Tuesday, February 6, 2024

Landscape of In Silico Tools for Modeling Covalent Modification of Proteins: A Review on Computational Covalent Drug Discovery

Md Nazmul Hasan, Manisha Ray, and Arjun Saha
The Journal of Physical Chemistry B 2023 127 (45), 9663-9684

DOI: 10.1021/acs.jpcb.3c04710

Covalent drug discovery has been a challenging research area given the struggle of finding a sweet balance between selectivity and reactivity for these drugs, the lack of which often leads to off-target activities and hence undesirable side effects. However, there has been a resurgence in covalent drug design following the success of several covalent drugs such as boceprevir (2011), ibrutinib (2013), neratinib (2017), dacomitinib (2018), zanubrutinib (2019), and many others. Design of covalent drugs includes many crucial factors, where “evaluation of the binding affinity” and “a detailed mechanistic understanding on covalent inhibition” are at the top of the list. Well-defined experimental techniques are available to elucidate these factors; however, often they are expensive and/or time-consuming and hence not suitable for high throughput screens. Recent developments in in silico methods provide promise in this direction. In this report, we review a set of recent publications that focused on developing and/or implementing novel in silico techniques in “Computational Covalent Drug Discovery (CCDD)”. We also discuss the advantages and disadvantages of these approaches along with what improvements are required to make it a great tool in medicinal chemistry in the near future.


Mutant-selective AKT inhibition through lysine targeting and neo-zinc chelation

Gregory B. Craven, Hang Chu, Jessica D. Sun, Jordan D. Carelli, Brittany Coyne, Hao Chen, Ying Chen, Xiaolei Ma, Subhamoy Das, Wayne Kong, A...