Influence of V54M mutation in giant muscle protein titin: a computational screening and molecular dynamics approach

Walking with giants: The challenges of variant impact assessment in the giant sarcomeric protein titin

Titin, the so-called "third filament" of the sarcomere, represents a difficult challenge for the determination of damaging genetic variants. A single titin molecule extends across half the length of a sarcomere in striated muscle, fulfilling a variety of vital structural and signaling roles, and has been linked to an equally varied range of myopathies, resulting in a significant burden on individuals and healthcare systems alike. While the consequences of truncating variants of titin are well-documented, the ramifications of the missense variants prevalent in the general population are less so. We here present a compendium of titin missense variants-those that result in a single amino-acid substitution in coding regions-reported to be pathogenic and discuss these in light of the nature of titin and the variant position within the sarcomere and their domain, the structural, pathological, and biophysical characteristics that define them, and the methods used for characterization. Finally, we discuss the current knowledge and integration of the multiple fields that have contributed to our understanding of titin-related pathology and offer suggestions as to how these concurrent methodologies may aid the further development in our understanding of titin and hopefully extend to other, less well-studied giant proteins. This article is categorized under: Cardiovascular Diseases > Genetics/Genomics/Epigenetics Congenital Diseases > Genetics/Genomics/Epigenetics Congenital Diseases > Molecular and Cellular Physiology.

A computational study of structural analysis of Class I human glucose-6-phosphate dehydrogenase (G6PD) variants: Elaborating the correlation to chronic non-spherocytic hemolytic anemia (CNSHA)

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is the most common human enzyme defect that affects more than 500 million people worldwide. Individuals affected with G6PD deficiency may occasionally suffer mild-to-severe chronic hemolytic anemia. Chronic non-spherocytic hemolytic anemia (CNSHA) is a potential result of the Class I G6PD variants. This comparative computational study attempted to correct the defect in variants structure by docking the AG1 molecule to selected Class I G6PD variants [G6PD^Nashville (Arg393His), G6PD^Alhambra (Val394Leu), and G6PD^Durham (Lys238Arg)] at the dimer interface and structural NADP⁺ binding site. It was followed by an analysis of the enzyme conformations before and after binding to the AG1 molecule using the molecular dynamics simulation (MDS) approach, while the severity of CNSHA was determined via root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), hydrogen bonds, salt bridges, radius of gyration (Rg), solvent accessible surface area analysis (SASA), and principal component analysis (PCA). The results revealed that G6PD^Nashville (Arg393His) and G6PD^Durham (Lys238Arg) had lost the direct contact with structural NADP⁺ and salt bridges at Glu419 - Arg427 and Glu206 - Lys407 were disrupted in all selected variants. Furthermore, the AG1 molecule re-stabilized the enzyme structure by restoring the missing interactions. Bioinformatics approaches were also used to conduct a detailed structural analysis of the G6PD enzyme at a molecular level to understand the implications of these variants toward enzyme function. Our findings suggest that despite the lack of treatment for G6PDD to date, AG1 remains a novel molecule that promotes activation in a variety of G6PD variants.

The pathogenic effect of SNPs on structure and function of human TLR4 using a computational approach

The human toll-like receptor (hTLR) 4 single nucleotide polymorphisms (SNPs) are interconnected with cancer, multiple genetic disorders and other immune-related diseases. The detrimental effect of SNPs in hTLR4 with respect to structure and function has not been explored in depth. The present study concatenates the biological consequences of the SNPs along with structural modifications predicted at the hTLR4 gene. A total of 7910 SNPs of hTLR4 were screened, and 21 damage-causing SNPs were identified. Out of 21, seven are present in the extracellular region, of which three were detected as deleterious and the fourth one as moderate. These three mutations are located in a highly conserved region and influence conformational change. The change leads to the widening of the Leucine-rich repeat (LRR) arc to a maximum of 16.9 Å and a minimum of 8.7 Å. Expansion/shortening of LRR arc, never discussed before, would cause loss of myeloid differentiation factor 2 (MD-2) interactions in the interior and diminish lipopolysaccharide (LPS) responses. Similarly, in all mutant structures, the binding region for HMGB1 and LPS is deflating or in an unsupportive conformation. Thus, SNPs affect the regular signaling cascade and might result in human sepsis, genetic disorders, cancer and other immunological related diseases.Communicated by Ramaswamy H. Sarma.

Molecular simulation unravels the amyloidogenic misfolding of nascent ApoA1 protein, driven by deleterious point mutations occurring in between 170-178 hotspot region

Protein ApoA1 is extensively studied for its role in lipid metabolism. Its seedy dark side of amyloid formulation remains relatively understudied yet. Due to genetic mutations, the protein pathologically misshapes into its amyloid form that gets accumulated in various organs, including the heart. To contrive effective therapeutics against this debilitating congenital disorder, it is imperative to comprehend the structural ramifications induced by mutations in APoA1's dynamic conformation. Till now, several point mutations have been implicated in ApoA1's amyloidosis, although only a handful has been examined considerably. Especially, the single nucleotide polymorphisms (SNPs) that occur in-between 170-178 mutation hotspot site of APoA1 needs to be investigated, since most of them are culpable of amyloid deposition in the heart. To that effect, in the present study, we have computationally quantified and studied the ApoA1's biomolecular modifications fostered by SNPs in the 170-178 mutation hotspot. Findings from discrete molecular dynamics simulation studies indicate that the SNPs have noticeably steered the ApoA1's behaviour from its native structural dynamics. Analysis of protein's secondary structural changes exhibits a considerable change upon mutations. Further, subjecting the protein structures to simulated thermal denaturation shows increased resistance to denaturation among mutants when compared to native. Further, normal mode analysis of protein's dynamic motion also shows discrepancy in its dynamic structural change upon SNP. These structural digressions induced by SNPs can very well be the biomolecular incendiary that drives ApoA1 into its amyloidogenesis. And, understanding these structural modifications initiates a better understanding of SNP's amyloidogenic pathology on APoA1.Communicated by Ramaswamy H. Sarma.

Genotyping and In Silico Analysis of Delmarva (DMV/1639) Infectious Bronchitis Virus (IBV) Spike 1 (S1) Glycoprotein

Genetic diversity and evolution of infectious bronchitis virus (IBV) are mainly impacted by mutations in the spike 1 (S1) gene. This study focused on whole genome sequencing of an IBV isolate (IBV/Ck/Can/2558004), which represents strains highly prevalent in Canadian commercial poultry, especially concerning features related to its S1 gene and protein sequences. Based on the phylogeny of the S1 gene, IBV/Ck/Can/2558004 belongs to the GI-17 lineage. According to S1 gene and protein pairwise alignment, IBV/Ck/Can/2558004 had 99.44–99.63% and 98.88–99.25% nucleotide (nt) and deduced amino acid (aa) identities, respectively, with five Canadian Delmarva (DMV/1639) IBVs isolated in 2019, and it also shared 96.63–97.69% and 94.78–97.20% nt and aa similarities with US DMV/1639 IBVs isolated in 2011 and 2019, respectively. Further homology analysis of aa sequences showed the existence of some aa substitutions in the hypervariable regions (HVRs) of the S1 protein of IBV/Ck/Can/2558004 compared to US DMV/1639 isolates; most of these variant aa residues have been subjected to positive selection pressure. Predictive analysis of potential N-glycosylation and phosphorylation motifs showed either loss or acquisition in the S1 glycoprotein of IBV/Ck/Can/2558004 compared to S1 of US DMV/1639 IBV. Furthermore, bioinformatic analysis showed some of the aa changes within the S1 protein of IBV/Ck/Can/2558004 have been predicted to impact the function and structure of the S1 protein, potentially leading to a lower binding affinity of the S1 protein to its relevant ligand (sialic acid). In conclusion, these findings revealed that the DMV/1639 IBV isolates are under continuous evolution among Canadian poultry.

Computational structural assessment of BReast CAncer type 1 susceptibility protein (BRCA1) and BRCA1-Associated Ring Domain protein 1 (BARD1) mutations on the protein-protein interface

Breast cancer type 1 susceptibility protein (BRCA1) is closely related to the BRCA2 (breast cancer type 2 susceptibility protein) and BARD1 (BRCA1-associated RING domain-1) proteins. The homodimers were formed through their RING fingers; however they form more compact heterodimers preferentially, influencing BRCA1 residues 1-109 and BARD1 residues 26-119. We implemented an integrative computational pipeline to screen all the mutations in BRCA1 and identify the most significant mutations influencing the Protein-Protein Interactions (PPI) in the BRCA1-BARD1 protein complex. The amino acids involved in the PPI regions were identified from the PDBsum database with the PDB ID: 1JM7. We screened 2118 missense mutations in BRCA1 and none in BARD1 for pathogenicity and stability and analyzed the amino acid sequences for conserved residues. We identified the most significant mutations from these screenings as V11G, M18K, L22S, and T97R positioned in the PPI regions of the BRCA1-BARD1 protein complex. We further performed protein-protein docking using the ZDOCK server. The native protein-protein complex showed the highest binding score of 2118.613, and the V11G mutant protein complex showed the least binding score of 1992.949. The other three mutation protein complexes had binding scores between the native and V11G protein complexes. Finally, a molecular dynamics simulation study using GROMACS was performed to comprehend changes in the BRCA1-BARD1 complex's binding pattern due to the mutation. From the analysis, we observed the highest deviation with lowest compactness and a decrease in the intramolecular h-bonds in the BRCA1-BARD1 protein complex with the V11G mutation compared to the native complex or the complexes with other mutations.

Investigating mutations at the hotspot position of the ERBB2 and screening for the novel lead compound to treat breast cancer - a computational approach

Membrane proteins are the most common types of cancer that are active in the prognosis. Membrane proteins are a distinguishing characteristic of a cancer cell. In tumor cell therapy, the overexpressed membrane proteins are becoming ever more relevant. The 3-kinase (PI3K)/AKT phosphatidylinositol pathway is downstream triggered by different extracellular signals, and this signaling pathway activation impacts a variety of proliferation of the cellular processes like cell growth and surviving. Frequent PI3K/AKT dysregulation in human cancer has rendered proteins of this pathway desirable for diagnostic markers. Members of the ERBB family-like ERBB2 and ERBB3 activate intracellular signaling pathways such as PI3K/AKT. The mutations in these proteins dysfunctions the proteins in the downstream. Considering this importance, we have developed a computational pipeline to identify the mutation position with a highest number of mutations and to screen them for pathogenicity, stability, conservation, and structural changes using PredictSNP, iStable, ConSurf, and GROMACS simulation software respectively. Further, a virtual screening approach was initiated to find the most similar non-toxic lead compound, which could be an alternative to the currently used lapatinib. To conclude, protein-ligand dynamics were undertaken to study the actions of native and mutants with the lapatinib and the lead compound. From the overall analysis, we identified position 755 with leucine in the native condition is prone to frequent mutations. The leucine at 755th position is more prone to mutate as serine and tryptophan. Further from the computational analysis, we identified that the mutation L755S is more significant than the L755W mutation. We have witnessed CID140590176 be a potential lead compound with no toxicity. The behavior of the lead compound has shown more compactness with an increased number of intermolecular hydrogen bonds in the ERBB2 with L755S. This lead compound can be further taken for experimental validations, and we believe that this lead compound could be a potent ERBB2 inhibitor.

Molecular modeling and dynamic simulation of chicken Mx protein with the S631N polymorphism

Myxovirus resistance (Mx) proteins are antiviral GTPases induced by type I interferons (IFNs). In chickens, a single Mx protein variant, S631N, has been suggested to possess antiviral activity. However, the impact of this variant on chicken Mx (chMx) protein structure and conformation has not been investigated. Hence, in this study, we applied computational methods such as molecular modeling, molecular dynamic simulation, inter domain motion and residue networks to examine the structure and dynamic behavior of wild-type and mutant chMx. At first, we built 3-dimensional structural models for both wild-type and mutant chMx proteins, which revealed that the structural organization of chMx was similar to that of human Mx proteins. Subsequently, molecular dynamics simulations revealed that angle variation around the hinge1 region led to the different stalk domain conformations between the wild-type and mutant chMx proteins. Domain motion analysis further suggested that the conformational differences in the loop region surrounded by the mutant residue may lead to an inclined stalk domain conformation in the mutant compared to the wild-type protein. In addition, we performed betweenness centrality analysis from residue interaction networks, to identify the crucial residues for intramolecular signal flow in chMx. The results of this study provided information on the differences in structure and dynamics between wild-type and mutant chMx, which may aid in understanding the structural features of the S631N mutant, that may be associated with chMx protein antiviral activity.Communicated by Ramaswamy H. Sarma.

The pathogenicity, structural and functional exploration of human HMGB1 single nucleotide polymorphisms using in silico study

The human HMGB1 gene mutations have a major impact on several immune-related diseases and cancer. The detrimental effect of non-synonymous mutations of HMGB1 has not been investigated yet, hence the present study aims to examine single nucleotide polymorphisms and their implications on the structure-function of human HMGB1. The multifaceted HMGB1 protein acts as pleiotropic cytokine and regulates essential genes for coordinated cellular functions. The mutational effect on HMGB1 was analyzed by sequence-based homology methods, supervised learning methods, and structure-based methods. The study identified 58 non-synonymous mutations in human HMGB1, out of which only 2 mutations; R10T (rs61742222) and F103C (rs61733675) were classified as the SNPs with highest deleterious and disease-causing mutants. The effect of these mutations in structure of HMGB1 was scrutinized and the R10T mutant found to have a distinct structural behaviour in the B-box domain. In addition, R10T mutant predicted that it affects the MoRF function of HMGB1 and it could disrupt the DNA binding or/and protein partner interaction activity by HMGB1. F103C mutation takes place at the TLR binding and cytokine inducing region of HMGB1, hence it could affect the protein binding activity which involves in many cellular signaling. The study identified potent mutations R10T (a cancer-causing somatic mutation) and F103C (a novel mutation) and these mutations either directly or indirectly hinder DNA binding activity and TLR and cytokine binding of HMGB1. These findings will help in understanding the molecular basis of these promising mutations and functional role of human HMGB1 in cancer and immunological diseases.AbbreviationsAGERAdvanced glycosylation end product-specific receptorCXCLChemokine (C-X-C motif) liganddbSNPThe single nucleotide polymorphism databaseHMGB1High mobility group box 1LINCSLINear Constraint SolverMDSMolecular dynamics simulationMoRFMolecular recognition featuresNPTNumber of particle, Pressure and TemperatureNVTNumber of particle, Volume and TemperaturensSNPNon-synonymous SNPPBCPartial boundary conditionPCAPrincipal component analysisPMEPartial mesh EwaldRMSDRoot mean square deviationRMSFRoot mean square fluctuationSNPSingle nucleotide polymorphismSPCSingle-point chargeTLRToll-like receptorUTRUn-translated RegionCommunicated by Ramaswamy H. Sarma.

The importance of chain context in assessing small nucleotide variants in titin: in silico case study of the I10-I11 tandem and its arrhythmic right ventricular cardiomyopathy linked position T2580

Non-synonymous small nucleotide variations (nsSNVs) in the giant muscle protein, titin, have key roles in the development of several myopathologies. Although there is considerable motive to screen at-risk individuals for nsSNVs, to identify patients in early disease stages while therapeutic intervention is still possible, the clinical significance of most titin variations remains unclear. Therefore, there is a growing need to establish methods to classify nsSNVs in a simple, economic and rapid manner. Due to its strong correlation to arrhythmogenic right ventricular cardiomyopathy (ARVC), one particular mutation in titin-T2580I, located in the I10 immunoglobulin domain-has received considerable attention. Here, we use the I10-I11 tandem as a case study to explore the possible benefits of considering the titin chain context-i.e. domain interfaces-in the assessment of titin nsSNVs. Specifically, we investigate which exchanges mimic the conformational molecular phenotype of the T2580I mutation at the I10-I11 domain interface. Then, we computed a residue stability landscape for domains alone and in tandem to define a Domain Interface Score (DIS) which identifies several hotspot residues. Our findings suggest that the T2580 position is highly sensitive to exchange and that any variant found in this position should be considered with care. Furthermore, we conclude that the consideration of the higher order structure of the titin chain is important to gain accurate insights into the vulnerability of positions in linker regions and that titin nsSNV prediction benefits from a contextual analysis. Communicated by Ramaswamy H. Sarma.

Comprehensive in silico screening and molecular dynamics studies of missense mutations in Sjogren-Larsson syndrome associated with the ALDH3A2 gene

Sjögren-Larsson syndrome (SLS) is an autoimmune disorder inherited in an autosomal recessive pattern. To date, 80 missense mutations have been identified in association with the Aldehyde Dehydrogenase 3 Family Member A2 (ALDH3A2) gene causing SLS. Disruption of the function of ALDH3A2 leads to excessive accumulation of fat in the cells, which interferes with the normal function of protective membranes or materials that are necessary for the body to function normally. We retrieved 54 missense mutations in the ALDH3A2 from the OMIM, UniProt, dbSNP, and HGMD databases that are known to cause SLS. These mutations were examined with various in silico stability tools, which predicted that the mutations p.S308N and p.R423H that are located at the protein-protein interaction domains are the most destabilizing. Furthermore, to determine the atomistic-level differences within the protein-protein interactions owing to mutations, we performed macromolecular simulation (MMS) using GROMACS to validate the motion patterns and dynamic behavior of the biological system. We found that both mutations (p.S380N and p.R423H) had significant effects on the protein-protein interaction and disrupted the dimeric interactions. The computational pipeline provided in this study helps to elucidate the potential structural and functional differences between the ALDH3A2 native and mutant homodimeric proteins, and will pave the way for drug discovery against specific targets in the SLS patients.

An extensive computational approach to analyze and characterize the functional mutations in the galactose-1-phosphate uridyl transferase (GALT) protein responsible for classical galactosemia

Type I galactosemia is a very rare autosomal recessive genetic metabolic disorder that occurs because of the mutations present in the galactose-1-phosphate uridyl transferase (GALT) gene, resulting in a deficiency of the GALT enzyme. The action of the GALT enzyme is to convert galactose-1-phosphate and uridine diphosphate glucose into glucose-1-phosphate (G1P) and uridine diphosphate-galactose, a crucial second step of the Leloir pathway. A missense mutation in the GALT enzyme leads to variable galactosemia's clinical presentations, ranging from mild to severe. Our study aimed to employ a comprehensive computational pipeline to analyze the most prevalent missense mutations (p.S135L, p.K285 N, p.Q188R, and p.N314D) responsible for galactosemia; these genes could serve as potential targets for chaperone therapy. We analyzed the four mutations through different computational analyses, including amino acid conservation, in silico pathogenicity and stability predictions, and macromolecular simulations (MMS) at 50 ns The stability and pathogenicity predictors showed that the p.Q188R and p.S135L mutants are the most pathogenic and destabilizing. In agreement with these results, MMS analysis demonstrated that the p.Q188R and p.S135L mutants possess higher deviation patterns, reduced compactness, and intramolecular H-bonds of the protein. This could be due to the physicochemical modifications that occurred in the mutants p.S135L and p.Q188R compared to the native. Evolutionary conservation analysis revealed that the most prevalent mutations positions were conserved among different species except N314. The proposed research study is intended to provide a basis for the therapeutic development of drugs and future treatment of classical galactosemia and possibly other genetic diseases using chaperone therapy.

Bioinformatics classification of mutations in patients with Mucopolysaccharidosis IIIA

Mucopolysaccharidosis (MPS) IIIA, also known as Sanfilippo syndrome type A, is a severe, progressive disease that affects the central nervous system (CNS). MPS IIIA is inherited in an autosomal recessive manner and is caused by a deficiency in the lysosomal enzyme sulfamidase, which is required for the degradation of heparan sulfate. The sulfamidase is produced by the N-sulphoglucosamine sulphohydrolase (SGSH) gene. In MPS IIIA patients, the excess of lysosomal storage of heparan sulfate often leads to mental retardation, hyperactive behavior, and connective tissue impairments, which occur due to various known missense mutations in the SGSH, leading to protein dysfunction. In this study, we focused on three mutations (R74C, S66W, and R245H) based on in silico pathogenic, conservation, and stability prediction tool studies. The three mutations were further subjected to molecular dynamic simulation (MDS) analysis using GROMACS simulation software to observe the structural changes they induced, and all the mutants exhibited maximum deviation patterns compared with the native protein. Conformational changes were observed in the mutants based on various geometrical parameters, such as conformational stability, fluctuation, and compactness, followed by hydrogen bonding, physicochemical properties, principal component analysis (PCA), and salt bridge analyses, which further validated the underlying cause of the protein instability. Additionally, secondary structure and surrounding amino acid analyses further confirmed the above results indicating the loss of protein function in the mutants compared with the native protein. The present results reveal the effects of three mutations on the enzymatic activity of sulfamidase, providing a molecular explanation for the cause of the disease. Thus, this study allows for a better understanding of the effect of SGSH mutations through the use of various computational approaches in terms of both structure and functions and provides a platform for the development of therapeutic drugs and potential disease treatments.

Prioritization of SNPs in y+LAT-1 culpable of Lysinuric protein intolerance and their mutational impacts using protein-protein docking and molecular dynamics simulation studies

Lysinuric protein intolerance (LPI) is a rare, yet inimical, genetic disorder characterized by the paucity of essential dibasic amino acids in the cells. Amino acid transporter y+LAT-1 interacts with 4F2 cell-surface antigen heavy chain to transport the required dibasic amino acids. Mutation in y+LAT-1 is rumored to cause LPI. However, the underlying pathological mechanism is unknown, and, in this analysis, we investigate the impact of point mutation in y+LAT-1's interaction with 4F2 cell-surface antigen heavy chain in causing LPI. Using an efficient and extensive computational pipeline, we have isolated M50K and L334R single-nucleotide polymorphisms to be the most deleterious mutations in y+LAT-1s. Docking of mutant y+LAT-1 with 4F2 cell-surface antigen heavy chain showed decreased interaction compared with native y+LAT-1. Further, molecular dynamic simulation analysis reveals that the protein molecules increase in size, become more flexible, and alter their secondary structure upon mutation. We believe that these conformational changes because of mutation could be the reason for decreased interaction with 4F2 cell-surface antigen heavy chain causing LPI. Our analysis gives pathological insights about LPI and helps researchers to better understand the disease mechanism and develop an effective treatment strategy.

An integrative bioinformatics pipeline to demonstrate the alteration of the interaction between the ALDH2*2 allele with NAD+ and Disulfiram

Alcohol use disorder (AUD) is a multifactorial psychiatric behavior disorder. Disulfiram is the first approved drug by the Food and Drug Administration for alcohol-dependent patients, which targets the ALDH2 enzyme. Several genes are known to be involved in alcohol metabolism; mutations in any of these genes are known to be associated with AUD. The E504K mutation in the ALDH2 of the precursor protein or the E487K of the mature protein (E504K/E487K; ALDH2*2 allele) is carried by approximately 8% of the world population. In this study, we aimed to test the known inactive allele ALDH2*2, to validate the use of our extensive computational pipeline (in silico tools, molecular modeling, and molecular docking) for testing the interaction between the ALDH2*2 allele, NAD^+, and Disulfiram. In silico predictions showed that the E504K variant of ALDH2 to be pathogenic and destabilizing with the maximum number of prediction in silico tools. Consequently, we studied the effect of this mutation mainly on the interaction between NAD⁺ -E504K and Disulfiram-E504K complexes using molecular docking technique, and molecular dynamics (MD) analysis. From the molecular docking analysis with NAD⁺ , we observed that the interaction affinity of the NAD⁺ decreases with the impact of E504K variant. On the other hand, the drug Disulfiram showed similar interaction in both the native and mutant ALDH2 proteins. Further, the comprehensive MD analysis predicted that the E504K destabilizes the protein and influences the NAD⁺ and Disulfiram interactions. Our findings reveal that the interaction of NAD⁺ to the protein is disturbed by the E504K/E487K variant whereas the drug Disulfiram has a similar effect as both native ALDH2 and ALDH2 bearing E504K/E487K variant. This study provides a platform to understand the effect of E504K/E487K on the molecular interaction with NAD⁺ and Disulfiram.

Probing light chain mutation effects on thrombin via molecular dynamics simulations and machine learning

Thrombin is a key component for chemotherapeutic and antithrombotic therapy development. As the physiologic and pathologic roles of the light chain still remain vague, here, we continue previous efforts to understand the impacts of the disease-associated single deletion of LYS9 in the light chain. By combining supervised and unsupervised machine learning methodologies and more traditional structural analyses on data from 10 μs molecular dynamics simulations, we show that the conformational ensemble of the ΔK9 mutant is significantly perturbed. Our analyses consistently indicate that LYS9 deletion destabilizes both the catalytic cleft and regulatory functional regions and result in some conformational changes that occur in tens to hundreds of nanosecond scaled motions. We also reveal that the two forms of thrombin each prefer a distinct binding mode of a Na+ ion. We expand our understanding of previous experimental observations and shed light on the mechanisms of the LYS9 deletion associated bleeding disorder by providing consistent but more quantitative and detailed structural analyses than early studies in literature. With a novel application of supervised learning, i.e. the decision tree learning on the hydrogen bonding features in the wild-type and ΔK9 mutant forms of thrombin, we predict that seven pairs of critical hydrogen bonding interactions are significant for establishing distinct behaviors of wild-type thrombin and its ΔK9 mutant form. Our calculations indicate the LYS9 in the light chain has both localized and long-range allosteric effects on thrombin, supporting the opinion that light chain has an important role as an allosteric effector.

Understanding the structure-function relationship of HPRT1 missense mutations in association with Lesch-Nyhan disease and HPRT1-related gout by in silico mutational analysis

The nucleotide salvage pathway is used to recycle degraded nucleotides (purines and pyrimidines); one of the enzymes that helps to recycle purines is hypoxanthine guanine phosphoribosyl transferase 1 (HGPRT1). Therefore, defects in this enzyme lead to the accumulation of DNA and nucleotide lesions and hence replication errors and genetic disorders. Missense mutations in hypoxanthine phosphoribosyl transferase 1 (HPRT1) are associated with deficiencies such as Lesch-Nyhan disease and chronic gout, which have manifestations such as arthritis, neurodegeneration, and cognitive disorders. In the present study, we collected 88 non-synonymous single nucleotide polymorphisms (nsSNPs) from the UniProt, dbSNP, ExAC, and ClinVar databases. We used a series of sequence-based and structure-based in silico tools to prioritize and characterize the most pathogenic and stabilizing or destabilizing nsSNPs. Moreover, to obtain the structural impact of the pathogenic mutations, we mapped the mutations to the crystal structure of the HPRT protein. We further subjected these mutant proteins to a 50 ns molecular dynamics simulation (MDS). The MDS trajectory showed that all mutant proteins altered the structural conformation and dynamic behavior of the HPRT protein and corroborated its association with LND and gout. This study provides essential information regarding the use of HPRT protein mutants as potential targets for therapeutic development.

Computational modelling approaches as a potential platform to understand the molecular genetics association between Parkinson's and Gaucher diseases

Gaucher's disease (GD) is a genetic disorder in which glucocerebroside accumulates in cells and specific organs. It is broadly classified into type I, type II and type III. Patients with GD are at high risk of Parkinson's disease (PD), and the clinical and pathological presentation of GD patients with PD is almost identical to idiopathic PD. Several experimental models like cell culture, animal models, and transgenic mice models were used to understand the molecular mechanism behind GD and PD association; however, such mechanism remains unclear. In this context, based on literature reports, we identified the most common mutations K198T, E326K, T369M, N370S, V394L, D409H, L444P, and R496H, in the Glucosylceramidase (GBA) protein that are known to cause GD1, and represent a risk of developing PD. However, to date, no computational analyses have designed to elucidate the potential functional role of GD mutations with increased risk of PD. The present computational pipeline allows us to understand the structural and functional significance of these GBA mutations with PD. Based on the published data, the most common and severe mutations were E326K, N370S, and L444P, which further selected for our computational analysis. PredictSNP and iStable servers predicted L444P mutant to be the most deleterious and responsible for the protein destabilization, followed by the N370S mutation. Further, we used the structural analysis and molecular dynamics approach to compare the most frequent deleterious mutations (N370S and L444P) with the mild mutation E326K. The structural analysis demonstrated that the location of E326K and N370S in the alpha helix region of the protein whereas the mutant L444P was in the starting region of the beta sheet, which might explain the predicted pathogenicity level and destabilization effect of the L444P mutant. Finally, Molecular Dynamics (MD) at 50 ns showed the highest deviation and fluctuation pattern in the L444P mutant compared to the two mutants E326K and N370S and the native protein. This was consistent with more loss of intramolecular hydrogen bonds and less compaction of the radius of gyration in the L444P mutant. The proposed study is anticipated to serve as a potential platform to understand the mechanism of the association between GD and PD, and might facilitate the process of drug discovery against both GD and PD.

In silico site-directed mutagenesis of neutralizing mAb 4C4 and analysis of its interaction with G-H loop of VP1 to explore its therapeutic applications against FMD

Investigating the behaviour of bio-molecules through computational mutagenesis is gaining interest to facilitate the development of new therapeutic solutions for infectious diseases. The antigenetically variant genotypes of foot and mouth disease virus (FMDV) and their subsequent infections are challenging to tackle with traditional vaccination. In such scenario, neutralizing antibodies might provide an alternate solution to manage the FMDV infection. Thus, we have analysed the interaction of the mAb 4C4 with a synthetic G-H loop of FMDV-VP1 through in silico mutagenesis and molecular modelling. Initially, a set of 25,434 mutants were designed and the mutants having better energetic stability than 4C4 were clustered based on sequence identity. The best mutant representing each cluster was selected and evaluated for its binding affinity with the antigen in terms of docking scores, interaction energy and binding energy. Six mutants have confirmed better binding affinities towards the antigen than 4C4. Further, interaction of these mutants with the natural G-H loop that is bound to mAb SD6 was also evaluated. One 4C4 variant having mutations at the positions 2034(N→L), 2096(N→C), 2098(D→Y), 2532(T→K) and 2599(A→G) has revealed better binding affinities towards both the synthetic and natural G-H loops than 4C4 and SD6, respectively. A molecular dynamic simulation for 50 ns was conducted for mutant and wild-type antibody structures which supported the pre-simulation results. Therefore, these mutations on mAb 4C4 are believed to provide a better antibody-based therapeutic option for FMD. Communicated by Ramaswamy H. Sarma.

Computational insights of K1444N substitution in GAP-related domain of NF1 gene associated with neurofibromatosis type 1 disease: a molecular modeling and dynamics approach

The NF1 gene encodes for neurofibromin protein, which is ubiquitously expressed, but most highly in the central nervous system. Non-synonymous SNPs (nsSNPs) in the NF1 gene were found to be associated with Neurofibromatosis Type 1 disease, which is characterized by the growth of tumors along nerves in the skin, brain, and other parts of the body. In this study, we used several in silico predictions tools to analyze 16 nsSNPs in the RAS-GAP domain of neurofibromin, the K1444N (K1423N) mutation was predicted as the most pathogenic. The comparative molecular dynamic simulation (MDS; 50 ns) between the wild type and the K1444N (K1423N) mutant suggested a significant change in the electrostatic potential. In addition, the RMSD, RMSF, Rg, hydrogen bonds, and PCA analysis confirmed the loss of flexibility and increase in compactness of the mutant protein. Further, SASA analysis revealed exchange between hydrophobic and hydrophilic residues from the core of the RAS-GAP domain to the surface of the mutant domain, consistent with the secondary structure analysis that showed significant alteration in the mutant protein conformation. Our data concludes that the K1444N (K1423N) mutant lead to increasing the rigidity and compactness of the protein. This study provides evidence of the benefits of the computational tools in predicting the pathogenicity of genetic mutations and suggests the application of MDS and different in silico prediction tools for variant assessment and classification in genetic clinics.

Structural analysis of missense mutations in galactokinase 1 (GALK1) leading to galactosemia type-2

Galactosemia type 2 is an autosomal recessive disorder characterized by the deficiency of galactokinase (GALK) enzyme due to missense mutations in GALK1 gene, which is associated with various manifestations such as hyper galactosemia and formation of cataracts. GALK enzyme catalyzes the adenosine triphosphate (ATP)-dependent phosphorylation of α-d-galactose to galactose-1-phosphate. We searched 4 different literature databases (Google Scholar, PubMed, PubMed Central, and Science Direct) and 3 gene-variant databases (Online Mendelian Inheritance in Man, Human Gene Mutation Database, and UniProt) to collect all the reported missense mutations associated with GALK deficiency. Our search strategy yielded 32 missense mutations. We used several computational tools (pathogenicity and stability, biophysical characterization, and physiochemical analyses) to prioritize the most significant mutations for further analyses. On the basis of the pathogenicity and stability predictions, 3 mutations (P28T, A198V, and L139P) were chosen to be tested further for physicochemical characterization, molecular docking, and simulation analyses. Molecular docking analysis revealed a decrease in interaction between the protein and ATP in all the 3 mutations, and molecular dynamic simulations of 50 ns showed a loss of stability and compactness in the mutant proteins. As the next step, comparative physicochemical changes of the native and the mutant proteins were carried out using essential dynamics. Overall, P28T and A198V were predicted to alter the structure and function of GALK protein when compared to the mutant L139P. This study demonstrates the power of computational analysis in variant classification and interpretation and provides a platform for developing targeted therapeutics.

Computational simulations assessment of mutations impact on streptokinase (SK) from a group G streptococci with enhanced activity - insights into the functional roles of structural dynamics flexibility of SK and stabilization of SK-μplasmin catalytic complex

Streptokinase (SK), a plasminogen activator (PA) that converts inactive plasminogen (Pg) to plasmin (Pm), is a protein secreted by groups A, C, and G streptococci (GAS, GCS, and GGS, respectively), with high sequence divergence and functional heterogeneity. While roles of some residual changes in altered SK functionality are shown, the underlying structural mechanisms are less known. Herein, using computational approaches, we analyzed the conformational basis for the increased activity of SK from a GGS (SKG132) isolate with four natural residual substitutions (Ile33Phe, Arg45Gln, Asn228Lys, Phe287Ile) compared to the standard GCS (SKC). Using the crystal structure of SK.Pm catalytic complex as main template SKC.μPm catalytic complex was modeled through homology modeling process and validated by several online validation servers. Subsequently, SKG132.μPm structure was constructed by altering the corresponding residual substitutions. Results of three independent MD simulations showed increased RMSF values for SKG132.μPm, indicating the enhanced structural flexibility compared to SKC.μPm, specially in 170 and 250 loops and three regions: R1 (149-161), R2 (182-215) and R3 (224-229). In parallel, the average number of Hydrogen bonds in 170 loop, R2 and R3 (especially for Asn228Lys) of SKG132 compared to that of the SKC was decreased. Accordingly, residue interaction networks (RINs) analyses indicated that Asn228Lys might induce more level of structural flexibility by generation of free Lys256, while Phe287Ile and Ile33Phe enhanced the stabilization of the SKG132.μPm catalytic complex. These results denoted the potential role of the optimal dynamic state and stabilized catalytic complex for increased PA potencies of SK as a thrombolytic drug.

Dynamics and structural stability effects of germline PTEN mutations associated with cancer versus autism phenotypes

Individuals with germline mutations in the tumor suppressor gene phosphatase and tensin homolog (PTEN), irrespective of clinical presentation, are diagnosed with PTEN hamartoma tumor syndrome (PHTS). PHTS confers a high risk of breast, thyroid, and other cancers or autism spectrum disorder (ASD) with macrocephaly. It remains unclear why mutations in one gene can lead to seemingly disparate phenotypes. Thus, we sought to identify differences in ASD vs. cancer-associated germline PTEN missense mutations by investigating putative structural effects induced by each mutation. We utilized a theoretical computational approach combining in silico structural analysis and molecular dynamics (MD) to interrogate 17 selected mutations from our patient population: six mutations were observed in patients with ASD (only), six mutations in patients with PHTS-associated cancer (only), four mutations shared across both phenotypes, and one mutation with both ASD and cancer. We demonstrate structural stability changes where all six cancer-associated mutations showed a global decrease in structural stability and increased dynamics across the domain interface with a proclivity to unfold, mediating a closed (inactive) active site. In contrast, five of the six ASD-associated mutations showed localized destabilization that contribute to the partial opening of the active site. Our results lend insight into distinctive structural effects of germline PTEN mutations associated with PTEN-ASD vs. those associated with PTEN-cancer, potentially aiding in identification of the shared and separate molecular features that contribute to autism or cancer, thus, providing a deeper understanding of genotype-phenotype relationships for germline PTEN mutations.

Structural, molecular motions, and free-energy landscape of Leishmania sterol-14α-demethylase wild type and drug resistant mutant: a comparative molecular dynamics study

Sterol-14α-demethylase (CYP51) is an ergosterol pathway enzyme crucial for the survival of infectious Leishmania parasite. Recent high-throughput metabolomics and whole genome sequencing study revealed amphotericin B resistance in Leishmania is indeed due to mutation in CYP51. The residue of mutation (asparagine 176) is conserved across the kinetoplastidae and not in yeast or humans, portraying its functional significance. In order to understand the possible cause for the resistance, knowledge of structural changes due to mutation is of high importance. To shed light on the structural changes of wild and mutant CYP51, we conducted comparative molecular dynamics simulation study. The active site, substrate biding cavity, substrate channel entrance (SCE), and cavity involving the mutated site were studied based on basic parameters and large concerted molecular motions derived from essential dynamics analyses of 100 ns simulation. Results indicated that mutant CYP51 is stable and less compact than the wild type. Correspondingly, the solvent accessible surface area (SASA) of the mutant was found to be increased, especially in active site and cavities not involving the mutation site. Free-energy landscape analysis disclosed mutant to have a rich conformational diversity than wild type, with various free-energy conformations of mutant having SASA greater than wild type with SCE open. More residues were found to interact with the mutant CYP51 upon docking of substrate to both the wild and mutant CYP51. These results indicate that, relative to wild type, the N176I mutation of CYP51 in Leishmania mexicana could possibly favor increased substrate binding efficiency.

A profound computational study to prioritize the disease-causing mutations in PRPS1 gene

Charcot-Marie-Tooth disease (CMT) is one of the most commonly inherited congenital neurological disorders, affecting approximately 1 in 2500 in the US. About 80 genes were found to be in association with CMT. The phosphoribosyl pyrophosphate synthetase 1 (PRPS1) is an essential enzyme in the primary stage of de novo and salvage nucleotide synthesis. The mutations in the PRPS1 gene leads to X-linked Charcot-Marie-Tooth neuropathy type 5 (CMTX5), PRS super activity, Arts syndrome, X-linked deafness-1, breast cancer, and colorectal cancer. In the present study, we obtained 20 missense mutations from UniProt and dbSNP databases and applied series of comprehensive in silico prediction methods to assess the degree of pathogenicity and stability. In silico tools predicted four missense mutations (D52H, M115 T, L152P, and D203H) to be potential disease causing mutations. We further subjected the four mutations along with native protein to 50 ns molecular dynamics simulation (MDS) using Gromacs package. The resulting trajectory files were analyzed to understand the stability differences caused by the mutations. We used the Root Mean Square Deviation (RMSD), Radius of Gyration (Rg), solvent accessibility surface area (SASA), Covariance matrix, Principal Component Analysis (PCA), Free Energy Landscape (FEL), and secondary structure analysis to assess the structural changes in the protein upon mutation. Our study suggests that the four mutations might affect the PRPS1 protein function and stability of the structure. The proposed study may serve as a platform for drug repositioning and personalized medicine for diseases that are caused by the PRPS1 deficiency.

Effects of Peutz-Jeghers syndrome (PJS) causing missense mutations L67P, L182P, G242V and R297S on the structural dynamics of LKB1 (Liver kinase B1) protein

The liver kinase B1 (LKB1) is encoded by LKB1 gene. Several pathogenic mutations of LKB1 causing Peutz-Jeghers syndrome and also cancers in breast, gastric, pancreas, and colon have been reported. The present study is focused to analyze the effects on the structural dynamics of LKB1 caused by the 4 pathogenic missense mutations (L67P, L182P, G242V, and R297S), which are reported to reduce the catalytic activity. In this study, the structural changes of LKB1 in apo- and in heterotrimeric complex (LKB1-STRADα-MO25α) form with wild and mutated LKB1 are investigated using all atomistic molecular dynamic simulation. The present study reveals that these four mutations initiate local structural distortions and the solvent accessibility of the surrounding regions of ATP-binding pocket such as glycine-rich loop, αB and αC loop, activation and catalytic loops. The mutations of L67P, L182P, and G242 V induce distortions of the secondary structure of β1-β3 sheets, π - π interaction (observed between Phe204 of LKB1 and Phe243 of MO25α), and increase the helical properties (both helical twist and length) of the adjacent αH-helix, respectively. The active kinase features like the conformation of catalytic and activation loops, salt bridge and, finally, the formation of stable R- and C-hydrophobic spines are also found to be perturbed by these mutations. Hence, the observed mutation-induced structural distortions fail to coordinate the essential binding nature of LKB1 with STRADα and MO25α, which eventually affects the native function of LKB1. These observations are in line with the experimentally reported reduced kinase activity of LKB1.

Recent Developments and Applications of the MMPBSA Method

The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach has been widely applied as an efficient and reliable free energy simulation method to model molecular recognition, such as for protein-ligand binding interactions. In this review, we focus on recent developments and applications of the MMPBSA method. The methodology review covers solvation terms, the entropy term, extensions to membrane proteins and high-speed screening, and new automation toolkits. Recent applications in various important biomedical and chemical fields are also reviewed. We conclude with a few future directions aimed at making MMPBSA a more robust and efficient method.

Computational Resources for Predicting Protein-Protein Interactions

Proteins are the essential building blocks and functional components of a cell. They account for the vital functions of an organism. Proteins interact with each other and form protein interaction networks. These protein interactions play a major role in all the biological processes and pathways. The previous methods of predicting protein interactions were experimental which focused on a small set of proteins or a particular protein. However, these experimental approaches are low-throughput as they are time-consuming and require a significant amount of human effort. This led to the development of computational techniques that uses high-throughput experimental data for analyzing protein-protein interactions. The main purpose of this review is to provide an overview on the computational advancements and tools for the prediction of protein interactions. The major databases for the deposition of these interactions are also described. The advantages, as well as the specific limitations of these tools, are highlighted which will shed light on the computational aspects that can help the biologist and researchers in their research.

Probing the Protein-Protein Interaction Network of Proteins Causing Maturity Onset Diabetes of the Young

Protein-protein interactions (PPIs) play vital roles in various cellular pathways. Most of the proteins perform their responsibilities by interacting with an enormous number of proteins. Understanding these interactions of the proteins and their interacting partners has shed light toward the field of drug discovery. Also, PPIs enable us to understand the functions of a protein by understanding their interacting partners. Consequently, in the current study, PPI network of the proteins causing MODY (Maturity Onset Diabetes of the Young) was drawn, and their correlation in causing a disease condition was marked. MODY is a monogenic type of diabetes caused by autosomal dominant inheritance. Extensive research on transcription factor and their corresponding genetic pathways have been studied over the last three decades, yet, very little is understood about the molecular modalities of highly dynamic interactions between transcription factors, genomic DNA, and the protein partners. The current study also reveals the interacting patterns of the various transcription factors. Consequently, in the current work, we have devised a PPI analysis to understand the plausible pathway through which the protein leads to a deformity in glucose uptake.

IGF2BP1: a novel binding protein of p38 MAPK

Signal transduction pathways control various biological processes in cells leading to distinct cellular functions. Protein-protein interactions and post-translational modifications are the physiological events that occur in signaling pathway. p38 MAPK are known to be involved in regulating wide range of cellular processes by interacting and activating relevant signaling molecules by means of phosphorylation. Deregulation of p38 MAPK is associated with various pathological conditions. In order to get an insight into the role played by p38 MAPK in cellular signaling, studies were carried out to identify proteins that interact with p38 MAPK. Mass spectrometry was used to identify the proteins present in p38 MAPK complex obtained by co-immunoprecipitation. Based on mass spectrometry data, here we report insulin-like growth factor-II binding protein 1 (IGF2BP1) as a novel interacting partner of p38 MAPK. IGF2BP1 is a RNA-binding protein predominantly known to be involved in tumor progression. To reconfirm the mass spectrometry data, in silico analysis was carried out. Based on different models predicted in silico, we report the possible interaction domains of p38MAPK and IGF2BP1. Considering the involvement of p38MAPK and IGF2BP1 in cancer, our study opens up the possibility of p38MAPK regulating IGF2BP1 function, and the possibility of targeting this novel interaction for developing cancer-treating drugs is discussed.

Insights and Challenges of Multi-Scale Modeling of Sarcomere Mechanics in cTn and Tm DCM Mutants-Genotype to Cellular Phenotype

Dilated Cardiomyopathy (DCM) is a leading cause of sudden cardiac death characterized by impaired pump function and dilatation of cardiac ventricles. In this review we discuss various in silico approaches to elucidating the mechanisms of genetic mutations leading to DCM. The approaches covered in this review focus on bridging the spatial and temporal gaps that exist between molecular and cellular processes. Mutations in sarcomeric regulatory thin filament proteins such as the troponin complex (cTn) and Tropomyosin (Tm) have been associated with DCM. Despite the experimentally-observed myofilament measures of contractility in the case of these mutations, the mechanisms by which the underlying molecular changes and protein interactions scale up to organ failure by these mutations remains elusive. The review highlights multi-scale modeling approaches and their applicability to study the effects of sarcomeric gene mutations in-silico. We discuss some of the insights that can be gained from computational models of cardiac biomechanics when scaling from molecular states to cellular level.