Pharmacophore Optimization and Design of Competitive Inhibitors of Thymidine Monophosphate Kinase Through Molecular Modeling Studies
A series of N1‐(4‐substituted‐benzyl)‐pyrimidines were subjected to 2D and 3D quantitative structure–activity relationship analyses. Statistically significant models were generated, and the most robust model for 2D quantitative structure–activity relationship was obtained using simulated annealing‐m...
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| Published in | Chemical biology & drug design Vol. 78; no. 5; pp. 826 - 834 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Oxford, UK
Blackwell Publishing Ltd
01.11.2011
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| Subjects | |
| Online Access | Get full text |
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| Abstract | A series of N1‐(4‐substituted‐benzyl)‐pyrimidines were subjected to 2D and 3D quantitative structure–activity relationship analyses. Statistically significant models were generated, and the most robust model for 2D quantitative structure–activity relationship was obtained using simulated annealing‐multiple linear regression. The physicochemical descriptors, viz., slogp, estate descriptors like SaaCHE index and SdsCHE index contribute significantly to the biological activity. The pharmacophore requirements for selective inhibition of Mycobacterium tuberculosis thymidine monophosphate kinase were optimized using the information derived from 2D and 3D quantitative structure–activity relationship studies. With the results from the studies, we have designed new chemical entities using the CombiLib Tool of V‐Life Molecular Design Suite. In addition, using structure‐based drug design, the distances between interacting groups of ligands and amino acid residues of the protein Mycobacterium tuberculosis thymidine monophosphate kinase (PDB ID:1W2H) were thoroughly analyzed. Thus, we have successfully replaced the sugar moiety with substituted aromatic ring on N1 of thymidine. Thorough studies on substitution pattern around pyrimidine ring were carried out.
The pharmacophore requirements for selective inhibition of Mycobacterium tuberculosis thymidine monophosphate kinase (TMPKmt) were optimized using molecular modelling studies. |
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| AbstractList | A series of N
1
‐(4‐substituted‐benzyl)‐pyrimidines were subjected to 2D and 3D quantitative structure–activity relationship analyses. Statistically significant models were generated, and the most robust model for 2D quantitative structure–activity relationship was obtained using simulated annealing‐multiple linear regression. The physicochemical descriptors, viz., slogp, estate descriptors like SaaCHE index and SdsCHE index contribute significantly to the biological activity. The pharmacophore requirements for selective inhibition of
Mycobacterium tuberculosis
thymidine monophosphate kinase were optimized using the information derived from 2D and 3D quantitative structure–activity relationship studies. With the results from the studies, we have designed new chemical entities using the C
ombi
L
ib
Tool of V‐Life Molecular Design Suite. In addition, using structure‐based drug design, the distances between interacting groups of ligands and amino acid residues of the protein
Mycobacterium tuberculosis
thymidine monophosphate kinase (PDB ID:1W2H) were thoroughly analyzed. Thus, we have successfully replaced the sugar moiety with substituted aromatic ring on N1 of thymidine. Thorough studies on substitution pattern around pyrimidine ring were carried out. A series of N1‐(4‐substituted‐benzyl)‐pyrimidines were subjected to 2D and 3D quantitative structure–activity relationship analyses. Statistically significant models were generated, and the most robust model for 2D quantitative structure–activity relationship was obtained using simulated annealing‐multiple linear regression. The physicochemical descriptors, viz., slogp, estate descriptors like SaaCHE index and SdsCHE index contribute significantly to the biological activity. The pharmacophore requirements for selective inhibition of Mycobacterium tuberculosis thymidine monophosphate kinase were optimized using the information derived from 2D and 3D quantitative structure–activity relationship studies. With the results from the studies, we have designed new chemical entities using the CombiLib Tool of V‐Life Molecular Design Suite. In addition, using structure‐based drug design, the distances between interacting groups of ligands and amino acid residues of the protein Mycobacterium tuberculosis thymidine monophosphate kinase (PDB ID:1W2H) were thoroughly analyzed. Thus, we have successfully replaced the sugar moiety with substituted aromatic ring on N1 of thymidine. Thorough studies on substitution pattern around pyrimidine ring were carried out. The pharmacophore requirements for selective inhibition of Mycobacterium tuberculosis thymidine monophosphate kinase (TMPKmt) were optimized using molecular modelling studies. A series of N(1) -(4-substituted-benzyl)-pyrimidines were subjected to 2D and 3D quantitative structure-activity relationship analyses. Statistically significant models were generated, and the most robust model for 2D quantitative structure-activity relationship was obtained using simulated annealing-multiple linear regression. The physicochemical descriptors, viz., slogp, estate descriptors like SaaCHE index and SdsCHE index contribute significantly to the biological activity. The pharmacophore requirements for selective inhibition of Mycobacterium tuberculosis thymidine monophosphate kinase were optimized using the information derived from 2D and 3D quantitative structure-activity relationship studies. With the results from the studies, we have designed new chemical entities using the CombiLib Tool of V-Life Molecular Design Suite. In addition, using structure-based drug design, the distances between interacting groups of ligands and amino acid residues of the protein Mycobacterium tuberculosis thymidine monophosphate kinase (PDB ID:1W2H) were thoroughly analyzed. Thus, we have successfully replaced the sugar moiety with substituted aromatic ring on N1 of thymidine. Thorough studies on substitution pattern around pyrimidine ring were carried out. |
| Author | Chitre, Trupti S. Kathiravan, Muthu K. Bothara, Kailash G. Jalnapurkar, Rajeshwar R. Bhandari, Shashikant V. |
| Author_xml | – sequence: 1 givenname: Trupti S. surname: Chitre fullname: Chitre, Trupti S. email: drugdesign2@gmail.com organization: Department of Pharmaceutical Chemistry (PG), AISSMS College of Pharmacy, Near RTO, Kennedy Road, Pune 411001, Maharashtra, India – sequence: 2 givenname: Muthu K. surname: Kathiravan fullname: Kathiravan, Muthu K. organization: Department of Pharmaceutical Chemistry, Sinhgad College of Pharmacy, Vadgaon (Bk) Pune 411041, Maharashtra, India – sequence: 3 givenname: Kailash G. surname: Bothara fullname: Bothara, Kailash G. organization: Department of Pharmaceutical Chemistry (PG), AISSMS College of Pharmacy, Near RTO, Kennedy Road, Pune 411001, Maharashtra, India – sequence: 4 givenname: Shashikant V. surname: Bhandari fullname: Bhandari, Shashikant V. organization: Department of Pharmaceutical Chemistry (PG), AISSMS College of Pharmacy, Near RTO, Kennedy Road, Pune 411001, Maharashtra, India – sequence: 5 givenname: Rajeshwar R. surname: Jalnapurkar fullname: Jalnapurkar, Rajeshwar R. organization: Department of Pharmaceutical Chemistry (PG), AISSMS College of Pharmacy, Near RTO, Kennedy Road, Pune 411001, Maharashtra, India |
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| CitedBy_id | crossref_primary_10_1080_07391102_2023_2227711 crossref_primary_10_1016_j_compbiolchem_2017_03_015 crossref_primary_10_1080_10799893_2020_1794004 crossref_primary_10_1016_j_medidd_2021_100108 crossref_primary_10_1016_j_chemolab_2015_06_016 crossref_primary_10_1016_j_jksus_2024_103220 crossref_primary_10_1002_cmdc_201200339 crossref_primary_10_2174_1381612826666200403114152 crossref_primary_10_2174_1570180819666220414102310 crossref_primary_10_1002_cem_3189 crossref_primary_10_1080_07391102_2023_2262594 crossref_primary_10_2174_1570180819666220509103648 crossref_primary_10_1080_10799893_2020_1742740 crossref_primary_10_14233_ajchem_2023_27263 crossref_primary_10_1080_07391102_2024_2309644 |
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| Snippet | A series of N1‐(4‐substituted‐benzyl)‐pyrimidines were subjected to 2D and 3D quantitative structure–activity relationship analyses. Statistically significant... A series of N(1) -(4-substituted-benzyl)-pyrimidines were subjected to 2D and 3D quantitative structure-activity relationship analyses. Statistically... A series of N 1 ‐(4‐substituted‐benzyl)‐pyrimidines were subjected to 2D and 3D quantitative structure–activity relationship analyses. Statistically... |
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| SubjectTerms | 2D quantitative structure-activity relationship 3D quantitative structure-activity relationship Binding Sites Computer Simulation docking Drug Design Enzyme Inhibitors - chemistry Enzyme Inhibitors - pharmacology LeadGrow Models, Molecular Mycobacterium tuberculosis - drug effects Mycobacterium tuberculosis - enzymology Mycobacterium tuberculosis thymidine monophosphate kinase new chemical entities Nucleoside-Phosphate Kinase - antagonists & inhibitors Nucleoside-Phosphate Kinase - metabolism pharmacophore optimization Pyrimidines - chemistry Quantitative Structure-Activity Relationship |
| Title | Pharmacophore Optimization and Design of Competitive Inhibitors of Thymidine Monophosphate Kinase Through Molecular Modeling Studies |
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