Recent Theoretical Studies Concerning Important Tropical Infections

Computational Prediction of Binding Affinity for CDK2-ligand Complexes. A Protein Target for Cancer Drug Discovery

BACKGROUND

CDK2 participates in the control of eukaryotic cell-cycle progression. Due to the great interest in CDK2 for drug development and the relative easiness in crystallizing this enzyme, we have over 400 structural studies focused on this protein target. This structural data is the basis for the development of computational models to estimate CDK2-ligand binding affinity.

OBJECTIVE

This work focuses on the recent developments in the application of supervised machine learning modeling to develop scoring functions to predict the binding affinity of CDK2.

METHOD

We employed the structures available at the protein data bank and the ligand information accessed from the BindingDB, Binding MOAD, and PDBbind to evaluate the predictive performance of machine learning techniques combined with physical modeling used to calculate binding affinity. We compared this hybrid methodology with classical scoring functions available in docking programs.

RESULTS

Our comparative analysis of previously published models indicated that a model created using a combination of a mass-spring system and cross-validated Elastic Net to predict the binding affinity of CDK2-inhibitor complexes outperformed classical scoring functions available in AutoDock4 and AutoDock Vina.

CONCLUSION

All studies reviewed here suggest that targeted machine learning models are superior to classical scoring functions to calculate binding affinities. Specifically for CDK2, we see that the combination of physical modeling with supervised machine learning techniques exhibits improved predictive performance to calculate the protein-ligand binding affinity. These results find theoretical support in the application of the concept of scoring function space.

Post kala-azar dermal leishmaniasis: A threat to elimination program

Leishmaniasis remains a public health concern around the world that primarily affects poor folks of the developing world spanning across 98 countries with mortality of 0.2 million to 0.4 million annually. Post kala-azar dermal leishmaniasis (PKDL) is the late skin manifestation of visceral leishmaniasis (VL). It has been reported that about 2.5% to 20% of patients recovered from VL develop PKDL having stilted macular or nodular lesions with parasites. In the Indian subcontinent (ISC), it manifests a few months after recovery from VL, though in Africa it can occur simultaneously with VL or a little later. New cases of PKDL are also observed without prior VL in the ISC. These individuals with PKDL represent an important but largely neglected reservoir of infection that perpetuates anthroponotic Leishmania donovani transmission in the ISC and can jeopardize the VL elimination program as these cases can infect the sand flies and spread the endemic. Therefore, it becomes imperative to eradicate PKDL as a part of the VL elimination program. With the limited treatment options besides little knowledge on PKDL, this review stands out in focusing on different aspects that should be dealt for sustained VL elimination.