In silico approaches for predicting the half-life of natural and modified peptides in blood

Mathur, Deepika; Singh, Sandeep; Mehta, Ayesha; Agrawal, Piyush; Raghava, Gajendra P. S.

doi:10.1371/journal.pone.0196829

Cited by 85 publications

(64 citation statements)

References 33 publications

(35 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The findings indicate leveraging physiochemical charge and hydrophobicity assays as preclinical in vitro tools to filter molecules prior to any in vivo PK assessments are methods to speed the selection and improve the probability of technical success for mAbs. The increased attention and research activity toward the development of in silico and other model-based drug design and selection tools to predict these phenomena for improving druggability within the last few years also reinforces the importance of these factors in affecting nonspecific clearance mechanisms (Mathur et al, 2018;Wolf Pérez et al, 2019;Xu et al, 2019).…”

Section: Molecule-centric Phsiochemical Factors Influencing Dispositimentioning

confidence: 96%

“…This is likely due to early elimination during the drug discovery and development process due to poor expression, purification, and/or solution solubility given the propensity of these molecules to aggregate. For peptides, a number of recent studies have predicted the elimination half-life as it relates to charge and hydrophobic content-based physicochemical properties related to their residue composition, potential for metabolism (discussed subsequently), chemical modification, and transformations (Sharma et al, 2014;Broom et al, 2017;Mathur et al, 2018). Due to their more complicated large tertiary structures and dynamics, the role of hydrophobicity and charge in mAb clearance has been determined through more empirical-based experimentation.…”

Section: Molecule-centric Phsiochemical Factors Influencing Dispositimentioning

confidence: 99%

See 1 more Smart Citation

Mechanisms Influencing the Pharmacokinetics and Disposition of Monoclonal Antibodies and Peptides

Datta‐Mannan

2019

Drug Metab Dispos

View full text Add to dashboard Cite

Monoclonal antibodies (mAbs) and peptides are an important class of therapeutic modalities that have brought improved health outcomes in areas with limited therapeutic optionality. Presently, there more than 90 mAb and peptide therapeutics on the United States market, with over 600 more in various clinical stages of development in a broad array of therapeutic areas, including diabetes, autoimmune disorders, oncology, neuroscience, and cardiovascular and infectious diseases. Notwithstanding this potential, there is high clinical rate of attrition, with approximately 10% reaching patients. A major contributor to the failure of the molecules is often times an incomplete or poor understanding of the pharmacokinetics (PK) and disposition profiles leading to limited or diminished efficacy. Increased and thorough characterization efforts directed at disseminating mechanisms influencing the PK and disposition of mAbs and peptides can aid in improving the design for their intended pharmacological activity, and thereby their clinical success. The PK and disposition factors for mAbs and peptides are broadly influenced by target-mediated drug disposition and nontarget-related clearance mechanisms related to the interplay between the relationship of the structure and physiochemical properties of mAbs and peptides with physiologic processes. This review focuses on nontarget-related factors influencing the disposition and PK of mAbs and peptides. Contemporary considerations around the increasing in silico approaches to identify nontarget-related molecule limitations and enhancing the druggability of mAbs and peptides, including parenteral and nonparenteral delivery strategies that are geared toward improving patient experience and compliance, are also discussed.

show abstract

Section: Molecule-centric Phsiochemical Factors Influencing Dispositimentioning

confidence: 96%

Section: Molecule-centric Phsiochemical Factors Influencing Dispositimentioning

confidence: 99%

Mechanisms Influencing the Pharmacokinetics and Disposition of Monoclonal Antibodies and Peptides

Datta‐Mannan

2019

Drug Metab Dispos

View full text Add to dashboard Cite

show abstract

“…We group protein-peptide complexes based on rotatable bonds in the peptide to understand the effect of rotatable bonds on quality of docking pose generated by different methods (Tables 6,7,8). Considering average L-RMSD, we found the different behaviour of software in docking results with respect to the number of rotatable bonds.…”

Section: Rotatable Bondsmentioning

confidence: 99%

“…Peptides can be used to prevent diseases involving malfunctioning of proteins due to undesirable protein-protein interactions [3,4]. Many databases and algorithms have been developed in the past specifically in the field of peptide-based therapeutics [5][6][7][8][9][10][11][12][13][14][15]. There are more than 200 therapeutics peptides, approved by FDA for the treatment of various diseases [16,17].…”

Section: Introductionmentioning

confidence: 99%

Benchmarking of different molecular docking methods for protein-peptide docking

et al. 2019

Self Cite

View full text Add to dashboard Cite

Background: Molecular docking studies on protein-peptide interactions are a challenging and time-consuming task because peptides are generally more flexible than proteins and tend to adopt numerous conformations. There are several benchmarking studies on protein-protein, protein-ligand and nucleic acid-ligand docking interactions. However, a series of docking methods is not rigorously validated for protein-peptide complexes in the literature. Considering the importance and wide application of peptide docking, we describe benchmarking of 6 docking methods on 133 protein-peptide complexes having peptide length between 9 to 15 residues. The performance of docking methods was evaluated using CAPRI parameters like FNAT, I-RMSD, L-RMSD. Result: Firstly, we performed blind docking and evaluate the performance of the top docking pose of each method. It was observed that FRODOCK performed better than other methods with average L-RMSD of 12.46 Å. The performance of all methods improved significantly for their best docking pose and achieved highest average L-RMSD of 3.72 Å in case of FRODOCK. Similarly, we performed re-docking and evaluated the performance of the top and best docking pose of each method. We achieved the best performance in case of ZDOCK with average L-RMSD 8.60 Å and 2.88 Å for the top and best docking pose respectively. Methods were also evaluated on 40 protein-peptide complexes used in the previous benchmarking study, where peptide have length up to 5 residues. In case of best docking pose, we achieved the highest average L-RMSD of 4.45 Å and 2.09 Å for the blind docking using FRODOCK and re-docking using AutoDock Vina respectively. Conclusion: The study shows that FRODOCK performed best in case of blind docking and ZDOCK in case of redocking. There is a need to improve the ranking of docking pose generated by different methods, as the present ranking scheme is not satisfactory. To facilitate the scientific community for calculating CAPRI parameters between native and docked complexes, we developed a web-based service named PPDbench (http://webs.iiitd.edu.in/ raghava/ppdbench/).

show abstract

“…Despite tremendous potential of peptides, there are many challenges in designing therapeutic peptides that include short half-life, challenges in oral delivery, immunotoxicity, cytotoxicity, etc. To address these issues, a number of computational resources has been developed in last two decades ( Gupta et al, 2013 ; Sharma et al, 2014 ; Mathur et al, 2016 , 2018 ; Liu et al, 2017 ; Porto et al, 2017b ).…”

Section: Introductionmentioning

confidence: 99%

Prediction of Antimicrobial Potential of a Chemically Modified Peptide From Its Tertiary Structure

Agrawal

Raghava

2018

Front. Microbiol.

Self Cite

View full text Add to dashboard Cite

Designing novel antimicrobial peptides is a hot area of research in the field of therapeutics especially after the emergence of resistant strains against the conventional antibiotics. In the past number of in silico methods have been developed for predicting the antimicrobial property of the peptide containing natural residues. This study describes models developed for predicting the antimicrobial property of a chemically modified peptide. Our models have been trained, tested and evaluated on a dataset that contains 948 antimicrobial and 931 non-antimicrobial peptides, containing chemically modified and natural residues. Firstly, the tertiary structure of all peptides has been predicted using software PEPstrMOD. Structure analysis indicates that certain type of modifications enhance the antimicrobial property of peptides. Secondly, a wide range of features was computed from the structure of these peptides using software PaDEL. Finally, models were developed for predicting the antimicrobial potential of chemically modified peptides using a wide range of structural features of these peptides. Our best model based on support vector machine achieve maximum MCC of 0.84 with an accuracy of 91.62% on training dataset and MCC of 0.80 with an accuracy of 89.89% on validation dataset. To assist the scientific community, we have developed a web server called “AntiMPmod” which predicts the antimicrobial property of the chemically modified peptide. The web server is present at the following link (http://webs.iiitd.edu.in/raghava/antimpmod/).

show abstract

In silico approaches for predicting the half-life of natural and modified peptides in blood

Cited by 85 publications

References 33 publications

Mechanisms Influencing the Pharmacokinetics and Disposition of Monoclonal Antibodies and Peptides

Mechanisms Influencing the Pharmacokinetics and Disposition of Monoclonal Antibodies and Peptides

Benchmarking of different molecular docking methods for protein-peptide docking

Prediction of Antimicrobial Potential of a Chemically Modified Peptide From Its Tertiary Structure

Contact Info

Product

Resources

About