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An in silico approach to map the binding site of doxorubicin on hemoglobin.

ABSTRACT: Binding modalities of doxorubicin (DOX), a widely used antineoplastic anthracyline antibiotic with hemoglobin (Hb) have been studied. The protein and the ligand were prepared using CORINA and protonated with insight II. The best conformation was sought by employing GOLDV. Molecular modeling calculations showed that DOX binds Hb to a non-classical drug binding site. The alpha subunit of Hb has been assigned to posses the binding site for DOX with a binding affinity (Ka) = 16.98 x10(3) mol(-1). The interaction was found to be thermodynamically favorable (DeltaG degrees = -66.23 KJmol(-1)). The analysis of DOX binding site to Hb suggested that the types of interactions that contribute in this binding are hydrophobic contacts, hydrogen bonding and electrostatic interactions.

SUBMITTER: Khan SN

PROVIDER: S-EPMC2533059 | biostudies-literature | 2008 Jul

REPOSITORIES: biostudies-literature

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An in silico approach to map the binding site of doxorubicin on hemoglobin.

Khan Shahper Nazeer SN Khan Asad Ullah AU

Bioinformation 20080714 9

Binding modalities of doxorubicin (DOX), a widely used antineoplastic anthracyline antibiotic with hemoglobin (Hb) have been studied. The protein and the ligand were prepared using CORINA and protonated with insight II. The best conformation was sought by employing GOLDV. Molecular modeling calculations showed that DOX binds Hb to a non-classical drug binding site. The alpha subunit of Hb has been assigned to posses the binding site for DOX with a binding affinity (Ka) = 16.98 x10(3) mol(-1). Th ...[more]

PMID: 18795113

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Project description:BACKGROUND:Finding peptides with high binding affinity to Class I major histocompatibility complex (MHC-I) attracts intensive research, and it serves a crucial part of developing a better vaccine for precision medicine. Traditional methods cost highly for designing such peptides. The advancement of computational approaches reduces the cost of new drug discovery dramatically. Compared with flourishing computational drug discovery area, the immunology area lacks tools focused on in silico design for the peptides with high binding affinity. Attributed to the ever-expanding amount of MHC-peptides binding data, it enables the tremendous influx of deep learning techniques for modeling MHC-peptides binding. To leverage the availability of these data, it is of great significance to find MHC-peptides binding specificities. The binding motifs are one of the key components to decide the MHC-peptides combination, which generally refer to a combination of some certain amino acids at certain sites which highly contribute to the binding affinity. RESULT:In this work, we propose the Motif Activation Mapping (MAM) network for MHC-I and peptides binding to extract motifs from peptides. Then, we substitute amino acid randomly according to the motifs for generating peptides with high affinity. We demonstrated the MAM network could extract motifs which are the features of peptides of highly binding affinities, as well as generate peptides with high-affinities; that is, 0.859 for HLA-A*0201, 0.75 for HLA-A*0206, 0.92 for HLA-B*2702, 0.9 for HLA-A*6802 and 0.839 for Mamu-A1*001:01. Besides, its binding prediction result reaches the state of the art. The experiment also reveals the network is appropriate for most MHC-I with transfer learning. CONCLUSIONS:We design the MAM network to extract the motifs from MHC-peptides binding through prediction, which are proved to generate the peptides with high binding affinity successfully. The new peptides preserve the motifs but vary in sequences.

Dataset Information

An in silico approach to map the binding site of doxorubicin on hemoglobin.

Publications

An in silico approach to map the binding site of doxorubicin on hemoglobin.

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