it is not only safer to use than other treatments, but also more efficient. The docking of the AIGT with 4-hydroxyphenylpyruvate dioxygenase, which revealed a binding affinity of around -9.099 kcal/mol, highlights the AIK's potential as a therapeutic candidate. An innovative approach to deal with challenging circumstances is thus presented in this study by new formulations kaempferol that have been meticulously designed by AI. The results of the in vitro tests must be confirmed in vivo, even though AI-designed AIK is effective and sufficiently safe as computed.

Identification of promising SARS-CoV-2 main protease inhibitor through molecular docking, dynamics simulation, and ADMET analysis

The COVID-19 pandemic caused by SARS-CoV-2 continues to pose a major challenge to global health. Targeting the main protease of the virus (Mpro), which is essential for viral replication and transcription, offers a promising approach for therapeutic intervention. In this study, advanced computational techniques such as molecular docking and molecular dynamics simulations were used to screen a series of antiviral compounds for their potential inhibitory effect on the SARS-CoV-2 Mpro. A comprehensive analysis of compounds from the ChemDiv and PubChem databases was performed. The physicochemical properties, pharmacokinetics, and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiles were evaluated to determine drug similarity and safety. Compound 4896 - 4038 proved to be the most promising candidate. It exhibited a favorable balance between molecular weight (491.06) and lipophilicity (logP 3.957), high intestinal absorption (92.119%), and broad tissue distribution (VDss of 0.529), indicating good oral bioavailability and therapeutic potential. Molecular docking studies showed that 4896 - 4038 has a strong binding affinity to the active site of Mpro and forms key interactions, such as hydrogen bonds, carbon-hydrogen bonds, pi-sulfur, and multiple van der Waals and pi-pi stacked bonds. The binding energy was comparable to that of the reference drug X77, indicating potential efficacy. Molecular dynamics simulations over 300 ns confirmed the stability of the Mpro/4896 - 4038 complex of protein-ligand. Free energy landscape mapping and MM/PBSA calculations further substantiated the favorable binding and stability of the complex. Importantly, 4896 - 4038 exhibited a comparatively favorable safety profile. In summary, compound 4896 - 4038 shows significant potential as a potent SARS-CoV-2 Mpro inhibitor, combining potent inhibitory activity with favorable pharmacokinetic and safety profiles. These results support the further development of 4896 - 4038 as a promising therapeutic agent in the fight against COVID-19 that warrants experimental validation and clinical investigation.

Discovery of the selective and nanomolar inhibitor of DPP-4 more potent than sitagliptin by structure-guided rational design

Various therapeutic targets and approaches are commonly employed in the management of Type 2 Diabetes. These encompass diverse groups of drugs that target different mechanisms involved in glucose regulation. Inhibition of the DPP-4 enzyme has been proven an excellent target for antidiabetic drug design. Our previous work on discovering multitarget antidiabetic drugs led to the identification of a gallic acid-thiazolidinedione hybrid as a potent DPP4 inhibitor (IC50 = 36 nM). In current research, our efforts resulted in a new dihydropyrimidine-based scaffold with enhanced DPP4 inhibition potential. After virtual evaluation, the designed molecules with excellent interaction patterns and binding energy values were synthesized in the wet laboratory. The inhibition potential of synthesized compounds was assessed against the DPP-4 enzyme. Compound 46 with single digit IC50 value 2 nM exhibited 4-fold and 18-fold higher activity than Sitagliptin and our previously reported hybrid respectively. Moreover, compounds 46, 47 and 50 have shown manyfold selectivity against DPP8 and DPP9. Further pretreatment with compounds 43, 45-47 and 50 (at doses of 10 and 20 mg/kg) in OGTT conducted on rats resulted in a significant decrease in the serum glucose levels compared to the control group. In the long-term STZ-induced diabetic rats, tested compound 50 performed similarly to the reference drug. Molecular dynamics simulations and in-silico molecular docking studies were employed to elucidate the time-dependent interactions of inhibitors within the active sites of DPP4. The compounds examined in this work might serve as a possible lead in the development of effective diabetic mellitus treatments.

Exploring optimal drug targets through subtractive proteomics analysis and pangenomic insights for tailored drug design in tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis, ranks among the top causes of global human mortality, as reported by the World Health Organization's 2022 TB report. The prevalence of M. tuberculosis strains that are multiple and extensive-drug resistant represents a significant barrier to TB eradication. Fortunately, having many completely sequenced M. tuberculosis genomes available has made it possible to investigate the species pangenome, conduct a pan-phylogenetic investigation, and find potential new drug targets. The 442 complete genome dataset was used to estimate the pangenome of M. tuberculosis. This study involved phylogenomic classification and in-depth analyses. Sequential filters were applied to the conserved core genome containing 2754 proteins. These filters assessed non-human homology, virulence, essentiality, physiochemical properties, and pathway analysis. Through these intensive filtering approaches, promising broad-spectrum therapeutic targets were identified. These targets were docked with FDA-approved compounds readily available on the ZINC database. Selected highly ranked ligands with inhibitory potential include dihydroergotamine and abiraterone acetate. The effectiveness of the ligands has been supported by molecular dynamics simulation of the ligand-protein complexes, instilling optimism that the identified lead compounds may serve as a robust basis for the development of safe and efficient drugs for TB treatment, subject to further lead optimization and subsequent experimental validation.

Anti-inflammatory and anti-diabetic properties of indanone derivative isolated from Fernandoa adenophylla in vitro and in silico studies

Fernandoa adenophylla, due to the presence of phytochemicals, has various beneficial properties and is used in folk medicine to treat many conditions. This study aimed to isolate indanone derivative from F. adenophylla root heartwood and assess in-vitro anti-inflammatory and anti-diabetic characteristics at varying concentrations. Heat-induced hemolysis and glucose uptake by yeast cells assays were conducted to evaluate these properties. Besides, docking analyses were performed on four molecular targets. These studies were combined with molecular dynamics simulations to elucidate the time-evolving inhibitory effect of selected inhibitors within the active pockets of the target proteins (COX-1 and COX-2). Indanone derivative (10-100 µM) inhibited the lysis of human red blood cells from 9.12 ± 0.75 to 72.82 ± 4.36% and, at 5-100 µM concentrations, it significantly increased the yeast cells' glucose uptake (5.16 ± 1.28% to 76.59 ± 1.62%). Concluding, the isolated indanone might act as an anti-diabetic agent by interacting with critical amino acid residues of 5' adenosine monophosphate-activated protein kinase (AMPK), and it showed a binding affinity with anti-inflammatory targets COX-1, COX-2, and TNF-α. Besides, the obtained results may help to consider the indanone derivative isolated from F. adenophylla as a promising candidate for drug delivery, subject to outcomes of further in vivo and clinical studies.

XRD/DFT, Hirshfeld surface analysis and molecular modelling simulations for unfolding reactivity of newly synthesized vanillin derivatives: excellent optical, NLO and protein binding efficiency

New vanillin derivatives, namely, ethyl (4-formyl-2-methoxyphenoxy)acetate (2a) and 2-(4-formyl-2-methoxyphenoxy)-N-phenylacetamide (2b), respectively, were synthesized and characterized by NMR (1H and 13C), IR, mass spectra and confirmed by single-crystal X-ray analysis. Hirshfeld surface (HS) analysis was performed to probe intra- and intermolecular interactions and surface reactivity. 2D fingerprint plots (FP) were used to study the nature and percentage contribution of intermolecular interactions leading to the formation of the crystal unit. Density functional theory (DFT) simulations were used to obtain the electronic structure and reactivity of the new molecules. Natural population analysis (NPA) and frontier molecular orbital (FMO) calculations reveal significant charge transfer and a reduced HOMO-LUMO gap up to 4.34 eV for 2b. Bader's quantum theory of atoms in molecules (QTAIM) study is utilized to understand the surface topological and bonding nature of 2a and 2b. The performed molecular electrostatic potential (MESP) and density of states (DOS) study further suggest sites likely to be attractive to incoming reagents. At the same time, hyperpolarizability (βo) is used to characterize the nonlinear optical properties, and TD-DFT study shows the excitation energy and absorption behavior. In silico studies were performed, including docking, binding free energies (MMBGSA) and molecular dynamics simulations. Compounds 2a and 2b were docked with RdRp of SARS-Cov-2, and the MMBGSA for 2a and 2b were -30.70 and -28.47 kcal/mol, respectively, while MD simulation showed the stability of protein-ligand complexes.Communicated by Ramaswamy H. Sarma.

Designing a novel chimeric multi-epitope vaccine subunit against Staphylococcus argenteus through artificial intelligence approach integrating pan-genome analysis, in vitro identification, and immunogenicity profiling

Staphylococcus argenteus is a newly identified pathogen that causes respiratory tract infections, skin infections, such as cellulitis, abscesses, and impetigo, and currently, there is no licensed vaccine available against it. To develop a vaccine against S. argenteus, a bacterial pan-genome analysis was applied to identify potential vaccine candidates. A total of 4908 core proteins were retrieved and utilized for identifying four proteins, including SG38 Panton-Valentine leukocidin LukS-PV protein, SG62 staphylococcal enterotoxin type A protein, SG39 enterotoxin B protein, and SG43 enterotoxin type C3 protein as potential vaccine candidates. Epitopes were predicted for these proteins using different types of B and T-cell epitope prediction tools, and only those with a non-toxic profile, antigenic, non-allergenic, and immunogenic were selected. The selected epitopes were linked to each other to form a multi-epitope vaccine construct, which was further linked to the PADRE sequence (AKFVAAWTLKAAA) and 50s ribosomal L7/L12 protein to enhance the vaccine's antigenicity. The three-dimensional structure of the vaccine construct was assessed to determine its binding affinity with key Toll-like receptor 9 (TLR-9) and Toll-like receptor 5 (TLR-5) immune cell receptors. Our findings demonstrate that the vaccine exhibits favorable binding interactions with these immune cell receptors, indicating its potential efficacy. Molecular dynamic simulations further confirmed the accessibility of vaccine epitopes to the host immune system, substantiating its ability to elicit protective immune responses. Taken together, this study highlights the promising candidacy of the modeled vaccine construct for future in vivo and in vitro experimental investigations.Communicated by Ramaswamy H. Sarma.

Computational Modeling, High-Level Soluble Expression and In Vitro Cytotoxicity Assessment of Recombinant Pseudomonas aeruginosa Azurin: A Promising Anti-Cancer Therapeutic Candidate

Azurin is a natural protein produced by Pseudomonas aeruginosa that exhibits potential anti-tumor, anti-HIV, and anti-parasitic properties. The current study aimed to investigate the potential of azurin protein against breast cancer using both in silico and in vitro analyses. The amino acid sequence of Azurin was used to predict its secondary and tertiary structures, along with its physicochemical properties, using online software. The resulting structure was validated and confirmed using Ramachandran plots and ERRAT2. The mature azurin protein comprises 128 amino acids, and the top-ranked structure obtained from I-TASSER was shown to have a molecular weight of 14 kDa and a quality factor of 100% by ERRAT2, with 87.4% of residues in the favored region of the Ramachandran plot. Docking and simulation studies of azurin protein were conducted using HDOCK and Desmond servers, respectively. The resulting analysis revealed that Azurin docked against p53 and EphB2 receptors demonstrated maximum binding affinity, indicating its potential to cause apoptosis. The recombinant azurin gene was successfully cloned and expressed in a BL21 (DE3) strain using a pET20b expression vector under the control of the pelB ladder, followed by IPTG induction. The azurin protein was purified to high levels using affinity chromatography, yielding 70 mg/L. In vitro cytotoxicity assay was performed using MCF-7 cells, revealing the significant cytotoxicity of the azurin protein to be 105 µg/mL. These findings highlight the potential of azurin protein as an anticancer drug candidate.

In Silico Investigation of a Chimeric IL24-LK6 Fusion Protein as a Potent Candidate Against Breast Cancer

Targeted delivery of therapeutic anticancer chimeric molecules enhances the efficacy of drug by improving cellular uptake and circulation time. Engineering the molecules to facilitate the specific interaction between chimeric protein and its receptor is critical to elucidate biological mechanism as well as accuracy in modeling of complexes. A theoretically designed novel protein-protein interfaces can serve as a bottom-up method for comprehensive understanding of interacting protein residues. This study was aimed for in silico analyses of a chimeric fusion protein against breast cancer. The amino acid sequences of the interleukin 24 (IL-24) and LK-6 peptide were used to design the chimeric fusion protein via a rigid linker. The secondary and tertiary structures along with physicochemical properties by ProtParam and solubility were predicted using online software. The validation and quality of the fusion protein was confirmed by Rampage and ERRAT2. The newly designed fusion construct has a total length of 179 amino acids. The top-ranked structure from alpha fold2 showed 18.1 KD molecular weight by ProtParam, quality factor of 94.152 by ERRAT, and a valid structure by a Ramachandran plot with 88.5% residues in the favored region. Finally, the docking and simulation studies were performed using HADDOCK and Desmond module of Schrodinger. The quality, validity, interaction analysis, and stability of the fusion protein depict a functional molecule. The fusion gene IL24-LK6 after cloning and expression in a suitable prokaryotic cell might be a useful candidate for developing a novel anticancer therapy.

In-silico assessment of high-risk non-synonymous SNPs in ADAMTS3 gene associated with Hennekam syndrome and their impact on protein stability and function

Hennekam Lymphangiectasia-Lymphedema Syndrome 3 (HKLLS3) is a rare genetical disorder caused by mutations in a few genes including ADAMTS3. It is characterized by lymphatic dysplasia, intestinal lymphangiectasia, severe lymphedema and distinctive facial appearance. Up till now, no extensive studies have been conducted to elucidate the mechanism of the disease caused by various mutations. As a preliminary investigation of HKLLS3, we sorted out the most deleterious nonsynonymous single nucleotide polymorphisms (nsSNPs) that might affect the structure and function of ADAMTS3 protein by using a variety of in silico tools. A total of 919 nsSNPs in the ADAMTS3 gene were identified. 50 nsSNPs were predicted to be deleterious by multiple computational tools. 5 nsSNPs (G298R, C567Y, A370T, C567R and G374S) were found to be the most dangerous and can be associated with the disease as predicted by different bioinformatics tools. Modelling of the protein shows it can be divided into segments 1, 2 and 3, which are connected by short loops. Segment 3 mainly consists of loops without substantial secondary structures. With prediction tools and molecular dynamics simulation, some SNPs were found to significantly destabilize the protein structure and disrupt the secondary structures, especially in segment 2. The deleterious effects of mutations in segment 1 are possibly not from destabilization but from other factors such as the change in phosphorylation as suggested by post-translational modification (PTM) studies. This is the first-ever study of ADAMTS3 gene polymorphism, and the predicted nsSNPs in ADAMST3, some of which have not been reported yet in patients, will serve for diagnostic purposes and further therapeutic implications in Hennekam syndrome, contributing to better diagnosis and treatment.

Switching of newly synthesized linker-based derivatives of non-steroidal anti-inflammatory drugs toward anti-inflammatory and anticancer activity

A new series of linker-based derivatives of non-steroidal anti-inflammatory drugs were designed and synthesized. All the compounds were well characterized with the help of various spectroscopic techniques such as FT-IR, ¹H NMR, ¹³C NMR, and HRMS. The main emphasis of this paper is to understand the switching of the most promising compounds 8 and 10 towards anti-inflammatory and anticancer activity in terms of in-silico and in-vitro studies in detail. During the molecular docking study, compounds 8 and 10 demonstrated the importance of hetero atoms as well as the perfect alignment of a compound in the binding pocket of a target site, which may affect their bioactivity. Here, the presence of 1,3‑dicarbonyl interactions with ASN 351 in compound 8 (not found in compound 10) may be responsible for its better inhibitory activity against the COX-2 target site. On the other hand, a slight increase in the potency of compound 10 towards anticancer activity may be due to the instantaneous participation of the OH group and carbonyl group to give conventional hydrogen bonds towards THR 149 amino acid residue, which was missing in compound 8. Molecular dynamics simulation was also performed for compounds 10 and 8 toward COX-2 and HER-2 protein sites. Further, compounds 8 and 10 were subjected to in-vitro COX-2 inhibition and cytotoxicity assay and the results obtained were in accordance with the in-silico study. Thus, compound 8 become more potent towards COX-2 inhibition with IC₅₀ value of 48.51 µg/ml and compound 10 showed good bioactivity toward cytotoxic activity with IC₅₀ value of 93.03 µg/ml.

Predicting the effects of rare genetic variants on oncogenic signaling pathways: A computational analysis of HRAS protein function

The HRAS gene plays a crucial role in regulating essential cellular processes for life, and this gene's misregulation is linked to the development of various types of cancers. Nonsynonymous single nucleotide polymorphisms (nsSNPs) within the coding region of HRAS can cause detrimental mutations that disrupt wild-type protein function. In the current investigation, we have employed in-silico methodologies to anticipate the consequences of infrequent genetic variations on the functional properties of the HRAS protein. We have discovered a total of 50 nsSNPs, of which 23 were located in the exon region of the HRAS gene and denoting that they were expected to cause harm or be deleterious. Out of these 23, 10 nsSNPs ([G60V], [G60D], [R123P], [D38H], [I46T], [G115R], [R123G], [P11OL], [A59L], and [G13R]) were identified as having the most delterious effect based on results of SIFT analysis and PolyPhen2 scores ranging from 0.53 to 69. The DDG values -3.21 kcal/mol to 0.87 kcal/mol represent the free energy change associated with protein stability upon mutation. Interestingly, we identified that the three mutations (Y4C, T58I, and Y12E) were found to improve the structural stability of the protein. We performed molecular dynamics (MD) simulations to investigate the structural and dynamic effects of HRAS mutations. Our results showed that the stable model of HRAS had a significantly lower energy value of -18756 kj/mol compared to the initial model of -108915 kj/mol. The RMSD value for the wild-type complex was 4.40 Å, and the binding energies for the G60V, G60D, and D38H mutants were -107.09 kcal/mol, -109.42 kcal/mol, and -107.18 kcal/mol, respectively as compared to wild-type HRAS protein had -105.85 kcal/mol. The result of our investigation presents convincing corroboration for the potential functional significance of nsSNPs in augmenting HRAS expression and adding to the activation of malignant oncogenic signalling pathways.

Osteoclast rich osteopetrosis due to defects in the TCIRG1 gene

Discovery that mutations in TCIRG1 (also known as Atp6i) gene are responsible for most instances of autosomal recessive osteopetrosis (ARO) heralded a new era for comprehension and treatment of this phenotypically heterogeneous rare bone disease. TCIRG1 encodes the a3 subunit, an essential isoform of the vacuolar ATPase proton pump involved in acidification of the osteoclast resorption lacuna and in secretory lysosome trafficking. TCIRG1 defects lead to inefficient bone resorption by nonfunctional osteoclasts seen in abundance on bone marrow biopsy, delineating this ARO as 'osteoclast-rich'. Presentation is usually in early childhood and features of extramedullary haematopoiesis (hepatosplenomegaly, anaemia, thrombocytopenia) due to bone marrow fibrosis, and cranial nerve impingement (blindness in particular). Impaired dietary calcium uptake due to high pH causes the co-occurrence of rickets, described as "osteopetrorickets". Osteoclast dysfunction leads to early death if untreated, and allogeneic haematopoietic stem cell transplantation is currently the treatment of choice. Studies of patients as well as of mouse models carrying spontaneous (the oc/oc mouse) or targeted disruption of Atp6i (TCIRG1) gene have been instrumental providing insight into disease pathogenesis and development of novel cellular therapies that exploit gene correction.