Atnaujinkite slapukų nuostatas

El. knyga: Advances in Protein Molecular and Structural Biology Methods

Edited by (Professor, School of Biochemical Engineering, Indian Institute of Technology (BHU), Varanasi, India), Edited by (Professor of Molecular Biology, School of Life Sciences, North-Eastern Hill University, Shillong, India)
  • Formatas: EPUB+DRM
  • Išleidimo metai: 14-Jan-2022
  • Leidėjas: Academic Press Inc
  • Kalba: eng
  • ISBN-13: 9780323902656
Kitos knygos pagal šią temą:
Advances in Protein Molecular and Structural Biology MethodsDidesnis paveikslėlis
  • Formatas: EPUB+DRM
  • Išleidimo metai: 14-Jan-2022
  • Leidėjas: Academic Press Inc
  • Kalba: eng
  • ISBN-13: 9780323902656
Kitos knygos pagal šią temą:

DRM apribojimai

  • Kopijuoti:

    neleidžiama

  • Spausdinti:

    neleidžiama

  • El. knygos naudojimas:

    Skaitmeninių teisių valdymas (DRM)
    Leidykla pateikė šią knygą šifruota forma, o tai reiškia, kad norint ją atrakinti ir perskaityti reikia įdiegti nemokamą programinę įrangą. Norint skaityti šią el. knygą, turite susikurti Adobe ID . Daugiau informacijos  čia. El. knygą galima atsisiųsti į 6 įrenginius (vienas vartotojas su tuo pačiu Adobe ID).

    Reikalinga programinė įranga
    Norint skaityti šią el. knygą mobiliajame įrenginyje (telefone ar planšetiniame kompiuteryje), turite įdiegti šią nemokamą programėlę: PocketBook Reader (iOS / Android)

    Norint skaityti šią el. knygą asmeniniame arba „Mac“ kompiuteryje, Jums reikalinga  Adobe Digital Editions “ (tai nemokama programa, specialiai sukurta el. knygoms. Tai nėra tas pats, kas „Adobe Reader“, kurią tikriausiai jau turite savo kompiuteryje.)

    Negalite skaityti šios el. knygos naudodami „Amazon Kindle“.

Advances in Protein Molecular and Structural Biology Methods offers a complete overview of the latest tools and methods applicable to the study of proteins at the molecular and structural level. The book begins with sections exploring tools to optimize recombinant protein expression and biophysical techniques such as fluorescence spectroscopy, NMR, mass spectrometry, cryo-electron microscopy, and X-ray crystallography. It then moves towards computational approaches, considering structural bioinformatics, molecular dynamics simulations, and deep machine learning technologies. The book also covers methods applied to intrinsically disordered proteins (IDPs)followed by chapters on protein interaction networks, protein function, and protein design and engineering.

It provides researchers with an extensive toolkit of methods and techniques to draw from when conducting their own experimental work, taking them from foundational concepts to practical application.

  • Presents a thorough overview of the latest and emerging methods and technologies for protein study
  • Explores biophysical techniques, including nuclear magnetic resonance, X-ray crystallography, and cryo-electron microscopy
  • Includes computational and machine learning methods
  • Features a section dedicated to tools and techniques specific to studying intrinsically disordered proteins
Contributors xix
About the Editors xxiii
Foreword xxv
Preface xxvii
1 Strategies to improve the expression and solubility of recombinant proteins in E. coli
Niharika Nag
Heena Khan
Timir Tripathi
1 Introduction
1(1)
2 Before starting with protein expression
2(2)
3 Materials required
4(1)
4 Standard protocol for recombinant protein expression in E. coli
5(1)
4.1 For protein solubilization
5(1)
4.2 For protein purification
5(1)
5 Troubleshooting strategies
6(4)
5.1 Handling protein expression and solubility issues
6(3)
5.2 Handling of inclusion bodies
9(1)
5.3 Handling protein leakage
9(1)
5.4 Handling of toxic proteins
9(1)
5.5 Handling of unstable proteins
10(1)
5.6 Posttranslational modifications
10(1)
6 Conclusion and future perspectives
10(3)
References
10(3)
2 Advances in heterologous protein expression strategies in yeast and insect systems
Meenakshi Singh
Smita Gupta
Arun Kumar Rawat
Sudhir Kumar Singh
1 Introduction
13(1)
2 Heterologous protein expression strategies in yeast systems
13(8)
2.1 Introduction
13(1)
2.2 Synthetic gene optimization
14(1)
2.3 Expression optimization by controlling gene copy number
14(1)
2.4 Optimization of promoters
15(1)
2.5 Engineering yeast secretion pathway
16(5)
2.6 Conclusion of yeast expression systems
21(1)
3 Heterologous protein expression strategies in insect systems
21(4)
3.1 Introduction
21(1)
3.2 Growth factors and in vitro culture
22(1)
3.3 Insect cell lines
22(1)
3.4 Use of novel or genetically improved cell lines
23(1)
3.5 Baculovirus insect cell expression system
24(1)
3.6 Baculovirus-free insect cell expression system
25(1)
4 Conclusion of baculovirus expression systems
25(6)
Acknowledgment
25(1)
References
26(5)
3 Methods for transient expression and purification of monoclonal antibodies in mammalian cells
Suchitra Kamle
Dawei Li
Chun Geun Lee
Jack A. Elias
1 Introduction
31(1)
2 Background experimental preparation
32(2)
2.1 Plasmid DNA extraction protocol step-by-step
34(1)
2.2 Agarose gel preparation
34(1)
3 Materials required for antibody purification
34(1)
4 Detailed step-by-step protocol for antibody purification
35(2)
4.1 Adherent cells
35(2)
4.2 Suspension cells
37(1)
5 Troubleshooting problems
37(1)
5.1 Optimization of cell transfection
37(1)
5.2 Antibody yield
37(1)
5.3 Postpurification storage of the protein
38(1)
5.4 Precautions, recommendations, and general troubleshooting
38(1)
6 Conclusions
38(3)
References
38(3)
4 Methods for recombinant production and purification of intrinsically disordered proteins
Steffen P. Graether
1 Before you begin
41(1)
1.1 Timing: 1 day to 1 month, depending on the gene of interest cloned in an expression plasmid
41(1)
2 Materials and equipment
41(1)
3 Step-by-step method details
42(2)
3.1 Bacterial growth and protein expression
42(1)
3.2 Bacterial cell lysis
43(1)
3.3 Protein purification
43(1)
3.4 Optional steps---Isotopic labeling
44(1)
4 Expected outcomes
44(1)
5 Optimization and troubleshooting
44(5)
References
47(2)
5 Methods to determine the oligomeric structure of proteins
Puma Bahadur Chetri
Heena Khan
Timir Tripathi
1 Introduction
49(1)
2 Electrophoretic methods
50(3)
2.1 Native PAGE
50(1)
2.2 Chemical crosslinking with glutaraldehyde followed by SDS-PAGE
50(3)
3 Size exclusion chromatography
53(1)
3.1 Case study 1
53(1)
3.2 Case study 2
53(1)
3.3 Case study 3
54(1)
4 Dynamic light scattering
54(2)
4.1 Case study 1
56(1)
4.2 Case study 2
56(1)
5 Circular dichroism spectroscopy
56(2)
5.1 Case study 1
58(1)
6 Fluorescence-based methods
58(7)
6.1 Fluorescence correlation spectroscopy
58(2)
6.2 Fluorescence resonance energy transfer
60(2)
6.3 Fluorescence fluctuation spectroscopy
62(1)
6.4 Fluorescence recovery after photobleaching
62(1)
6.5 Bimolecular fluorescence complementation assay
63(1)
6.6 Confocal microscopy
64(1)
7 Analytical ultracentrifugation
65(1)
7.1 Case study
66(1)
8 X-ray crystallography and NMR spectroscopy
66(2)
9 Mass spectroscopy
68(1)
9.1 Case study
68(1)
10 Atomic force microscopy
69(1)
10.1 Case study
69(1)
11 Co-immunoprecipitation
69(1)
11.1 Case study
70(1)
12 Computational methods
70(1)
13 Conclusions
71(6)
References
71(6)
6 Multimodal methods to study protein aggregation and fibrillation
Maria Georgina Herrera
Marco Giampa
Nicolo Tonali
Veronica Isabel Dodero
1 Introduction
77(2)
1.1 Protein misfolding and aggregation
77(1)
1.2 Multilevel approach to close the gap between the in vitro to the in vivo aggregation processes
77(2)
2 Combination of in vitro techniques to evaluate isolated protein aggregates and fibrils
79(10)
2.1 Structural and morphological analysis of protein aggregates and fibrils by the combination of low-resolution methods
79(6)
2.2 Implementation of atomistic methods to reveal the structure of aggregates and fibrils
85(4)
3 Multimodal methods to evaluate the aggregation of proteins in cells tissues and living system
89(14)
3.1 Protein aggregation studies in cells
89(3)
3.2 Protein aggregation studies in tissues
92(3)
3.3 Protein aggregation studies in animal models or in vivo
95(1)
Acknowledgments
95(1)
References
95(8)
7 Experimental methods to study the thermodynamics of protein--protein interactions
Santanu Sasidharan
Niharika Nag
Timir Tripathi
Prakash Saudagar
1 Introduction
103(1)
2 Criteria for forming a protein-protein interaction
103(1)
3 Characteristic features of PPI interfaces
103(2)
3.1 Interface shape and size
103(1)
3.2 Amino acids
104(1)
3.3 Structural motifs and secondary structures
104(1)
3.4 Driving forces of interaction
105(1)
3.5 Binding affinity
105(1)
3.6 Transient pockets
105(1)
3.7 Packing cavities
105(1)
3.8 Water molecules
105(1)
4 Thermodynamic parameters associated with PPI
105(2)
4.1 Gibbs free energy, enthalpy, entropy, and heat capacity
105(1)
4.2 Enthalpy--entropy compensation, cooperativity, and flexibility
106(1)
4.3 Solvation and desolvation effects
106(1)
5 Techniques to study the thermodynamics of PPI
107(6)
5.1 Isothermal titration calorimetry
107(2)
5.2 Differential scanning calorimetry
109(1)
5.3 Microscale thermophoresis
110(3)
6 Conclusions
113(2)
References
113(2)
8 Experimental methods to study the kinetics of protein-protein interactions
Abhay Narayan Singh
Kristijan Ramadan
Shalini Singh
1 Introduction
115(1)
2 Surface plasmon resonance
115(2)
2.1 Principle
115(1)
2.2 Experimental setup
116(1)
2.3 Advantages
116(1)
2.4 Limitations
117(1)
2.5 Case study
117(1)
3 Bio-layer interferometry
117(2)
3.1 Principle
117(1)
3.2 Experimental setup
118(1)
3.3 Advantages
118(1)
3.4 Limitations
118(1)
3.5 Case study
119(1)
4 Microscale thermophoresis
119(2)
4.1 Principle
119(1)
4.2 Experimental setup
119(1)
4.3 Advantages
119(1)
4.4 Limitations
120(1)
4.5 Case study
120(1)
5 Isothermal titration calorimetry
121(1)
5.1 Principle
121(1)
5.2 Experimental setup
121(1)
5.3 Advantages
122(1)
5.4 Limitations
122(1)
5.5 Case study
122(1)
6 Quartz crystal microbalance
122(1)
6.1 Principle
122(1)
6.2 Experimental setup
122(1)
6.3 Advantages
123(1)
6.4 Limitations
123(1)
6.5 Case study
123(1)
7 Conclusions
123(2)
Acknowledgment
123(1)
References
124(1)
9 Computational techniques for studying protein-protein interactions
Khattab Al-Khafaji
Tugba Taskin-Tok
1 Introduction
125(1)
2 Types of protein-protein complexes
125(1)
3 PPIs as targets for drug discovery
126(1)
4 Mining PPIs
126(1)
5 Computational techniques in PPI detection
127(5)
5.1 Sequence-based techniques
127(1)
5.2 Structure-based techniques
128(2)
5.3 Gene fusion-based approach
130(1)
5.4 In silico two-hybrid techniques
130(1)
5.5 Mirrortree-based technique
130(1)
5.6 Phylogenetic tree-based technique
131(1)
5.7 Phylogenetic profile-based technique
131(1)
5.8 Chromosome proximity/gene neighborhood-based technique
131(1)
5.9 Network topology-based technique
131(1)
5.10 Gene expression-based technique
131(1)
6 Comparison of available computational approaches
132(1)
7 PPI databases
132(1)
8 PPI network and visualization
132(1)
9 Conclusion and future perspectives
133(4)
References
133(4)
10 Experimental methods to study protein--nucleic acid interactions
Roberto Giambruno
Jakob Rupert
Elsa Zacco
1 Introduction
137(1)
2 Single-molecule approaches for the identification and validation of protein--nucleic acid interactions
138(5)
2.1 Methods to determine the kinetics and dynamics of the interactions
139(2)
2.2 Methods to determine structural characteristics of the interactions
141(2)
3 Investigation of protein--nucleic acid interactions in mammalian cell lines
143(9)
3.1 Methods to study protein--DNA interaction
143(4)
3.2 Methods to study protein--RNA interactions
147(5)
4 Conclusions
152(11)
References
152(11)
11 Advanced computational tools for quantitative analysis of protein--nucleic acid interfaces
Sunandan Mukherjee
Chandran Nithin
1 Protein-RNA complexes
163(1)
2 Datasets for studying protein--RNA interfaces
164(2)
2.1 Protein--RNA docking benchmarks
164(1)
2.2 Protein--RNA affinity benchmarks
165(1)
2.3 Databases of protein--RNA interactions
165(1)
3 Tools for the analysis of protein--RNA interfaces
166(2)
4 Tools for protein--RNA binding site prediction
168(1)
5 Tools for protein--RNA binding affinity prediction
168(1)
6 Tools for hot spots at protein--RNA interfaces
169(1)
7 A brief survey of tools for studying protein--DNA interactions
170(1)
8 Conclusions
171(10)
Acknowledgment
172(1)
References
172(9)
12 Experimental techniques to study protein dynamics and conformations
Akshita Gupta
Anamika Singh
Nabeei Ahmad
Tej P. Singh
Sujata Sharma
Pradeep Sharma
1 Introduction
181(1)
2 Various methods to study protein dynamics and conformations
181(14)
2.1 Nuclear magnetic resonance spectroscopy
182(2)
2.2 Cryo-electron microscopy
184(3)
2.3 Small-angle X-ray scattering/small-angle neutron scattering
187(2)
2.4 Mass spectrometry
189(1)
2.5 Single-molecule fluorescence resonance energy transfer (smFRET)
190(3)
2.6 Atomic force microscopy
193(2)
3 Conclusion and future perspectives
195(4)
References
196(3)
13 Computational techniques to study protein dynamics and conformations
Anil Mhashal
Agusti Emperador
Laura Orellana
1 Introduction
199(1)
2 "Realistic" methods: Molecular dynamics and enhanced sampling
200(1)
3 "Simplified" approaches: Coarse-graining and path-sampling algorithms
201(3)
3.1 Coarse-grained normal mode analysis (NMA)
201(1)
3.2 Langevin and Brownian dynamics (BD)
202(1)
3.3 Discrete molecular dynamics (dMD)
203(1)
3.4 Coarse-grained molecular dynamics
203(1)
4 A case study: The open-to-close transition of the ribose-binding protein
204(3)
4.1 Classical and replica-exchange molecular dynamics simulations
205(1)
4.2 Coarse-grain (CG) MARTINI simulations
205(1)
4.3 Discrete molecular dynamics-PACSAB simulations
205(1)
4.4 Comparative analysis of conformational sampling
206(1)
5 Summary and conclusions
207(6)
Acknowledgments
207(1)
References
207(6)
14 Application of circular dichroism spectroscopy in studying protein folding, stability and interaction
Md Anzarul Haque
Punit Kaur
Asimul Islam
Md Imtaiyaz Hassan
1 Introduction
213(1)
2 Theory of circular dichroism
214(1)
3 Application of CD spectroscopy
215(5)
3.1 Estimation of secondary structures
215(1)
3.2 Thermal denaturation studies
216(1)
3.3 Urea and GdmCI-induced denaturation studies
216(3)
3.4 Measurement of the impact of osmolyte in protein stability
219(1)
3.5 Impact of crowding agents in protein stability
220(1)
3.6 Protein--DNA and protein--ligand interactions
220(1)
4 Time-resolved CD spectroscopy and its uses in protein folding kinetics
220(1)
5 Conclusion and future perspectives
221(4)
Conflict of interests
221(1)
References
221(4)
15 Studying protein-folding dynamics using single-molecule fluorescence methods
Narattam Mandal
Krishnananda Chattopadhyay
Achinta Sannigrahi
1 Introduction
225(1)
2 Single-molecule fluorescence techniques for protein-folding dynamics
226(8)
2.1 Theory of single-molecule fluorescence
226(1)
2.2 Fluorescence correlation spectroscopy (FCS)
227(4)
2.3 Single-molecule fluorescence resonance energy transfer (smFRET)
231(2)
2.4 Single-molecule fluorescence microscopy (SMFM)
233(1)
3 Conclusion and future perspectives
234(3)
References
235(2)
16 Advances in liquid-state NMR spectroscopy to study the structure, function, and dynamics of biomacromolecules
Priyanka Aggarwal
Pooja Kumari
Neel Sarovar Bhavesh
1 Introduction to liquid-state NMR spectroscopy
237(4)
1.1 Recent advancements in NMR hardware
237(4)
2 Liquid-state NMR spectroscopy of biomacromolecules
241(14)
2.1 Sequence-specific resonance assignments
241(7)
2.2 New NMR methods
248(1)
2.3 Structure determination
249(4)
2.4 Dynamics of biomacromolecules
253(2)
3 Biomolecular behavior and drug discovery
255(3)
3.1 Biomacromolecular interactions
255(2)
3.2 Biomacromolecular hydration
257(1)
3.3 NMR of biologies and biosimilars
258(1)
4 NMR of biomacromolecules in living cells
258(1)
4.1 Structure determination in the living cell
258(1)
4.2 In-cell drug discovery
259(1)
5 Summary
259(8)
References
259(8)
17 In-cell NMR spectroscopy: A tool to study cellular structure biology
Vijay Kumar
1 Introduction
267(1)
2 Overview of in-cell NMR
267(2)
3 Bioreactor systems for in-cell NMR observations
269(1)
4 Applications of in-cell NMR
269(4)
5 Conclusion and future perspectives
273(4)
References
273(4)
18 Current trends in membrane protein crystallography
Koomity V. Nageswar
Mansi Sharma
Dipak N. Patil
Santoshi Nayak
Anwesha Roy
Appu K. Singh
1 Introduction
277(1)
1.1 Basics of protein crystallography
277(1)
1.2 Membrane protein crystallography
277(1)
2 Expression screening of membrane proteins for crystallization
278(1)
3 Detergent screening and fluorescence size exclusion chromatography of membrane proteins
279(1)
4 Crystallization of membrane proteins
279(3)
4.1 Vapor diffusion
279(2)
4.2 Lipidic cubic phase crystallization
281(1)
4.3 Bicelle crystallization
282(1)
4.4 In situ crystallography
282(1)
5 Engineering membrane proteins to facilitate crystal formation
282(1)
6 X-ray sources
282(3)
7 Detectors
285(1)
8 Time-resolved crystallography
285(1)
9 X-ray free-electron laser
285(2)
10 Conclusion and future perspectives
287(4)
Acknowledgments
288(1)
References
288(3)
19 Advances in sample preparation and data processing for single-particle cryo-electron microscopy
Anshul Assaiya
Suparna Bhar
Janesh Kumar
1 Introduction
291(2)
2 Sample quality is the key to high-resolution structure determination
293(4)
2.1 Sample preparation for SPA
293(1)
2.2 Tools and reagents to facilitate structure determination of membrane proteins
293(3)
2.3 Strategies for sample preparation of macromolecular assemblies
296(1)
2.4 Low molecular weight specimens
296(1)
3 Grid preparation for SPA
297(3)
3.1 Grid materials
297(1)
3.2 Mesh size of the grids
297(1)
3.3 Grid support foil
297(1)
3.4 Popular grid types
298(1)
3.5 Grid treatment and modifications to improve particle distribution and orientation
298(1)
3.6 Sample vitrification
299(1)
4 Time-resolved cryoEM
300(1)
5 Advances in SPA data collection and processing
301(2)
5.1 Data collection
301(1)
5.2 Motion correction
301(1)
5.3 CTF estimation
302(1)
5.4 Particle detection and selection
302(1)
5.5 2D classification
302(1)
5.6 Ab initio 3D reconstruction and refinement
303(1)
6 AI/ML-based approaches in cryoEM data processing pipeline
303(2)
7 Conclusion and future perspectives
305(6)
Acknowledgments
306(1)
Author contributions
306(1)
Conflict of interest
306(1)
References
306(5)
20 Advanced mass spectrometry-based methods for protein molecular-structural biologists
Joanna Bons
Jacob Rose
Amy O'Broin
Birgit Schilling
1 Introduction
311(2)
2 Data-independent acquisitions (DIA) for accurate protein quantification
313(5)
2.1 Selected recent DIA strategies
313(1)
2.2 Bioinformatic processing of DIA data
314(1)
2.3 DDA-based spectral libraries, sample-specific
315(1)
2.4 DDA-based spectral libraries, public resources
315(1)
2.5 Challenges and opportunities related to DDA-based spectral libraries
316(1)
2.6 Spectral library-free workflows
316(1)
2.7 Alternative library strategies for DIA data analysis
317(1)
3 Resolving protein structures using DIA-MS
318(3)
3.1 Protein structures and posttranslational modifications
318(1)
3.2 Determination of different protein conformations using DIA-MS
319(2)
4 Conclusions and outlooks
321(6)
Acknowledgments
322(1)
References
322(5)
21 Developments, advancements, and contributions of mass spectrometry in omics technologies
Saravanan Kumar
1 Introduction
327(4)
2 Omics mass spectrometry
331(7)
2.1 Ionization methods
331(5)
2.2 Mass analyzers-Now and then
336(2)
3 Mass spectrometry in Omics technologies
338(9)
3.1 Proteomics and mass spectrometry
338(7)
3.2 Metabolomics and mass spectrometry
345(2)
4 Recent developments in the mass spectrometer
347(1)
5 Fragmentation principles
348(5)
5.1 Collision-induced dissociation (CID)
349(1)
5.2 Higher energy collisional dissociation (HCD)
349(1)
5.3 Electron transfer dissociation (ETD)
350(1)
5.4 ETcaD; EThCD---Hybrid dissociation techniques
351(2)
5.5 Ultraviolet photodissociation (UVPD)
353(1)
6 Conclusion and future perspectives
353(4)
References
353(4)
22 Role of structural biology methods in drug discovery
Fouzia Nasim
Insaf Ahmed Qureshi
1 Introduction
357(1)
2 Structural biology aided selection of drug targets
357(2)
3 Role of experimental and computational approaches in drug discovery
359(6)
3.1 X-ray crystallography
359(3)
3.2 NMR spectroscopy
362(1)
3.3 Cryogenic electron microscopy (cryo-EM)
363(1)
3.4 Comparative modeling and QSAR studies
364(1)
4 Virtual screening
365(1)
5 Enhancement of ligand specificity
366(1)
6 Optimization of hits and drug-likeness
367(1)
7 Development of peptidomimetics
367(1)
8 Conclusion and future perspectives
368(5)
References
368(5)
23 Prediction, validation, and analysis of protein structures: A beginner's guide
Santanu Sasidharan
Prakash Saudagar
1 Introduction
373(1)
2 Protein structure modeling
374(3)
2.1 Template-based modeling
374(3)
2.2 Template-free modeling
377(1)
3 Protein structure refinement and validation
377(3)
3.1 SWISS-MODEL validation
377(1)
3.2 I-TASSER validation
378(1)
3.3 General validation of models
379(1)
3.4 Refinement of modeled structure
379(1)
4 Protein structure analysis and importance of protein folding
380(3)
5 Recent advances in in silico protein structure determination
383(1)
6 Conclusion and future perspectives
383(4)
References
383(4)
24 Advances in structure-based virtual screening for drug discovery
Olujide O. Olubiyi
Suman Samantray
Alexander-Maurice Illig
1 Introduction
387(1)
2 Drug design and the computers
387(8)
2.1 Molecular descriptor-based screening
387(1)
2.2 From HTS to structure-based virtual screening
388(1)
2.3 Structural imperatives for ligand-receptor coupling and virtual screening
388(1)
2.4 Structural inputs for SBVS
389(1)
2.5 Core foundations of structure-based virtual screening
390(1)
2.6 Higher dimensional search protocol in SBVS
391(1)
2.7 Macromolecular flexibility in SBVS
391(1)
2.8 Docking reference ligands, validation, and modeling access to receptors
391(2)
2.9 Typical protocol for performing SBVS
393(2)
3 Conclusion and future perspectives
395(10)
References
401(3)
Further reading
404(1)
25 Methods and applications of machine learning in structure-based drug discovery
Madhumathi Sanjeevi
Prajna N. Hebbar
Natarajan Aiswarya
S. Rashmi
Chandrashekar Narayanan Rahul
Ajitha Mohan
Jeyaraman Jeyakanthan
Kanagaraj Sekar
1 Introduction
405(1)
2 Protein crystallography and Al-assisted drug discovery
406(2)
2.1 Evolution of protein crystallography in drug design
406(1)
2.2 Methods in FBDD and enhancements provided by ML
406(1)
2.3 Improvement of X-ray crystallography using ML
407(1)
2.4 Applications of ML in NMR method
407(1)
2.5 Applications of ML in cryoEM method
407(1)
3 Application of ML in protein structure prediction (in silico approach)
408(7)
3.1 Homology modeling
408(4)
3.2 Threading
412(1)
3.3 Ab initio method
413(1)
3.4 Model assessment
414(1)
4 Virtual screening
415(14)
4.1 Concepts in ligand-based virtual screening (LBVS)
415(1)
4.2 Concepts of structure-based virtual screening (SBVS)
415(14)
5 Conclusion and future perspectives
429(10)
Acknowledgments
430(1)
References
430(5)
Further reading
435(4)
26 Molecular dynamics simulations: Principles, methods, and applications in protein conformational dynamics
Aditya K. Padhi
Matej Janezic
Kam Y.J. Zhang
1 Introduction
439(1)
2 Applications of MD simulations
440(1)
3 Materials
441(2)
3.1 Hardware dependencies
441(1)
3.2 Software dependencies
441(1)
3.3 Structural coordinates
441(1)
3.4 Structural and dynamic parameters
442(1)
3.5 MD simulation settings and workflow
442(1)
4 Methods
443(4)
4.1 Preparing the coordinates
443(1)
4.2 Defining and solvating the simulation box
444(1)
4.3 Adding counterions
444(1)
4.4 Energy minimization
444(1)
4.5 Heating
445(1)
4.6 Equilibration
445(1)
4.7 Production
445(1)
4.8 Analysis
446(1)
5 Notes
447(2)
6 Utility of MD simulation: A case study on conformational dynamics of D-amino acid oxidase (DAAO)
449(1)
7 Conclusion and future perspectives
449(6)
Acknowledgments
450(1)
References
451(4)
27 Applications of molecular dynamics simulations in drug discovery
Xubo Lin
1 Introduction
455(1)
2 Identification of protein conformation ensemble and drug binding site
455(1)
2.1 Identification of protein conformation ensemble
456(1)
2.2 Identification of drug binding site
456(1)
3 Modeling protein-drug interactions
456(6)
3.1 Molecular docking using MD force field functions
456(1)
3.2 Long timescale MD simulations
457(1)
3.3 MD simulations with enhanced sampling methods
458(2)
3.4 MM/PBSA and MM/GBSA binding free energy calculation
460(1)
3.5 Alchemical binding free energy calculation
461(1)
3.6 The integration of molecular docking and molecular dynamics simulations
461(1)
4 Modeling drug-membrane interactions
462(1)
5 Conclusion and future perspectives
463(4)
References
463(4)
28 Envisaging the conformational space of proteins by coupling machine learning and molecular dynamics
Murali Aarthy
Sanjeev Kumar Singh
1 Introduction
467(1)
2 Conformational impact due to various environment
468(1)
3 Multiple conformational states of proteins
468(1)
4 Impact of Ramachandran plot in conformational space
469(1)
5 Variability in the conformation of intrinsically disordered proteins
470(1)
6 Conformational sampling analysis through different methods
470(1)
7 Role of force fields in different conformational space observation
470(1)
8 Conformational space assessment on the explicit and implicit solvent model
471(1)
9 Conformational space analysis through machine learning
472(1)
10 Combination of MD simulation and machine learning
472(1)
11 Conclusion and future perspectives
472(5)
Acknowledgments
472(1)
Declaration of competing interests
473(1)
References
473(4)
29 Immunoinformatics and reverse vaccinology methods to design peptide-based vaccines
Vinita Sharma
Satyendra Singh
Tadi Sai Ratnakar
Vijay Kumar Prajapati
1 Introduction
477(1)
2 Peptide vaccines
477(2)
3 Methods and tools in reverse vaccinology
479(4)
3.1 T-cell epitope mapping
479(2)
3.2 Prediction of MHC polymorphism in T-cell epitope mapping
481(1)
3.3 B-cell epitope mapping
481(1)
3.4 Vaccine construction
481(1)
3.5 Analysis of the designed vaccine
482(1)
3.6 Molecular docking and molecular dynamics simulation
483(1)
3.7 Immune dynamics (ID) simulation of the designed vaccine candidate
483(1)
4 Steps involved in reverse vaccinology
483(1)
5 Advantage of peptide vaccine or multi-epitope vaccines
484(1)
6 Conclusion and future perspectives
485(4)
References
485(4)
30 Computational methods to study intrinsically disordered proteins
Prateek Kumar
Aparna Bhardwaj
Vladimir N. Uversky
Timir Tripathi
Rajanish Giri
1 Introduction
489(3)
1.1 Two decades of IDP research
490(1)
1.2 IDPs in diseases, misfunctioning, and viral infections
490(2)
2 Bioinformatics over biophysical techniques to study IDP
492(1)
2.1 Usage of machine learning approaches in disorder predictors and structure modeling servers
492(1)
2.2 IDPs from the lens of molecular modeling and simulations
493(1)
3 Common predictors for identification of IDPs
493(5)
3.1 PONDR (predictor of naturally disordered regions)
493(2)
3.2 PONDRVLXT
495(1)
3.3 PONDRVSL2
495(1)
3.4 PONDRVL3
496(1)
3.5 PONDR FIT
496(1)
3.6 lUPred
496(1)
3.7 Foldlndex
496(1)
3.8 ToplDP
497(1)
3.9 MobiDB
497(1)
3.10 PrDOS
497(1)
3.11 MetaDisorder
497(1)
3.12 ClobPlot
497(1)
3.13 DisEMBL
498(1)
4 Identification of molecular recognition features (MoRFs)
498(2)
4.1 ANCHOR
499(1)
4.2 MoRFpred
499(1)
4.3 MoRFchibLweb
499(1)
4.4 DISOPRED
499(1)
5 Prediction of nucleic acid-binding regions
500(1)
5.1 DRNAPred
500(1)
5.2 DisoRDPbind
500(1)
5.3 PPRInt
500(1)
6 Biological relevance of predictions
501(1)
7 Conclusion and future perspectives
501(4)
Acknowledgments
501(1)
References
501(4)
31 Experimental methods to study intrinsically disordered proteins
Niharika Nag
Purna Bahadur Chetri
Vladimir N. Uversky
Rajanish Giri
Timir Tripathi
1 Introduction
505(1)
2 Size exclusion chromatography
505(1)
2.1 Case study
506(1)
3 UV-vis absorption spectroscopy
506(1)
3.1 Case study
507(1)
4 Circular dichroism spectroscopy
507(3)
4.1 Case study 1
508(1)
4.2 Case study 2
509(1)
4.3 Case study 3
509(1)
5 Fluorescence spectroscopy
510(5)
5.1 Intrinsic protein fluorescence
511(1)
5.2 Extrinsic fluorescence probes
511(1)
5.3 Fluorescence resonance energy transfer
512(1)
5.4 Fluorescence correlation spectroscopy
513(1)
5.5 Fluorescence anisotropy
513(2)
5.6 Fast relaxation imaging
515(1)
6 Nuclear magnetic resonance spectroscopy
515(1)
6.1 Case study
516(1)
7 Fourier transform infrared spectroscopy
516(1)
7.1 Case study 1
517(1)
7.2 Case study 2
517(1)
8 Electron spin resonance spectroscopy
517(2)
8.1 Case study
518(1)
9 Raman spectroscopy
519(2)
9.1 Case study
520(1)
10 Light scattering methods
521(3)
10.1 Static light scattering
521(1)
10.2 Dynamic light scattering
521(1)
10.3 Small-angle X-ray scattering
522(2)
11 Microscopy-based methods
524(1)
11.1 Atomic force microscopy
524(1)
12 Analytical ultracentrifugation
525(2)
12.1 Case study
527(1)
13 Mass spectrometry
527(3)
13.1 Case study 1
528(1)
13.2 Case study 2
529(1)
14 Conclusions and future perspectives
530(5)
References
530(5)
32 Analysis of structure and dynamics of intrinsically disordered regions in proteins using solution NMR methods
Nikita V. Saibo
Snigdha Maiti
Bidisha Acharya
Soumya De
1 Introduction
535(1)
2 NMR chemical shift assignments of intrinsically disordered sequences
535(5)
2.1 Standard backbone assignment strategy
536(1)
2.2 Backbone assignment using 13C detection
537(1)
2.3 Fast data acquisition to reduce experiment time
537(1)
2.4 Segmental isotope labeling of IDRPs
538(1)
2.5 Cell-free protein synthesis for IDRPs
539(1)
3 Structural characterization of IDRPs
540(2)
3.1 Chemical shift-based methods
540(1)
3.2 Residual dipolar coupling (RDC)
540(1)
3.3 Paramagnetic relaxation enhancement (PRE)
541(1)
3.4 Determination of ensemble structure of IDRPs
541(1)
4 Characterization of IDRP dynamics
542(3)
4.1 Measuring fast timescale (ps-ns) dynamics
542(1)
4.2 Identifying rigid segments in IDRPs
543(1)
4.3 Determination of global flexibility of disordered sequences
544(1)
4.4 Slow dynamics (us-ms) in IDRPs
544(1)
5 In-cell NMR experiments
545(1)
6 Conclusions and future perspectives
546(5)
References
546(5)
33 Methods to study the effect of solution variables on the conformational dynamics of intrinsically disordered proteins
Hakan Alici
Orkun Hasekioglu
Vladimir N. Uversky
Orkid Coskuner-Weber
1 Introduction
551(1)
2 Computational tools to study the impacts of solution variables on IDPs
552(13)
2.1 Density functional theory calculations
552(2)
2.2 Multiple MD simulations
554(4)
2.3 Deep neural networks: Generative neural networks
558(3)
References
561(4)
34 Molecular simulations to study IDP-IDP interactions and their complexes
Kota Kasahara
1 Intrinsically disordered proteins and their interactions
565(1)
2 Introduction of the molecular simulation techniques
566(1)
3 Characterizing IDP-IDP interactions and their complexes by coarse-grained models
567(3)
3.1 Coarse-grained models for the LLPS
567(1)
3.2 Analyzing phase diagrams of the LLPS
568(1)
3.3 Sequence determinants for the LLPS: Ionic interactions
568(2)
3.4 Applications for other types of condensates
570(1)
4 Challenges in coarse-grained models
570(3)
4.1 Hydrogen bonds and secondary structure formation
570(1)
4.2 Treatment with Jt group interactions
571(1)
4.3 Treatment with solvents
571(1)
4.4 Limitations with the size of the simulation system
571(1)
4.5 Improvements of coarse-grained models and potentials
572(1)
5 Conclusion and future perspectives
573(2)
References
573(2)
35 Exploring large-scale protein function using systematic mutant analysis
Amrita Arpita Padhy
Subhashree Sahoo
Kummari Shivani
Varsha Kumari
Pawl Misbra
1 Introduction
575(1)
2 Engineering systematic site saturation mutant libraries
576(1)
2.1 Random mutagenesis
576(1)
2.2 Site-directed mutagenesis
576(2)
3 Screening the systematic mutant libraries for variant function
578(501)
3.1 Display methods
578(1)
3.2 Fluorescence-based screening
579(1)
3.3 Coupling protein function to host cell fitness
579(1)
4 Next-generation sequencing of the variants
579(1)
5 Large-scale functional mapping in proteins
580(5)
5.1 Epitope mapping
581(2)
5.2 Mutant effects on structure and stability of proteins
583(1)
5.3 Protein-protein interactions
584(1)
5.4 In silico prediction of mutant effects
584(1)
6 Conclusion and future perspectives
585(4)
Acknowledgments
585(1)
References
585(4)
36 Approaches and methods to study cell signaling: Linguistics of cellular communication
Siddharth Neog
Vishal Trivedi
1 Introduction
589(1)
2 Molecular players in signal transduction
589(1)
2.1 Signals
589(1)
2.2 Receptors
590(1)
2.3 Intracellular messengers
590(1)
3 Cell signaling can occur in a variety of ways
590(2)
3.1 Signaling via soluble molecules
590(2)
3.2 Signaling via cell-cell direct contact or Juxtacrine signaling
592(1)
4 Cell signaling orchestrates key biological processes
592(8)
4.1 Cells can proliferate upon induction with long-range signaling by soluble molecules
592(1)
4.2 Insulin signaling controls various metabolic activities of the cell
593(2)
4.3 Cell signaling by morphogens and growth factors orchestrate embryonic development
595(1)
4.4 The RTK pathway regulates a wide array of developmental cellular processes
595(1)
4.5 Wnt signaling pathway regulates proliferation and differentiation of stem cells
596(1)
4.6 Sonic hedgehog signaling is vital for the normal development of different organs
597(1)
4.7 Notch signaling regulates binary cell fate decisions, proliferation, and differentiation
597(1)
4.8 Cell migration is induced by several growth factors that primarily act through mitogen-activated protein kinase (MAPK) cascades
598(1)
4.9 Death receptor signaling leads to apoptotic cell death
599(1)
5 Experimental techniques used to study cell signaling
600(18)
5.1 Biochemical approaches to study signal transduction
600(5)
5.2 Studying signaling events in live cells
605(5)
5.3 Experimental techniques for studying second messengers involved in cell signaling
610(2)
5.4 Techniques for detection and measurement of intracellular calcium
612(2)
5.5 Phosphoproteomics: Global approaches to studying cell signaling
614(4)
6 Conclusion and future perspectives
618(7)
References
618(7)
37 Methods to study systems biology of signaling networks: A case study of NSCLC
Nikhil H. Samarth
Shailza Singh
1 Introduction
625(1)
2 Non-small cell lung carcinoma (NSCLC)
625(1)
3 Systems biology
626(1)
4 Applications of systems biology approaches in cancer studies
627(1)
5 System biology methods and approaches
628(1)
5.1 Reconstruction of signaling network
628(1)
5.2 Parameter estimation
628(1)
5.3 Sensitivity analysis
628(1)
5.4 Flux analysis
628(1)
5.5 Principle component analysis
628(1)
5.6 Model reduction
629(1)
6 Analysis of the data
629(1)
6.1 Model reconstruction and simulation
629(1)
6.2 Principal component analysis (PCA)
629(1)
6.3 Flux analysis
629(1)
6.4 Model reduction
629(1)
7 Interpretations and conclusions
629(6)
Acknowledgments
633(1)
References
633(2)
38 Advancements in the analysis of protein post-translational modifications
Sandip Mukherjee
Ritesh Kumar
Arianne L. Theiss
K. Venuprasad
1 Introduction
635(1)
2 Ubiquitination
635(1)
3 Types of ubiquitination
636(1)
4 Detection of protein ubiquitination
636(1)
4.1 Immunoprecipitation and immunoblotting
636(1)
4.2 Identification of ubiquitinated proteins with a ubiquitin-specific affinity resin
636(1)
4.3 Efficient isolation of ubiquitylated proteins using tandem ubiquitin-binding entities (TUBEs)
637(1)
4.4 Modification of TUBEs
637(1)
4.5 Detection of polyubiquitination by the luminescent method
637(1)
5 Identification of the site of ubiquitination
637(1)
5.1 Site-directed mutagenesis
637(1)
5.2 Mass spectrometric analysis
638(1)
6 Ubiquitin chain architecture detection
638(1)
7 Conclusion and future perspectives
639(2)
References
639(2)
39 Protein engineering: Methods and applications
Saurabh Bansal
Bishwajit Kundu
1 Introduction
641(1)
2 Protein engineering approaches
641(1)
3 Directed evolution
641(12)
3.1 Nonrecombination methods (asexual methods)
642(3)
3.2 Recombination methods
645(8)
4 Semi-rational design
653(1)
4.1 Structure-based combinatorial protein engineering (SCOPE)
653(1)
5 De novo design
653(1)
6 Rational design
654(2)
6.1 Identification of sites (amino acid residues) for modification
655(1)
6.2 Multiple sequence alignment (MSA)
655(1)
6.3 Co-evolutionary analysis
655(1)
6.4 Structure analysis
655(1)
6.5 Site-directed mutagenesis (SDM)
655(1)
7 Applications of protein engineering
656(5)
7.1 Protein engineering for industrial enzymes
656(4)
7.2 Protein engineering in healthcare
660(1)
7.3 Protein engineering in metabolic pathway engineering (MPE)
661(1)
8 Conclusions
661(8)
References
662(7)
40 Designer 3D-DNA nanodevices: Structures, functions, and cellular applications
Anjali Rajwar
Payal Vaswani
A. Hema Naveena
Dhiraj Bhatia
1 Introduction
669(1)
2 Different approaches to realize 3D DNA polyhedral nanodevices
670(1)
2.1 One-pot synthesis method
670(1)
2.2 Modular assembly method
671(1)
2.3 Origami-based assembly
671(1)
3 Methods for characterization of DNA nanostructures
671(2)
3.1 Electrophoretic mobility shift assay
671(1)
3.2 Dynamic light scattering
672(1)
3.3 High-performance liquid chromatography
673(1)
3.4 Atomic force microscopy
673(1)
3.5 Transmission electron microscopy
673(1)
4 Cellular uptake of TDN and its characterization
673(1)
5 Conclusions and future perspectives
674(3)
Acknowledgments
675(1)
Declaration
675(1)
References
675(2)
Index 677
Professor Timir Tripathi is a Professor of Molecular Biology, School of Life Sciences, North-Eastern Hill University, Shillong, India. Earlier, he served as the Regional Director of Indira Gandhi National Open University. His previous role was Senior Assistant Professor and Principal Investigator at the Department of Biochemistry, NEHU, Shillong. He holds a Ph.D. from Jawaharlal Nehru University, New Delhi. His primary research focus is studying the conformational dynamics, interaction, and stabilization of the complexes formed by intrinsically disordered neuropathological protein aggregates, their properties of liquid-liquid phase separation, interaction, and roles in nucleocytoplasmic transport in neurodegenerative diseases. Professor Tripathi is an Associate Fellow of the Indian National Science Academy, New Delhi, and an elected member of the National Academy of Sciences, India, the Royal Society of Chemistry, and the Royal Society of Biology, UK

Vikash Kumar Dubey is a Professor at the School of Biochemical Engineering and Associate Dean for Academic Affairs at the Indian Institute of Technology (BHU), Varanasi, India. Prior to joining IIT (BHU), he was a postdoctoral fellow at Florida State University, USA before joining IIT Guwahati, India, where he served as Associate Professor and Professor. He has published over 130 articles in peer-reviewed journals and over 80 conference presentations/proceedings. He has seven awarded and licensed USA patents and many Indian patents. He has also written several book chapters and has guided a number of PhD students, MTech students, and postdoctoral fellows. He has received several awards and has been elected as a member of a number of scientific societies and academies; Among these, he is currently the Vice President of the Bioinformatics and Drug Discovery Society [ BIDDS], India and a Fellow of the Royal Society of Biology, UK.
Daugiau apie elektronines knygas Daugiau apie elektronines knygas
Pastovi nuoroda: https://www.kriso.lt/db/97803239026566e.html
Raktažodžiai: