Senior Research Scientist
Ph.D., University of Illinois at Urbana-Champaign, 2003
Center for the Study of Systems Biology
950 Atlantic Drive, Room 2147
Atlanta GA, 30332, Mail Code: 2000
Tel: (404) 407-8988
Fax: (404) 385-7478
mu.gao@gatech.edu
Research Interests
- Protein-DNA, Protein-RNA, protein-protein interactions
- Protein structure/function prediction and design
- Macromolecular assembly
- Molecular dynamics simulations
- Mechanobiology
- Drug discovery
My Google Scholar Profile
Publications
von Beck, T, Navarrete K, Arce N A, Gao, M, Dale G A, Davis-Gardner M E, Floyd K, Hernandez L M, Mullick N, Vanderheiden A, Skountzou I, Kuchipudi S V, Saravanan R, Li R, Skolnick J, Suthar M S, Jacob J. A wild boar cathelicidin peptide derivative inhibits severe acute respiratory syndrome coronavirus-2 and its drifted variants. Scientific Reports 2023: 13: 14650. https://doi.org/10.1038/s41598-023-41850-7. PDF
Davidson, R, Coletti M, Gao, M, Piatkowski B, Sreedasyam A, Quadir F, Weston D J, Schmutz, J, Cheng J, Skolnick J, Parks J, Sedova A. 2023. Predicted structural proteome of Sphagnum divinum and annotation with proteome-scale structural alignment. Bioinformatics 39(8): btad511. https://doi.org/10.1093/bioinformatics/btad511. PDF
Gao, M, Nakajima An D, Skolnick J. 2022. Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria. eLife 11:e82885. https://doi.org/10.7554/eLife.82885. PDF
Gao, M, Nakajima An D, Skolnick J. 2022. Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria. bioRxiv 2022.08.25.505253; doi: https://doi.org/10.1101/2022.08.25.505253. PDF
*This article is a preprint and has not been certified by peer review.
Gao, M, Nakajima An D, Parks J M, Skolnick J. 2022. AF2Compex Predicts direct physical interactions in multimeric proteins with deep learning. Nat Commun. 13, 1774. doi.org/10.1038/s41467-022-29394-2. PDF
Gao, M, Nakajima An D, Parks J M, Skolnick J. 2021. Predicting direct physical interactions in multimeric proteins with deep learning. bioRxiv 2021.11.09.467949; doi: https://doi.org/10.1101/2021.11.09.467949. PDF
*This article is a preprint and has not been certified by peer review.
Skolnick, J, Gao M, Zhou H, Singh S. 2021. AlphaFold 2: Why it works and its implications for understanding the relationships of protein sequence, structure and function. J. Chem. Inf. Model. 61: 10: 4827-4831. doi: 10.1021/acs.jcim.1c01114 PDF
Gao, M, Lund-Andersen P, Morehead A, Mahmud S, Chen C, Chen X, Giri N, Roy R S, Quadir F, Effler T C, Prout R, Abraham S, Skolnick J, Cheng J, Sedova A. 2021. High-Performance Deep Learning Toolbox for Genome-Scale Prediction of Protein Structure and Function. 2021 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC), 2021, pp. 46-57, doi: 10.1109/MLHPC54614.2021.00010. PDF
Gao, M, Skolnick, J. 2021. A general framework to learn tertiary structure for protein sequence annotation. Front. Bioinform. 1: 689960. doi: 10.3389/fbinf.2021.689960. PDF
Gao, M, Skolnick, J. 2021. A general framework to learn tertiary structure for protein sequence annotation. bioRxiv 2021.04.01.438098; doi: https://doi.org/10.1101/2021.04.01.438098. PDF
*This article is a preprint and has not been certified by peer review.
Skolnick, J, Gao, M. 2021. On the emergence of homochirality and life itself. The Biochemist. 43(1): 4-12. doi:10.1042/BIO20210002 PDF
Skolnick, J, Gao, M. 2021. The role of local versus nonlocal physicochemical restraints in determining protein native structure. Curr Opin Struct Bio. 68:1–8. doi: 10.1016/j.sbi.2020.10.008. PDF
Gao, M, Skolnick, J. 2021. A novel sequence alignment algorithm based on deep learning of the protein folding code. Bioinformatics. 37(4): 490-496. doi: 10.1093/bioinformatics/btaa810. PDF
Cao, H, Jin M, Gao M, Zhou H, Tao YJ, Skolnick J. 2020. Differential kinase activity of ACVR1 G328V and R206H mutations with implications to possible TβRI pathway cross-talk in diffuse intrinsic pontine glioma. Scientific Reports. 10: 6140. doi: 10.1038/s41598-020-63061-0. PDF
Skolnick, J, Zhou H, Gao M. 2019. On the possible origin of protein homochirality, structure and biochemical function. PNAS. 116(52): 26571–26579. https://doi.org/10.1073/pnas.1908241116. PDF
Gao, M, Zhou H, Skolnick J. 2019. DESTINI: A deep-learning approach to contact-driven protein structure prediction. Scientific Reports. 9: 3514. https://doi.org/10.1038/s41598-019-40314-1. PDF
Cao, H, Gao M, Zhou H, Skolnick J. 2018. The crystal structure of a tetrahydrofolate-bound dihydrofolate reductase reveals the origin of slow product release. Communications Biology. 1:226: https://doi.org/10.1038/s42003-018-0236-y. PDF
Zhou, H, Gao M, Skolnick J. 2018. ENTPRISE-X: Predicting disease-associated frameshift and nonsense mutations. PlosOne. 13(5):e0196849. PDF
Eimon, PM, Ghannad-Rezaie M, De Rienzo G, Allalou A, Wu Y, Gao M, Roy A, Skolnick J, Yanik M F. 2018. Brain activity patterns in high-throughput electrophysiology screen predict both drug efficacies and side effects. Nature Communications. 9:219 PDF
Snell, T, Johnson R, Matthews AB, Zhou H, Gao M, Skolnick J. 2018. Repurposed FDA-approved drugs targeting genes influencing aging can extend lifespan and healthspan in rotifers. Biogerontology. PDF
Zhou, H, Gao M, Skolnick J. 2016. ENTPRISE: An Algorithm for Predicting Human Disease-Associated Amino Acid Substitutions from Sequence Entropy and Predicted Protein Structures. PLOS ONE. 11(3):e0150965. PDF
Skolnick, J, Gao M, Zhou H. 2016. How special is the biochemical function of native proteins? F1000Research. 5:207. PDF
Snell, TW, Johnston RK, Srinivasan B, Zhou H, Gao M, Skolnick J. 2016. Repurposing FDA-approved drugs for anti-aging therapies. Biogerontology. 17(5-6):907-920. PDF
Zhou, H, Gao M, Skolnick J. 2015. Comprehensive prediction of drug-protein interactions and side effects for the human proteome. Scientific Reports. 5:11090. PDF
Boles, RG, Hornung HA, Moody AE, Ortiz TB, Wong SA, Eggington JM, Stanley CM, Gao M, Zhou H, McLaughlin S et al. 2015. Hurt, tired and queasy: Specific variants in the ATPase domain of the TRAP1 mitochondrial chaperone are associated with common, chronic “functional” symptomatology including pain, fatigue and gastrointestinal dysmotility. Mitochondrion. 23:64-70. PDF
Gao M, Zhou H, Skolnick J. 2015. Insights into Disease-Associated Mutations in the Human Proteome through Protein Structural Analysis. Structure. 23(7):1362-1369. PDF
Skolnick, J, Gao M, Roy A, Srinivasan B, Zhou H. 2015. Implications of the small number of distinct ligand binding pockets in proteins for drug discovery, evolution and biochemical function.Bioorganic & Medicinal Chemistry Letters. 25:1163-1170. PDF
Skolnick, J, Gao M, Zhou H. 2014. On the Role of Physics and Evolution in Dictating Protein Structure and Function. Israel Journal of Chemistry. 54(8-9):1176-1188. PDF
Skolnick, J, Gao M. 2013. Interplay of physics and evolution in the likely origin of protein biochemical function. Proceedings of the National Academy of Sciences. 110(23):9344-9349. PDF
Gao M, Skolnick J. 2013. APoc: large-scale identification of similar protein pockets. Bioinformatics. 29(5):597-604. PDF
Skolnick, J, Zhou H, Gao M. 2013. Are predicted protein structures of any value for binding site prediction and virtual ligand screening? Current opinion in structural biology. 23(2):191-7. PDF
Gao M, Skolnick J. 2013. A Comprehensive Survey of Small-Molecule Binding Pockets in Proteins. PLoS Computational Biology. 9(10):e1003302. PDF
Gao M, Skolnick J. 2012. The distribution of ligand-binding pockets around protein-protein interfaces suggests a general mechanism for pocket formation. Proceedings of the National Academy of Sciences. 109(10):3784-3789. PDF
Gao M, Skolnick J. 2011. New benchmark metrics for protein-protein docking methods. Proteins: Structure, Function, and Bioinformatics. 79(5):1623-1634. PDF
Brylinski, M, Gao M, Skolnick J. 2011. Why not consider a spherical protein? Implications of backbone hydrogen bonding for protein structure and function Physical Chemistry Chemical Physics. 13 (38):17044-17055. PDF
Pandit, S B, Brylinski M, Zhou H, Gao M, Arakaki AK, Skolnick J. 2010. PSiFR: an integrated resource for prediction of protein structure and function. Bioinformatics (Oxford, England). 26(5):687-8. PDF
Gao M, Skolnick J. 2010. iAlign: a method for the structural comparison of protein-protein interfaces. Bioinformatics (Oxford, England). 26(18):2259-65. PDF Supplementary Data
Gao M, Skolnick J. 2010. Structural space of protein-protein interfaces is degenerate, close to complete, and highly connected. Proceedings of the National Academy of Sciences of the United States of America. 107(52):22517-22. PDF Supplementary Data
Gao M, Skolnick J. 2009. A threading-based method for the prediction of DNA-binding proteins with application to the human genome. PLoS computational biology. 5(11):e1000567. PDF Supplementary Data
Gao M, Skolnick J. 2009. From nonspecific DNA-protein encounter complexes to the prediction of DNA-protein interactions. PLoS computational biology. 5(3):e1000341. PDF
Gao M, Skolnick J. 2008. DBD-Hunter: a knowledge-based method for the prediction of DNA-protein interactions. Nucleic acids research. 36(12):3978-92. PDF Supplementary Data
Puklin-Faucher, E, Gao M, Schulten K, Vogel V. 2006. How the headpiece hinge angle is opened: New insights into the dynamics of integrin activation. The Journal of cell biology. 175(2):349-60. PDF
Gao, M, Sotomayor M, Villa E, Lee EH, Schulten K. 2006. Molecular mechanisms of cellular mechanics. Physical chemistry chemical physics: PCCP. 8(32):3692-706. PDF
Lee, EH, Gao M, Pinotsis N, Wilmanns M, Schulten K. 2006. Mechanical strength of the titin Z1Z2-telethonin complex. Structure (London, England: 1993). 14(3):497-509. PDF
Gao, M, Schulten K. 2006. Onset of anthrax toxin pore formation. Biophysical journal. 90(9):3267-79. PDF
Gao, M, Schulten K. 2004. Integrin activation in vivo and in silico. Structure (London, England: 1993). 12(12):2096-8. PDF
Craig, D, Gao M, Schulten K, Vogel V. 2004. Structural insights into how the MIDAS ion stabilizes integrin binding to an RGD peptide under force. Structure (London, England: 1993). 12(11):2049-58. PDF
Craig, D, Gao M, Schulten K, Vogel V. 2004. Tuning the mechanical stability of fibronectin type III modules through sequence variations. Structure (London, England : 1993). 12(1):21-30. PDF
Gao, M, Craig D, Lequin O, Campbell ID, Vogel V, Schulten K. 2003. Structure and functional significance of mechanically unfolded fibronectin type III1 intermediates. Proceedings of the National Academy of Sciences of the United States of America. 100(25):14784-9. PDF
Tajkhorshid, E, Aksimentiev A, Balabin I, Gao M, Isralewitz B, Phillips JC, Zhu F, Schulten K. 2003. Large scale simulation of protein mechanics and function. Advances in protein chemistry. 66:195-247. PDF
Gao, M, Lu H, Schulten K. 2002. Unfolding of titin domains studied by molecular dynamics simulations. Journal of muscle research and cell motility. 23(5-6):513-21. PDF
Gao, M, Wilmanns M, Schulten K. 2002. Steered molecular dynamics studies of titin I1 domain unfolding. Biophysical journal. 83(6):3435-45. PDF
Gao, M, Craig D, Vogel V, Schulten K. 2002. Identifying unfolding intermediates of FN-III(10) by steered molecular dynamics. Journal of molecular biology. 323(5):939-50. PDF
Gao, M, Lu H, Schulten K. 2001. Simulated refolding of stretched titin immunoglobulin domains. Biophysical journal. 81(4):2268-77. PDF
Isralewitz, B, Gao M, Schulten K. 2001. Steered molecular dynamics and mechanical functions of proteins. Current opinion in structural biology. 11(2):224-30. PDF