Computational Mutation Analysis Research Articles

Analysis of 10,478 cancer genomes identifies candidate driver genes and opportunities for precision oncology

Tumor genomic profiling is increasingly seen as a prerequisite to guide the treatment of patients with cancer. To explore the value of whole-genome sequencing (WGS) in broadening the scope of cancers potentially amenable to a precision therapy, we analysed whole-genome sequencing data on 10,478 patients spanning 35 cancer types recruited to the UK 100,000 Genomes Project. We identified 330 candidate driver genes, including 74 that are new to any cancer. We estimate that approximately 55% of patients studied harbor at least one clinically relevant mutation, predicting either sensitivity or resistance to certain treatments or clinical trial eligibility. By performing computational chemogenomic analysis of cancer mutations we identify additional targets for compounds that represent attractive candidates for future clinical trials. This study represents one of the most comprehensive efforts thus far to identify cancer driver genes in the real world setting and assess their impact on informing precision oncology.

From driver genes to gene families: A computational analysis of oncogenic mutations and ubiquitination anomalies in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a widespread primary liver cancer with a high fatality rate. Despite several genes with oncogenic effects in HCC have been identified, many remain undiscovered. In this study, we conducted a comprehensive computational analysis to explore the involvement of genes within the same families as known driver genes in HCC. Specifically, we expanded the concept beyond single-gene mutations to encompass gene families sharing homologous structures, integrating various omics data to comprehensively understand gene abnormalities in cancer. Our analysis identified 74 domains with an enriched mutation burden, 404 domain mutation hotspots, and 233 dysregulated driver genes. We observed that specific low-frequency somatic mutations may contribute to HCC occurrence, potentially overlooked by single-gene algorithms. Furthermore, we systematically analyzed how abnormalities in the ubiquitinated proteasome system (UPS) impact HCC, finding that abnormal genes in E3, E2, DUB families, and Degron genes often result in HCC by affecting the stability of oncogenic or tumor suppressor proteins. In conclusion, expanding the exploration of driver genes to include gene families with homologous structures emerges as a promising strategy for uncovering additional oncogenic alterations in HCC.

Computational analysis of missense mutations in dystrophin protein: Insights into domain-specific effects and functional implications

BackgroundDystrophin is a structural protein primarily found in skeletal muscles that connects trans-membrane component of dystrophin-glycoprotein complex to the intracellular cytoskeleton network. N-terminal domain of dystrophin binds to F-actin and its C-terminal domain attaches to dystrophin-associated complex (DAG) in the membrane. It serves as the bridge connecting the extracellular matrix to the actin based cytoskeleton of muscle cells across the plasma membrane. This complex works together to strengthen muscle fibers and shield them from damage as they contract and relax. ObjectiveOur Objective is to investigate the different pathogenic mutations in four distinct domains of dystrophin protein and to decipher how these mutations impact protein structure and function. In this study, we investigated the impact of disease causing missense mutations in isoforms of dystrophin – P.11532–1 (K18N.A165V, D3187G, F3228L); P11532–4 (Y223N, D3179G) and P-11532-11 (Y227N,D3183G).Occurrence of pathogenic mutations in dystrophin might compromise structural stability, interfere with protein-protein interactions or alter cellular signaling pathways collectively. All these can contribute to the progressive muscle degeneration observed in Duchene or Becker muscular dystrophy(DMD or BMD) and X-lined dilated cardiomyopathy(CMD3B) affected individuals. MethodsEvolutionary conservation analysis using multiple sequence alignment followed by pathogenicity prediction using web based server was performed. Homology modeling of mutants was performed bySWISS MODEL a fully automated homology-modeling server, accessible through the Expasy web server. These models were then analyzed using various servers such as Dynamut. Pymol was used for visualization and structural analysis. ResultsAnalyzed mutations cause structural instability by either gaining or losing specific interactions involved in the folding of protein. Loss of pi-pi stacking interactions has the potential to significant impact the overall stability of the protein. It is important to note that the majority of the mutations lead to stability defects rather than functional defects, ultimately contributing to different forms of muscular dystrophy. ConclusiónThe mutations in different domains of Dystrophin protein significantly alters the protein structure. This may in turn impact its ability to interact with other proteins. Understanding the specific impacts of these mutations can pave the way for development of targeted therapies that aims at restoring functionality of dystrophin and ameliorating the debilitating effects of muscular dystrophy.

Effect of Mutation of RNA-dependent RNA Polymerase (RdRp) of Hepatitis C Virus on Affinities of Dasabuvir: Computational Study

Hepatitis C Virus (HCV) is one of the infectious diseases that has posed a serious threat to global public health for the past few decades. HCV is an RNA virus that infects the human liver and can lead to chronic liver damage, cirrhosis, and even liver cancer. Treatment for HCV infection has made rapid advancements in recent years, particularly with the development of more effective antiviral drugs. One of the drugs used in HCV therapy is dasabuvir. Dasabuvir is an RNA-dependent RNA polymerase (RdRp) inhibitor that functions to inhibit the replication of the HCV virus. The RdRp enzyme in HCV is represented by NS5B, and dasabuvir specifically targets this enzyme. Several reports have revealed mutations in HCV NS5B due to the use of dasabuvir. This study conducted a computational mutation analysis on NS5B of HCV resulting from dasabuvir usage. The research findings indicate that mutations in the HCV polymerase induced by dasabuvir usage lead to changes in dasabuvir's conformation and binding energy. Some mutations decrease binding energy, such as mutations C316N, C451S, and N411S. However, on the other hand, there are mutations that increase binding energy, such as M414V, A553V, and C445F. The decrease in binding energy is supported by increased hydrogen bonding interactions with Asp318, Gln446, and Tyr448, as well as the formation of new hydrogen bonds, such as hydrogen bonding with Ser288 in C451S and Arg200 in C451S. Meanwhile, the increase in binding energy is supported by decreased binding interactions with Asp318 and pi-pi interactions with Phe193. Hydrogen bonding with Asn291 also decreases, as seen in A553V, and is even lost in C445F. Future work will be devoted for designing new dasabuvir derivatives which having better affinited to NS5B of HCV.

Identification of the effects of pathogenic genetic variations of human CYP2C9 and CYP2D6: an in silico approach

Genetic variations in the human cytochrome P450 family 2 subfamily C member 9 (CYP2C9) and cytochrome P450 family 2 subfamily D member 6 (CYP2D6) genes may affect drug metabolism and lead to alterations in phenotypes. Genetic variations are associated with toxicity, adverse drug reactions, inefficient treatment. Various in silico tools were combined to investigate the deleterious effects of missense non-synonymous single nucleotide polymorphisms (nsSNPs) of the human CYP2C9 and CYP2D6. The structural and functional effects of the high-risk non-synonymous SNPs in the human CYP2C9 and CYP2D6 were predicted by numerous computational mutation analysis methods. Out of 24 pathogenic missense SNPs in the CYP2C9, 22 nsSNPs had a decreasing effect on protein stability and 13 SNPs were showed to be located at conserved positions. Out of 27 high-risk deleterious non-synonymous SNPs in the human CYP2D6, 21 SNPs decreased protein stability and 16 nsSNPs were predicted to be positioned at conserved regions. Our present study suggests that the identified functional SNPs may affect drug metabolism associated with CYP2C9 and CYP2D6 enzymes.

Elucidation of Short Linear Motif-Based Interactions of the FERM Domains of Ezrin, Radixin, Moesin, and Merlin.

The ERM (ezrin, radixin, and moesin) family of proteins and the related protein merlin participate in scaffolding and signaling events at the cell cortex. The proteins share an N-terminal FERM [band four-point-one (4.1) ERM] domain composed of three subdomains (F1, F2, and F3) with binding sites for short linear peptide motifs. By screening the FERM domains of the ERMs and merlin against a phage library that displays peptides representing the intrinsically disordered regions of the human proteome, we identified a large number of novel ligands. We determined the affinities for the ERM and merlin FERM domains interacting with 18 peptides and validated interactions with full-length proteins through pull-down experiments. The majority of the peptides contained an apparent Yx[FILV] motif; others show alternative motifs. We defined distinct binding sites for two types of similar but distinct binding motifs (YxV and FYDF) using a combination of Rosetta FlexPepDock computational peptide docking protocols and mutational analysis. We provide a detailed molecular understanding of how the two types of peptides with distinct motifs bind to different sites on the moesin FERM phosphotyrosine binding-like subdomain and uncover interdependencies between the different types of ligands. The study expands the motif-based interactomes of the ERMs and merlin and suggests that the FERM domain acts as a switchable interaction hub.

Computational analysis of PTP-1B site-directed mutations and their structural binding to potential inhibitors

Protein tyrosine phosphatase-1B (PTP-1B) is a well-known therapeutic target for diabetes and obesity as it suppresses insulin and leptin signaling. PTP-1B deletion or pharmacological suppression boosted glucose homeostasis and insulin signaling without altering hepatic fat storage. Inhibitors of PTP-1B may be useful in the treatment of type 2 diabetes, and shikonin, a naturally occurring naphthoquinone dye pigment, is reported to inhibit PTP-1B and possess antidiabetic properties. Since the cell contains a large number of phosphatases, PTP-1B inhibitors must be effective and selective. To explore more about the mechanism underlying the inhibitor's efficacy and selectivity, we investigated its top four pharmacophores and used site-directed mutagenesis to insert amino acid mutations into PTP-1B as an extension of our previous study where we identified 4 pharmacophores of shikonin. The study aimed to examine the site-directed mutations like R24Y, S215E, and S216C influence the binding of shikonin pharmacophores, which act as selective inhibitors of PTP-1B. To achieve this purpose, docking and molecular dynamics simulations of wild-type (WT) and mutant PTP-1B with antidiabetic compounds were undertaken. The simulation results revealed that site-directed mutations can change the hydrogen bond and hydrophobic interactions between shikonin pharmacophores and many residues in PTP-1B's active site, influencing the drug's binding affinity. These findings could aid researchers in better understanding PTP-1B inhibitors' selective binding mechanism and pave the path for the creation of effective PTP-1B inhibitors.

Computational Analysis of Mutations in the Receptor-Binding Domain of SARS-CoV-2 Spike and Their Effects on Antibody Binding.

Currently, SARS-CoV-2 causing coronavirus disease 2019 (COVID-19) is responsible for one of the most deleterious pandemics of our time. The interaction between the ACE2 receptors at the surface of human cells and the viral Spike (S) protein triggers the infection, making the receptor-binding domain (RBD) of the SARS-CoV-2 S-protein a focal target for the neutralizing antibodies (Abs). Despite the recent progress in the development and deployment of vaccines, the emergence of novel variants of SARS-CoV-2 insensitive to Abs produced in response to the vaccine administration and/or monoclonal ones represent a potential danger. Here, we analyzed the diversity of neutralizing Ab epitopes and assessed the possible effects of single and multiple mutations in the RBD of SARS-CoV-2 S-protein on its binding affinity to various antibodies and the human ACE2 receptor using bioinformatics approaches. The RBD-Ab complexes with experimentally resolved structures were grouped into four clusters with distinct features at sequence and structure level. The performed computational analysis indicates that while single amino acid replacements in RBD may only cause partial impairment of the Abs binding, moreover, limited to specific epitopes, the variants of SARS-CoV-2 with multiple mutations, including some which were already detected in the population, may potentially result in a much broader antigenic escape. Further analysis of the existing RBD variants pointed to the trade-off between ACE2 binding and antigenic escape as a key limiting factor for the emergence of novel SAR-CoV-2 strains, as the naturally occurring mutations in RBD tend to reduce its binding affinity to Abs but not to ACE2. The results provide guidelines for further experimental studies aiming to identify high-risk RBD mutations that allow for an antigenic escape.

Computational analysis of interior mutations of SARS-CoV-2 Spike protein suggest a balance of protein stability and S2: S1 separation propensity

SARS-CoV-2 variants often include surface mutations in the Spike protein that are important for viruses to recognize host receptors and evade antibody neutralization. The Spike protein also has mutations in the interior of the protein likely to affect the Spike protein S1 – S2 subunit’s separation propensity, the most important of which is the D614G mutation. Remarkably, the Omicron variant contains a large number of internal mutations at the S2: S1 interface, which have not been investigated yet. In this study, we examined the effects of such interfacial mutations on the S2: S1 and subunit domain interactions and on the subunit’s dissociation process. We found that the interaction with S2 is mainly contributed by the three encapsulation domains, named INT, ED1 and ED2 of S1, which are sandwiched between the S1 RBD and N-terminal NTD domain. We found that D614 is the strongest contributor for the S2: S1 interaction which is greatly weakened by the D614G mutation. Surprisingly, we found that, mutations T547K, H655Y, N764K, N856K, N969K, L981F in the Omicron variant largely enhance the S2: ED1 interaction, partially compensating the loss of S2: ED2 interaction due to the D614G mutation. Lastly, these results, together with biological considerations, allow us to suggest that in addition to the binding strength of between the RBD and ACE2, the stability of the Spike protein and the propensity of Spike protein S2: S1 separation are critical factors which likely exist in a balance for a particular infectivity and pathogenicity of the virus.

Residue 6.43 defines receptor function in class F GPCRs

The class Frizzled of G protein-coupled receptors (GPCRs), consisting of ten Frizzled (FZD1-10) subtypes and Smoothened (SMO), remains one of the most enigmatic GPCR families. While SMO relies on cholesterol binding to the 7TM core of the receptor to activate downstream signaling, underlying details of receptor activation remain obscure for FZDs. Here, we aimed to investigate the activation mechanisms of class F receptors utilizing a computational biology approach and mutational analysis of receptor function in combination with ligand binding and downstream signaling assays in living cells. Our results indicate that FZDs differ substantially from SMO in receptor activation-associated conformational changes. SMO manifests a preference for a straight TM6 in both ligand binding and functional readouts. Similar to the majority of GPCRs, FZDs present with a kinked TM6 upon activation owing to the presence of residue P6.43. Functional comparison of FZD and FZD P6.43F mutants in different assay formats monitoring ligand binding, G protein activation, DVL2 recruitment and TOPflash activity, however, underlines further the functional diversity among FZDs and not only between FZDs and SMO.

Molecular and computational analysis of natural drug resistance mutations among Moroccan chronic hepatitis B carriers

Despite the effectiveness of nucleotide analogs (NAs), drug resistance and cccDNA inaccessibility are still significant obstacles to long-term efficacy of antiviral therapy in chronic hepatitis B infection (CHB). Mutations pre-exist spontaneously in Hepatitis B Virus (HBV) reverse transcriptase (RT) gene in minor viral populations and can emerge to confer drug resistance and treatment failure. This study aimed to analyze mutations within the HBV polymerase gene in treatment-naive Moroccan patients with CHB.The HBV polymerase gene was analyzed by nested-PCR and direct sequencing in 123 subjects. A computational analysis was performed to confirm the effect of detected mutations on targeted NAs, using homology and docking tools.Sixty samples were successfully amplified by PCR. Analyses revealed an intermediate rate (13%) of pre-treatment NA resistance mutations and a high frequency of putative resistance mutations (65%). Among these, 56% were lamivudine resistance mutations and 44% adefovir resistance mutations. Two pretreatment resistance mutations, “Y124N” and “N139D/K/H/Q” were detected in 8/60 patients, and 11 putative resistance mutations (N53S/T/D, L91I, H126Y, T128I, V207I, V214A, Q215P/S, L217R, F221Y, L229V, N238H/T) in 39/60 patients, where two have a combination of F221Y and A194T “a classical NA drug resistance mutation.” The computational analysis demonstrated that the combination of A194T + F221Y mutations on HBV RT sequence does not affect its susceptibility to ADV.These results confirm that HBV mutations conferring resistance against currently available anti-HBV NA predate treatment in naïve Moroccan patients. The high rate of non-classical NA resistance mutations needs further in vitro phenotype analysis.

Computational Analysis of the Effect Collagen Glycine Mutations Have on Hydrogen Bonding

Computational Analysis of the Effect Collagen Glycine Mutations Have on Hydrogen Bonding

Identification and computational analysis of mutations in SARS-CoV-2

SARS-CoV-2 infection has become a worldwide pandemic and is spreading rapidly to people across the globe. To combat the situation, vaccine design is the essential solution. Mutation in the virus genome plays an important role in limiting the working life of a vaccine. In this study, we have identified several mutated clusters in the structural proteins of the virus through our novel 2D Polar plot and qR characterization descriptor. We have also studied several biochemical properties of the proteins to explore the dynamics of evolution of these mutations. This study would be helpful to understand further new mutations in the virus and would facilitate the process of designing a sustainable vaccine against the deadly virus.

Bioinformatic Methods to Identify Mutational Signatures in Cancer.

The genome of a cancer contains somatic mutations that reflect the activities of endogenous and exogenous mutational processes, with each mutational process imprinting a characteristic mutational signature. Computational analysis of somatic mutations derived from next-generation sequencing data allows revealing the mutational signatures operative in a set of cancer genomes. In this chapter, we briefly review the concept of mutational signatures and the tools available for deciphering mutational signatures. Further, we provide a quick guide as well as an in-depth protocol for deciphering mutational signatures using the tool SigProfilerExtractor and review the results generated from an example dataset of cancer genomes.

Computational analysis of TP53 vs. CTNNB1 mutations in hepatocellular carcinoma suggests distinct cancer subtypes with differential gene expression profiles and chromatin states

Genetic variations are important drivers of carcinogenesis. It is extremely important to identify molecular distinctions between patients of the same disease for effective cancer treatment. This study aims to understand cellular and molecular differences between hepatocellular carcinoma patients carrying TP53 or CTNNB1 mutations, which could possess clinical significance. For this purpose, DNA sequencing and mRNA expression data for hepatocellular carcinoma patients were analyzed. Differentially expressed genes and the cellular processes that they are involved in were determined for TP53/CTNNB1-altered patient groups. We found that the mutations of TP53/CTNNB1 genes in the patient cohort was almost mutually exclusive and gene expression profiling in these subgroups were unique. Gene Ontology (GO) enrichment analysis of the differentially expressed genes identified several important cellular processes. In line with this, selected histone variants, histone chaperons, as well as the binding partners of TP53/CTNNB1 showed distinct enrichment levels. TP53/CTNNB1-altered patient groups laso showed different prognostic outcomes and tumor infiltration levels. In conclusion, our results strongly imply differential chromatin states and transcriptional regulation in relation to the mutational status of TP53 vs. CTNNB1, suggesting that these genes might be inducing different cellular pathways involving distinct chromatin environments during the course of carcinogenesis.

Computational analysis of hereditary spastic paraplegia mutations in the kinesin motor domains of KIF1A and KIF5A

Hereditary spastic paraplegias (HSPs) are a genetically heterogeneous collection of neurodegenerative disorders categorized by progressive lower-limb spasticity and frailty. The complex HSP forms are characterized by various neurological features including progressive spastic weakness, urinary sphincter dysfunction, extra pyramidal signs and intellectual disability (ID). The kinesin superfamily proteins (KIFs) are microtubule-dependent molecular motors involved in intracellular transport. Kinesins directionally transport membrane vesicles, protein complexes, and mRNAs along neurites, thus playing important roles in neuronal development and function. Recent genetic studies have identified kinesin mutations in patients with HSPs. In this study, we used the computational approaches to investigate the 40 missense mutations associated with HSP and ID in KIF1A and KIF5A. We performed homology modeling to construct the structures of kinesin–microtubule binding domain and kinesin–tubulin complex. We applied structure-based energy calculation methods to determine the effects of missense mutations on protein stability and protein–protein interaction. The results revealed that the most of disease-causing mutations could change the folding free energy of kinesin motor domain and the binding free energy of kinesin–tubulin complex. We found that E253K associated with ID in KIF1A decrease the protein stability of kinesin motor domains. We showed that the HSP mutations located in kinesin–tubulin complex interface, such as K253N and R280C in KIF5A, can destabilize the kinesin–tubulin complex. The computational analysis provides useful information for understanding the roles of kinesin mutations in the development of ID and HSPs.

Identification and Computational Analysis of Novel TYR and SLC45A2 Gene Mutations in Pakistani Families With Identical Non-syndromic Oculocutaneous Albinism.

Non-syndromic oculocutaneous albinism (nsOCA) is an inherited disorder of melanin biosynthesis with autosomal recessive mode of inheritance, presenting either hypopigmented or depigmented skin, hair, and eyes. It is genetically heterogeneous with seven loci (OCA1–OCA7) reported to date. In the present study, we have reported three consanguineous families (A, B, C) presenting identical nsOCA phenotypes. Sanger sequencing revealed a novel [NM_000372.5: c.826 T > C, p.(Cys276Arg)] and a recurrent variant [NM_000372.5: c.832C > T, p.(Arg278∗)] in tyrosinase (TYR) in families A and B, respectively. Microsatellite marker-based homozygosity mapping linked family C to OCA4. Sequence analysis identified a novel insertion variant (NM_016180.5: c.1331_1332insA) in the SLC45A2. Further, in silico mutagenesis and dynamic simulation approaches revealed that a novel Cys276Arg variant abolished the cysteine bridge and might contribute toward decreased stability of the TYR protein. Our study expands the mutation spectrum of the TYR and SLC45A2 genes and emphasizes that molecular investigations are essential for accurate disease diagnosis.

Molecular dynamics simulation and binding free energy calculations of microcin J25 binding to the FhuA receptor

Microcins are low-molecular weight, highly stable, ribosomally produced, bacterial inhibitory molecules involved in competitive research. Microcin J25 consists of 21 amino acids and has a lasso-like structure. The first step is bacteria binding to the ion receptor of FhuA on the bacterial surface. In this study, molecular dynamics simulation was implemented to study the binding mechanism of MJ25 and three mutants, to find the changing of individual amino acids in the β-hair region of MJ25. The binding-free energy calculation was subjected to MJ25 and FhuA. In addition, computational mutation analysis was revealed for association between MJ25 and FhuA. However, we found that the mutating 12th amino acid of the β-hair region into histidine is extremely important for the binding of MJ25 to FhuA. In addition, the number of hydrogen bonds is essential for binding of MJ25 to FhuA. The overall results show that the key guiding significance is improving the sterilizing efficiency of MJ25 and the drug design of MJ25. Communicated by Ramaswamy H. Sarma

Computational Analysis of Missense Mutations in Creatine Transporter Protein Associated with Creatine Deficiency Syndrome

Computational Analysis of Missense Mutations in Creatine Transporter Protein Associated with Creatine Deficiency Syndrome

Computational Modeling Explains the Multi Sterol Ligand Specificity of the N-Terminal Domain of Niemann-Pick C1-Like 1 Protein.

Niemann–Pick C1 like 1 (NPC1L1) is a sterol transporter expressed in the apical membrane of enterocytes and hepatocytes. NPC1L1 resembles the lysosomal NPC1 protein including an N-terminal domain (NTD), which binds a variety of sterols. The molecular mechanisms underlying this multiligand specificity of the NTD of NPC1L1 (NPC1L1–NTD) are not known. On the basis of the crystal structure of NPC1L1–NTD, we have investigated the structural details of protein–sterol interactions using molecular mechanics Poisson Boltzmann surface area calculations here. We found a good agreement between experimental and calculated binding affinities with similar ranking of various sterol ligands. We defined hydrogen bonding of sterol ligands via the 3′-β-hydroxy group inside the binding pose as instrumental in stabilizing the interaction. A leucine residue (LEU213) at the mouth of the binding pocket transiently opens to allow for the access of sterol into the binding pose. Our calculations also predict that NPC1L1–NTD binds polyene sterols, such as dehydroergosterol or cholestatrienol with high affinity, which validates their use in future experiments as close intrinsically fluorescent cholesterol analogs. A free energy decomposition and computational mutation analysis revealed that the binding of various sterols to NPC1L1–NTD depends critically on specific amino acid residues within the binding pocket. Some of these residues were previously detected as being relevant for intestinal cholesterol absorption. We show that clinically known mutations in the NPC1L1–NTD associated with lowered risk of coronary heart disease result in strongly reduced binding energies, providing a molecular explanation for the clinical phenotype.