Publications

2020
Heyne M, Shirian J, Cohen I., Y. Peleg, Papo N., and Shifman J. M. 2020. “Climbing up and down binding landscapes: a high-throughput study of mutational effects in homologous protein-protein complexes.” BioArxiv, 10.1101, /2020.10.14.338756.
Heyne M., N Papo, and J. M. Shifman. 2020. “Generating quantitative binding landscapes through fractional binding selections combined with deep sequencing and data normalization.” Nature Communications, 11 (1), Pp. 1-7.
H. Kumar and J. M. Shifman. 2020. “Predicting Mutational Effects.” In Protein interactions: computational methods, analysis and applications, edited by M. M. Gromiha. Vol. in press. Singapore: World Scientific Publishing Co. Pvt. Ltd.
Thillaivillalan D, Singh S, Killoran R. C, Singh A., Xu X, Shifman J. M., and Smith M. J. 2020. “RASSF effectors couple diverse Ras subfamily GTPases to the Hippo pathway.” Science Signal, 13(653), eabb4778.
2019
M. Ben-David, H. Huang, M. G. F. Sun, C. Corbi-Verge, E. Petsalaki, K. Liu, D. Gfeller, P. Garg, W. Tempel, I. Sochirca, J. M. Shifman, A. Davidson, J. Min, P. M. Kim, and S. S. Sidhu. 2019. “Allosteric Modulation of Binding Specificity by Alternative Packing of Protein Cores.” J Mol Biol, 431, Pp. 336-350. Abstract
Hydrophobic cores are often viewed as tightly packed and rigid, but they do show some plasticity and could thus be attractive targets for protein design. Here we explored the role of different functional pressures on the core packing and ligand recognition of the SH3 domain from human Fyn tyrosine kinase. We randomized the hydrophobic core and used phage display to select variants that bound to each of three distinct ligands. The three evolved groups showed remarkable differences in core composition, illustrating the effect of different selective pressures on the core. Changes in the core did not significantly alter protein stability, but were linked closely to changes in binding affinity and specificity. Structural analysis and molecular dynamics simulations revealed the structural basis for altered specificity. The evolved domains had significantly reduced core volumes, which in turn induced increased backbone flexibility. These motions were propagated from the core to the binding surface and induced significant conformational changes. These results show that alternative core packing and consequent allosteric modulation of binding interfaces could be used to engineer proteins with novel functions.
2018
J. M. Shifman and A. Singh. 2018. “Computational Protein Design.” Edited by Gordon C. K. Roberts Anthony and Watts.
J. Shirian, V. Arkadash, I. Cohen, T. Sapir, E. S. Radisky, N. Papo, and J. M. Shifman. 2018. “Converting a broad matrix metalloproteinase family inhibitor into a specific inhibitor of MMP-9 and MMP-14.” FEBS Lett, 592, Pp. 1122-1134. Abstract
MMP-14 and MMP-9 are two well-established cancer targets for which no specific clinically relevant inhibitor is available. Using a powerful combination of computational design and yeast surface display technology, we engineered such an inhibitor starting from a nonspecific MMP inhibitor, N-TIMP2. The engineered purified N-TIMP2 variants showed enhanced specificity toward MMP-14 and MMP-9 relative to a panel of off-target MMPs. MMP-specific N-TIMP2 sequence signatures were obtained that could be understood from the structural perspective of MMP/N-TIMP2 interactions. Our MMP-9 inhibitor exhibited 1000-fold preference for MMP-9 vs. MMP-14, which is likely to translate into significant differences under physiological conditions. Our results provide new insights regarding evolution of promiscuous proteins and optimization strategies for design of inhibitors with single-target specificities.
2017
V. Arkadash, G. Yosef, J. Shirian, I. Cohen, Y. Horev, M. Grossman, I. Sagi, E. S. Radisky, J. M. Shifman, and N. Papo. 2017. “Development of high-affinity and high-specificity inhibitors of metalloproteinase 14 through computational design and directed evolution.” J Biol Chem, 292, Pp. 3481-3495. Abstract
Degradation of the extracellular matrices in the human body is controlled by matrix metalloproteinases (MMPs), a family of more than 20 homologous enzymes. Imbalance in MMP activity can result in many diseases, such as arthritis, cardiovascular diseases, neurological disorders, fibrosis, and cancers. Thus, MMPs present attractive targets for drug design and have been a focus for inhibitor design for as long as three decades. Yet, to date, all MMP inhibitors have failed in clinical trials because of their broad activity against numerous MMP family members and the serious side effects of the proposed treatment. In this study, we integrated a computational method and a yeast surface display technique to obtain highly specific inhibitors of MMP-14 by modifying the natural non-specific broad MMP inhibitor protein N-TIMP2 to interact optimally with MMP-14. We identified an N-TIMP2 mutant, with five mutations in its interface that has an MMP-14 inhibition constant (Ki) of 0.9 pM, the strongest MMP-14 inhibitor reported so far. Compared with wild-type N-TIMP2, this variant displays ~900-fold improved affinity towards MMP-14 and up to 16,000-fold greater specificity towards MMP-14 relative to other MMPs. In an in vitro and cell-based model of MMP-dependent breast cancer cellular invasiveness, this N-TIMP2 mutant acted as a functional inhibitor. Thus, our study demonstrates the enormous potential of a combined computational/directed-evolution approach to protein engineering. Furthermore, it offers fundamental clues into the molecular basis of MMP regulation by N-TIMP2 and identifies a promising MMP-14 inhibitor as a starting point for the development of protein-based anticancer therapeutics.
E. Rabinovich, M. Heyne, A. Bakhman, M. Kosloff, J. M. Shifman, and N. Papo. 2017. “Identifying Residues that Determine SCF Molecular-Level Interactions through a Combination of Experimental and In silico Analyses.” J Mol Biol, 429, Pp. 97-114. Abstract
The stem cell factor (SCF)/c-Kit receptor tyrosine kinase complex-with its significant roles in hematopoiesis and angiogenesis-is an attractive target for rational drug design. There is thus a need to map, in detail, the SCF/c-Kit interaction sites and the mechanisms that modulate this interaction. While most residues in the direct SCF/c-Kit binding interface can be identified from the existing crystal structure of the complex, other residues that affect binding through protein unfolding, intermolecular interactions, allosteric or long-distance electrostatic effects cannot be directly inferred. Here, we describe an efficient method for protein-wide epitope mapping using yeast surface display. A library of single SCF mutants that span the SCF sequence was screened for decreased affinity to soluble c-Kit. Sequencing of selected clones allowed the identification of mutations that reduce SCF binding affinity to c-Kit. Moreover, the screening of these SCF clones for binding to a structural antibody helped identify mutations that result in small or large conformational changes in SCF. Computational modeling of the experimentally identified mutations showed that these mutations reduced the binding affinity through one of the three scenarios: through SCF destabilization, through elimination of favorable SCF/c-Kit intermolecular interactions, or through allosteric changes. Eight SCF variants were expressed and purified. Experimentally measured in vitro binding affinities of these mutants to c-Kit confirmed both the yeast surface display selection results and the computational predictions. This study has thus identified the residues crucial for c-Kit/SCF binding and has demonstrated the advantages of using a combination of computational and combinatorial methods for epitope mapping.
2016
J. Shirian, O. Sharabi, and J. M. Shifman. 2016. “Cold-spots in Protein Binding.” Trends Biochem Sci, 41(9), Pp. 739-45.
L. Rosenfeld, M. Heyne, J. M. Shifman, and N. Papo. 2016. “Protein Engineering by Combined Computational and In Vitro Evolution Approaches.” Trends Biochem Sci, 41, Pp. 421-33. Abstract
Two alternative strategies are commonly used to study protein-protein interactions (PPIs) and to engineer protein-based inhibitors. In one approach, binders are selected experimentally from combinatorial libraries of protein mutants that are displayed on a cell surface. In the other approach, computational modeling is used to explore an astronomically large number of protein sequences to select a small number of sequences for experimental testing. While both approaches have some limitations, their combination produces superior results in various protein engineering applications. Such applications include the design of novel binders and inhibitors, the enhancement of affinity and specificity, and the mapping of binding epitopes. The combination of these approaches also aids in the understanding of the specificity profiles of various PPIs.
A. Erijman and J. M. Shifman. 2016. “Ras/effector interactions from structural and biophysical perspective.” Mini-Reviews in Medicinal Chemistry, 16, Pp. 370-375.
I. Leung, A. Dekel, J. M. Shifman, and S. S. Sidhu. 2016. “Saturation scanning of ubiquitin variants reveals a common hot spot for binding to USP2 and USP21.” Proc Natl Acad Sci U S A, 113, Pp. 8705-10. Abstract
A detailed understanding of the molecular mechanisms whereby ubiquitin (Ub) recognizes enzymes in the Ub proteasome system is crucial for understanding the biological function of Ub. Many structures of Ub complexes have been solved and, in most cases, reveal a large structural epitope on a common face of the Ub molecule. However, owing to the generally weak nature of these interactions, it has been difficult to map in detail the functional contributions of individual Ub side chains to affinity and specificity. Here we took advantage of Ub variants (Ubvs) that bind tightly to particular Ub-specific proteases (USPs) and used phage display and saturation scanning mutagenesis to comprehensively map functional epitopes within the structural epitopes. We found that Ubvs that bind to USP2 or USP21 contain a remarkably similar core functional epitope, or "hot spot," consisting mainly of positions that are conserved as the wild type sequence, but also some positions that prefer mutant sequences. The Ubv core functional epitope contacts residues that are conserved in the human USP family, and thus it is likely important for the interactions of Ub across many family members.
2015
L. Rosenfeld, J. Shirian, Y. Zur, N. Levaot, J. M. Shifman, and N. Papo. 2015. “Combinatorial and Computational Approaches to Identify Interactions of Macrophage Colony-stimulating Factor (M-CSF) and Its Receptor c-FMS.” J Biol Chem, 290, Pp. 26180-93. Abstract
The molecular interactions between macrophage colony-stimulating factor (M-CSF) and the tyrosine kinase receptor c-FMS play a key role in the immune response, bone metabolism, and the development of some cancers. Because no x-ray structure is available for the human M-CSF . c-FMS complex, the binding epitope for this complex is largely unknown. Our goal was to identify the residues that are essential for binding of the human M-CSF to c-FMS. For this purpose, we used a yeast surface display (YSD) approach. We expressed a combinatorial library of monomeric M-CSF (M-CSFM) single mutants and screened this library to isolate variants with reduced affinity for c-FMS using FACS. Sequencing yielded a number of single M-CSFM variants with mutations both in the direct binding interface and distant from the binding site. In addition, we used computational modeling to map the identified mutations onto the M-CSFM structure and to classify the mutations into three groups as follows: those that significantly decrease protein stability; those that destroy favorable intermolecular interactions; and those that decrease affinity through allosteric effects. To validate the YSD and computational data, M-CSFM and three variants were produced as soluble proteins; their affinity and structure were analyzed; and very good correlations with both YSD data and computational predictions were obtained. By identifying the M-CSFM residues critical for M-CSF . c-FMS interactions, we have laid down the basis for a deeper understanding of the M-CSF . c-FMS signaling mechanism and for the development of target-specific therapeutic agents with the ability to sterically occlude the M-CSF.c-FMS binding interface.
U. Kafurke, A. Erijman, Y. Aizner, J. M. Shifman, and J. Eichler. 2015. “Synthetic peptides mimicking the binding site of human acetylcholinesterase for its inhibitor fasciculin 2.” J Pept Sci, 21, Pp. 723-30. Abstract
Molecules capable of mimicking protein binding and/or functional sites present useful tools for a range of biomedical applications, including the inhibition of protein-ligand interactions. Such mimics of protein binding sites can currently be generated through structure-based design and chemical synthesis. Computational protein design could be further used to optimize protein binding site mimetics through rationally designed mutations that improve intermolecular interactions or peptide stability. Here, as a model for the study, we chose an interaction between human acetylcholinesterase (hAChE) and its inhibitor fasciculin-2 (Fas) because the structure and function of this complex is well understood. Structure-based design of mimics of the hAChE binding site for Fas yielded a peptide that binds to Fas at micromolar concentrations. Replacement of hAChE residues known to be essential for its interaction with Fas with alanine, in this peptide, resulted in almost complete loss of binding to Fas. Computational optimization of the hAChE mimetic peptide yielded a variant with slightly improved affinity to Fas, indicating that more rounds of computational optimization will be required to obtain peptide variants with greatly improved affinity for Fas. CD spectra in the absence and presence of Fas point to conformational changes in the peptide upon binding to Fas. Furthermore, binding of the optimized hAChE mimetic peptide to Fas could be inhibited by hAChE, providing evidence for a hAChE-specific peptide-Fas interaction.
2014
O. Sharabi, J. Shirian, M. Grossman, I. Sagi, and J. M. Shifman. 2014. “Affinity- and specificity-enhancing mutations are frequent in mulstispecific interaction between MMP14 and its inhibitor TIMP2.” PloS ONE, 9, Pp. e93712.
J. Murciano-Calles, M. E. McLaughlin, A. Erijman, Y. Hooda, N. Chakravorty, J. C. Martinez, J. M. Shifman, and S. S. Sidhu. 2014. “Alteration of the C-Terminal Ligand Specificity of the Erbin PDZ Domain by Allosteric Mutational Effects.” J Mol Biol. Abstract
Modulation of protein binding specificity is important for basic biology and for applied science. Here we explore how binding specificity is conveyed in PDZ (postsynaptic density protein-95/discs large/zonula occludens-1) domains, small interaction modules that recognize various proteins by binding to an extended C terminus. Our goal was to engineer variants of the Erbin PDZ domain with altered specificity for the most C-terminal position (position 0) where a Val is strongly preferred by the wild-type domain. We constructed a library of PDZ domains by randomizing residues in direct contact with position 0 and in a loop that is close to but does not contact position 0. We used phage display to select for PDZ variants that bind to 19 peptide ligands differing only at position 0. To verify that each obtained PDZ domain exhibited the correct binding specificity, we selected peptide ligands for each domain. Despite intensive efforts, we were only able to evolve Erbin PDZ domain variants with selectivity for the aliphatic C-terminal side chains Val, Ile and Leu. Interestingly, many PDZ domains with these three distinct specificities contained identical amino acids at positions that directly contact position 0 but differed in the loop that does not contact position 0. Computational modeling of the selected PDZ domains shows how slight conformational changes in the loop region propagate to the binding site and result in different binding specificities. Our results demonstrate that second-sphere residues could be crucial in determining protein binding specificity.
A. Erijman, E. Rosenthal, and J. M. Shifman. 2014. “How structure defines affinity in protein-protein interactions.” PLoS ONE, 9, Pp. e110085.
Y. Aizner, O. Sharabi, J. Shirian, G. Dakwar, O Abvraham, M. Risman, and J. M. Shifman. 2014. “Mapping the binding landscape of a picomolar protein-protein complex through computation and experiment.” Structure, 22, Pp. 1-10.
A. Erijman, J. M. Shifman, and Y. Peleg. 2014. “A single-tube assembly of DNA using the Transfer-PCR(TPCR) platform.” Methods Mol Biol, 1116, Pp. 89-101 .

Pages