Intrinsically disordered proteins (IDPs) or intrinsically disordered regions have not fixed tertiary structure, but play key roles in signal regulation, molecule recognition, and drug target. However it is difficult to study the structure and function of IDPs by traditional experimental methods because of their diverse conformations. Limitations of current generic protein force fields were reported in the previous simulations of IDPs. We have also explored to overcome these limitations by developing precise force fields ff99IDPS and ff14IDPS to correct the dihedral distribution for eight disordered promoting residues, ff14IDPSFF, CHARMM36IDPSFF, OPLSIDPSFF, ff03CMAP force fields for all 20 naturally occurring amino acids, and ESFF1 force field for environmental specific residues to further improve the quality in the modeling of IDPs. Extensive tests of IDPs and unstructured short peptides show that the simulated Cα chemical shifts with the precise force field are in quantitative agreement with those from NMR experiment and are more accurate than the base generic force field. Furthermore, the simulation effectiveness is also higher than other force fields. These findings confirm that the newly developed precise force field can improve the conformer sampling of intrinsically disordered proteins.
Computer-aided drug design uses computational approaches to discover, develop, and analyze drugs and similar biologically active molecules. In our group, we used three dimension quantitative structure and activity relationship (3D-QSAR) combined with molecular docking, molecular dynamics simulation to research the molecular mechanism for HIV-1 protease, integrase, reverse Transcriptase, CCR5, respiratory syncytial virus fusion protein, and tumor, etc.
Z. Wu, H. Liu, L. Xu, H.F. Chen*, Y. Feng*. Algorithm-based Coevolution Network Identification Reveals Key Functional Sectors of the α/β Hydrolase Subfamilies. The FASEB Journal. 2020, 34:1983-1995.
Q. Li, R. Luo*, H.F. Chen*. Dynamical Important Residue Network (DIRN): Network Inference via Conformational Change. Bioinformatics. 2019, 35:4664–4670.
Y. Zhang, H. Liu, S. Yang, R. Luo*, H.F. Chen*. Well-balanced Force Field ff03CMAP for Folded and Disordered Proteins. J. Chem. Theory Comput. 2019,15:6769-6780.
W. Ye, T. Qian, H. Liu, R. Luo, H.F. Chen*. Allosteric Autoinhibition Pathway in Transcription Factor ERG: Dynamics Network and Mutant Experimental Evaluations. J. Chem. Inf. Model. 2017, 57:1153-1165 (Citation: 34).
D. Song, R. Luo, H.F. Chen*. The IDP-Specific Force Field ff14IDPSFF Improves the Conformer Sampling of Intrinsically Disordered Proteins. J. Chem. Inf. Model. 2017, 57:1166-1178 (Citation: 51).
W. Wang, W. Ye, C. Jiang, R. Luo, H.F. Chen*. New force field on modeling intrinsically disordered proteins. Chem. Biol. Drug Des. 2014, 84: 253-269 (citation: 56).
Z. Huang, L. Zhu, Y. Cao, G. Wu, X. Liu, Y. Chen, Q. Wang, T. Shi, Y. Zhao, Y. Wang, W. Li, Y. Li, H.F. Chen*, G. Chen, J. Zhang*. ASD: a comprehensive database of allosteric proteins and modulators. Nucleic Acids Res. 2011, 39: D663-D669 (Citation: 100).
H. Zhang, Z. Liu, Y. Sun, J. Zhu, S. Lu, X. Liu, Q. Huang,Y. Xie, H. Zhu, S. Dang, H.F. Chen, G. Zheng, Y. Li, Y. Kuang, J. Fei, S. Chen, Z. Chen, Z.G. Wang*. Rig-I regulates NF-κB activity through binding to Nf-κb13′-UTR mRNA. Proc. Natl. Acad. Sci. U. S. A. 2013, 110:6459-6464.