Regents’ Professor, School of Biological Sciences
Director, Center for the Study of Systems Biology
Thrust Lead for Precision Medicine and Drug Discovery, Institute for Data Engineering and Science (IDEaS)
Mary and Maisie Gibson Chair & GRA Eminent Scholar in Computational Systems Biology
Deputy Chief Research Officer, Ovarian Cancer Institute
Ph.D., Yale University, 1978
Center for the Study of Systems Biology
950 Atlantic Drive, Room 2151
Atlanta, GA 30332, Mail Code: 2000
Tel: (404) 407-8975
Fax: (404) 385-7478
skolnick@gatech.edu
Research Interests
- Systems Biology, Computational Biology, and Bioinformatics
- Cancer Metabolomics
- Prediction of protein tertiary and quaternary structure and folding pathways
- Prediction of membrane protein tertiary structure
- Prediction of DNA-binding proteins
- Protein Evolution
- Prediction of small molecule ligands for drug discovery
- Prediction of druggable protein targets
- Drug Design
- Automatic assignment of enzymes to metabolic pathways
- Simulation of Virtual Cells
School of Biological Sciences Faculty Page | CV
My Google Scholar Profile
Submitted
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In Press
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2023
Chen, S-J, Hassan M, Jernigan R, Jia K, Kihara D, Kloczkowski A, Kotelnikov S, Kozakov D, Liang J, Liwo A, Matysiak S, Meller J, Micheletti C, Mitchell J, Mondal S, Nussinov R, Okazaki K, Padhorny D, Skolnick J, Sosnick T, Stan G, Vakser I, Zou X, Rose G D. 2023. Opinion: Protein folds vs. protein folding: Differing questions, different challenges. PNAS 120(1):e2214423119. https://doi.org/10.1073/pnas.2214423119. PDF
2022
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
Zhou, H, Astore C, Skolnick J. 2022. PHEVIR: An artificial intelligence algorithm that predicts the molecular role of pathogens in complex human diseases. Sci Rep 12, 20889 (2022). https://doi.org/10.1038/s41598-022-25412-x. PDF
Guo, Z, Liu J, Skolnick J, Cheng J. 2022. Prediction of inter-chain distance maps of protein complexes with 2D attention-based deep neural networks. Nat Commun 13, 6963 (2022). https://doi.org/10.1038/s41467-022-34600-2. PDF
Zhou, H, Skolnick J. 2022. Implications of the essential role of small molecule ligand binding pockets in protein-protein interactions. J. Phys. Chem. B. 126 (36), 6853-6867. doi.org/10.1021/acs.jpcb.2c04525. 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.
Astore, C, Zhou H, Ilkowski B, Forness J, Skolnick J. 2022. LeMeDISCO: A computational method for large-scale prediction & molecular interpretation of disease comorbidity. Commun Biol. 5, 87. doi.org/10.1038/s42003-022-03816-9. PDF
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
2021
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.
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
Mitchel, J, Bajaj P, Patil K, Gunnarson A, Pourchet E, Kim Y, Skolnick J, Pai S B. 2021. Computational Identification of Stearic Acid as a Potential PDK1 Inhibitor and in vitro Validation of Stearic Acid as Colon Cancer Therapeutic in Combination with 5-Fluorouracil. Cancer Inform. 2021 Dec 13;20:11769351211065979. doi: 10.1177/11769351211065979. PDF
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
Astore, C, Zhou H, Jacob J, Skolnick J. 2021. Prediction of severe adverse events, modes of action and drug treatments for COVID-19’s complications. Scientific Reports. 11: 20864. 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
Astore, C, Zhou H, Skolnick J. 2021. LeMeDISCO: A computational method for large-scale prediction & molecular interpretation of disease comorbidity. medRxiv 2021.06.28.21259559; doi: https://doi.org/10.1101/2021.06.28.21259559 PDF
*This article is a preprint and has not been certified by peer review.
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 novel sequence alignment algorithm based on deep learning of the protein folding code. Bioinformatics. 37(4): 490-496. doi: 10.1093/bioinformatics/btaa810. PDF
Zhou, H, Cao H, Skolnick J. 2021. FRAGSITE: A Fragment Based Approach for Virtual Ligand Screening. J Chem Inf Model. 61(4): 2074-2089. doi: 10.1021/acs.jcim.0c01160. 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. 2021. Memories of Harold Scheraga. J Chem Theory Comput. 17(4): 2011-2012. doi: 10.1021/acs.jctc.1c00251. PDF
Skolnick, J, Gao, M. 2021. On the emergence of homochirality and life itself. The Biochemist. 43(1): 4-12. doi: 10.1042/BIO20210002 PDF
Astore, C, Zhou H, Jacob J, Skolnick J. 2021. MOATAI-VIR – an AI algorithm that predicts severe adverse events and molecular features for COVID-19’s complications. medRxiv 2021.01.29.21250712; doi: https://doi.org/10.1101/2021.01.29.21250712. PDF
*This article is a preprint and has not been certified by peer review.
2020
Maisuradze, G, Montelione G, Rackovsky S, Skolnick J. 2020. Tribute to Harold A. Scheraga. The Journal of Physical Chemistry B. https://dx.doi.org/10.1021/acs.jpcb.0c08867. PDF
Zhou, H, Cao H, Matyunina L, Shelby M, Cassels L, McDonald J, Skolnick, J. 2020. MEDICASCY: A Machine Learning Approach for Predicting Small-Molecule Drug Side Effects, Indications, Efficacy and Modes of Action. Molecular Pharmaceutics. 17(5): 1558-1574. doi: 10.1021/acs.molpharmaceut.9b01248. 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
Sweeney-Jones, AM, Gagaring K, Antonova-Koch J, Zhou H, Mojib N, Soapi K, Skolnick J, McNamara C, Kubanek J. 2020. Antimalarial Peptide and Polyketide Natural Products from the Fijian Marine Cyanobacterium Moorea producens. Marine Drugs. 18: 167. doi:10.3390/md18030167. PDF
2019
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, Skolnick J. 2019. Time resolved x-ray crystallography capture of a slow reaction tetrahydrofolate intermediate. Structural Dynamics. 6: 024701. https://doi.org/10.1063/1.5086436. PDF
2018
Zhou, H, Cao H, Skolnick J. 2018. FINDSITEcomb2.0: A New Approach for Virtual Ligand Screening of Proteins and Virtual Target Screening of Biomolecules. Journal of Chemical Information and Modeling. 58(11): 2343-2354 doi: 10.1021/acs.jcim.8b00309. 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
Srinivasan, B, Tonddast-Navaei S, Roy A, Zhou H, Skolnick J. 2018. Chemical Space of Escherichia coli Dihydrofolate Reductase Inhibitors: New Approaches for Discovering Novel Drugs for Old Bugs. Medicinal Research Reviews. 1-22. 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
2017
Srinivasan, B, Tonddast-Navaei S, Skolnick J. 2017. Pocket detection and interaction-weighted ligand-similarity search yields novel high-affinity binders for Myocilin-OLF, a protein implicated in glaucoma. Bioorganic & Medicinal Chemistry Letters. 27(17):4133-4139. PDF
Chow, E, Skolnick J. 2017. DNA internal motion likely accelerates protein target search in a packed nucleoid. Biophysical Journal. 112(11):2261–2270. PDF
Tonddast-Navaei, S, Srinivasan B, Skolnick J. 2017. On the importance of COmposite Protein multiple LIGand (COLIG) Interactions in Protein Pockets. Journal of Computational Chemistry. 38:1252-1259. PDF
Srinivasan, B, Rodrigues JV, Tonddast-Navaei S, Shakhnovich E, Skolnick J. 2017. Rational Design of Novel Allosteric Dihydrofolate Reductase Inhibitors Showing Antibacterial Effects on Drug-Resistant Escherichia coli Escape Variants. ACS Chemical Biology. 12:1848–1857. PDF
Skolnick, J, Zhou H. 2017. Why Is There a Glass Ceiling for Threading Based Protein Structure Prediction Methods? The Journal of Physical Chemistry B. 121(15):3546-3554. PDF
Skolnick, J. 2017. Editorial: Integrating the whole from the sum of the parts: Vignettes in Computational Biology. Emerging Topics in Life Sciences. 1:241–243. PDF
2016
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
Srinivasan, B, Zhou H, Mitra S, Skolnick J. 2016. Novel small molecule binders of human N-glycanase 1, a key player in the endoplasmic reticulum associated degradation pathway. Bioorganic & Medicinal Chemistry. 24(19):4750-4758. PDF
Srinivasan, B, Marks H, Mitra S, Smalley DM, Skolnick J. 2016. Catalytic and substrate promiscuity: distinct multiple chemistries catalysed by the phosphatase domain of receptor protein tyrosine phosphatase. Biochemical Journal. 473(14):2165-2177. PDF
Zhou, H, Skolnick J. 2016. A knowledge-based approach for predicting gene-disease associations. Bioinformatics. 32(18): 2831-8. PDF
Skolnick, J. 2016. Perspective: On the importance of hydrodynamic interactions in the subcellular dynamics of macromolecules. The Journal of Chemical Physics. 145:100901. PDF
2015
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
Roy, A, Skolnick J. 2015. LIGSIFT: an open-source tool for ligand structural alignment and virtual screening. Bioinformatics (Oxford, England). 31(4):539-44. PDF
Dhakshinamoorthy, S, Dinh N-T, Skolnick J, Styczynski MP. 2015. Metabolomics identifies the intersection of phosphoethanolamine with menaquinone-triggered apoptosis in an in vitro model of leukemia. Mol. BioSyst.. 11(9):2406-2416. PDF
Tonddast-Navaei, S, Skolnick J. 2015. Are protein-protein interfaces special regions on a protein’s surface? The Journal of Chemical Physics. 143(24):243149. PDF
Chow, E, Skolnick J. 2015. Effects of confinement on models of intracellular macromolecular dynamics. Proceedings of the National Academy of Sciences. 112(48):14846-14851. PDF
Srinivasan, B, Tonddast-Navaei S, Skolnick J. 2015. Ligand binding studies, preliminary structure–activity relationship and detailed mechanistic characterization of 1-phenyl-6,6-dimethyl-1,3,5-triazine-2,4-diamine derivatives as inhibitors of Escherichia coli dihydrofolate reductase.European Journal of Medicinal Chemistry. 103:600-614. PDF
Roy, A, Srinivasan B, Skolnick J. 2015. PoLi: A Virtual Screening Pipeline Based on Template Pocket and Ligand Similarity. Journal of Chemical Information and Modeling. 55(8):1757-1770. PDF
Lee, H S, Jo S, Mukherjee S, Park S-J, Skolnick J, Lee J, Im W. 2015. GS-align for glycan structure alignment and similarity measurement. Bioinformatics. 31(16):2653-2659. PDF
Boles, RG, Hornung HA, Moody AE, Ortiz TB, Wong SA, Eggington JM, Stanley CM, Gao M, Zhou H, McLaughlin S, Zare AS, Sheldon KM, Skolnick J. 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
Srinivasan, B, Skolnick J. 2015. Insights into the slow-onset tight-binding inhibition of Escherichia coli dihydrofolate reductase: detailed mechanistic characterization of pyrrolo [3,2-f] quinazoline-1,3-diamine and its derivatives as novel tight-binding inhibitors. FEBS Journal. 282(10):1922-1938. 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
2014
Srinivasan, B, Zhou H, Kubanek J, Skolnick J. 2014. Experimental validation of FINDSITEcomb virtual ligand screening results for eight proteins yields novel nanomolar and micromolar binders.Journal of Cheminformatics. 6(1):16. PDF
Ando, T, Skolnick J. 2014. Sliding of Proteins Non-specifically Bound to DNA: Brownian Dynamics Studies with Coarse-Grained Protein and DNA Models. PLoS Computational Biology. 10(12):e1003990. PDF
Kufareva, I, Katritch V, Stevens R C., Abagyan R, Skolnick J, Zhou H, Roy A. 2014. Advances in GPCR Modeling Evaluated by the GPCR Dock 2013 Assessment: Meeting New Challenges.Structure. 22(8):1120-1139. 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
Khoury, GA, Liwo A, Khatib F, Zhou H, Chopra G, Bacardit J, Bortot LO, Faccioli RA, Deng X, He Y et al.. 2014. WeFold: A Coopetition for Protein Structure Prediction. Proteins: Structure, Function, and Bioinformatics. 82(9): 1850-68. PDF