sv.
- MeSH
- Protein Conformation MeSH
- Molecular Sequence Data MeSH
- Molecular Structure MeSH
- Protein Folding MeSH
- Publication type
- Periodical MeSH
- Conspectus
- Biochemie. Molekulární biologie. Biofyzika
- NML Fields
- biologie
- biochemie
... Contents -- Protein Structure -- Part 1 Basic Structural Principles -- 1. ... ... Motifs of Protein Structure -- Few general principles emerged from the first protein structure -- The ... ... for classification of protein structures -- Secondary structure elements are connected into simple motifs ... ... 62 -- The retinol-binding protein belongs to a superfamily of protein structures 62 -- Retinol binding ... ... Prediction, Engineering, and Design of -- Protein Structures 247 -- Prediction of protein structure from ...
xv, 302 stran : ilustrace ; 28 cm
- Conspectus
- Biochemie. Molekulární biologie. Biofyzika
- NML Fields
- biochemie
- molekulární biologie, molekulární medicína
The most accredited hypothesis links the toxicity of amyloid proteins to their harmful effects on membrane integrity through the formation of prefibrillar-transient oligomers able to disrupt cell membranes. However, damage mechanisms necessarily assume a first step in which the amyloidogenic protein transfers from the aqueous phase to the membrane hydrophobic core. This determinant step is still poorly understood. However, according to our lipid-chaperon hypothesis, free lipids in solution play a crucial role in facilitating this footfall. Free phospholipid concentration in the aqueous phase acts as a switch between ion channel-like pore and fibril formation, so that high free lipid concentration in solution promotes pore and repress fibril formation. Conversely, low free lipids in the solution favor fibril and repress pore formation. This behavior is due to the formation of stable lipid-protein complexes. Here, we hypothesize that the helix propensity is a fundamental requirement to fulfill the lipid-chaperon model. The alpha-helix region seems to be responsible for the binding with amphiphilic molecules fostering the proposed mechanism. Indeed, our results show the dependency of protein-lipid binding from the helical structure presence. When the helix content is substantially lower than the wild type, the contact probability decreases. Instead, if the helix is broadening, the contact probability increases. Our findings open a new perspective for in silico screening of secondary structure-targeting drugs of amyloidogenic proteins.
- MeSH
- Amyloidogenic Proteins chemistry genetics MeSH
- Hydrophobic and Hydrophilic Interactions MeSH
- Protein Conformation, alpha-Helical MeSH
- Humans MeSH
- Drug Design * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
... Contents -- Preface xi -- 1 Introduction to Protein Engineering 1 -- Jeffrey L. Cleland, Andrew J. ... ... Craik -- 2 Protein Conformation 33 -- Fred E. Cohen and David P. ... ... Hearst -- 3 Predicting the Conformation of Proteins from Sequence Data 71 -- Steven A. ... ... on Protein Folding: Methodology, Application, and Interpretation 249 -- Mark R. ... ... Structure-Function Relationships for Protein Design 317 -- Craig S. ...
x, 518 s. : il.
Most of the available crystal structures of epidermal growth factor receptor (EGFR) kinase domain, bound to drug inhibitors, originated from ligand-based drug design studies. Here, we used variations in 110 crystal structures to assemble eight distinct families highlighting the C-helix orientation in the N-lobe of the EGFR kinase domain. The families shared similar mutational profiles and similarity in the ligand R-groups (chemical composition, geometry, and charge) facing the C-helix, mutation sites, and DFG domain. For structure-based drug design, we recommend a systematic decision-making process for choice of template, guided by appropriate pairwise fitting and clustering before the molecular docking step. Alternatively, the binding site shape/volume can be used to filter and select the compound libraries.
- MeSH
- ErbB Receptors antagonists & inhibitors chemistry genetics MeSH
- Protein Kinase Inhibitors pharmacology MeSH
- Humans MeSH
- Ligands MeSH
- Mutation MeSH
- Drug Design methods MeSH
- Decision Making MeSH
- Molecular Docking Simulation MeSH
- Binding Sites MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Review MeSH
The human 5'(3')-deoxyribonucleotidases catalyze the dephosphorylation of deoxyribonucleoside monophosphates to the corresponding deoxyribonucleosides and thus help to maintain the balance between pools of nucleosides and nucleotides. Here, the structures of human cytosolic deoxyribonucleotidase (cdN) at atomic resolution (1.08 Å) and mitochondrial deoxyribonucleotidase (mdN) at near-atomic resolution (1.4 Å) are reported. The attainment of an atomic resolution structure allowed interatomic distances to be used to assess the probable protonation state of the phosphate anion and the side chains in the enzyme active site. A detailed comparison of the cdN and mdN active sites allowed the design of a cdN-specific inhibitor.
- MeSH
- Cytosol chemistry enzymology MeSH
- Deoxyribonucleotides chemistry MeSH
- Escherichia coli genetics metabolism MeSH
- Eukaryotic Cells chemistry enzymology MeSH
- Phosphates chemistry MeSH
- Enzyme Inhibitors chemistry MeSH
- Isoenzymes antagonists & inhibitors chemistry genetics MeSH
- Catalytic Domain MeSH
- Protein Conformation MeSH
- Crystallography, X-Ray MeSH
- Humans MeSH
- Mitochondria chemistry enzymology MeSH
- Models, Molecular MeSH
- Nucleotidases antagonists & inhibitors chemistry genetics MeSH
- Organophosphonates chemistry MeSH
- Organ Specificity MeSH
- Drug Design MeSH
- Recombinant Proteins chemistry genetics MeSH
- Molecular Docking Simulation MeSH
- Structure-Activity Relationship MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Recent advancements in deep learning and generative models have significantly expanded the applications of virtual screening for drug-like compounds. Here, we introduce a multitarget transformer model, PCMol, that leverages the latent protein embeddings derived from AlphaFold2 as a means of conditioning a de novo generative model on different targets. Incorporating rich protein representations allows the model to capture their structural relationships, enabling the chemical space interpolation of active compounds and target-side generalization to new proteins based on embedding similarities. In this work, we benchmark against other existing target-conditioned transformer models to illustrate the validity of using AlphaFold protein representations over raw amino acid sequences. We show that low-dimensional projections of these protein embeddings cluster appropriately based on target families and that model performance declines when these representations are intentionally corrupted. We also show that the PCMol model generates diverse, potentially active molecules for a wide array of proteins, including those with sparse ligand bioactivity data. The generated compounds display higher similarity known active ligands of held-out targets and have comparable molecular docking scores while maintaining novelty. Additionally, we demonstrate the important role of data augmentation in bolstering the performance of generative models in low-data regimes. Software package and AlphaFold protein embeddings are freely available at https://github.com/CDDLeiden/PCMol.
- MeSH
- Protein Conformation MeSH
- Ligands MeSH
- Models, Molecular * MeSH
- Proteins * chemistry metabolism MeSH
- Drug Design * MeSH
- Publication type
- Journal Article MeSH
AlphaFold is an artificial intelligence approach for predicting the three-dimensional (3D) structures of proteins with atomic accuracy. One challenge that limits the use of AlphaFold models for drug discovery is the correct prediction of folding in the absence of ligands and cofactors, which compromises their direct use. We have previously described the optimization and use of the histone deacetylase 11 (HDAC11) AlphaFold model for the docking of selective inhibitors such as FT895 and SIS17. Based on the predicted binding mode of FT895 in the optimized HDAC11 AlphaFold model, a new scaffold for HDAC11 inhibitors was designed, and the resulting compounds were tested in vitro against various HDAC isoforms. Compound 5a proved to be the most active compound with an IC50 of 365 nM and was able to selectively inhibit HDAC11. Furthermore, docking of 5a showed a binding mode comparable to FT895 but could not adopt any reasonable poses in other HDAC isoforms. We further supported the docking results with molecular dynamics simulations that confirmed the predicted binding mode. 5a also showed promising activity with an EC50 of 3.6 μM on neuroblastoma cells.
- MeSH
- Histone Deacetylases * metabolism MeSH
- Histone Deacetylase Inhibitors * pharmacology chemistry chemical synthesis MeSH
- Humans MeSH
- Molecular Structure MeSH
- Cell Line, Tumor MeSH
- Neuroblastoma * drug therapy pathology MeSH
- Antineoplastic Agents * pharmacology chemistry chemical synthesis MeSH
- Drug Design * MeSH
- Molecular Dynamics Simulation MeSH
- Molecular Docking Simulation MeSH
- Artificial Intelligence MeSH
- Dose-Response Relationship, Drug MeSH
- Structure-Activity Relationship MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Recent years witnessed rapid expansion of our knowledge about structural features of human glutamate carboxypeptidase II (GCPII). There are over thirty X-ray structures of human GCPII (and of its close ortholog GCPIII) publicly available at present. They include structures of ligand-free wild-type enzymes, complexes of wild-type GCPII/GCPIII with structurally diversified inhibitors as well as complexes of the GCPII(E424A) inactive mutant with several substrates. Combined structural data were instrumental for elucidating the catalytic mechanism of the enzyme. Furthermore the detailed knowledge of the GCPII architecture and protein-inhibitor interactions offers mechanistic insight into structure-activity relationship studies and can be exploited for the rational design of novel GCPII-specific compounds. This review presents a summary of structural information that has been gleaned since 2005, when the first GCPII structures were solved.
- MeSH
- Glutamate Carboxypeptidase II antagonists & inhibitors chemistry genetics metabolism MeSH
- Enzyme Inhibitors chemistry pharmacology MeSH
- Protein Conformation MeSH
- Crystallography, X-Ray MeSH
- Humans MeSH
- Models, Molecular MeSH
- Polymorphism, Genetic MeSH
- Drug Design MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Review MeSH
