scholarly journals Recent advances in the development of protein–protein interactions modulators: mechanisms and clinical trials

Author(s):  
Haiying Lu ◽  
Qiaodan Zhou ◽  
Jun He ◽  
Zhongliang Jiang ◽  
Cheng Peng ◽  
...  

Abstract Protein–protein interactions (PPIs) have pivotal roles in life processes. The studies showed that aberrant PPIs are associated with various diseases, including cancer, infectious diseases, and neurodegenerative diseases. Therefore, targeting PPIs is a direction in treating diseases and an essential strategy for the development of new drugs. In the past few decades, the modulation of PPIs has been recognized as one of the most challenging drug discovery tasks. In recent years, some PPIs modulators have entered clinical studies, some of which been approved for marketing, indicating that the modulators targeting PPIs have broad prospects. Here, we summarize the recent advances in PPIs modulators, including small molecules, peptides, and antibodies, hoping to provide some guidance to the design of novel drugs targeting PPIs in the future.

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Anna Lucia Fallacara ◽  
Iuni Margaret Laura Tris ◽  
Amalia Belfiore ◽  
Maurizio Botta

The Drug development process has undergone a great change over the years. The way, from haphazard discovery of new natural products with a potent biological activity to a rational design of small molecule effective against a selected target, has been long and sprinkled with difficulties. The oldest drug development models are widely perceived as opaque and inefficient, with the cost of research and development continuing to rise even if the production of new drugs remains constant. The present paper, will give an overview of the principles, approaches, processes, and status of drug discovery today with an eye towards the past and the future.


2017 ◽  
Vol 474 (7) ◽  
pp. 1109-1125 ◽  
Author(s):  
Patrick G. Dougherty ◽  
Ziqing Qian ◽  
Dehua Pei

Macrocyclic compounds such as cyclic peptides have emerged as a new and exciting class of drug candidates for inhibition of intracellular protein–protein interactions, which are challenging targets for conventional drug modalities (i.e. small molecules and proteins). Over the past decade, several complementary technologies have been developed to synthesize macrocycle libraries and screen them for binding to therapeutically relevant targets. Two different approaches have also been explored to increase the membrane permeability of cyclic peptides. In this review, we discuss these methods and their applications in the discovery of macrocyclic compounds against protein–protein interactions.


2017 ◽  
Vol 61 (5) ◽  
pp. 453-464 ◽  
Author(s):  
Bas Lamoree ◽  
Roderick E. Hubbard

It is over 20 years since the first fragment-based discovery projects were disclosed. The methods are now mature for most ‘conventional’ targets in drug discovery such as enzymes (kinases and proteases) but there has also been growing success on more challenging targets, such as disruption of protein–protein interactions. The main application is to identify tractable chemical startpoints that non-covalently modulate the activity of a biological molecule. In this essay, we overview current practice in the methods and discuss how they have had an impact in lead discovery – generating a large number of fragment-derived compounds that are in clinical trials and two medicines treating patients. In addition, we discuss some of the more recent applications of the methods in chemical biology – providing chemical tools to investigate biological molecules, mechanisms and systems.


Author(s):  
D Samba Reddy

This article provides a brief overview of novel drugs approved by the U.S. FDA in 2016.  It also focuses on the emerging boom in the development of neurodrugs for central nervous system (CNS) disorders. These new drugs are innovative products that often help advance clinical care worldwide, and in 2016, twenty-two such drugs were approved by the FDA. The list includes the first new drug for disorders such as spinal muscular atrophy, Duchenne muscular dystrophy or hallucinations and delusions of Parkinson’s disease, among several others. Notably, nine of twenty-two (40%) were novel CNS drugs, indicating the industry shifting to neurodrugs. Neurodrugs are the top selling pharmaceuticals worldwide, especially in America and Europe. Therapeutic neurodrugs have proven their significance many times in the past few decades, and the CNS drug portfolio represents some of the most valuable agents in the current pipeline. Many neuroproducts are vital or essential medicines in the current therapeutic armamentarium, including dozens of “blockbuster drugs” (drugs with $1 billion sales potential).  These drugs include antidepressants, antimigraine medications, and anti-epilepsy medications. The rise in neurodrugs’ sales is predominantly due to increased diagnoses of CNS conditions. The boom for neuromedicines is evident from the recent rise in investment, production, and introduction of new CNS drugs.  There are many promising neurodrugs still in the pipeline, which are developed based on the validated “mechanism-based” strategy. Overall, disease-modifying neurodrugs that can prevent or cure serious diseases, such as multiple sclerosis, epilepsy, and Alzheimer’s disease, are in high demand. 


2019 ◽  
Vol 26 (21) ◽  
pp. 3890-3910 ◽  
Author(s):  
Branislava Gemovic ◽  
Neven Sumonja ◽  
Radoslav Davidovic ◽  
Vladimir Perovic ◽  
Nevena Veljkovic

Background: The significant number of protein-protein interactions (PPIs) discovered by harnessing concomitant advances in the fields of sequencing, crystallography, spectrometry and two-hybrid screening suggests astonishing prospects for remodelling drug discovery. The PPI space which includes up to 650 000 entities is a remarkable reservoir of potential therapeutic targets for every human disease. In order to allow modern drug discovery programs to leverage this, we should be able to discern complete PPI maps associated with a specific disorder and corresponding normal physiology. Objective: Here, we will review community available computational programs for predicting PPIs and web-based resources for storing experimentally annotated interactions. Methods: We compared the capacities of prediction tools: iLoops, Struck2Net, HOMCOS, COTH, PrePPI, InterPreTS and PRISM to predict recently discovered protein interactions. Results: We described sequence-based and structure-based PPI prediction tools and addressed their peculiarities. Additionally, since the usefulness of prediction algorithms critically depends on the quality and quantity of the experimental data they are built on; we extensively discussed community resources for protein interactions. We focused on the active and recently updated primary and secondary PPI databases, repositories specialized to the subject or species, as well as databases that include both experimental and predicted PPIs. Conclusion: PPI complexes are the basis of important physiological processes and therefore, possible targets for cell-penetrating ligands. Reliable computational PPI predictions can speed up new target discoveries through prioritization of therapeutically relevant protein–protein complexes for experimental studies.


2019 ◽  
Vol 26 (28) ◽  
pp. 5340-5362 ◽  
Author(s):  
Xin Chen ◽  
Giuseppe Gumina ◽  
Kristopher G. Virga

:As a long-term degenerative disorder of the central nervous system that mostly affects older people, Parkinson’s disease is a growing health threat to our ever-aging population. Despite remarkable advances in our understanding of this disease, all therapeutics currently available only act to improve symptoms but cannot stop the disease progression. Therefore, it is essential that more effective drug discovery methods and approaches are developed, validated, and used for the discovery of disease-modifying treatments for Parkinson’s disease. Drug repurposing, also known as drug repositioning, or the process of finding new uses for existing or abandoned pharmaceuticals, has been recognized as a cost-effective and timeefficient way to develop new drugs, being equally promising as de novo drug discovery in the field of neurodegeneration and, more specifically for Parkinson’s disease. The availability of several established libraries of clinical drugs and fast evolvement in disease biology, genomics and bioinformatics has stimulated the momentums of both in silico and activity-based drug repurposing. With the successful clinical introduction of several repurposed drugs for Parkinson’s disease, drug repurposing has now become a robust alternative approach to the discovery and development of novel drugs for this disease. In this review, recent advances in drug repurposing for Parkinson’s disease will be discussed.


2020 ◽  
Vol 27 (37) ◽  
pp. 6306-6355 ◽  
Author(s):  
Marian Vincenzi ◽  
Flavia Anna Mercurio ◽  
Marilisa Leone

Background:: Many pathways regarding healthy cells and/or linked to diseases onset and progression depend on large assemblies including multi-protein complexes. Protein-protein interactions may occur through a vast array of modules known as protein interaction domains (PIDs). Objective:: This review concerns with PIDs recognizing post-translationally modified peptide sequences and intends to provide the scientific community with state of art knowledge on their 3D structures, binding topologies and potential applications in the drug discovery field. Method:: Several databases, such as the Pfam (Protein family), the SMART (Simple Modular Architecture Research Tool) and the PDB (Protein Data Bank), were searched to look for different domain families and gain structural information on protein complexes in which particular PIDs are involved. Recent literature on PIDs and related drug discovery campaigns was retrieved through Pubmed and analyzed. Results and Conclusion:: PIDs are rather versatile as concerning their binding preferences. Many of them recognize specifically only determined amino acid stretches with post-translational modifications, a few others are able to interact with several post-translationally modified sequences or with unmodified ones. Many PIDs can be linked to different diseases including cancer. The tremendous amount of available structural data led to the structure-based design of several molecules targeting protein-protein interactions mediated by PIDs, including peptides, peptidomimetics and small compounds. More studies are needed to fully role out, among different families, PIDs that can be considered reliable therapeutic targets, however, attacking PIDs rather than catalytic domains of a particular protein may represent a route to obtain selective inhibitors.


2020 ◽  
Vol 20 (10) ◽  
pp. 855-882
Author(s):  
Olivia Slater ◽  
Bethany Miller ◽  
Maria Kontoyianni

Drug discovery has focused on the paradigm “one drug, one target” for a long time. However, small molecules can act at multiple macromolecular targets, which serves as the basis for drug repurposing. In an effort to expand the target space, and given advances in X-ray crystallography, protein-protein interactions have become an emerging focus area of drug discovery enterprises. Proteins interact with other biomolecules and it is this intricate network of interactions that determines the behavior of the system and its biological processes. In this review, we briefly discuss networks in disease, followed by computational methods for protein-protein complex prediction. Computational methodologies and techniques employed towards objectives such as protein-protein docking, protein-protein interactions, and interface predictions are described extensively. Docking aims at producing a complex between proteins, while interface predictions identify a subset of residues on one protein that could interact with a partner, and protein-protein interaction sites address whether two proteins interact. In addition, approaches to predict hot spots and binding sites are presented along with a representative example of our internal project on the chemokine CXC receptor 3 B-isoform and predictive modeling with IP10 and PF4.


MedChemComm ◽  
2017 ◽  
Vol 8 (12) ◽  
pp. 2216-2227 ◽  
Author(s):  
Wiktoria Jedwabny ◽  
Szymon Kłossowski ◽  
Trupta Purohit ◽  
Tomasz Cierpicki ◽  
Jolanta Grembecka ◽  
...  

A computationally affordable, non-empirical model based on electrostatic multipole and dispersion terms successfully predicts the binding affinity of inhibitors of menin–MLL protein–protein interactions.


Sign in / Sign up

Export Citation Format

Share Document