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Journal articles on the topic 'Protein-small molecule interactions'

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Published: 6 September 2023

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1

Kuusk, Ave, Helen Boyd, Hongming Chen, and Christian Ottmann. "Small-molecule modulation of p53 protein-protein interactions." Biological Chemistry 401, no. 8 (July 28, 2020): 921–31. http://dx.doi.org/10.1515/hsz-2019-0405.

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AbstractSmall-molecule modulation of protein-protein interactions (PPIs) is a very promising but also challenging area in drug discovery. The tumor suppressor protein p53 is one of the most frequently altered proteins in human cancers, making it an attractive target in oncology. 14-3-3 proteins have been shown to bind to and positively regulate p53 activity by protecting it from MDM2-dependent degradation or activating its DNA binding affinity. PPIs can be modulated by inhibiting or stabilizing specific interactions by small molecules. Whereas inhibition has been widely explored by the pharmaceutical industry and academia, the opposite strategy of stabilizing PPIs still remains relatively underexploited. This is rather interesting considering the number of natural compounds like rapamycin, forskolin and fusicoccin that exert their activity by stabilizing specific PPIs. In this review, we give an overview of 14-3-3 interactions with p53, explain isoform specific stabilization of the tumor suppressor protein, explore the approach of stabilizing the 14-3-3σ-p53 complex and summarize some promising small molecules inhibiting the p53-MDM2 protein-protein interaction.

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2

Ottmann, Christian. "Small-molecule modulation of protein–protein interactions." Drug Discovery Today: Technologies 10, no. 4 (December 2013): e499-e500. http://dx.doi.org/10.1016/j.ddtec.2013.08.001.

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3

Pollock, Julie A., Courtney L. Labrecque, Cassidy N. Hilton, Justin Airas, Alexis Blake, Kristen J. Rubenstein, and Carol A. Parish. "Small Molecule Modulation of MEMO1 Protein-Protein Interactions." Journal of the Endocrine Society 5, Supplement_1 (May 1, 2021): A1031. http://dx.doi.org/10.1210/jendso/bvab048.2110.

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Abstract MEMO1 (mediator of ErbB2-driven cell motility) is upregulated in breast tumors and has been correlated with poor prognosis in patients. As a scaffolding protein that binds to phosphorylated-tyrosine residues on receptors such as estrogen receptor and ErbB2, MEMO1 levels can influence phosphorylation cascades. Using our previously developed fluorescence polarization assay, we have identified small molecules with the ability to disrupt the interactions of MEMO1. We have performed limited structure-activity-relationship studies and computational analyses to investigate the molecular requirements for MEMO1 inhibition. The most promising compounds exhibit slowed migration of breast cancer cell lines (T47D and SKBR3) in a wound-healing assay emulating results obtained from the knockdown of MEMO1 protein. To our knowledge, these are the first small molecules targeting the MEMO1 protein-protein interface and therefore, will be invaluable tools for the investigation of the role of the MEMO1 in breast cancer and other biological contexts.

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4

Linhares, Brian M., Jolanta Grembecka, and Tomasz Cierpicki. "Targeting epigenetic protein–protein interactions with small-molecule inhibitors." Future Medicinal Chemistry 12, no. 14 (July 2020): 1305–26. http://dx.doi.org/10.4155/fmc-2020-0082.

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Epigenetic protein–protein interactions (PPIs) play essential roles in regulating gene expression, and their dysregulations have been implicated in many diseases. These PPIs are comprised of reader domains recognizing post-translational modifications on histone proteins, and of scaffolding proteins that maintain integrities of epigenetic complexes. Targeting PPIs have become focuses for development of small-molecule inhibitors and anticancer therapeutics. Here we summarize efforts to develop small-molecule inhibitors targeting common epigenetic PPI domains. Potent small molecules have been reported for many domains, yet small domains that recognize methylated lysine side chains on histones are challenging in inhibitor development. We posit that the development of potent inhibitors for difficult-to-prosecute epigenetic PPIs may be achieved by interdisciplinary approaches and extensive explorations of chemical space.

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5

Guo, Z. "Designing Small-Molecule Switches for Protein-Protein Interactions." Science 288, no. 5473 (June 16, 2000): 2042–45. http://dx.doi.org/10.1126/science.288.5473.2042.

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6

Li, Xiyan, Xin Wang, and Michael Snyder. "Systematic investigation of protein-small molecule interactions." IUBMB Life 65, no. 1 (December 7, 2012): 2–8. http://dx.doi.org/10.1002/iub.1111.

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7

D’Abramo, C. M. "Small Molecule Inhibitors of Human Papillomavirus Protein - Protein Interactions." Open Virology Journal 5, no. 1 (July 4, 2011): 80–95. http://dx.doi.org/10.2174/1874357901105010080.

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8

Song, Yun, and Peter Buchwald. "TNF Superfamily Protein-Protein Interactions: Feasibility of Small- Molecule Modulation." Current Drug Targets 16, no. 4 (April 6, 2015): 393–408. http://dx.doi.org/10.2174/1389450116666150223115628.

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9

de Vink, Pim J., Sebastian A. Andrei, Yusuke Higuchi, Christian Ottmann, Lech-Gustav Milroy, and Luc Brunsveld. "Cooperativity basis for small-molecule stabilization of protein–protein interactions." Chemical Science 10, no. 10 (2019): 2869–74. http://dx.doi.org/10.1039/c8sc05242e.

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A cooperativity framework to describe and interpret small-molecule stabilization of protein–protein interactions (PPI) is presented, which allows elucidating structure–activity relationships regarding cooperativity and intrinsic affinity.

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10

Aeluri, Madhu, Srinivas Chamakuri, Bhanudas Dasari, Shiva Krishna Reddy Guduru, Ravikumar Jimmidi, Srinivas Jogula, and Prabhat Arya. "Small Molecule Modulators of Protein–Protein Interactions: Selected Case Studies." Chemical Reviews 114, no. 9 (March 27, 2014): 4640–94. http://dx.doi.org/10.1021/cr4004049.

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11

Ottmann, Christian. "Small-molecule modulators of 14-3-3 protein–protein interactions." Bioorganic & Medicinal Chemistry 21, no. 14 (July 2013): 4058–62. http://dx.doi.org/10.1016/j.bmc.2012.11.028.

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12

Fry, David C. "Protein–protein interactions as targets for small molecule drug discovery." Biopolymers 84, no. 6 (2006): 535–52. http://dx.doi.org/10.1002/bip.20608.

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13

Vargas, Carolyn, Gerald Radziwill, Gerd Krause, Anne Diehl, Sandro Keller, Nestor Kamdem, Constantin Czekelius, et al. "Small-Molecule Inhibitors of AF6 PDZ-Mediated Protein-Protein Interactions." ChemMedChem 9, no. 7 (March 25, 2014): 1458–62. http://dx.doi.org/10.1002/cmdc.201300553.

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14

Zhang, Changsheng, and Luhua Lai. "Towards structure-based protein drug design." Biochemical Society Transactions 39, no. 5 (September 21, 2011): 1382–86. http://dx.doi.org/10.1042/bst0391382.

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Structure-based drug design for chemical molecules has been widely used in drug discovery in the last 30 years. Many successful applications have been reported, especially in the field of virtual screening based on molecular docking. Recently, there has been much progress in fragment-based as well as de novo drug discovery. As many protein–protein interactions can be used as key targets for drug design, one of the solutions is to design protein drugs based directly on the protein complexes or the target structure. Compared with protein–ligand interactions, protein–protein interactions are more complicated and present more challenges for design. Over the last decade, both sampling efficiency and scoring accuracy of protein–protein docking have increased significantly. We have developed several strategies for structure-based protein drug design. A grafting strategy for key interaction residues has been developed and successfully applied in designing erythropoietin receptor-binding proteins. Similarly to small-molecule design, we also tested de novo protein-binder design and a virtual screen of protein binders using protein–protein docking calculations. In comparison with the development of structure-based small-molecule drug design, we believe that structure-based protein drug design has come of age.

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15

Li, Fengzhi, Ieman A. M. Aljahdali, and Xiang Ling. "Molecular Glues: Capable Protein-Binding Small Molecules That Can Change Protein–Protein Interactions and Interactomes for the Potential Treatment of Human Cancer and Neurodegenerative Diseases." International Journal of Molecular Sciences 23, no. 11 (June 1, 2022): 6206. http://dx.doi.org/10.3390/ijms23116206.

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Molecular glue (MG) compounds are a type of unique small molecule that can change the protein–protein interactions (PPIs) and interactomes by degrading, stabilizing, or activating the target protein after their binging. These small-molecule MGs are gradually being recognized for their potential application in treating human diseases, including cancer. Evidence suggests that small-molecule MG compounds could essentially target any proteins, which play critical roles in human disease etiology, where many of these protein targets were previously considered undruggable. Intriguingly, most MG compounds with high efficacy for cancer treatment can glue on and control multiple key protein targets. On the other hand, a single key protein target can also be glued by multiple MG compounds with distinct chemical structures. The high flexibility of MG–protein interaction profiles provides rich soil for the growth and development of small-molecule MG compounds that can be used as molecular tools to assist in unraveling disease mechanisms, and they can also facilitate drug development for the treatment of human disease, especially human cancer. In this review, we elucidate this concept by using various types of small-molecule MG compounds and their corresponding protein targets that have been documented in the literature.

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16

Balci, Hamza, Sujay Ray, Jagat Budhathoki, and Parastoo Maleki. "Single Molecule Studies on G-Quadruplex, Protein, and Small Molecule Interactions." Biophysical Journal 112, no. 3 (February 2017): 170a. http://dx.doi.org/10.1016/j.bpj.2016.11.940.

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17

Guan, Yan, Xiaonan Shan, Fenni Zhang, Shaopeng Wang, Hong-Yuan Chen, and Nongjian Tao. "Kinetics of small molecule interactions with membrane proteins in single cells measured with mechanical amplification." Science Advances 1, no. 9 (October 2015): e1500633. http://dx.doi.org/10.1126/sciadv.1500633.

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Measuring small molecule interactions with membrane proteins in single cells is critical for understanding many cellular processes and for screening drugs. However, developing such a capability has been a difficult challenge. We show that molecular interactions with membrane proteins induce a mechanical deformation in the cellular membrane, and real-time monitoring of the deformation with subnanometer resolution allows quantitative analysis of small molecule–membrane protein interaction kinetics in single cells. This new strategy provides mechanical amplification of small binding signals, making it possible to detect small molecule interactions with membrane proteins. This capability, together with spatial resolution, also allows the study of the heterogeneous nature of cells by analyzing the interaction kinetics variability between different cells and between different regions of a single cell.

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18

Nagatoishi, Satoru, Jose M. M. Caaveiro, and Kouhei Tsumoto. "Biophysical Analysis of the Protein-Small Molecule Interactions to Develop Small Molecule Drug Discovery." YAKUGAKU ZASSHI 138, no. 8 (August 1, 2018): 1033–41. http://dx.doi.org/10.1248/yakushi.17-00211-2.

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19

Zhu, Yan, and Xiche Hu. "Molecular Recognition of FDA-Approved Small Molecule Protein Kinase Drugs in Protein Kinases." Molecules 27, no. 20 (October 21, 2022): 7124. http://dx.doi.org/10.3390/molecules27207124.

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Protein kinases are key enzymes that catalyze the covalent phosphorylation of substrates via the transfer of the γ-phosphate of ATP, playing a crucial role in cellular proliferation, differentiation, and various cell regulatory processes. Due to their pivotal cellular role, the aberrant function of kinases has been associated with cancers and many other diseases. Consequently, competitive inhibition of the ATP binding site of protein kinases has emerged as an effective means of curing these diseases. Decades of intense development of protein kinase inhibitors (PKIs) resulted in 71 FDA-approved PKI drugs that target dozens of protein kinases for the treatment of various diseases. How do FDA-approved protein kinase inhibitor PKI drugs compete with ATP in their own binding pocket? This is the central question we attempt to address in this work. Based on modes of non-bonded interactions and their calculated interaction strengths by means of the advanced double hybrid DFT method B2PLYP, the molecular recognition of PKI drugs in the ATP-binding pockets was systematically analyzed. It was found that (1) all the FDA-approved PKI drugs studied here form one or more hydrogen bond(s) with the backbone amide N, O atoms in the hinge region of the ATP binding site, mimicking the adenine base; (2) all the FDA-approved PKI drugs feature two or more aromatic rings. The latter reach far and deep into the hydrophobic regions I and II, forming multiple CH-π interactions with aliphatic residues L(3), V(11), A(15), V(36), G(51), L(77) and π-π stacking interactions with aromatic residues F(47) and F(82), but ATP itself does not utilize these regions extensively; (3) all FDA-approved PKI drugs studied here have one thing in common, i.e., they frequently formed non-bonded interactions with a total of 12 residues L(3),V(11), A(15), K(17), E(24),V(36),T(45), F(47), G(51), L(77), D(81) and F(82) in the ATP binding. Many of those 12 commonly involved residues are highly conserved residues with important structural and catalytic functional roles. K(17) and E(24) are the two highly conserved residues crucial for the catalytic function of kinases. D(81) and F(82) belong to the DFG motif; T(45) was dubbed the gate keeper residue. F(47) is located on the hinge region and G(51) sits on the linker that connects the hinge to the αD-helix. It is this targeting of highly conserved residues in protein kinases that led to promiscuous PKI drugs that lack selectivity. Although the formation of hydrogen bond(s) with the backbone of the hinge gives PKI drugs the added binding affinity and the much-needed directionality, selectivity is sacrificed. That is why so many FDA-approved PKI drugs are known to have multiple targets. Moreover, off-target-mediated toxicity caused by a lack of selectivity was one of the major challenges facing the PKI drug discovery community. This work suggests a road map for future PKI drug design, i.e., targeting non-conserved residues in the ATP binding pocket to gain better selectivity so as to avoid off-target-mediated toxicity.

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20

Zhu, Yan, and Xiche Hu. "Molecular Recognition of FDA-Approved Small Molecule Protein Kinase Drugs in Protein Kinases." Molecules 27, no. 20 (October 21, 2022): 7124. http://dx.doi.org/10.3390/molecules27207124.

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Abstract:

Protein kinases are key enzymes that catalyze the covalent phosphorylation of substrates via the transfer of the γ-phosphate of ATP, playing a crucial role in cellular proliferation, differentiation, and various cell regulatory processes. Due to their pivotal cellular role, the aberrant function of kinases has been associated with cancers and many other diseases. Consequently, competitive inhibition of the ATP binding site of protein kinases has emerged as an effective means of curing these diseases. Decades of intense development of protein kinase inhibitors (PKIs) resulted in 71 FDA-approved PKI drugs that target dozens of protein kinases for the treatment of various diseases. How do FDA-approved protein kinase inhibitor PKI drugs compete with ATP in their own binding pocket? This is the central question we attempt to address in this work. Based on modes of non-bonded interactions and their calculated interaction strengths by means of the advanced double hybrid DFT method B2PLYP, the molecular recognition of PKI drugs in the ATP-binding pockets was systematically analyzed. It was found that (1) all the FDA-approved PKI drugs studied here form one or more hydrogen bond(s) with the backbone amide N, O atoms in the hinge region of the ATP binding site, mimicking the adenine base; (2) all the FDA-approved PKI drugs feature two or more aromatic rings. The latter reach far and deep into the hydrophobic regions I and II, forming multiple CH-π interactions with aliphatic residues L(3), V(11), A(15), V(36), G(51), L(77) and π-π stacking interactions with aromatic residues F(47) and F(82), but ATP itself does not utilize these regions extensively; (3) all FDA-approved PKI drugs studied here have one thing in common, i.e., they frequently formed non-bonded interactions with a total of 12 residues L(3),V(11), A(15), K(17), E(24),V(36),T(45), F(47), G(51), L(77), D(81) and F(82) in the ATP binding. Many of those 12 commonly involved residues are highly conserved residues with important structural and catalytic functional roles. K(17) and E(24) are the two highly conserved residues crucial for the catalytic function of kinases. D(81) and F(82) belong to the DFG motif; T(45) was dubbed the gate keeper residue. F(47) is located on the hinge region and G(51) sits on the linker that connects the hinge to the αD-helix. It is this targeting of highly conserved residues in protein kinases that led to promiscuous PKI drugs that lack selectivity. Although the formation of hydrogen bond(s) with the backbone of the hinge gives PKI drugs the added binding affinity and the much-needed directionality, selectivity is sacrificed. That is why so many FDA-approved PKI drugs are known to have multiple targets. Moreover, off-target-mediated toxicity caused by a lack of selectivity was one of the major challenges facing the PKI drug discovery community. This work suggests a road map for future PKI drug design, i.e., targeting non-conserved residues in the ATP binding pocket to gain better selectivity so as to avoid off-target-mediated toxicity.

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21

Zhu, Yan, and Xiche Hu. "Molecular Recognition of FDA-Approved Small Molecule Protein Kinase Drugs in Protein Kinases." Molecules 27, no. 20 (October 21, 2022): 7124. http://dx.doi.org/10.3390/molecules27207124.

Full text

Abstract:

Protein kinases are key enzymes that catalyze the covalent phosphorylation of substrates via the transfer of the γ-phosphate of ATP, playing a crucial role in cellular proliferation, differentiation, and various cell regulatory processes. Due to their pivotal cellular role, the aberrant function of kinases has been associated with cancers and many other diseases. Consequently, competitive inhibition of the ATP binding site of protein kinases has emerged as an effective means of curing these diseases. Decades of intense development of protein kinase inhibitors (PKIs) resulted in 71 FDA-approved PKI drugs that target dozens of protein kinases for the treatment of various diseases. How do FDA-approved protein kinase inhibitor PKI drugs compete with ATP in their own binding pocket? This is the central question we attempt to address in this work. Based on modes of non-bonded interactions and their calculated interaction strengths by means of the advanced double hybrid DFT method B2PLYP, the molecular recognition of PKI drugs in the ATP-binding pockets was systematically analyzed. It was found that (1) all the FDA-approved PKI drugs studied here form one or more hydrogen bond(s) with the backbone amide N, O atoms in the hinge region of the ATP binding site, mimicking the adenine base; (2) all the FDA-approved PKI drugs feature two or more aromatic rings. The latter reach far and deep into the hydrophobic regions I and II, forming multiple CH-π interactions with aliphatic residues L(3), V(11), A(15), V(36), G(51), L(77) and π-π stacking interactions with aromatic residues F(47) and F(82), but ATP itself does not utilize these regions extensively; (3) all FDA-approved PKI drugs studied here have one thing in common, i.e., they frequently formed non-bonded interactions with a total of 12 residues L(3),V(11), A(15), K(17), E(24),V(36),T(45), F(47), G(51), L(77), D(81) and F(82) in the ATP binding. Many of those 12 commonly involved residues are highly conserved residues with important structural and catalytic functional roles. K(17) and E(24) are the two highly conserved residues crucial for the catalytic function of kinases. D(81) and F(82) belong to the DFG motif; T(45) was dubbed the gate keeper residue. F(47) is located on the hinge region and G(51) sits on the linker that connects the hinge to the αD-helix. It is this targeting of highly conserved residues in protein kinases that led to promiscuous PKI drugs that lack selectivity. Although the formation of hydrogen bond(s) with the backbone of the hinge gives PKI drugs the added binding affinity and the much-needed directionality, selectivity is sacrificed. That is why so many FDA-approved PKI drugs are known to have multiple targets. Moreover, off-target-mediated toxicity caused by a lack of selectivity was one of the major challenges facing the PKI drug discovery community. This work suggests a road map for future PKI drug design, i.e., targeting non-conserved residues in the ATP binding pocket to gain better selectivity so as to avoid off-target-mediated toxicity.

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22

Zhu, Yan, and Xiche Hu. "Molecular Recognition of FDA-Approved Small Molecule Protein Kinase Drugs in Protein Kinases." Molecules 27, no. 20 (October 21, 2022): 7124. http://dx.doi.org/10.3390/molecules27207124.

Full text

Abstract:

Protein kinases are key enzymes that catalyze the covalent phosphorylation of substrates via the transfer of the γ-phosphate of ATP, playing a crucial role in cellular proliferation, differentiation, and various cell regulatory processes. Due to their pivotal cellular role, the aberrant function of kinases has been associated with cancers and many other diseases. Consequently, competitive inhibition of the ATP binding site of protein kinases has emerged as an effective means of curing these diseases. Decades of intense development of protein kinase inhibitors (PKIs) resulted in 71 FDA-approved PKI drugs that target dozens of protein kinases for the treatment of various diseases. How do FDA-approved protein kinase inhibitor PKI drugs compete with ATP in their own binding pocket? This is the central question we attempt to address in this work. Based on modes of non-bonded interactions and their calculated interaction strengths by means of the advanced double hybrid DFT method B2PLYP, the molecular recognition of PKI drugs in the ATP-binding pockets was systematically analyzed. It was found that (1) all the FDA-approved PKI drugs studied here form one or more hydrogen bond(s) with the backbone amide N, O atoms in the hinge region of the ATP binding site, mimicking the adenine base; (2) all the FDA-approved PKI drugs feature two or more aromatic rings. The latter reach far and deep into the hydrophobic regions I and II, forming multiple CH-π interactions with aliphatic residues L(3), V(11), A(15), V(36), G(51), L(77) and π-π stacking interactions with aromatic residues F(47) and F(82), but ATP itself does not utilize these regions extensively; (3) all FDA-approved PKI drugs studied here have one thing in common, i.e., they frequently formed non-bonded interactions with a total of 12 residues L(3),V(11), A(15), K(17), E(24),V(36),T(45), F(47), G(51), L(77), D(81) and F(82) in the ATP binding. Many of those 12 commonly involved residues are highly conserved residues with important structural and catalytic functional roles. K(17) and E(24) are the two highly conserved residues crucial for the catalytic function of kinases. D(81) and F(82) belong to the DFG motif; T(45) was dubbed the gate keeper residue. F(47) is located on the hinge region and G(51) sits on the linker that connects the hinge to the αD-helix. It is this targeting of highly conserved residues in protein kinases that led to promiscuous PKI drugs that lack selectivity. Although the formation of hydrogen bond(s) with the backbone of the hinge gives PKI drugs the added binding affinity and the much-needed directionality, selectivity is sacrificed. That is why so many FDA-approved PKI drugs are known to have multiple targets. Moreover, off-target-mediated toxicity caused by a lack of selectivity was one of the major challenges facing the PKI drug discovery community. This work suggests a road map for future PKI drug design, i.e., targeting non-conserved residues in the ATP binding pocket to gain better selectivity so as to avoid off-target-mediated toxicity.

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23

Zhu, Yan, and Xiche Hu. "Molecular Recognition of FDA-Approved Small Molecule Protein Kinase Drugs in Protein Kinases." Molecules 27, no. 20 (October 21, 2022): 7124. http://dx.doi.org/10.3390/molecules27207124.

Full text

Abstract:

Protein kinases are key enzymes that catalyze the covalent phosphorylation of substrates via the transfer of the γ-phosphate of ATP, playing a crucial role in cellular proliferation, differentiation, and various cell regulatory processes. Due to their pivotal cellular role, the aberrant function of kinases has been associated with cancers and many other diseases. Consequently, competitive inhibition of the ATP binding site of protein kinases has emerged as an effective means of curing these diseases. Decades of intense development of protein kinase inhibitors (PKIs) resulted in 71 FDA-approved PKI drugs that target dozens of protein kinases for the treatment of various diseases. How do FDA-approved protein kinase inhibitor PKI drugs compete with ATP in their own binding pocket? This is the central question we attempt to address in this work. Based on modes of non-bonded interactions and their calculated interaction strengths by means of the advanced double hybrid DFT method B2PLYP, the molecular recognition of PKI drugs in the ATP-binding pockets was systematically analyzed. It was found that (1) all the FDA-approved PKI drugs studied here form one or more hydrogen bond(s) with the backbone amide N, O atoms in the hinge region of the ATP binding site, mimicking the adenine base; (2) all the FDA-approved PKI drugs feature two or more aromatic rings. The latter reach far and deep into the hydrophobic regions I and II, forming multiple CH-π interactions with aliphatic residues L(3), V(11), A(15), V(36), G(51), L(77) and π-π stacking interactions with aromatic residues F(47) and F(82), but ATP itself does not utilize these regions extensively; (3) all FDA-approved PKI drugs studied here have one thing in common, i.e., they frequently formed non-bonded interactions with a total of 12 residues L(3),V(11), A(15), K(17), E(24),V(36),T(45), F(47), G(51), L(77), D(81) and F(82) in the ATP binding. Many of those 12 commonly involved residues are highly conserved residues with important structural and catalytic functional roles. K(17) and E(24) are the two highly conserved residues crucial for the catalytic function of kinases. D(81) and F(82) belong to the DFG motif; T(45) was dubbed the gate keeper residue. F(47) is located on the hinge region and G(51) sits on the linker that connects the hinge to the αD-helix. It is this targeting of highly conserved residues in protein kinases that led to promiscuous PKI drugs that lack selectivity. Although the formation of hydrogen bond(s) with the backbone of the hinge gives PKI drugs the added binding affinity and the much-needed directionality, selectivity is sacrificed. That is why so many FDA-approved PKI drugs are known to have multiple targets. Moreover, off-target-mediated toxicity caused by a lack of selectivity was one of the major challenges facing the PKI drug discovery community. This work suggests a road map for future PKI drug design, i.e., targeting non-conserved residues in the ATP binding pocket to gain better selectivity so as to avoid off-target-mediated toxicity.

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24

Zhu, Yan, and Xiche Hu. "Molecular Recognition of FDA-Approved Small Molecule Protein Kinase Drugs in Protein Kinases." Molecules 27, no. 20 (October 21, 2022): 7124. http://dx.doi.org/10.3390/molecules27207124.

Full text

Abstract:

Protein kinases are key enzymes that catalyze the covalent phosphorylation of substrates via the transfer of the γ-phosphate of ATP, playing a crucial role in cellular proliferation, differentiation, and various cell regulatory processes. Due to their pivotal cellular role, the aberrant function of kinases has been associated with cancers and many other diseases. Consequently, competitive inhibition of the ATP binding site of protein kinases has emerged as an effective means of curing these diseases. Decades of intense development of protein kinase inhibitors (PKIs) resulted in 71 FDA-approved PKI drugs that target dozens of protein kinases for the treatment of various diseases. How do FDA-approved protein kinase inhibitor PKI drugs compete with ATP in their own binding pocket? This is the central question we attempt to address in this work. Based on modes of non-bonded interactions and their calculated interaction strengths by means of the advanced double hybrid DFT method B2PLYP, the molecular recognition of PKI drugs in the ATP-binding pockets was systematically analyzed. It was found that (1) all the FDA-approved PKI drugs studied here form one or more hydrogen bond(s) with the backbone amide N, O atoms in the hinge region of the ATP binding site, mimicking the adenine base; (2) all the FDA-approved PKI drugs feature two or more aromatic rings. The latter reach far and deep into the hydrophobic regions I and II, forming multiple CH-π interactions with aliphatic residues L(3), V(11), A(15), V(36), G(51), L(77) and π-π stacking interactions with aromatic residues F(47) and F(82), but ATP itself does not utilize these regions extensively; (3) all FDA-approved PKI drugs studied here have one thing in common, i.e., they frequently formed non-bonded interactions with a total of 12 residues L(3),V(11), A(15), K(17), E(24),V(36),T(45), F(47), G(51), L(77), D(81) and F(82) in the ATP binding. Many of those 12 commonly involved residues are highly conserved residues with important structural and catalytic functional roles. K(17) and E(24) are the two highly conserved residues crucial for the catalytic function of kinases. D(81) and F(82) belong to the DFG motif; T(45) was dubbed the gate keeper residue. F(47) is located on the hinge region and G(51) sits on the linker that connects the hinge to the αD-helix. It is this targeting of highly conserved residues in protein kinases that led to promiscuous PKI drugs that lack selectivity. Although the formation of hydrogen bond(s) with the backbone of the hinge gives PKI drugs the added binding affinity and the much-needed directionality, selectivity is sacrificed. That is why so many FDA-approved PKI drugs are known to have multiple targets. Moreover, off-target-mediated toxicity caused by a lack of selectivity was one of the major challenges facing the PKI drug discovery community. This work suggests a road map for future PKI drug design, i.e., targeting non-conserved residues in the ATP binding pocket to gain better selectivity so as to avoid off-target-mediated toxicity.

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25

Zhu, Yan, and Xiche Hu. "Molecular Recognition of FDA-Approved Small Molecule Protein Kinase Drugs in Protein Kinases." Molecules 27, no. 20 (October 21, 2022): 7124. http://dx.doi.org/10.3390/molecules27207124.

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Protein kinases are key enzymes that catalyze the covalent phosphorylation of substrates via the transfer of the γ-phosphate of ATP, playing a crucial role in cellular proliferation, differentiation, and various cell regulatory processes. Due to their pivotal cellular role, the aberrant function of kinases has been associated with cancers and many other diseases. Consequently, competitive inhibition of the ATP binding site of protein kinases has emerged as an effective means of curing these diseases. Decades of intense development of protein kinase inhibitors (PKIs) resulted in 71 FDA-approved PKI drugs that target dozens of protein kinases for the treatment of various diseases. How do FDA-approved protein kinase inhibitor PKI drugs compete with ATP in their own binding pocket? This is the central question we attempt to address in this work. Based on modes of non-bonded interactions and their calculated interaction strengths by means of the advanced double hybrid DFT method B2PLYP, the molecular recognition of PKI drugs in the ATP-binding pockets was systematically analyzed. It was found that (1) all the FDA-approved PKI drugs studied here form one or more hydrogen bond(s) with the backbone amide N, O atoms in the hinge region of the ATP binding site, mimicking the adenine base; (2) all the FDA-approved PKI drugs feature two or more aromatic rings. The latter reach far and deep into the hydrophobic regions I and II, forming multiple CH-π interactions with aliphatic residues L(3), V(11), A(15), V(36), G(51), L(77) and π-π stacking interactions with aromatic residues F(47) and F(82), but ATP itself does not utilize these regions extensively; (3) all FDA-approved PKI drugs studied here have one thing in common, i.e., they frequently formed non-bonded interactions with a total of 12 residues L(3),V(11), A(15), K(17), E(24),V(36),T(45), F(47), G(51), L(77), D(81) and F(82) in the ATP binding. Many of those 12 commonly involved residues are highly conserved residues with important structural and catalytic functional roles. K(17) and E(24) are the two highly conserved residues crucial for the catalytic function of kinases. D(81) and F(82) belong to the DFG motif; T(45) was dubbed the gate keeper residue. F(47) is located on the hinge region and G(51) sits on the linker that connects the hinge to the αD-helix. It is this targeting of highly conserved residues in protein kinases that led to promiscuous PKI drugs that lack selectivity. Although the formation of hydrogen bond(s) with the backbone of the hinge gives PKI drugs the added binding affinity and the much-needed directionality, selectivity is sacrificed. That is why so many FDA-approved PKI drugs are known to have multiple targets. Moreover, off-target-mediated toxicity caused by a lack of selectivity was one of the major challenges facing the PKI drug discovery community. This work suggests a road map for future PKI drug design, i.e., targeting non-conserved residues in the ATP binding pocket to gain better selectivity so as to avoid off-target-mediated toxicity.

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Berwanger, Anja, Susanne Eyrisch, Inge Schuster, Volkhard Helms, and Rita Bernhardt. "Polyamines: Naturally occurring small molecule modulators of electrostatic protein–protein interactions." Journal of Inorganic Biochemistry 104, no. 2 (February 2010): 118–25. http://dx.doi.org/10.1016/j.jinorgbio.2009.10.007.

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Arkin, Michelle R., and James A. Wells. "Small-molecule inhibitors of protein–protein interactions: progressing towards the dream." Nature Reviews Drug Discovery 3, no. 4 (April 2004): 301–17. http://dx.doi.org/10.1038/nrd1343.

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Arkin, Michelle R., Yinyan Tang, and James A. Wells. "Small-Molecule Inhibitors of Protein-Protein Interactions: Progressing toward the Reality." Chemistry & Biology 21, no. 9 (September 2014): 1102–14. http://dx.doi.org/10.1016/j.chembiol.2014.09.001.

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Hashimoto, Chie, and Jutta Eichler. "Turning Peptide Ligands into Small-Molecule Inhibitors of Protein-Protein Interactions." ChemBioChem 16, no. 13 (July 23, 2015): 1855–56. http://dx.doi.org/10.1002/cbic.201500298.

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Uvebrant, Kristina, Dorthe Da Graça Thrige, Anna Rosén, Mats Åkesson, Helena Berg, Björn Walse, and Per Björk. "Discovery of Selective Small-Molecule CD80 Inhibitors." Journal of Biomolecular Screening 12, no. 4 (March 22, 2007): 464–72. http://dx.doi.org/10.1177/1087057107300464.

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Protein-protein interactions are widely found in biological systems controlling diverse cellular events. Because these interactions are implicated in many diseases such as autoimmunity and cancer, regulation of protein-protein interactions provides ideal targets for drug intervention. The CD80-CD28 costimulatory pathway plays a critical role in regulation of the immune response and thus constitutes an attractive target for therapeutic manipulation of autoimmune diseases. The objective of this study is to identify small compounds disrupting these pivotal protein-protein interactions. Compounds that specifically blocked binding of CD80 to CD28 were identified using a strategy involving a cell-based scintillation proximity assay as the initial step. Secondary screening (e.g., by analyzing the direct binding of these compounds to the target immobilized on a biosensor surface) revealed that these compounds are highly selective CD80 binders. Screening of structurally related derivatives led to the identification of the chemical features required for inhibition of the CD80-CD28 interaction. In addition, the optimization process led to a 10-fold increase in binding affinity of the CD80 inhibitors. Using this approach, the authors identify low-molecular-weight compounds that specifically and with high potency inhibit the interaction between CD80 and CD28. These compounds serve as promising starting points for further development of CD80 inhibitors as potential immunomodulatory drugs. ( Journal of Biomolecular Screening 2007:464-472)

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Pedram Fatemi, Roya, Sultan Salah-Uddin, Farzaneh Modarresi, Nathalie Khoury, Claes Wahlestedt, and Mohammad Ali Faghihi. "Screening for Small-Molecule Modulators of Long Noncoding RNA-Protein Interactions Using AlphaScreen." Journal of Biomolecular Screening 20, no. 9 (July 14, 2015): 1132–41. http://dx.doi.org/10.1177/1087057115594187.

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Long non–protein coding RNAs (lncRNAs) are an important class of molecules that help orchestrate key cellular events. Although their functional roles in cells are not well understood, thousands of lncRNAs and a number of possible mechanisms by which they act have been reported. LncRNAs can exert their regulatory function in cells by interacting with epigenetic enzymes. In this study, we developed a tool to study lncRNA-protein interactions for high-throughput screening of small-molecule modulators using AlphaScreen technology. We tested the interaction of two lncRNAs: brain-derived neurotrophic factor antisense ( BDNF-AS) and Hox transcript antisense RNA ( HOTAIR), with Enhancer of zeste homolog 2 (EZH2), a histone methyltransferase against a phytochemical library, to look for small-molecule inhibitors that can alter the expression of downstream target genes. We identified ellipticine, a compound that up-regulates BDNF transcription. Our study shows the feasibility of using high-throughput screening to identify modulators of lncRNA-protein interactions and paves the road for targeting lncRNAs that are dysregulated in human disorders using small-molecule therapies.

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Huang, Da, Aaron D. Robison, Yiquan Liu, and Paul S. Cremer. "Monitoring protein–small molecule interactions by local pH modulation." Biosensors and Bioelectronics 38, no. 1 (October 2012): 74–78. http://dx.doi.org/10.1016/j.bios.2012.05.023.

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McFedries, Amanda, Adam Schwaid, and Alan Saghatelian. "Methods for the Elucidation of Protein-Small Molecule Interactions." Chemistry & Biology 20, no. 5 (May 2013): 667–73. http://dx.doi.org/10.1016/j.chembiol.2013.04.008.

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34

HAYASHI, YOSHIHARU, MIME KOBAYASHI, KATSUYOSHI SAKAGUCHI, NAO IWATA, MASAKI KOBAYASHI, YO KIKUCHI, and YOSHIMASA TAKAHASHI. "PROTEIN CLASSIFICATION USING COMPARATIVE MOLECULAR INTERACTION PROFILE ANALYSIS SYSTEM." Journal of Bioinformatics and Computational Biology 02, no. 03 (September 2004): 497–510. http://dx.doi.org/10.1142/s0219720004000703.

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We recently introduced a new molecular description factor, interaction profile Factor (IPF) that is useful for evaluating molecular interactions. IPF is a data set of interaction energies calculated by the Comparative Molecular Interaction Profile Analysis system (CoMIPA). CoMIPA utilizes AutoDock 3.0 docking program, and the system has shown to be a powerful tool in clustering the interacting properties between small molecules and proteins. In this report, we describe the application of CoMIPA for protein clustering. A sample set of 15 proteins that share less than 20% homology and have no common functional motifs in primary structure were chosen. Using CoMIPA, we were able to cluster proteins that bound to the same small molecule. Other structural homology-based clustering programs such as PSI-BLAST or PFAM were unable to achieve the same classification. The results are striking because it is difficult to find any common features in the active sites of these proteins that share the same ligand. CoMIPA adds new dimensions for protein classification and has the potential to be a helpful tool in predicting and analyzing molecular interactions.

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Bai, Bing, Rongfeng Zou, H. C. Stephen Chan, Hongchun Li, and Shuguang Yuan. "MolADI: A Web Server for Automatic Analysis of Protein–Small Molecule Dynamic Interactions." Molecules 26, no. 15 (July 30, 2021): 4625. http://dx.doi.org/10.3390/molecules26154625.

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Protein–ligand interaction analysis is important for drug discovery and rational protein design. The existing online tools adopt only a single conformation of the complex structure for calculating and displaying the interactions, whereas both protein residues and ligand molecules are flexible to some extent. The interactions evolved with time in the trajectories are of greater interest. MolADI is a user-friendly online tool which analyzes the protein–ligand interactions in detail for either a single structure or a trajectory. Interactions can be viewed easily with both 2D graphs and 3D representations. MolADI is available as a web application.

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36

C. Fry, David. "Small-Molecule Inhibitors of Protein-Protein Interactions: How to Mimic a Protein Partner." Current Pharmaceutical Design 18, no. 30 (August 23, 2012): 4679–84. http://dx.doi.org/10.2174/138161212802651634.

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Xin, Dongyue, Andreas Holzenburg, and Kevin Burgess. "Small molecule probes that perturb a protein–protein interface in antithrombin." Chem. Sci. 5, no. 12 (2014): 4914–21. http://dx.doi.org/10.1039/c4sc01295j.

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Small molecule probes for perturbing protein–protein interactions (PPIs) in vitro can be useful if they cause the target proteins to undergo biomedically relevant changes to their tertiary and quaternary structures.

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38

Cossins, Benjamin, and Alastair Lawson. "Small Molecule Targeting of Protein–Protein Interactions through Allosteric Modulation of Dynamics." Molecules 20, no. 9 (September 10, 2015): 16435–45. http://dx.doi.org/10.3390/molecules200916435.

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39

Horswill, A. R., S. N. Savinov, and S. J. Benkovic. "A systematic method for identifying small-molecule modulators of protein-protein interactions." Proceedings of the National Academy of Sciences 101, no. 44 (October 21, 2004): 15591–96. http://dx.doi.org/10.1073/pnas.0406999101.

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40

Lee, Wan-Hung, Zhili Xu, Nicole M. Ashpole, Andy Hudmon, Pushkar M. Kulkarni, Ganesh A. Thakur, Yvonne Y. Lai, and Andrea G. Hohmann. "Small molecule inhibitors of PSD95-nNOS protein–protein interactions as novel analgesics." Neuropharmacology 97 (October 2015): 464–75. http://dx.doi.org/10.1016/j.neuropharm.2015.05.038.

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41

Arkin, Michelle. "Finding Small Molecule Ligands for Protein-Protein Interactions and Other “Undruggable” Targets." Biophysical Journal 98, no. 3 (January 2010): 411a. http://dx.doi.org/10.1016/j.bpj.2009.12.2216.

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42

Guo, Wenxing, John A. Wisniewski, and Haitao Ji. "Hot spot-based design of small-molecule inhibitors for protein–protein interactions." Bioorganic & Medicinal Chemistry Letters 24, no. 11 (June 2014): 2546–54. http://dx.doi.org/10.1016/j.bmcl.2014.03.095.

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43

Cummings, Christopher G., and Andrew D. Hamilton. "Disrupting protein–protein interactions with non-peptidic, small molecule α-helix mimetics." Current Opinion in Chemical Biology 14, no. 3 (June 2010): 341–46. http://dx.doi.org/10.1016/j.cbpa.2010.04.001.

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44

Xu, David, Khuchtumur Bum-Erdene, Yubing Si, Donghui Zhou, Mona K. Ghozayel, and Samy O. Meroueh. "Mimicking Intermolecular Interactions of Tight Protein-Protein Complexes for Small-Molecule Antagonists." ChemMedChem 12, no. 21 (October 23, 2017): 1794–809. http://dx.doi.org/10.1002/cmdc.201700572.

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45

Pagano, Katiuscia, Elisa Longhi, Henriette Molinari, Giulia Taraboletti, and Laura Ragona. "Inhibition of FGFR Signaling by Targeting FGF/FGFR Extracellular Interactions: Towards the Comprehension of the Molecular Mechanism through NMR Approaches." International Journal of Molecular Sciences 23, no. 18 (September 17, 2022): 10860. http://dx.doi.org/10.3390/ijms231810860.

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NMR-based approaches play a pivotal role in providing insight into molecular recognition mechanisms, affording the required atomic-level description and enabling the identification of promising inhibitors of protein–protein interactions. The aberrant activation of the fibroblast growth factor 2 (FGF2)/fibroblast growth factor receptor (FGFR) signaling pathway drives several pathologies, including cancer development, metastasis formation, resistance to therapy, angiogenesis-driven pathologies, vascular diseases, and viral infections. Most FGFR inhibitors targeting the intracellular ATP binding pocket of FGFR have adverse effects, such as limited specificity and relevant toxicity. A viable alternative is represented by targeting the FGF/FGFR extracellular interactions. We previously identified a few small-molecule inhibitors acting extracellularly, targeting FGFR or FGF. We have now built a small library of natural and synthetic molecules that potentially act as inhibitors of FGF2/FGFR interactions to improve our understanding of the molecular mechanisms of inhibitory activity. Here, we provide a comparative analysis of the interaction mode of small molecules with the FGF2/FGFR complex and the single protein domains. DOSY and residue-level NMR analysis afforded insights into the capability of the potential inhibitors to destabilize complex formation, highlighting different mechanisms of inhibition of FGF2-induced cell proliferation.

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46

Stringer, Bas, Hans de Ferrante, Sanne Abeln, Jaap Heringa, K. Anton Feenstra, and Reza Haydarlou. "PIPENN: protein interface prediction from sequence with an ensemble of neural nets." Bioinformatics 38, no. 8 (February 12, 2022): 2111–18. http://dx.doi.org/10.1093/bioinformatics/btac071.

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Abstract Motivation The interactions between proteins and other molecules are essential to many biological and cellular processes. Experimental identification of interface residues is a time-consuming, costly and challenging task, while protein sequence data are ubiquitous. Consequently, many computational and machine learning approaches have been developed over the years to predict such interface residues from sequence. However, the effectiveness of different Deep Learning (DL) architectures and learning strategies for protein–protein, protein–nucleotide and protein–small molecule interface prediction has not yet been investigated in great detail. Therefore, we here explore the prediction of protein interface residues using six DL architectures and various learning strategies with sequence-derived input features. Results We constructed a large dataset dubbed BioDL, comprising protein–protein interactions from the PDB, and DNA/RNA and small molecule interactions from the BioLip database. We also constructed six DL architectures, and evaluated them on the BioDL benchmarks. This shows that no single architecture performs best on all instances. An ensemble architecture, which combines all six architectures, does consistently achieve peak prediction accuracy. We confirmed these results on the published benchmark set by Zhang and Kurgan (ZK448), and on our own existing curated homo- and heteromeric protein interaction dataset. Our PIPENN sequence-based ensemble predictor outperforms current state-of-the-art sequence-based protein interface predictors on ZK448 on all interaction types, achieving an AUC-ROC of 0.718 for protein–protein, 0.823 for protein–nucleotide and 0.842 for protein–small molecule. Availability and implementation Source code and datasets are available at https://github.com/ibivu/pipenn/. Supplementary information Supplementary data are available at Bioinformatics online.

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47

Euston, Stephen. "Modelling of Protein–Polyphenol Interactions." Medical Sciences Forum 2, no. 1 (December 3, 2020): 22. http://dx.doi.org/10.3390/cahd2020-08893.

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The interaction between proteins and polyphenols is known to modify both the bioavailability and bioactivity of dietary polyphenols. Understanding these interactions can facilitate the design of delivery systems for polyphenols in the digestive tract. Molecular modelling of protein–polyphenol and protein–ligand interactions in general has long been used as a way to identify small molecule binding sites on proteins. However, these are often used without a careful consideration of the assumptions used and limitations of these methods, and how this affects the accuracy of the predictions. In this paper, two common methods for predicting binding site location and binding energy, molecular dynamics simulation and molecular docking, will be discussed. The simplifications and assumptions implicit in these approaches, as well as ways to improve their predictions will be covered.

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48

Yamaguchi, A. "Het-PDB Navi.: A Database for Protein-Small Molecule Interactions." Journal of Biochemistry 135, no. 1 (January 1, 2004): 79–84. http://dx.doi.org/10.1093/jb/mvh009.

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49

Lenz, Thomas, and Kai Stühler. "Small Molecule Arranged Thermal Proximity Coaggregation (smarTPCA)—A Novel Approach to Characterize Protein–Protein Interactions in Living Cells by Similar Isothermal Dose–Responses." International Journal of Molecular Sciences 23, no. 10 (May 17, 2022): 5605. http://dx.doi.org/10.3390/ijms23105605.

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Chemical biology and the application of small molecules has proven to be a potent perturbation strategy, especially for the functional elucidation of proteins, their networks, and regulators. In recent years, the cellular thermal shift assay (CETSA) and its proteome-wide extension, thermal proteome profiling (TPP), have proven to be effective tools for identifying interactions of small molecules with their target proteins, as well as off-targets in living cells. Here, we asked the question whether isothermal dose–response (ITDR) CETSA can be exploited to characterize secondary effects downstream of the primary binding event, such as changes in post-translational modifications or protein–protein interactions (PPI). By applying ITDR-CETSA to MAPK14 kinase inhibitor treatment of living HL-60 cells, we found similar dose–responses for the direct inhibitor target and its known interaction partners MAPKAPK2 and MAPKAPK3. Extension of the dose–response similarity comparison to the proteome wide level using TPP with compound concentration range (TPP-CCR) revealed not only the known MAPK14 interaction partners MAPKAPK2 and MAPKAPK3, but also the potentially new intracellular interaction partner MYLK. We are confident that dose-dependent small molecule treatment in combination with ITDR-CETSA or TPP-CCR similarity assessment will not only allow discrimination between primary and secondary effects, but will also provide a novel method to study PPI in living cells without perturbation by protein modification, which we named “small molecule arranged thermal proximity coaggregation” (smarTPCA).

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Xu, David, Shadia I. Jalal, George W. Sledge, and Samy O. Meroueh. "Small-molecule binding sites to explore protein–protein interactions in the cancer proteome." Molecular BioSystems 12, no. 10 (2016): 3067–87. http://dx.doi.org/10.1039/c6mb00231e.

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