Biomedical subjects

Sumeet Salaniwal

Publications and source records attributed to Sumeet Salaniwal.

3 recordsLinked to original sources

PubMed2026

Enozertinib Is a Selective, Brain-Penetrant EGFR Inhibitor for Treating Non-Small Cell Lung Cancers with EGFR Exon 20 and Atypical Mutations.

UNLABELLED: EGFR mutations are common oncogenic drivers in non-small cell lung cancer (NSCLC), and approximately half of patients develop brain metastases over the course of their disease. Patients with nonclassic EGFR mutations, such as insertions in exon 20, are a high unmet need with a worse prognosis compared with patients with classic EGFR mutations. Here, we describe the discovery and development of enozertinib (formerly ORIC-114), a highly brain-penetrant, orally bioavailable, irreversible inhibitor that targets EGFR exon 20 mutations with unparalleled kinome selectivity. Preclinical studies revealed strong potency and tumor regressions driven by enozertinib across a broad range of atypical EGFR-mutant models. In a phase I clinical trial of enozertinib in patients with advanced NSCLC bearing atypical mutations in EGFR, a patient harboring an EGFR exon 20 insertion experienced sustained complete response of all systemic and brain metastases. Together, these findings identify enozertinib as a promising investigational inhibitor to address the unmet need for brain-penetrant therapies in NSCLC with EGFR exon 20 insertions or other atypical mutations. SIGNIFICANCE: Preclinical and initial phase I clinical data demonstrate the potency, kinome selectivity, efficacy, and brain penetration of enozertinib in NSCLC with EGFR exon 20 insertions and atypical mutations, warranting further clinical development.

Carcinoma, Non-Small-Cell Lung↗

PubMed2007

Critical evaluation of methods to incorporate entropy loss upon binding in high-throughput docking.

Proper accounting of the positional/orientational/conformational entropy loss associated with protein-ligand binding is important to obtain reliable predictions of binding affinity. Herein, we critically examine two simplified statistical mechanics-based approaches, namely a constant penalty per rotor method, and a more rigorous method, referred to here as the partition function-based scoring (PFS) method, to account for such entropy losses in high-throughput docking calculations. Our results on the estrogen receptor beta and dihydrofolate reductase proteins demonstrate that, while the constant penalty method over-penalizes molecules for their conformational flexibility, the PFS method behaves in a more "DeltaG-like" manner by penalizing different rotors differently depending on their residual entropy in the bound state. Furthermore, in contrast to no entropic penalty or the constant penalty approximation, the PFS method does not exhibit any bias towards either rigid or flexible molecules in the hit list. Preliminary enrichment studies using a lead-like random molecular database suggest that an accurate representation of the "true" energy landscape of the protein-ligand complex is critical for reliable predictions of relative binding affinities by the PFS method.

Algorithms↗

PubMed2002

Amorphous solidification in polymer-platelet nanocomposites.

Computer simulations are used to understand the molecular basis of the rheology changes in polymer melts when loaded with platelet filler particles, specifically when the polymer and nanofiller interact attractively. With decreasing temperature, there is increasing aggregation between chains and filler and an increase in the polymer matrix structural relaxation time. These lifetimes are predicted to diverge at an extrapolated temperature, which we identify with the emergence of an amorphous solid state. Our findings suggest that filled polymers are phenomenologically similar to solutions of associating polymers and to supercooled liquids near their glass transition.

Journal Article↗