Molecular insights of the G2019S substitution in LRRK2 kinase domain associated with Parkinson's disease: A molecular dynamics simulation approach

In silico prediction of CD8+ and CD4+ T cell epitopes in Leishmania major proteome: Using immunoinformatics

The leishmaniases are NDTs (neglected tropical diseases) that affect people all over the world. They are brought on by protozoans from the genus Leishmania and disseminated by phlebotomine flies that are afflicted with the disease. The best option to manage and lower the incidence of these diseases has been thought by the creation of a safe and effective vaccination. This research used an in silico based mining approach to look for high potential epitopes that might bind to MHC Class I and MHC Class II molecules (mainly; HLA-A*02:01 & HLA-DRB1*03:01) from human population in order to promote vaccine development. Based on the presence of signal peptides, GPI anchors, antigenicity predictions, and a subtractive proteomic technique, we have screened 17 putative antigenic proteins from the 8083 total proteins of L. major. After that thorough immunogenic epitope prediction were done using IEDB-AR tools. We isolated five immunogenic epitopes (three 9-mer & two 15-mer) from five antigenic proteins through docking and MD simulation analysis. Finally, these five anticipated epitopes, viz., TLPEIPVNV, ELMAPVFGL, TLAAAVALL, NSINIRLDGVTSAGF and NVPLVVDASSLFRVA have considerably stronger binding potential with their respective alleles and may trigger immunological responses. The goal of this work was to identify MHC restricted epitopes for CD8+ and CD4+ T cells activation using immunoinformatics in order to identify potential vaccine candidates against L. major parasites.

A computational approach to analyzing the functional and structural impacts of Tripeptidyl-Peptidase 1 missense mutations in neuronal ceroid lipofuscinosis

Neuronal ceroid-lipofuscinosis (NCLs) are a group of severe neurodegenerative conditions, most likely present in infantile, late infantile, juvenile, and adult-onset forms. Their phenotypic characteristics comprise eyesight damage, reduced motor activity and cognitive function, and sometimes tend to die in the initial stage. In recent studies, NCLs have been categorized into at least 14 genetic collections (CLN1-14). CLN2 gene encodes Tripeptidyl peptidase 1 (TPP1), which affects late infantile-onset form. In this study, we retrieved a mutational dataset screening for TPP1 protein from various databases (ClinVar, UniProt, HGMD). Fifty-six missense mutants were enumerated with computational methods to perceive the significant mutants (G475R and G501C) and correlated with clinical and literature data. A structure-based screening method was initiated to understand protein-ligand interaction and dynamic simulation. The docking procedure was performed for the native (3EDY) and mutant (G473R and G501C) structures with Gemfibrozil (gem), which lowers the lipid level, decreases the triglycerides amount in the blood circulation, and controls hyperlipidemia. The Native had an interaction score of -5.57 kcal/mol, and the mutants had respective average binding scores of -6.24 (G473R) and - 5.17 (G501C) kcal/mol. Finally, molecular dynamics simulation showed that G473R and G501C mutants had better flexible and stable orientation in all trajectory analyses. Therefore, this work gives an extended understanding of both functional and structural levels of influence for the mutant form that leads to NCL disorder.

Multi-method computational evaluation of the inhibitors against leucine-rich repeat kinase 2 G2019S mutant for Parkinson's disease

Leucine-rich repeat kinase 2 G2019S mutant (LRRK2 G2019S) is a potential target for Parkinson's disease therapy. In this work, the computational evaluation of the LRRK2 G2019S inhibitors was conducted via a combined approach which contains a preliminary screening of a large database of compounds via similarity and pharmacophore, a secondary selection via structure-based affinity prediction and molecular docking, and a rescoring treatment for the final selection. MD simulations and MM/GBSA calculations were performed to check the agreement between different prediction methods for these inhibitors. 331 experimental ligands were collected, and 170 were used to build the structure-activity relationship. Eight representative ligand structural models were employed in similarity searching and pharmacophore screening over 14 million compounds. The process for selecting proper molecular descriptors provides a successful sample which can be used as a general strategy in QSAR modelling. The rescoring used in this work presents an alternative useful treatment for ranking and selection.

Computational identification and analysis of deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in the human POR gene: a structural and functional impact

Cytochrome P450 oxidoreductase (POR) protein is essential for steroidogenesis, and POR gene mutations are frequently associated with P450 Oxidoreductase Deficiency (PORD), a disorder of hormone production. To our knowledge, no previous attempt has been made to identify and analyze the deleterious/pathogenic non-synonymous single nucleotide polymorphisms (nsSNPs) in the human POR gene through an extensive computational approach. Computational algorithms and tools were employed to identify, characterize, and validate the pathogenic SNPs associated with certain diseases. To begin with, all the high-confidence SNPs were collected, and their structural and functional impacts on the protein structures were explored. The results of various in silico analyses affirm that the A287P and R457H variants of POR could destabilize the interactions between the amino acids and the hydrogen bond networks, resulting in functional deviations of POR. The literature study further confirms that the pathogenic mutations (A287P and R457H) are associated with the onset of PORD. Molecular dynamics simulations (MDS) and essential dynamics (ED) studies characterized the structural consequences of prioritized deleterious mutations, representing the structural destabilization that might disrupt POR biological function. The identified deleterious mutations at the cofactor's binding domains might interfere with the essential interactions between the protein and cofactors, thus inhibiting POR catalytic activity. The consolidated insights from the computational analyses can be used to predict potential deleterious mutants and understand the disease's pathological basis and the molecular mechanism of drug metabolism for the application of personalized medication. HIGHLIGHTSNADPH cytochrome P450 oxidoreductase (POR) mutations are associated with a broad spectrum of human diseasesIdentified and analyzed the most deleterious nsSNPs of POR through the sequence and structure-based prediction toolsInvestigated the structural and functional impacts of the most significant mutations (A287P and R457H) associated with PORDMolecular dynamics and PCA-based FEL analysis were utilized to probe the mutation-induced structural alterations in PORCommunicated by Ramaswamy H. Sarma.

Genomic insights and advanced machine learning: characterizing autism spectrum disorder biomarkers and genetic interactions

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by altered brain connectivity and function. In this study, we employed advanced bioinformatics and explainable AI to analyze gene expression associated with ASD, using data from five GEO datasets. Among 351 neurotypical controls and 358 individuals with autism, we identified 3,339 Differentially Expressed Genes (DEGs) with an adjusted p-value (≤ 0.05). A subsequent meta-analysis pinpointed 342 DEGs (adjusted p-value ≤ 0.001), including 19 upregulated and 10 down-regulated genes across all datasets. Shared genes, pathogenic single nucleotide polymorphisms (SNPs), chromosomal positions, and their impact on biological pathways were examined. We identified potential biomarkers (HOXB3, NR2F2, MAPK8IP3, PIGT, SEMA4D, and SSH1) through text mining, meriting further investigation. Additionally, ‎we shed light on the roles of RPS4Y1 and KDM5D genes in neurogenesis and neurodevelopment. Our analysis detected 1,286 SNPs linked to ASD-related conditions, of which 14 high-risk SNPs were located on chromosomes 10 and X. We highlighted potential missense SNPs associated with FGFR inhibitors, suggesting that it may serve as a promising biomarker for responsiveness to targeted therapies. Our explainable AI model identified the MID2 gene as a potential ASD biomarker. This research unveils vital genes and potential biomarkers, providing a foundation for novel gene discovery in complex diseases.

In-silico bioprospecting of secondary metabolites from endophytic Streptomyces spp. against Magnaporthe oryzae, a cereal killer fungus

Rice blast disease, caused by Magnaporthe oryzae, is the most devastating cereal killer worldwide. Note that melanin pigment is an essential factor of M. oryzae virulence, thus fungicides interfering with melanin biosynthesizing enzymes would reduce the pathogenicity. Scytalone dehydratase (SDH) is the key target for commercial fungicides, like carpropamid, due to its role in the dehydration reaction of the fungal melanin pathway. However, a single-point mutation (V75M) in SDH elicits resistance to carpropamid. A lack of effective fungicides against this resistant strain expedited the quest for novel bioactive inhibitors. Currently, bacterial endophytes like Streptomyces have been heralded for synthesizing bioactive metabolites to protect plants from phytopathogens. The literature search led to the identification of 21 Streptomyces spp. symbionts of paddy that can suppress M. oryzae growth. An antiSMASH server was used to explore Streptomyces spp. gene clusters and found 4463 putative metabolites. Besides, 745 unique metabolites were subjected to a series of virtual screening techniques. Ideally, this process identified five potential SDH inhibitors. The docking result highlights that the metabolite pseudopyronine A interacted hydrophobically with both Val75 of SDHWT and Met75 of SDHV75M targets. Moreover, pseudopyronine A has a higher binding free energy with SDHWT (- 89.94 kcal/mol) and SDHV75M (- 71.95 kcal/mol). Interestingly, the pyranones scaffold of pseudopyronine A was reported for antifungal activity against phytopathogens. Dynamic behavior confirms that pseudopyronine A has excellent conformational states with both SDHWT and SDHV75M. Altogether, we hope that this study creates a new avenue for the discovery of novel phytopathogen inhibitors from endophytes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03859-7.

Exome sequence analysis of rare frequency variants in Late-Onset Alzheimer Disease

Alzheimer disease (AD) is a leading cause of dementia in elderly patients who continue to live between 3 and 11 years of diagnosis. A steep rise in AD incidents is observed in the elderly population in East-Asian countries. The disease progresses through several changes, including memory loss, behavioural issues, and cognitive impairment. The etiology of AD is hard to determine because of its complex nature. The whole exome sequences of late-onset AD (LOAD) patients of Korean origin are investigated to identify rare genetic variants that may influence the complex disorder. Computational annotation was performed to assess the function of candidate variants in LOAD. The in silico pathogenicity prediction tools such as SIFT, Polyphen-2, Mutation Taster, CADD, LRT, PROVEAN, DANN, VEST3, fathmm-MKL, GERP +  + , SiPhy, phastCons, and phyloP identified around 17 genes harbouring deleterious variants. The variants in the ALDH3A2 and RAD54B genes were pathogenic, while in 15 other genes were predicted to be variants of unknown significance. These variants can be potential risk candidates contributing to AD. In silico computational techniques such as molecular docking, molecular dynamic simulation and steered molecular dynamics were carried out to understand the structural insights of RAD54B with ATP. The simulation of mutant (T459N) RAD54B with ATP revealed reduced binding strength of ATP at its binding site. In addition, lower binding free energy was observed when compared to the wild-type RAD54B. Our study shows that the identified uncommon variants are linked to AD and could be probable predisposing genetic factors of LOAD.

Computational analysis of missense variant CYP4F2*3 (V433M) in association with human CYP4F2 dysfunction: a functional and structural impact

BACKGROUND

Cytochrome P450 4F2 (CYP4F2) enzyme is a member of the CYP4 family responsible for the metabolism of fatty acids, therapeutic drugs, and signaling molecules such as arachidonic acid, tocopherols, and vitamin K. Several reports have demonstrated that the missense variant CYP4F2*3 (V433M) causes decreased activity of CYP4F2 and inter-individual variations in warfarin dose in different ethnic groups. However, the molecular pathogenicity mechanism of missense V433M in CYP4F2 at the atomic level has not yet been completely elucidated.

METHODS AND RESULTS

In the current study, we evaluated the effect of the V433M substitution on CYP4F2 using 14 different bioinformatics tools. Further molecular dynamics (MD) simulations were performed to assess the impact of the V433M mutation on the CYP4F2 protein structure, stability, and dynamics. In addition, molecular docking was used to illustrate the effect of V433M on its interaction with vitamin K1. Based on our results, the CYP4F2*3 variant was a damaging amino acid substitution with a destabilizing nature. The simulation results showed that missense V433M affects the dynamics and stability of CYP4F2 by reducing its compactness and stability, which means that it tends to change the overall structural conformation and flexibility of CYP4F2. The docking results showed that the CYP4F2*3 variant decreased the binding affinity between vitamin K1 and CYP4F2, which reduced the activity of CYP4F2*3 compared to native CYP4F2.

CONCLUSIONS

This study determined the molecular pathogenicity mechanism of the CYP4F2*3 variant on the human CYP4F2 protein and provided new information for understanding the structure-function relationship of CYP4F2 and other CYP4 enzymes. These findings will aid in the development of effective drugs and treatment options.

In silico exploration and molecular dynamics of deleterious SNPs on the human TERF1 protein triggering male infertility

By limiting chromosome erosion and end-to-end fusions, telomere integrity is critical for chromosome stability and cell survival. During mitotic cycles or due to environmental stresses, telomeres become progressively shorter and dysfunctional, thus triggering cellular senescence, genomic instability and cell death. To avoid such consequences, the telomerase action, as well as the Shelterin and CST complexes, assure the telomere's protection. Telomeric repeat binding factor 1 (TERF1), which is one of the primary components of the Shelterin complex, binds directly to the telomere and controls its length and function by regulating the telomerase activity. Several reports about TERF1 gene variations have been associated with different diseases, and some of them have linked these variations to male infertility. Hence, this paper can be advantageous to investigate the association between the missense variants of the TERF1 gene and the susceptibility to male infertility. The stepwise prediction of SNPs pathogenicity followed in this study was based on stability and conservation analysis, post-translational modification, secondary structure, functional interaction prediction, binding energy evaluation and finally molecular dynamic simulation. Prediction matching among the tools revealed that out of 18 SNPs, only four (rs1486407144, rs1259659354, rs1257022048 and rs1320180267) were predicted as the most damaging and highly deleterious SNPs affecting the TERF1 protein and its molecular dynamics when interacting with the TERB1 protein by influencing the function, structural stability, flexibility and compaction of the overall complex. Interestingly, these polymorphisms should be considered during genetic screening so they can be used effectively as genetic biomarkers for male infertility diagnosis.Communicated by Ramaswamy H. Sarma.

High risk genetic variants of human insulin receptor substrate 1(IRS1) infer structural instability and functional interference

Insulin receptor substrate 1(IRS1) is a signaling adapter protein encoded by the IRS1 gene. This protein delivers signals from insulin and insulin-like growth factor-1(IGF-1) receptors to the phosphatidylinositol 3-kinases (P13K)/protein kinase B (Akt) and Extracellular signal-regulated kinases (Erk) - Mitogen-activated protein (MAP) kinase pathways, which regulate particular cellular processes. Mutations in this gene have been linked to type 2 diabetes mellitus, a heightened risk of insulin resistance, and an increased likelihood of developing a number of different malignancies. The structure and function of IRS1 could be severely compromised as a result of single nucleotide polymorphism (SNP) type genetic variants. In this study, we focused on identification of the most harmful non-synonymous SNPs (nsSNPs) of the IRS1 gene as well as prediction of their structural and functional consequences. Six different algorithms made the initial prediction that 59 of the 1142 IRS1 nsSNPs would have a negative impact on the protein structure. In-depth evaluations detected 26 nsSNPs located inside the functional domains of IRS1. Following that, 16 nsSNPs were identified as more harmful based on conservation profile, hydrophobic interaction, surface accessibility, homology modelling, and inter-atomic interactions. Following an in-depth analysis of protein stability, M249T (rs373826433), I223T (rs1939785175) and V204G (rs1574667052) were identified as three most deleterious SNPs and were subjected to molecular dynamics simulation for further insights. These findings will help us understand the implications for disease susceptibility, cancer progression, and the efficacy of therapeutic development against IRS1 gene mutants.Communicated by Ramaswamy H. Sarma.

Structural characterization and conformational dynamics of alpha-1 antitrypsin pathogenic variants causing alpha-1-antitrypsin deficiency

Background: Alpha-1 antitrypsin deficiency (A1ATD) is a progressive lung disease caused by inherited pathogenic variants in the SERPINA1 gene. However, their actual role in maintenance of structural and functional characteristics of the corresponding α-1 anti-trypsin (A1AT) protein is not well characterized. Methods: The A1ATD causative SERPINA1 missense variants were initially collected from variant databases, and they were filtered based on their pathogenicity potential. Then, the tertiary protein models were constructed and the impact of individual variants on secondary structure, stability, protein-protein interactions, and molecular dynamic (MD) features of the A1AT protein was studied using diverse computational methods. Results: We identified that A1ATD linked SERPINA1 missense variants like F76S, S77F, L278P, E288V, G216C, and H358R are highly deleterious as per the consensual prediction scores of SIFT, PolyPhen, FATHMM, M-CAP and REVEL computational methods. All these variants were predicted to alter free energy dynamics and destabilize the A1AT protein. These variants were seen to cause minor structural drifts at residue level (RMSD = <2Å) of the protein. Interestingly, S77F and L278P variants subtly alter the size of secondary structural elements like beta pleated sheets and loops. The residue level fluctuations at 100 ns simulation confirm the highly damaging structural consequences of all the six missense variants on the conformation dynamics of the A1AT protein. Moreover, these variants were also predicted to cause functional deformities by negatively impacting the binding energy of A1AT protein with NE ligand molecule. Conclusion: This study adds a new computational biology dimension to interpret the genotype-protein phenotype relationship between SERPINA1 pathogenic variants with its structural plasticity and functional behavior with NE ligand molecule contributing to the Alpha-1-antitrypsin deficiency. Our results support that A1ATD complications correlates with the conformational flexibility and its propensity of A1AT protein polymerization when misfolded.

Molecular Pathways Involved in LRRK2-Linked Parkinson’s Disease: A Systematic Review

Parkinson’s disease is one of the most common neurodegenerative diseases affecting the ageing population, with a prevalence that has doubled over the last 30 years. As the mechanism of the disease is not fully elucidated, the current treatments are unable to effectively prevent neurodegeneration. Studies have found that mutations in Leucine-rich-repeat-kinase 2 (LRRK2) are the most common cause of familial Parkinson’s disease (PD). Moreover, aberrant (higher) LRRK2 kinase activity has an influence in idiopathic PD as well. Hence, the aim of this review is to categorize and synthesize current information related to LRRK2-linked PD and present the factors associated with LRRK2 that can be targeted therapeutically. A systematic review was conducted using the databases PubMed, Medline, SCOPUS, SAGE, and Cochrane (January 2016 to July 2021). Search terms included “Parkinson’s disease”, “mechanism”, “LRRK2”, and synonyms in various combinations. The search yielded a total of 988 abstracts for initial review, 80 of which met the inclusion criteria. Here, we emphasize molecular mechanisms revealed in recent in vivo and in vitro studies. By consolidating the recent updates in the field of LRRK2-linked PD, researchers can further evaluate targets for therapeutic application.

Genetic variations in GBA1 and LRRK2 genes: Biochemical and clinical consequences in Parkinson disease

Variants in the GBA1 and LRRK2 genes are the most common genetic risk factors associated with Parkinson disease (PD). Both genes are associated with lysosomal and autophagic pathways, with the GBA1 gene encoding for the lysosomal enzyme, glucocerebrosidase (GCase) and the LRRK2 gene encoding for the leucine-rich repeat kinase 2 enzyme. GBA1-associated PD is characterized by earlier age at onset and more severe non-motor symptoms compared to sporadic PD. Mutations in the GBA1 gene can be stratified into severe, mild and risk variants depending on the clinical presentation of disease. Both a loss- and gain- of function hypothesis has been proposed for GBA1 variants and the functional consequences associated with each variant is often linked to mutation severity. On the other hand, LRRK2-associated PD is similar to sporadic PD, but with a more benign disease course. Mutations in the LRRK2 gene occur in several structural domains and affect phosphorylation of GTPases. Biochemical studies suggest a possible convergence of GBA1 and LRRK2 pathways, with double mutant carriers showing a milder phenotype compared to GBA1-associated PD. This review compares GBA1 and LRRK2-associated PD, and highlights possible genotype-phenotype associations for GBA1 and LRRK2 separately, based on biochemical consequences of single variants.

In silico assessment of DNA damage response gene variants associated with head and neck cancer

Head and neck cancer (HNC), the sixth most common cancer globally, stands first in India, especially Northeast India, where tobacco usage is predominant, which introduces various carcinogens leading to malignancies by accumulating DNA damages. Consequently, the present work aimed to predict the impact of significant germline variants in DNA repair and Tumour Suppressor genes on HNC development. WES in Ion Proton^TM platform on 'discovery set' (n = 15), followed by recurrence assessment of the observed variants on 'confirmation set' (n = 40) using Sanger Sequencing was performed on the HNC-prevalent NE Indian populations. Initially, 53 variants were identified, of which seven HNC-linked DNA damage response gene variants were frequent in the studied populations. Different tools ascertained the biological consequences of these variants, of which the non-coding variants viz. EXO1_rs4150018, RAD52_rs6413436, CHD5_rs2746066, HACE1_rs6918700 showed risk, while FLT3_rs2491227 and BMPR1A_rs7074064 conferred protection against HNC by affecting transcriptional regulation and splicing mechanism. Molecular Dynamics Simulation of the full-length p53 model predicted that the observed coding TP53_rs1042522 variant conferred HNC-risk by altering the structural dynamics of the protein, which displayed difficulty in the transition between active and inactive conformations due to high-energy barrier. Subsequent pathway and gene ontology analysis revealed that EXO1, RAD52 and TP53 variants affected the Double-Strand Break Repair pathway, whereas CHD5 and HACE1 variants inactivated DNA repair cascade, facilitating uncontrolled cell proliferation, impaired apoptosis and malignant transformation. Conversely, FLT3 and BMPR1A variants protected against HNC by controlling tumorigenesis, which requires experimental validation. These findings may serve as prognostic markers for developing preventive measures against HNC.

Glucocerebrosidase 1 and leucine-rich repeat kinase 2 in Parkinson disease and interplay between the two genes

The glucocerebrosidase 1 gene (GBA1), bi-allelic variants of which cause Gaucher disease (GD), encodes the lysosomal enzyme glucocerebrosidase (GCase) and is a risk factor for Parkinson Disease (PD). GBA1 variants are linked to a reduction in GCase activity in the brain. Variants in Leucine-Rich Repeat Kinase 2 (LRRK2), such as the gain-of-kinase-function variant G2019S, cause the most common familial form of PD. In patients without GBA1 and LRRK2 mutations, GCase and LRRK2 activity are also altered, suggesting that these two genes are implicated in all forms of PD and that they may play a broader role in PD pathogenesis. In this review, we review the proposed roles of GBA1 and LRRK2 in PD, focussing on the endolysosomal pathway. In particular, we highlight the discovery of Ras-related in brain (Rab) guanosine triphosphatases (GTPases) as LRRK2 kinase substrates and explore the links between increased LRRK2 activity and Rab protein function, lysosomal dysfunction, alpha-synuclein accumulation and GCase activity. We also discuss the discovery of RAB10 as a potential mediator of LRRK2 and GBA1 interaction in PD. Finally, we discuss the therapeutic implications of these findings, including current approaches and future perspectives related to novel drugs targeting LRRK2 and GBA1.

Molecular Dockings and Molecular Dynamics Simulations Reveal the Potency of Different Inhibitors against Xanthine Oxidase

Xanthine oxidase (XO), which can catalyze the formation of xanthine or hypoxanthine to uric acid, is the most important target of gout. To explore the conformational changes for inhibitor binding, molecular dockings and molecular dynamics simulations were performed. Docking results indicated that three inhibitors had similar pose binding to XO. Molecular dynamics simulations showed that the binding of three inhibitors influenced the secondary structure changes in XO. After binding to the inhibitor, the peptide Phe798-Leu814 formed different degrees of unhelix, while for the peptide Glu1065-Ser1075, only a partial helix region was formed when allopurinol was bound. Through the protein structure analysis in the simulation process, we found that the distance between the active residues Arg880 and Thr1010 was reduced and the distance between Glu802 and Thr1010 was increased after the addition of inhibitors. The above simulation results showed the similarities and differences of the interaction between the three inhibitors binding to the protein. MM-PBSA calculations suggested that, among three inhibitors, allopurinol had the best binding effect with XO followed by daidzin and puerarin. This finding was consistent with previous experimental data. Our results can provide some useful clues for further gout treatment research.

Prediction of Functional Consequences of Missense Mutations in ANO4 Gene

The anoctamin (TMEM16) family of transmembrane protein consists of ten members in vertebrates, which act as Ca²⁺-dependent ion channels and/or Ca²⁺-dependent scramblases. ANO4 which is primarily expressed in the CNS and certain endocrine glands, has been associated with various neuronal disorders. Therefore, we focused our study on prioritizing missense mutations that are assumed to alter the structure and stability of ANO4 protein. We employed a wide array of evolution and structure based in silico prediction methods to identify potentially deleterious missense mutations in the ANO4 gene. Identified pathogenic mutations were then mapped to the modeled human ANO4 structure and the effects of missense mutations were studied on the atomic level using molecular dynamics simulations. Our data show that the G80A and A500T mutations significantly alter the stability of the mutant proteins, thus providing new perspective on the role of missense mutations in ANO4 gene. Results obtained in this study may help to identify disease associated mutations which affect ANO4 protein structure and function and might facilitate future functional characterization of ANO4.

Elucidation of Structural Determinants Delineates the Residues Playing Key Roles in Differential Dynamics and Selective Inhibition of Sirt1-3

Sirt1-3 are the most studied sirtuins, playing a key role in caloric-dependent epigenetic modifications. Since they are localized in distinct cellular compartments and act differently under various pathological conditions, selective inhibition would be a promising strategy to understand their biological function and to discover effective therapeutics. Here, sirtuin's inhibitor Ex527* is used as a probe to speculate the possible root cause of selective inhibition and differential structural dynamics of Sirt1-3. Comparative energetics and mutational studies revealed the criticality of residues I279 and I316 for the Sirt1 selectivity toward Ex527*. Furthermore, essential dynamics and residue network analysis revealed that the side-chain reorientation in residue F190 due to nonconserved residue Y191 played a major role in the formation of an extended selectivity pocket in Sirt2. These changes at the dynamical and residual level, which impact the internal wiring significantly, might help in rationally designing selective inhibitors against Sirt1-3.

How Parkinson's disease-related mutations disrupt the dimerization of WD40 domain in LRRK2: a comparative molecular dynamics simulation study

The multidomain kinase enzyme leucine-rich-repeat kinase 2 (LRRK2), activated through a homodimerization manner, has been identified as an important pathogenic factor in Parkinson's disease (PD), the second most common neurodegenerative disease wordwide. The Trp-Asp-40 (WD40) domain, located in the C-terminal LRRK2, harbours one of the most frequent PD-related variants, G2385R. However, the detailed dynamics of WD40 during LRRK2 dimerization and the underlying mechanism through which the pathogenic mutations disrupt the formation of the WD40 dimer have remained elusive. Here, microsecond-scale molecular dynamics simulations were employed to provide a mechanistic view underlying the WD40 dimerization and unveil the structural basis by which the interface-based mutations G2385R, H2391D and R2394E compromise the corresponding process. The simulation results identified important residues, D2351, R2394, E2395, R2413, and R2443, involved in establishing the complex binding network along the dimerization interface, which was significantly weakened in the presence of interfacial mutations. A "sag-bulge" model was proposed to explain the unfavorable dimer formation in the mutant systems. In addition, mutations altered the community configuration in the wild-type system in which inter-monomeric interplay is prominent, leading to the destabilization of the WD40 dimer under mutation.

A series of molecular modeling techniques to reveal selective mechanisms of inhibitors to β-Site amyloid precursor protein cleaving enzyme 1 (BACE1) and β-site amyloid precursor protein cleaving enzyme 2 (BACE2)

Inhibition of β-Site amyloid precursor protein cleaving enzyme 1 (BACE1) has been shown to be an effective treatment for Alzheimer's disease. A wealth of research has focused on finding highly selective small-molecule inhibitors targeting the BACE1 over its close homologue BACE2 to avoid potential side effects. However, given the highly structural similarities of BACE1 and BACE2, designing highly selective BACE1 inhibitors remains a huge challenge. Recently, it has been reported that a potential BACE1 inhibitor named C28 (∼52-fold selectivity) exhibited greater selectivity to BACE1 over BACE2 than the previously reported inhibitors AZD3293 and AZD3839 (∼1.5-fold and 14-fold selectivity). However, few computational studies have been performed to reveal its underlying mechanisms. In this study, a series of molecular modeling techniques were performed to reveal the selective mechanisms. Classical molecular dynamics (cMD) simulations indicated that the major variations appeared to be controlled by overall protein dynamics. Free energy calculations further suggested that the binding affinities of AZD3293 to BACE1 and BACE2 are similar, but the binding affinity of AZD3839 and C28 to BACE1 is much higher than to BACE2, and that the major variations are electrostatic interactions. The protein dynamics and energy differences were further observed in accelerated molecular dynamics (aMD) simulations. In addition, the umbrella sampling simulations revealed the inhibitors' different patterns of dissociation from the binding pockets of BACE1 and BACE2, and that different energy barriers were responsible for the selectivity. The physical principles revealed by this study may facilitate the rational design of more potent BACE1 selective inhibitors. Communicated by Ramaswamy H. Sarma.

Mechanistic insights into the deleterious roles of Nasu-Hakola disease associated TREM2 variants

Recently, the critical roles played by genetic variants of TREM2 (Triggering Receptor Expressed on Myeloid cells 2) in Alzheimer's disease have been aggressively highlighted. However, few studies have focused on the deleterious roles of Nasu-Hakola disease (NHD) associated TREM2 variants. In order to get insights into the contributions made by these variants to neurodegeneration, we investigated the influences of four NHD associated TREM2 mutations (Y38C, W50C, T66M, and V126G) on loss-of-function, and followed this with in silico prediction and conventional molecular dynamics simulation. NHD mutations were predicted to be highly deleterious by eight different in silico bioinformatics tools and found to induce conformational changes by molecular dynamics simulation. As compared with the wild-type, the four variants produced substantial differences in the collective motions of loop regions, which not only promoted structural remodeling in the CDR2 (complementarity-determining region 2) loop but also in the CDR1 loop, by changing inter- and intra-loop hydrogen bonding networks. In addition, structural studies in a free energy landscape analysis showed that Y38, T66, and V126 are crucial for maintaining the structural features of CDR1 and CDR2 loops, and that mutations in these positions produced steric clashes and loss of ligand binding. These results showed the presence of mutations in the TREM2 ectodomain induced flexibility and caused structural alterations. Dynamical scenarios, as provided by the present study, may be critical to our understanding of the roles of these TREM2 mutations in neurodegenerative diseases.

Structural and Dynamic Characterizations Highlight the Deleterious Role of SULT1A1 R213H Polymorphism in Substrate Binding

Sulfotransferase 1A1 (SULT1A1) is responsible for catalyzing various types of endogenous and exogenous compounds. Accumulating data indicates that the polymorphism rs9282861 (R213H) is responsible for inefficient enzymatic activity and associated with cancer progression. To characterize the detailed functional consequences of this mutation behind the loss-of-function of SULT1A1, the present study deployed molecular dynamics simulation to get insights into changes in the conformation and binding energy. The dynamics scenario of SULT1A1 in both wild and mutated types as well as with and without ligand showed that R213H induced local conformational changes, especially in the substrate-binding loop rather than impairing overall stability of the protein structure. The higher conformational changes were observed in the loop3 (residues, 235-263), turning loop conformation to A-helix and B-bridge, which ultimately disrupted the plasticity of the active site. This alteration reduced the binding site volume and hydrophobicity to decrease the binding affinity of the enzyme to substrates, which was highlighted by the MM-PBSA binding energy analysis. These findings highlight the key insights of structural consequences caused by R213H mutation, which would enrich the understanding regarding the role of SULT1A1 mutation in cancer development and also xenobiotics management to individuals in the different treatment stages.

In silico analysis of nonsynonymous single-nucleotide polymorphisms (nsSNPs) of the SMPX gene

Mutations in the SMPX gene can disrupt the regular activity of the SMPX protein, which is involved in the hearing process. Recent reports showing a link between nonsynonymous single-nucleotide polymorphisms (nsSNPs) in SMPX and hearing loss, thus classifying deleterious SNPs in SMPX will be an uphill task before designing a more extensive population study. In this study, damaging nsSNPs of SMPX from the dbSNP database were identified by using 13 bioinformatics tools. Initially, the impact of nsSNPs in the SMPX gene were evaluated through different in silico predictors; and the deleterious convergent changes were analyzed by energy-minimization-guided residual network analysis. In addition, the pathogenic effects of mutations in SMPX-mediated protein-protein interactions were also characterized by structural modeling and binding energy calculations. A total of four mutations (N19D, A29T, K54N, and S71L) were found to be highly deleterious by all the tools, which are located at highly conserved regions. Furthermore, all four mutants showed structural alterations, and the communities of amino acids for mutant proteins were readily changed, compared to the wild-type. Among them, A29T (rs772775896) was revealed as the most damaging nsSNP, which caused significant structural deviation of the SMPX protein, as a result reducing the binding affinity to other functional partners. These findings reflect the computational insights into the deleterious role of nsSNPs in SMPX, which might be helpful for subjecting wet-lab confirmatory analysis.