AIMC Topic: Proto-Oncogene Proteins c-mdm2

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Cyclic peptide structure prediction and design using AlphaFold2.

Nature communications May 21, 2025
Small cyclic peptides have gained significant traction as a therapeutic modality; however, the development of deep learning methods for accurately designing such peptides has been slow, mostly due to the lack of sufficiently large training sets. Here...
Deep Learning Computational Biology Models, Molecular Humans Drug Design Protein Conformation Proto-Oncogene Proteins c-mdm2 Kelch-Like ECH-Associated Protein 1 Amino Acid Sequence Peptides, Cyclic Crystallography, X-Ray
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Insights into the Interaction Mechanisms of Peptide and Non-Peptide Inhibitors with MDM2 Using Gaussian-Accelerated Molecular Dynamics Simulations and Deep Learning.

Molecules (Basel, Switzerland) Jul 18, 2024
Inhibiting MDM2-p53 interaction is considered an efficient mode of cancer treatment. In our current study, Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and binding free energy calculations were combined together to probe the bi...
Molecular Dynamics Simulation Hydrogen Bonding Binding Sites Peptides Deep Learning Protein Binding Protein Structure, Secondary Proto-Oncogene Proteins c-mdm2 Protein Structure, Tertiary
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Artificial Intelligence Approach to Find Lead Compounds for Treating Tumors.

The journal of physical chemistry letters Jul 22, 2019
It has been demonstrated that MMP13 enzyme is related to most cancer cell tumors. The world's largest traditional Chinese medicine database was applied to screen for structure-based drug design and ligand-based drug design. To predict drug activity, ...
Cyclin-Dependent Kinase 6 Databases, Pharmaceutical Matrix Metalloproteinase 13 Tumor Suppressor Protein p53 Binding Sites Proto-Oncogene Proteins c-mdm2 Proteins Databases, Protein Models, Molecular Mutation Ligands Proto-Oncogene Proteins c-bcl-2 Antineoplastic Agents Deep Learning Cyclin-Dependent Kinase Inhibitor p16 Algorithms Machine Learning Peptides Drug Design
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iSEE: Interface structure, evolution, and energy-based machine learning predictor of binding affinity changes upon mutations.

Proteins Dec 3, 2018
Quantitative evaluation of binding affinity changes upon mutations is crucial for protein engineering and drug design. Machine learning-based methods are gaining increasing momentum in this field. Due to the limited number of experimental data, using...
Machine Learning Protein Binding Protein Domains Proteins Models, Molecular Binding, Competitive Computational Biology Mutation Tumor Suppressor Protein p53 Proto-Oncogene Proteins c-mdm2 Evolution, Molecular Thermodynamics
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Control of Gene Regulatory Networks Using Bayesian Inverse Reinforcement Learning.

IEEE/ACM transactions on computational biology and bioinformatics Apr 26, 2018
Control of gene regulatory networks (GRNs) to shift gene expression from undesirable states to desirable ones has received much attention in recent years. Most of the existing methods assume that the cost of intervention at each state and time point,...
Bayes Theorem Models, Biological Tumor Suppressor Protein p53 Proto-Oncogene Proteins c-mdm2 Wnt-5a Protein Computational Biology Gene Expression Regulation, Neoplastic Models, Genetic Skin Neoplasms Gene Expression Profiling Gene Regulatory Networks Software Algorithms Melanoma Humans Machine Learning
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Integrative machine learning approach for identification of new molecular scaffold and prediction of inhibition responses in cancer cells using multi-omics data.

Briefings in functional genomics Jan 15, 2025
MDM2 (Mouse Double Minute 2), a fundamental governor of the p53 tumor suppressor pathway, has garnered significant attention as a favorable target for cancer therapy. Recent years have witnessed the development and synthesis of potent MDM2 inhibitors...
Proto-Oncogene Proteins c-mdm2 Molecular Docking Simulation Antineoplastic Agents Cell Line, Tumor Genomics Multiomics Gene Expression Regulation, Neoplastic Humans Machine Learning Neoplasms
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ASSOCIATION BETWEEN MURINE DOUBLE MINUTE 2 - T309G polymorphism and recurrence of hepatocellular carcinoma after surgical treatment.

Arquivos de gastroenterologia Dec 1, 2015
BACKGROUND: Discovery and incorporation of biomarker panels to cancer studies enabled the understanding of genetic variation and its interference in carcinogenesis at molecular level. The potential association between single nucleotide polymorphism (...
Neoplasm Recurrence, Local Aged, 80 and over Disease-Free Survival Polymorphism, Single Nucleotide Hepatectomy Male Humans Proto-Oncogene Proteins c-mdm2 Female Genotype Liver Neoplasms Middle Aged Retrospective Studies Risk Factors Treatment Outcome Carcinoma, Hepatocellular Aged Genetic Predisposition to Disease
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