Studies on flexibility and binding affinity of Asp25 of HIV-1 protease mutants

Repurposing FDA-approved drugs targeting FZD10 in nasopharyngeal carcinoma: insights from molecular dynamics simulations and experimental validation

Wnt signaling is a critical pathway implicated in cancer development, with Frizzled proteins, particularly FZD10, playing key roles in tumorigenesis and recurrence. This study focuses on the potential of repurposed FDA-approved drugs targeting FZD10 as a therapeutic strategy for nasopharyngeal carcinoma (NPC). The tertiary structure of human FZD10 was constructed using homology modeling, validated by Ramachandran plot and ProQ analysis. Virtual screening of 1,094 FDA-approved drugs identified 17 potential inhibitors, with prazosin, rilpivirine, doxazosin, and nicergoline demonstrating significant cytotoxicity against NPC cells. Further molecular dynamics simulations and binding energy analyses confirmed the stable binding of these drugs to FZD10. The results suggest that these repurposed drugs could serve as promising candidates for targeted NPC therapy, warranting further investigation.

Identification of AChE targeted therapeutic compounds for Alzheimer's disease: an in-silico study with DFT integration

Alzheimer's disease (AD) is a progressive neurodegenerative condition marked by cognitive deterioration and changes in behavior. Acetylcholinesterase (AChE), which hydrolyzes acetylcholine, is a key drug target for treating AD. This research aimed to identify new AChE inhibitors using the IMPPAT database. We used known drugs as a basis to search for similar chemicals in the IMPPAT database and created a library of 127 plant-based compounds. Initial screening of these compounds was performed using molecular docking, followed by an analysis of their drug-likeness and ADMET properties. Compounds with favorable properties underwent density functional theory (DFT) calculations to assess their electronic properties such as HOMO-LUMO gap, electron density, and molecular orbital distribution. These descriptors provided insights into each compound's reactivity, stability, and binding potential with AChE. Promising candidates were further evaluated through molecular dynamics (MD) simulations over 100 ns and MMPBSA analysis for the last 30 ns. Two compounds, Biflavanone (IMPHY013027) with a binding free energy of - 130.394 kcal/mol and Calomelanol J (IMPHY007737) with - 107.908 kcal/mol, demonstrated strong binding affinities compared to the reference molecule HOR, which has a binding free energy of - 105.132 kcal/mol. These compounds exhibited promising drug-ability profiles in both molecular docking and MD simulations, indicating their potential as novel AChE inhibitors for AD treatment. However, further experimental validation is necessary to verify their effectiveness and safety.

In silico identification of potential protein kinase C alpha inhibitors from phytochemicals from IMPPAT database for anticancer therapeutics: a virtual screening approach

Protein Kinase C alpha (PKCα) is a critical signaling molecule that plays a crucial role in various physiological processes, including cell growth, differentiation, and survival. Over the years, there has been a growing interest in targeting PKCα as a promising drug target for the treatment of various diseases, including cancer. Targeting PKCα can, therefore, serve as a potential strategy to prevent cancer progression and enhance the efficacy of conventional anticancer therapies. We conducted a systematic search for promising compounds for their anticancer potential that target PKCα using natural compounds from the IMPPAT database. The initial compounds were screened through various tests, including analysis of their physical and chemical properties, PAINS filter, ADMET analysis, PASS analysis, and specific interaction analysis. We selected those that showed high binding affinity and specificity to PKCα from the screened compounds, and we further analyzed them using molecular dynamics simulations (MDS) and principal component analysis (PCA). Various systematic parameters from the MDS analyses suggested that the protein-ligand complexes were stabilized throughout the simulation trajectories of 100 nanoseconds (ns). Our findings indicated that compounds Nicandrenone and Withaphysalin D bind to PKCα with high stability and affinity, making them potential candidates for further research in cancer therapeutics innovation in clinical contexts.Communicated by Ramaswamy H. Sarma.

Structural and dynamical insights revealed the anti-glioblastoma potential of withanolides from Withania coagulans against vascular endothelial growth factor receptor (VEGFR)

CONTEXT

Glioblastoma (GBM), well known as grade 4 tumors due to its progressive malignant features such as vascular proliferation and necrosis, is the most aggressive form of primary brain tumor found in adults. Mutations and amplifications in the vascular endothelial growth factor receptor (VEGFR) contribute to almost 25% of GBM tumors. And thus, VEGFR has been declared the primary target in glioblastoma therapeutic strategies. However, many studies have been previously reported that include GBM as global therapeutics challenge, but they lack the molecular level insights that could help in understanding the biological function of a therapeutically important protein playing a major role in the disease and design the best strategies to develop the potential drugs.

METHODS

Therefore, to the best of our knowledge, the present study is the first time of kind, which involves multi-in silico approaches to predict the inhibition potential of withanolides from Withania coagulan against VEGFR. The study is actually based on determining the mode of action of five isolates: withanolide J, withaperuvin, 27-hydroxywithanolide I, coagule E, and coagule E, along with their respective binding energies. Molecular docking simulations revealed primarily four ligands, withanolide J (- 7.33 kJ/mol), 27-withanolide (- 7.01 kJ/mol), ajugine, withaperuvin (- 6.89 kJ/mol), and ajugine E (- 6.39 kJ/mol), to have significant binding potencies against the protein. Ligand binding was found to enhance the confirmational stability of the protein revealed through RMSD analysis, and RMSF assessment revealed the protein residues especially from 900-1000 surrounding the binding of the protein. Structural and dynamics of the protein via dynamics cross-correlation movement (DCCM) and principal component analysis (PCA) in both the unbound form and complexed with most potent ligand, withanolide J, reveal the ligand binding affecting the entire conformational integrity of the protein stabilized by hydrogen bonds and electrostatic attractions. Free energy of binding estimations by means of molecular mechanics Poisson-Boltzmann surface area (MMPBSA) method further revealed the withanolide J to have maximum binding potency of the all ligands. Withanolide J in final was also found to have suitable molecular characterizations to cross the blood-brain barrier (BBB +) and reasonable human intestinal absorption ability determined by ADMET profiling via admetSAR tools.

Discovery of novel CDK4/6 inhibitors from fungal secondary metabolites

The development of targeted therapies for breast cancer, particularly those focusing on cyclin-dependent kinases 4/6 (CDK4/6), has significantly improved patient outcomes. However, the currently approved CDK4/6 inhibitors are associated with various side effects, underscoring the need for novel compounds with enhanced efficacy and safety profiles. This study aimed to identify potential CDK4/6 inhibitors from MeFSAT, a database of fungal secondary metabolites using an in-silico screening approach. The virtual screening process incorporated drug-likeness filters, ADME and toxicity predictions, consensus molecular docking, and 200 ns molecular dynamics simulations. Out of 411 initial compounds, two molecules demonstrated favorable binding interactions and stability with the CDK4/6 protein complex. The MTT assay showed that MSID000025 had dose-dependent cytotoxicity against MCF7 breast cancer cells. This suggests that MSID000025 could be a good candidate CDK4/6 inhibitor for treating breast cancer. Our study highlights the potential of fungal secondary metabolites as a source of novel compounds for drug discovery. It provides a framework for identifying CDK4/6 inhibitors with improved therapeutic properties.

Identification of Pathogenic Missense Mutations of NF1 Using Computational Approaches

Neurofibromatosis type 1 (NF1) is a prevalent autosomal dominant disorder caused by mutations in the NF1 gene, leading to multisystem disorders. Given the critical role of cysteine residues in protein stability and function, we aimed to identify key NF1 mutations affecting cysteine residues that significantly contribute to neurofibromatosis pathology. To identify the most critical mutations in the NF1 gene that contribute to the pathology of neurofibromatosis, we employed a sophisticated computational pipeline specifically designed to detect significant mutations affecting the NF1 gene. Our approach involved an exhaustive search of databases such as the Human Gene Mutation Database (HGMD), UniProt, and ClinVar for information on missense mutations associated with NF1. Our search yielded a total of 204 unique cysteine missense mutations. We then employed in silico prediction tools, including PredictSNP, iStable, and Align GVGD, to assess the impact of these mutations. Among the mutations, C379R, R1000C, and C1016Y stood out due to their deleterious effects on the biophysical properties of the neurofibromin protein, significantly destabilizing its structure. These mutations were subjected to further phenotyping analysis using SNPeffect 4.0, which predicted disturbances in the protein's chaperone binding sites and overall structural stability. Furthermore, to directly visualize the impact of these mutations on protein structure, we utilized AlphaFold3 to simulate both the wild-type and mutant NF1 structures, revealing the significant effects of the R1000C mutation on the protein's conformation. In conclusion, the identification of these mutations can play a pivotal role in advancing the field of precision medicine and aid in the development of effective drugs for associated diseases.

Genes adaptability and NOL6 protein inhibition studies of fabricated flavan-3-ols lead skeleton intended to treat breast carcinoma

Breast cancer invasive 2.3 million women worldly and second prominent factor of cancer-related mortality. Finding a new site-specific and safe small molecule is a current need in this field. With the aid of deep learning Algorithms, we analyzed the published big database from cancer CBioportal to find the best target protein. Further, Multi-omics analysis such as enrichment analysis, scores of molecular, RNA biological function at a cellular level, and protein domain were obtained and matched to find the better hit molecules. The gene analysis output shows nucleolar protein 6 plays a significant responsibility in breast carcinoma and 354 natural and synthetic lead molecules are docked inside the active site. Docking result gave the output hit molecule falavan-3-ols with a binding score of -5.325 (Kcal/mol) and interaction analysis illustrates, 13 active amino acids favoring the binding interaction with functional groups of the hit molecule compared to the standard molecule Abemacilib (-2.857 (Kcal/mol)). Best docked complex of flavan-3-ols and NOL6 protein subjected to dynamic simulation 100 ns to study the stability. The results proved that π-π stacked, carbon‑hydrogen and electrostatic interactions are stable throughout the 100 ns simulation. The overall results conclude the hit molecule flavan-3-ol will be a safe and potent lead molecule to generate and treat breast carcinoma patients.

Computational modeling of in-stent restenosis: Pharmacokinetic and pharmacodynamic evaluation

Persistence of the pathology of in-stent restenosis even with the advent of drug-eluting stents warrants the development of highly resolved in silico models. These computational models assist in gaining insights into the transient biochemical and cellular mechanisms involved and thereby optimize the stent implantation parameters. Within this work, an already established fully-coupled Lagrangian finite element framework for modeling the restenotic growth is enhanced with the incorporation of endothelium-mediated effects and pharmacological influences of rapamycin-based drugs embedded in the polymeric layers of the current generation drug-eluting stents. The continuum mechanical description of growth is further justified in the context of thermodynamic consistency. Qualitative inferences are drawn from the model developed herein regarding the efficacy of the level of drug embedment within the struts as well as the release profiles adopted. The framework is then intended to serve as a tool for clinicians to tune the interventional procedures patient-specifically.

Discovery of Nirmatrelvir Resistance Mutations in SARS-CoV-2 3CLpro: A Computational-Experimental Approach

The COVID-19 pandemic has emphasized the urgency for effective antiviral therapies against SARS-CoV-2. Targeting the main protease (3CLpro) of the virus has emerged as a promising approach, and nirmatrelvir (PF-07321332), the active component of Pfizer's oral drug Paxlovid, has demonstrated remarkable clinical efficacy. However, the emergence of resistance mutations poses a challenge to its continued success. In this study, we employed alchemical free energy perturbation (FEP) alanine scanning to identify nirmatrelvir-resistance mutations within SARS-CoV-2 3CLpro. FEP identified several mutations, which were validated through in vitro IC50 experiments and found to result in 8- and 72-fold increases in nirmatrelvir IC50 values. Additionally, we constructed SARS-CoV-2 omicron replicons containing these mutations, and one of the mutants (S144A/E166A) displayed a 20-fold increase in EC50, confirming the role of FEP in identifying drug-resistance mutations. Our findings suggest that FEP can be a valuable tool in proactively monitoring the emergence of resistant strains and guiding the design of future inhibitors with reduced susceptibility to drug resistance. As nirmatrelvir is currently widely used for treating COVID-19, this research has important implications for surveillance efforts and antiviral development.

Decoding the deactivation mechanism of R192W mutation of ZAP-70 using molecular dynamics simulations and binding free energy calculations

CONTEXT

ZAP-70 (zeta-chain-associated protein of 70 kDa), serving as a critical regulator for T cell antigen receptor signaling, represents an attractive therapeutic target for autoimmunity disease. How the mechanistical mechanism of ZAP-70 to a human autoimmune syndrome-associated R192W mutation remains unclear. The results indicated that the R192W mutation of ZAP-70 clearly affected the conformational flexibility of the N-terminal ITAM-Y2P. Structural analysis unveiled that the R192W mutation of ZAP-70 caused the exposure of the N-terminal ITAM-Y2P to the solvent. MM-GBSA binding free energy calculations exhibited that the R192W mutation decreased the binding affinity of ITAM-Y2P to the ZAP-70 mutant. Residue-based free energy decomposition further revealed that the protein-peptide interaction networks involving electrostatic interactions provide significant contributions for complex formation. The energy unfavorable residues include Arg43, Arg192, Tyr240, and Lys244 from ZAP-70 and Asn301, Leu303, pY304, and pY315 from ITAM-Y2P in the R192W mutant. Our obtained results may help the understanding of the deactivation mechanism of ZAP-70 induced by the R192W mutation.

METHODS

In the work, multiple replica molecular dynamics simulations and molecular mechanics-generalized Born surface area (MM-GBSA) method were performed to reveal the doubly phosphorylated ITAMs (ITAM-Y2P)-mediated deactivation mechanism of ZAP-70 induced by the R192W mutation.

Computational design and validation of effective siRNAs to silence oncogenic KRAS

Oncogenic KRAS mutations drive cancer progression in lung, colon, breast, and pancreatic ductal adenocarcinomas. Apart from the current strategies, such as KRAS upstream inhibitors, downstream effector inhibitors, interaction inhibitors, cell cycle inhibitors, and direct KRAS inhibitors, against KRAS-mutated cancers, the therapeutic small interfering RNAs (siRNAs) represent a promising alternative strategy that directly binds with the target mRNA and inhibits protein translation via mRNA degradation. Here, in the present study, we utilized various in silico approaches to design potential siRNA candidates against KRAS mRNA. We have predicted nearly 17 siRNAs against the KRAS mRNA, and further through various criteria, such as U, R, and A rules, GC%, secondary structure formation, mRNA-siRNA duplex stability, Tm (Cp), Tm (Conc), and inhibition efficiency, they have been filtered into 4 potential siRNAs namely siRNA8, siRNA11, siRNA12, and siRNA17. Further, the molecular docking analysis revealed that the siRNA8, siRNA11, siRNA12, and siRNA17 showed higher negative binding energies, such as - 379.13 kcal/mol, - 360.19 kcal/mol, - 288.47 kcal/mol, and - 329.76 kcal/mol, toward the human Argonaute2 protein (hAgo2) respectively. In addition, the normal mode analysis of the hAgo2-siRNAs complexes indicates the structural changes and deformation of the hAgo2 protein upon the binding of siRNA molecules in the dynamic environment which suggests that these siRNAs could be effective. Finally, we conclude that these 4 siRNAs have therapeutic potential against KRAS mRNA and also have to be studied in vitro and in vivo to evaluate their specificity toward mutant KRAS (not degrading wild-type KRAS). Also, the current challenges in the use of siRNA therapeutics could be overcome by the emerging siRNA delivery methods, such as Antibody-siRNA conjugates (ARCs) and Gelatin-Antibody Delivery System (GADS), in the near future and these siRNAs could be employed as potential therapeutic agents against KRAS-mutated cancers.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03767-w.

Free energy landscape and thermodynamics properties of novel mutations in PncA of pyrazinamide resistance isolates of Mycobacterium tuberculosis

Pyrazinamide (PZA) is one of the first-line antituberculosis therapy, active against non-replicating Mycobacterium tuberculosis (Mtb). The conversion of PZA into pyrazinoic acid (POA), the active form, required the activity of pncA gene product pyrazinamidase (PZase) activity. Mutations occurred in pncA are the primary cause behind the PZA resistance. However, the resistance mechanism is important to explore using high throughput computational approaches. Here we aimed to explore the mechanism of PZA resistance behind novel P62T, L120R, and V130M mutations in PZase using 200 ns molecular dynamics (MD) simulations. MD simulations were performed to observe the structural changes for these three mutants (MTs) compared to the wild types (WT). Root means square fluctuation, the radius of gyration, free energy landscape, root means square deviation, dynamic cross-correlation motion, and pocket volume were found in variation between WT and MTs, revealing the effects of P62T, L120R, and V130M. The free energy conformational landscape of MTs differs significantly from the WT system, lowering the binding of PZA. The geometric shape complementarity of the drug (PZA) and target protein (PZase) further confirmed that P62T, L120R, and V130M affect the protein structure. These effects on PZase may cause vulnerability to convert PZA into POA.Communicated by Ramaswamy H. Sarma.

Design of siRNA Bioconjugates for Efficient Control of Cancer-Associated Membrane Receptors

Research on siRNA delivery has seen tremendous growth over the past few decades. As one of the major delivery strategies, siRNA bioconjugates offer the potential to enhance and extend the pharmacological properties of siRNAs while minimizing toxicity. In this paper, we suggest the development of a siRNA conjugate platform with peptides and proteins that are ligands of target receptors for cancer treatment. The siRNA bioconjugates target and block the receptor membrane proteins, enter the cells through receptor-mediated endocytosis, and inhibit the expression of that same target membrane receptor, thereby doubly controlling the function of the membrane proteins. The three kinds of bioconjugates targeting CD47, PD-L1, and EGFR were synthesized via two different copper-free click chemistry reactions. Results showed the cellular uptake of each conjugate, reduction of target gene expression, and efficient functional control of receptor proteins. This platform provides an effective approach for regulating membrane proteins in various diseases beyond cancer.

Active site determination of novel plant versatile peroxidase extracted from Citrus sinensis and bioconversion of β-naphthol

A ligninolytic peroxidase called versatile peroxidase, VP, (EC 1.11.1.16) is an iron-containing metalloenzyme. The most distinctive feature of this enzyme is its composite molecular framework, which combines lignin peroxidase's capacity to oxidize compounds with high-redox potential with manganese peroxidase's capacity to oxidize Mn2+ to Mn3+. In this study, we have extracted amino acid sequences from the Citrus sinensis source and subjected them to various computation tools to visualize the insight secondary and 3D structure, physicochemical properties, and validation of the structure which have not been studied so far to further investigate the catalytic efficiency and effectiveness of VP. The binding energies of HEME and HEME C (HEC) ligands with produced PDB (6rqf.1. A) have been also assessed, analyzed, and confirmed utilizing AutoDock. Binding energies were calculated using the AutoDock and validated by MD simulation using SCHRODINGER DESMOND. Most stable confirmation was achieved through a protein-ligand interaction study. Bio-technological use of VP in the biotransformation of β-naphthol has also been studied. The findings in the current study will have a substantial impact on proteomics, biochemistry, biotechnology, and possible uses of versatile peroxidase in the bio-remediation of different toxic organic compounds.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03758-x.

In silico guided screening of active components of C. lanceolata as 3-chymotrypsin-like protease inhibitors of novel coronavirus

Despite the intense worldwide efforts towards the identification of potential anti-CoV therapeutics, no antiviral drugs have yet been discovered. Numerous vaccines are now approved for use, but they all serve as preventative measures. To effectively treat viral infections, it is crucial to find new antiviral drugs that are derived from natural sources. Various compounds with potential activity against 3 chymotrypsin-like protease (3CLpro) were reported and some are validated by bioassay studies. Therefore, we performed the computational screening of phytoconstituents of Codonopsis lanceolata to search for potential antiviral hit candidates. The curated compounds of the plant C. lanceolata were collected and downloaded from the literature. The binding affinity of the curated datasets was predicted for the target 3CLpro. Stigmasterol exhibits the highest docking score for the 3CLpro target. In addition, molecular dynamics (MD) simulations were conducted for the validation of docking results using root mean square deviation and root mean square fluctuation plots. The MD results indicated that the docked complex was stable and retained hydrogen bonding and non-bonding interactions. Furthermore, the calculation of pharmacokinetic parameters and Lipinski's rule of five suggest that C. lanceolata has the potential for drug-likeness. In order to develop new medicines for this debilitating disease, we will focus on the primary virus-based and host-based targets that can direct medicinal chemists to identify novel treatments to produce new drugs for it.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03745-2.

3D based generative PROTAC linker design with reinforcement learning

Proteolysis targeting chimera (PROTAC), has emerged as an effective modality to selectively degrade disease-related proteins by harnessing the ubiquitin-proteasome system. Due to PROTACs' hetero-bifunctional characteristics, in which a linker joins a warhead binding to a protein of interest (POI), conferring specificity and a E3-ligand binding to an E3 ubiquitin ligase, this could trigger the ubiquitination and transportation of POI to the proteasome, followed by degradation. The rational PROTAC linker design is challenging due to its relatively large molecular weight and the complexity of maintaining the binding mode of warhead and E3-ligand in the binding pockets of counterpart. Conventional linker generation method can only generate linkers in either 1D SMILES or 2D graph, without taking into account the information of ternary structures. Here we propose a novel 3D linker generative model PROTAC-INVENT which can not only generate SMILES of PROTAC but also its 3D putative binding conformation coupled with the target protein and the E3 ligase. The model is trained jointly with the RL approach to bias the generation of PROTAC structures toward pre-defined 2D and 3D based properties. Examples were provided to demonstrate the utility of the model for generating reasonable 3D conformation of PROTACs. On the other hand, our results show that the associated workflow for 3D PROTAC conformation generation can also be used as an efficient docking protocol for PROTACs.

Identification of potential inhibitors against Alzheimer-related proteins in Cordyceps militaris ethanol extract: experimental evidence and computational analyses

Laboratory experiments were carried out to identify the chemical composition of Cordyceps militaris and reveal the first evidence of their Alzheimer-related potential. Liquid chromatography-mass spectrometry analysis identified 21 bioactive compounds in the ethanol extract (1-21). High-performance liquid chromatography quantified the content of cordycepin (0.32%). Bioassays revealed the overall anti-Alzheimer potential of the extract against acetylcholinesterase (IC50 = 115.9 ± 11.16 µg mL-1). Multi-platform computations were utilized to predict the biological inhibitory effects of its phytochemical components against Alzheimer-related protein structures: acetylcholinesterase (PDB-4EY7) and β-amyloid protein (PDB-2LMN). In particular, 7 is considered as a most effective inhibitor predicted by its chemical stability in dipole-based environments (ground state - 467.26302 a.u.; dipole moment 11.598 Debye), inhibitory effectiveness (DS ¯ - 13.6 kcal mol-1), polarized compatibility (polarizability 25.8 Å3; logP - 1.01), and brain penetrability (logBB - 0.244; logPS - 3.047). Besides, 3 is promising as a brain-penetrating agent (logBB - 0.257; logPS - 2.400). The results preliminarily suggest further experimental attempts to verify the pro-cognitive effects of l(-)-carnitine (7).

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03714-9.

Elucidation of Pharmacological Mechanism Underlying the Anti-Alzheimer's Disease Effects of Evodia rutaecarpa and Discovery of Novel Lead Molecules: An In Silico Study

Alzheimer's disease (AD) is a brain disease with a peculiarity of multiformity and an insidious onset. Multiple-target drugs, especially Chinese traditional medicine, have achieved a measure of success in AD treatment. Evodia rutaecarpa (Juss.) Benth. (Wuzhuyu, WZY, i.e., E. rutaecarpa), a traditional Chinese herb, has been identified as an effective drug to cure migraines. To our surprise, our in silico study showed that rather than migraines, Alzheimer's disease was the primary disease to which the E. rutaecarpa active compounds were targeted. Correspondingly, a behavioral experiment showed that E. rutaecarpa extract could improve impairments in learning and memory in AD model mice. However, the mechanism underlying the way that E. rutaecarpa compounds target AD is still not clear. For this purpose, we employed methods of pharmacology networking and molecular docking to explore this mechanism. We found that E. rutaecarpa showed significant AD-targeting characteristics, and alkaloids of E. rutaecarpa played the main role in binding to the key nodes of AD. Our research detected that E. rutaecarpa affects the pathologic development of AD through the serotonergic synapse signaling pathway (SLC6A4), hormones (PTGS2, ESR1, AR), anti-neuroinflammation (SRC, TNF, NOS3), transcription regulation (NR3C1), and molecular chaperones (HSP90AA1), especially in the key nodes of PTGS2, AR, SLCA64, and SRC. Graveoline, 5-methoxy-N, N-dimethyltryptamine, dehydroevodiamine, and goshuyuamide II in E. rutaecarpa show stronger binding affinities to these key proteins than currently known preclinical and clinical drugs, showing a great potential to be developed as lead molecules for treating AD.

Indole-based LpxC (UDP-3-O-(R-3-hydroxyacyl)-N-acetylglucosaminedeacetylase) inhibitors for Salmonella typhi: rational drug discovery through in silico screening

Salmonella typhi is an infectious bacteria that causes typhoid fever and poses a significant risk to human health. The emergence of antibiotic resistance has become a growing concern in the management of this disease. In this work, a structure-based drug design approach was used to identify inhibitors for zinc-dependent metalloamidase LpxC, the enzyme responsible for the biosynthesis of lipid A. Using an in silico approach (virtual screening, docking, and molecular dynamics (MD) simulations), from a library of 59,000 indole derivatives, we were able to identify promising lead molecules with high binding affinity to the LpxC. Of these, five molecules (compound 435 (CID: 12253558), compound 436 (CID: 122514279), compound 1812 (CID: 90797680), compound 2584 (CID: 57056726), and compound 2545 (CID: 59897361)) have passed all the filtering criteria. This finding was verified by molecular dynamics (MD) simulation as well as post-dynamics free energy calculations. The five compounds that have been identified have shown the most promise compared to other compounds that are already recognized. To further validate the positive outcome of this study, experimental validation and optimization are necessary. These lead compounds may help to develop new antibiotics for antibiotic-resistant Salmonella typhi and improve typhoid fever treatment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03699-5.

Evaluation of Antioxidant Activities from a Sustainable Source of Okara Protein Hydrolysate Using Enzymatic Reaction

Okara is a solid byproduct created during the processing of soy milk. The production of protein hydrolysates utilizing enzymatic tests such as papain can result in the production of bioactive peptides (BPs), which are amino acid sequences that can also be produced from the okara protein by hydrolysis. The objective of this study was to investigate the antioxidant activities of okara hydrolysates using papain, based on the in silico and in vitro assays using the papain enzyme. We found that using the in silico assessment, the antioxidant peptides can be found from the precursor (glycinin and conglycinin) in okara. When used as a protease, papain provides the maximum degree of hydrolysis for antioxidative peptides. The highest-peptide-rank peptide sequence was predicted using peptide ranks such as proline-histidine-phenylalanine (PHF), alanine-aspartic acid-phenylalanine (ADF), tyrosine-tyrosine-leucine (YYL), proline-histidine-histidine (PHH), isoleucine-arginine (IR), and serine-valine-leucine (SVL). Molecular docking studies revealed that all peptides generated from the parent protein impeded substrate access to the active site of xanthine oxidase (XO). They have antioxidative properties and are employed in the in silico approach to the XO enzyme. We also use papain to evaluate the antioxidant activity by using in vitro tests for protein hydrolysate following proteolysis. The antioxidant properties of okara protein hydrolysates have been shown in vitro, utilizing DPPH and FRAP experiments. This study suggests that okara hydrolysates generated by papain can be employed as natural antioxidants in food and for further applications, such as active ingredients for antioxidants in packaging.

Prediction and evaluation of deleterious and disease causing non-synonymous SNPs (nsSNPs) in human NF2 gene responsible for neurofibromatosis type 2 (NF2)

The majority of genetic variations in the human genome that lead to variety of different diseases are caused by non-synonymous single nucleotide polymorphisms (nsSNPs). Neurofibromatosis type 2 (NF2) is a deadly disease caused by nsSNPs in the NF2 gene that encodes for a protein called merlin. This study used various in silico methods, SIFT, Polyphen-2, PhD-SNP and MutPred, to investigate the pathogenic effect of 14 nsSNPs in the merlin FERM domain. The G197C and L234R mutations were found to be two deleterious and disease mutations associated with the mild and severe forms of NF2, respectively. Molecular dynamics (MD) simulations were conducted to understand the stability, structure and dynamics of these mutations. Both mutant structures experienced larger flexibility compared to the wildtype. The L234R mutant suffered from more prominent structural instability, which may help to explain why it is associated with the more severe form of NF2. The intramolecular hydrogen bonding in L234R mutation decreased from the wildtype, while intermolecular hydrogen bonding of L234R mutation with solvent greatly increased. The native contacts were also found to be important. Protein-protein docking revealed that L234R mutation decreased the binding complementarity and binding affinity of LATS2 to merlin, which may have an impact on merlin's ability to regulate the Hippo signaling pathway. The calculated binding affinity of the LATS2 to L234R mutant and wildtype merlin protein is found to be 21.73 and -11 kcal/mol, respectively. The binding affinity of the wildtype merlin agreed very well with the experimental value, -8 kcal/mol.Communicated by Ramaswamy H. Sarma.

Trehalose synthesis inhibitor: A molecular in silico drug design

Infectious diseases are serious public health problems, affecting a large portion of the world's population. A molecule that plays a key role in pathogenic organisms is trehalose and recently has been an interest in the metabolism of this molecule for drug development. The trehalose-6-phosphate synthase (TPS1) is an enzyme responsible for the biosynthesis of trehalose-6-phosphate (T6P) in the TPS1/TPS2 pathway, which results in the formation of trehalose. Studies carried out by our group demonstrated the inhibitory capacity of T6P in the TPS1 enzyme from Saccharomyces cerevisiae, preventing the synthesis of trehalose. By in silico techniques, we compiled sequences and experimentally determined structures of TPS1. Sequence alignments and molecular modeling were performed. The generated structures were submitted in validation of algorithms, aligned structurally and analyzed evolutionarily. Molecular docking methodology was applied to analyze the interaction between T6P and TPS1 and ADMET properties of T6P were analyzed. The results demonstrated the models created presented sequence and structural similarities with experimentally determined structures. With the molecular docking, a cavity in the protein surface was identified and the molecule T6P was interacting with the residues TYR-40, ALA-41, MET-42, and PHE-372, indicating the possible uncompetitive inhibition mechanism provided by this ligand, which can be useful in directing the molecular design of inhibitors. In ADMET analyses, T6P had acceptable risk values compared with other compounds from World Drug Index. Therefore, these results may present a promising strategy to explore to develop a broad-spectrum antibiotic of this specific target with selectivity, potency, and reduced side effects, leading to a new way to treat infectious diseases like tuberculosis and candidiasis.

Identification and structural characterization of deleterious non-synonymous single nucleotide polymorphisms in the human SKP2 gene

In SCF (Skp, Cullin, F-box) ubiquitin-protein ligase complexes, S-phase kinase 2 (SKP2) is one of the major players of F-box family, that is responsible for the degradation of several important cell regulators and tumor suppressor proteins. Despite of having significant evidence for the role of SKP2 on tumorgenesis, there is a lack of available data regarding the effect of non-synonymous polymorphisms. In this communication, the structural and functional consequences of non-synonymous single nucleotide polymorphisms (nsSNPs) of SKP2 have been reported by employing various computational approaches and molecular dynamics simulation. Initially, several computational tools like SIFT, PolyPhen-2, PredictSNP, I-Mutant 2.0 and ConSurf have been implicated in this study to explore the damaging SNPs. In total of 172 nsSNPs, 5 nsSNPs were identified as deleterious and 3 of them were predicted to be decreased the stability of protein. Guided from ConSurf analysis, P101L (rs761253702) and Y346C (rs755010517) were categorized as the highly conserved and functional disrupting mutations. Therefore, these mutations were subjected to three dimensional model building and molecular dynamics simulation study for the detailed structural consequences upon the mutations. The study revealed that P101L and Y346C mutations increased the flexibility and changed the structural dynamics. As both these mutations are located in the most functional regions of SKP2 protein, these computational insights might be helpful to consider these nsSNPs for wet-lab confirmatory analysis as well as in rationalizing future population based studies and structure based drug design against SKP2.

Prediction of a highly deleterious mutation E17K in AKT-1 gene: An in silico approach

The AKT1 (v-akt murine thymoma viral oncogene homologue 1) kinase is a member of most frequently activated proliferation and survival signaling pathway in cancer. Recently, hyperactivation of AKT1, due to functional point mutation in the pleckstrin homology (PH) domain of AKT1 gene, has been found to be associated with human colorectal, breast and ovarian cancer. Thus, considering its crucial role in cellular signaling pathway, a functional analysis of missense mutations of AKT1 gene was undertaken in this study. Twenty nine nsSNPs (non-synonymous single nucleotide polymorphism) within coding region of AKT1 gene were selected for our investigation and six SNPs were found to be deleterious by combinatorial predictions of various computational tools. RMSD values were calculated for the mutant models which predicted four substitutions (E17K, E319G, D32E and A255T) to be highly deleterious. The insight of the structural attribute was gained through analysis of, secondary structures, solvent accessibility and intermolecular hydrogen bond analysis which confirmed one missense mutation (E17K) to be highly deleterious nsSNPs. In conclusion, the investigated gene AKT1 has twenty nine SNPs in the coding region and through progressive analysis using different bioinformatics tools one highly deleterious SNP with rs121434592 was profiled. Thus, results of this study can pave a new platform to sort nsSNPs for several important regulatory genes that can be undertaken for the confirmation of their phenotype and their correlation with diseased status in case control studies.

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We have added a small portion of text in introduction part as per reviewers comment.

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We have added a schematic representation of methodology used (Fig. 1).

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We have added text in the discussion portion as per the comment of reviewer.

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We have also corrected the conclusion as per reviewer's comments.

In Silico Template Selection of Short Antimicrobial Peptide Viscotoxin for Improving Its Antimicrobial Efficiency in Development of Potential Therapeutic Drugs

Rapid increase in antibiotic resistance has posed a worldwide threat, due to increased mortality, morbidity, and expenditure caused by antibiotic-resistant microbes. Recent development of the antimicrobial peptides like viscotoxin (Vt) has been successfully comprehended as a substitute for classical antibiotics. A structurally stable peptide, Vt can enhance antimicrobial property and can be used for various developmental purposes. Thus, structural stability among the antimicrobial peptides, Vt A1 (3C8P), A2 (1JMN), A3 (1ED0), B (1JMP), and C (1ORL) of Viscus album was computationally analyzed. In specific, the static confirmation of VtA3 showed high number of intramolecular interactions, along with an increase in hydrophobicity than others comparatively. Further, conformational sampling was used to analyze various geometrical parameters such as root mean square deviation, root mean square fluctuation, radius of gyration, and ovality which also revealed the structural stability of VtA3. Moreover, the statistically validated contours of surface area, lipophilicity, and distance constraints of disulfide bonds also supported the priority of VtA3 with respect to stability. Finally, the functional activity of peptides was accessed by computing their free energy of membrane association and membrane interactions, which defined VtA3 as functionally stable. Currently, peptide-based antibiotics and nanoparticles have attracted the pharmaceutical industries for their potential therapeutic applications. Thereby, it is proposed that viscotoxin A3 (1ED0) could be used as a preeminent template for scaffolding potentially efficient antimicrobial peptide-based drugs and nanomaterials in future.

Biophysical Studies on HCV 1a NS3/4A Protease and Its Catalytic Triad in Wild Type and Mutants by the In Silico Approach

The hepatitis C virus (HCV), of the family flaviviridae, is one of the major causes of chronic liver diseases. Until the year 2012, HCV infections were treated using PEG-interferon and ribavirin combinations, which have a low cure rate and severe side effects. Currently, many direct-acting antivirals (DAAs) are available, e.g. protease inhibitors, NS5A and polymerase inhibitors. These drugs have proven to be efficient in interferon-free treatment combinations and capable of enhancing the cure rate to above 90 %. Unlike PEG-interferon and ribavirin combinations, DAAs select for resistance in HCV. The R155K mutation in the HCV was found to resist all the currently available protease inhibitors. Here, we studied biophysical parameters like pocket (cavity) geometries and stabilizing residues of HCV 1a NS3/4A protease in wild type and mutants. We also studied HCV 1a NS3/4A protease's catalytic residues: their accessibility, energy, flexibility and binding to Phase II oral protease inhibitor vedroprevir (GS-9451), and compared these parameters between wild type and mutant(s). All these studies were performed using various bioinformatics tools (e.g. Swiss-PdbViewer and Schrödinger's Maestro) and web servers (e.g. DoGSiteScorer, SRide, ASA-View, WHAT IF, elNémo, CABS-flex, PatchDock and PLIP). From our study, we found that introduction of R155K, A156T or D168A mutation to wild-type NS3/4A protease increases the pocket's volume, surface (in the R155K mutant, surface decreases), lipo surface and depth and decreases the number of stabilizing residues. Additionally, differences in catalytic residues' solvent accessibility, energy, root-mean-square deviation (RMSD) and flexibility between wild type and mutants might explain changes in the protease activity and the resistance to protease inhibitors.

In-silico Studies Show Potent Inhibition of HIV-1 Reverse Transcriptase Activity by a Herbal Drug

Acquired immunodeficiency syndrome (AIDS) is a life threatening disease of the human immune system caused by human immunodeficiency virus (HIV). Effective inhibition of reverse transcriptase activity is a prominent, clinically viable approach for the treatment of AIDS. Few non-nucleoside reverse transcriptase inhibitors (NNRTIs) have been approved by the United States Food and Drug Administration (US FDA) as drugs for AIDS. In order to enhance therapeutic options against AIDS we examined novel herbal compounds of 4-thiazolidinone and its derivatives that are known to have remarkable antiviral potency. Our molecular docking and simulation experiments have identified one such herbal molecule known as (5E)-3-(2-aminoethyl)-5-benzylidene-1, 3-thiazolidine-2,4-dione that may bind HIV-1RT with high affinity to cause noncompetitive inhibition. Results are also compared with other US FDA approved drugs. Long de novo simulations and docking study suggest that the ligand (5E)-3-(2-aminoethyl)-5-benzylidene-1, 3-thiazolidine-2,4-dione (CID: 1656714) has strong binding interactions with Asp113, Asp110, Asp185 and Asp186 amino acids, all of which belong to one or the other catalytic pockets of HIV-1RT. It is expected that these interactions could be critical in the inhibitory activity of the HIV-1RT. Therefore, this study provides an evidence for consideration of (5E)-3-(2-aminoethyl)-5-benzylidene-1, 3-thiazolidine-2,4-dione as a valuable natural molecule in the treatment and prevention of HIV-associated disorders.

Evidence of colorectal cancer-associated mutation in MCAK: a computational report

Computational prediction of disease-associated non-synonymous polymorphism (nsSNP) has provided a significant platform to filter out the pathological mutations from large pool of SNP datasets at a very low cost input. Several methodologies and complementary protocols have been previously implemented and has provided significant prediction results. Although the previously implicated prediction methods were capable of investigating the most likely deleterious nsSNPs, but due to the lack of genotype-phenotype association analysis, the prediction results lacked in accuracy level. In this work we implemented the computational compilation of protein conformational changes as well as the probable disease-associated phenotypic outcomes. Our result suggested E403K mutation in mitotic centromere-associated kinesin protein as highly damaging and showed strong concordance to the previously observed colorectal cancer mutations aggregation tendency and energy value changes. Moreover, the molecular dynamics simulation results showed major loss in conformation and stability of mutant N-terminal kinesin-like domain structure. The result obtained in this study will provide future prospect of computational approaches in determining the SNPs that may affect the native conformation of protein structure and lead to cancer-associated disorders.

Investigation of binding phenomenon of NSP3 and p130Cas mutants and their effect on cell signalling

Members of the novel SH2-containing protein (NSP3) and Crk-associated substrate (p130Cas) protein families form a multi-domain signalling platforms that mediate cell signalling process. We analysed the damaging consequences of three mutations, each from NSP3 (NSP3(L469R), NSP3(L623E), NSP3(R627E)) and p130Cas (p130Cas(F794R), p130Cas(L787E), p130Cas(D797R)) protein with respect to their native biological partners. Mutations depicted notable loss in interaction affinity towards their corresponding biological partners. NSP3(L469R) and p130Cas(D797R) mutations were predicted as most prominent in docking analysis. Molecular dynamics (MD) studies were conducted to evaluate structural consequences of most prominent mutation in NSP3 and p130Cas obtained from the docking analysis. MD analysis confirmed that mutation in NSP3(L469R) and p130Cas(D797R) showed significant structural deviation, changes in conformations and increased flexibility, which in turn affected the binding affinity with their biological partners. Moreover, the root mean square fluctuation has indicated a rise in fluctuation of residues involved in moderate interaction acquired between the NSP3 and p130Cas. It has significantly affected the binding interaction in mutant complexes. The results obtained in this work present a detailed overview of molecular mechanisms involved in the loss of cell signalling associated with NSP3 and p130Cas protein.

Development of pharmacophore similarity-based quantitative activity hypothesis and its applicability domain: applied on a diverse data-set of HIV-1 integrase inhibitors

Quantitative pharmacophore hypothesis combines the 3D spatial arrangement of pharmacophore features with biological activities of the ligand data-set and predicts the activities of geometrically and/or pharmacophoric similar ligands. Most pharmacophore discovery programs face difficulties in conformational flexibility, molecular alignment, pharmacophore features sampling, and feature selection to score models if the data-set constitutes diverse ligands. Towards this focus, we describe a ligand-based computational procedure to introduce flexibility in aligning the small molecules and generating a pharmacophore hypothesis without geometrical constraints to define pharmacophore space, enriched with chemical features necessary to elucidate common pharmacophore hypotheses (CPHs). Maximal common substructure (MCS)-based alignment method was adopted to guide the alignment of carbon molecules, deciphered the MCS atom connectivity to cluster molecules in bins and subsequently, calculated the pharmacophore similarity matrix with the bin-specific reference molecules. After alignment, the carbon molecules were enriched with original atoms in their respective positions and conventional pharmacophore features were perceived. Distance-based pharmacophoric descriptors were enumerated by computing the interdistance between perceived features and MCS-aligned 'centroid' position. The descriptor set and biological activities were used to develop support vector machine models to predict the activities of the external test set. Finally, fitness score was estimated based on pharmacophore similarity with its bin-specific reference molecules to recognize the best and poor alignments and, also with each reference molecule to predict outliers of the quantitative hypothesis model. We applied this procedure to a diverse data-set of 40 HIV-1 integrase inhibitors and discussed its effectiveness with the reported CPH model.

Computational investigation of cancer-associated molecular mechanism in Aurora A (S155R) mutation

Centrosomes are the key-regulating element of cell cycle progression. Aberrations in their functional mechanism lead to several cancer-related disorders. Aurora A protein is a centrosome-associated protein that regulates the centriole duplication and its abberations are associated with multiple cases of aneuploidy and cancer-related disorders. S155R mutation in Aurora A is reported to induce cancer like phenotype and disrupt its binding with TPX2 protein. In this study, we have demonstrated the structural consequences of Aurora A S155R mutation and the atomic changes that influenced the loss of TPX2-binding affinity. Docking and molecular dynamics simulation results suggested significant loss in atomic contacts between mutant Aurora A and TPX2 protein. Further, we observed a notable changes in conformation of mutant Aurora A-TPX2 docked complex as compared to the native. Loss of binding affinity rendered the TPX2 domain free which then induced unfolding in its coiled region and enabled the overall expansion of mutant complex as compared to the native. The significant outcomes obtained from this study will facilitate in future cancer researches and in developing the potent drug therapies.

Role of ELA region in auto-activation of mutant KIT receptor: a molecular dynamics simulation insight

KIT receptor is the prime target in gastrointestinal stromal tumor (GISTs) therapy. Second generation inhibitor, Sunitinib, binds to an inactivated conformation of KIT receptor and stabilizes it in order to prevent tumor formation. Here, we investigated the dynamic behavior of wild type and mutant D816H KIT receptor, and emphasized the extended A-loop (EAL) region (805-850) by conducting molecular dynamics simulation (∼100 ns). We analyzed different properties such as root mean square cutoff or deviation, root mean square fluctuation, radius of gyration, solvent-accessible surface area, hydrogen bonding network analysis, and essential dynamics. Apart from this, clustering and cross-correlation matrix approach was used to explore the conformational space of the wild type and mutant EAL region of KIT receptor. Molecular dynamics analysis indicated that mutation (D816H) was able to alter intramolecular hydrogen bonding pattern and affected the structural flexibility of EAL region. Moreover, flexible secondary elements, specially, coil and turns were dominated in EAL region of mutant KIT receptor during simulation. This phenomenon increased the movement of EAL region which in turn helped in shifting the equilibrium towards the active kinase conformation. Our atomic investigation of mutant KIT receptor which emphasized on EAL region provided a better insight into the understanding of Sunitinib resistance mechanism of KIT receptor and would help to discover new therapeutics for KIT-based resistant tumor cells in GIST therapy.

Relationship between a point mutation S97C in CK1δ protein and its affect on ATP-binding affinity

CK1δ (Casein kinase I isoform delta) is a member of CK1 kinase family protein that mediates neurite outgrowth and the function as brain-specific microtubule-associated protein. ATP binding kinase domain of CK1δ is essential for regulating several key cell cycle signal transduction pathways. Mutation in CK1δ protein is reported to cause cancers and affects normal brain development. S97C mutation in kinase domain of CK1δ protein has been involved to induce breast cancer and ductal carcinoma. We performed molecular docking studies to examine the effect of this mutation on its ATP-binding affinity. Further, we conducted molecular dynamics simulations to understand the structural consequences of S97C mutation over the kinase domain of CK1δ protein. Docking results indicated the loss of ATP-binding affinity of mutant structure, which were further rationalized by molecular dynamics simulations, where a notable loss in 3-D conformation of CK1δ kinase domain was observed in mutant as compared to native. Our results explained the underlying molecular mechanism behind the observed cancer associated phenotype caused by S97C mutation in CK1δ protein.

Drug resistance mechanism of PncA in Mycobacterium tuberculosis

Tuberculosis continues to be a global health threat. Pyrazinamide (PZA) is an important first-line drug in multidrug-resistant tuberculosis treatment. The emergence of strains resistant to PZA represents an important public health problem, as both first- and second-line treatment regimens include PZA. It becomes toxic to Mycobacterium tuberculosis when converted to pyrazinoic acid by the bacterial pyrazinamidase (PncA) enzyme. Resistance to PZA is caused mainly by the loss of enzyme activity by mutation, the mechanism of resistance is not completely understood. In our studies, we analysed three mutations (D8G, S104R and C138Y) of PncA which are involved in resistance towards PZA. Binding pocket analysis solvent accessibility analysis, molecular docking and interaction analysis were performed to understand the interaction behaviour of mutant enzymes with PZA. Molecular dynamics simulations were conducted to understand the three-dimensional (3D) conformational behaviour of native and mutants PncA. Our analysis clearly indicates that the mutation (D8G, S104R and C138Y) in PncA is responsible for rigid binding cavity which in turn abolishes conversion of PZA to its active form and is the sole reason for PZA resistance. Excessive hydrogen bonding between PZA binding cavity residues and their neighbouring residues are the reason of rigid binding cavity during simulation. We present an exhaustive analysis of the binding site flexibility and its 3D conformations that may serve as new starting points for structure-based drug design and helps the researchers to design new inhibitors with consideration of rigid criterion of binding residues due to mutation of this essential target. An animated Interactive 3D Complement (I3DC) is available in Proteopedia at http://proteopedia.org/w/Journal:JBSD:11.

Computational screening and molecular dynamics simulation of disease associated nsSNPs in CENP-E

Aneuploidy and chromosomal instability (CIN) are hallmarks of most solid tumors. Mutations in centroemere proteins have been observed in promoting aneuploidy and tumorigenesis. Recent studies reported that Centromere-associated protein-E (CENP-E) is involved in inducing cancers. In this study we investigated the pathogenic effect of 132 nsSNPs reported in CENP-E using computational platform. Y63H point mutation found to be associated with cancer using SIFT, Polyphen, PhD-SNP, MutPred, CanPredict and Dr. Cancer tools. Further we investigated the binding affinity of ATP molecule to the CENP-E motor domain. Complementarity scores obtained from docking studies showed significant loss in ATP binding affinity of mutant structure. Molecular dynamics simulation was carried to examine the structural consequences of Y63H mutation. Root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (R(g)), solvent accessibility surface area (SASA), energy value, hydrogen bond (NH Bond), eigenvector projection, trace of covariance matrix and atom density analysis results showed notable loss in stability for mutant structure. Y63H mutation was also shown to disrupt the native conformation of ATP binding region in CENP-E motor domain. Docking studies for remaining 18 mutations at 63rd residue position as well as other two computationally predicted disease associated mutations S22L and P69S were also carried to investigate their affect on ATP binding affinity of CENP-E motor domain. Our study provided a promising computational methodology to study the tumorigenic consequences of nsSNPs that have not been characterized and clear clue to the wet lab scientist.

In silico prediction of a disease-associated STIL mutant and its affect on the recruitment of centromere protein J (CENPJ)

Human STIL (SCL/TAL1 interrupting locus) protein maintains centriole stability and spindle pole localisation. It helps in recruitment of CENPJ (Centromere protein J)/CPAP (centrosomal P4.1-associated protein) and other centrosomal proteins. Mutations in STIL protein are reported in several disorders, especially in deregulation of cell cycle cascades. In this work, we examined the non-synonymous single nucleotide polymorphisms (nsSNPs) reported in STIL protein for their disease association. Different SNP prediction tools were used to predict disease-associated nsSNPs. Our evaluation technique predicted rs147744459 (R242C) as a highly deleterious disease-associated nsSNP and its interaction behaviour with CENPJ protein. Molecular modelling, docking and molecular dynamics simulation were conducted to examine the structural consequences of the predicted disease-associated mutation. By molecular dynamic simulation we observed structural consequences of R242C mutation which affects interaction of STIL and CENPJ functional domains. The result obtained in this study will provide a biophysical insight into future investigations of pathological nsSNPs using a computational platform.