Predicting the impact of single-nucleotide polymorphisms in CDK2-flavopiridol complex by molecular dynamics analysis

Marmesin and Marmelosin Interact with the Heparan Sulfatase-2 Active Site: Potential Mechanism for Phytochemicals from Bael Fruit Extract as Antitumor Therapeutics

Human heparan sulfatase-2 (HSULF-2) is an oncoprotein overexpressed in the surface of all types of tumor cells and its activity plays a critical role in cancer survival and progression. Our previous studies have shown that bael fruit extract, containing marmesin and marmelosin, inhibits the HSULF-2 activity and kills breast tumor cells, but the mechanism of these processes remains fairly known mainly because the HSULF-2's 3D structure is partially known. Herein, we aimed at providing an in silico molecular mechanism of the inhibition of human HSULF-2 by phytochemicals from bael fruit extract. Pharmacokinetic parameters of the main phytochemicals contained in the bael fruit extract, sequence-based 3D structure of human HSULF-2, and the interaction of bael fruit's phytochemicals with the enzyme active site was modeled, evaluated, and verified. Docking studies revealed marmesin and marmelosin as potential inhibitors with binding score -8.5 and -7.7 Kcal/mol; these results were validated using molecular dynamics simulations, which exhibited higher stability of the protein-ligand complexes. Taking together, with our earlier in vitro data, our computational analyses suggest that marmesin and marmelosin interact at the active site of HSULF-2 providing a potential mechanism for its inhibition and consequent antitumor activity by phytochemicals contained in the bael fruit extract.

Identification of natural inhibitor against L1 β-lactamase present in Stenotrophomonas maltophilia

Antibiotic resistance is threatening the medical industry in treating microbial infections. Many organisms are acquiring antibiotic resistance because of the continuous use of the same drug. Gram-negative organisms are developing multi-drug resistance properties (MDR) due to chromosomal level changes that occurred as a part of evolution or some intrinsic factors already present in the organism. Stenotrophomonas maltophilia falls under the category of multidrug-resistant organism. WHO has also urged to evaluate the scenario and develop new strategies for making this organism susceptible to otherwise resistant antibiotics. Using novel compounds as drugs can ameliorate the issue to some extent. The β-lactamase enzyme in the bacteria is responsible for inhibiting several drugs currently being used for treatment. This enzyme can be targeted to find an inhibitor that can inhibit the enzyme activity and make the organism susceptible to β-lactam antibiotics. Plants produce several secondary metabolites for their survival in adverse environments. Several phytoconstituents have antimicrobial properties and have been used in traditional medicine for a long time. The computational technologies can be exploited to find the best compound from many compounds. Virtual screening, molecular docking, and dynamic simulation methods are followed to get the best inhibitor for L1 β-lactamase. IMPPAT database is screened, and the top hit compounds are studied for ADMET properties. Finally, four compounds are selected to set for molecular dynamics simulation. After all the computational calculations, withanolide R is found to have a better binding and forms a stable complex with the protein. This compound can act as a potent natural inhibitor for L1 β-lactamase.

Development of pyrazolo[3,4-d]pyrimidin-4-one scaffold as novel CDK2 inhibitors: Design, synthesis, and biological evaluation

A series of pyrazolo[3,4-d]pyrimidin-4-one scaffold were designed and synthesized as novel CDK2 inhibitors. By analyzing the common motifs of various known inhibitors, the designed compounds 1 were virtually screen for their inhibitory activity by docking into the active pocket of CDK2. The influence of different substitutes on the docking results was investigated. A total of 15 pyrazolo[3,4-d]pyrimidin-4-ones 1 were synthesized by Paal-Knorr reaction, pyrimidine ring closure, bromination, Suzuki coupling reaction, amide formation and Knoevenagel condensation. The Cell Counting Kit-8 (CCK-8) was used to evaluate the inhibitory activity of pyrazolo[3,4-d]pyrimidin-4-ones 1 in the breast cancer cell line MCF-7 in vitro using Etoposide as a reference control substance. The screening results demonstrated that the designed compounds have significant antiproliferative activity, and compounds 1e and 1j were the most active compounds with IC₅₀ values of 10.79 μM and 10.88 μM, respectively, being better than that of Etoposide (IC₅₀ = 18.75 μM). The enzyme inhibition assay was carried out against CDK2, the results indicated that the compounds 1e and 1j significantly inhibited CDK2 with IC₅₀ values of 1.71 μM and 1.60 μM.

A study of genomic diversity in populations of Maharashtra, India, inferred from 20 autosomal STR markers

OBJECTIVE

This study was planned to evaluate the genetic diversity in the admixed and Teli (a Hindu caste) populations of Maharashtra, India using 20 autosomal Short Tandem Repeat (STR) genetic markers. We further investigated the genetic relatedness of the studied populations with other Indian populations.

RESULTS

The studied populations showed a wide range of observed heterozygosity viz. 0.690 to 0.918 for the admixed population and 0.696 to 0.942 for the Teli population. This might be due to the multi-directional gene flow. The admixed and Teli populations also showed a high degree polymorphism which ranged from 0.652 to 0.903 and 0.644 to 0.902, respectively. Their combined value of matching probability for all the studied loci was 4.29 × 10-25 and 5.01 × 10-24, respectively. The results of Neighbor-Joining tree and Principal Component Analysis showed that the studied populations clustered with the general populations of Jharkhand, UttarPradesh, Rajasthan and Central Indian States, as well as with the specific populations of Maharashtra (Konkanastha Brahmins) and Tamil Nadu (Kurmans). Overall, the obtained data showed a high degree of forensic efficacy and would be useful for forensic applications as well as genealogical studies.

Molecular docking and dynamics study of natural compound for potential inhibition of main protease of SARS-CoV-2

Newly emerged SARS-CoV-2 made recent pandemic situations across the globe is accountable for countless unwanted death and insufferable panic associated with co-morbidities among mass people. The scarcity of appropriate medical treatment and no effective vaccine or medicine against SARS-CoV-2 has turned the situation worst. Therefore, in this study, we made a deep literature review to enlist plant-derived natural compounds and considered their binding mechanism with the main protease of SARS-CoV-2 through combinatorial bioinformatics approaches. Among all, a total of 14 compounds were filtered where Carinol, Albanin, Myricetin were had better binding profile than the rest of the compounds with having binding energy of –8.476, –8.036, –8.439 kcal/mol, respectively. Furthermore, MM-GBSA calculations were also considered in this selection process to support docking studies. Besides, 100 ns molecular dynamics simulation endorsed the rigid nature, less conformational variation and binding stiffness. As this study, represents a perfect model for SARS-CoV-2 main protease inhibition through bioinformatics study, these potential drug candidates may assist the researchers to find a superior and effective solution against COVID-19 after future experiments.

Communicated by Ramaswamy Sarma

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.

Vitamin D receptor (VDR) non-synonymous single nucleotide polymorphisms (nsSNPs) affect the calcitriol drug response - A theoretical insight

Pharmacogenetics and pharmacogenomics have become presumptive with advancements in next-generation sequencing technology. In complex diseases, distinguishing the feasibility of pathogenic and neutral disease-causing variants is a time consuming and expensive process. Recent drug research and development processes mainly rely on the relationship between the genotype and phenotype through Single nucleotide polymorphisms (SNPs). The SNPs play an indispensable role in elucidating the individual's vulnerability to disease and drug response. The understanding of the interplay between these leads to the establishment of personalized medicine. In order to address this issue, we developed a computational pipeline of vitamin D receptor (VDR) for SNP centered study by application of elegant molecular docking and molecular dynamics simulation approaches. In a few SNPs the volume of the binding cavities has increased in mutant structures when compared to the wild type, indicating a weakening in interaction (699.1 ų in wild type Vs. 738.8 in Leu230Val, 820.7 ų in Arg247Leu). This also differently reflected in the H-bond interactions and binding free energies -169.93 kcal/mol (wild type) Vs -156.43 kcal/mol (R154W), -105.49 kcal/mol (R274L) in Leu230Val and Arg247Leu respectively. Although we could not find noteworthy changes in the binding free energies and binding pocket in the remaining mutations, the H-bond interactions made these SNPs deleterious. Thus, we further analyzed the H-bond interactions and distances using molecular dynamics (MD) simulation studies.

Investigating the Inhibitory Effect of Wortmannin in the Hotspot Mutation at Codon 1047 of PIK3CA Kinase Domain: A Molecular Docking and Molecular Dynamics Approach

Oncogenic mutations in phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha (PIK3CA) are the most frequently reported in association with various forms of cancer. Several studies have reported the significance of hotspot mutations in a catalytic subunit of PIK3CA in association with breast cancer. Mutations are frequently observed in the highly conserved region of the kinase domain (797-1068 amino acids) of PIK3CA are activating or gain-of-function mutations. Mutation in codon 1047 occurs in the C-terminal region of the kinase domain with histidine (H) replaced by arginine (R), lysine (L), and tyrosine (Y). Pathogenicity and protein stability predictors PhD-SNP, Align GVGD, HANSA, iStable, and MUpro classified H1047R as highly deleterious when compared to H1047L and H1047Y. To explore the inhibitory activity of Wortmannin toward PIK3CA, the three-dimensional structure of the mutant protein was determined using homology modeling followed by molecular docking and molecular dynamics analysis. Docking studies were performed for the three mutants and native with Wortmannin to measure the differences in their binding pattern. Comparative docking study revealed that H1047R-Wortmannin complex has a higher number of hydrogen bonds as well as the best binding affinity next to the native protein. Furthermore, 100 ns molecular dynamics simulation was initiated with the docked complexes to understand the various changes induced by the mutation. Though Wortmannin was found to nullify the effect of H1047R over the protein, further studies are required for designing a better compound. As SNPs are major genetic variations observed in disease condition, personalized medicine would provide enhanced drug therapy.

Analysing the Effect of Mutation on Protein Function and Discovering Potential Inhibitors of CDK4: Molecular Modelling and Dynamics Studies

The cyclin-dependent kinase 4 (CDK4)-cyclin D1 complex plays a crucial role in the transition from the G1 phase to S phase of the cell cycle. Among the CDKs, CDK4 is one of the genes most frequently affected by somatic genetic variations that are associated with various forms of cancer. Thus, because the abnormal function of the CDK4-cyclin D1 protein complex might play a vital role in causing cancer, CDK4 can be considered a genetically validated therapeutic target. In this study, we used a systematic, integrated computational approach to identify deleterious nsSNPs and predict their effects on protein-protein (CDK4-cyclin D1) and protein-ligand (CDK4-flavopiridol) interactions. This analysis resulted in the identification of possible inhibitors of mutant CDK4 proteins that bind the conformations induced by deleterious nsSNPs. Using computational prediction methods, we identified five nsSNPs as highly deleterious: R24C, Y180H, A205T, R210P, and R246C. From molecular docking and molecular dynamic studies, we observed that these deleterious nsSNPs affected CDK4-cyclin D1 and CDK4-flavopiridol interactions. Furthermore, in a virtual screening approach, the drug 5_7_DIHYDROXY_ 2_ (3_4_5_TRI HYDROXYPHENYL) _4H_CHROMEN_ 4_ONE displayed good binding affinity for proteins with the mutations R24C or R246C, the drug diosmin displayed good binding affinity for the protein with the mutation Y180H, and the drug rutin displayed good binding affinity for proteins with the mutations A205T and R210P. Overall, this computational investigation of the CDK4 gene highlights the link between genetic variation and biological phenomena in human cancer and aids in the discovery of molecularly targeted therapies for personalized treatment.

Integrating in silico prediction methods, molecular docking, and molecular dynamics simulation to predict the impact of ALK missense mutations in structural perspective

Over the past decade, advancements in next generation sequencing technology have placed personalized genomic medicine upon horizon. Understanding the likelihood of disease causing mutations in complex diseases as pathogenic or neutral remains as a major task and even impossible in the structural context because of its time consuming and expensive experiments. Among the various diseases causing mutations, single nucleotide polymorphisms (SNPs) play a vital role in defining individual's susceptibility to disease and drug response. Understanding the genotype-phenotype relationship through SNPs is the first and most important step in drug research and development. Detailed understanding of the effect of SNPs on patient drug response is a key factor in the establishment of personalized medicine. In this paper, we represent a computational pipeline in anaplastic lymphoma kinase (ALK) for SNP-centred study by the application of in silico prediction methods, molecular docking, and molecular dynamics simulation approaches. Combination of computational methods provides a way in understanding the impact of deleterious mutations in altering the protein drug targets and eventually leading to variable patient's drug response. We hope this rapid and cost effective pipeline will also serve as a bridge to connect the clinicians and in silico resources in tailoring treatments to the patients' specific genotype.