Structural and Biofunctional Insights into the Cyclo(Pro-Pro-Phe-Phe-) Scaffold from Experimental and In Silico Studies: Melanoma and Beyond †
Abstract
:1. Introduction
2. Results and Discussion
2.1. Biological Studies
2.1.1. P11 and CLA Decreases Cell Confluence in Concentration and Time Dependent Manner
2.1.2. P11 and CLA Efficiently Decrease Number of Viable Cells in APA Assay
2.1.3. CLA Effectively Induces Cell Death in Concentration Dependent Manner
2.1.4. Assessment of Changes in Cell Morphology after Exposure to Short Peptides
2.2. Molecular and Crystal Structure
2.2.1. Geometry Optimization
Bond Length [Å] | X-ray | B3LYP | |
---|---|---|---|
vacuum | solution | ||
N1—C4 | 1.471 (3) | 1.461 | 1.465 |
C4—C5 | 1.548 (3) | 1.557 | 1.556 |
C5—N2 | 1.358 (3) | 1.373 | 1.365 |
N2—C9 | 1.472 (3) | 1.474 | 1.475 |
C9—C10 | 1.511 (4) | 1.539 | 1.537 |
C10—N3 | 1.335 (3) | 1.362 | 1.350 |
N3—C11 | 1.449 (3) | 1.461 | 1.463 |
C11—C19 | 1.539 (3) | 1.539 | 1.540 |
C19—C20 | 1.515 (3) | 1.523 | 1.522 |
C20—N4 | 1.361 (4) | 1.372 | 1.363 |
N4—C29 | 1.455 (3) | 1.460 | 1.459 |
C29—C30 | 1.533 (3) | 1.548 | 1.551 |
C30—N1 | 1.345 (2) | 1.363 | 1.355 |
N1—C1 | 1.476 (3) | 1.478 | 1.481 |
C1—C2 | 1.532 (3) | 1.540 | 1.539 |
C2—C3 | 1.533 (3) | 1.539 | 1.538 |
C3—C4 | 1.534 (3) | 1.550 | 1.549 |
N2—C6 | 1.474 (3) | 1.475 | 1.480 |
C6—C7 | 1.512 (4) | 1.530 | 1.528 |
C7—C8 | 1.515 (5) | 1.537 | 1.536 |
C8—C9 | 1.545 (3) | 1.559 | 1.559 |
C5—O1 | 1.221 (3) | 1.223 | 1.229 |
C10—O2 | 1.230 (4) | 1.218 | 1.230 |
C20—O3 | 1.227 (4) | 1.220 | 1.229 |
C30—O4 | 1.231 (3) | 1.226 | 1.234 |
Bond angle [°] | |||
C30—N1—C4 | 130.2 (2) | 131.3 | 130.8 |
N1—C4—C5 | 108.8 (2) | 110.1 | 109.8 |
C4—C5—N2 | 117.8 (2) | 118.3 | 118.5 |
C5—N2—C9 | 127.0 (2) | 128.4 | 127.8 |
N2—C9—C10 | 115.7 (2) | 115.0 | 114.9 |
C9—C10—N3 | 117.6 (2) | 115.1 | 115.8 |
C10—N3—C11 | 122.5 (2) | 123.7 | 125.1 |
N3—C11—C19 | 109.6 (2) | 108.8 | 108.7 |
C11—C19—C20 | 109.9 (2) | 110.8 | 110.9 |
C19—C20—N4 | 114.6 (2) | 116.2 | 116.2 |
C20—N4—C29 | 119.9 (2) | 120.9 | 122.0 |
N4—C29—C30 | 114.0 (2) | 113.6 | 113.3 |
C29—C30—N1 | 120.1 (2) | 120.1 | 120.3 |
C1—N1—C30 | 118.6 (2) | 117.5 | 118.2 |
C4—N1—C1 | 109.8 (2) | 111.2 | 110.9 |
N1—C1—C2 | 105.1 (2) | 104.5 | 104.7 |
C1—C2—C3 | 104.3 (2) | 104.6 | 104.7 |
C2—C3—C4 | 102.6 (2) | 102.9 | 102.9 |
C3—C4—N1 | 101.3 (2) | 101.1 | 101.3 |
C3—C4—C5 | 108.0 (2) | 109.7 | 109.7 |
C5—N2—C6 | 120.4 (2) | 120.0 | 120.2 |
C9—N2—C6 | 110.3 (2) | 111.4 | 111.2 |
N2—C6—C7 | 102.7 (2) | 102.5 | 102.5 |
C6—C7—C8 | 101.4 (2) | 103.6 | 103.6 |
C7—C8—C9 | 104.7 (2) | 105.0 | 104.8 |
C8—C9—N2 | 103.2 (2) | 104.2 | 104.3 |
C8—C9—C10 | 108.9 (2) | 109.8 | 110.0 |
C4—C5—O1 | 120.5 (2) | 120.6 | 120.2 |
N2—C5—O1 | 121.5 (2) | 120.9 | 121.2 |
C9—C10—O2 | 117.4 (3) | 119.8 | 119.4 |
N3—C10—O2 | 124.9 (2) | 125.0 | 124.8 |
C19—C20—O3 | 122.5 (2) | 121.3 | 121.3 |
N4—C20—O3 | 122.8 (3) | 122.5 | 122.5 |
C29—C30—O4 | 119.9 (2) | 119.6 | 119.5 |
N1—C30—O4 | 119.8 (2) | 120.1 | 120.0 |
Torsion angle [°] | |||
N1—C4—C5—N2 | 169.4 (2) | 179.1 | 176.5 |
C4—C5—N2—C9 | −1.9 (3) | −12.7 | −9.6 |
C5—N2—C9—C10 | −82.6 (3) | −75.8 | −78.0 |
N2—C9—C10—N3 | −10.8 (3) | −18.7 | −17.8 |
C9—C10—N3—C11 | 177.3 (2) | 170.9 | 172.5 |
C10—N3—C11—C19 | −114.8 (2) | −118.7 | −117.9 |
N3—C11—C19—C20 | 42.2 (3) | 57.6 | 56.6 |
C11—C19—C20—N4 | −120.3 (2) | −127.2 | −127.2 |
C19—C20—N4—C29 | −163.5 (2) | −167.6 | −170.5 |
C20—N4—C29—C30 | −136.6 (3) | −137.1 | −138.5 |
N4—C29—C30—N1 | 59.8 (3) | 59.2 | 62.5 |
C29—C30—N1—C4 | −3.3 (3) | −9.6 | −10.0 |
C30—N1—C4—C5 | −113.6 (2) | −97.6 | −100.6 |
C29—C30—N1—C1 | 161.4 (2) | 169.3 | 165.1 |
C30—N1—C1—C2 | −155.9 (2) | −166.7 | −164.4 |
N1—C1—C2—C3 | 14.7 (2) | 13.4 | 14.0 |
C1—C2—C3—C4 | −34.4 (2) | −32.6 | −32.8 |
C2—C3—C4—N1 | 40.8 (2) | 39.1 | 39.0 |
C2—C3—C4—C5 | −73.5 (2) | −77.1 | −77.0 |
C4—C5—N2—C6 | 159.3 (2) | 160.9 | 160.0 |
C5—N2—C6—C7 | −135.5 (2) | −145.3 | −142.5 |
N2—C6—C7—C8 | −40.8 (3) | −36.3 | −36.6 |
C6—C7—C8—C9 | 38.9 (3) | 30.9 | 31.9 |
C7—C8—C9—N2 | −21.8 (3) | −13.5 | −14.7 |
C7—C8—C9—C10 | −145.3 (2) | −137.1 | −138.4 |
C8—C9—C10—N3 | 104.9 (3) | 98.3 | 99.4 |
N1—C4—C5—O1 | −16.2 (3) | −5.9 | −8.4 |
C9—N2—C5—O1 | −176.2 (2) | 172.3 | 175.3 |
N2—C9—C10—O2 | 172.5 (2) | 163.7 | 164.0 |
C11—N3—C10—O2 | −6.3 (4) | −11.7 | −9.5 |
C11—C19—C20—O3 | 57.0 (3) | 50.8 | 51.1 |
C29—N4—C20—O3 | 19.2 (3) | 14.4 | 11.2 |
N4—C29—C30—O4 | −125.0 (2) | −126.2 | −123.2 |
C4—N1—C30—O4 | −178.5 (2) | 175.8 | 175.7 |
Atom | Vacuum | Solution |
---|---|---|
O4 | −0.632 | −0.684 |
O1 | −0.628 | −0.670 |
N1 | −0.497 | −0.485 |
N2 | −0.546 | −0.531 |
O3 | −0.630 | −0.688 |
N4 | −0.643 | −0.630 |
O2 | −0.617 | −0.688 |
N3 | −0.652 | −0.635 |
C5 | 0.689 | 0.700 |
C1 | −0.167 | −0.165 |
C28 | −0.207 | −0.209 |
C3 | −0.375 | −0.376 |
C24 | −0.185 | −0.203 |
C4 | −0.094 | −0.091 |
C23 | −0.033 | −0.032 |
C22 | −0.401 | −0.401 |
C27 | −0.203 | −0.205 |
C29 | −0.096 | −0.091 |
C30 | 0.693 | 0.704 |
C14 | −0.204 | −0.205 |
C20 | 0.688 | 0.699 |
C9 | −0.088 | −0.089 |
C12 | −0.392 | −0.400 |
C26 | −0.208 | −0.218 |
C2 | −0.399 | −0.399 |
C8 | 0.682 | 0.691 |
C6 | −0.165 | −0.166 |
C13 | −0.031 | −0.032 |
C19 | −0.458 | −0.461 |
C25 | −0.191 | −0.206 |
C18 | −0.188 | −0.206 |
C16 | −0.207 | −0.217 |
C15 | −0.201 | −0.205 |
C11 | −0.021 | −0.011 |
C17 | −0.189 | −0.205 |
C7 | −0.390 | −0.390 |
C8 | −0.376 | −0.374 |
2.2.2. X-ray Diffraction Studies
2.2.3. Long-Range Synthon Aufbau Modules
2.3. Hirshfeld Surface Analysis, and Enrichment Ratios
2.4. Energy Frameworks
2.5. In Silico Pharmacokinetics & Bioactivity Study
3. Materials and Methods
3.1. Chemical Synthesis & Physicochemical Parameters
3.2. Biological Screening
3.2.1. Generation and Culture of Melanoma Cell Lines
3.2.2. APA Assay
3.2.3. Time-Lapse Microscopy (IncuCyte ZOOM)
3.2.4. Flow Cytometry
3.2.5. Statistical Analysis
3.3. Single-Crystal X-ray Diffraction (SC-XRD)
3.4. Computational Methods
3.4.1. Density Functional Theory (DFT) Calculations
3.4.2. Hirshfeld Surface Calculations
3.4.3. In Silico Analysis
4. Conclusions and Future Perspectives
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
ADMET | Absorption: distribution, metabolism, excretion, toxicity |
APA | Acid phosphatase activity |
BOILED | Brain or intestinal estimated |
BBB | Blood–brain barrier |
CNS | Central nervous system |
CLA | Cyclolinopeptide A |
CLC | Cell line cytotoxicity |
CPCM | Conductor-like polarizable continuum model |
CSD | Cambridge Structure Database |
CYP | Cytochrome P450 enzymes |
2D | Two dimensionality |
3D | Three dimensionality |
DFT | Density functional theory |
DMSO | Dimethyl sulfoxide |
de | Distance from HS to the nearest external atom to the surface |
di | Distance from HS to the nearest internal atom to the surface |
dnorm | Normalized distance |
E′dis | Dispersion energy term |
E′ele | Electrostatic energy term |
E′pol | Polarization energy term |
E′rep | Repulsion energy term |
E′tot | Total energy |
EMA | European Medicines Agency |
ER | Enrichment ratio |
EP | Electrostatic potential |
FLEX | Flexibility |
FP | Fingerprint plot |
GI absorption | Gastrointestinal absorption |
HBA | Hydrogen bond acceptor |
HBD | Hydrogen bond donor |
HBSS | Hanks’ balanced salt solution |
hERG | Human ether-a-go-go-related gene |
HOMO | Highest occupied molecular orbital |
HS | Hirshfeld surface |
Ile | Isoleucine |
INSATU | Insaturation |
INSOLU | Insolubility |
LD50 | Lethal dosage |
Leu | Leucine |
LIPO | Lipophilicity |
LSAM | Long-range Aufbau module |
LUMO | Lowest unoccupied molecular orbital |
NBO | Natural bond orbital |
OCT2 | Organic cation transporter 2 |
Pa | Probability of action |
Pi | Probability of inactivity |
PAINS | Pan-assay interference |
POLAR | Polarity |
Pro | Proline |
RCSB PDB | Research Collaboratory for Structural Bioinformatics Protein Data Bank |
SC-XRD | Single crystal X-ray diffraction |
SIZE | Molecular weight |
SMILE | Simplified molecular input line entry specification |
TPSA | Topological polar surface area |
Val | Valine |
WHO | World Health Organization |
References
- Ferlay, J.; Colombet, M.; Soerjomataram, I.; Parkin, D.M.; Piñeros, M.; Znaor, A.; Bray, F. Cancer statistics for the year 2020: An overview. Int. J. Cancer 2021, 149, 778–789. [Google Scholar] [CrossRef] [PubMed]
- Heistein, J.B.; Acharya, U. Malignant Melanoma; StatPearls: Treasure Island, FL, USA, 2021. [Google Scholar]
- Siegel, R.L.; Miller, K.D.; Fuchs, H.E.; Jemal, A. Cancer statistics 2021. CA Cancer J. Clin. 2021, 71, 7–33. [Google Scholar] [CrossRef] [PubMed]
- Carlino, M.S.; Larkin, J.; Long, G.V. Immune checkpoint inhibitors in melanoma. Lancet 2021, 398, 1002–1014. [Google Scholar] [CrossRef]
- Naik, P.P. Cutaneous malignant melanoma: A review of early diagnosis and management. World J. Oncol. 2021, 12, 7–19. [Google Scholar] [CrossRef]
- Domingues, B.; Lopes, J.M.; Soares, P.; Populo, H. Melanoma treatment in review. ImmunoTargets Ther. 2018, 7, 35–49. [Google Scholar] [CrossRef] [Green Version]
- Hamid, O.; Molinero, L.; Bolen, C.R.; Sosman, J.A.; Munoz-Couselo, E.; Kluger, H.M.; McDermott, D.F.; Powderly, J.D.; Sarkar, I.; Ballinger, M.; et al. Safety, clinical activity, and biological correlates of response in patients with metastatic melanoma: Results from a phase I trial of atezolizumab. Clin. Cancer Res. 2019, 25, 6061–6072. [Google Scholar] [CrossRef] [Green Version]
- Marra, A.; Ferrone, C.R.; Fusciello, C.; Scognamiglio, G.; Ferrone, S.; Pepe, S.; Perri, F.; Sabbatino, F. Translational research in cutaneous melanoma: New therapeutic perspectives. Anti-Cancer Agents Med. Chem. 2018, 18, 166–181. [Google Scholar] [CrossRef]
- Vrettos, E.I.; Mezo, G.; Tzakos, A.G. On the design principles of peptide-drug conjugates for targeted drug delivery to the malignant tumor site. Beilstein J. Org. Chem. 2018, 14, 930–954. [Google Scholar] [CrossRef]
- Ragupathy, S.; Brunner, J.; Borchard, G. Short peptide sequence enhances epithelial permeability through interaction with protein kinase C. Eur. J. Pharm. Sci. 2021, 160, 105747. [Google Scholar] [CrossRef]
- Yang, N.J.; Hinner, M.J. Getting across the cell membrane: An overview for small molecules, peptides, and proteins. Methods Mol. Biol. 2015, 1266, 29–53. [Google Scholar]
- Apostolopoulos, V.; Bojarska, J.; Chai, T.T.; Elnagdy, S.; Kaczmarek, K.; Matsoukas, J.; New, R.; Parang, K.; Lopez, O.P.; Parhiz, H.; et al. A Global Review on Short Peptides: Frontiers and Perspectives. Molecules 2021, 26, 430. [Google Scholar] [CrossRef] [PubMed]
- Rezai, T.; Yu, B.; Millhauser, G.L.; Jacobson, M.P.; Lokey, R.S. Testing the conformational hypothesis of passive membranę permeability using synthetic cyclic peptide diastereoisomers. J. Am. Chem. Soc. 2006, 128, 2510–2511. [Google Scholar] [CrossRef] [PubMed]
- Joo, S.H. Cyclic peptides as therapeutic agents and biochemical tools. Biomol. Ther. 2012, 20, 19–26. [Google Scholar] [CrossRef] [Green Version]
- Song, M.; Liu, C.; Chen, S.; Zhang, W. Nanocarrier-Based Drug Delivery for Melanoma Therapeutics. Int. J. Mol. Sci. 2021, 22, 1873. [Google Scholar] [CrossRef] [PubMed]
- Abdalla, M.A.; McGaw, L.J. Natural cyclic peptides as an attractive modality for therapeutics: A mini review. Molecules 2018, 23, 2080. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Valery, C.; Artzner, F.; Paternostre, M. Peptide nanotubes: Molecular organisations, self-assembly mechanisms and applications. Soft Matter 2011, 7, 9583–9594. [Google Scholar] [CrossRef]
- Hsieh, W.H.; Liaw, J. Applications of cyclic peptide nanotubes (cPNTs). J. Food Drug Anal. 2019, 27, 32–47. [Google Scholar] [CrossRef] [Green Version]
- Tang, M.; Fan, J.; Liu, J.; He, L.; He, K. Applications of cyclic peptide nanotubes. Prog. Chem. 2010, 22, 648–653. [Google Scholar]
- Sun, L.; Fan, Z.; Wang, Y.; Huang, Y.; Schmidt, M.; Zhang, M. Tunable synthesis of self-assembled cyclic peptide nanotubes and nanoparticles. Soft Matter 2015, 11, 3822–3831. [Google Scholar] [CrossRef]
- Tiangtrong, P.; Thamwattana, N.; Baowan, D. Modelling water molecules inside cyclic peptide nanotubes. Appl. Nanosci. 2016, 6, 345–357. [Google Scholar] [CrossRef] [Green Version]
- Martin-Algarra, S.; Espinosa, E.; Rubio, J.; López, J.J.L.; Manzano, J.L.; Carrión, L.J.A.; Plazaola, A.; Tanovic, A.; Paz-Ares, L. Phase II study of weekly Kahalalide F in patients with advanced malignant melanoma. Eur. J. Cancer 2009, 45, 732–735. [Google Scholar] [CrossRef] [PubMed]
- Xing, H.; Tong, M.; Jiang, N.; Zhang, X.; Hu, H.; Pan, H.; Li, D. Antitumor bioactive peptides isolated from marine organisms. Clin. Exp. Pharmacol. Physiol. 2017, 44, 1077–1082. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Okinyo-Owiti, D.P.; Dong, Q.; Ling, B.; Jadhav, P.D.; Bauer, R.; Maley, J.M.; Reaney, M.J.T.; Yang, J.; Sammynaiken, R. Evaluating the cytotoxicity of flaxseed orbitides for potential cancer treatment. Toxicol. Rep. 2015, 2, 1014–1018. [Google Scholar] [CrossRef] [Green Version]
- Zimecki, M.; Kaczmarek, K. Effects of Modifications on the Immunosuppressive Properties of Cyclolinopeptide A and Its Analogs in Animal Experimental Models. Molecules 2021, 26, 2538. [Google Scholar] [CrossRef] [PubMed]
- Chiangjong, W.; Chutipongtanate, S.; Hongeng, S. Anticancer peptide: Physicochemical property, functional aspect and trend in clinical application (Review). Int. J. Oncol. 2020, 57, 678–696. [Google Scholar] [CrossRef]
- Zhang, J.N.; Xia, Y.X.; Zhang, H.J. Natural Cyclopeptides as Anticancer Agents in the Last 20 Years. Int. J. Mol. Sci. 2021, 22, 3973. [Google Scholar] [CrossRef]
- Pivarcsik, T.; Dömötör, O.; Mészáros, J.P.; May, N.V.; Spengler, G.; Csuvik, O.; Szatmári, I.; Enyedy, É.A. 8-Hydroxyquinoline-Amino Acid Hybrids and Their Half-Sandwich Rh and Ru Complexes: Synthesis, Anticancer Activities, Solution Chemistry and Interaction with Biomolecules. Int. J. Mol. Sci. 2021, 22, 11281. [Google Scholar] [CrossRef]
- Bojarska, J.; Mieczkowski, A.; Ziora, Z.M.; Skwarczynski, M.; Toth, I.; Shalash, A.O.; Parang, K.; El-Mowafi, S.A.; Mohammed, E.H.M.; Elnagdy, S.; et al. Cyclic Dipeptides: The Biological and Structural Landscape with Special Focus on the Anti-Cancer Proline-Based Scaffold. Biomolecules 2021, 11, 1515. [Google Scholar] [CrossRef]
- Durán-Maldonado, M.X.; Hernández-Padilla, L.; Gallardo-Pérez, J.C.; Díaz-Pérez, A.L.; Martínez-Alcantar, L.; Reyes De la Cruz, H.; Rodríguez-Zavala, J.S.; Pacheco-Rodríguez, G.; Moss, J.; Campos-García, J. Bacterial Cyclodipeptides Target Signal Pathways Involved in Malignant Melanoma. Front. Oncol. 2020, 10, 1111–1127. [Google Scholar] [CrossRef]
- Zimecki, M.; Artym, J.; Kałas, W.; Strządała, L.; Kaleta-Kuratewicz, K.; Kuryszko, J.; Kaszuba, A.; Kaczmarek, K.; Zabrocki, J. Anti-inflammatory activity of a cyclic tetrapeptide in mouse and human experimental models. Pharmaceutics 2020, 12, 1030. [Google Scholar] [CrossRef]
- Zaczyńska, E.; Kaczmarek, K.; Zabrocki, J.; Artym, J.; Zimecki, M. Antiviral activity of a cyclic tetrapeptide. Molecules 2022, 27, 3552. [Google Scholar] [CrossRef] [PubMed]
- Surh, I.; Rundhaug, J.; Pavone, A.; Mikulec, C.; Abel, E.; Fischer, S.M. Upregulation of the EP1 receptor for prostaglandin E2 promotes skin tumor progression. Mol. Carcinog. 2011, 50, 458–468. [Google Scholar] [CrossRef] [PubMed]
- Hester, A.; Salzmann, B.; Rahmeh, M.; Kolben, T.; Czogalla, B.; Ditsch, N.; Mahner, S.; Jeschke, U.; Kolben, T.M. EP3 receptor antagonist L798,106 reduces proliferation and migration of SK-BR-3 breast cancer cells. OncoTargets Ther. 2019, 12, 6053–6068. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kubo, H.; Hosono, K.; Suzuki, T.; Ogawa, Y.; Kato, H.; Kamata, H.; Ito, Y.; Amano, H.; Kato, T.; Sakagami, H.; et al. Host prostaglandin EP3 receptor signaling relevant to tumor-associated lymphangiogenesis. Biomed. Pharmacother. 2010, 64, 101–106. [Google Scholar] [CrossRef]
- Kiraly, A.J.; Soliman, E.; Jenkins, A.; Rukiyah, T.; Van Dross, R.T. Apigenin inhibits COX-2, PGE2, and EP1 and also initiates terminal differentiation in the epidermis of tumor bearing mice. Prostaglandins Leukot. Essent. Fat. Acids 2016, 104, 44–53. [Google Scholar] [CrossRef]
- Allen, F.H. The Cambridge Structural Database: A Quarter of a Million Crystal Structures and Rising. Acta Crystallogr. Sect. B 2002, 58, 380–388. [Google Scholar] [CrossRef]
- Groom, C.R.; Bruno, I.J.; Lightfoot, M.P.; Ward, S.C. The Cambridge Structural Database. Acta Crystallogr. B 2016, 72, 171–179. [Google Scholar] [CrossRef]
- Norgren, A.S.; Büttner, F.; Prabpai, S.; Kongsaeree, P.; Arvidsson, P.I. β‚2-Amino Acids in the Design of Conformationally Homogeneous cyclo-Peptide Scaffolds. J. Org. Chem. 2006, 71, 6814–6821. [Google Scholar] [CrossRef]
- Karle, I.L.; Wieland, T.; Schermer, D.; Ottenheijm, H.C.J. Conformation of the Li-antamanide complex and Na- (Phe 4, Val 6)-antamanide complex in the crystalline state. Proc. Nat. Acad. Sci. USA 1973, 70, 1836–1840. [Google Scholar] [CrossRef] [Green Version]
- Lotter, H.; Rohr, G.; Wieland, T. Conformation of [4-cis,Br-Pro7]-antamanide crystallized from methanol/water. Naturwissenschaften 1984, 71, 46–47. [Google Scholar] [CrossRef]
- Kessler, H.; Bats, J.W.; Lautz, J.; Muller, A. Conformation of Antamanide. Liebigs Ann. Chem. 1989, 1989, 913–928. [Google Scholar] [CrossRef]
- Burley, S.K.; Berman, H.M. RCSB Protein Data Bank: Biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy. Nucleic Acids Res. 2019, 47, D464–D474. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Bojarska, J.; Apostolopouos, V.; Matsoukas, J.; Feehan, J.; Ridgway, H.; Zielenkiewicz, P.; Wolf, W.M. The role of structural biology in pandemic’s puzzles: Amino acids and short peptides as key players. Acta Cryst. A 2021, 77, c794–c795. [Google Scholar] [CrossRef]
- Bojarska, J. Bio-complexes as supermolecules: Towards the design of idealized peptide-based ligands. Acta Cryst. A 2021, 77, c1070. [Google Scholar] [CrossRef]
- Bojarska, J. The first supramolecular consideration on crystal of DFMO—Promising antiviral and anticancer pan-drug. Acta Cryst. A 2021, 77, c1210. [Google Scholar] [CrossRef]
- Bojarska, J. Short Peptides: On the Trail of Future Stem Cell-Based Regenerative Therapies. Int. J. Nutr. Sci. 2021, 6, 104–108. [Google Scholar]
- Bojarska, J.; Złoty, P.; Wolf, W.M. Life cycle assessment as tool for realization of sustainable development goals—Towards sustainable future of the world: Mini review. Acta Innov. 2021, 38, 49–61. [Google Scholar] [CrossRef]
- Bojarska, J.; Remko, M.; Breza, M.; Madura, I.; Fruzinski, A.; Wolf, W.M. A Proline-Based Tectons and Supramolecular Synthons for Drug Design 2.0: A Case Study of ACEI. Pharmaceuticals 2020, 13, 338. [Google Scholar] [CrossRef]
- Bojarska, J.; Remko, M.; Breza, M.; Madura, I.D.; Kaczmarek, K.; Zabrocki, J.; Wolf, W.M. A Supramolecular Approach to Structure-Based Design with A Focus on Synthons Hierarchy in Ornithine-Derived Ligands: Review, Synthesis, Experimental and in Silico Studies. Molecules 2020, 25, 1135. [Google Scholar] [CrossRef] [Green Version]
- Bojarska, J.; Remko, M.; Madura, I.D.; Kaczmarek, K.; Zabrocki, J.; Wolf, W.M. Synthesis, Experimental and in Silico Studies of N-Fluorenylmethoxycarbonyl-O-Tert-Butyl-N-Methyltyrosine, Coupled with CSD Data: A Survey of Interactions in the Crystal Structures of Fmoc-Amino Acids. Acta Crystallogr. C 2020, 76, 328–345. [Google Scholar] [CrossRef] [Green Version]
- Bojarska, J.; Wolf, W.M. Ultra-short cyclo-peptides as bio-inspired therapeutics: Proline-based 2,5-diketopiperazines (DKP). Proceedings 2021, 79, 10. [Google Scholar]
- Bojarska, J.; Remko, M.; Madura, I.D.; Wojciechowski, J.M.; Olczak, A.; Kaczmarek, K.; Zabrocki, J.; Wolf, W.M. Supramolecular Synthon Polymorphism in Modified Amino Acids. Structural, Conformational and Energy Landscapes of N-Benzoyl-2′-Hydroxy-3-Methylisovaline. J. Mol. Struct. 2019, 1190, 11–22. [Google Scholar] [CrossRef]
- Bojarska, J.; Kaczmarek, K.; Zabrocki, J.; Wolf, W.M. Amino Acids: Molecules of Life. Int. J. Nutr. Sci. 2019, 4, 1035–1037. [Google Scholar]
- Bojarska, J.; Kaczmarek, K.; Zabrocki, J.; Wolf, W.M. Supramolecular Synthons as Related to Cooperativity in Biocomplexes: Towards Design and Development of Oligopeptide-Based Modern Drugs and Cosmeceuticals. Nov. Approaches Drug Des. Dev. 2019, 129, 1–27. [Google Scholar]
- Bojarska, J.; Wolf, W.; Zabrocki, J.; Kaczmarek, K.; Remko, M. New Synthons in Supramolecular Chemistry of Short Biologically Active Peptides. Acta Cryst. Sect. A 2019, 75, e588. [Google Scholar] [CrossRef]
- Bojarska, J.; Fruzinski, A.; Sieron, L.; Maniukiewicz, W. The First Insight into the Supramolecular Structures of Popular Drug Repaglinide: Focus on Intermolecular Interactions in Antidiabetic Agents. J. Mol. Struct. 2019, 1179, 411–420. [Google Scholar] [CrossRef]
- Bojarska, J.; Kaczmarek, K.; Zabrocki, J.; Wolf, W.M. Supramolecular Chemistry of Modified Amino Acids and Short Peptides. In Advances in Organic Synthesis; Rahman, A., Ed.; Bentham Science Publishers Ltd.: Sharjah, United Arab Emirates, 2018; Volume 11, pp. 43–107. [Google Scholar]
- Bojarska, J.; Remko, M.; Fruzinski, A.; Maniukiewicz, W. The Experimental and Theoretical Landscape of a New Antiplatelet Drug Ticagrelor: Insight into Supramolecular Architecture Directed by C-H…F, π…π and C-H…π Interactions. J. Mol. Struct. 2018, 1154, 290–300. [Google Scholar] [CrossRef]
- Bojarska, J.; Fruzinski, A.; Maniukiewicz, W. Quantifying Intermolecular Interactions in Solid State Indapamide and Other Popular Diuretic Drugs: Insights from Hirshfeld Surface Study. J. Mol. Struct. 2016, 1116, 22–29. [Google Scholar] [CrossRef]
- Bojarska, J.; Maniukiewicz, W. Investigation of Intermolecular Interactions in Finasteride Drug Crystals in View of X-Ray and Hirshfeld Surface Analysis. J. Mol. Struct. 2015, 1099, 419–426. [Google Scholar] [CrossRef]
- Bojarska, J.; Maniukiewicz, W.; Fruzinski, A.; Sieron, L.; Remko, M. Captopril and its Dimer Captopril Disulfide: Comparative Structural and Conformational Studies. Acta Crystallogr. C 2015, 71, 199–203. [Google Scholar] [CrossRef]
- Bojarska, J.; Maniukiewicz, W.; Fruzinski, A.; Jedrzejczyk, M.; Wojciechowski, J.; Krawczyk, H. Structural and Spectroscopic Characterization and Hirshfeld Surface Analysis of Major Component of Antibiotic Mupirocin—Pseudomonic Acid A. J. Mol. Struct. 2014, 1076, 126–135. [Google Scholar] [CrossRef]
- Bojarska, J.; Maniukiewicz, W.; Sieron, L.; Remko, M. An Orthorhombic Polymorph of a Cyclization Product of Perindopril. Acta Crystallogr. C 2013, 69, 630–633. [Google Scholar] [CrossRef] [PubMed]
- Bojarska, J.; Maniukiewicz, W.; Glówka, M.L.; Sieron, L.; Remko, M. Crystal Structure of a Perindopril Cyclization Product, C19H30N2O4. J. Chil. Chem. Soc. 2013, 58, 1530–1533. [Google Scholar] [CrossRef] [Green Version]
- Bojarska, J.; Maniukiewicz, W.; Sieron, L. Three New Olanzapine Structures: The Acetic Acid Monosolvate, and the Propan-2-Ol and Propan-2—One Hemisolvate Monohydrates. Acta Crystallogr. C 2013, 69, 781–786. [Google Scholar] [CrossRef]
- Bojarska, J.; Maniukiewicz, W.; Sieron, L.; Kopczacki, P.; Walczynski, K.; Remko, M. Perindoprilat Monohydrate. Acta Crystallogr. C 2012, 68, o443–o446. [Google Scholar] [CrossRef]
- Bojarska, J.; Maniukiewicz, W.; Sieron, L.; Fruzinski, A.; Kopczacki, P.; Walczynski, K.; Remko, M. Novel Pseudopolymorph of the Active Metabolite of Perindopril. Acta Crystallogr. C 2012, 68, o341–o343. [Google Scholar] [CrossRef]
- Remko, M.; Bojarska, J.; Remková, A.; Maniukiewicz, W. Molecular Structure and Acidity of Captopril, Zofenopril and Their Metabolites Captopril Disulfide and Zofenoprilat. Comput. Theor. Chem. 2015, 1062, 50–55. [Google Scholar] [CrossRef]
- Remko, M.; Bojarska, J.; Jezko, P.; Maniukiewicz, W.; Olczak, A. Molecular Structure of Antihypertensive Drug Perindopril, its Active Metabolite Perindoprilat and Impurity F. J. Mol. Struct. 2013, 1036, 292–297. [Google Scholar] [CrossRef]
- Remko, M.; Bojarska, J.; Jezko, P.; Sieron, L.; Olczak, A.; Maniukiewicz, W. Crystal and Molecular Structure of Perindopril Erbumine Salt. J. Mol. Struct. 2011, 997, 103–109. [Google Scholar] [CrossRef]
- Olczak, A.; Główka, M.L.; Szczesio, M.; Bojarska, J.; Wawrzak, Z.; Duax, W.L. The First Crystal Structure of a Gramicidin Complex with Sodium: High-Resolution Study of a Nonstoichiometric Gramicidin D-NaI Complex. Acta Crystallogr. D Biol. Cryst. 2010, 66, 874–880. [Google Scholar] [CrossRef]
- Olczak, A.; Główka, M.L.; Szczesio, M.; Bojarska, J.; Duax, W.L.; Burkhart, B.M.; Wawrzak, Z. Nonstoichiometric Complex of Gramicidin D with KI at 0.80 Å Resolution. Acta Crystallogr. D Biol. Cryst. 2007, 63, 319–327. [Google Scholar] [CrossRef] [PubMed]
- Główka, M.; Olczak, A.; Bojarska, J.; Szczesio, M. Structural Puzzles of Complexed Gramicidins in Their Crystals. J. Polish Chem. Soc. 2007, 61, 161–187. [Google Scholar]
- Główka, M.L.; Olczak, A.; Bojarska, J.; Szczesio, M.; Duax, W.L.; Burkhart, B.M.; Pangborn, W.A.; Langs, D.A.; Wawrzak, Z. Structure of Gramicidin D-RbCl Complex at Atomic Resolution from Low-Temperature Synchrotron Data: Interactions of Double-Stranded Gramicidin Channel Contents and Cations with Channel Wall. Acta Crystallogr. D Biol. Crystallogr. 2005, 61, 433–441. [Google Scholar] [CrossRef] [PubMed]
- Główka, M.; Olczak, A.; Bojarska, J.; Szczesio, M.; Duax, W.; Burkhart, B.; Pangborn, W.A.; Langs, D.A.; Li, N.; Wawrzak, Z. Ion Channels in Crystals of Gramicidin D Complex with RbCl. Atomic Resolution Low-Temperature Synchrotron X-ray Data. Acta Crystallogr. Sect. A Found. Crystallogr. 2004, 60, 165. [Google Scholar] [CrossRef]
- Spackman, P.; Yu, L.-J.; Morton, C.J.; Parker, M.W.; Bond, C.S.; Spackman, M.A.; Jayatilaka, D.; Thomas, S. Bridging Crystal Engineering and Drug Discovery by Utilizing Intermolecular Interactions and Molecular Shapes in Crystals. Angew. Chem. 2019, 131, 16936–16940. [Google Scholar] [CrossRef]
- Desiraju, G.M. Supramolecular synthons in crystal engineering—A new organic synthesis. Angew. Chem. Int. Ed. 1995, 34, 2311–2327. [Google Scholar] [CrossRef]
- Desiraju, G.R. Crystal Engineering: From Molecule to Crystal. J. Am. Chem. Soc. 2013, 135, 9952–9967. [Google Scholar] [CrossRef]
- Mukherjee, A. Building upon Supramolecular Synthons: Some Aspects of Crystal Engineering. Cryst. Growth Des. 2015, 15, 3076–3085. [Google Scholar] [CrossRef]
- Li, L.; Zhan, H.; Duan, P.; Liao, J.; Quan, J.; Hu, Y.; Chen, Z.; Zhu, J.; Liu, M.; Wu, Y.-D.; et al. Self-assembling nanotubes consisting of rigid cyclic γ–peptides. Adv. Funct. Mater. 2012, 22, 3051–3056. [Google Scholar] [CrossRef]
- Hartman, M.L.; Sztiller-Sikorska, M.; Czyz, M. Whole-exome sequencing reveals novel genetic variants associated with diverse phenotypes of melanoma cells. Mol. Carcinog. 2019, 58, 588–602. [Google Scholar] [CrossRef]
- Hartman, M.; Rozanski, M.; Osrodek, M.; Zalesna, I.; Czyz, M. Vemurafenib and trametinib reduce expression of CTGF and IL-8 in V600EBRAF melanoma cells. Lab. Investig. 2017, 97, 217–227. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Czyz, M.; Sztiller-Sikorska, M.; Gajos-Michniewicz, A.; Osrodek, M.; Hartman, M.L. Plasticity of drug-naïve and vemurafenib- or trametinib-resistant melanoma cells in execution of differentiation/pigmentation program. J. Oncol. 2019, 2019, 1697913. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hartman, M.L.; Sztiller-Sikorska, M.; Gajos-Michniewicz, A.; Czyz, M. Dissecting mechanisms of melanoma resistance to BRAF and MEK inhibitors revealed genetic and non-genetic patient- and drug-specific alterations and remarkable phenotypic plasticity. Cells 2020, 9, 142. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hartman, M.L.; Gajos-Michniewicz, A.; Talaj, J.A.; Mielczarek-Lewandowska, A.; Czyz, M. BH3 mimetics potentiate pro-apoptopic activity of encorafenib in BRAF V600E melanoma cells. Cancer Lett. 2021, 499, 122–136. [Google Scholar] [CrossRef] [PubMed]
- Swart, M.; Snijders, J.G. Accuracy of geometries: Influences of basis set, exchange-correlation potential, inclusion of core electrons, and relativistic corrections. Theor. Chem. Acc. 2003, 110, 34–41. [Google Scholar] [CrossRef] [Green Version]
- Cremer, D.; Pople, J.A. General definition of ring puckering coordinates. J. Amer. Chem. Soc. 1975, 97, 1354–1358. [Google Scholar] [CrossRef]
- Wood, P.A.; Olsson, T.S.G.; Cole, J.C.; Cottrell, S.J.; Feeder, N.; Galek, P.T.A.; Groom, C.R.; Pidcock, E. Evaluation of molecular crystal structures using Full Interaction Maps. CrystEngComm 2013, 15, 65–72. [Google Scholar] [CrossRef]
- Etter, M.C.; MacDonald, J.C.; Bernstein, J. Graph-Set Analysis of Hydrogen-Bond Patterns in Organic Crystals. Acta Crystallogr. Sect. B 1990, 46, 256–262. [Google Scholar] [CrossRef]
- Ganguly, P.; Desiraju, G.R. Long-range Synthon Aufbau Modules (LSAM) in Crystal Structures: Systematic Changes in C6H6−nFn (0 ≤ N ≤ 6) Fluorobenzenes. CrystEngComm 2010, 12, 817–833. [Google Scholar] [CrossRef]
- Spackman, M.A.; Jayatilaka, D. Hirshfeld surface analysis. CrystEngComm 2009, 11, 19–32. [Google Scholar] [CrossRef]
- Spackman, P.R.; Turner, M.J.; McKinnon, J.J.; Wolff, S.K.; Grimwood, D.J.; Jayatilaka, D.; Spackman, A. CrystalExplorer: A program for Hirshfeld surface analysis, visualization and quantitative analysis of molecular crystals. J. Appl. Crystallogr. 2021, 54, 1006–1011. [Google Scholar] [CrossRef] [PubMed]
- Mooney, C.; Haslam, N.J.; Pollastri, G.; Shields, D.C. Towards the Improved Discovery and Design of Functional Peptides: Common Features of Diverse Classes Permit Generalized Prediction of Bioactivity. PLoS ONE 2012, 7, e45012. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Daina, A.; Zoete, V. A boiled-egg to predict gastrointestinal absorption and brain penetration of small molecules. ChemMedChem 2016, 11, 1117–1121. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Daina, A.; Michielin, O.; Zoete, V. SwissADME: A free web tool to evaluate pharmacokinetics, druglikeness and medicinal chemistry friendliness of small molecules. Sci. Rep. 2017, 7, 42717–42730. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lipinski, C.A.; Lombardo, F.; Dominy, B.W.; Feeney, P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 2001, 46, 3–26. [Google Scholar] [CrossRef]
- Leeson, P. Drug Discovery: Chemical Beauty Contest. Nature 2012, 481, 455–456. [Google Scholar] [CrossRef]
- Martin, Y.C. A Bioavailability Score. J. Med. Chem. 2005, 48, 3164–3170. [Google Scholar] [CrossRef]
- Veber, D.F.; Johnson, S.R.; Cheng, H.Y.; Smith, B.R.; Ward, K.W.; Kopple, K.D. Molecular properties that influence the oral bioavailability of drug candidates. J. Med. Chem. 2002, 45, 2615–2623. [Google Scholar] [CrossRef]
- Egan, W.J.; Merz, K.M.; Baldwin, J.J. Prediction of drug absorption using multivariate statistics. J. Med. Chem. 2000, 43, 3867–3877. [Google Scholar] [CrossRef]
- Muegge, I.; Heald, S.L.; Brittelli, D. Simple selection criteria for drug-like chemical matter. J. Med. Chem. 2001, 44, 1841–1846. [Google Scholar] [CrossRef]
- Ghose, A.K.; Viswanadhan, V.N.; Wendoloski, J.J. A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases. J. Comb. Chem. 1999, 1, 55–68. [Google Scholar] [CrossRef] [PubMed]
- Raschi, E.; Vasina, V.; Poluzzi, E.; De Ponti, F. The hERG K+ channel: Target and antitarget strategies in drug development. Pharmacol. Res. 2008, 57, 181–195. [Google Scholar] [CrossRef] [PubMed]
- Braga, R.C.; Alves, V.M.; Silva, M.F.B.; Muratov, E.; Fourches, D.; Liao, L.M.; Tropsha, A.; Andrade, C.H. Pred-hERG: A novel web-accessible computational tool for predicting cardiac toxicity. Mol. Inf. 2015, 34, 698–701. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Galati, S.; Di Stefano, M.; Martinelli, E.; Macchia, M.; Martinelli, A.; Poli, G.; Tuccinardi, T. VenomPred: A Machine Learning Based Platform for Molecular Toxicity Predictions. Int. J. Mol. Sci. 2022, 23, 2105. [Google Scholar] [CrossRef] [PubMed]
- Lagunin, A.A.; Dubovskaja, V.I.; Rudik, A.V.; Pogodin, P.V.; Druzhilovskiy, D.S.; Gloriozova, T.A.; Filimonov, D.; Sastry, N.G.; Poroikov, V.V. CLC-Pred: A freely available web-service for in silico prediction of human cell line cytotoxicity for drug-like compounds. PLoS ONE 2018, 13, e0191838. [Google Scholar] [CrossRef] [Green Version]
- Jeyakumar, A.; Chua, T.C.; Lam, A.K.Y.; Gopalan, V. The melanoma and breast cancer association: An overwiew of their second primary cancers and the epidemiological, genetic and biological correlations. Crit. Rev. Oncol./Hematol. 2020, 152, 102989. [Google Scholar] [CrossRef]
- Kim, K.; Chung, T.H.; Etzel, C.J.; Kim, J.; Ryu, H.; Kim, D.W.; Hwu, P.; Hwu, W.J.; Patel, S.P.; Liu, M.; et al. Association between melanoma and renal-cell carcinoma for sequential diagnoses: A single-center retrospective study. Cancer Epidemiol. 2018, 57, 80–84. [Google Scholar] [CrossRef]
- Daina, A.; Michielin, O.; Zoete, V. SwissTargetPrediction: Updated data and new features for efficient prediction of protein targets of small molecules. Nucleic Acids Res. 2019, 47, w357–w364. [Google Scholar] [CrossRef] [Green Version]
- Gupta, G.K.; Kumar, V. Chemical Drug Design; Walter de Gruyter GmbH: Berlin, Germany, 2016. [Google Scholar]
- Gore, M.; Jagtap, U.B. Computational Drug Discovery and Design; Humana: New York, NY, USA, 2018. [Google Scholar]
- Paramashiwam, S.K.; Elayaperumal, K.; Natarajan, B.B.; Ramamoorthy, M.D.; Balasubramanian, S.; Dhiraviam, K.N. In silico pharmacokinetic and molecular docking studies of small molecules derived from Indigofera aspalathoides Vahl targeting receptor tyrosine kinases. Bioinformation 2015, 11, 73–84. [Google Scholar] [CrossRef] [Green Version]
- Rosero, R.A.; Villares, G.J.; Bar-Eli, M. Protease-Activated Receptors and other G-Protein-Coupled Receptors: The Melanoma Connection. Front. Genet. 2016, 7, 112–118. [Google Scholar] [CrossRef] [Green Version]
- Zabrocki, J.; Zimecki, M.; Kaszuba, A.; Kaczmarek, K. Cyclic Tetrapeptides and Therapeutic Applications Thereof. U.S. Patent 09382292, 5 July 2016. [Google Scholar]
- Macrae, C.F.; Bruno, I.J.; Chisholm, J.A.; Edgington, P.R.; McCabe, P.; Pidcock, E.; Rodriguez-Monge, L.; Taylor, R.; van de Streek, J.; Wood, P.A. New features for the visualization and investigation of crystal structures. J. Appl. Crystallogr. 2008, 41, 466–470. [Google Scholar] [CrossRef]
- Sztiller-Sikorska, M.; Hartman, M.; Talar, B.; Jakubowska, J.; Zalesna, I.; Czyz, M. Phenotypic diversity of patient-derived melanoma populations in stem cell medium. Lab. Investig. 2015, 95, 672–683. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Dolomanov, O.V.; Bourhis, L.J.; Gildea, R.J.; Howard, J.A.K.; Puschmann, H. A complete structure solution, refinement and analysis program. J. Appl. Cryst. 2009, 42, 339–341. [Google Scholar] [CrossRef]
- Sheldrick, G.M. A short history of SHELX. Acta Crystallogr. Sect. A 2008, 64, 112–122. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sheldrick, G.M. Crystal structure refinement with SHELXL. Acta Crystallogr. Sect. C 2015, 71, 3–8. [Google Scholar] [CrossRef] [PubMed]
- Spek, A.L. Structure validation in chemical crystallography. Acta Crystallogr. Sect. D Biol. Crystallogr. 2009, 65, 148–155. [Google Scholar] [CrossRef]
- Frisch, M.J.; Trucks, G.W.; Schlegel, H.B.; Scuseria, G.E.; Robb, M.A.; Cheeseman, J.R.; Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G.A.; et al. Gaussian 09, version 9.0; Gaussian Inc: Wallingford, CT, USA, 2011. [Google Scholar]
- Parr, R.G.; Wang, W. Density-Functional Theory of Atoms and Molecules; Oxford University Press: New York, NY, USA, 1994. [Google Scholar]
- Neumann, R.; Nobes, R.H.; Handy, N.C. Exchange functionals and potentials. Mol. Phys. 1996, 87, 1–36. [Google Scholar] [CrossRef]
- Bickelhaupt, F.M.; Baerends, E.J. Kohn-Sham Density Functional Theory: Predicting and Understanding Chemistry. In Reviews in Computational Chemistry; Lipkowitz, K.B., Boyd, D.B., Eds.; Wiley-VCH: New York, NY, USA, 2000; Volume 15, pp. 1–86. [Google Scholar]
- Becke, A.D. Density-functional exchange-energy approximation with correct asymptotic behawior. Phys. Rev. 1988, A38, 3098–3100. [Google Scholar] [CrossRef]
- Becke, A.D. Density-functional thermochemistry. III. The role of exact exchange. J. Chem. Phys. 1993, 98, 5648–5652. [Google Scholar] [CrossRef] [Green Version]
- Lee, C.; Yang, W.; Parr, R.G. Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density. Phys. Rev. B 1998, 37, 785–789. [Google Scholar] [CrossRef] [Green Version]
- Klamt, A.; Schűűman, G. COSMO: A new approach to dielectric screening in solvents with explicit expressions for the screening energy and its gradient. J. Chem. Soc. Perkin Trans. 1993, 24, 799–805. [Google Scholar] [CrossRef]
- Barone, V.; Cossi, M. Quantum Calculation of Molecular Energies and Energy Gradients in Solution by a Conductor Solvent Model. J. Phys. Chem. A 1998, 102, 1995–2001. [Google Scholar] [CrossRef]
- Cossi, M.; Rega, N.; Scalmani, G.; Barone, V. Energies, structures, and electronic properties of molecules in solution with the C-PCM solvation model. J. Comput. Chem. 2003, 24, 669–681. [Google Scholar] [CrossRef] [PubMed]
- Reed, A.E.; Weinhold, F. Natural bond orbital analysis of near-Hartree-Fock water dimer. J. Chem. Phys. 1983, 78, 4066–4073. [Google Scholar] [CrossRef]
- Reed, A.E.; Weinhold, F. Natural Localized Molecular Orbitals. J. Chem. Phys. 1985, 83, 1736–1740. [Google Scholar] [CrossRef]
- Reed, A.E.; Weinstock, R.B.; Weinhold, F. Natural-population analysis. J. Chem. Phys. 1985, 83, 735–746. [Google Scholar] [CrossRef]
- Reed, A.E.; Curtiss, L.A.; Weinhold, F. Intermolecular interactions from a natural bond orbital, donor-acceptor viewpoint. Chem. Rev. 1988, 88, 899–926. [Google Scholar] [CrossRef]
- Carpenter, J.E.; Weinhold, F. Analysis of the geometry of the hydroxymethyl radical by the different hybrids for different spins natural bond orbital procedure. J. Mol. Struct. 1988, 169, 41–62. [Google Scholar] [CrossRef]
- Hirshfeld, H.L. Bonded-atom fragments for describing molecular charge densities. Theor. Chim. Acta 1977, 44, 129–138. [Google Scholar] [CrossRef]
- Turner, M.J.; McKinnon, J.J.; Wolff, S.K.; Grimwood, D.J.; Spackman, P.R.; Jayatilaka, D.; Spackman, M.A. Crystal Explorer17; The University of Western Australia: Crawley, Australia, 2017. [Google Scholar]
- Mackenzie, C.F.; Spackman, P.R.; Jayatilaka, D.; Spackman, M.A. CrystalExplorer model energies and energy frameworks: Extension to metal coordination compounds, organic salts, solvates and open-shell systems. IUCrJ 2017, 4, 575–587. [Google Scholar] [CrossRef] [Green Version]
- Jelsch, C.; Ejsmont, K.; Huder, L. The enrichment ratio of atomic contacts in crystals, an indicator derived from the Hirshfeld surface analysis. IUCrJ 2014, 1, 119–128. [Google Scholar] [CrossRef] [PubMed]
Formula | C29H34N4O4 |
---|---|
Molecular weight | 502.60 |
Temperature (K) | 100 |
Crystal system, space group | triclinic, P1 |
a, b, c (Å); α, β, ɣ (°) | 5.6034 (2), 9.9007 (3), 12.5815 (4); 67.2640 (10), 87.2840 (10), 77.831 (2) |
V (Å3) | 628.84(4) |
Z | 1 |
Radiation type | CuKα |
µ (mm−1) | 0.722 |
No. of reflections | 7452 |
No. of unique reflections | 4444/3656 |
No. of parameters | 343 |
No. of restraints | 3 |
Rint | 0.0130 |
Tmin, Tmax | 0.878, 0.897 |
R[F2 > 2σ(F2)], wR(F2), S | 0.0293, 0.0783, 0.994 |
CCDC number | 2158219 |
D-H…A | D-H | H…A | D…A | D-H…A |
---|---|---|---|---|
* N3-H3N…N2 | 0.85 (3) | 2.39 (3) | 2.783 (3) | 109 (2) |
C3-H3A…O4 i | 0.97 | 2.53 | 3.467 (3) | 163 |
* C29-H23…O3 | 0.98 | 2.34 | 2.785 (3) | 107 |
C9-H9…O1 i | 0.98 | 2.34 | 3.172 (3) | 143 |
C19-H19A…O2 ii | 0.97 | 2.33 | 3.139 (4) | 140 |
C16-H16…O4 iii | 0.93 | 2.46 | 3.379 (3) | 169 |
* C11-H11…O2 | 0.98 | 2.41 | 2.830 (4) | 105 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Bojarska, J.; Breza, M.; Remko, M.; Czyz, M.; Gajos-Michniewicz, A.; Zimecki, M.; Kaczmarek, K.; Madura, I.D.; Wojciechowski, J.M.; Wolf, W.M. Structural and Biofunctional Insights into the Cyclo(Pro-Pro-Phe-Phe-) Scaffold from Experimental and In Silico Studies: Melanoma and Beyond. Int. J. Mol. Sci. 2022, 23, 7173. https://doi.org/10.3390/ijms23137173
Bojarska J, Breza M, Remko M, Czyz M, Gajos-Michniewicz A, Zimecki M, Kaczmarek K, Madura ID, Wojciechowski JM, Wolf WM. Structural and Biofunctional Insights into the Cyclo(Pro-Pro-Phe-Phe-) Scaffold from Experimental and In Silico Studies: Melanoma and Beyond. International Journal of Molecular Sciences. 2022; 23(13):7173. https://doi.org/10.3390/ijms23137173
Chicago/Turabian StyleBojarska, Joanna, Martin Breza, Milan Remko, Malgorzata Czyz, Anna Gajos-Michniewicz, Michał Zimecki, Krzysztof Kaczmarek, Izabela D. Madura, Jakub M. Wojciechowski, and Wojciech M. Wolf. 2022. "Structural and Biofunctional Insights into the Cyclo(Pro-Pro-Phe-Phe-) Scaffold from Experimental and In Silico Studies: Melanoma and Beyond" International Journal of Molecular Sciences 23, no. 13: 7173. https://doi.org/10.3390/ijms23137173
APA StyleBojarska, J., Breza, M., Remko, M., Czyz, M., Gajos-Michniewicz, A., Zimecki, M., Kaczmarek, K., Madura, I. D., Wojciechowski, J. M., & Wolf, W. M. (2022). Structural and Biofunctional Insights into the Cyclo(Pro-Pro-Phe-Phe-) Scaffold from Experimental and In Silico Studies: Melanoma and Beyond. International Journal of Molecular Sciences, 23(13), 7173. https://doi.org/10.3390/ijms23137173