Pub Date : 2020-01-01DOI: 10.1504/IJCBDD.2020.113829
Matthew Hayes, Derrick Mullins
{"title":"The minimum weight clique partition problem and its application to structural variant calling","authors":"Matthew Hayes, Derrick Mullins","doi":"10.1504/IJCBDD.2020.113829","DOIUrl":"https://doi.org/10.1504/IJCBDD.2020.113829","url":null,"abstract":"","PeriodicalId":13612,"journal":{"name":"Int. J. Comput. Biol. Drug Des.","volume":"282 1","pages":"475-487"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72568203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.1504/ijcbdd.2020.10033062
S. Chaudry, Waqar Hussain, N. Rasool
{"title":"Inhibitory role of selective phytochemicals against HIV-2 protease: a study of molecular docking, ADMET and DFT computations","authors":"S. Chaudry, Waqar Hussain, N. Rasool","doi":"10.1504/ijcbdd.2020.10033062","DOIUrl":"https://doi.org/10.1504/ijcbdd.2020.10033062","url":null,"abstract":"","PeriodicalId":13612,"journal":{"name":"Int. J. Comput. Biol. Drug Des.","volume":"25 1","pages":"390-414"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84600831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.1504/ijcbdd.2020.10033057
Rohini Kanagavelu, Shanthi Veerappapillai
{"title":"Identification of novel neuraminidase inhibitors through e-pharmacophore based virtual screening","authors":"Rohini Kanagavelu, Shanthi Veerappapillai","doi":"10.1504/ijcbdd.2020.10033057","DOIUrl":"https://doi.org/10.1504/ijcbdd.2020.10033057","url":null,"abstract":"","PeriodicalId":13612,"journal":{"name":"Int. J. Comput. Biol. Drug Des.","volume":"38 1","pages":"359-377"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87213298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.1504/IJCBDD.2020.113878
Maciej Pietrzak, G. Lozanski, M. Grever, L. Andritsos, J. Blachly, K. Rogers, M. Seweryn
{"title":"On the analysis of the human immunome via an information theoretical approach","authors":"Maciej Pietrzak, G. Lozanski, M. Grever, L. Andritsos, J. Blachly, K. Rogers, M. Seweryn","doi":"10.1504/IJCBDD.2020.113878","DOIUrl":"https://doi.org/10.1504/IJCBDD.2020.113878","url":null,"abstract":"","PeriodicalId":13612,"journal":{"name":"Int. J. Comput. Biol. Drug Des.","volume":"1 1","pages":"555-581"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83006000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-13DOI: 10.1504/ijcbdd.2019.10025245
K. M. Latha, G. Babu
GSK-3 has a prominent role in glucose uptake and was investigated using more specific, ATP-competitive GSK-3 inhibitors. This multifunctional kinase apart from the ability to phosphorylate glycogen synthase and regulate glucose metabolism was subsequently found to be a critical component in numerous cellular functions including regulation of different cell signalling, cell division, differentiation, proliferation and growth as well as apoptosis. In this work, we report molecular docking analysis of 2035 approved drugs from DrugBank database based on their potential to bind against type-2 diabetes protein target, GSK-3β. Molecular docking analysis revealed several new classes of drugs reported to exhibit inhibitory properties against GSK-3β. Out of 13 best drugs resulted from the analysis, top three (Venetoclax, Cobicistat and Atorvastatin) were selected based on consensus scoring using six scoring schemes such as MolDock score of Molegro, mcule, Pose&Rank, MTiAutoDock, DockThor and DSX respectively.
{"title":"A novel approach for identification of possible GSK-3β inhibitors using computational virtual screening analysis of drugs","authors":"K. M. Latha, G. Babu","doi":"10.1504/ijcbdd.2019.10025245","DOIUrl":"https://doi.org/10.1504/ijcbdd.2019.10025245","url":null,"abstract":"GSK-3 has a prominent role in glucose uptake and was investigated using more specific, ATP-competitive GSK-3 inhibitors. This multifunctional kinase apart from the ability to phosphorylate glycogen synthase and regulate glucose metabolism was subsequently found to be a critical component in numerous cellular functions including regulation of different cell signalling, cell division, differentiation, proliferation and growth as well as apoptosis. In this work, we report molecular docking analysis of 2035 approved drugs from DrugBank database based on their potential to bind against type-2 diabetes protein target, GSK-3β. Molecular docking analysis revealed several new classes of drugs reported to exhibit inhibitory properties against GSK-3β. Out of 13 best drugs resulted from the analysis, top three (Venetoclax, Cobicistat and Atorvastatin) were selected based on consensus scoring using six scoring schemes such as MolDock score of Molegro, mcule, Pose&Rank, MTiAutoDock, DockThor and DSX respectively.","PeriodicalId":13612,"journal":{"name":"Int. J. Comput. Biol. Drug Des.","volume":"18 1","pages":"312-331"},"PeriodicalIF":0.0,"publicationDate":"2019-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84195780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-10DOI: 10.1504/ijcbdd.2019.10025244
Arpita Devi
Runt-related transcription factors (RUNX) are a family of proteins expressed by RUNX genes. In mammals, there are three members in this family- RUNX1, RUNX2 and RUNX3. There is high sequence similarity in the three members. However, there is a presence of QA domain in the N-terminal of Runx2. The structural aspect of this domain has not been elucidated till now. Here, we model the structures RUNX1, RUNX2 and RUNX2 without the QA domain (RUNX2Δqa) from its N-terminal to DNA binding domain. It has been found that there is a significant difference in structure of RUNX2 and RUNX2Δqa. The structure of RUNX2Δqa resembles that of RUNX1. Also, RUNX2Δqa seems to bind to the consensus DNA sequence of RUNX1 with higher affinity than that of RUNX2. The presence of QA domain also decreases the affinity of Runx2 towards CBFbeta. Thus, we find that the QA domain structurally and functionally diverts RUNX2 from that of RUNX1.
{"title":"The unique QA domain of RUNX2 causes conformational change in the Runt DNA binding domain which may result in alteration in its function","authors":"Arpita Devi","doi":"10.1504/ijcbdd.2019.10025244","DOIUrl":"https://doi.org/10.1504/ijcbdd.2019.10025244","url":null,"abstract":"Runt-related transcription factors (RUNX) are a family of proteins expressed by RUNX genes. In mammals, there are three members in this family- RUNX1, RUNX2 and RUNX3. There is high sequence similarity in the three members. However, there is a presence of QA domain in the N-terminal of Runx2. The structural aspect of this domain has not been elucidated till now. Here, we model the structures RUNX1, RUNX2 and RUNX2 without the QA domain (RUNX2Δqa) from its N-terminal to DNA binding domain. It has been found that there is a significant difference in structure of RUNX2 and RUNX2Δqa. The structure of RUNX2Δqa resembles that of RUNX1. Also, RUNX2Δqa seems to bind to the consensus DNA sequence of RUNX1 with higher affinity than that of RUNX2. The presence of QA domain also decreases the affinity of Runx2 towards CBFbeta. Thus, we find that the QA domain structurally and functionally diverts RUNX2 from that of RUNX1.","PeriodicalId":13612,"journal":{"name":"Int. J. Comput. Biol. Drug Des.","volume":"1 1","pages":"303-311"},"PeriodicalIF":0.0,"publicationDate":"2019-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75603374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-10DOI: 10.1504/ijcbdd.2019.10025247
Monica Jha, P. Guzzi, P. Veltri, Swarup Roy
A group of functionally related genes constitutes a functional module taking part in similar biological activities. Such modules can be employed for the interpretation of biological and cellular processes or their involvement in associated diseases. Detection of such modules from gene expression data is a difficult task, but important from system biology point of view. Different module detectors have been proposed for a few decades with their relative merits and demerits. They can be broadly classified as Clustering, Bi-Clustering and Network based. In this work, we try to combine the merits of some of the selective module detectors picked from three types of module detectors. We perform a two-level ensemble by unifying the goodness of different module detectors. For our experimentation, we use RNAseq read counts as a measure of gene expression. We compare ensemble outcomes with state-of-the-art module detectors and observe a superior performance in comparison to them.
{"title":"Functional module extraction by ensembling the ensembles of selective module detectors","authors":"Monica Jha, P. Guzzi, P. Veltri, Swarup Roy","doi":"10.1504/ijcbdd.2019.10025247","DOIUrl":"https://doi.org/10.1504/ijcbdd.2019.10025247","url":null,"abstract":"A group of functionally related genes constitutes a functional module taking part in similar biological activities. Such modules can be employed for the interpretation of biological and cellular processes or their involvement in associated diseases. Detection of such modules from gene expression data is a difficult task, but important from system biology point of view. Different module detectors have been proposed for a few decades with their relative merits and demerits. They can be broadly classified as Clustering, Bi-Clustering and Network based. In this work, we try to combine the merits of some of the selective module detectors picked from three types of module detectors. We perform a two-level ensemble by unifying the goodness of different module detectors. For our experimentation, we use RNAseq read counts as a measure of gene expression. We compare ensemble outcomes with state-of-the-art module detectors and observe a superior performance in comparison to them.","PeriodicalId":13612,"journal":{"name":"Int. J. Comput. Biol. Drug Des.","volume":"53 1","pages":"345-361"},"PeriodicalIF":0.0,"publicationDate":"2019-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77361251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-10DOI: 10.1504/ijcbdd.2019.10025246
Surya Sukumaran, M. Haridas
Protein-carbohydrate recognition, an important form of inter-cell communication, plays promising role in biological events. Extensive studies were already done in areas of protein-carbohydrate recognition using legume lectins for drug targeting. In this study, an attempt was made to reveal the interaction homogeneity of carbohydrates and their comparative analysis of binding modes towards α and β monomers of Spatholobus parviflorus lectin (SPL). The sugars, based on their structural diversity in information coding were selected for virtual screening. Based on the glidescores, 20 sugars were screened and extra precision docking exercises were carried out to explore the variabilities in their binding affinities exhibited by SPL monomers. Among the sugars, raffinose exhibited highest affinity towards the α and β monomers. These alterations exhibited by α and β monomers may be due to its asymmetry in the pairing of subunits. This prediction, deciphered the in silico binding report of sugars with SPL, along with their inconsistency in binding with monomeric units.
{"title":"Asymmetric glycan recognition among α-β monomers of Spatholobus parviflorus lectin: an insilico insight","authors":"Surya Sukumaran, M. Haridas","doi":"10.1504/ijcbdd.2019.10025246","DOIUrl":"https://doi.org/10.1504/ijcbdd.2019.10025246","url":null,"abstract":"Protein-carbohydrate recognition, an important form of inter-cell communication, plays promising role in biological events. Extensive studies were already done in areas of protein-carbohydrate recognition using legume lectins for drug targeting. In this study, an attempt was made to reveal the interaction homogeneity of carbohydrates and their comparative analysis of binding modes towards α and β monomers of Spatholobus parviflorus lectin (SPL). The sugars, based on their structural diversity in information coding were selected for virtual screening. Based on the glidescores, 20 sugars were screened and extra precision docking exercises were carried out to explore the variabilities in their binding affinities exhibited by SPL monomers. Among the sugars, raffinose exhibited highest affinity towards the α and β monomers. These alterations exhibited by α and β monomers may be due to its asymmetry in the pairing of subunits. This prediction, deciphered the in silico binding report of sugars with SPL, along with their inconsistency in binding with monomeric units.","PeriodicalId":13612,"journal":{"name":"Int. J. Comput. Biol. Drug Des.","volume":"25 1","pages":"332-344"},"PeriodicalIF":0.0,"publicationDate":"2019-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89870595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-10DOI: 10.1504/ijcbdd.2019.10025248
A. Al-Zahrani
Inhibition of disease-related proteins by natural inhibitors revealed its efficiency and became a promising step in drug discovery. With hundreds of advanced web servers and software, it is possible to predict potential drug-target in order to reduce laboratory cost and time. In the current study, computational simulations were performed to investigate the possible role of teucrolivins, isolated from Teucrium oliverianum plant, as natural inhibitors against DP4 protein, which is related to type 2 diabetes. The docking results revealed that teucrolivin D showed higher binding affinities compared to the native inhibitor PF2 and other teucrolivins with the minimum binding energy of -144.16. Sitagliptin, vildagliptin and omarigliptin are antidiabetic drugs for inhibition of DP4 protein. They gave minimum binding energy of -120.19, -103.1 and -104.69 respectively, and showed a lower binding affinity compared to teucrolivin D. Evaluation of ADMET confirmed the capability of teucrolivin D as an effective inhibitor against DP4.
{"title":"The potential inhibitory role of teucrolivins against human dipeptidyl peptidase 4 protein as a promising strategy for treatment of type 2 diabetes","authors":"A. Al-Zahrani","doi":"10.1504/ijcbdd.2019.10025248","DOIUrl":"https://doi.org/10.1504/ijcbdd.2019.10025248","url":null,"abstract":"Inhibition of disease-related proteins by natural inhibitors revealed its efficiency and became a promising step in drug discovery. With hundreds of advanced web servers and software, it is possible to predict potential drug-target in order to reduce laboratory cost and time. In the current study, computational simulations were performed to investigate the possible role of teucrolivins, isolated from Teucrium oliverianum plant, as natural inhibitors against DP4 protein, which is related to type 2 diabetes. The docking results revealed that teucrolivin D showed higher binding affinities compared to the native inhibitor PF2 and other teucrolivins with the minimum binding energy of -144.16. Sitagliptin, vildagliptin and omarigliptin are antidiabetic drugs for inhibition of DP4 protein. They gave minimum binding energy of -120.19, -103.1 and -104.69 respectively, and showed a lower binding affinity compared to teucrolivin D. Evaluation of ADMET confirmed the capability of teucrolivin D as an effective inhibitor against DP4.","PeriodicalId":13612,"journal":{"name":"Int. J. Comput. Biol. Drug Des.","volume":"63 1","pages":"362-372"},"PeriodicalIF":0.0,"publicationDate":"2019-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80720386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-10DOI: 10.1504/ijcbdd.2019.10025251
V. Adarsh, A. Santhiagu
Resistance to existing drugs of tuberculosis bacteria demands an immediate requirement to develop effective new chemical entities acting on emerging targets. Seryl-tRNA synthetase (SerRS) is essential for the viability of Mycobacterium tuberculosis (MTB). In this study, we have attempted to develop the tertiary structure of SerRS through homology modelling and to elucidate the active site interactions of inhibitor compounds aided by docking. Homology modelling using PDB ID: '2DQ3: A' chain as template and validation of the model was carried out with Modeller V9.13 and SAVES online server respectively. About 1248 compounds from a putative kinase compound library of PubChem database found active in whole cell bioassay (AID2842) on MTB - H37Rv was used in docking studies using 'AutoDock'. Out of the tested molecules, nine showed docking scores ≤-10 kcal/mol with good drug-like properties were further subjected to molecular dynamics (MD) simulations and found three of the compounds have stable interactions.
{"title":"Identifying drug-like inhibitors of Mycobacterium tuberculosis H37Rv Seryl tRNA synthetase based on bioassay dataset: homology modelling, docking and molecular dynamics simulation","authors":"V. Adarsh, A. Santhiagu","doi":"10.1504/ijcbdd.2019.10025251","DOIUrl":"https://doi.org/10.1504/ijcbdd.2019.10025251","url":null,"abstract":"Resistance to existing drugs of tuberculosis bacteria demands an immediate requirement to develop effective new chemical entities acting on emerging targets. Seryl-tRNA synthetase (SerRS) is essential for the viability of Mycobacterium tuberculosis (MTB). In this study, we have attempted to develop the tertiary structure of SerRS through homology modelling and to elucidate the active site interactions of inhibitor compounds aided by docking. Homology modelling using PDB ID: '2DQ3: A' chain as template and validation of the model was carried out with Modeller V9.13 and SAVES online server respectively. About 1248 compounds from a putative kinase compound library of PubChem database found active in whole cell bioassay (AID2842) on MTB - H37Rv was used in docking studies using 'AutoDock'. Out of the tested molecules, nine showed docking scores ≤-10 kcal/mol with good drug-like properties were further subjected to molecular dynamics (MD) simulations and found three of the compounds have stable interactions.","PeriodicalId":13612,"journal":{"name":"Int. J. Comput. Biol. Drug Des.","volume":"42 1","pages":"373-402"},"PeriodicalIF":0.0,"publicationDate":"2019-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87889657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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