Structural signatures of DRD4 mutants revealed using molecular dynamics simulations: Implications for drug targeting

Exploring the impact of deleterious missense nonsynonymous single nucleotide polymorphisms in the DRD4 gene using computational approaches

Dopamine receptor D4 (DRD4) plays a vital role in regulating various physiological functions, including attention, impulse control, and sleep, as well as being associated with various neurological diseases, including attention deficit hyperactivity disorder, novelty seeking, and so on. However, a comprehensive analysis of harmful nonsynonymous single nucleotide polymorphisms (nsSNPs) of the DRD4 gene and their effects remains unexplored. The aim of this study is to uncover novel damaging missense nsSNPs and their structural and functional effects on the DRD4 receptor. From the dbSNP database, we found 677 nsSNPs, and then we analyzed their functional consequences, disease associations, and effects on protein stability with fifteen in silico tools. Five variants, including L65ICL1P (rs1459150721), V1163.33D (rs761875546), I1293.46S (rs751467198), I1564.46T (rs757732258), and F2015.47S (rs199609858), were identified as the most deleterious mutations that were also present in the conserved region and showed lower interactions with neighboring residues. To comprehensively understand their impact, we docked agonist dopamine and antagonist nemonapride at the binding site of the receptor, followed by 200 ns molecular dynamics simulations. We identified the V116D and I129S mutations as the most damaging, followed by F201S in the dopamine-bound states. Both the V116D and I129S variants demonstrated significantly high RMSD, Rg, and SASA, and low thermodynamic stability. The F201S-dopamine complex exhibited lower compactness and higher motions, along with a significant loss of hydrogen bonds and active site interactions. By contrast, while interacting with nemonapride, the impact of the I156T and L65P mutations was highly deleterious; both showed lower stability, higher flexibility, and higher motions. Additionally, nemonapride significantly lost interactions with the active site, notably in the I156T variant. We also found the V116D-nemonapride complex as structurally damaging; however, the interaction patterns of nemonapride were less altered in the MMPBSA analysis. Overall, this study revealed five novel deleterious variants along with a comprehensive understanding of their effect in the presence of an agonist and antagonist, which could be helpful for understanding disease susceptibility, precision medicine, and developing potential drugs.

The Pivotal Distinction between Antagonists' and Agonists' Binding into Dopamine D4 Receptor-MD and FMO/PIEDA Studies

The dopamine D4 receptor (D4R) is a promising therapeutic target in widespread diseases, and the search for novel agonists and antagonists appears to be clinically relevant. The mechanism of binding to the receptor (R) for antagonists and agonists varies. In the present study, we conducted an in-depth computational study, teasing out key similarities and differences in binding modes, complex dynamics, and binding energies for D4R agonists and antagonists. The dynamic network method was applied to investigate the communication paths between the ligand (L) and G-protein binding site (GBS) of human D4R. Finally, the fragment molecular orbitals with pair interaction energy decomposition analysis (FMO/PIEDA) scheme was used to estimate the binding energies of L-R complexes. We found that a strong salt bridge with D3.32 initiates the inhibition of the dopamine D4 receptor. This interaction also occurs in the binding of agonists, but the change in the receptor conformation to the active state starts with interaction with cysteine C3.36. Such a mechanism may arise in the case of agonists unable to form a hydrogen bond with the serine S5.46, considered, so far, to be crucial in the activation of GPCRs. The energy calculations using the FMO/PIEDA method indicate that antagonists show higher residue occupancy of the receptor binding site than agonists, suggesting they could form relatively more stable complexes. Additionally, antagonists were characterized by repulsive interactions with S5.46 distinguishing them from agonists.

The interaction analysis between human serum albumin with chlorpyrifos and its derivatives through sub-atomic docking and molecular dynamics simulation techniques

Chlorpyrifos (CPF) is an extensively used organophosphate pesticide for crop protection. However, there are concerns about it contaminating the environment and human health, with estimated three lakh deaths annually. The molecular modeling protocol was assisted in redesigning thirteen well-known CPF linkers and inserting them at five selectable CPF (R1-R5) positions of CPF to get 258 CPF derivatives. CPF and its derivatives were optimized using LigPrep and docked to a grid centralized on Trp214 using extra precision glide docking. The Binding free energy of complexes was calculated using molecular mechanics/generalized born surface area (MM-GBSA). CPF and CPFD-225 have glide scores of - 3.08 and - 6.152 kcal/mol, respectively, with human serum albumin and ΔG bind for CPF (- 33.041817 kcal/mol) (- 52.825 kcal/mol) for CPF-D225. The top ten CPF derivatives showed at least ninefold better binding free energy than the CPF proposed for polyclonal antibody production. Subsequently, molecular docking studies revealed that CPF and its derivatives could bind to human serum albumin (HSA). Furthermore, using the Desmond package, a 100-ns molecular dynamics (MD) simulation was performed on the potential binding site. The final systems of CPF-HSA and CPF-222D complexes consist of 76,014 and 76,026 atoms, respectively. The physical stability of both the systems (CPF-HSA and CPF-222D) was analyzed by considering the overall potential energy, RMSF, RMSD, Hydrophobic interactions, and water-mediated patterns, which showed total energy of - 141,610 kcal/mol and - 140,150 kcal/mol, respectively.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03344-7.

A next generation sequencing gene panel for use in the diagnosis of anorexia nervosa

PURPOSE

The aim of this study was to increase knowledge of genes associated with anorexia nervosa (AN) and their diagnostic offer, using a next generation sequencing (NGS) panel for the identification of genetic variants. The rationale underlying this test is that we first analyze the genes associated with syndromic forms of AN, then genes that were found to carry rare variants in AN patients who had undergone segregation analysis, and finally candidate genes intervening in the same molecular pathways or identified by GWAS or in mouse models.

METHODS

We developed an NGS gene panel and used it to screen 68 Italian AN patients (63 females, 5 males). The panel included 162 genes. Family segregation study was conducted on available relatives of probands who reported significant genetic variants.

RESULTS

In our analysis, we found potentially deleterious variants in 2 genes (PDE11A and SLC25A13) associated with syndromic forms of anorexia and predicted deleterious variants in the following 12 genes: CD36, CACNA1C, DRD4, EPHX2, ESR1, GRIN2A, GRIN3B, LRP2, NPY4R, PTGS2, PTPN22 and SGPP2. Furthermore, by Sanger sequencing of the promoter region of NNAT, we confirmed the involvement of this gene in the pathogenesis of AN. Family segregation studies further strengthened the possible causative role of CACNA1C, DRD4, GRIN2A, PTGS2, SGPP2, SLC25A13 and NNAT genes in AN etiology.

CONCLUSION

The major finding of our study is the confirmation of the involvement of the NNAT gene in the pathogenesis of AN; furthermore, this study suggests that NGS-based testing can play an important role in the diagnostic evaluation of AN, excluding syndromic forms and increasing knowledge of the genetic etiology of AN.

LEVEL OF EVIDENCE

Level I, experimental study.

An association study in the Taiwan Biobank elicits three novel candidates for cognitive aging in old adults: NCAM1, TTC12 and ZBTB20

The dopamine receptor-related loci have been suggested to be associated with cognitive functions and neurodegenerative diseases. It is unknown whether genetic variants such as single nucleotide polymorphisms (SNPs) in the dopamine receptor-related loci could contribute to cognitive aging independently as well as by virtue of complicated interplays in the elder population. To assess whether SNPs in the dopamine receptor-related loci are associated with cognitive aging in the elder population, we evaluated SNPs in the DRD1, NCAM1-TTC12-ANKK1-DRD2, DRD3-LOC107986115-ZNF80-TIGIT-MIR568-ZBTB20, DRD4, and DRD5-SLC2A9 loci from 25,195 older Taiwanese individuals from the Taiwan Biobank. Mini-Mental State Examination (MMSE) was scrutinized for all participants, where MMSE scores were employed to evaluate cognitive functions. From our analysis, we identified three novel genes for cognitive aging that have not previously been reported: ZBTB20 on chromosome 3 and NCAM1 and TTC12 on chromosome 11. NCAM1 and ZBTB20 are strong candidates for having a role in cognitive aging with mutations in ZBTB20 resulting in intellectual disability, and NCAM1 previously found to be associated with associative memory in humans. Additionally, we found the effects of interplays between physical activity and these three novel genes. Our study suggests that genetic variants in the dopamine receptor-related loci may influence cognitive aging individually and by means of gene-physical activity interactions.

Benefits and Challenges of Rare Genetic Variation in Alzheimer's Disease

Purpose of Review

It is well established that sporadic Alzheimer's disease (AD) is polygenic with common and rare genetic variation alongside environmental factors contributing to disease. Here, we review our current understanding of the genetic architecture of disease, paying specific attention to rare susceptibility variants, and explore some of the limitations in rare variant detection and analysis.

Recent Findings

Rare variation has been shown to robustly associate with disease. These include potentially damaging and loss of function mutations that are easily modelled in silico, in vitro and in vivo, and represent potentially druggable targets. A number of risk genes, including TREM2, SORL1 and ABCA7 show multiple independent associations suggesting that they may influence disease via multiple mechanisms. With transcriptional regulation, inflammatory response and modification of protein production suggested to be of primary importance.

Summary

We are at the beginning of our journey of rare variant detection in AD. Whole exome sequencing has been the predominant technology of choice. While fruitful, this has introduced a number of challenges with regard to data integration. Ultimately the future of disease-associated rare variant identification lies in whole genome sequencing projects that will allow the testing of the full range of genomic variation.